Quantum technology will be a game changer for defense

Quantum computing, a groundbreaking technology based on the principles of quantum mechanics, has enormous potential to transform several fields, and the military is no exception: it promises to deliver exponential computing power that will revolutionize military operations and redefine the battlefield of the future.

 

According to EPJ Quantum Technology's report, Quantum technology for military applications, military applications of quantum technology will include land, air, space, electronic, cyber, and underwater warfare, as well as ISTAR - Intelligence, Surveillance, Targeted Search and Reconnaissance. Intelligence, surveillance, target search and reconnaissance and other multi-faceted, omni-directional areas.

 

Now, the U.S. defense frequently put forward quantum-related strategies, increase the financial budget; the British Ministry of Defense is also working with commercial companies to explore quantum technology is defense applications. As of June 2023, a total of 11 countries (U.S., Canada, U.K., Germany, Denmark, Sweden, the Netherlands, China, India, Japan, Australia, and South Korea) and the European Union have issued more than 40 quantum-related policies, which include 20 national strategic policies, 16 funding programs, and 4 inter-country cooperation policies.

 

As more and more countries recognize the military potential of quantum computing, a new arms race may ensue, raising serious geopolitical and security concerns.

 

While fourth-generation modern warfare is characterized by decentralization and the loss of the state's monopoly on war, the militaries of developed countries typically have access to state-of-the-art military technology - and this includes the emergence of quantum technology.

 

Quantum technology (QT) refers to technologies that stem primarily from the second quantum revolution. Previously, the first quantum revolution brought about technologies we are familiar with today, such as nuclear power, semiconductors, lasers, magnetic resonance imaging, modern communications technology, or digital cameras and other imaging devices. The first quantum technologies gave rise to nuclear weapons and energy; then, classical computers were given an important role. Currently, laser weapons are being implemented and tested.

 

The second quantum revolution is characterized by the manipulation and control of individual quantum systems (e.g., atoms, ions, electrons, photons, molecules, or quasiparticles of various kinds) so as to reach the standard quantum limit; that is, the limit of the precision of measurements at the quantum scale.

 

Quantum technology in this article 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, precision, computational power, and efficiency of current and future military technologies. Most quantum technologies are typically dual-use. Thus, quantum technology's have tremendous potential for military applications.

 

The military implications of quantum computing are far-reaching. As the technology matures, quantum systems could make a huge difference to national defense and warfare, from secure communications to advanced detection and navigation. However, the quantum leap must be approached with caution, as it brings great opportunities along with new complexities and potential risks.

 

Right now, different quantum technologies and their applications are at different stages of development (TRL), with their maturity ranging from TRL1 (e.g., certain types of quantum bits) to TRL8 (e.g., quantum key distribution).

 

Quantum computing refers to the use of quantum information science to perform calculations, and such machines can be referred to as quantum computers, which are very complex to categorize.

 

- Digital quantum computers (also known as gate-level quantum computers) are general-purpose, programmable, can perform all possible quantum algorithms, and have many of the applications described below. Classical computers can fully emulate gate-level based quantum computers. The difference is in resources and speed. For example, simulating fully entangled quantum bits exponentially increases the demand on classical resources. This means that ≥45 quantum bits are nearly impossible to simulate on a classical (super) computer.

 

- Analog quantum computers (also known as Hamiltonian volume computation) are typically implemented using quantum annealing (as a noisy version of adiabatic quantum computation). Quantum annealers differ from digital quantum computers in the finite connectivity of quantum bits and different principles. As a result, the 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 in the study of quantum systems and the simulation of other come 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 an unprogrammable quantum circuit.

 

Overall, quantum computing will not replace classical computing. Quantum computers are only applicable to a limited type of problems, usually highly complex ones. The actual deployment of quantum computing applications depends on the quality (coherence, error resistance, gate fidelity) and the number of quantum bits. Some of the 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 applying quantum gates on a single quantum bit is known as a quantum circuit. Quantum circuits are practical implementations of quantum algorithms.

 

Quantum computers can be divided into three evolutionary stages: component quantum computing (CQC), noisy intermediate scale quantum computing (NISQ), and fault-tolerant quantum computing (FTQC).The CQC stage consists of the demonstration of quantum computation and the maturation of the basic elements.The computational power of the CQC is very limited, but sufficient to demonstrate some of the principles.The NISQ stage of the quantum computers should have a sufficient number of quantum bits to demonstrate the advantages of quantum computing. Continued research should increase the number and quality of quantum bits. The FTQC phase begins when a perfect logical quantum bit is reached.

 

Physical quantum bits can be realized by many quantum systems. The latest advances are quantum computers based on superconducting quantum bits and imprisoned ion quantum bits at or near the NISQ stage. All other technologies, such as cold atoms, topology, electron spins, photons, or quantum bits based on NV color centers, are still at the CQC stage or theoretical stage. Individual quantum computers and their performances are very different (e.g., speed, coherence time, possibility of entangling all quantum bits, gate fidelity). Various metrics and benchmarks, such as the quantum volume metric, have been developed for their comparison.

 

The common problem with all types of quantum bits is their mass. Quantum bits are very fragile and have a finite coherence time (a time scale on which no quantum information is lost). Each operation performed on a quantum bit has finite fidelity. Therefore, researchers need to use error-correcting codes. Error correction for quantum bits is much more complex than for classical bits because quantum bits cannot be copied, as explained by the non-clonability theorem.

 

There are two types of quantum bits: physical quantum bits, which are realized by a physical quantum system, and logical quantum bits, which consist of a number of physical quantum bits and an error-correcting code. 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.

 

The difference between analog and digital quantum computers is 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 annealing machines). Thus, the applicability of analog quantum computers is limited.

 

In fact, most of the tasks accomplished by quantum computers are merely subroutines or subroutines of classical computer programs. Classical programs not only control quantum computers, but also provide a large number of computations that are not possible on quantum computers. This includes recent applications of quantum simulations in chemistry, such as the use of variational quantum eigen solvers (VQEs) - a hybrid combination of classical and quantum computation. In addition, quantum computers are large machines, many of which require cryogenics. As a result, it is unlikely that most customers will purchase personal quantum computers in the coming decades, but rather access them as cloud services.

