Why is there so much emphasis on quantum technology in the defense sector
Quantum technology is an emerging and potentially disruptive discipline that can impact many human activities. And because quantum technology is a dual-use technology, it is of interest to the defense and security industries as well as to the military and government.
A recent report published in EPJ Quantum Technology, "Military Applications of Quantum Technology," reviews and describes possible military applications of quantum technology as an entry point for international peace and security assessments, ethical research, military and government policy, strategy and decision making. This report provides a basic overview of quantum technologies under development and also estimates the expected timing of delivery or impact of use, describes specific military applications of quantum technologies in various warfare domains (e.g., land, air, space, electronic, cyber, and underwater warfare, and ISTAR - Intelligence, Surveillance, Target Search, and Reconnaissance) , and describes related issues and challenges.
Although the fourth generation of modern warfare is characterized by decentralization and loss of state monopoly over warfare [1, 2], militaries of developed countries usually have access to the most advanced military technologies. This includes the emergence of quantum technologies.
Quantum technology (QT) refers to technologies that originated mainly from the second quantum revolution. Previously, the first quantum revolution brought about the technologies we are familiar with today, such as nuclear power, semiconductors, lasers, magnetic resonance imaging, modern communication technologies or digital cameras and other imaging devices. The first quantum technologies produced nuclear weapons and energy; then, classical computers were given an important role to play. Currently, laser weapons are being implemented and tested [3].
The second quantum revolution [4] is characterized by the manipulation and control of individual quantum systems (e.g., atoms, ions, electrons, photons, molecules, or various quasiparticles) so as to reach the standard quantum limit; that is, the limit of measurement accuracy at the quantum scale. For the purpose of this report, quantum technology refers to the technology of the second quantum revolution. Quantum technologies will not lead to entirely new weapons or stand-alone military systems, but will significantly enhance the measurement capabilities, sensing, accuracy, computational power, and efficiency of current and future military technologies. Most quantum technologies typically have dual uses. As a result, quantum technologies have tremendous potential for military applications. Various studies and proposals continue to emerge, signaling the increasing possibility of such technology realization; see, for example, [5-8].
This report provides a deeper context for understanding "quantum warfare," discusses its potential to impact the intelligence, security, and defense sectors, and describes new possible capabilities or improvements. The goal of this paper is not to provide precise predictions of quantum-based technologies, but rather to demonstrate possible directions and trends in implementation and application. Quantum technologies are often considered to be emerging technologies that have the potential to change the conduct and outcome of warfare [8]. Although most of the current quantum technologies have low Technology Readiness Levels (TRLs), they are considered to have disruptive potential [9], and elaborating on possible military applications of quantum technologies is also important to further assess threats to global peace and to discuss ethical policies or quantum-based preventive arms control.
This report consists of eight parts. Part 2 defines "quantum technology" and "quantum warfare," and introduces quantum technology classification and quantum technologies. Part 3 provides an overview of basic quantum technologies as the basis for specific applications, including the expected timing of deployment and the impact of exploitation. Part 4 presents general considerations and expectations regarding the development and deployment of quantum technologies in the military. Part 5 describes the application of individual quantum technologies in military domains, such as cyber, underwater, space, and electronic warfare. Part 6 identifies and discusses quantum hype as well as realistic possibilities. Part 7 develops a preliminary discussion of the military, peace and ethics, and technological consequences and challenges. Part 8 elaborates on the conclusions obtained in this paper.
Parts 4 and 5 address national security and defense issues. Part 3 is based on state-of-the-art research with relevant references, while Part 5 is based more on various military or government reports, policy briefs, and international security analyses, e.g., [5-8,10-13]. Here, readers should be wary of the hype surrounding quantum technologies and avoid exaggerated expectations. For the numerous current military applications of quantum technology, it is uncertain whether all the challenges associated with the need for high-end military technology will be addressed or even whether the technology will actually be deployed.
Quantum technology is defined as follows:
Quantum technology (QT) is an emerging field of physics and engineering based on quantum mechanical properties, especially quantum entanglement, quantum superposition and quantum tunneling effects, applied to individual quantum systems, as well as their practical applications.
By definition, quantum technologies describe various physical principles of quantum mechanical systems and have many applications; for example, captive ion technologies can be used as quantum bits for quantum computers and quantum sensors for magnetic fields or quantum clocks.
Dual-use technologies are areas of research and development that have potential for applications in both defense and commercial production [15]. Quantum technology is a typical dual-use technology that has implications not only for the military, but also for governments [16] and peacekeeping organizations.
Quantum warfare (QW) is a type of warfare that uses quantum technology for military applications, which affects intelligence, security, and defense capabilities in all areas of warfare and brings new military strategies, doctrines, scenarios, peace, and ethical issues.
There are also attempts to define the quantum domain [17] as a new domain of warfare. However, in this paper, the authors will consider quantum technology as a factor that improves all currently defined domains, rather than as a separate domain of warfare.
A quantum attack is the use of quantum technology to disrupt, disrupt, or eavesdrop on a classical or quantum security system. Typical examples are the use of quantum key distribution or quantum computers to break RSA encryption schemes for eavesdropping.
Although there is a large quantum technology literature, there is no clear agreement on the classification of quantum technologies. The authors will use the following taxonomy.
Quantum computing and simulation
-Quantum computers (digital and analog quantum computers and their applications, such as quantum system simulation, quantum optimization, etc.)
-Quantum simulators (non-programmable quantum circuits)
Quantum communication and cryptography
-Quantum networks and communications (quantum network components, quantum key distribution, quantum communications)
-Post-quantum cryptography (quantum elasticity algorithms, quantum random number generators)
Photon Box Note: Quantum random numbers are not part of post-quantum ciphers
Quantum sensing and metrology
-Quantum sensing (quantum magnetometer, gravimeter, etc.)
-Quantum timing (precise time measurement and distribution)
-Quantum imaging (quantum radar, low signal-to-noise imaging, etc.)
In addition to the general classification of quantum technologies presented above, the authors have made a new division of quantum technologies based on their advantages and applications. The following classification can be summarized and quantum technologies are classified using impact as follows:
Must have: framework of quantum technology platforms to be implemented to prevent future quantum attacks (e.g., post-quantum cryptography).
Effectiveness: quantum technologies improve the efficiency of current technologies and methods (e.g. quantum optimization, quantum machine learning or artificial intelligence).
Precision: quantum technologies improve the precision of current measurement techniques (e.g., quantum magnetometers, quantum gravimetry, quantum inertial navigation, timekeeping).
New capabilities: quantum technologies provide new capabilities beyond the scope of existing technologies (e.g., quantum radar, quantum chemical simulation, quantum cryptanalysis, quantum key distribution).
Note that this classification is not mutually exclusive.
This section describes the basics of quantum technologies, as well as relevant references. For each quantum technology, the current state of development is shown, factors affecting the application are identified, the expected time of deployment is estimated, and the main challenges are outlined. For quantum computing applications, the approximate number of required logical quantum bits is provided.
Different quantum technologies and their applications are at different TRLs, e.g. maturity levels ranging from TRL1 (e.g. certain types of quantum bits) to TRL8 (e.g. quantum key distribution), and no completeness is sought here, nor is any theoretical background provided, but rather the basics, effects and current state of development are presented.
3.1 Quantum Information Science
Quantum information science is the information science related to quantum physics and studies quantum information. In classical information science, the basic carrier of information is a bit that can only be 0 or 1. The basic carrier of quantum information is a quantum bit. A quantum bit can be |0⟩ or |1⟩, or any complex linear combination of states |0⟩ and |1⟩, called a quantum superposition state.
Another important property is quantum entanglement. Quantum entanglement is the absence of strong correlations between two or more quantum bits (or two or more quantum systems) as classically simulated. Quantum entanglement is the cause of many quantum surprises. Another property is the unclonable theorem [18], which says that quantum information (quantum bits) is irreducible. This theorem has far-reaching implications for quantum bit error correction as well as quantum communication security.
Quantum information science describes the flow of quantum information in quantum computing and quantum communication, and in a broader sense, it can be applied to quantum sensing and metrology, see [19,20].
There is considerable academic interest in this area and several quantum algorithms have been created [21]. However, only a few are expected to be of value for defense and security applications.
3.2 Quantum computing
Current status: Very limited number of physical quantum bits commercially available
Factors affecting applications: new capabilities, effectiveness, precision
Timeline expectations: one million quantum bits in ten years
Major challenges: improving the quality of quantum bits (coherence, error resistance, gate fidelity), increasing the number of quantum bits and logical quantum bits
Quantum computing refers to the use of quantum information science to perform calculations, and such machines can be called quantum computers. The classification of quantum computers is very complex. This report simplifies the classification as follows.
Digital quantum computers (also known as gate-level quantum computers) are general-purpose, programmable, and can perform all possible quantum algorithms, and have many of the applications described below. Classical computers can fully emulate gate-level quantum-based computers. The difference lies in resources and speed. For example, simulating fully entangled quantum bits increases the demand on classical resources in an exponential way. This means that ≥45 quantum bits are almost impossible to simulate on a classical (super) computer.
Analog quantum computers (also known as Hamiltonian quantum computing) are usually implemented using quantum annealing (as a noisy version of adiabatic quantum computing). Quantum annealers differ from digital quantum computers by the finite connectivity of quantum bits and by different principles. As a result, applications of analog quantum computers are more restricted, but still suitable for tasks such as quantum optimization or simulations based on Hamiltonian quantities.
Quantum simulators are used for the study of quantum systems and the simulation of other incoming quantum systems. They are usually less accessible and are built as single-purpose machines. In contrast to a quantum computer, a quantum simulator can be imagined as a quantum circuit that is not programmable.
In general, quantum computing will not replace classical computing. Quantum computers are only applicable to a limited type of problems, usually highly complex ones. The practical deployment of quantum computing applications depends on the quality (coherence, error resistance, gate fidelity) and the number of quantum bits. Some basic parameters to be followed are: number of quantum bits, quantum bit coherence time, quantum gate fidelity, and quantum bit interconnectivity. The set of quantum instructions that apply quantum gates on a single quantum bit is called a quantum circuit. A quantum circuit is a practical implementation of a quantum algorithm.
Following [7], quantum computers can be divided into three evolutionary stages: component quantum computing (CQC), noise-containing intermediate scale quantum computing (NISQ), and fault-tolerant quantum computing (FTQC).The CQC stage includes quantum computing demonstrations and maturation of the basic elements.The computational power of CQC is very limited, but sufficient to demonstrate some principles.The NISQ stage quantum computers should have a sufficient number of quantum bits to demonstrate the benefits of quantum computing. Continued research should increase the number and quality of quantum bits. The FTQC stage begins when a perfect logical quantum bit is reached.
Physical quantum bits can be achieved by many quantum systems. The latest advances are quantum computers based on superconducting quantum bits and imprisoned ion quantum bits that are at or near the NISQ stage. All other technologies, such as cold atoms, topology, electron spin, photons or NV color-center based quantum bits, are still in the CQC stage or theoretical stage. Individual quantum computers differ significantly from their performance (e.g., speed, coherence time, possibility of entangling all quantum bits, gate fidelity). Various metrics and benchmarks, such as the quantum volume metric [22], have been developed for their comparison.
The common problem of all types of quantum bits is their quality. Quantum bits are very fragile and have a finite coherence time (a time scale at which no quantum information is lost). Each operation performed on a quantum bit has a finite fidelity. Therefore, researchers need to use error-correcting codes. Error correction of quantum bits is much more complex than that of classical bits because quantum bits cannot be copied, as explained by the unclonability theorem.
There are two types of quantum bits: physical quantum bits implemented by physical quantum systems and logical quantum bits consisting of several physical quantum bits and error correction codes. A logical quantum bit is a perfect or near-perfect quantum bit with long to infinite coherence time, high fidelity and high resistance to environmental interference. For example, based on surface error correction protocols, for a logical quantum bit, up to 10,000 physical quantum bits are required, depending on the algorithm [23]. For a recent overview of quantum computing, see [24].
Leading quantum computers, such as the one made by Google with 53 physical superconducting quantum bits (Google claims quantum hegemony in 2019 [25]), and the quantum computer made by IBM. The best imprisoned ion quantum computers are IonQ's 32 quantum bits or Honeywell's 20 quantum bits. the expected timeline envisaged by IBM and Google's quantum computing roadmap is as follows: the IBM plans to launch a 433 quantum bit quantum processor in 2022 and a 1121 quantum bit quantum processor by 2023 [26]. Google has announced a plan to implement a 10,000-quantum-bit quantum module. in 2029, all other quantum processors will consist of modules of up to 1 million quantum bits [27]. According to a survey of leaders in key related fields of quantum science and technology, quantum computers are likely to start becoming powerful enough to pose a threat to most public-key cryptography schemes in about 20 years (for more details, see Section 3.2.2) [28]. Examples of analog quantum computers include the quantum annealer of the D-Wave system with more than 5000 quantum bits and Toshiba's coherent Ising machine.
The difference between analog and digital quantum computers lies in the difference in physical principles and the limitations of each. Digital quantum computers are limited by resources rather than noise (noise can be corrected with more resources). In contrast, analog quantum computers are limited by noise that is difficult to understand, control, and characterize (especially for quantum annealers). Therefore, the applicability of analog quantum computers is limited [24].
