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Why the United States Needs to Support Near-Term Quantum Computing Applications

Why the United States Needs to Support Near-Term Quantum Computing Applications
April 27, 2021

As other nations rapidly scale up their investments to develop and use quantum computing, U.S. policymakers should ensure the United States remains a leader. Investing in near-term applications would bolster the development of longer-term use cases, thereby helping to cement U.S. economic competitiveness and protect national security.

Recent advances in quantum computing technologies have led to a wave of interest, bringing with it hype and confusion about both the potential of quantum computing and its current status. While large-scale quantum computers could, in theory, conduct such feats as decrypting current cryptographic ciphers, in reality, quantum technologies are still in the very early stages. John Preskill, a professor of theoretical physics at Caltech University and a leading scientist in quantum computing, noted in 2018 that “we are entering a pivotal new era in quantum technology”—an era he referred to as the “NISQ era.” NISQ stands for noisy intermediate-scale quantum technology and refers to the fact that the systems that will be available over the next few years, will be relatively small in size, and have imperfections (or noise) that will limit what they are able to achieve.

Overcoming technical challenges on the path toward large-scale quantum computers will depend on the ability to scale the number of qubits in quantum systems, much like modern classical computers have depended on the growth in the number of transistors in superconducting chips. The current enthusiasm for quantum computing could lead to a virtuous cycle of progress, as the semiconductor industry has already seen, but only if near-term applications for the quantum computing technologies under development are successful. The U.S. government can best support the scaling of current quantum technologies by fostering a commercial market for them in the near term.

Current quantum devices can already solve problems in an array of application areas, such as health care, manufacturing, transportation, and the environment. Researchers have identified several other potential application areas, but these findings remain in the research space. To ensure quantum research is effectively translated into real-world applications, Congress should provide $500 million in funding over 5 years for academic research projects that have near-term applications to work with industry on research and development (R&D). Ideally, this program would encourage and support research projects that align with regional economic development goals by fostering collaboration and partnerships between universities, local businesses, and state and local governments.

The proven advantages of using quantum computers for optimization problems suggest that these systems may also help solve classification problems by improving artificial intelligence (AI) models. AI technologies, such as machine learning, deep learning, neural networks, and computer vision, rely on the processing of large amounts of data to identify patterns. While classical systems can use parallelism to train AI models on large datasets, some datasets are too large or too complex to be solved efficiently. Quantum computing could help address this challenge. Quantum systems use quantum principles to create non-classical correlations between data points (called entanglement), which suggests they might also be able to recognize highly complex relationships in datasets that classical systems cannot. Google’s AI Quantum team is already examining how near-term quantum computers can improve neural networks, which are algorithms that mimic the way the human brain recognizes relationships between different datasets.

Because quantum computers are highly specialized, difficult to maintain, and expensive to develop, most users will likely access these systems through cloud-based solutions. Indeed, the private sector is already offering cloud-based access to quantum computing, such as Amazon Braket and Microsoft Azure Quantum, that allows users to learn, build, and deploy solutions using the latest quantum computing hardware.

However, the cost of quantum computing may be too high for many academic researchers and thus limit their ability to develop future talent in the field and apply quantum computing solutions to ongoing work. To address this problem, Congress should establish a National Quantum Research Task Force to provide academic researchers with affordable access to high-end quantum computing resources in a secure cloud environment, as well as the necessary training they need to make the most of it. This task force could be analogous to the AI research task force that was established as part of the National AI Research Resource Task Force Act of 2020 and consist of members from academia, government, and industry. Their goal should be to develop a roadmap for building, deploying, funding, and governing a national quantum computing research cloud that can accelerate access to quantum computing for research in the public interest. The National Quantum Research Task Force should also ensure it considers how to provide equitable access to quantum computing at Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs).

The U.S. government itself should play a role in exploring quantum applications, not only to better solve agency-specific problems but also to signal the benefits of doing so to the private sector. To this end, the Office of Science and Technology Policy (OSTP) should issue a quantum challenge that requires every federal agency to identify at least two existing use cases for which they can use quantum computing. For instance, the Department of Transportation (DOT) could identify ways quantum computing could help optimize public transportation across cities. But, since this relies on access to mobility data that is often held by private companies, DOT should establish a platform that aggregates and centralizes mobility data across cities, which public and private players would contribute to.

Finally, even though the development of a large-scale quantum computer capable of breaking cryptographic protocols is at least a decade away, Congress should consider incentivizing post-quantum cryptography transition (PQC) in the public and private sectors through mechanisms such as a dedicated fund to support state and local governments in their transition efforts and a certification scheme for companies that implement PQC protocols. As the development of quantum computing technologies will likely become globalized industries, the National Quantum Coordinating Office (NQCO) should publish a report outlining what the quantum supply chain looks like today and where risks are likely to emerge to better inform future economic and national security policies.

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