The Business Case for Quantum Computing
1. C. Metinko, “Quantum Technology Gains Momentum as Computing Gets Closer to Reality,” Crunchbase, May 13, 2022, http://news.crunchbase.com; “What America’s Largest Technology Firms Are Investing In,” The Economist, Jan. 22, 2022, www.economist.com; and M. Aboy, T. Minssen, and M. Kop, “Mapping the Patent Landscape of Quantum Technologies: Patenting Trends, Innovation, and Policy Implications,” International Review of Intellectual Property and Competition Law 53, no. 10 (November 2022): 853-882.
2. F. Arute, K. Arya, R. Babbush, et al., “Quantum Supremacy Using a Programmable Superconducting Processor,” Nature 574, no. 7779 (Oct. 24, 2019): 505-510.
3. L.S. Madsen, F. Laudenbach, M.F. Askarani, et al., “Quantum Computational Advantage With a Programmable Photonic Processor,” Nature 606, no. 7912 (June 2, 2022): 75-81.
4. A.K. Fedorov, N. Gisin, S.M. Beloussov, et al., “Quantum Computing at the Quantum Advantage Threshold: A Down-to-Business Review” (preprint, submitted in March 2022), https://arxiv.org; L. Mueck, C. Palacios-Berraquero, and D.M. Persaud, “Towards a Quantum Advantage,” Physics World, Feb. 5, 2020, https://physicsworld.com; and S. Chen, “Quantum Advantage Showdowns Have No Clear Winners,” Wired, July 11, 2022, www.wired.com.
5. F. Bova, A. Goldfarb, and R.G. Melko, “Quantum Economic Advantage,” Management Science, Articles in Advance, published online Dec. 2, 2022.
6. “Near term” in this context refers to the quantum computers of the next few years, which will be better than today’s but still not fully fault tolerant.
7. “Value of Assets Under Management Worldwide in Selected Years From 2003 to 2021,” Statista, July 8, 2022, www.statista.com.
8. “Wall Street’s Latest Shiny New Thing: Quantum Computing,” The Economist, Dec. 19, 2020, www.economist.com.
9. S. Mugel, C. Kuchkovsky, E. Sanchez, et al., “Dynamic Portfolio Optimization With Real Datasets Using Quantum Processors and Quantum-Inspired Tensor Networks,” Physical Review Research 4, no. 1 (January 2022): 1-12.
10. L.K. Grover, “A Fast Quantum Mechanical Algorithm for Database Search,” in “STOC ’96: Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing” (Philadelphia: Association for Computing Machinery, 1996).
11. F. Bova, A. Goldfarb, and R.G. Melko, “Commercial Applications of Quantum Computing,” EPJ Quantum Technology 8 (2021): 1-13.
12. S.N. Genin, I.G. Ryabinkin, N.R. Paisley, et al., “Estimating Phosphorescent Emission Energies in Ir(III) Complexes Using Large-Scale Quantum Computing Simulations” (preprint, submitted in November 2021), https://arxiv.org. Since atoms and electrons themselves are quantum objects, they are natural candidates for study by quantum computers. In fact, such “simulation” (or emulation) was the first value proposition made for a quantum computer by California Institute of Technology physicist Richard Feynman in 1982.
13. S. Lee, J. Lee, H. Zhai, et al., “Is There Evidence for Exponential Quantum Advantage in Quantum Chemistry?” (preprint, submitted in August 2022), https://arxiv.org.
14. P.W. Shor, “Algorithms for Quantum Computation: Discrete Logarithms and Factoring,” in “Proceedings 35th Annual Symposium on Foundations of Computer Science” (Santa Fe, New Mexico: IEEE, 1994).
15. R. Van Meter and D. Horsman, “A Blueprint for Building a Quantum Computer,” Communications of the ACM 56, no. 10 (October 2013): 84-93.
16. It should be noted that quantum computers are not the only quantum technology that can produce true random numbers.
17. J. Melia, “The Odds Are in Quantum Security’s Favor,” QuintessenceLabs, March 2, 2017, www.quintessencelabs.com; and “Rigged Random Number Generators,” QuintessenceLabs, May 27, 2016, www.quintessencelabs.com.
i. Bova, Goldfarb, and Melko, “Commercial Applications of Quantum Computing.”
ii. D. Layden, G. Mazzola, R.V. Mishmash, et al., “Quantum-Enhanced Markov Chain Monte Carlo” (preprint, submitted in March 2022), https://arxiv.org; and S. Chakrabarti, J. Krishnakumar, G. Mazzola, et al., “A Threshold for Quantum Advantage in Derivative Pricing” (preprint, submitted in December 2020), https://arxiv.org.