In fact, most of the tasks performed by quantum computers are just subroutines or subroutines of classical computer programs. Classical programs not only control quantum computers, but also provide a large number of calculations that are not possible on quantum computers. This includes recent applications of quantum simulations in chemistry, such as the use of variational quantum instanton solvers (VQE) [29], which is a hybrid combination of classical and quantum computing. Moreover, quantum computers are large machines, many of which require cryogenic techniques. Therefore, it is unlikely that most customers will purchase individual quantum computers in the coming decades, but rather access them as a cloud service.
Cloud-based models of quantum computing (often called quantum computing as a service - QCaaS) are commercially available today, even for free, and they allow access to anyone interested in quantum computing. Cloud access to quantum computers is provided by various quantum hardware manufacturers. Some platforms, such as Microsoft Azure Quantum or Amazon Braket, allow access to quantum computers from different manufacturers in one ecosystem.
This also helps to clarify quantum hegemony, advantage and practicality (supremacy, advantage and practicality). Quantum hegemony refers to the fact that quantum computers can solve specific problems significantly faster than classical computers. However, this problem is likely to be theoretical rather than practical. Quantum dominance refers to the situation where a quantum computer is able to solve real-world problems that a classical computer cannot solve. Quantum utility is similar to quantum advantage, the only difference being that quantum computers can solve real-world problems faster than classical computers.
A basic overview of the possible applications of quantum computers is presented below. The reader should keep in mind that quantum computing is a rapidly evolving field and that new revolutionary quantum algorithms are still to be discovered. Note that in the context of quantum computing applications, the term "quantum bits" refers to logical quantum bits. However, small quantum circuits can be run with only physical quantum bits with reasonable accuracy.
3.2.1 Quantum Simulation
Status: Algorithms under development, small-scale applications
Factors affecting applications: new capabilities (e.g., quantum chemical computing)
Timeline expectations: near term, availability increases with the number of quantum bits
Quantum bit requirement: 200 (e.g. for nitrogen fixation problems)
Major challenge: number of logical quantum bits
Long before the first quantum computers were created, the main task of quantum computers was to simulate other quantum systems [30], and molecules are one such quantum system. Despite the existing improvements in computational power, using current computational chemistry only allows complete simulations of simpler molecules, or larger molecules at the cost of many approximations and simplifications. For example, for a system with n electrons, a classical computer requires 2n bits to describe the state of the electrons, while a quantum computer requires only n quantum bits. Thus, quantum simulation is the first and probably the most promising application of quantum computers.
There are two most prominent approaches: quantum phase estimation [31] and quantum variational partitioning (VQE) techniques [32, 33]. In particular, the latter approach is most likely to succeed on NISQ computers; for example, in 2020, Google performed the largest quantum chemistry simulation (using VQE for the H12 molecule) [34].
Algorithms for quantum chemistry simulations are under development. They can be applied to more complex simulations, closely related to the number of quantum bits. Thus, even in the early stages of quantum computing, there is a great interest in quantum computing in the chemical and pharmaceutical industries. In general, such simulations allow the discovery and design of new drugs, chemicals and materials. Examples include high-temperature superconductivity, better batteries, protein folding, nitrogen fixation, and peptide research.
3.2.2 Quantum Cryptanalysis
Current status: Algorithm ready
Factors affecting applications: New features (e.g., breaking public key encryption schemes)
Timeline expectations: medium to long term
Quantum bit requirements: 6200 for 2048-bit RSA factorization [35], 2900 for 256-bit ECDLP encryption [36]
Main challenge: number of logical quantum bits
One of the most famous applications of quantum computers is the exponentially accelerated factorization of large prime numbers by the Shor algorithm [37]. This is a threat to public-key cryptosystems such as RSA, DH and ECC, based on large prime multiplication, discrete logarithm problems or schemes based on elliptic curve discrete logarithm problems, which are considered computationally intractable or very difficult for classical computers.
Although the resources of existing NISQ quantum computers fall far short of what is needed for RSA cracking, the threat is quite real. Until quantum cryptanalysis becomes available, an adversary or foreign intelligence agency can intercept and store encrypted traffic. Because many secrets take far longer to decrypt than the expected timeline for delivery by powerful quantum computers, the threat can now be considered real.
Quantum cryptanalysis also provides improved tools for brute force attacks on symmetric encryption schemes. For example, the well-known Grover search algorithm [38] reduces key security by half against brute force attacks; a 256-bit AES key can be strongly cracked in about 2128 quantum operations. Doubling the symmetric key length is recommended despite the large resources required for quantum computers [39]. Moreover, Simon's algorithm and superposition queries [40] can completely break most message authentication codes (MACs), as well as authenticated encryption of associated data (AEAD), such as HMAC-CBC and AES-GCM [41, 42].
In addition, cryptanalytic attacks on symmetric key systems have been actively studied based on the structures present in symmetric cryptosystems, which can provide up to super-polynomial speedups [43]. However, these algorithms are overly demanding on the resources of quantum computers.
3.2.3 Quantum search and quantum walk
Current status: algorithms are under development
Factors affecting applications: effectiveness (e.g., faster search)
Timeline expectation: near to mid-term
Quantum bit requirement: ~100, depending on the size of the search system
Major challenge: number of logical quantum bits
One of the best known search quantum algorithms is the Grover algorithm [38], which provides squared speedups in database searches or usually in inversion functions. For an unsorted list or database, the classical search algorithm has a complexity of about O(N) (meaning proportional to the number of N entities), while the Grover algorithm has a complexity of about.
Quantum search algorithms are an important topic for the analysis of so-called big data (unstructured data). Processing large amounts of data requires large capacity quantum memory. However, there are no reliable quantum memories that can keep large amounts of quantum information for arbitrarily long periods of time. Second, converting classical data into quantum form is both time-consuming and inefficient. Therefore, only a search of algorithmically generated data is currently considered feasible.
An alternative search method can be based on the quantum random walk mechanism [44], which provides a similar speedup to the Grover algorithm.
3.2.4 Quantum optimization
Current status: algorithm in development
Factors affecting application: effectiveness (e.g. faster solution of NP problems)
Timeline expectation: Near to mid-term
Quantum bit requirement: 100, depending on the complexity of the problem
Main challenges: Number of logical quantum bits
Quantum optimization is a very active topic of exploration considering the possibility of solving NP complex problems. An example of such an NP problem is the traveler problem, where given a list of locations and the distances between them, the goal is to find the shortest (optimal) route. Naively, one can try all possibilities, but this approach has serious drawbacks. With increasing complexity, it may even become impossible. Therefore, the most common solutions are based on heuristic algorithms that do not necessarily find the optimal solution, but at least find a solution close to it.
Quantum computing introduces a new perspective on this problem and offers different methods and techniques. The most current methods are based on variational methods such as the quantum approximate optimization algorithm (QAOA) [45]. part of QAOA is a subtechnique called quadratic unconstrained binary optimization (QUBO) [46], which is also applicable to analog quantum computers. Other methods are quantum simulation with least squares fitting [47] or semidefinite programming [48].
So far, it is not clear whether quantum optimization will provide some speedup relative to classical heuristics. However, there is a consensus that if some speedup is achievable, it will not be more than polynomial [48]. The new paradigm introduced by quantum computing leads to new quantum-inspired classical algorithms, such as QAOA without quantum acceleration [49]. On the other hand, we can say that quantum-inspired algorithms are the first practical result of quantum computing.
For quantum optimization, there have been many demonstrations, use cases and proofs of concept, especially in simulated quantum computing, which currently provides the most quantum computing resources for such applications. Typical demonstrations are optimizations for the transportation, logistics or financial industries.
3.2.5 Quantum Linear Algebra
Status: Algorithms in development
Factors affecting applications: effectiveness (e.g., faster linear equation solving)
Timeline expectation: Near to medium term
Quantum bit requirement: depends on the size of the system being solved
Main challenge: Number of logical quantum bits
It has been shown that quantum computers can also achieve super-polynomial speedups when solving systems of linear equations, especially for the HHL (Harrow-Hassidim-Lloyd) [50] algorithm for sparse matrices. However, the estimated speedup depends on the size of the problem (matrix) and also on the large resource requirements, which is impractical for some problems [51]. On the other hand, for example, for a system of linear equations with 10,000 parameters, 10,000 steps are required to solve the problem, while HHL can provide an approximate solution after 13 steps.
Currently, many numerical simulations in planning, engineering, construction, and weather forecasting reduce complex problems to systems of linear equations. For many of these problems, approximate solutions may be sufficient since they are statistical in nature.
Note that the HHL algorithm is proven to be a general algorithm for quantum computing and has been shown to be suitable for various applications such as k-means clustering, support vector machines, data fitting, etc. For more details, see [52].
A major caveat of quantum algorithms that deal with large amounts of input data is data loading. Classical data, especially binary data or bits, need to be converted into quantum states for subsequent processing by efficient quantum algorithms. This process is slow, and the classical data loading itself may take longer than the coherence time. The solution is quantum memory or quantum RAM [52,53].
3.2.6 Quantum machine learning and artificial intelligence
Current status: algorithms in development
Factors affecting applications: effectiveness (e.g., better machine learning optimization)
Timeline expectation: near to mid-term
Quantum bit requirement: 100, depending on the complexity of the problem
Main challenges: Number of logical quantum bits
Given the hype around classical machine learning and artificial intelligence (ML/AI), it can be expected that there will be quantum research on this topic as well. First, note that given the very low efficiency of processing classical data [54], one cannot expect to obtain full quantum ML/AI, even more so if one considers the lost quantum memory and the very slow loading and encoding of classical data (e.g., image data) into quantum information formats. This is simply not practical. A different situation arises when ML/AI is applied to quantum data; for example, quantum sensors or imaging [55].
However, quantum-enhanced ML/AI can be introduced [56, 57], where quantum computing can improve some machine learning tasks such as quantum sampling, linear algebra (where machine learning is about processing complex vectors in a high-dimensional linear space) or quantum neural networks [54], such as quantum support vector machines [58].
In fact, the ML/AI topic covers a variety of techniques and methods, which are not different from quantum computing. Quantum ML/AI or quantum-enhanced ML/AI is the subject of many research efforts today. For a study of quantum ML/AI algorithms and their possible acceleration, see [59].
3.3 Quantum communication and cryptography
Quantum communication refers to the exchange of quantum information through quantum networks using optical fibers or free-space channels. In most cases, quantum communication is achieved using photons as quantum information carriers. However, due to the limitations of photons, such as losses over long distances, quantum networks need to contain other components such as quantum repeaters or quantum switches.
The goal of quantum cryptography is to replace traditional (mainly asymmetric) encryption schemes with techniques such as quantum key distribution (QKD). Typical quantum features used for quantum communication are as follows: quantum entanglement, quantum uncertainty, and the theory of unclonable quantum information that cannot be replicated [18, 60].
3.3.1 Quantum networks
Status: under research (commercial QKD with trusted nodes only)
Factors affecting applications: new capabilities, effectiveness (e.g., ultra-secure communication, quantum resilient encryption)
Timeline expectations: mid-term
Key challenges: quantum repeaters and switches (quantum memory)
The goal of quantum networks (sometimes referred to as the quantum Internet [61] or quantum information networks (QINs)) is to transmit quantum information over a variety of channels through multiple technologies. Quantum information (quantum bits) is usually carried by a single photon, and thus quantum information transmission is fragile. In addition, many quantum network applications rely on quantum entanglement.
The common channels for quantum information transmission are dedicated low-loss optical fibers or the current higher loss telecommunication fiber infrastructure. The case of two communication endpoints in close proximity to each other is as simple as using a single optical fiber. The complexity of the network increases with more end nodes or with distance, where components such as quantum repeaters or quantum switches are required. Note that for most quantum network applications, very small (one quantum bit) quantum processors are sufficient.
Free space quantum channels are more challenging. Optical or near-optical photons are of limited use in the atmosphere due to strong atmospheric attenuation. Therefore, the most frequently considered and implemented quantum network scenario is the use of quantum satellites [62, 63]. Satellites have the advantage of being able to transmit quantum information using optical-photonic communication, where the loss in the satellite-ground link is lower than the loss between two ground nodes that are far apart. However, photon communication over short distances in free space channels can be achieved by, for example, unmanned aircraft [64]. The best approach is to use the microwave spectrum used for classical wireless communication. However, communication at the single photon level using the microwave spectrum is more challenging [65]. Microwave single photon techniques have greater difficulties in generating and detecting individual photons. Another problem is the noisy environment of the microwave band.
Quantum communication over long distances requires quantum repeaters due to photon loss and decoherence. A quantum repeater is an intermediate node that works like an amplifier in a classical optical network, but needs to obey the unclonable theorem. In fact, quantum repeaters allow to entangle the quantum bits of the end nodes. When two end nodes are entangled, the effect of quantum invisible transmission of states can be exploited [66]. This means that quantum information can be transmitted without physically sending a photon; only a classical communication is required. Using quantum entanglement, quantum information can flow through a quantum network or part of it, even under the control of an eavesdropper, without any chance of leaking the transmitted quantum information. In order for quantum repeaters to work properly, quantum memory is needed. However, there are no reliable and practical quantum memories available.
As an intermediate step, trusted repeaters can be used. Trusted relays do not entangle end nodes and are only used for quantum key distribution (QKD, see the next section 3.3.2). To illustrate how it works, let us consider two parties A and B and a trusted relay R. The key kAB is then encrypted with the key kAR. the trusted relay R decrypts kAR to obtain kAB. at this point, the trusted relay R knows the key kAB and A and B must believe that the key is secure and not under the control of an eavesdropper. Finally, R re-encrypts kAB using the key kRB and sends it to B. This is a technique currently used in QKD networks.