 

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 shed light on quantum hegemony, advantage and practicality (SUPREME, 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 more theoretical than practical. Quantum dominance refers to situations in which a quantum computer is able to solve real-world problems that a classical computer cannot. Quantum utility is similar to quantum advantage, with the only difference being that quantum computers solve real-world problems faster than classical computers.

 

2) Quantum simulation

 

Long before the first quantum computers, the main task of quantum computers was to simulate other quantum systems, and molecules are one such quantum system. Despite the increased computational power available, complete simulations of simpler molecules, or larger molecules at the cost of many approximations and simplifications, are only possible using current computational chemistry. For example, for a system with n electrons, a classical computer requires 2n bits to describe the state of the electrons, whereas 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 predominant approaches: quantum phase estimation and quantum variational techniques (VQE).

 

Algorithms for quantum chemical 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 deal of interest 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) Quantum cryptanalysis

 

One of the most famous quantum computer applications is the exponentially accelerated factorization of large prime numbers via the Shor algorithm. This is a threat to public-key cryptosystems, such as RSA, DH and ECC, based on large prime multiplication, discrete logarithmic problems, or schemes based on elliptic curve discrete logarithmic problems, which are considered to be computationally intractable or very difficult for classical computers.

 

While 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, adversaries or foreign intelligence agencies can intercept and store encrypted traffic. Because many secrets take far longer to decrypt than the expected timeline delivered 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 halves key security against brute-force attacks; a 256-bit AES key can be strongly cracked in about 2,128 quantum operations. Doubling the length of symmetric keys is recommended, despite the massive resources required for quantum computers. Moreover, Simon's algorithm and superposition queries can completely break most message authentication codes (MACs), as well as authenticated encryption of associated data (AEAD), such as HMAC-CBC and AES-GCM.

 

In addition, cryptanalytic attacks on symmetric key systems have been actively studied based on the structure present in symmetric cryptosystems, which can provide up to super-polynomial speedups. However, these algorithms are too demanding on the resources of quantum computers.

 

4) Quantum search and quantum walking

 

One of the best-known search quantum algorithms is the Grover algorithm, which provides squared speedups in database searches or usually in inverse functions. For unordered lists or databases, the complexity of the classical search algorithm is 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 in the analysis of so-called big data (unstructured data). Processing large amounts of data requires large quantum memories. However, there are no reliable quantum memories that can store 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 searching algorithmically generated data is currently considered feasible.

 

An alternative search method could be based on a quantum random walk mechanism, which provides a similar speedup to Grover's algorithm.

 

5) Quantum Optimization

 

Considering the possibility of solving NP complex problems, quantum optimization is a very active topic of exploration. An example of such an NP problem is the traveler's 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 a solution close to it.

 

Quantum computing introduces a new perspective on this problem and offers different approaches and techniques. Currently the most prominent methods are based on variational methods such as the Quantum Approximate Optimization Algorithm (QAOA).Part of QAOA is a subtechnique called Quadratic Unconstrained Binary Optimization (QUBO), which is also suitable for simulating quantum computers. Other methods are quantum simulation with least squares fitting or semidefinite planning.

 

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. The new paradigm introduced by quantum computing has led to new quantum-inspired classical algorithms, such as QAOA without quantum speedups. on the other hand, we can say that quantum-inspired algorithms are the first practical results of quantum computing.

 

For quantum optimization, there have been many demonstrations, use cases and proofs of concept, especially in analog quantum computing, which currently provides the most quantum computing resources for such applications. Typical demonstrations are optimizations for transportation, logistics or financial industries.

 

6) Quantum Linear Algebra

 

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) algorithm for sparse matrices. However, the estimated speedup depends on the size of the problem (matrix) and also on the large resource requirements, which are impractical for some problems. On the other hand, for example, for a system of linear equations with 10,000 parameters, 10,000 steps are required to solve it, 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, being statistical in nature, approximate solutions may be sufficient.

 

Note that the HHL algorithm proved to be a generalized algorithm for quantum computation and has been shown to be suitable for a variety of applications such as k-mean clustering, support vector machines, data fitting, etc.

 

A major caveat for quantum algorithms dealing with large amounts of input data is data loading. Classical data, especially binary data or bits, needs to be converted into a quantum state 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.

 

7) Quantum machine learning and artificial intelligence

 

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 one cannot expect full quantum ML/AI given the very low efficiency of processing classical data, and even more so if one takes into account 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. Another situation arises when ML/AI is applied to quantum data; for example, quantum sensors or imaging.

 

However, it is possible to introduce quantum-enhanced ML/AI, where quantum computation improves some machine learning tasks such as quantum sampling, linear algebra (where machine learning is about working with complex vectors in high-dimensional linear spaces) or quantum neural networks such as quantum support vector machines.

 

Indeed, the ML/AI topic covers a wide range of techniques and approaches, and it is not different from quantum computing. Quantum ML/AI or quantum-enhanced ML/AI is the subject of many research efforts today.

 

8) Quantum Networks

 

The goal of quantum networks (sometimes called quantum internet or quantum information networks (QIN)) is to transmit quantum information over a variety of channels through a variety of technologies. Quantum information (quantum bits) is typically carried by individual photons, making quantum information transmission fragile. In addition, many quantum network applications rely on quantum entanglement.

 

Commonly used channels for quantum information transmission are dedicated low-loss optical fibers or the current higher-loss telecom 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 distance, where components such as quantum repeaters or quantum switches are required. Note that very small (one quantum bit) quantum processors are sufficient for most quantum network applications.

 

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 commonly considered and realized scenario for quantum networking is the use of quantum satellites. The advantage of satellites is that optical-photonic communication can be utilized to transmit quantum information, where the loss in the satellite-terrestrial link is lower than the loss between two terrestrial nodes that are far apart. However, photon communication over short distances in free-space channels can be realized by, for example, drones. The best method is to use the microwave spectrum used for classical wireless communication. However, communication using the microwave spectrum at the level of individual photons is more challenging. Microwave single photon technology has greater difficulties in generating and detecting individual photons. Another problem is the noisy environment in 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 in a similar way to an amplifier in a classical optical network, but needs to obey the non-clonability theorem. In fact, a quantum repeater allows to entangle the quantum bits of the end nodes. When two end nodes are entangled, the effect of quantum invisible state transfer can be utilized. This means that quantum information can be transmitted without physically sending photons; 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 required. However, there is no reliable and practical quantum memory yet.

