- Physical Review Journals
All JournalsPhysics Magazine

Physical Review Physics Education Research

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Editors' Suggestion
  • Open Access

Do we have a quantum computer? Expert perspectives on current state and future prospects

Liam Doyle, Fargol Seifollahi, and Chandralekha Singh

PDF

Phys. Rev. Phys. Educ. Res. 22, 010101 – Published 5 January, 2026

DOI: https://doi.org/10.1103/md6x-pfrr

Abstract

The rapid growth of quantum information science and technology (QIST) in the 21st century has created both excitement and uncertainty about the field’s trajectory. This qualitative study presents perspectives from leading quantum researchers, who are educators, on fundamental questions frequently posed by students, the public, and the media regarding QIST. Through in-depth interviews, we explored several issues related to QIST including the following key areas: the current state of quantum computing in the noisy intermediate-scale quantum (NISQ) era and timelines for fault-tolerant quantum computers, including a possible timeline for quantum advantage on Shor’s factoring algorithm, the feasibility of personal quantum computers in our pockets, and promising qubit architectures for future development. Our findings reveal diverse yet convergent perspectives on these critical issues. While experts agree that the current machines with physical qubits that are being built in the NISQ era should be called quantum computers, most estimated that it will take a decade to build a small fault-tolerant quantum computer, and several decades to achieve scalable systems capable of running Shor’s factoring algorithm with quantum advantage and some stated that they would find it exciting if some law of physics prevents achieving those ultimate goals. Regarding carrying a quantum computer in the pocket, experts viewed quantum computers as specialized tools that will remain in central locations such as data centers and can be accessed remotely for applications for which they are particularly effective compared to classical computers. Quantum researchers suggested that multiple platforms show promise, including neutral atoms, superconducting circuits, semiconducting qubits, and photonic systems, with no clear winner emerging. These insights provide valuable guidance for educators, policymakers, and the broader community in establishing realistic expectations for developments in this exciting field. Our findings can provide valuable information for educators to clarify student doubts about these important yet confusing issues related to quantum technologies at a time we are celebrating the International Year of Quantum Science and Technology.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (135)