The next step, currently tested in experiments, is the measurement device-independent QKD (MDI-QKD) [67, 68]. It is such a quantum protocol that not only replaces trusted repeaters with secure repeaters (still not quantum and not supporting entanglement), but also acts as a switch. This means that the usual star network topology and infrastructure can start to be built. Note that in an MDI-QKD network, an attack on the central node cannot physically reveal either the key or sensitive information. After that, the central node will be replaced by quantum switches and repeaters, resulting in a fully functional quantum information network.
The quantum network will work in parallel with the classical network because not all transmitted information needs to be encoded with quantum information. For example, quantum invisible transmission requires parallel classical networks, and quantum networks can be used for the following applications.
Quantum key distribution (QKD), secure transmission of cryptographic keys (see Section 3.3.2).
Quantum information transfer between distant quantum computers or quantum computing clusters, or remote quantum capability sharing.
Blind quantum computing [69, 70] allowing the transmission of quantum algorithms to quantum computers, the execution of calculations and the retrieval of results without the owner or eavesdropper knowing what the algorithms or results are.
Network clock synchronization [71], see Section 3.4.2.
Secure identification [72], allowing identification without revealing authentication credentials.
quantum location verification [73] allowing to verify the location of another party.
distributed quantum computing for multiple quantum computers [74, 75], allowing to compute tasks as a single quantum computer.
Consensus and protocol tasks, referring to the so-called Byzantine protocols (problems in which the team makes a decision on an output despite the intervention of the adversary). The quantum version [76] can reach a complexity of O(1) compared to the classical complexity.
Entangled sensor networks [77, 78] can improve sensor sensitivity and reduce errors, and evaluate global properties instead of collecting data on specific parts of the system.
Quantum networks allow direct and secure quantum communication between quantum computers, where quantum data can be exchanged directly. This helps to efficiently redistribute computational tasks based on the performance of individual quantum computers, mainly when a huge task can be divided into smaller tasks. Another example is the quantum cloud, where quantum data can be shared among multiple quantum computers. In addition, the possibility of building a stand-alone high-performance quantum computer is also questionable. It is more likely to be achieved through distributed quantum computing [74, 75], where many quantum computers will be connected through a quantum network.
3.3.2 Quantum key distribution
Current status: commercial (with trusted relays)
Factors affecting applications: new capabilities
Timeline expectations: near future
Main challenges: secure quantum repeaters (quantum memory), secure authentication of physical hardware
Quantum key distribution (QKD) is the most mature application of quantum communication. The goal is to distribute keys between two or more parties for encrypted data distributed over a classical channel. Due to the unclonable theorem, any eavesdropper must perform a measurement that can be detected by the communicating party.
There are two main types of protocols:one based on the BB84 (Bennett-Brassard 1984) protocol [79] and the other based on the E91 (Ekert 1991) protocol [80]. The dominant BB84 protocol is technically simpler, but requires the generation of quantum random numbers (cf. Sect. 3.3.4) and the provider must prepare the key before distribution. Protocol E91 uses quantum entanglement to generate the key during distribution and all parties know the key at the same time. In this protocol, a quantum random number generator is not required. However, the technical solution for quantum entanglement is more challenging. Both types of protocols are secure in terms of information theory.
Theoretically, QKD is impenetrable during transmission. However, typical attacks may focus on the final (receiver/transmitter) or intermediate nodes where the hardware at the software layer may contain vulnerabilities such as errors in the control software, imperfect single photon sources, verification issues between parties, etc. This is a very active area of research. For example, imperfect physical hardware may be misused by photon number splitting (PNS) [81] or Trojan horse [82] attacks. Here, secure authentication of hardware and software is necessary and takes time.
Besides trusted relays, another weakness is that the quantum bit transfer rate is too slow to distribute long keys. A new high transmission rate single photon source could solve this problem.
Currently, QKD technology is available for commercial applications, such as point-to-point connections over short distances or the use of trusted repeaters over long distances. A trusted repeater can be a space satellite, as has been demonstrated in China [62, 63].
3.3.3 Post-quantum ciphers
Current status: algorithm ready
Factors affecting applications: must have
Timeline expectations: near future
Main challenges: standardization, implementation
Post-quantum ciphers (sometimes referred to as quantum proofs, quantum security, or quantum-resistant ciphers) represent an area of cryptography that is resistant to future attacks by quantum computers. Currently, this is not the case for most asymmetric encryption using public key techniques. On the other hand, most symmetric cryptographic algorithms and hash functions are considered relatively secure against attacks by quantum computers [83]. However, doubling the symmetric key length is still recommended [39].
Nowadays, several methods are considered to be quantum resistant. Examples are lattice based ciphers [84], super singular elliptic curve homology ciphers [85], hash based ciphers [86], multivariate based ciphers [87], code-based ciphers [88] and quantum resistant symmetric keys.
Unlike QKD, all these algorithms are not provably secure from a mathematical point of view. Therefore, all these algorithms have been rigorously tested and analyzed during the standardization process, including the implementation. There is no worst-case scenario where a classical computer can crack an anti-quantum algorithm with a flaw in the implementation [89]. The most talked about standardization effort is that of the National Institute of Standards and Technology (NIST) [90]. the NIST standardization process is expected to be concluded in 2023-2024. In any case, new quantum-resistant encryption solutions are now being offered by a growing number of commercial vendors.
3.3.4 Quantum Random Number Generator
Current status: Commercial
Factors affecting application: New features (true random number generation)
Timeline expectation: near future
Main challenges: Increasing the bit rate
Random number generators (RNGs) are essential for many applications, such as Monte Carlo simulation and integration, cryptographic operations, statistics, and computer games. However, RNGs in classical computers, which are not truly random because they are deterministic, are called pseudo-random number generators. However, for many applications, pseudo-RNGs are sufficient.
On the other hand, generating strong keys is the cornerstone of security and can only be achieved by a true random number generator. One solution is a hardware-based quantum random number generator (QRNG). Moreover, QRNG is a key part of the BB84-based QKD protocol and is provably secure.
QRNG can be used in any cryptography and makes all cryptography better. Unlike other RNGs, one of the advantages of the quantum random number generator is that it can be verified and authenticated [91].
3.4 Quantum sensing and metrology
Quantum sensing and metrology is the most mature area of quantum technology that can improve timing, sensing, or imaging. For example, the atomic clocks of the first quantum revolution have been part of the Global Positioning System (GPS) for almost half a century. Current quantum clocks offer much higher accuracy in time measurement.
Quantum sensing represents all quantum technologies that measure various physical variables such as external magnetic or electric fields, gravitational gradients, acceleration and rotation. Quantum sensors can produce very precise information about electrical signals, magnetic anomalies and inertial navigation.
Quantum imaging is a branch of quantum optics that uses photonic correlations to suppress noise and improve the resolution of imaged objects. Quantum imaging protocols are considered for quantum radar, detection of objects in optically impenetrable environments, and medical imaging.
Quantum sensing and metrology techniques rely on one or more of the following features: quantum energy levels, quantum coherence, and quantum entanglement [92]. Individual quantum sensors have different metrics, which vary from application to application. Common metrics are: sensitivity (signal per unit signal-to-noise ratio given after 1 second), dynamic range (minimum and maximum detectable signal), sampling rate (signal sampling frequency), operating temperature, etc. Key metrics derived include, for example, spatial resolution at a given distance and the time required to reach a given sensitivity. Typical measured quantities are magnetic and electric fields, rotation, time, force, temperature, and photon counting.
3.4.1 Quantum electric, magnetic and inertial force sensing
Current status: Laboratory prototype
Factors affecting applications: accuracy, new capabilities
Timeline expectations: near to far future
Major challenges: miniaturization, cooling
Many sensing quantum technologies are generic and can measure a variety of physical quantities. A detailed description of each technology is beyond the scope of this report; however, a basic overview is provided. Many applications include a variety of quantum technologies. For example, quantum inertial navigation includes three types of sensing: acceleration, rotation, and time. In general, many applications require precise quantum-based timing, not just quantum technology. For quantum timing, see Section 3.4.2. The most promising techniques are: atomic vapor, cold atom interferometry, nitrogen-vacancy color centers, superconducting circuits, and captive ions.
Cold atom interferometry (quantities measured: magnetic field, inertial force, time). Atoms cooled at very low temperatures exhibit wave-like behavior and are sensitive to all forces interacting with their mass. These changes can be observed in interferograms [5, 92, 93]. Specific implementations can be in the form of Raman atomic interferometry, atomic Bloch oscillations or others [94-96]. For example, in gravity measurements, quantum-based gravimeters have the potential to achieve accuracies several orders of magnitude higher than the best classical gravimeters. Such precision gravimeters are capable of mapping the Earth's surface and subsurface in great detail with centimeter-level resolution. Regarding inertial navigation, vibrational lattice interferometry has the potential to overcome the shortcomings of the state-of-the-art atomic interferometry techniques and can be used as both accelerometer and gyroscope [97]. Several challenges remain, some of the biggest being the integration of quantum sensors into a quantum inertial measurement cell, the miniaturization of laser cooling devices for cooling atoms while maintaining coherence (suppressing interactions with the noisy environment), or maintaining the dynamic range of cold atomic sensors outside the laboratory. However, significant progress has also been made in this field, e.g. [98], for a review see [99].
Imprisoned ions (measured quantities: electric and magnetic fields, inertial forces, time). The captive ion is one of the most versatile sensing platforms [100-102]. Well-controlled captive ions form a crystal with quantized patterns of motion. Any disturbance can be measured by switching between these modes. A single imprisoned ion can be used as an exact measurement of time or as a quantum bit in a quantum computer. For inertial navigation, the optical lattice technique of imprisoning cold atoms in 1, 2 and 3-dimensional arrays has the potential to provide sub-centimeter dimensions, and it can measure Casimir or van der Waals forces in addition to gravity and inertial parameters. Recently, using quantum entanglement of imprisoned ions, electric field measurements have reached a sensitivity of [103], which is several orders of magnitude higher than classical methods.
Nitrogen-vacancy (NV) color centers (measured quantities: electric and magnetic fields, rotation, temperature, pressure). The NV color center in a diamond crystal is an electron spin quantum bit coupled to an external magnetic field. In addition, the rotation can be measured using a negatively charged NV color center in Berry phase. In general, NV color-center-based sensors have high sensitivity, low production and operational costs under various conditions [92, 104, 105]. In particular, NV color-center-based techniques can also operate at room temperature and higher temperatures. A newly proposed 3D design can sense all three components of magnetism, acceleration, velocity, rotation, or gravity simultaneously [106].The advantages of NV color centers for diamond sensing are spatial resolution and sensitivity. On the other hand, the challenge is to select, implement and fabricate individual NV color centers or a combination of them. In the case of electric field sensing, it is challenging to define the sensitivity [107].
Superconducting circuits (measured quantities: electric and magnetic fields). The technique of superconducting circuits based on the Josephson effect describes the quantum tunneling effect between two superconductors [92]. This technique allows the fabrication of quantum systems on a macroscopic scale and can be efficiently controlled with microwave signals. The superconducting quantum interferometer (SQUID) is one of the best magnetometer sensors. However, the disadvantage is that it requires low temperature operation. Note that for measurements of magnetic field variations smaller than geomagnetic noise, the preferred design is based on sensor arrays to eliminate spatial correlation with the application, for example in medical and biomedical applications (e.g. MRI or molecular labeling). Recent developments have shown that superconducting quantum bits used in quantum computers can also be used to measure electric and magnetic fields [92].
Atomic vapor (measured quantities: magnetic field, rotation, time). Spin-polarized, high-density atomic vapors undergo state transitions under an external magnetic field that can be optically measured [92, 108, 109], an advantage being that they unfold at room temperature. Atomic vapors are suitable for spin sensing, called atomic spin gyroscopes (AGS), and AGS can be chip-scale [5]. In contrast, the best classical rotation sensors are very accurate (e.g., ring laser gyroscopes) and the expected quantum sensors will be twice as accurate. However, the size of the best classical gyroscopes is 4 × 4 m, which is impractical for quantum devices [110]. Atomic vapour cell magnetometers based on the atomic system synthesis have the potential to surpass SQUID magnetometers and operate at room temperature [92].
3.4.2 Quantum clocks
Current status: laboratory prototype
Factors affecting application: accuracy
Timeline expectations: near to mid-term
Main challenges: miniaturization
Atomic clocks have been with us for decades; for example as part of GPS satellites. Current atomic clocks are based on atomic physics, where the electromagnetic emission of electrons emits a "ticking sound" when changing energy levels. Atomic clocks are a very mature technology and can achieve relative uncertainties of ~10-15-10-16 based on the principles of atomic fountains or thermal atomic beams and magnetic state selection [111], or 2 × 10-12 for the most advanced chip-size atomic clocks [5].
The second quantum revolution brought new principles of atomic clocks or quantum clocks. Quantum logic clocks are based on single ions, a technique related to the quantum bits of imprisoned ions in quantum computing [101]. Quantum logic clocks were the first clocks with clock uncertainties below 10-18 [112], and quantum clocks can also benefit from quantum entanglement [113].