 

Quantum networks will work in parallel with classical networks because not all transmitted information needs to be encoded with quantum information. For example, quantum invisible state transfer requires parallel classical networks, and quantum networks can be used for the following applications:

 

- Quantum key distribution (QKD), secure transmission of encryption 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 allows a quantum algorithm to be transmitted to a quantum computer, perform the computation and retrieve the result without the owner or eavesdropper knowing what the algorithm or result is;

- Network clock synchronization;

- Secure identification,allowing identification without revealing authentication credentials;

- Quantum positional verification allowing verification of another party's position;

- Distributed quantum computation of multiple quantum computers allowing computation of tasks as a single quantum computer;

- consensus and protocol tasks.

......

 

Quantum networks allow direct secure quantum communication between quantum computers where quantum data can be exchanged directly. Primarily when a huge task can be divided into smaller tasks, this helps to efficiently redistribute computational tasks based on the performance of a single quantum computer. Another example is a quantum cloud, where quantum data can be shared between multiple quantum computers.

 

It is also questionable whether a standalone high-performance quantum computer can be built. It is more likely to be realized through distributed quantum computing, in which many quantum computers would be connected through a quantum network.

 

9)       Quantum Key Distribution

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 non-clonability 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 and the other on the E91 (Ekert 1991) protocol. The dominant BB84 protocol is technically simpler, but requires the generation of quantum random numbers and the provider must prepare the key prior to distribution. Protocol E91 utilizes 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 of quantum entanglement is more challenging. Both types of protocols are information-theoretically secure.

 

Theoretically, QKDs are 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 bugs in the control software, imperfect single-photon sources, authentication problems for all parties, and so on. This is a very active research area.

 

In addition to trusted repeaters, another weakness is that quantum bit transmission rates are too slow to distribute long keys. A new single-photon source with a high transmission rate 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.

 

10) Post-quantum cryptography

 

Post-quantum cryptography (sometimes referred to as quantum proof, quantum security, or anti-quantum cryptography) represents an area of cryptography that is resistant to future quantum computer attacks. 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 quantum computer attacks.

 

Nowadays, there are several methods that are considered quantum-resistant. Examples include lattice-based ciphers, hyper-singular elliptic curve homology ciphers, hash-based ciphers, multivariate-based ciphers, code-based ciphers, and quantum-resistant symmetric keys.

 

Unlike QKD, all these algorithms are not provably secure from a mathematical point of view. Therefore, during the standardization process, all these algorithms are rigorously tested and analyzed, including implementations. There is no worst-case scenario in which a classical computer can break a flawed quantum-resistant algorithm in the implementation. The standardization effort that has received the most attention is that of the National Institute of Standards and Technology (NIST): the NIST standardization process is expected to conclude in 2023-2024. Regardless, a growing number of commercial vendors are now offering new anti-quantum cryptographic solutions.

 

11) Quantum random number generators

 

Random number generators (RNGs) are essential for many applications, such as Monte Carlo simulation and integration, cryptographic operations, statistics, and computer games. However, the RNG in classical computers, which is not truly random because it is deterministic, is known as pseudo-random number generation. However, for many applications, pseudo-RNG is sufficient.

 

On the other hand, generating strong keys is a cornerstone of security and can only be achieved with a true random number generator. One solution is a hardware-based quantum random number generator (QRNG). Furthermore, 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. One of the advantages of a quantum random number generator, unlike other RNGs, is that it can be verified and authenticated.

 

12) Quantum electric, magnetic and inertial force sensing

 

Many of the sensing quantum techniques are generalized to measure a variety of physical quantities. A detailed description of each technique 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 technologies.

 

Currently, the most promising techniques are: atomic vapor, cold atom interferometry, nitrogen-vacancy color centers, superconducting circuits, and trapped ions.

 

13) Quantum Clocks

 

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 "ticks" when changing energy levels.

 

Various clock technologies have their own challenges, such as precise frequency combs, laser systems for control and cooling, and blackbody radiation offsets (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.

 

Precision 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 critical for quantum technologies, especially for quantum sensing and imaging. For example, a very high-precision clock could enable new measurements such as centimeter-scale gravitational potential measurements on the Earth's surface or the search for new physics.

 

14) Quantum RF antennas

 

Radio frequency (RF) antennas are used as receivers or transmitters of various signals. They can be simple dipole antennas or complex AESA modules. Their size is limited by the wavelength of the signal being generated or received. For example, a 3 GHz signal has a wavelength of 10 cm, and the size of the antenna should be no smaller than about 1/3 of that wavelength.This is known as the Chu-Harrington limit.

 

The technology of the Rydberg Atom can break this limit and have an antenna with a size of a few micrometers independent of the wavelength of the received signal. Rydberg atoms are highly excited state atoms with correspondingly large electric dipole moments and are therefore highly sensitive to external electric fields.

 

The latest prototype of the Rydberg Atom Analyzer was demonstrated in the frequency range from 0 to 20 GHz for AM or FM radio, WiFi and Bluetooth signals. More combinations of antennas allow detection of the angle of arrival of the signal. At the laboratory level, the Riedelberg Atom technology has been commercialized.

 

Quantum RF receivers as single units (for target frequencies, narrow bandwidth) or as array sensors (wide frequency range) can be used in navigation, active imaging (radar), telecommunications, media receivers or passive THz imaging.

 

15)       Quantum imaging systems

 

Quantum imaging systems are a vast field covering 3D quantum cameras, behind-the-corner cameras, low-luminance imaging and quantum radar or lidar.

 

Single Photon Avalanche Detectors (SPAD) arrays are very sensitive single-photon detectors that are 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. SPADs can then be placed in an array to work like a 3D camera.SPADs operate in the spectrum extending into the near-infrared.

 

SPAD arrays can also be used to detect objects beyond detection (e.g. hidden behind corners). 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 corners, where photons can be reflected back 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.

 

Quantum ghost imaging, also known as conformal imaging or two-photon imaging, is a technique that permits imaging of objects beyond the camera's line of sight. In a light source, two entangled photons, each with a different frequency, are created, 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, where the reflected photons are detected by a single-photon detector (a so-called "bucket" detector), and an image is created based on the correlation between the two photons. The image is then created based on the correlation between the two photons. Despite the poor resolution, the ghost imaging protocol has also been demonstrated without quantum entanglement (using classical correlations).

