Progress Toward Practical Areas of Quantum Technology

Quantum technologies have long underpinned modern foundational technologies, including lasers, atomic clocks, transistors, and semiconductor devices. Today, advancements in quantum information science and technology (QIST) are unlocking new tools for utilizing, generating, manipulating, and reading quantum states of matter, particularly quantum phenomena such as superposition and entanglement—with major potential implications on U.S. national security and economic prosperity.

As a transformative platform technology, potentially on par with artificial intelligence, it is critical to understand the current state of technological development, as well as the global policy and investment landscape surrounding QIST. Research, development, and commercialization in QIST span various fields and disciplines and are progressing at varying speeds depending on the field or discipline in question.

This commentary is the first in a series of three papers that explore the current state of quantum technology, the global competitive landscape as countries compete against each other to develop new QIST technologies, and considerations for U.S. quantum policy.

This paper outlines five foundational areas of QIST—quantum computing and quantum-centric supercomputing, quantum communication, quantum sensing, quantum materials, and quantum AI and quantum data centers—and describes the technological readiness and strategic relevance of each to U.S. national security and economic prosperity.

Since German physicist Werner Heisenberg formulated a type of quantum mechanics in 1925 based on matrices, scientists have made advances in these five areas. While commercial applications of QIST are currently limited, each area is evolving toward commercialization at a different pace. There is currently no globally recognized objective quantum technology readiness level (TRL) assessment.

Among quantum technologies, some experts rate quantum magnetometers, for example, as more mature in their development stage compared to quantum computing and quantum networking. The most rudimentary quantum networking technology, quantum key distribution, has been available commercially for over two decades, but more general quantum networking is probably less advanced than quantum computing.

1. Quantum Computing and Quantum-Centric Supercomputing

Quantum computers have the potential to solve problems that are beyond the reach of classical computers. However, significant technical and engineering challenges remain, such as scaling up qubits, developing more efficient error correction codes, and integrating with high-performance computing systems.

By exploiting the principles of quantum mechanics, researchers and industry aim to use quantum computers to achieve a so-called “quantum advantage.” It is expected that quantum computers will be able to solve complex problems that cannot currently be solved by classical high-performance computers, even those using high-performance graphics processing units.

The computational power of a quantum computer increases exponentially (relative to a binary-based computer) with the addition of more qubits, highly sensitive computing units that employ superposition to encode information. Quantum computers with more qubits can accurately perform more complex calculations, helping scientists solve difficult problems in fields like chemistry and optimization challenges related to supply chains, finance, and engineering. In the midterm, the goal is to develop and commercialize intermediate-scaled quantum computers with measurement and control systems and facilitate widespread adoption of quantum computers. 

However, researchers are facing numerous technical challenges as they work to achieve a quantum advantage. Unlike the semiconductor industry, which has advanced through miniaturization in line with Moore’s Law and 3D integration, new advances in the field of quantum computing and efforts to commercialize quantum technologies will rely heavily upon a deeper understanding of the principles of quantum physics. 

Researchers and industry are currently using various approaches to create high-quality qubits, each with its own strengths and challenges. For example, superconducting qubits, which are made from superconducting materials operating at extremely low temperatures, are favored for their speed in performing computations and fine-tuned control. While this approach has led to the development of higher-quality qubits, physical and engineering challenges have emerged, including the need for increasingly complex wires and ever-larger cryogenic cooling systems to manage heat. Other approaches currently being developed by researchers and industry involve using photonics, neutral atoms, trapped ions, and silicon spin. There are no clear answers on the best approach for enabling utility-scale quantum computing and its commercialization, nor is there consensus on whether multiple approaches will complement each other and coexist in the future or converge on a single approach.

Logical qubits, which are abstractions and encoded using a collection of physical qubits to protect against errors through quantum error correction techniques, are one meaningful indicator of quantum computing performance. Although the exact ratio depends on the approach that is used, tens of thousands of physical qubits are generally required to create 1,000 logical qubits. These logical qubits can then be used to reliably run algorithms on quantum systems. High-fidelity physical qubits at a scale and with error correction are key challenges. As of February 2024, at least eight companies have achieved logical qubits (10–17), regardless of the approach used. Challenges to scale quantum computational powers include protecting qubits from external noise, mitigating and correcting errors, advancing quantum control, and adding extra qubits to encode the information to detect and correct errors.