Later, quantum logic clocks were replaced by experimental optical lattice clocks. Note that the current atomic clocks use microwave frequencies, i.e., jumps between energy levels emit microwave photons. Measuring energy level jumps with emitted photons in optical frequencies is more difficult to implement, although it provides better performance. Optical clocks are still under development, with systems based on: individual ions separated in ion traps, neutral atoms trapped in an optical lattice, and atoms encapsulated in a 3-dimensional quantum gas optical lattice. In particular, 3-dimensional quantum gas optical lattice clocks have achieved a frequency accuracy of 2.5 × 10-19 [114]. Recently, it has been shown that quantum entanglement can enhance the stability of clocks [115].
Another study focused on vapor chamber (or gas chamber) atomic clocks, offering chip-sized implementations [116]; solid-state (e.g., NV centers in diamond) clocks [117]; or nuclear clocks similar in principle to microwave or optical atomic clocks, except that it uses nuclear rather than electronic leaps in the atomic shell layers [118], with unprecedented performance potential over atomic optical clocks [119 ].
Various clock technologies have their own challenges, such as precise frequency combs, laser systems for control and cooling, and blackbody radiation shifts (in the case of optical clocks). In addition, miniaturization usually comes at the cost of lower frequency accuracy. Another common challenge is the synchronization of these clocks.
Precise timing is essential for many technologies, such as satellite navigation, space systems, precision measurements, telecommunications, defense, network synchronization, the financial industry, energy grid control, and virtually all industrial control systems. However, very precise timing is essential for quantum technologies, especially for quantum sensing and imaging. For example, a very high precision clock can enable new measurements such as gravitational potential measurements at the centimeter level on the Earth's surface or the search for new physics.
3.4.3 Quantum RF antenna
Current status: Laboratory prototype
Factors affecting application: effectiveness
Timeline expectations: near to mid-term
Main challenges: miniaturization, cooling
Radio frequency (RF) antennas are used as receivers or transmitters for a variety of signals. They can be as simple as dipole antennas or as complex AESA modules. Their size is limited by the wavelength of the signal being generated or received. For example, the wavelength of a 3 GHz signal is 10 cm and the size of the antenna should be no less than about 1/3 of that wavelength. this is the so-called Chu-Harrington limit [120, 121].
The technology of the Riedberg atom can break this limit and have an antenna with a size of a few microns independent of the wavelength of the received signal. Riedberg atoms are highly excited state atoms with correspondingly large electric dipole moments and thus highly sensitive to external electric fields [122, 123]. Note that antennas based on Riedberg atoms can receive only one signal.
The latest prototype of the Riedberg Atom analyzer was demonstrated in the frequency range from 0 to 20 GHz for AM or FM radio, WiFi and Bluetooth signals [124]. A combination of more antennas allows the detection of the angle of arrival of the signal [125]. At the laboratory level, the Riedberg Atom technology has been commercialized.
Quantum RF receivers as single units (for target frequencies, narrow bandwidth) or arrays of sensors (wide frequency range) can find applications in navigation, active imaging (radar), telecommunications, media receivers, or passive THz imaging.
3.4.4 Quantum imaging systems
Current status: Laboratory prototypes and proof of concept
Factors affecting applications: new capabilities
Timeline expectations: near to far future
Key challenges: improved resolution, high rate single photon sources
Quantum imaging systems are a vast field covering 3D quantum cameras, behind-the-corner cameras, low luminance imaging and quantum radar or lidar (see Section 3.4.5 for quantum radar).
The Single Photon Avalanche Detectors (SPAD) array is a very sensitive single photon detector that is connected to a pulsed illumination source to measure the time of flight from the light source to the object, and thus the range of the object. The SPAD can then be placed into an array that works like a 3D camera. the SPAD works with a spectrum that extends to the near infrared spectrum.
The SPAD array can also be used to detect objects beyond detection (e.g. hidden behind a corner). The idea is based on the cooperation of a laser and a camera, where the laser sends a pulse in front of the SPAD camera (e.g. a point on the floor). From that point, the laser pulse will scatter in all directions, including behind the corner, where photons can be reflected to the point in front of the SPAD camera and then reach the camera. the sensitivity of the SPAD is sufficient to detect such a thrice scattered signal [126].
Quantum ghost imaging (QGI) [127-129], also known as conformal imaging or two-photon imaging, is a technique that allows imaging of objects beyond the line of sight of the camera. In the light source, two entangled photons are generated, each with a different frequency, one of which is recorded directly by a high-resolution photon counting camera, and a second photon with a different frequency (e.g., infrared) is sent to the object, and the reflected photon is detected by a single photon detector (so-called "bucket" detector), which then, based on the correlation between the two The image is then created based on the correlation between the two photons. Despite the poor resolution, the ghost imaging protocol was also demonstrated in the absence of quantum entanglement (using classical correlation).
This model allows imaging objects at very low light levels. In addition, infrared light can better penetrate some environments with better signal-to-noise ratio (SNR) [130], and ghost imaging experiments using x-rays or extreme relativistic electrons have been recently demonstrated [131, 132].
Sub-shot-noise imaging [133] is another quantum optical scheme that allows the detection of weakly absorbing objects with signals below the scattering noise, which is the result of fluctuations in the number of detected photons, e.g., the scattering noise is the limit of the laser, and this limit can be overcome using correlated photons, a "pilot The detection of a "pilot" or "auxiliary" photon indicates the presence of a correlated photon that detects the object or environment.
Quantum Illumination (QI) [134] is a quantum protocol that uses two correlated (entangled) photons to detect a target. One "idle" photon is kept and the other, called the "signal" photon, is sent to the target and is reflected, and both photons are measured. The QI protocol is one of the main protocols applicable to quantum radar, but it can also be applied to medical imaging or quantum communication.
3.4.5 Quantum Radar Technology
Current status: Laboratory prototypes and proof of concept
Factors affecting applications: new capabilities
Timeline expectations: far or further out
Major challenges: high-speed single-photon sources, quantum microwave technology
In principle, quantum radar works in a similar way to classical radar in that signals must be sent to the target and the radar system needs to wait for the reflected signal. However, theoretically improved accuracy and new capabilities can be achieved by quantum mechanical methods.
Several protocols have been considered for quantum radar, such as interferometric quantum radar [135], quantum illumination (QI) [134], hybrid quantum radar [136, 137], or Maccone-Ren quantum radar [138]. None of the above protocols is perfect. For example, interferometric quantum radar is too sensitive to noise and needs to maintain quantum entanglement. qI is an ideal protocol in noisy environments and has even been laboratory validated in the microwave spectrum [139], but it needs to know the distance to the target, so it has no ranging capabilities. However, QI-based quantum target ranging methods are under development [140]. This ranging problem can also be solved by hybrid quantum radar, but at the expense of sensitivity.The Maccone-Ren protocol has QI properties and ranging capabilities, but so far it is only a theoretical concept.
The biggest challenge common to all protocols is (not only) the high-speed generation of entangled photons in the microwave range. The quantum version of the radar equation [141] still maintains the dominant term 1/R4, where R is the radar-target distance. Therefore, the number of entangled photons (modes) required is several orders of magnitude higher than the number currently available [142]. In a sense, quantum radar is similar to noise radar and has many common properties such as interception probability, low detection probability, and effective spectrum sharing. See [137] and references therein.
Another related challenge is finding the target. Theoretical work [143] shows that quantum entanglement can outperform any classical strategy when it comes to finding the unknown location of a target. Moreover, the method can be used as a quantum-enhanced frequency scanner for a fixed target range.
3.4.6 Other sensors and techniques
Current status: Laboratory prototype
Factors affecting applications: New capabilities (e.g., chemical and precise acoustic detection)
Timeline expectations: near to mid-term
Key challenges: improving resolution
Using photoacoustic detection, quantum technologies can be used for ultra-precise sound sensing up to the level of phonons, which are quasiparticles that quantify acoustic waves in solid matter by photoacoustic detection [144, 145]. Accurate detection of acoustic waves is essential for many applications, including medical diagnostics, sonar, navigation, trace gas sensing, and industrial processes [146, 147].
Photoacoustic detection can be combined with quantum cascade lasers for gas or general chemical detection. A well-established technology is the quantum cascade laser (QCL) [148], a semiconductor laser that emits in the mid-wave and long-wave infrared bands and, like many other quantum technologies, requires cooling to well below -70°C. However, recent developments allow chip-level implementations at temperatures of approximately -23°C, which can be achieved with portable cooling systems [149].
Military technology has higher requirements than industrial or public applications. This requires greater caution given the potential for deployment on the battlefield. Section 5 describes a variety of possible military applications with different levels of technology maturity, time expectations, and multiple implementation risks.
This would be simpler and less risky for technologies that are easy to implement and suitable for current technology, such as quantum sensors, which simply means we can replace classical sensors with quantum sensors.
In contrast, QKD is a technology that has been commercialized but is difficult to deploy, requiring significant new hardware, systems, and interoperability with current communications systems. As a result, this technology carries greater risk in terms of military deployment.
In the long run, we can expect advantages in reducing SWaP (size, weight, and power) and scaling up quantum computers and quantum networks, which will make deployment easier and may be necessary if nations/military forces want to compete with other nations/military forces for edge (quantum) technologies.
4.1 Quantum Strategy
Future users of military quantum technologies will have to carefully consider if, where, and when to invest time and resources. The goal of defense forces is not to develop military technology, but usually to simply specify specific requirements and procurements. However, especially if they are the end users, they can be largely involved in the development.
As a basis, it is desirable to have a national quantum ecosystem consisting of industry and academic institutions, which should be generally supported at the governmental level, i.e., the development of a national quantum program, but should also be incentivized to develop technologies for the defense sector, which can be achieved through appropriate grant funding or even various thematic challenges in which individuals and startups can participate and perhaps bring new disruptive ideas and solutions, which will naturally lead to closer collaboration with industry and academia. The quantum industry is very interesting, and there is a great deal of collaboration between academia and industry.
The first step is to develop a quantum technology roadmap or quantum strategy. The roadmap/strategy should define all subsequent steps, from identifying loop-breaking quantum solutions, market surveys, technology and risk assessments, and the development itself, to prototype testing and final solution deployment. A roadmap or quantum strategy can consist of three parts.
Identification.
Development.
Implementation and Deployment.
The most critical part is the identification of the most beneficial and disruptive quantum technologies for the warfare domain under consideration. This step also includes technical and scientific assessments to balance the technical risks (limited deployability, lower-than-expected performance, or inability to transfer from the laboratory to the battlefield) with the potential benefits of individual quantum technologies. This identification process should be repeated cyclically to allow for a relatively rapid response to new discoveries and disruptive solutions. It is important to remember that many applications have yet to be identified or discovered.
The next step is the usual research and development process (R&D). R&D should be adequately supported financially, but also with minimal bureaucratic hurdles. It should include a rapid development cycle (specification and performance consulting, prototype testing, certification preparation, etc.) that interacts closely with the end users of the military technology. At the end of this phase, a new system in initial operational capability should be ready to go.
The final step is the achievement of full operational capability, which includes the modification or creation of new military doctrine and the preparation of new military scenarios, strategies, and tactics that take full advantage of the quantum advantage.
The final point involves the identity confirmation phase. Here, decision makers also need to take a long-term perspective. So far, many quantum technologies have been considered separately: sensors, quantum key distribution, quantum computing, etc. However, the long-term vision considers the interconnection of quantum sensors and quantum computing through quantum networks. Theoretical and experimental work has demonstrated additional quantum advantages using quantum entangled sensors and computers [77, 78], and more similar applications may be discovered or invented. It is important to consider this when building fiber/quantum networks. In the longer term future, existing components such as trusted repeaters can be replaced by full quantum repeaters and switches, thus realizing the full potential of quantum networks.
4.2 TRL and Time Range
As already mentioned several times, various quantum technologies are at different TRLs, ranging from 1 to 8. TRL variations and time ranges are expected to be even more complex when considering various applications and deployment platforms, especially for military purposes. Some estimates of TRLs and time ranges are provided in [150]. However, some estimates, such as TRL 6 for quantum precision navigation, seem overly optimistic based on the description in this report.
Table 1 Technology maturity level (TRL) and time horizon expectations
Actual military deployments may take some time to overcome all technical obstacles and meet military requirements. For example, with quantum gravimeters for subsurface scanning, the first generation is likely to deploy static sensors for trucks with fairly low range or spatial resolution. Over time, the next generation will improve sensitivity and spatial resolution. As SWaP decreases, the sensor will be able to be placed on an aircraft, which could later be mounted on an unmanned aircraft, and possibly on a low-orbiting satellite. However, it is also possible that the limits of the sensor will be reached earlier, making it impossible to deploy, for example, on a UAV or a low-orbiting satellite.
4.3 Quantum technology countermeasures
Quantum technology countermeasures refer to methods and techniques that spoof, disable, or disrupt quantum technologies, whether they are quantum computers, quantum networks, or quantum sensors and imaging systems, quantum technologies exploit the quantum physical properties of individual quanta. As such, they are susceptible to environmental interference and noise, and therefore have the potential to be spoofed or crippled. Especially regarding quantum networks and especially quantum key distribution, quantum hacking [151-155] has been developed hand in hand with quantum key distribution.
Developers and decision makers of quantum strategies should keep in mind that sooner or later various countermeasures will emerge when quantum technologies are deployed in the military domain; what is unknown is the possible effectiveness of quantum technology countermeasures and their impact.
Quantum technology has the potential to dramatically impact many areas of human activity, especially for the defense sector. Quantum technology can affect all areas of modern warfare. Instead of developing new types of weapons, the second quantum revolution will increase sensitivity and efficiency, introducing new capabilities and improving modern warfare technologies.