 

Sub-shot-noise imaging is another quantum optics 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 lasers, a limit that can be overcome by using correlated photons, a "pilot" or "auxiliary" photon. The detection of a "pilot" or "auxiliary" photon indicates the presence of a correlated photon that detects the object or environment.

 

Quantum Illumination (QI) is a quantum protocol that uses two correlated (entangled) photons to detect a target. One "idle" photon is retained and the other, called the "signal" photon, is sent to the target and reflected, and both photons are measured. The advantages of this protocol remain even when the entanglement is corrupted by lossy and noisy environments.The QI protocol is one of the protocols mainly applicable to quantum radar, but it can also be applied to medical imaging or quantum communications.

 

16) Quantum Radar Technology

 

In principle, quantum radar works in a similar way to classical radar, i.e. the signal has to be sent towards the target and the radar system has to wait for the reflected signal. However, theoretically improved accuracy and new capabilities can be realized through quantum mechanical methods.

 

Several protocols have been considered for quantum radar, such as interferometric quantum radar, quantum illumination (QI), hybrid quantum radar or Maccone-Ren quantum radar. None of the above protocols are perfect. For example, interferometric quantum radar is too sensitive to noise and needs to maintain quantum entanglement.QI is an ideal protocol for noisy environments and has even been laboratory-validated in the microwave spectrum, but it needs to know the distance to the target, and therefore it does not have ranging capabilities. However, QI-based quantum target ranging methods are under development. 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 still maintains the dominant term 1/R4, where R is the radar-target distance. As a result, the number of entangled photons (modes) required is orders of magnitude higher than currently available. In a sense, quantum radar is similar to noise radar with many common properties such as interception probability, low detection probability, and effective spectrum sharing.

 

Another related challenge is finding targets. Theoretical work has shown that quantum entanglement can outperform any classical strategy in finding the unknown location of a target. In addition, the method can be used as a quantum-enhanced frequency scanner within a fixed target range.

 

17) Other sensors and technologies

 

Using photoacoustic detection, quantum technology can be used for ultra-precise sound sensing up to the level of phonons, which are quasi-particles that quantize sound waves in solid matter through photoacoustic detection. Precise detection of sound waves is essential for many applications, including medical diagnostics, sonar, navigation, trace gas sensing and industrial processes.

 

Photoacoustic detection can be combined with quantum cascade lasers for gas or general chemical detection. Quantum cascade lasers (QCLs) are a well-established technology, QCLs are semiconductor lasers that emit in the mid-wave and long-wave infrared bands and, like many other quantum technologies, require cooling to well below -70°C, however, recent developments allow chip-scale implementations to be implemented at temperatures of approximately -23°C, which can be achieved with portable cooling systems.

 

Military technologies have higher requirements than industrial or public applications. Considering possible deployments on the battlefield, this requires more caution.

 

It 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 that 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 for military deployment.

 

In the long run, we can expect advantages in terms of reduced SWaP (size, weight, and power) and expansion of quantum computers and quantum networks, which will make deployment easier, and may be necessary if nations/military forces want to compete with others for edge (quantum) technologies.

 

1) Quantum Strategy

 

Prospective users of military quantum technologies will have to carefully consider if, where and when to invest their time and resources. The goal of the defense forces is not to develop military technology, but usually just to identify specific requirements and procurements. However, especially if they are the end users, they can be heavily involved in the development.

 

As a basis, it would be desirable to have a national quantum ecosystem of industry and academic institutions, which should be generally supported at the governmental level, i.e., the development of a national quantum plan, but also incentivized to develop technologies for the defense sector, which could be achieved through appropriate grant funding or even a variety of thematic challenges, in which individuals and startups could participate and perhaps bring new disruptive ideas and solutions, which would 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 specify all subsequent steps, from the identification of loop-breaking quantum solutions, market surveys, technology and risk assessments, and 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 warfighting domain under consideration. This step also includes technical and scientific assessments to balance technical risks (limited deployability, lower-than-expected performance, or inability to transfer from the lab to the battlefield) with the potential advantages of individual quantum technologies. This identification process should be repeated in a cycle 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 (R&D) process. R&D should be adequately supported financially, but 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, new systems at initial operational capability should be ready.

 

The final step is the realization of full operational capability, which includes the modification or creation of new military doctrines and the preparation of new military scenarios, strategies, and tactics that take full advantage of quantum superiority.

 

This last point relates to the identification phase. Here, policymakers also need to take a long-term perspective; so far, many quantum technologies have been considered individually: sensors, quantum key distribution, quantum computation, etc., but the long-term vision contemplates the interconnection of quantum sensors and quantum computation through quantum networks. Theoretical and experimental work has demonstrated additional quantum advantages of utilizing quantum entangled sensors and computers, and more similar applications may be discovered or invented. It is important to consider this when building fiber optic/quantum networks. In the longer term future, existing components such as trusted repeaters could be replaced by full quantum repeaters and switches, thus realizing the full potential of quantum networks.

 

2) Technology maturity and timeframe

 

As has been mentioned several times, various quantum technologies are at different TRLs, ranging from 1 to 8. TRL variations and time horizons are expected to be even more complex when considering various applications and deployment platforms, especially for military purposes.

 

 

Technology maturity level (TRL) and time horizon expectations

 

Actual military deployments may take some time to overcome all technical hurdles and meet military requirements. For example, the first generation of quantum gravimeters for subsurface scanning will likely 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 airplane, which could later be mounted on a drone and possibly on a low-orbit satellite. However, it is also possible that the limits of the sensor will be reached early, making it impossible to deploy, for example on a UAV or LEO satellite.

 

3) Quantum technical countermeasures

 

Quantum technology countermeasures refer to methods and techniques that deceive, disable or disrupt quantum technologies, whether they are quantum computers, quantum networks or quantum sensors and imaging systems, which utilize the quantum physical properties of individual quanta. As such, they are susceptible to environmental disturbances and noise, and therefore have the potential to be spoofed or paralyzed. With regard to quantum networks in particular, and quantum key distribution in particular, quantum hacking has evolved hand in hand with quantum key distribution.