  1. A. Acín, I. Bloch et al., The quantum technologies roadmap: A European community view, New. J. Phys. 20, 080201 (2018).
  2. M. G. Raymer and C. Monroe, The US National Quantum Initiative, Quantum Sci. Technol. 4, 020504 (2019).
  3. D. Castelvecchi, Europe shows first cards in €1-billion quantum bet, Nature (London) 563, 14 (2018).
  4. Y. Alexeev, D. Bacon et al., Quantum computer systems for scientific discovery, PRX Quantum 2, 017001 (2021).
  5. D. P. DiVincenzo, The physical implementation of quantum computation, Fortschr. Phys. 48, 771 (2000).
  6. S. Lloyd, Universal quantum simulators, Science 273, 1073 (1996).
  7. A. Daley, I. Bloch et al., Practical quantum advantage in quantum simulation, Nature (London) 607, 667 (2022).
  8. E. Altman, K. R. Brown et al., Quantum simulators: Architectures and opportunities, PRX Quantum 2, 017003 (2021).
  9. C. Jones, M. A. Fogarty et al., Logical qubit in a linear array of semiconductor quantum dots, Phys. Rev. X 8, 021058 (2018).
  10. A. Trabesinger, Quantum simulation, Nat. Phys. 8, 263 (2012).
  11. F. Arute, K. Arya et al., Quantum supremacy using a programmable superconducting processor, Nature (London) 574, 505 (2019).
  12. C. H. Bennett and G. Brassard, Quantum cryptography: Public key distribution and coin tossing, Theor. Comput. Sci. 560, 7 (2014).
  13. A. K. Ekert, Quantum cryptography based on Bell’s theorem, Phys. Rev. Lett. 67, 661 (1991).
  14. D. S. Naik, C. G. Peterson, A. G. White, A. J. Berglund, and P. G. Kwiat, Entangled state quantum cryptography: Eavesdropping on the Ekert protocol, Phys. Rev. Lett. 84, 4733 (2000).
  15. V. Scarani, H. Bechmann-Pasquinucci et al., The security of practical quantum key distribution, Rev. Mod. Phys. 81, 1301 (2009).
  16. S.-K. Liao, W.-Q. Cai et al., Satellite-to-ground quantum key distribution, Nature (London) 549, 43 (2017).
  17. J. P. Ralston, What can we learn from entanglement and quantum tomography?, Physics 4, 1371 (2022).
  18. P. Shor, Algorithms for quantum computation: Discrete logarithms and factoring, in Proceedings of the 35th Annual Symposium on Foundations of Computer Science, Santa Fe, NM (IEEE, New York, 1994), pp. 124–134.
  19. A. R. Calderbank and P. W. Shor, Good quantum error-correcting codes exist, Phys. Rev. A 54, 1098 (1996).
  20. J. Eckstein and J. Levy, Materials issues for quantum computation, MRS Bull. 38, 783 (2013).
  21. C. D. Bruzewicz, J. Chiaverini, R. McConnell, and J. M. Sage, Trapped-ion quantum computing: Progress and challenges, Appl. Phys. Rev. 6, 021314 (2019).
  22. X. Zhang, H.-O. Li et al., Semiconductor quantum computation, Natl. Sci. Rev. 6, 32 (2019).
  23. M. Kjaergaard, M. E. Schwartz et al., Superconducting qubits: Current state of play, Annu. Rev. Condens. Matter Phys. 11, 369 (2020).
  24. A. Blais, S. M. Girvin, and W. D. Oliver, Quantum information processing and quantum optics with circuit quantum electrodynamics, Nat. Phys. 16, 247 (2020).
  25. L. Henriet, L. Beguin et al., Quantum computing with neutral atoms, Quantum 4, 327 (2020).
  26. H. J. Kimble, The quantum internet, Nature (London) 453, 1023 (2008).
  27. D. Awschalom, K. K. Berggren et al., Development of quantum interconnects (QuICs) for next-generation information technologies, PRX Quantum 2, 017002 (2021).
  28. H.-S. Zhong, H. Wang et al., Quantum computational advantage using photons, Science 370, 1460 (2020).
  29. S. Slussarenko and G. J. Pryde, Photonic quantum information processing: A concise review, Appl. Phys. Rev. 6, 041303 (2019).
  30. R. Hanson, O. Gywat, and D. D. Awschalom, Room-temperature manipulation and decoherence of a single spin in diamond, Phys. Rev. B 74, 161203 (2006).
  31. J. Preskill, Quantum computing in the NISQ era and beyond, Quantum 2, 79 (2018).
  32. M. Fox, B. M. Zwickl, and H. Lewandowski, Preparing for the quantum revolution: What is the role of higher education?, Phys. Rev. Phys. Educ. Res. 16, 020131 (2020).