The following text describes the military, security, space and intelligence applications of quantum technology in different aspects of modern warfare, and it also mentions industrial applications that may indicate the capabilities and performance of quantum technology, especially in the absence of publicly available information on military applications.
Figure 1 Schematic diagram of quantum warfare using various quantum technology systems
It is important to note that many applications are still more theoretical than real. Significant quantum advances made in the laboratory do not always lead to similar advances outside the laboratory. The transfer from the lab to practical deployment involves other aspects such as portability, sensitivity, resolution, speed, robustness, low SWaP (size, weight and power) and cost, as well as working lab prototypes. The practicality and cost effectiveness of quantum technologies will determine whether or not a particular quantum technology is built and deployed.
Integrating quantum technologies into military platforms is more challenging. In addition to quantum computers, which are primarily located in data centers similar to their civilian counterparts, the integration and deployment of quantum sensing, imaging, and networking face several challenges associated with increased demand for military use (as compared to civilian/industrial or scientific needs). For example, military-grade requirements for precision navigation require fast measurement rates, which are very limited for current quantum inertial sensors.
In addition, the field is still very young and new technological surprises, both good and bad, may bring other quantum advantages or disadvantages.
5.1 Quantum cybersecurity
Key point.
The need for quantum cryptographic flexibility implementation.
Operations that want to take advantage of Shor's algorithm should start collecting data of interest before quantum-secure encryption is deployed.
QKD implementation requires careful consideration.
QKD endpoints will be the weakest part of the system.
The quantum advantage in cyberwarfare can provide new, but very effective (with exponential acceleration) attack vectors for current asymmetric encryption (based on integer decomposition, discrete logarithm or elliptic curve discrete logarithm problems) as well as theoretically symmetric encryption. On the other hand are new quantum elastic encryption algorithms and methods, as well as quantum key distribution. For an overview, see [157-160].
The current trend is also the development and application of machine learning or artificial intelligence in cyberwarfare [161]. For more details on quantization opportunities, see Section 5.2.
5.1.1 Quantum Defense Capabilities
The implementation of post-quantum cryptography is a "must have" technology and should be implemented as soon as possible. The risk that hostile intelligence is collecting encrypted data and expects future decryption using the capabilities of quantum computers is real, high-risk, and present [162], and this applies to military, intelligence, and government sectors, as well as industries or academia that exchange or store classified and confidential data. The current trend is to start preparing the infrastructure for implementing quantum cryptographic flexibility when certified (standardized) post-quantum cryptography is ready to be deployed [90, 156].
New quantum flexibility algorithms can provide not only a new mathematical approach that is difficult enough even for quantum computers, but also a new paradigm for handling encrypted data. For example, fully homomorphic encryptio (FHE) allows data to never be decrypted - even if they are being processed [163]. While security applications, such as genomic data, medical records or financial information are of the highest interest, intelligence, military or governmental applications are also evident. Therefore, FHE is a good candidate for a secure cloud-based quantum computing approach [164].
Note that post-quantum ciphers should be implemented in the Internet of Things (IoT) or the Internet of Military Things (IoMT) [165] as a fast growing field with many potential security vulnerabilities, for an overview of post-quantum ciphers for the IoT, see [166].
Quantum key distribution (QKD) [160, 167, 168] is another new feature that allows secure cryptographic key exchange with mathematically proven security. Although it is not possible to eavesdrop on the quantum carrier of quantum data (keys), weaknesses can be found at end nodes and trusted relays due to imperfect hardware or software implementations. Another issue is the cost, if the solution is based on fiber optics or utilizes quantum satellites, independently considering quantum data throughput, security and non-quantum alternatives.QKD solutions seem to be more popular in the EU [169], while post-quantum encryption solutions are more popular in the US [170].
The last caveat refers to the Quantum Random Number Generator (QRNG). the QRNG improves security [171] and rejects attacks on pseudo-random number generators [172].
5.1.2 Quantum Attack Capabilities
With Shor's quantum cryptanalysis-based public key encryption algorithms (PKE), such as RSA, DH, and ECC, an attacker can decrypt previously collected encrypted data. There is no accurate prediction of when the so-called "Q-Day", i.e., the day when quantum computers break 2048-bit RSA encryption, will occur. However, the general opinion is that it will take about 10-15 years (based on a survey in 2017) [173]. Similar threats apply to most Message Authentication Codes (MACs) and Authenticated Encryption of Associated Data (AEADs) such as HMAC-CBC and AES-GCM due to Simon's algorithm and overlay queries.
One has to assume that such offensive actions already exist or are under intensive research. 10 years from now, the most sensitive communications or subjects of interest will use post-quantum ciphers or QKDs implemented in the next 6 years. this means that when quantum computers capable of cracking PKE are available, most security-sensitive data will use quantum security solutions.
Theoretically, Grover's algorithm weakens symmetric key encryption algorithms; such as DES and AES. however, quantum computing, especially quantum memory, is in such great demand that it seems infeasible in the next decades [174].
Another means of attack is the classical hacking method using classical computers, which will still lag behind quantum technologies. In general, quantum technology is a young technology field and many new software for the control of quantum systems are under development. New software and hardware often have more vulnerabilities and security holes. For example, QKD quantum satellites currently controlled by classical computers working as trusted relays may be ideal targets for cyber attacks. Moreover, specific physics-based attack vectors against quantum networks (e.g., QKD) are the subject of active research [175], such as photon number splitting [81] or Trojan horse attacks [82], and future surprises are not excluded. For an overview of quantum hacking, see e.g. [157].
5.2 Quantum computing capabilities
Key point.
Quantum computing power will increase with the number of logical quantum bits.
Most likely, quantum computing will be used as part of a hybrid cloud.
Small embedded quantum computing systems are ideal for direct quantum data processing.
They are typically used for quantum optimization, ML/AI enhancement and faster numerical simulations.
Quantum computing will introduce new capabilities to current classical computing services to help solve highly complex computational problems. Moreover, in addition to the quantum simulations mentioned above, quantum computing includes quantum optimization, machine learning and artificial intelligence (ML/AI) enhancements, quantum data analysis, and faster numerical modeling [11, 24]. Recent military problems that can be solved by quantum computers are presented in [10], such as battlefield or war simulation; radio spectrum analysis; logistics management; supply chain optimization; energy management; and predictive maintenance.
In order to obtain the most efficient results, future quantum computing will be implemented in computing fields alongside classical computers, which will create a hybrid system where a hybrid quantum classical operating system will use ML/AI to analyze the tasks to be computed and split the separate computations into resources such as CPUs, GPUs, FPGAs, or quantum processors (QPUs), where the best and fastest results.
For example, it is doubtful that a small embedded quantum computer could be installed in a self-driving car or a mobile command center. The current state-of-the-art quantum bit designs require cryogenic cooling. Therefore, more effort should be focused on other quantum bit designs, such as photons, spins, or NV color centers, which can operate at room temperature. Embedded quantum chips can perform simple analytical tasks or be used for simple operations associated with quantum network applications that require direct quantum data processing. However, machine learning and model optimization for autonomous systems and robotics can also benefit from "large" quantum computers.
Quantum computing may be effective in optimization problems [10, 176, 177]. In the military domain, examples of quantum optimization could be overseas operations and deployments, mission planning, war exercises, system validation and verification, and the design of new vehicles and their properties such as stealth or agility. At the top would be applications for enhanced decision making, supporting military operations and functions through quantum information science, including predictive analytics and ML/AI [178]. Specifically, quantum annealers have already proven themselves in verifying and validating software code for complex systems [179, 180].
Quantum computers are expected to play an important role in command and control (C2) systems, whose role is to analyze and provide situational awareness or assist in planning and surveillance, including simulating various possible scenarios to provide the best conditions for optimal decision making. Quantum computers can improve and accelerate scenario simulation or process and analyze big data from ISR (intelligence, surveillance, and reconnaissance) to enhance situational awareness. This also includes the involvement of quantum-enhanced machine learning and quantum sensors and imaging.
Quantum information processing may be critical to intelligence, surveillance and reconnaissance (ISR) or situational awareness. ISR will benefit from quantum computing, which greatly improves the ability to filter, decode, correlate and identify signals and images captured by ISR. In particular, quantum image processing is an area of extensive interest and development. It is expected that quantum image analysis and pattern detection using neural networks [13] will contribute to situational awareness and understanding in the near future.
Quantum computing will enhance classical machine learning and artificial intelligence [54], including defense applications [178]. Here, quantum computing will certainly not actually perform the complete machine learning process. Nevertheless, quantum computing can improve ML/AI mechanisms (e.g., quantum sampling, linear algebra, quantum neural networks). A recent study [181] showed that quantum machine learning provides advantages only for some kernels (kernels) that are suitable for specific problems. Theoretically, quantum computing has the potential to enhance most classical AI applications in the defense domain, e.g., automated network operations, algorithmic localization, situational awareness and understanding, and automated mission planning [182, 183]. The most immediate application of quantum ML/AI may be quantum data, for example, generated by quantum sensing or measurement instruments [55]. The practical applicability will grow with the growth of quantum computer resources, and within eight years quantum ML/AI could be one of the important quantum computing applications [184]. This applicability can be accelerated by hybrid classical-quantum machine learning, where tensor network models can be implemented on small near-term quantum devices [185].
With quantum neural networks, quantum computers are expected to provide better pattern recognition and higher speedups. This may be essential, for example, in bionetwork defense systems that protect networks, similar to the immune system of biological organisms [13].
Moreover, through faster linear algebraic solutions (see 3.2.5), quantum computing has the potential to improve the current numerical modeling based on linear equations in the defense sector, such as warfare simulations, radar cross-section calculations, stealth design modeling, etc.
In the long term, quantum systems can enable Network Quantum Enabling Capabilities (NQEC) [13].NQEC is a future system that allows communication and sharing of information between forces and commanders over networks for rapid response to battlefield developments and coordination. Quantum augmentation can lead to secure communications, enhanced situational awareness and understanding, remote quantum sensor output fusion and processing, and improved C2.
5.3 Quantum Communication Networks
Key points.
Various security applications (e.g., QKD, identification and authentication, digital signatures).
The adoption of security applications will occur rapidly with careful exploration of the security aspects of all new technologies.
Quantum clock synchronization allows the use of higher precision quantum clocks.
The quantum Internet is the most efficient way to communicate between quantum computers and/or quantum clouds.
The quantum Internet represents a quantum network with a variety of services [186] that have important, not just security, implications. However, many advanced quantum communication network applications require quantum entanglement; that is, they require quantum repeaters and quantum switches. Recall that trusted repeaters can only be used for QKD (see Section 3.3.1). Future combinations of fiber optic and free space channels will interconnect various end nodes such as drones, aircraft, ships, vehicles, soldiers, command centers, etc.
5.3.1 Security Applications
Quantum key distribution is one of the most mature applications of quantum networks. When remote communication using MDI-QKD or quantum repeaters becomes possible, this technology will be of interest to the defense sector. Basic commercial technologies using trusted repeaters are currently available, and these pioneers can serve as examples of how quantum technology can be applied. Here, QKD claims that this technology is the most secure and a growing number of use cases are emerging, especially in the financial and medical sectors. On the other hand, numerous recommendation reports and authorities are more cautious; for example, the UK National Cyber Security Centre [187] does not support QKD in its current state for any government or military applications.
In addition to distribution-only key QKD, quantum networks can be used for quantum secure direct communication (QSDC) between space, special forces, air force, navy, and army assets [188-191]. Here, quantum data encryption of direct messages utilizes QKD-like security. One obstacle may be the low quantum bit rate, which would allow sending only simple messages, but not audio-visual and complex telemetry data. In this case, the network switches to the QKD protocol to distribute the keys and the encrypted data will be distributed over the classical channel. Other protocols such as Quantum Talk [192] and Quantum Direct Secret Sharing [193] aim to use quantum networks as QSDCs in provably secure communications. Note that QKD and QSDC are considered to be an inherent part of 6G wireless communication networks and are discussed accordingly in [194].
Another important contribution of quantum methods to security is quantum digital signature (QDS) [195]. qds provides security against tampering of messages by the sender after signing them.
Next, quantum secure identification exploits quantum properties that allow identification without revealing authentication credentials [72].
Another application is location-based quantum cryptography [196, 197]. Location-based quantum cryptography can provide more secure communications in which the information accessed can only be obtained from a specific geographical location, for example, only from a specific military base communicating with a military satellite. Location-based quantum cryptography can also provide secure communication when the geographical location of a party is its only credential.
5.3.2 Technology Applications
Quantum networks will perform network clock synchronization [71, 198], which is already a major topic in classical digital networks. Clock synchronization aims at coordinating other independent clocks, in particular atomic clocks (e.g. in GPS) and local digital clocks (e.g. in digital computers). Especially when deploying quantum clocks, quantum networks using quantum entanglement will achieve more precise synchronization, (for time standards and frequency transmission, see Section 5.4). Otherwise, the high precision of quantum clocks can only be used locally. Accurate clock synchronization is essential for the cooperation of C4ISR (Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance) systems to precisely synchronize various data and operations in radar, electronic warfare, command centers, weapons systems, etc.
A short note introduces blind quantum computing [69, 70]. Such quantum protocols allow quantum programs to run on remote quantum computers or quantum computing clouds and retrieve the results without the owner knowing what the algorithms or results are. This is valuable when covert computation is required (e.g., for military operations planning or new weapons technology design) and no quantum computer capability of its own is available.