 

Developers of quantum strategies and policymakers should bear in mind that when quantum technologies are deployed in the military sphere, various countermeasures will emerge sooner or later, and that what is unknown at present is the possible effectiveness of quantum technology countermeasures and their impact.

 

 

Schematic of quantum warfare utilizing various quantum technology systems

 

It is important to note that many applications remain more theoretical than real. Significant quantum advances in the lab do not always lead to similar advances outside the lab. 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 particular quantum technologies are made and deployed; the field is still very young and new technological surprises, both good and bad, may bring other quantum advantages or disadvantages.

 

1) Quantum Cybersecurity

 

Key point:

 

- The need for quantum cryptographic flexibility implementation.

- Operations that want to utilize the Shor algorithm should start collecting data of interest before quantum secure cryptography is deployed.

- QKD implementation requires careful consideration.

- The QKD endpoint will be the weakest part of the system.

 

The quantum advantage in cyberwarfare could provide new, but very effective (with exponential speedup) attack vectors for current asymmetric encryption (based on integer decomposition, discrete logarithmic, or elliptic curve discrete logarithmic problems) as well as theoretical symmetric encryption. On the other hand are new quantum resilient encryption algorithms and methods, as well as quantum key distribution.

 

The current trend is also the development and application of machine learning or artificial intelligence in cyber warfare.

 

2) Quantum Defense Capabilities

 

The realization of post-quantum cryptography is a "must-have" technology that should be implemented as soon as possible. The risk that hostile intelligence is collecting encrypted data with the expectation that it will be decrypted in the future using the capabilities of quantum computers is real, high, and existential, and applies to the military, intelligence, and government sectors, as well as to industries or academia that exchange or store classified and secret data. The current trend is to start preparing infrastructures for implementing quantum cryptographic flexibility when certified (standardized) post-quantum cryptography is ready for deployment.

 

New quantum-flexible algorithms may not only provide 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. While security applications such as genomic data, medical records or financial information are the most popular, intelligence, military or governmental applications are also obvious. Therefore, FHE is a good candidate for a cloud-based approach to secure cloud quantum computing.

 

Quantum Key Distribution (QKD) is another new feature that allows secure cryptographic key exchange with mathematically proven security. Although it is not possible to eavesdrop on the quantum carriers of quantum data (keys), weaknesses can be found at the end nodes and trusted repeaters due to imperfect hardware or software implementations. Another issue is the cost, independently considering quantum data throughput, security and non-quantum alternatives if the solution is based on fiber optics or utilizes quantum satellites.QKD solutions seem to be more popular in the EU, while post-quantum encryption solutions are more popular in the US.

 

This last caveat refers to Quantum Random Number Generators (QRNG).QRNG improves security and rejects attacks on pseudo-random number generators.

 

3) Quantum Attack Capabilities

 

With Shor's quantum cryptanalysis-based public key encryption (PKE) algorithms, such as RSA, DH, ECC, an attacker can decrypt previously collected encrypted data. There is no accurate prediction of when the so-called "Q-Day", the day a quantum computer breaks the 2048-bit RSA encryption, will occur. However, the general opinion is that it will take about 10-15 years (based on a 2017 survey).

 

Similar threats apply to most Message Authentication Codes (MACs) and Authenticated Encryption of Associated Data (AEAD), such as HMAC-CBC and AES-GCM, due to the Simon algorithm and overlay queries.

 

One has to assume that such an offensive operation already exists or that intensive research is underway.10 years from now, the most sensitive communications or topics of interest will be using post-quantum ciphers or QKDs that will be implemented within the next six years.This means that when quantum computers capable of cracking PKEs are available, most security-sensitive data will be secured using quantum security solutions.10 years from now, the most sensitive data will be encrypted using post-quantum ciphers or QKDs that will be implemented within the next six years.

 

In theory, the Grover algorithm weakens symmetric key encryption algorithms; such as DES and AES. however, the demand for quantum computing, and in particular quantum memory, is so great that it does not appear to be feasible in the coming decades.

 

Another means of attack is classical hacking methods using classical computers, which will still lag behind quantum technology. Overall, quantum technology is a young field of technology and many new software for controlling quantum systems are being developed. New software and hardware often have more vulnerabilities and security holes. For example, the QKD quantum satellites, which are currently controlled by classical computers working as trusted repeaters, may be ideal targets for cyberattacks.

 

In addition, specific physically-based attack vectors against quantum networks (e.g., QKD) are the subject of active research, such as photon number splitting or Trojan horse attacks, and future surprises cannot be ruled out.

 

4) 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 and help solve highly complex computational problems. Moreover, in addition to the quantum simulations mentioned above, quantum computing also includes quantum optimization, machine learning and artificial intelligence (ML/AI) improvements, quantum data analysis, and faster numerical modeling. Recent military problems that can be solved by quantum computers are presented in, 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 computation will be implemented in computational arenas where it will appear alongside classical computers, which will create a hybrid system where the hybrid quantum classical operating system will analyze the task to be computed using ML/AI and split the separate computation into resources such as CPUs, GPUs, FPGAs, or quantum processors (QPUs), in which the best and fastest results.

 

Quantum computing may be effective in optimization problems. 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 attributes such as stealth or agility. At the top would be applications for enhanced decision making to support military operations and functions through quantum information science, including predictive analytics and ML/AI.Specifically, quantum annealers have already proven themselves in verifying and validating software code for complex systems.

 

Quantum computers are expected to play an important role in Command and Control (C2) systems.The role of C2 systems is to analyze and provide situational awareness or to assist in planning and surveillance, including simulating a variety of possible scenarios to provide the best conditions for optimal decision making. Quantum computers can improve and accelerate scenario simulations or process and analyze big data from ISR (Intelligence, Surveillance and Reconnaissance) to enhance situational awareness. This also includes quantum-enhanced machine learning and the involvement of quantum sensors and imaging.

 

Quantum information processing may be critical for intelligence, surveillance and reconnaissance (ISR) or situational awareness.ISR will benefit from quantum computing, which greatly improves the ability to filter, decode, correlate and recognize signals and images captured by ISR. In particular, quantum image processing is an area of widespread interest and development. It is expected that quantum image analysis and pattern detection using neural networks will contribute to situational awareness and understanding in the near future.

 

Quantum computing will enhance classical machine learning and artificial intelligence, including defense applications. 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).