  33. C. Singh, A. Asfaw, and J. Levy, Preparing students to be leaders of the quantum information revolution, Phys. Today (2021), 10.1063/PT.6.5.20210927a.
  34. J. C. Meyer, G. Passante, S. J. Pollock, and B. R. Wilcox, Today’s interdisciplinary quantum information classroom: Themes from a survey of quantum information science instructors, Phys. Rev. Phys. Educ. Res. 18, 010150 (2022).
  35. A. Asfaw, A. Blais et al., Building a quantum engineering undergraduate program, IEEE Trans. Ed. 65, 220 (2022).
  36. F. Greinert, R. Müller, P. Bitzenbauer, M. S. Ubben, and K.-A. Weber, Future quantum workforce: Competences, requirements, and forecasts, Phys. Rev. Phys. Educ. Res. 19, 010137 (2023).
  37. A. Merzel, P. Bitzenbauer et al., The core of secondary level quantum education: A multi-stakeholder perspective, Eur. Phys. J. Quantum Technol. 11, 27 (2024).
  38. P. Bitzenbauer, J. M. Veith, B. Girnat, and J.-P. Meyn, Assessing engineering students’ conceptual understanding of introductory quantum optics, Physics 4, 1180 (2022).
  39. V. K. Sewani, H. H. Vallabhapurapu et al., Coherent control of NV- centers in diamond in a quantum teaching lab, Am. J. Phys. 88, 1156 (2020).
  40. J. Levy and C. Singh, Hands-on quantum: Teaching core quantum concepts with Bloch cubes, Phys. Teach. 63, 85 (2025).
  41. J. Levy and C. Singh, Teaching quantum formalism and postulates to first-year undergraduates, Am. J. Phys. 93, 46 (2025).
  42. D. Schneble, T.-C. Wei, and A. M. Kelly, Quantum information science and technology high school outreach: Conceptual progression for introducing principles and programming skills, Am. J. Phys. 93, 88 (2025).
  43. P. Neto Mendes, P. André, and E. Zambrini Cruzeiro, Simple portable quantum key distribution for science outreach, Am. J. Phys. 93, 69 (2025).
  44. A. Bista, B. Sharma, and E. J. Galvez, A demonstration of quantum key distribution with entangled photons for the undergraduate laboratory, Am. J. Phys. 89, 111 (2021).
  45. A. Kohnle and A. Rizzoli, Interactive simulations for quantum key distribution, Eur. J. Phys. 38, 035403 (2017).
  46. S. Loepp and W. K. Wootters, Protecting Information: From Classical Error Correction to Quantum Cryptography (Cambridge University Press, Cambridge, England, 2006).
  47. J. S. Kashyap and C. Singh, Strategies educators can use to counter misinformation related to the quantum information revolution, Phys. Educ. 60, 035024 (2025).
  48. C. Singh, Student understanding of quantum mechanics, Am. J. Phys. 69, 885 (2001).
  49. D. A. Zollman, N. S. Rebello, and K. Hogg, Quantum mechanics for everyone: Hands-on activities integrated with technology, Am. J. Phys. 70, 252 (2002).
  50. J. J. Thorn, M. S. Neel et al., Observing the quantum behavior of light in an undergraduate laboratory, Am. J. Phys. 72, 1210 (2004).
  51. C. Singh, Student understanding of quantum mechanics at the beginning of graduate instruction, Am. J. Phys. 76, 277 (2008).
  52. C. Singh, Interactive learning tutorials on quantum mechanics, Am. J. Phys. 76, 400 (2008).
  53. G. Zhu and C. Singh, Improving students’ understanding of quantum measurement. I. Investigation of difficulties, Phys. Rev. ST Phys. Educ. Res. 8, 010117 (2012).
  54. G. Zhu and C. Singh, Improving students’ understanding of quantum measurement. II. Development of research-based learning tools, Phys. Rev. ST Phys. Educ. Res. 8, 010118 (2012).
  55. G. Zhu and C. Singh, Surveying students’ understanding of quantum mechanics in one spatial dimension, Am. J. Phys. 80, 252 (2012).
  56. A. Kohnle, I. Bozhinova et al., A new introductory quantum mechanics curriculum, Eur. J. Phys. 35, 015001 (2013).
  57. C. Singh and E. Marshman, Review of student difficulties in upper-level quantum mechanics, Phys. Rev. ST Phys. Educ. Res. 11, 020117 (2015).
  58. E. Marshman and C. Singh, Framework for understanding the patterns of student difficulties in quantum mechanics, Phys. Rev. ST Phys. Educ. Res. 11, 020119 (2015).
  59. E. Marshman and C. Singh, Validation and administration of a conceptual survey on the formalism and postulates of quantum mechanics, Phys. Rev. Phys. Educ. Res. 15, 020128 (2019).