Distributed quantum computing connected via quantum networks - see Section 3.3.1. For military and government actors with quantum computers, it will be important to build high-performance quantum computing services or quantum clouds.
Quantum networks capable of distributing entanglement can integrate and entangle quantum sensors [77] to improve sensor sensitivity, reduce errors, and most importantly, make global measurements. This provides advantages in cases where the parameter of interest is a global property of the entire network, for example, when the arrival angle of a signal needs to be measured from three sensors, each measuring a signal with a specific amplitude and phase, and then the output of each sensor can be used to estimate the arrival angle of the signal, which can be globally evaluated by quantum entangled sensors, a process that can be improved by machine learning [ 78].
Quantum protocols for distributed computing protocols [76] can have favorable military applications for a swarm of drones, or for a swarm of autonomous vehicles (AVs). Here, quantum protocols can help to achieve consistency among all AVs on the same time scale, independent of their number. However, open-space quantum communication between all fast-moving AVs will be a challenge that must be addressed first. Note that recently successful experiments on unmanned quantum entanglement distribution have been performed [64].
5.4 Quantum PNT
Key point.
All quantum PNT techniques require highly accurate quantum clocks.
The accuracy of quantum inertial navigation may be several orders of magnitude higher than that of conventional navigation.
Quantum inertial navigation can be extended by quantum enhanced navigation using quantum magnetic or gravity mapping.
Promising quantum navigation based on Earth's magnetic field anomalies.
Quantum technologies are expected to significantly improve positioning, navigation and timing (PNT) systems, especially inertial navigation. Time standard and frequency transfer (TFT) is a fundamental service that provides precise timing for communications, metrology, and the global navigation satellite system (GNSS). Although current TFT systems are mature, the performance of optical atomic clocks or quantum clocks combined with TFTs using quantum networks [199, 200] will keep pace with the growing needs of current applications (communication, GNSS, financial sector, radar, electronic warfare systems) and enable new applications (quantum sensing and imaging).
Quantum-based technologies and methods support the development of PNT-sensitive precision instruments. The quantum advantage will be seen in GPS failures or challenging operational environments that enable precision operations. Examples of such environments include underwater and underground, or under GPS jamming.
Current global navigation satellite systems (GPS, GLONASS, Galileo, Compass, etc.) rely on precise timing provided by multiple atomic clocks on individual satellites that are calibrated by more stable atomic clocks on the ground, and the greater accuracy of quantum clocks will also improve positioning and navigation accuracy. In the long term, GNSS satellites should be connected to the quantum Internet for time distribution and clock synchronization, and chip-sized precision moving clocks could help detect GNSS spoofing [201].
Some quantum GNSS (not only quantum clocks) have been considered and studied; for example, the interferometric quantum positioning system (QPS) [199, 202, 203]. one of the schemes of QPS [202, 203] has a similar structure to the conventional GNSS, where there are three baselines, each consisting of two LEO satellites with perpendicular baselines to each other. However, although the theoretical positioning accuracy is impressive, extensive engineering must be performed to design a realistic QPS.
Most current navigation relies on GPS, or GNSS in general, which is the most accurate navigation technology. GNSS technology is susceptible to interference, spoofing or lack of GPS in environments such as densely populated areas with high electromagnetic spectrum usage. And for underground or underwater environments, GNSS technology is simply not available. The solution is inertial navigation.
The problem with classical inertial navigation is drift, which degrades accuracy over time. For example, marine-grade inertial navigation (for ships, submarines, and spacecraft) has a drift of 1.8 km/day, and navigation-grade inertial navigation (for military aircraft) has a drift of 1.5 km/h [204].In 2014, DARPA launched an MTO-PTN project with the goal of achieving a drift of 20 m and 1 m/h [205]. Even so, some have high expectations that quantum inertial navigation will have an error of only about a few hundred meters per month [5, 206].
A full quantum inertial navigation system consists of a quantum gyroscope, an accelerometer, and an atomic clock/quantum clock. Although the individual sensors required for quantum inertial navigation are tested outside the laboratory, creating a full quantum inertial measurement unit is still challenging. For navigation on highly mobile platforms, the sensors require fast measurement rates of hundreds of Hz or increased measurement bandwidth of quantum sensors [204, 207]. The key component most in need of improvement is the low-drift rotational sensor, on which classical inertial sensors are based on various principles [208]. A common chip-size technology is MEMS (microelectromechanical systems) technology, and MEMS gyroscopes exhibit instabilities at the ~10-7 rad.s-1 level and are suitable for military applications [99]. The best current cold-atom gyroscopes have an instability limit of ~10-9-10-10 rad.s-1 (integration time of 1000s) [209]. There are uncertainties in the accuracy of field-deployable quantum sensors compared to the accuracy of current laboratory experiments. An intermediate step between classical and quantum inertial navigation could be a hybrid system fusing classical and quantum accelerometer outputs [210]. As the size of quantum inertial navigation devices decreases to chip size, it is expected that it can be deployed on smaller vehicles, especially driverless autonomous vehicles or missiles. However, the degree of miniaturization we can achieve is unknown, and there are many questions about chip-sized quantum inertial navigation.
Individual components such as gyroscopes or accelerometers are also currently being tested on various platforms; for example, on aircraft [211] or, more recently, on [212].
For many years, the National Oceanic and Atmospheric Administration (NOAA) has been mapping and producing magnetic anomaly maps of the Earth, and the use of sensitive quantum magnetometers in combination with magnetic anomaly maps of the Earth is another way to achieve quantum non-GNSS navigation [213, 214].
Gravity map matching [215] works similarly and can be used to improve performance using quantum gravimeters. Quantum gravimeters together with magnetometers can be the basis for underwater quantum-enhanced navigation, especially in submarine canyons, folded seabeds, or coastal environments.
Overall, quantum inertial or augmented navigation has great potential because GPS, infrared or radar navigation is not required, and it is less susceptible to interference and less vulnerable to electronic warfare attacks. However, the statement "no GPS required" is not very accurate, these systems always require some external input at the initial position, most likely from GNSS.
5.5 Quantum ISTAR
Key point.
Extensive use of quantum computing to collect and process information.
Hopefully deployed on LEO satellites, but resolution is questionable.
Widely used for subsea operations.
Expected to perform advanced subsurface surveillance, with uncertain resolution.
New 3D, low light or low signal-to-noise ratio quantum vision devices.
ISTAR (Intelligence, Surveillance, Target Search and Reconnaissance) is a key capability for modern military precision operations, and quantum technology has the potential to greatly improve situational awareness on the multi-domain battlefield.
Overall, a huge impact can be expected from quantum computing, which will help to acquire new intelligence data, process big data from surveillance and reconnaissance, and identify targets using quantum ML/AI [178, 183].
In addition to the processing part of ISTAR, quantum sensing installed on individual land/sea/aircraft and LEO satellites is expected to make great advances.
Quantum gravimeters and gravity gradiometers with high accuracy can improve or introduce new applications: geophysical studies, seismology, archaeology, mineral (fissile materials or precious metals) and oil detection, subsurface scanning and precise georeferencing and topographic mapping (e.g. sea bed for underwater navigation) [7].
Another important type of sensing is the quantum magnetometer. The applications of quantum magnetometers partially overlap with those of quantum gravimetry, thus introducing new applications: the Earth's magnetic field, including local magnetic anomalies caused by metallic objects (submarines, mines, etc.), or weak biomagnetic signals (mainly for medical purposes) [7].
A third area of interest for ISTAR is quantum imaging. Quantum imaging offers a large number of different applications; for example, quantum radar (see Section 5.7), medical imaging devices, 3D cameras, stealth rangefinders, etc.
Section 5.2 describes the potential applications of quantum computing in ISR and situational awareness.
5.5.1 Surface and Subsurface Surveillance for Quantum Earth
Quantum sensing based on first-level magnetometry, gravimetry and gravity gradiometry helps to study the subsurface variations of continents and seas, including their natural origin. Magnetic anomalies and gravity sensing provide different images of the Earth's surface, which is very heterogeneous (oceans, rocks, caves, metallic minerals, etc.), including huge human-built structures or vehicles that produce unique gravity (depending on mass) and magnetic (depending on metallic composition) footprints.
The quantum sensing techniques discussed - magnetic measurements, gravimetry, and gravity gradient measurements - can achieve very high accuracy, at least in the laboratory. For example, the accuracy of absolute gravity measurements outside the laboratory is about 1 μGal (10 nm.s^-2) [216]. Note that a sensitivity of 3.1 μGal corresponds to a sensitivity per centimeter of height above the Earth's surface. However, the problem is that spatial resolution is usually inversely correlated with sensitivity (higher sensitivity comes at the cost of lower spatial resolution, and vice versa). Spatial resolution and sensitivity are key attributes in determining what to identify (large-scale natural variability or small subsurface structures) and from what distance (from ground, UAV, or satellite-based measurements), e.g., the current spatial resolution is about 100 km [217] for satellite-based gravity gradiometers, about 16 km for radar satellite altimeters [218], and about 5 km [219]. For more information, see [5].
For many quantum sensing applications, placement of sensors on low Earth orbit (LEO) satellites is essential [220]. However, the current sensitivity and spatial resolution only allow applications for Earth monitoring (mapping resources such as water or oil, earthquake or tsunami detection).
In addition to LEO satellites, the aforementioned quantum sensors have been considered for deployment on airborne, maritime or ground vehicle platforms. Today, quantum sensing experiments are performed outside of laboratory environments, such as in trucks [221], drones and aircraft [222, 223], or on ships [217]. For example, quantum gravimeters can be mounted on drones to search for man-made structures, such as tunnels used for drug smuggling [223]. Installing quantum sensing devices on an unmanned aircraft (possibly an unmanned aircraft (UAV), an unmanned surface vessel (USV), a remotely operated vehicle (ROV), or an unmanned underwater vessel (UUV)) requires additional engineering to achieve optimal sensitivity, resolution, and operability simultaneously.
Low-resolution quantum sensing can be used for precise georeferencing and terrain mapping to aid in underwater navigation or mission planning in rugged terrain. In addition, the detection of new minerals and oil fields may become a new center of interest, especially on the seafloor [224], although in most cases the boundaries are well defined, which may be a source of international friction.
Many reports and articles [7, 225, 228-231] consider high-resolution quantum magnetic and gravity sensing [217, 225-227] as capable of: detecting camouflaged vehicles or aircraft; efficiently searching fleets or individual vessels from LEOs; detecting subsurface structures such as caves, tunnels, underground bunkers, research facilities, and missile silos; locate buried unexploded objects (mines, underwater mines, and improvised explosive devices); and enable through-wall detection of rotating machinery.
However, note again that it is very uncertain where the technical limitations lie and whether the mentioned applications of quantum gravimetry and magnetometry will achieve the sensitivity and resolution (especially in low Earth orbit) to realize all the above ideas. Quantum sensors will be brought to the market in several generations, each with better sensitivity and resolution and lower SWaP, allowing a wider range of deployments and applications.
5.5.2 Quantum Imaging Systems
In addition to quantum radar and lidar (see Section 5.7), quantum imaging has other military-relevant applications. iSTAR uses all-weather, day/night tactical sensing technology to exploit the characteristics and advantages of EO/IR/THz/RF frequencies for long-range/short-range, active/passive, and stealth/stealth. Quantum imaging systems can use a variety of techniques and quantum protocols; for example, SPAD, quantum resonance imaging, subscattered particle noise imaging, or quantum illumination, as described in Section 3.4.4. In general, constructing small-scale quantum imaging systems is not a problem; the key parameters are the flux of single-photon/entangled photon emitters or the single-photon detection resolution and sensitivity. In addition, large-scale deployment of quantum imaging systems with high photon fluxes requires powerful processing power, which may limit the system's deployment capability and performance.
Quantum 3D cameras using quantum entanglement and photon number correlation would introduce fast 3D imaging with unprecedented depth of focus and low noise aimed at subscattered particle noise or remote performance, a capability that could be used to inspect and detect deviations or structural cracks in jets, satellites and other sensitive military technologies. Long-range 3D imaging from UAVs can be used for reconnaissance and exploration of mission destinations or enemy facilities and equipment.
Another commercial technology is the quantum gas sensor [232]. Technically, this is a single-photon quantum lidar that is calibrated to detect methane leaks, and the next ready product is a multi-gas detector capable of detecting carbon dioxide (CO2), which, with appropriate modifications and calibration, could also be used for human detection.
A specific feature of proximity is visibility behind corners or out of sight [126]. These methods are useful to locate and retrieve trapped persons, hostages or to improve automated driving by detecting vehicles coming around corners.
Quantum imaging can be advantageous as a low-light or low signal-to-noise vision device, for example, in murky water, fog, dust, smoke, jungle foliage, or nighttime environments. Low signal-to-noise ratio quantum imaging facilitates target detection, classification and identification using low signal-to-noise ratio or hidden visible features, and has the potential to counter enemy camouflage or other target deception techniques. Quantum imaging will be very useful when helicopter pilots land in dusty, foggy or smoky environments [9].
An important product is the quantum rangefinder [233, 234], a conventional rangefinder that uses a bright laser that is easily detected by the target. When observed from the target, quantum rangefinders are not distinguishable from the background in time and spectrum. In other words, a quantum rangefinder would be invisible, including at night, while a classical rangefinder could be seen by the target or by others.
In some cases, quantum ghost imaging can play the role of quantum lidar [235], especially when the target does not move or moves very slowly and 3D imaging requires depth of focus.