 

Practical applicability will grow with the resources of quantum computers, and within eight years, quantum ML/AI could be one of the important quantum computing applications. This applicability can be accelerated by hybrid classical-quantum machine learning, where tensor network models can be implemented on small near-term quantum devices.

 

With quantum neural networks, quantum computers are expected to provide better pattern recognition and higher speed. This may be essential, for example, in bionic cyber defense systems that protect the network, similar to the immune system of a biological organism.

 

In addition, through faster linear algebra solving, quantum computing has the potential to improve current numerical modeling in the defense sector based on linear equations, such as war simulations, radar cross-section calculations, and stealth design modeling.

 

In the long term, quantum systems could enable Network Quantum Enabling Capability (NQEC).NQEC is a future system that allows communication and information sharing between units and commanders over a network to rapidly respond to and coordinate battlefield developments. Quantum augmentation can lead to secure communications, enhanced situational awareness and understanding, remote quantum sensor output fusion and processing, and improved C2.

 

5) Quantum Communication Networks

 

Key point:

 

- Various security applications (e.g., QKD, identification and authentication, digital signatures).

- 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.

- Quantum Internet is the most efficient way of communication between quantum computers and/or quantum clouds.

 

The quantum Internet represents a quantum network with a variety of services 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. Future combinations of fiber optics and free-space channels will interconnect a variety of end nodes, such as drones, aircraft, ships, vehicles, soldiers, command centers, and so on.

 

6) Quantum PNT

 

Key Points:

 

- All quantum PNT technologies require highly accurate quantum clocks.

- Quantum inertial navigation may be orders of magnitude more accurate than 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 promise significant improvements in 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). While current TFT systems are mature, the performance of optical atomic clocks or quantum clocks combined with TFTs utilizing quantum networks will keep pace with the growing demands of current applications (communications, 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 realized in GPS-deficient or challenging operational environments, enabling precision operations. Examples of such environments include underwater and underground, or environments under GPS interference.

 

Current global navigation satellite systems (GPS, GLONASS, Galileo, BeiDou, etc.) rely on precise timing provided through multiple atomic clocks on individual satellites that are calibrated by more stable atomic clocks on the ground, and the higher accuracy of quantum clocks will also improve positioning and navigation accuracy. In the long run, 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.

 

Some quantum GNSS (not just quantum clocks) have already been considered and studied; for example, interferometric quantum positioning systems (QPS.) One of the QPS schemes has a structure similar to that of conventional GNSS, where there are three baselines, each consisting of two low-orbiting satellites, and the baselines are perpendicular to each other. However, while the theoretical accuracy of positioning is phenomenal, a great deal of engineering must be done 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 vulnerable to interference, spoofing, or lack of GPS in environments such as densely populated areas with high electromagnetic spectrum utilization. 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/hour.

 

Full quantum inertial navigation systems consist of quantum gyroscopes, accelerometers, and atomic/quantum clocks. Although the individual sensors required for quantum inertial navigation were tested outside the laboratory, creating a complete quantum inertial measurement unit remains challenging. For navigation of highly mobile platforms, the sensors require fast measurement rates of hundreds of Hz or increased measurement bandwidth of the quantum sensors. The key component most in need of improvement is the low-drift rotary sensor, where classical inertial sensors are based on various principles.

 

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. As the size of quantum inertial navigation devices is reduced to the size of a chip, it is expected that it could be deployed in smaller vehicles, especially unmanned self-driving vehicles or missiles. However, the degree of miniaturization we can achieve is unknown, and there are many questions about chip-sized quantum inertial navigation.

 

For many years, the National Oceanic and Atmospheric Administration (NOAA) has been mapping the Earth's magnetic anomalies and producing magnetic anomaly maps, and the use of sensitive quantum magnetometers in conjunction with Earth's magnetic anomaly maps is another way to achieve quantum non-GNSS navigation.

 

Gravitational map matching works in a similar way and can be used with quantum gravimeters to improve performance. Together, quantum gravimeters and 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 it does not require GPS, infrared or radar navigation, and it is less susceptible to jamming and less vulnerable to electronic warfare attacks. However, the term "no GPS" is not quite accurate, and these systems will always require some external input, most likely from GNSS, at the initial position.

 

7) Quantum ISTAR

 

Key Points:

 

- Extensive use of quantum computing to collect and process information.

- Hopes to deploy on LEO satellites, but resolution is questionable.

- Widely used for undersea operations.

- Advanced subsurface surveillance expected, resolution uncertain.

- 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 dramatically improve situational awareness on multi-domain battlefields.

 

Overall, a huge impact can be expected from quantum computing, which will help in acquiring new intelligence data, processing big data from surveillance and reconnaissance, and identifying targets using quantum ML/AI.

 

In addition to the processing component of ISTAR, quantum sensing mounted on individual land/sea/aircraft and LEO satellites is also expected to make great strides.

 

Quantum gravimeters and gravity gradiometers are highly accurate and can improve or introduce new applications: geophysical studies, seismology, archaeology, mineral (fissile material or precious metal) and oil detection, subsurface scanning and precise geo-referencing and topographic mapping (e.g., seabed for underwater navigation).

 

Another important type of sensing is the quantum magnetometer. The applications of quantum magnetometers partially overlap with those of quantum gravity measurements, thus introducing new applications: the Earth's magnetic field, including localized magnetic anomalies induced by metallic objects (submarines, mines, etc.), or weak biomagnetic signals (mainly for medical purposes).

 

A third area of interest for ISTAR is quantum imaging. Quantum imaging offers a large number of different applications; for example, quantum radar, medical imaging devices, 3D cameras, stealth range finders, etc.

 

8) Quantum Electronic Warfare

 

Key point:

 

- Enhancement of current electronic warfare through smaller general-purpose quantum antennas, precision timing, and advanced RF spectrum analyzers.

- Problems with quantum channel detection.

- Several types of attacks are considered and developed when quantum channels are localized.

 

Quantum electronic warfare can be categorized into quantum-enhanced classical electronic warfare and quantum electronic warfare that focuses on countering, countering and supporting countering 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 Rydberg atoms can provide small dimensions independent of the wavelength (frequency) of the measured signal. This means that even for low-frequency (MHz to kHz) signal interception, quantum antennas of a few micrometers are sufficient. There can be arrays of quantum antennas for multi-frequency measurements at different bandwidths, or one antenna with dynamically changing bandwidths depending on the interest. In addition, antennas based on Rydberg atoms can measure AM and FM signals, provide self-calibration, measure weak and very strong fields, and detect angles of arrival.

