No longer far away! The "Quantum Era" has arrived, six cases reveal the future of science and technology wind direction ---

The problems that quantum computers excel at solving stem from their unique historical roots.

In 1981, physics giant Richard Feynman introduced the concept of quantum computers, designed to simulate the infinite complexity of the quantum world.

Since then, scientists have developed a series of ingenious algorithms that enable quantum computers to play a role in non-quantum areas, such as searching databases and cracking codes. For database searches, however, quantum computers may not be able to realize substantial speed advantages in the foreseeable future. Similarly, new types of machines for threatening Internet security appear to be a controversial development.

But the latest research points to the potential of quantum computers to simulate quantum phenomena of interest to several industries, possibly sooner than the progress they have made in other applications.

"The commercial impact of problem solving in quantum systems is mainly seen in the chemical, materials science and pharmaceutical industries." Matthias Troi adds. These are key industry sectors. "From the Stone Age, Bronze Age, Iron Age, Iron and Steel Age to the Silicon Age, we are defining the course of history through material innovation."

On the road to a potential new quantum era, here are a few key examples of the empirical quantum advantages that quantum computing researchers expect these devices to demonstrate over the next decade.

Troy hopes that the $5 million reward prize will inspire the scientific community to find more ways to apply quantum algorithms to real-world problems. "The goal of this prize is to attract more quantum scientists to focus not just on developing quantum algorithms and theories, but to think about questions like: in what areas are quantum algorithms useful? How can we use quantum computers to solve the major challenges facing the world?"

In a paper in Proceedings of the National Academy of Sciences (PNAS) 2022, the drug company Boehringer Ingelheim, Columbia University, Google Quantum Artificial Intelligence, and QSimulate jointly explore the enzyme cytochrome P450.

This enzyme plays a key role in human drug metabolism and is involved in the metabolism of about 70% of drugs. The study found that quantum computers can simulate its oxidation process faster and more accurately than traditional methods, which is significant for drug development.

While the traditional method of ammonia production-the Haber-Bosch process-requires high-temperature and high-pressure environments, a team of researchers from Microsoft Research and ETH Zurich is exploring a more environmentally friendly alternative. They are considering the use of nitrogen-fixing enzymes to produce ammonia at room temperature and pressure, which could have revolutionary implications for global food security.

The researchers found that classical methods cannot accurately model this reaction, but that classical and quantum computers can work in tandem. Troy, who worked on the study, said, "For example, if you could find the chemical process of nitrogen fixation on a small scale on a farm in a village, that would have a huge impact on food security."

Due to the environmental and safety concerns associated with cobalt mining, scientists are looking for alternatives, such as nickel. A study conducted by BASF, Google Quantum Artificial Intelligence, Macquarie University in Sydney and QSimulate worked to simulate a nickel-based cathode - lithium nickel oxide - on a quantum computer to explore the possibility of producing a stable material.

Pure lithium nickel oxide is not stable during production and little is known about its basic structure, the researchers said. If the ground state of this material can be better modeled, it may be possible to find ways to make a stable version. In a blog post, the authors wrote: "The quantum computational requirements needed to adequately model this problem are beyond the capabilities of the first error-correcting quantum computers, but we expect this number to decrease with future algorithmic improvements."

In 2022, the National Ignition Facility (NIF) in the United States made headlines when it performed the first inertial fusion reaction, producing more energy than was directly put into it. In an inertial fusion reaction, a tritium-deuterium mixture is heated by a laser until it forms a plasma and collapses in on itself, triggering a fusion reaction. Babush, who worked on the study, explained that this plasma is extremely difficult to model.

He said, "Hundreds of millions, if not billions, of CPU hours have been spent by the Department of Energy calculating just one quantity."

In a preprint, Babush and his collaborators outline an algorithm with which a quantum computer could model the full complexity of the reaction. This, like battery cathode research, would require more quantum bits than are currently available, but the authors believe that future hardware and algorithmic improvements may close the gap.

Unlike quantum computers, quantum sensors are already having an impact on the real world.

These sensors measure magnetic fields more accurately than any other technology and are currently being used in brain scans, gravity measurements for mapping geological activity, and more. The output of quantum sensors is quantum data, but currently reads out classical data, the traditional 1s and 0s, ignoring some of the full quantum complexity.

In 2022, a study conducted in collaboration with Google, Caltech, Harvard, UC Berkeley, and Microsoft showed that if the output of a quantum sensor is imported into a quantum computer, a clever algorithm can be used to learn relevant properties with exponentially fewer copies of the sensor's data, resulting in faster readouts.

They demonstrated their quantum algorithm on an analog sensor, showing that even existing quantum computers can use it.

Learning the "Quantum Advantage" of Physical Dynamics

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The field of quantum technology has had an exciting year as 2024 approaches, preparing the opening chapter for breakthroughs. Looking back over the past few years, especially in the pivotal year of 2023, while we can't predict the future, the momentum in the quantum field has allowed us to chart the trends in the quantum landscape that are likely to shape this year.

Most notable are quantum-inspired developments in AI, especially those breakthroughs that make large language models smaller and more efficient. Quantum-inspired AI is expected to revolutionize the way we interact with generative AI such as ChatGPT, LLaMA, and others, enabling significant streamlining of model size without sacrificing accuracy.

Additionally, in 2024 we are also expected to see the rise of hybrid quantum machine learning techniques combining quantum and classical techniques, a fusion that runs on Noise-Intermediate Scale Quantum (NISQ) computers that can greatly expand the application areas of AI, and may even make it possible for models like ChatGPT to run on smartwatches.

In 2023, IBM achieved the milestone achievement of 1,121 superconducting quantum bits, and QuERA Computing developed 48 logic quantum bits using neutral atoms, signaling a major advance in hardware this year.

Google's Quantum Advantage experiment last year was also highly publicized, with its 70-qubit quantum computer successfully completing tasks that would have taken 47 years for the same task on a classical computer.

In addition to Google's quantum superiority, hardware development is focusing on three key areas - error mitigation, quantum error correction and scalability - to build deeper, more accurate quantum circuits and eventually support millions of error-correcting quantum bits.

2024 is expected to be a key year in the development of computer hardware beyond NISQ, and we expect to see the first clusters of quantum computers connected via quantum channels and working together. In terms of quantum error correction, quantum coding of more than 100 quantum bits is expected to be realized.

In short, 2024 will be the year that quantum technology goes beyond the hype and becomes truly integrated into everyday life. The synergy of inspired AI developments, hardware advances and venture capital investment is laying a solid foundation for this transformation.

In this regard, Jay Gambetta, vice president of IBM Quantum, said that quantum computers are on the verge of reaching a level of hardware that is sufficient to test more heuristic algorithms, which will set the stage for more use cases to emerge. Gambetta said, "We can finally start using hardware to discover algorithms. This opens up another new path for scientific discovery, and that's the most exciting part."