5.6 Quantum electronic warfare
Key point.
Enhance current electronic warfare with smaller general-purpose quantum antennas, precision timing, and advanced RF spectrum analyzers.
Problems with quantum channel detection.
When quantum channels are targeted, several types of attacks are considered and developed.
Quantum electronic warfare can be divided into quantum-enhanced classical electronic warfare and quantum electronic warfare that focuses on adversarial, anti-adversarial, and pro-adversarial quantum channels. A quantum channel is the transmission of photons carrying quantum information for the quantum Internet, quantum radar, or another quantum system using free space or fiber optic channels.
Classical electronic warfare systems used for electronic support measures can benefit from quantum antennas. Quantum antennas based on Riedberg atoms can provide small dimensions independent of the wavelength (frequency) of the measured signal [122, 123]. This means that even for low frequency (MHz to kHz [124, 236]) signal interception, quantum antennas of a few microns are sufficient. There can be quantum antenna arrays for multi-frequency measurements with different bandwidths or one antenna that dynamically changes the bandwidth according to the interest. In addition, antennas based on Riedberg atoms can measure AM and FM signals, provide self-calibration, measure weak and very strong fields, and detect angles of arrival [125]. In the future, quantum antennas may look like an array (matrix) of Reedeburg atoms, where different cells can measure different signals and, in a joint measurement of two or more cells, the angle of arrival of the signal can be determined; the weakest aspect of such antennas is the low temperature required to cool the Reedeburg atoms, which needs to be reduced to an acceptable size. Overall, quantum RF sensors are key enablers for advanced LPD/LPI communications, over-the-horizon directional RF, immunity to RF interference, RF direction finding, or RF terahertz imaging. For example, arrays of quantum RF sensors were developed as a potential upgrade for the fighter F-35 [237].
Classical electronic warfare can also benefit from quantum computing by providing improved RF spectrum analyzers for electronic warfare, where quantum optimization and quantum ML/AI techniques can be applied. Higher efficiency can be achieved by directly processing and analyzing quantum data from quantum RF sensors (Riedberg atoms, NV color centers) [55], where the impact of quantum computers may be more significant. In addition, other quantum-based solutions and methods are under development, such as NV color-center-based RF spectrum analysis or SHB-based rainbow analyzers [238].
Current electronic warfare systems would also benefit from quantum timing, which could enhance signals intelligence, anti-DRFM (digital RF memory), and other electronic warfare systems that require precise timing; for example, anti-radar jamming capabilities.
Another area of quantum electronic warfare will be signals intelligence (SIGINT) and communications intelligence (COMINT) (detection, interception, identification, localization) and quantum electronic attack (jamming, deception, use of direct energy weapons). Quantum channels (for quantum communication or quantum imaging) have specific characteristics; first, simple signal interception is problematic because quantum data are carried by individual quanta and their interception is easily detected; second, typical quantum imaging techniques use low signal-to-noise ratios, which means that identifying signals and noise without additional knowledge is a challenge; third, coherent signals that are typically used as photons resemble very focused lasers, and finding such a quantum signal without knowing the location of at least one side is very challenging. These properties make classical electronic warfare obsolete and invisible to the quantum channel.
This situation is difficult even for potential quantum electronic warfare systems, since the possibility of detecting the presence of quantum (free-space) channels remains a question, which would require the development of quantum simulations of laser warning receivers [239]. For quantum electronic warfare, it is crucial for Intel to know the location of one or both sides using quantum channels.
Classical electronic warfare will intercept and eavesdrop in a free-space classical channel. However, in a quantum channel this would be detected quickly. One possible attack is a man-in-the-middle type of attack [240, 241], as early quantum network parties may have problems with authentication or trusted relays. Other types of attacks are at the quantum physics level, for example, photon number splitting attacks rely on the use of coherent laser pulses for quantum channels [81] or Trojan horse attacks [82], or the collection and detection of scattered light [242]. However, these types of attacks are very complex and their practicality (e.g., in space) is uncertain.
5.5.2 Quantum Imaging Systems
In addition to quantum radar and lidar (see Section 5.7), quantum imaging has other military-relevant applications. iSTAR uses all-weather, day/night tactical sensing technology to exploit the characteristics and advantages of EO/IR/THz/RF frequencies for long-range/short-range, active/passive, and stealth/stealth. Quantum imaging systems can use a variety of techniques and quantum protocols; for example, SPAD, quantum resonance imaging, subscattered particle noise imaging, or quantum illumination, as described in Section 3.4.4. In general, constructing small-scale quantum imaging systems is not a problem; the key parameters are the flux of single-photon/entangled photon emitters or the single-photon detection resolution and sensitivity. In addition, large-scale deployment of quantum imaging systems with high photon fluxes requires powerful processing power, which may limit the system's deployment capability and performance.
Quantum 3D cameras using quantum entanglement and photon number correlation would introduce fast 3D imaging with unprecedented depth of focus and low noise aimed at subscattered particle noise or remote performance, a capability that could be used to inspect and detect deviations or structural cracks in jets, satellites and other sensitive military technologies. Long-range 3D imaging from UAVs can be used for reconnaissance and exploration of mission destinations or enemy facilities and equipment.
Another commercial technology is the quantum gas sensor [232]. Technically, this is a single-photon quantum lidar that is calibrated to detect methane leaks, and the next ready product is a multi-gas detector capable of detecting carbon dioxide (CO2), which, with appropriate modifications and calibration, could also be used for human detection.
A specific feature of proximity is visibility behind corners or out of sight [126]. These methods are useful to locate and retrieve trapped persons, hostages or to improve automated driving by detecting vehicles coming around corners.
Quantum imaging can be advantageous as a low-light or low signal-to-noise vision device, for example, in murky water, fog, dust, smoke, jungle foliage, or nighttime environments. Low signal-to-noise ratio quantum imaging facilitates target detection, classification and identification using low signal-to-noise ratio or hidden visible features, and has the potential to counter enemy camouflage or other target deception techniques. Quantum imaging will be very useful when helicopter pilots land in dusty, foggy or smoky environments [9].
An important product is the quantum rangefinder [233, 234], a conventional rangefinder that uses a bright laser that is easily detected by the target. When observed from the target, quantum rangefinders are not distinguishable from the background in time and spectrum. In other words, a quantum rangefinder would be invisible, including at night, while a classical rangefinder could be seen by the target or by others.
In some cases, quantum ghost imaging can play the role of quantum lidar [235], especially when the target does not move or moves very slowly and 3D imaging requires depth of focus.
5.6 Quantum electronic warfare
Key point.
Enhance current electronic warfare with smaller general-purpose quantum antennas, precision timing, and advanced RF spectrum analyzers.
Problems with quantum channel detection.
When quantum channels are targeted, several types of attacks are considered and developed.
Quantum electronic warfare can be divided into quantum-enhanced classical electronic warfare and quantum electronic warfare that focuses on adversarial, anti-adversarial, and pro-adversarial quantum channels. A quantum channel is the transmission of photons carrying quantum information for the quantum Internet, quantum radar, or another quantum system using free space or fiber optic channels.
Classical electronic warfare systems used for electronic support measures can benefit from quantum antennas. Quantum antennas based on Riedberg atoms can provide small dimensions independent of the wavelength (frequency) of the measured signal [122, 123]. This means that even for low frequency (MHz to kHz [124, 236]) signal interception, quantum antennas of a few microns are sufficient. There can be quantum antenna arrays for multi-frequency measurements with different bandwidths or one antenna that dynamically changes the bandwidth according to the interest. In addition, antennas based on Riedberg atoms can measure AM and FM signals, provide self-calibration, measure weak and very strong fields, and detect angles of arrival [125]. In the future, quantum antennas may look like an array (matrix) of Reedeburg atoms, where different cells can measure different signals and, in a joint measurement of two or more cells, the angle of arrival of the signal can be determined; the weakest aspect of such antennas is the low temperature required to cool the Reedeburg atoms, which needs to be reduced to an acceptable size. Overall, quantum RF sensors are key enablers for advanced LPD/LPI communications, over-the-horizon directional RF, immunity to RF interference, RF direction finding, or RF terahertz imaging. For example, arrays of quantum RF sensors were developed as a potential upgrade for the fighter F-35 [237].
Classical electronic warfare can also benefit from quantum computing by providing improved RF spectrum analyzers for electronic warfare, where quantum optimization and quantum ML/AI techniques can be applied. Higher efficiency can be achieved by directly processing and analyzing quantum data from quantum RF sensors (Riedberg atoms, NV color centers) [55], where the impact of quantum computers may be more significant. In addition, other quantum-based solutions and methods are under development, such as NV color-center-based RF spectrum analysis or SHB-based rainbow analyzers [238].
Current electronic warfare systems would also benefit from quantum timing, which could enhance signals intelligence, anti-DRFM (digital RF memory), and other electronic warfare systems that require precise timing; for example, anti-radar jamming capabilities.
Another area of quantum electronic warfare will be signals intelligence (SIGINT) and communications intelligence (COMINT) (detection, interception, identification, localization) and quantum electronic attack (jamming, deception, use of direct energy weapons). Quantum channels (for quantum communication or quantum imaging) have specific characteristics; first, simple signal interception is problematic because quantum data are carried by individual quanta and their interception is easily detected; second, typical quantum imaging techniques use low signal-to-noise ratios, which means that identifying signals and noise without additional knowledge is a challenge; third, coherent signals that are typically used as photons resemble very focused lasers, and finding such a quantum signal without knowing the location of at least one side is very challenging. These properties make classical electronic warfare obsolete and invisible to the quantum channel.
This situation is difficult even for potential quantum electronic warfare systems, since the possibility of detecting the presence of quantum (free-space) channels remains a question, which would require the development of quantum simulations of laser warning receivers [239]. For quantum electronic warfare, it is crucial for Intel to know the location of one or both sides using quantum channels.
Classical electronic warfare will intercept and eavesdrop in a free-space classical channel. However, in a quantum channel this would be detected quickly. One possible attack is a man-in-the-middle type of attack [240, 241], as early quantum network parties may have problems with authentication or trusted relays. Other types of attacks are at the quantum physics level, for example, photon number splitting attacks rely on the use of coherent laser pulses for quantum channels [81] or Trojan horse attacks [82], or the collection and detection of scattered light [242]. However, these types of attacks are very complex and their practicality (e.g., in space) is uncertain.
5.8 Quantum Underwater War
Key Point.
Submarines may be among the first adopters of quantum inertial navigation.
Quantum magnetometers as the primary tool for detecting submarines or underwater mines.
Quantum technology could provide significant disruption to underwater warfare through enhanced magnetic detection of submarines or underwater mines, new inertial submarine navigation, and quantum-enhanced precision sonar. In general, sensing technologies based on quantum photodetectors, radar, lidar, magnetometers or gravimeters can be applied in the marine environment [257]. For an overview of the near-infallible impact of quantum technologies on nuclear-armed submarines, see [261].
Submarines and other underwater delivery vehicles would benefit from quantum inertial navigation. Large submarines may be among the first adopters of quantum inertial navigation because they can be fitted with larger quantum devices, including cryogenic cooling. In addition, sensitive quantum magnetometers and gravimeters could help map the surrounding environment, such as submarine canyons, icebergs and folded seabeds, without the use of easily detectable sonar. Another example of inertial navigation that is particularly well suited for underwater Arctic navigation is quantum imaging [262].
The basic tool for ASW may be the quantum magnetometer. Researchers expect that, in particular, SQUID magnetometers can detect submarines up to 6 km away while also improving noise rejection [263, 264]. Note that current classical magnetic anomaly detectors are usually mounted on helicopters or aircraft and have a range of only a few hundred meters. Quantum magnetometer arrays along the coast can cover important areas, resulting in inaccessibility to submarines. In addition, quantum magnetometer arrays appear to work better with more suppressed noise.
Quantum magnetometers can also be used to detect underwater mines, for example using unmanned underwater vessels [230].
However, Section 5.5.1 focuses on detection range, sensitivity, etc., where other technologies in the underwater domain such as sonar are able to detect longer distances [229]. It is also noted in [261] that quantum technology has little impact on SSBNs (ballistic missile submarines). Quantum magnetometers have the potential to work with other sensors to help detect, identify, and classify targets [229].
5.9 Quantum space warfare
Key point.
Important for long-range quantum communication.
Near Earth orbit is important for the future deployment of quantum sensing and imaging technologies.
Space warfare will lead to the deployment of new quantum radar/lidar and quantum electronic warfare technologies in space.
The space domain is becoming increasingly important and will be an important battleground for developed countries. Space used to be used primarily for satellite navigation, mapping, communications, and surveillance, often for military purposes. Today, space is becoming increasingly weaponized [265], for example, by placing satellites with laser weapons or kamikazes in Earth orbit, and anti-satellite warfare is developing in parallel. Another problem that has proliferated is the amount of space junk, with an estimated 2,200 satellites and several plans already announced [266].
Space will also be the key to applying quantum sensing and communication technologies [267-271] to satellites as well as also space confrontation.
For many of the aforementioned quantum technology applications, it is desirable to place quantum sensing technologies such as quantum gravimeters, gravity gradiometers or magnetometers on satellites in Earth orbit, especially low orbit satellites. Such applications are under development, for example, a low-power quantum gravity sensing device that could be deployed in space on small satellites to accurately map resources or to help assess the impact of natural disasters [272]. However, such applications do not require too high a spatial resolution. The same applies to satellite-based quantum imaging, for example, China claims to have developed a satellite using ghost imaging [273], however, its spatial resolution is uncertain and quantum ghost imaging has the advantage that it can be used in cloudy or foggy weather or at night.