Another key challenge is performing quantum calculations. Quantum computers require users to use software on conventional computers to set up a quantum algorithm or model, configure the algorithm or model on the quantum computer to correctly find a solution, utilize the qubits on the computer to correctly output and read the results, and then return the computed results to the conventional computer. Researchers are developing optimized algorithms and readout systems to create practical quantum computing applications for both problem-specific and general-purpose uses. As quantum algorithms become more intricate, the need for error correction becomes pronounced, introducing complexity and demanding sophisticated algorithms to maintain accuracy.

Integrating high-performance computing (HPC) and quantum computing is expected to significantly increase existing quantum computing capabilities. IBM has said that quantum-centric supercomputing may potentially offer exponential speedups and processing power greater than either quantum or classical computing can provide for certain problems. Integration may alleviate current limitations of classical HPC by offloading specific tasks in classical computing workflows to quantum computers, thereby enhancing precision and efficiency. It is expected that integrating HPC into the same system as the quantum device will enable real-time error correction and noise reduction, greatly improve the reliability of quantum computing, and save operational costs and computation time.

HPC and quantum computing operate on completely different principles, and current challenges to integrating the two types of computing include barriers that make it difficult to establish a flexible software infrastructure framework, ensure low-latency communication interfaces between quantum and classical processors, and implement cross-disciplinary collaborative efforts.

2. Quantum Communications

Quantum communication uses quantum properties to enable secure information transfer and distributed quantum networking. Current efforts focus on deploying post-quantum cryptography and quantum key distribution while overcoming technical barriers to large-scale quantum networking.

Quantum communication makes use of physical systems that typically operate at the atomic and subatomic scale. The end goal of quantum communication is to build quantum networks through fiber-optic or free-space channels. These networks aim to connect geographically distributed quantum devices through optical qubits. Connecting distributed quantum computers can exponentially increase computing power.

Even as this advanced technology is being researched and developed, simpler quantum links are already possible. As a short-term application, encoding information in a quantum state-photon and transmitting it over a distance through fiber-optic and free-space channels enables secure communication, even against powerful quantum computers. There are two methodologies for securing communication against powerful quantum computers. The first is post-quantum cryptography (PQC), which involves using cryptographic algorithms based on advanced mathematical models. The second is quantum key distribution (QKD), a hardware-based quantum cryptography approach that uses principles of quantum mechanics.

The U.S. National Security Agency (NSA) has found that PQC is currently the best mitigation measure against quantum computer threats. Following the National Institute of Standards and Technology (NIST)’s release of PQC standards and guidelines, PQC is expected to be implemented by federal agencies and across sectors, and, ultimately, globally. Updating existing internet software for PQC is less costly and easier to deploy on a larger scale compared to QKD, as it does not require the creation of new physical infrastructure, whereas QKD does. QKD offers reduced vulnerability to increasing quantum computational power and immediate detection of information leakage. A combination of QKD and PQC to complement their characteristics is considered by some as the best mitigation strategy against future quantum computing threats, especially for high-value links. It is expected that this long-term virtual security framework will be valuable for securing defense platforms, finance systems, and other critical infrastructure sectors against threats from malicious cyber actors who systematically exploit global telecommunications networks such as Salt Typhoon.

Quantum communication is advancing through research and development in satellite technology and advanced optical components. At this time, there are a number of technical challenges to scale QKD, including reducing photon transmission loss and developing quantum repeaters and memories. This is the reason that more generalized quantum networking has a long way to go.

3. Quantum Sensing

Quantum sensors exploit the sensitivity of qubits to measure physical quantities with unprecedented precision, promising transformative impacts across industries. However, sensors currently face challenges related to environmental interference, miniaturization, and real-world deployment.

Quantum sensors utilize qubits, which are sensitive to the external environment, to create highly precise, sensitive, and responsive detection systems that are capable of making more accurate measurements than classical sensors. Quantum sensors are currently being used in the medical, finance, and defense industries. Examples include magnetic resonance imaging (MRI) machines for creating images of the body and atomic clocks for accurate timekeeping. 

Quantum sensors can measure temperature, pressure, frequency, acceleration, rotation, magnetic fields, images, and electric fields with unprecedented levels of precision. Quantum sensors will impact various industries, including navigation, geographic exploration, chemical and material analysis, intelligence, and defense. 

As researchers work to develop reliable quantum sensors, they are facing technical challenges related to the size, weight, power consumption, and cost of quantum hardware components. For example, quantum sensors are impacted by minuscule noises on moving platforms and environmental interference. The performance of quantum sensors degrades once a sensor is placed on moving platforms, due to electric and magnetic fields, field gradients, and system vibrations. The Department of Defense seeks to overcome these challenges through innovative physics approaches to quantum sensing.