 

In the future, quantum antennas may look like arrays (matrices) of Rydberg atoms, where different signals can be measured by different cells and the angle of arrival of the signals can be determined in joint measurements of two or more cells.The weakest aspect of such an antenna is the low temperatures required to cool the Rydberg atoms, which need to be scaled down to an acceptable size.

 

Overall, quantum RF sensors are key enablers for advanced LPD/LPI communications, over-the-horizon directional RF, resistance to RF interference, RF direction finding, or RF terahertz imaging. For example, array quantum RF sensors were developed as a potential upgrade for the fighter jet F-35.

 

Classical electronic warfare could also benefit from quantum computing to provide improved RF spectrum analyzers for electronic warfare, where quantum optimization and quantum ML/AI techniques could be applied. Higher efficiency can be achieved by directly processing and analyzing quantum data from quantum RF sensors (Rydberg atoms, NV color centers), where the impact of quantum computers may be more significant. In addition, other quantum-based solutions and methods are being developed, such as RF spectrum analysis based on NV color centers or SHB-based rainbow analyzers.

 

Current electronic warfare systems would also benefit from quantum timing, which could enhance the capabilities of signals intelligence, anti-DRFM (Digital Radio Frequency Memory) and other electronic warfare systems that require precision timing; for example, anti-radar jamming capabilities.

 

Another area of quantum electronic warfare would 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 is carried by individual quanta and their interception is easily detected; second, typical quantum imaging techniques use low signal-to-noise ratios, which means that recognizing signals and noise without additional knowledge is challenging; third, the coherence of signals that is typically used as a photons are similar to very focused lasers, and finding such quantum signals without knowing the position of at least one side is very challenging. These properties make classical electronic warfare obsolete and invisible to quantum channels.

 

This is difficult even for potential quantum electronic warfare systems, as it remains questionable whether it is possible to detect the presence of quantum (free-space) channels, which would require the development of quantum analogs of laser warning receivers. For quantum electronic warfare, it is critical to allow Intel to know the location of one or both sides using the quantum channel.

 

Classical electronic warfare will intercept and eavesdrop in free-space classical channels. However, in a quantum channel this would be detected quickly. One possible attack is a man-in-the-middle type of attack, as early quantum network parties may have problems with authentication or trusted repeaters. Other types of attacks are at the quantum physical level, e.g., photon number splitting attacks that rely on the use of coherent laser pulses for quantum channel or Trojan horse attacks, or the collection and detection of scattered light. However, these types of attacks are very complex and their utility (e.g., in space) is uncertain.

 

A quantum electronic warfare attack is more likely to be simply a denial of service, in which case the quantum channel is intercepted, resulting in the cessation of channel use. Another possibility is that receivers on one or both sides are subjected to complex interference, resulting in loud noise. When the location of the receiver or transmitter is known, another countermeasure to classical electronic warfare is the use of directed energy weapons, such as lasers, resulting in damage or destruction of sensors, an attack that can also help eavesdroppers.

 

Overall, new ways and methods need to be developed to realize the capabilities of quantum electronic warfare and meet the corresponding requirements.

 

9) Quantum Radar and Lidar

 

Key point:

 

- Remote surveillance of quantum radar is not possible using existing quantum microwave technology.

- Possible applications in the field of optics - quantum LIDAR.

- Quantum radar can be used for space warfare.

 

The theoretical advantages and characteristics of quantum radar are significant (some of which depend on separate quantum protocols): higher noise immunity - i.e., better signal-to-noise ratios - higher immunity to jamming and other electronic warfare countermeasures; based on individual photons; i.e., output signal power is so low that it is invisible to electronic warfare measures; target illumination; i.e., a radar that permits identification of targets.

 

Based on a unique set of quantum radar capabilities, it could be a powerfully disruptive technology that could change the rules of modern warfare. Therefore, despite the immaturity of the technology and the many questions about whether quantum radar can be used as a standard primary surveillance radar, international attention is being paid to the subject.

 

In addition, many will immediately visualize quantum radar as a long-range surveillance radar with a range of hundreds of kilometers, an application of quantum radar that seems unlikely. Such an optimal long-range surveillance quantum radar would be very expensive (many orders of magnitude more than the cost of a classical radar at any range), and it would still not realize all the advantages and capabilities described above.

 

In short, the practical problem is that quantum radar is also constrained by the radar equation, where received power is lost as the fourth power of the distance. At the same time, one or fewer photons per mode are required to maintain the quantum advantage. In short, the need to generate relatively high power consisting of low photon modes in the microwave range requires a large number of quantum signal generators, cryogenics, large antennas, and so on. All of this leads to extremely high costs and impractical designs, and scientists need to come up with more practical quantum microwave technologies to overcome these difficulties.

 

In addition to the high price tag, questions remain about the ability to detect stealthy targets or resist jamming. Quantum radar may be beneficial against blocking jammers, but not necessarily against DRFM or other smart jammers. In short, remote surveillance quantum radar is unlikely to be realized even in the long run. In order to achieve this goal, one needs to develop new technologies that allow smaller cryogenic, RF quantum emitters operating at higher temperatures or more efficient cryogenic cooling, and more powerful emitters (high-speed low photon pulses). Note that even if room-temperature superconducting materials were developed, they would not contribute to the Josephson parametric amplifier (JPA) method of entangled microwave photon generation. However, JPA is not the only method of obtaining entangled microwave photons, and future discoveries of new theories and designs for quantum radars are not entirely impossible; the aforementioned long-range surveillance quantum radars are relatively large in size, weight, and power consumption, and it is doubtful that such radars are invisible.

 

Another issue is ranging in the case of quantum illumination (QI) protocols.QI protocols require prior knowledge of the target, and therefore some extension of ranging, either classical or quantum, is needed.

 

For several years, it has been recognized that the quantum radar cross section (RCS) is larger than the classical radar cross section. A new and accurate study of quantum radar cross-sectional area shows that the previously claimed superiority of quantum radar cross-sectional area over classical radar cross-sectional area stems from faulty approximations, and that quantum and classical radar cross-sectional areas currently appear to be comparable.