On the other hand, the use of satellites for quantum communication has been demonstrated [62, 274]. Satellite-based quantum communication is essential for near-term integrated quantum networks over long distances [275],Current quantum communication satellites, face the same problems as trusted repeaters for fiber optic channels. In fact, current quantum satellites are trusted repeaters, and the problem with trusted repeaters is that they open the door to possible cyber attacks on the satellite control system. In contrast, the MDI-QKD protocol currently demonstrated has better security [276], where the central point works as a repeater or switch, but in a secure state, followed by the use of a quantum repeater. For an overview of quantum communication in space, see [270, 271].
A new required military capability will be the technology to detect other satellites, space objects, space junk and track them. Classical radars are used for this purpose, e.g., the Space Fence project as part of the U.S. space surveillance network. However, most of these space surveillance radars suffer from a size of about 10 cm or less [266] (in the case of Space Fence, the minimum size is about 5 cm), and another problem is the capacity, i.e., how many objects they can track, as is the case with most space junk that is only a few centimeters in size. Quantum or LIDAR is considered as an alternative to classical radar [6, 257, 259]. Especially in the space environment, quantum radar in the optical domain is used [259] because photons do not suffer losses as they do in the atmosphere. Space quantum radar has most of the advantages of quantum radar, including stealth, as described in Section 5.7. According to simulations [259], the detection sensitivity and target tracking sensitivity of space quantum radar is at least an order of magnitude higher in space compared to GEODSS (ground-based electro-optical deep space surveillance). Space quantum radar will be very useful to track small, dark and fast objects such as satellites, space junk or meteoroids.
The increasing number of quantum sensing and communication devices in space will lead to an increased interest in quantum electronic warfare, as described in Section 5.6.
5.10 Chemical and Biological Simulation and Detection
Key points.
200 quantum bits are sufficient to perform chemical quantum simulation studies.
The ability to implement more complex simulations increases with the number of logical quantum bits.
Chemical detection in air or samples.
Suitable for detection of explosives and chemical warfare agents.
Military and national laboratories, chemical defense industry or CBRN (Chemical, Biological, Radiological and Nuclear) defense forces are interested in defense-related chemical and biological simulations. Research on new drugs and chemicals based on quantum simulations will require advanced quantum computers, classical computing equipment, and quantum chemistry experts. Quantum simulations of chemical and biological chemical warfare agents have in principle the same requirements as civilian research, such as protein folding, nitrogen fixation, and peptide research already underway.
The number of required quantum bits depends on the number of spatial basis functions (various basis sets exist, such as STO-3G, 6-31G, or cc-pVTZ); for example, on the basis of 6-31G, benzene and caffeine molecules can be approximated with approximately 140 and 340 quantum bits, respectively. [278]. Then, sarin molecule simulations require about 250 quantum bits. According to the quantum computer roadmap [27, 279] and the requirement of logical quantum bits, one can reach 100 logical quantum bits within 10 years, but may achieve more efficient error correction and error resistant quantum bits sooner, which is sufficient for molecular simulations of moderate size.
The threat may be to design and accurately simulate the structure and chemical properties of new small and medium-sized molecules that may play a role similar to that of chemical warfare agents such as cyanide, phosgene, cyanogen chloride, sarin or Yperit. On the other hand, the same knowledge can be used for CBRN countermeasures and the development of new detection techniques.
Studies on protein folding, DNA and RNA exploration, such as motif identification, genome-wide association studies and ab initio structure prediction [280], may also influence the study of biological agents [281]. However, more detailed studies are needed to assess the real threat of quantum simulations.
Quantum cascade laser photoacoustic detection is an effective chemical detector. For example, quantum chemical detectors can detect TNT and triacetone triperoxide elements used in improvised explosive devices (IEDs), which are common weapons in asymmetric conflicts, and the same acetone detection systems can be used to identify boarding baggage and passengers carrying explosives. Quantum chemical detection can generally be used against chemical warfare agents or toxic industrial chemicals [282, 283].
In the medium to long term, such detectors could be installed on in autonomous drones or ground vehicles used to inspect an area [284].
5.11 New material design
Key points.
General research implications; for example, room temperature superconductivity allows high precision SQUID magnetometers to operate without cooling, which can have a significant impact on military quantum technology applications.
Defense industry research on camouflage, stealth, superhard armor, or high temperature resistant materials.
Modern science develops new materials, metamaterials, sometimes called quantum materials, by exploiting quantum mechanical properties (e.g. graphene, topological insulators). Materials that act as quantum systems can be simulated with quantum computers, such as the electronic structure of materials, and can be applied to room temperature superconductors, better batteries, and improvements in specific material properties.
To explain in more detail, room-temperature superconducting materials exploit superconductivity at high temperatures [285], which would allow the construction of Josephson junctions, commonly used as building blocks for SQUID or superconducting quantum bits. So far, cooling close to absolute zero has been required. A quantum computer of about 70 logical quantum bits [286] is expected to be sufficient for basic research on high-temperature superconductors.
For the defense industry, opportunities to study new materials, such as better camouflage, stealth (electromagnetic absorption), superhard armor or high temperature resistant material designs, are under consideration, but no details were revealed.
5.12 Brain imaging and human-machine interfaces
Key Points.
Quantum brain magnetic imaging
Enhanced human-machine interface
Magneto-encephalography (magneto-encephalography) scanners are medical imaging systems that visualize what the brain is doing by measuring the magnetic fields generated by currents flowing through collections of neurons. For example, quantum magnetometers based on light-pumped magnetometers [287] can generate high-resolution magnetoencephalography for real-time brain activity imaging, a technique that is safe and non-invasive and has been tested in the laboratory.
In the near future, quantum magnetoencephalography could be part of a soldier's helmet for continuous telemedical monitoring and diagnosis in case of injury. Long-term expectations include enhanced human-machine interfaces, i.e., practical non-invasive cognitive communication with machines and autonomous systems [11].
Many of the military applications of quantum technology mentioned above sound very optimistic, and some are taken from various reports and newspaper or magazine articles in which the authors may have overestimated the transfer of quantum technology from the laboratory to the battlefield or were influenced by quantum technology hype [288]. Avoiding exaggerated expectations is particularly important when the topic involves national security or defense.
The above-mentioned military applications of quantum technologies are based on the latest research in the public domain and are supplemented by various reports, newspaper or magazine articles about defense applications. Since there is no publicly available information on these technologies, no critical opinion is offered on the feasibility of several of these technologies. In these cases, the reader should be more cautious and discerning until more detailed research is available.
Large defense companies and national defense laboratories have had quantum research and development programs for many years, however, only some detailed information is publicly communicated.
For many of the quantum technologies mentioned, only laboratory proofs of concept have been provided to date. The decisive factors in determining whether quantum technologies can be widely used outside the laboratory are component miniaturization and sensitivity to interference, improvements that cannot be made at the expense of sensitivity, resolution, and functionality, and another decisive factor in actual deployment is the price of the technology.
In summary, given the advances in quantum technology research and support systems, such as the miniaturization of lasers and cryogenic cooling over the past few years, there is reason to be optimistic rather than pessimistic (from the perspective of military or government actors) about the future military applications of quantum technology. We need to carefully consider the actual capabilities in operational deployments to see if they meet the requirements and if the price/performance ratio is sufficient to justify the acquisition and deployment.
The development, acquisition, and deployment of quantum technologies for military applications will pose new challenges. The concept of quantum warfare will place new demands on military strategy, tactics and doctrine, ethics and disarmament activities, and technology implementation and deployment, and research should be conducted to understand the issues, implications, threats, and options arising from the development of quantum technologies, not just military applications.
7.1 Military Consequences and Challenges
Quantum technologies in military applications have the potential to enhance existing capabilities, such as providing more accurate navigation, ultra-secure communications, or advanced ISTAR and computing capabilities. Overall, quantum warfare will require updating, modifying, or creating new military doctrines, military scenarios, and programs to develop and acquire new technologies and weapons for the quantum age.
Until then, technology policies and strategies will need to be developed to address the strategic ambitions of individual participants. For example, national technology policies and strategies should include research, development status, and feasibility studies of national quantum technology resources (universities, laboratories, and companies) and markets, as well as military and security threat and potential assessments.
Monitoring the evolution and adaptation of quantum technologies is essential to avoid technological surprises in neighboring or potentially hostile countries. For some nations, quantum warfare surveillance is essential even if quantum technologies are beyond their financial, research, or technical capabilities. Therefore, all modern militaries should be interested in the possible implications of quantum warfare.
National trade and export policies are also important. For example, the European Union has declared quantum computing to be an emerging technology of global strategic importance and is considering strict access to a research project called Horizon Europe. In addition, China has banned the export of cryptographic technologies, including quantum cryptography.
Another theme is the careful communication with allies about important quantum advantages, particularly in terms of quantum ISTAR and quantum networking capabilities, which could reveal military secrets such as classified documents, nuclear submarine locations or underground facilities. Disruptions in the balance of power can be unsettling to allies as well as neutral or hostile players.
7.2 Peaceful and Ethical Consequences and Challenges
To date, the military applications of quantum technologies described in Section 5 have not introduced new weapons, even though they make existing military technologies more advanced; for example, through the development of more accurate sensing and navigation, new computing capabilities, and stronger information security. However, the question of whether quantum technology, especially for military applications, is good or bad for world peace is relevant.
Various calls for ethical guidelines for quantum computing have emerged, mentioning many ethical issues such as human DNA manipulation and the creation of new materials for warfare and invasive artificial intelligence.
Although quantum technologies will not create new weapons, their improvements to existing military technologies will enhance such capabilities and shorten the time to attack, warn and make decisions. Thus, even while reducing individual risk, quantum technologies can make the use of force more likely, making war more likely.
Preventive arms control of general-purpose dual-use technologies such as quantum technologies will be more difficult because they can also be used for civilian purposes, such as medical quantum sensing. Analogies have been drawn to nanotechnology, and export controls to prevent or slow proliferation and military use by other countries or non-state organizations are the most likely way to try to reduce any threat posed by quantum technologies.
Specifically, quantum computing R&D is very expensive. However, the goal is to develop a technology that can simply and reliably produce quantum bits, which could lead to cheaper, more widely distributed, and more readily available technology for less skilled participants, a feature of military technology that is about to become problematic.
7.3 Technical Consequences and Challenges
There are many technical and technological challenges to translating a successful laboratory proof of concept into a true "external" application, such as miniaturization and interoperability, but not at the expense of laboratory-implemented sensitivity and resolution, in addition to other related technical challenges.
One of these challenges may be the quantum workforce. The quantum workforce does not need to consist of physicists or scientists with PhDs, however, they should be quantum engineers with knowledge of quantum information science and an overview of quantum technologies, able to understand and capable of processing and evaluating output data from quantum sensors, computers and communications. There is an existing quantum ecosystem that is continuing to grow and this ecosystem will require an increasing quantum workforce. This will require training and educating new quantum engineers and specialists, meaning that more and more universities are offering quantum courses and more and more students are taking quantum courses. In addition, it will be more difficult to get these people to work in the military, so the fundamentals of quantum information and quantum technology should also be part of the curriculum of the military academies where quantum technology will be deployed in modern armies.
Another technical challenge is the huge volume of data. Quantum technologies, with all the quantum sensors, quantum imaging, quantum communications and computing, will generate huge amounts of classical and quantum data that will increase the requirements for data transmission, processing and evaluation, which should be considered when planning C4ISR and quantum infrastructure.
The final challenge will be standardization. The standardization process is important for the interoperability of devices produced by different manufacturers. In addition to harmonizing interfaces and communication protocols, the standardization process can also include security verification, for example in the post-quantum cryptographic standardization process. In the case of quantum networks, where various connected devices (e.g. nodes, repeaters, switches, fibre channels and open space channels) are to be expected, it is important to develop and implement some standards that allow successful transmission of quantum information.
Quantum technology is an emerging field of technology that uses the manipulation and control of individual quanta for a variety of potentially disruptive applications, many of which are dual-use or used directly for military purposes. However, individual quantum technologies, from TRL 1 (observed fundamentals) to TRL 6 (technology demonstrated in a relevant environment), are being used for military purposes in technical research laboratories.
Quantum technologies for military applications will not only provide improved and new capabilities, but will also require the development of new strategies, tactics, and policies, the assessment of threats to global peace and security, and the identification of ethical and moral issues, all of which are referred to as "quantum warfare.
In this report, various quantum technologies are described for different TRLs, focusing on possible applications or deployments in the defense sector. Since the transition from laboratory to real-world applications has not yet been implemented or is ongoing, precise predictions of quantum technology deployment are not possible, raising questions such as whether we can come up with a solution that offers real quantum advantages over classical systems that are often much cheaper and often already in use. While the description of possible military applications of quantum technology sounds very optimistic, one should be wary of quantum hype and focus on the challenges of practical deployment of quantum technology in military applications.
Quantum technology promises to have a strategic, long-range impact. However, the likelihood of technological surprises affecting military and defense forces is quite low, and the best way to avoid surprises is to develop knowledge of quantum technology and monitor its development and employment. A cautious approach to quantum technology will serve as quantum insurance.
Original report：
https://epjquantumtechnology.springeropen.com/articles/10.1140/epjqt/s40507-021-00113-y#
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