Different types of quantum sensors are at various stages of development. For example, quantum magnetometers—which measure both the strength and direction of magnetic fields—and quantum gravimeters—which detect subtle variations in gravity—are already being deployed to carry out mineral exploration and geological surveys. Microwave atomic clocks run GPS systems, and optical atomic clocks have been on sea trials.

Quantum navigation uses quantum states to provide highly precise and reliable measurements of time, acceleration, and magnetic fields, surpassing the capabilities of conventional satellite-based navigation methods. It is expected that improvements in this area will solve current signal jamming and spoofing threats, with over 1,000 flights per day now disrupted by GPS jamming incidents. According to a report in 2023, the accuracy of quantum kinematics and timing sensors is still undergoing early empirical validation, with a number of publications reporting on trials or demonstrations of these sensors.

4. Quantum Materials

Quantum materials exhibit unique quantum properties that could revolutionize electronics and quantum devices. Quantum materials enable quantum mechanical functions that differ from the properties of conventional metals and materials. These materials, which go beyond classical physics, can potentially form the basis of technologies that will redefine our daily lives. Research is underway to stabilize and control these materials for practical use.

One example of a quantum material that exhibits unique quantum mechanical properties is the topological insulator. Unlike traditional metals, semiconductors, and insulators, topological insulators serve as conductors on their surfaces while functioning as insulators internally. In the future, topological insulators could be used to create new transistors that consume far less power than existing ones. At the present moment, quantum materials are unstable and easily affected by ambient thermal noise. Researchers have demonstrated that certain devices can be used to control the quantum states of electrons and spins. 

Researchers aim to create devices that can more precisely control the quantum properties of quantum materials. On February 19, 2025, researchers at Microsoft formed a quasiparticle (a particle-like collective electronic state) that can function as a topological qubit. Quasiparticles are expected to enable a new approach to quantum computing.

5. Quantum AI and Quantum Data Centers

Researchers are exploring how quantum technologies and AI can complement each other to enhance computational efficiency and advance AI capabilities. Experts have expressed interest in exploring new quantum technologies that can provide more efficient solutions for data-intensive tasks by enhancing existing AI applications, such as machine learning and deep learning. As AI becomes more widely used and the volume of data used in AI models grows, these subsets of AI will require large amounts of data processing and computing power. Quantum machine learning (QML) is an area of research that explores how quantum technology can enhance the speed, efficiency, and accuracy of machine learning (a subset of AI). 

Commercial applications of QML have not yet been developed because of current technical challenges in the field of quantum computing. Recently, developments in “Hybrid Quantum-Classical Machine Learning” (QCML) have been driving progress in research aimed at addressing these technical challenges. Hybrid QCML is a process that involves performing calculations on a quantum computer and then optimizing the parameters of those calculations by using machine learning on a classical computer. 

On the other hand, AI could also help speed up the development of quantum technologies, including by improving quantum hardware development and design, helping researchers create more effective algorithms for controlling and optimizing quantum devices, mitigating and correcting computational errors, and analyzing outputs.

Researchers are also exploring the idea of building a quantum data center, which would integrate quantum machines into a data center or high-performance computing facility to perform large-scale quantum computation and data processing. Patrick P. Gelsinger, former Intel CEO, mentioned, “When we go into a data center in 2030, we’re [going to] have a quantum corner, AI corner, the general purpose corner, and they are all going to be operating in combination.”

Conclusion

The future potential impact of quantum technology on industry and national security cannot be overstated. The five areas of QIST discussed in this paper are at various stages of research and development, each with its own unique set of technical challenges and opportunities, and commercialization of each area is advancing at a different pace. The United States should closely monitor technological challenges and emerging applications in each of these areas to ensure effective and efficient quantum innovation policy, given the strategic importance of QIST technologies for the U.S. national security and economic prosperity.

The CSIS’s Renewing American Innovation program is undertaking a review of the U.S. Quantum Opportunity, as requested by the National Institute of Standards and Technology and in cooperation with the Quantum Economic Development Consortium.

Hideki Tomoshige is an associate fellow with Renewing American Innovation at the Center for Strategic and International Studies in Washington, D.C. Phillip Singerman is a senior adviser (non-resident) with Renewing American Innovation at CSIS.