  60. P. J. Emigh, G. Passante, and P. S. Shaffer, Student understanding of time dependence in quantum mechanics, Phys. Rev. ST Phys. Educ. Res. 11, 020112 (2015).
  61. P. J. Emigh, G. Passante, and P. S. Shaffer, Developing and assessing tutorials for quantum mechanics: Time dependence and measurements, Phys. Rev. Phys. Educ. Res. 14, 020128 (2018).
  62. M. Michelini and A. Stefanel, Research studies on learning quantum physics, in The International Handbook of Physics Education Research: Learning Physics (AIP Publishing, Melville, NY, 2023), Chap. 8, 10.1063/9780735425477_008.
  63. M. Chhabra and R. Das, Undergraduate students’ visualization of quantum mechanical eigenstates and the role of boundary conditions, Eur. J. Phys. 44, 025702 (2023).
  64. E. Marshman and C. Singh, Investigating and improving student understanding of quantum mechanical observables and their corresponding operators in Dirac notation, Eur. J. Phys. 39, 015707 (2017).
  65. B. R. Brown, A. Mason, and C. Singh, Improving performance in quantum mechanics with explicit incentives to correct mistakes, Phys. Rev. Phys. Educ. Res. 12, 010121 (2016).
  66. E. Marshman and C. Singh, Investigating and improving student understanding of the expectation values of observables in quantum mechanics, Eur. J. Phys. 38, 045701 (2017).
  67. A. Maries, R. Sayer, and C. Singh, Investigation of student and faculty problem solving: An example from quantum mechanics, Am. J. Phys. 93, 492 (2025).
  68. C. Singh, Helping students learn quantum mechanics for quantum computing, AIP Conf. Proc. 883, 42 (2007).
  69. E. Marshman and C. Singh, Interactive tutorial to improve student understanding of single photon experiments involving a Mach–Zehnder interferometer, Eur. J. Phys. 37, 024001 (2016).
  70. A. Kohnle and A. Rizzoli, Interactive simulations for quantum key distribution, Eur. J. Phys. 38, 035403 (2017).
  71. S. DeVore and C. Singh, Interactive learning tutorial on quantum key distribution, Phys. Rev. Phys. Educ. Res. 16, 010126 (2020).
  72. A. Maries, R. Sayer, and C. Singh, Can students apply the concept of “which-path” information learned in the context of Mach–Zehnder interferometer to the double-slit experiment?, Am. J. Phys. 88, 542 (2020).
  73. A. Bista, B. Sharma, and E. J. Galvez, A demonstration of quantum key distribution with entangled photons for the undergraduate laboratory, Am. J. Phys. 89, 111 (2021).
  74. C. Singh, A. Levy, and J. Levy, Preparing precollege students for the second quantum revolution with core concepts in quantum information science, Phys. Teach. 60, 639 (2022).
  75. E. Weissman, A. Merzel, N. Katz, and I. Galili, Keep it secret, keep it safe: Teaching quantum key distribution in high school, Eur. Phys. J. Quantum Technol. 11, 64 (2024).
  76. M. Brang, H. Franke et al., Spooky action at a distance? A two-phase study into learners’ views of quantum entanglement, Eur. Phys. J. Quantum Technol. 11, 33 (2024).
  77. G. Hellstern, J. Hettel, and B. Just, Introducing quantum information and computation to a broader audience with MOOCs at OpenHPI, Eur. Phys. J. Quantum Technol. 11, 59 (2024).
  78. S. Goorney, M. Sarantinou, and J. Sherson, The quantum technology open master: Widening access to the quantum industry, Eur. Phys. J. Quantum Technol. 11, 7 (2024).
  79. J. C. Meyer, G. Passante, S. J. Pollock, and B. R. Wilcox, Introductory quantum information science coursework at US institutions: Content coverage, Eur. Phys. J. Quantum Technol. 11, 16 (2024).
  80. Q. Sun, S. Zhou et al., From computing to quantum mechanics: Accessible and hands-on quantum computing education for high school students, Eur. Phys. J. Quantum Technol. 11, 58 (2024).
  81. P. Hu, Y. Li, R. S. K. Mong, and C. Singh, Student understanding of the Bloch sphere, Eur. J. Phys. 45, 025705 (2024).
  82. P. Hu, Y. Li, and C. Singh, Investigating and improving student understanding of the basics of quantum computing, Phys. Rev. Phys. Educ. Res. 20, 020108 (2024).