 

Another approach could be quantum-enhanced noise radar. Noise radar uses a noise waveform as the transmission signal and detection is based on the correlation between the transmission signal and the received radar echo of the noise waveform. The advantage is a low probability of interception (LPI) that is virtually undetectable by today's interception receivers, the design of quantum noise radar requires more research before practical applicability can be seen, however, one potential use here is for microwave applications.

 

However, current theory and research has applications in the field of radar, particularly in the field of radar using optical or near-optical photons, i.e., quantum lidar. Short-range quantum LIDAR can be used for target illumination at short ranges, with single photon imaging experiments being conducted at ranges from 10 km to 45 km, where quantum LIDAR can be used as an anti-drone surveillance radar or as part of a SHORAD (short-range air defense) complex.

 

Space can be another example of a favorable environment for quantum radar/LIDAR, its low noise for the optical domain and it even virtually eliminates decoherence problems in entangled photons. For example, Raytheon is modeling quantum radar in the optical realm of space. The idea is to install a quantum radar on satellites to detect small satellites that are difficult to detect due to their small cross-sectional area, low reflectivity, and poor ambient lighting conditions. Deploying a quantum radar/lidar in a space environment could provide almost all of the advantages listed above.

 

Special mention should be made here of quantum-enhanced radars, whereas classical radars can be equipped with either atomic or quantum clocks, quantum-enhanced radars show high accuracy and low noise, and therefore exhibit advantages in detecting small, slow-moving objects (e.g., drones).

 

10) Quantum Underwater Warfare

 

Key point:

 

- Submarines may be among the first adopters of quantum inertial navigation.

- Quantum magnetometers serve as the primary tool for detecting submarines or underwater mines.

 

Quantum technology could significantly disrupt 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.

 

Submarines and other underwater 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 their surroundings, such as submarine canyons, icebergs, and wrinkled seabeds, without the need for easy-to-detect sonar. Another example of inertial navigation that is particularly suited to underwater Arctic navigation is quantum imaging.

 

A fundamental tool in anti-submarine warfare may be the quantum magnetometer. Researchers anticipate that SQUID magnetometers in particular could detect submarines up to 6 kilometers away, while also improving noise suppression. Note that current classical magnetic anomaly detectors, usually mounted on helicopters or airplanes, have a range of only a few hundred meters. Quantum magnetometer arrays along the coast could cover significant areas, rendering them inaccessible to submarines. In addition, quantum magnetometer arrays appear to work better in situations where noise is more suppressed.

 

Quantum magnetometers could also be used to detect underwater mines, for example, using unmanned underwater vessels.

 

11) Quantum Space Warfare

 

Key point:

 

- Important for long-range quantum communications.

- Near-Earth orbit is important for 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 a key battleground for developed countries. Space used to be used primarily for satellite navigation, mapping, communications and surveillance, usually for military purposes. Today, space is becoming increasingly weaponized, with satellites equipped with laser weapons or kamikaze satellites placed in Earth orbit, and anti-satellite warfare is developing in parallel. Another proliferating problem is the amount of space junk, with an estimated 2,200 satellites and several programs already announced.

 

Space will also be key to applying quantum sensing and communication technologies to satellites as well as also space confrontations.

 

For many of the quantum technology applications mentioned above, it would be 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 being developed, for example, a low-power quantum gravity sensing device that could be deployed in space on small satellites for precise mapping of resources or to help assess the impact of natural disasters.

 

On the other hand, the use of satellites for quantum communications has already been demonstrated. Satellite-based quantum communication is essential for near-term integrated quantum networks over long distances, and current quantum communication satellites face the same problems as trusted repeaters for fiber-optic channels. In fact, today's quantum satellites are trusted repeaters, and the problem with trusted repeaters is that they open the door to possible cyberattacks on satellite control systems. In contrast, the currently demonstrated MDI-QKD protocol offers better security, in which the center point works as a repeater or switch, but in a secure state, followed by the use of a quantum repeater.

 

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, for example, the Space Fence program, which is part of the U.S. space surveillance network. However, most of these space surveillance radars have problems with sizes of about 10 centimeters or less (in the case of Space Fence, the minimum size is about 5 centimeters), and another problem is capacity, i.e., how many objects they can track, which is the case for most space junk that is only a few centimeters in size. Quantum radar or lidar is considered as an alternative to classical radar. Especially in the space environment, quantum radar in the optical domain is used because photons do not suffer losses as they do in the atmosphere. Compared to GEODSS (Ground-based Optical Deep Space Surveillance), the detection sensitivity and target tracking sensitivity of space quantum radar is at least an order of magnitude higher in space. Space quantum radar will be very useful for tracking small, dark and fast objects such as satellites, space junk or meteoroids.

 

The increasing presence of quantum sensing and communication devices in space will lead to increased interest in quantum electronic warfare.

 

Many of the military applications of quantum technology mentioned above sound very optimistic, and some of the applications 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 have been influenced by the hype surrounding quantum technology. It is especially important to avoid exaggerated expectations when the topic relates to national security or defense.

 

The military applications of quantum technologies described above are based on the latest research in the public domain, supplemented by various reports, newspaper or magazine articles on defense applications. In the absence of publicly available information on these technologies, no critical opinion is offered on the feasibility of these several technologies.

 

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 proof-of-concepts 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, these improvements cannot be made at the expense of sensitivity, resolution, and functionality, and the other decisive factor for practical deployment is the price of the technology.

 

In summary, given the advances in quantum technology research and support systems, such as laser and cryogenic cooling miniaturization over the past few years, there are reasons to be optimistic, rather than pessimistic (from the perspective of military or governmental 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 procurement and deployment.

 

In short, the military implications of quantum computing are far-reaching. As the technology matures, quantum systems could make a huge difference to national defense and warfare, from secure communications to advanced detection and navigation. However, the quantum leap must be approached with caution, as it brings great opportunities along with new complexities and potential risks.

 

Reference link:

[1]https://sofrep.com/news/quantum-tech-the-game-changer-in-defense-and-warfare/

[2]https://www.youtube.com/watch?v=disjVSlWe5o

[3]https://epjquantumtechnology.springeropen.com/articles/10.1140/epjqt/s40507-021-00113-y