  83. A. López-Incera, A. Hartmann, and W. Dür, Encrypt me! A game-based approach to Bell inequalities and quantum cryptography, Eur. J. Phys. 41, 065702 (2020).
  84. M. A. Schalkers, K. Dankers, M. Wimmer, and P. Vermaas, Explaining Grover’s algorithm with a colony of ants: A pedagogical model for making quantum technology comprehensible, Phys. Educ. 59, 035003 (2024).
  85. F. W. Strauch, Resource letter QI-1: Quantum information, Am. J. Phys. 84, 495 (2016).
  86. E. J. Galvez, Resource letter SPE-1: Single-photon experiments in the undergraduate laboratory, Am. J. Phys. 82, 1018 (2014).
  87. J. C. Meyer, S. J. Pollock, B. R. Wilcox, and G. Passante, How media hype affects our physics teaching: A case study on quantum computing, Phys. Teach. 61, 339 (2023).
  88. P. D. Justice, E. Marshman, and C. Singh, A framework for understanding the impact of integrating conceptual and quantitative reasoning in a quantum optics tutorial on students’ conceptual understanding, Educ. Sci. 15, 1314 (2025).
  89. L. V. Rodriguez, J. T. van der Veen, A. Anjewierden, E. van den Berg, and T. de Jong, Designing inquiry-based learning environments for quantum physics education in secondary schools, Phys. Educ. 55, 065026 (2020).
  90. A. Donhauser, P. Bitzenbauer et al., Empirical insights into the effects of research-based teaching strategies in quantum education, Phys. Rev. Phys. Educ. Res. 20, 020601 (2024).
  91. B. Brown, G. Zhu, and C. Singh, Investigating and improving student understanding of time dependence of expectation values in quantum mechanics using an interactive tutorial on larmor precession, Am. J. Phys. 93, 52 (2025).
  92. V. Borish and H. Lewandowski, Affordances and challenges of incorporating a remote, cloud-accessible quantum experiment into undergraduate courses, Phys. Rev. Phys. Educ. Res. 21, 010133 (2025).
  93. N. Didiş, The analysis of analogy use in the teaching of introductory quantum theory, Chem. Educ. Res. Pract. 16, 355 (2015).
  94. S. Faletič, How analogies helped novice students think about superposition states and collapse in quantum mechanics, Eur. Phys. J. Quantum Technol. 12, 9 (2025).
  95. E. Y. Weissman, A. Merzel, N. Katz, and I. Galili, Phenomena and principles: Presenting quantum physics in a high school curriculum, Physics 4, 1299 (2022).
  96. M. Michelini, A. Stefanel, and K. Tóth, Implementing Dirac approach to quantum mechanics in a Hungarian secondary school, Educ. Sci. 12, 606 (2022).
  97. F. Hennig, K. Tóth, M. Förster, and P. Bitzenbauer, A new teaching-learning sequence to promote secondary school students’ learning of quantum physics using Dirac notation, Phys. Educ. 59, 045007 (2024).
  98. P. Hu, Y. Li, and C. Singh, Challenges in addressing student difficulties with time-development of two-state quantum systems using a multiple-choice question sequence in virtual and in-person classes, Eur. J. Phys. 43, 025704 (2022).
  99. P. Hu, Y. Li, and C. Singh, Challenges in addressing student difficulties with measurement uncertainty of two-state quantum systems using a multiple-choice question sequence in online and in-person classes, Eur. J. Phys. 44, 015702 (2022).
  100. P. Hu, Y. Li, and C. Singh, Challenges in addressing student difficulties with basics and change of basis for two-state quantum systems using a multiple-choice question sequence in online and in-person classes, Eur. J. Phys. 44, 065703 (2023).
  101. P. Hu, Y. Li, and C. Singh, Challenges in addressing student difficulties with quantum measurement of two-state quantum systems using a multiple-choice question sequence in online and in-person classes, Phys. Rev. Phys. Educ. Res. 19, 020130 (2023).
  102. S. Goorney, J. Bley, S. Heusler, and J. Sherson, A framework for curriculum transformation in quantum information science and technology education, Eur. J. Phys. 45, 065702 (2024).
  103. B. Bungum and S. Selstø, What do quantum computing students need to know about quantum physics?, Eur. J. Phys. 43, 055706 (2022).
  104. M. Bondani, M. L. Chiofalo et al., Introducing quantum technologies at secondary school level: Challenges and potential impact of an online extracurricular course, Physics 4, 1150 (2022).
  105. S. Aaronson, Quantum Computing Since Democritus (Cambridge University Press, Cambridge, England, 2013).
  106. M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information (Cambridge University Press, Cambridge, England, 2010).
  107. N. D. Mermin, Quantum Computer Science (Cambridge University Press, Cambridge, England, 2007).
  108. M. G. Raymer, Quantum Physics: What Everyone Needs to Know (Oxford University Press, New York, 2017).
  109. T. G. Wong, Introduction to Classical and Quantum Computing (Rooted Grove, Omaha, Nebraska, 2022).
  110. R. S. Sutor, Dancing with Qubits: How Quantum Computing Works and How It Can Change the World (Packt Publishing Ltd, 2019).
  111. M. Orszag, Quantum Optics: Including Noise Reduction, Trapped Ions, Quantum Trajectories, and Decoherence (Springer, New York, 2016).
  112. A. Ghimire and C. Singh, Reflections of quantum educators on strategies to diversify the second quantum revolution, Phys. Teach. 63, 35 (2025).
  113. F. Seifollahi and C. Singh, Preparing students for the quantum information revolution: Interdisciplinary teaching, curriculum development, and advising in quantum information science and engineering, Eur. J. Phys. 46, 055709 (2025).
  114. L. Doyle, F. Seifollahi, and C. Singh, Building bridges in quantum information science education: Expert insights to guide framework development for interdisciplinary teaching and evolution of common language, Eur. Phys. J. Quantum Technol. (2025).
  115. J. Saldaña, The Coding Manual for Qualitative Researchers (SAGE Publications Ltd., 2021).
  116. N. Hedlund-de Witt, An overview and guide to qualitative data analysis for integral researchers, Integr. Res. Cent. 1, 76 (2013).
  117. M. Q. Patton, Qualitative Research and Evaluation Methods, 3rd ed. (Sage Publications, 2002).
  118. L. K. Grover, From Schrödinger’s equation to the quantum search algorithm, Am. J. Phys. 69, 769 (2001).
  119. E. Bernstein and U. Vazirani, Quantum complexity theory, SIAM J. Comput. 26, 1411 (1997).
  120. D. R. Simon, On the power of quantum computation, SIAM J. Comput. 26, 1474 (1997).
  121. IonQ, https://ionq.com/.
  122. QuEra, https://https://www.quera.com/.
  123. D-Wave, https://www.dwavequantum.com/.
  124. IBM, https://www.ibm.com/quantum/blog/large-scale-ftqc.
  125. Google, https://research.google/blog/making-quantum-error-correction-work/.
  126. A. G. Fowler, M. Mariantoni, J. M. Martinis, and A. N. Cleland, Surface codes: Towards practical large-scale quantum computation, Phys. Rev. A 86, 032324 (2012).
  127. J. Roffe, Quantum error correction: An introductory guide, Contemp. Phys. 60, 226 (2019).
  128. B. M. Terhal, Quantum error correction for quantum memories, Rev. Mod. Phys. 87, 307 (2015).
  129. A. Y. Kitaev, Quantum computations: Algorithms and error correction, Russ. Math. Surv. 52, 1191 (1997).
  130. J. Aasi et al., Enhanced sensitivity of the LIGO gravitational wave detector by using squeezed states of light, Nat. Photonics 7, 613 (2013).
  131. PsiQuantum, https://www.psiquantum.com/.
  132. J. Maze, P. Stanwix et al., Nanoscale magnetic sensing with an individual electronic spin in diamond, Nature (London) 455, 644 (2008).
  133. Y. Yang, H. H. Vallabhapurapu et al., Observing hyperfine interactions of NV− centers in diamond in an advanced quantum teaching lab, Am. J. Phys. 90, 550 (2022).
  134. G. Moore, http://cva.stanford.edu/classes/cs99s/papers/moore-crammingmorecomponents.pdf.
  135. W. K. Wootters and W. H. Zurek, A single quantum cannot be cloned, Nature (London) 299, 802 (1982).

Outline

Information

Phys. Rev. Phys. Educ. Res. 22, 010101– Published 5 January, 2026
  • Received 4 September 2025
  • Accepted 16 December 2025
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation