Pith. sign in

REVIEW 3 major objections 4 minor 43 references

Opinion: The simplest quantum computer

T0 review · 3 major / 4 minor · reviewed 2026-08-11 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read The simplest quantum computer uses only joint measurements as gates, and AI trained on quantum output turns it into the engine of scientific discovery.

desk verdict A readable opinion essay about measurement-only quantum computing, but it makes no testable claims and rests on an unsupported AI-driven economic story; fine as a column, not as a research contribution. read the letter →

arxiv 2412.18726 v1 pith:6647NTUW submitted 2024-12-25 quant-ph cond-mat.mes-hall

Charles Tahan This is my paper · ORCID
classification quant-phcond-mat.mes-hall
keywords quantumcomputingjointmeasurementmeasurement-basedcomputationerrorcorrectionencodedqubitslargesciencemodelshardwaresimplificationsolid-state
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper is a deliberately speculative retrospective from 2040, not a review. Its central claim is that the simplest useful quantum computer will have exactly one type of gate: a high-fidelity, repeatable, fast joint measurement of several qubits, with no separate one- or two-qubit gates. The author argues that such measurement-only machines are universal for quantum computation and that this simplification, driven by AI that is trained on quantum-processor output, is what makes quantum computers economically viable as scientific discovery engines. A sympathetic reader should take the essay as a hypothesis about how to cut hardware and control complexity, not as a report of results.

What carries the argument

The central object is the joint (multi-qubit) measurement used as the only computational gate. In this scheme a qubit's state is encoded into a subspace of several physical qubits, and computation proceeds by measurements that consume some entanglement while leaving enough behind to keep driving the process (as in fusion-based or topological schemes). The essay also treats Large Science Models trained on quantum data as the mechanism that turns technical feasibility into economic and scientific value.

What would settle it

Run the same large science model on identical scientific data with and without additional samples generated by a quantum processor (or a reliable classical simulation of one); if the quantum-trained model shows no measurable improvement in chemistry, materials, or physics prediction, the economic claim is falsified. Separately, building a small encoded quantum error-correction cycle that uses only joint measurements and showing it cannot sustain a logical qubit would falsify the technical claim.

Watch

Extended reading notes

Core claim

The essay's core claim is that joint measurements alone are sufficient to drive quantum computation, so a computer optimized around one gate type replaces the usual universal gate set. The author marshals a lineage: encoding lets qubits be controlled by exchange alone; photonic fusion and topological measurement gates make joint measurement the natural operation; and monitored-system physics connects measurement with error correction. Once measurement is the single gate, the design target becomes fast, stable, low-power readout rather than increasingly perfect two-qubit interactions. The second half of the claim is that large classical AI models trained on quantum-processor output become better at all science, which provides the economic forcing function that makes building these machines worthwhile.

Load-bearing premise

The load-bearing premise is that training large AI science models on quantum-computer output makes them dramatically better at all science, a claim the essay states as a 2040 discovery without giving evidence.

Editorial extensions

If this is right

  • Hardware development would concentrate on making one joint-measurement gate fast, stable, and repeatable rather than perfecting many gate types.
  • Readout speed and drift, not two-qubit gate fidelity, become the main cost drivers and the main targets for error-correction overhead.
  • The usual five criteria for a physical quantum computer effectively compress into one: good joint measurements, with encoding and feed-forward supplying the rest.
  • Quantum computers would first pay for themselves as scientific instruments that generate training data for discovery-oriented AI, rather than as standalone algorithm engines.
  • Platforms with fast, low-power, industry-compatible measurement, such as solid-state qubits, would be favored over atomic or other slow-readout systems.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Editorial inference: the technical half of the claim can be tested on existing spin or superconducting hardware by running small encoded algorithms that use only joint measurements and no entangling gates.
  • Editorial inference: the economic claim about AI training can be probed now with smaller models by comparing classical-only and quantum-augmented training sets on chemistry or materials benchmarks.
  • Editorial inference: even if the AI-training premise fails, the hardware-simplification argument stands on its own, so the two halves should be evaluated separately.
  • Editorial inference: the essay's emphasis on stability over fidelity suggests a direct experiment: holding measurement fidelity fixed while deliberately varying drift should show whether drift, not fidelity, is what limits logical-qubit performance.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. This is an opinion essay written as a retrospective from the year 2040. It argues that the quantum computing field converged on a "simplest quantum computer" in which the only gate type is a joint measurement, replacing separate single- and two-qubit gates, and that Large Science Models (LSMs) trained on quantum-processor outputs provided the economic and scientific "forcing function" that made this architecture viable. The author explicitly disclaims the accuracy of the narrative in footnote 1 and defers all technical details with statements such as "No need to get into that here!"

Significance. If the speculative scenario were correct, it would point to a drastic simplification of quantum hardware and a new economic rationale for quantum computers. The essay is readable and provocative, and it correctly draws attention to real research directions: measurement-based and fusion-based quantum computation, exchange-only encodings, erasure qubits, and the challenge of measurement speed and fidelity. However, it contains no derivations, datasets, or testable protocols. Its future claims are explicitly disclaimed in footnote 1, and the central argument rests on unsupported assertions about both hardware overhead and AI capabilities. As a scientific contribution the paper is therefore not assessable in the usual sense, though it might serve as a thought-provoking piece for a broader opinion-oriented readership.

major comments (3)
  1. [All you need is measurement / Feeding the beast] The central claim that a measurement-only computer with one gate type is a practical "simplest quantum computer" is not supported by the quantitative facts the paper itself cites. The text states that exchange pulses take 1–10 ns, while measurements take roughly 100 µs at 90–99% fidelity, and later admits that "readout was never as good as gates" and "even two-qubit gates could be way better, and faster." No encoding overhead, logical error-rate estimate, or wall-clock resource comparison is provided to show that a measurement-only logical architecture can be competitive. Because the essay presents this as solving the quantum computing problem, this missing resource analysis is a load-bearing omission rather than a minor gap.
  2. [Feeding the beast] The economic forcing function of the essay is the assertion that Large Science Models trained only on quantum-processor outputs become qualitatively better at all science, with the text admitting "the models got better at all science, and we didn't know why." This is an unexplained causal assumption: no mechanism, training-data description, control comparison against classical-only models, or quantitative evidence is offered. Since the essay states that "this sealed the deal," the entire value proposition collapses if this premise is false. This is an ad hoc axiom rather than a falsifiable prediction.
  3. [Footnote 1 and Section "Value"] The paper explicitly disclaims its own accuracy ("Do not assume that any statement in this article is accurate") and defers all key details: "what the best n-qubit joint measurements turned out to be, how quantum protection emerged, how large science models were trained, etc. Well, that’s a topic for another retrospective. No need to get into that here!" These self-asserted limitations make the central claims unfalsifiable. In a serious scientific journal, an article cannot rest its main conclusion on details that it explicitly refuses to provide; the disclaimer does not cure the absence of support, it confirms it.
minor comments (4)
  1. [All you need is measurement] The essay should briefly note that measurement-only universality is already an established theoretical result (e.g., measurement-based and fusion-based quantum computation), so that readers do not mistake the 2040 retrospective for a new technical proposal.
  2. [General] The transition from the factual 2024 status review to the fictional 2040 narrative is abrupt; a typographic or textual marker beyond the initial footnote would help avoid misinterpretation of the speculative sections as real claims.
  3. [Value] The humorous asides about Elon Musk and "the other Bacon" are clearly intended as satire, but they may be unprofessional for some journal venues; the author should check the journal's style guidelines for opinion content.
  4. [References] Several references have formatting or completeness issues, such as Ref. [16] ending with "Page 184," Ref. [9] containing "au2," and the Qubitzoo reference being only a bare URL; these should be cleaned up if the paper is revised.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the essay is a fictional retrospective with no derivation chain; self-citations supplement rather than constitute its central universality claims.

full rationale

This paper is a speculative opinion essay rather than a derivation, and it contains no equations or fitted parameters whose outputs could reduce to their inputs. The central claim that joint measurements alone are universal for quantum computation is supported by independent references, including measurement-based quantum computation [34], fusion-based photonic computation [26], and anyonic fusion/measurement gates [25], while the author's self-citations in [27, 28, 32, 33] are ancillary illustrations that particular solid-state qubit platforms can be operated in a measurement-based way. Those self-citations point to externally published, peer-reviewed results and are not the sole or load-bearing justification for universality. The economic and scientific case, namely that Large Science Models trained on quantum-processor output improve at all science, is explicitly presented as a fictional discovery within the retrospective ('And the greatest surprise: the models got better at all science, and we didn't know why'), with no mechanism offered; that is unsupported speculation rather than circular reasoning. Footnote 1 disclaims accuracy and testability, which further removes any pretense of a forced derivation. No step of the argument quotes an equation or definitional identity that would make a prediction equivalent to its input. Therefore the appropriate finding is no significant circularity.

Assumptions & free parameters 0 free parameters · 4 assumptions · 1 invented entities

The essay rests on established quantum information results (measurement-based computation, erasure-error thresholds, biased-noise thresholds) and on one unsupported future claim, the quantum-trained AI advantage. No free parameters or fitted constants appear. The only invented concept is the Large Science Model extrapolation.

assumptions (4)
  • standard math Universal quantum computation can be driven by joint measurements alone.
    Invoked throughout the essay; established in measurement-based quantum computation [34], fusion-based quantum computation [26], and measurement-only topological gates [25]. The essay does not reprove it.
  • standard math Erasure-type errors have higher quantum error correction thresholds.
    Used to argue that slow or imperfect measurements can be tolerable; cites Knill et al. [23].
  • standard math Biased noise with uniform error characteristics improves error correction thresholds.
    Used to motivate moving to a single measurement gate type; cites Tuckett et al. [35].
  • ad hoc to paper Large Science Models trained on quantum-processor outputs become qualitatively better at all science.
    Asserts the 2040 forcing function with no data or derivation; central to the economic argument in the "Feeding the beast" section.
invented entities (1)
  • Large Science Models (LSMs), quantum-trained AI systems
    purpose: Serve as the economic forcing function and source of qualitative scientific improvement in the 2040 narrative.
    No evidence outside the essay; the author presents them as a future discovery. They are a conceptual invention rather than a physical entity, but they carry the main speculative weight.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Opinion: The simplest quantum computer." pith.science (2026). https://pith.science/paper/6647NTUW

@misc{pith2026241218726,
  author       = {Pith},
  title        = {Pith review of: Opinion: The simplest quantum computer},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/6647NTUW}},
  note         = {Machine review of arXiv:2412.18726}
}
read the original abstract

Instead of writing a review article on the state of the field, I'm going to instead write a retrospective from the year 2040. I'll tell you how this whole "quantum computing thing" turned out.

Figures

Figures reproduced from arXiv: 2412.18726 by the authors.

Figure 1
Figure 1. A slide from talks I gave circa 2023. a handful of systems, usually with the aid of post-selection [6, 7]. These demonstrations checked many boxes on the path toward proving that the theories of fault tolerant and quantum error corrected quantum computation were valid. Other qubit systems with long-term promise such as photonic-based or topological qubits were approaching critical demonstrations. Finally, published … view at source ↗
Figure 2
Figure 2. The original DiVincenzo criteria for physical implementations of quantum computers com [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. The Hilbert space of a quantum system is exponentially large yet most systems in real life [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

43 extracted references · 37 canonical work pages

  1. [1]

    Simulating physics with computers

    Richard P. Feynman. “Simulating physics with computers”. International Journal of Theoretical Physics 21, 467–488 (1982)

    work page 1982

  2. [2]

    The physical implementation of quantum computation

    David P. DiVincenzo. “The physical implementation of quantum computation”. Fortschritte der Physik48, 771–783 (2000)

    work page 2000

  3. [3]

    High-fidelity, frequency-flexible two-qubit fluxonium gates with a transmon coupler

    Leon Ding, Max Hays, Youngkyu Sung, Bharath Kannan, Junyoung An, Agustin Di Paolo, Amir H. Karamlou, Thomas M. Hazard, Kate Azar, David K. Kim, Bethany M. Niedzielski, Alexander Melville, Mollie E. Schwartz, Jonilyn L. Yoder, Terry P. Orlando, Simon Gustavsson, Jeffrey A. Grover, Kyle Serniak, and William D. Oliver. “High-fidelity, frequency-flexible two-...

    work page 2023

  4. [4]

    Review of performance metrics of spin qubits in gated semiconducting nanostructures

    Peter Stano and Daniel Loss. “Review of performance metrics of spin qubits in gated semiconducting nanostructures”. Nature Reviews Physics4, 672–688 (2022)

    work page 2022

  5. [5]

    High-fidelity parallel entangling gates on a neutral-atom quantum computer

    Simon J. Evered, Dolev Bluvstein, Marcin Kalinowski, Sepehr Ebadi, Tom Manovitz, Hengyun Zhou, Sophie H. Li, Alexandra A. Geim, Tout T. Wang, Nishad Maskara, Harry Levine, Giulia Semeghini, Markus Greiner, Vladan Vuletić, and Mikhail D. Lukin. “High-fidelity parallel entangling gates on a neutral-atom quantum computer”. Nature 622, 268–272 (2023)

    work page 2023

  6. [6]

    Logical quantum processor based on reconfigurable atom arrays

    Dolev Bluvstein, Simon J. Evered, Alexandra A. Geim, Sophie H. Li, Hengyun Zhou, TomManovitz, SepehrEbadi, MadelynCain, MarcinKalinowski, DominikHangleiter, J.PabloBonillaAtaides, NishadMaskara, IrisCong, XunGao, PedroSalesRodriguez, Thomas Karolyshyn, Giulia Semeghini, Michael J. Gullans, Markus Greiner, Vladan Vuletić, and Mikhail D. Lukin. “Logical qua...

    work page 2024

  7. [7]

    Demonstration of logical qubits and repeated error correction with better-than-physical error rates

    M. P. da Silva, C. Ryan-Anderson, J. M. Bello-Rivas, A. Chernoguzov, J. M. Dreiling, C. Foltz, F. Frachon, J. P. Gaebler, T. M. Gatterman, L. Grans-Samuelsson, D. Hayes, N. Hewitt, J. Johansen, D. Lucchetti, M. Mills, S. A. Moses, B. Neyenhuis, A. Paz, J. Pino, P. Siegfried, J. Strabley, A. Sundaram, D. Tom, S. J. Wernli, M. Zanner, R. P. Stutz, and K. M....

    arXiv 2024

  8. [8]

    How to factor 2048 bit rsa integers in 8 hours using 20 million noisy qubits

    Craig Gidney and Martin Ekerå. “How to factor 2048 bit rsa integers in 8 hours using 20 million noisy qubits”. Quantum5 (2021)

    work page 2021

Show all 43 references
  1. [9]

    Quantum 7 simulation of realistic materials in first quantization using non-local pseudopoten- tials

    Dominic W. Berry, Nicholas C. Rubin, Ahmed O. Elnabawy, Gabriele Ahlers, A. Eu- gene DePrince III au2, Joonho Lee, Christian Gogolin, and Ryan Babbush. “Quantum 7 simulation of realistic materials in first quantization using non-local pseudopoten- tials” (2023). arXiv:2312.07654

    2023

  2. [10]

    Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry

    Seunghoon Lee, Joonho Lee, Huanchen Zhai, Yu Tong, Alexander M. Dalzell, Ashutosh Kumar, Phillip Helms, Johnnie Gray, Zhi-Hao Cui, Wenyuan Liu, Michael Kastoryano, Ryan Babbush, John Preskill, David R. Reichman, Earl T. Campbell, Edward F. Valeev, Lin Lin, and Garnet Kin-Lic C...

    2023

  3. [11]

    Drug design on quantum computers

    Raffaele Santagati, Alan Aspuru-Guzik, Ryan Babbush, Matthias Degroote, Leticia González, Elica Kyoseva, Nikolaj Moll, Markus Oppel, Robert M. Parrish, Nicholas C. Rubin, Michael Streif, Christofer S. Tautermann, Horst Weiss, Nathan Wiebe, and Clemens Utschig-Utschig. “Drug de...

    2024

  4. [12]

    Disentangling hype from practicality: On realistically achieving quantum advantage

    Torsten Hoefler, Thomas Haener, and Matthias Troyer. “Disentangling hype from practicality: On realistically achieving quantum advantage” (2023). arXiv:2307.00523

    2023 arXiv

  5. [13]

    Assessing requirements to scale to practical quantum ad- vantage

    Michael E. Beverland, Prakash Murali, Matthias Troyer, Krysta M. Svore, Torsten Hoefler, Vadym Kliuchnikov, Guang Hao Low, Mathias Soeken, Aarthi Sundaram, and Alexander Vaschillo. “Assessing requirements to scale to practical quantum ad- vantage” (2022). arXiv:2211.07629

    2022 arXiv

  6. [14]

    DerivativePricingusingQuantumSignal Processing

    NikitasStamatopoulosandWilliamJ.Zeng. “DerivativePricingusingQuantumSignal Processing”. Quantum 8, 1322 (2024)

    2024

  7. [15]

    Qubitzoo

    “Qubitzoo”. url: https://qubitzoo.org

  8. [16]

    Quantum error correction. in h.k. lo, s. popescu and t.p. spiller, ed- itor, introduction to quantum computation and information, page 184

    A.M. Steane. “Quantum error correction. in h.k. lo, s. popescu and t.p. spiller, ed- itor, introduction to quantum computation and information, page 184.”. Page 184. World Scientific (Singapore). (1999). url:https://www2.physics.ox.ac.uk/sites/ default/files/ErrorCorrectionSte...

    1999

  9. [17]

    Preserving coherence in quantum computation by pairing quantum bits

    Lu-Ming Duan and Guang-Can Guo. “Preserving coherence in quantum computation by pairing quantum bits”. Phys. Rev. Lett.79, 1953–1956 (1997)

    1997

  10. [18]

    Decoherence-freesubspacesandsubsystems

    DanielA.LidarandK.BirgittaWhaley. “Decoherence-freesubspacesandsubsystems”. Pages 83–120. Springer Berlin Heidelberg. Berlin, Heidelberg (2003)

    2003

  11. [19]

    Simple quantum computer

    Isaac L. Chuang and Yoshihisa Yamamoto. “Simple quantum computer”. Phys. Rev. A 52, 3489–3496 (1995)

    1995

  12. [20]

    Universal quantum computation with the exchange interaction

    D. P. DiVincenzo, D. Bacon, J. Kempe, G. Burkard, and K. B. Whaley. “Universal quantum computation with the exchange interaction”. Nature408, 339–342 (2000)

    2000

  13. [21]

    Surface codes: Towards practical large-scale quantum computation

    Austin G. Fowler, Matteo Mariantoni, John M. Martinis, and Andrew N. Cleland. “Surface codes: Towards practical large-scale quantum computation”. Phys. Rev. A 86, 032324 (2012)

    2012

  14. [22]

    Quantum Computing in the NISQ era and beyond

    John Preskill. “Quantum Computing in the NISQ era and beyond”. Quantum 2, 79 (2018)

    2018

  15. [23]

    A scheme for efficient quantum computa- tion with linear optics

    E. Knill, R. Laflamme, and G. J. Milburn. “A scheme for efficient quantum computa- tion with linear optics”. Nature409, 46–52 (2001)

    2001

  16. [24]

    Majorana zero modes and topological quantum computation

    Sankar Das Sarma, Michael Freedman, and Chetan Nayak. “Majorana zero modes and topological quantum computation”. npj Quantum Information1, 15001 (2015). 8

    2015

  17. [25]

    Universal gates via fusion and measurement op- erations on su (2) 4 anyons

    Claire Levaillant, Bela Bauer, Michael Freedman, Zhenghan Wang, and Parsa Bonderson. “Universal gates via fusion and measurement op- erations on su (2) 4 anyons”. Physical Review A 92, 12301 (2015). url: https://www.microsoft.com/en-us/research/publication/ universal-gates-via...

    2015

  18. [26]

    Fusion-based quantum computation

    Sara Bartolucci, Patrick Birchall, Hector Bombín, Hugo Cable, Chris Dawson, Mer- cedes Gimeno-Segovia, Eric Johnston, Konrad Kieling, Naomi Nickerson, Mihir Pant, Fernando Pastawski, Terry Rudolph, and Chris Sparrow. “Fusion-based quantum computation”. Nature Communications14,...

    2023

  19. [27]

    Semiconductor-inspired design principles for su- perconducting quantum computing

    Yun-Pil Shim and Charles Tahan. “Semiconductor-inspired design principles for su- perconducting quantum computing”. Nature Communications7, 11059 (2016)

    2016

  20. [28]

    Universal nonadiabatic control of small-gap superconducting qubits

    Daniel L. Campbell, Yun-Pil Shim, Bharath Kannan, Roni Winik, David K. Kim, Alexander Melville, Bethany M. Niedzielski, Jonilyn L. Yoder, Charles Tahan, Simon Gustavsson, and William D. Oliver. “Universal nonadiabatic control of small-gap superconducting qubits”. Phys. Rev. X1...

    2020

  21. [29]

    Dual-rail encoding with superconducting cavities

    James Teoh, Patrick Winkel, Harshbardhan Babla, and Robert Schoelkopf. “Dual-rail encoding with superconducting cavities”. PNAS (2023)

    2023

  22. [30]

    Demonstrating a long-coherence dual-rail erasure qubit using tunable transmons

    H. Levine, A. Haim, J. S. C. Hung, N. Alidoust, M. Kalaee, L. DeLorenzo, E. A. Wol- lack, P. Arrangoiz-Arriola, A. Khalajhedayati, R. Sanil, H. Moradinejad, Y. Vaknin, A.Kubica, D.Hover, S.Aghaeimeibodi, J.A.Alcid, C.Baek, J.Barnett, K.Bawdekar, P. Bienias, H. A. Carson, C. Ch...

    2024

  23. [31]

    Symmetry Protected Quantum Computation

    Michael H. Freedman, Matthew B. Hastings, and Modjtaba Shokrian Zini. “Symmetry Protected Quantum Computation”. Quantum5, 554 (2021)

    2021

  24. [32]

    Quantum computation by spin-parity measure- ments with encoded spin qubits

    Matthew Brooks and Charles Tahan. “Quantum computation by spin-parity measure- ments with encoded spin qubits”. Phys. Rev. B108, 035206 (2023)

    2023

  25. [33]

    Hybrid exchange–measurement-based qubit operations in semiconductor double-quantum-dot qubits

    Matthew Brooks and Charles Tahan. “Hybrid exchange–measurement-based qubit operations in semiconductor double-quantum-dot qubits”. Phys. Rev. Appl. 16, 064019 (2021)

    2021

  26. [34]

    Measurement-based quantum computation

    H. J. Briegel, D. E. Browne, W. Dür, R. Raussendorf, and M. Van den Nest. “Measurement-based quantum computation”. Nature Physics5, 19–26 (2009)

    2009

  27. [35]

    Ultrahigh error threshold for surface codes with biased noise

    David K. Tuckett, Stephen D. Bartlett, and Steven T. Flammia. “Ultrahigh error threshold for surface codes with biased noise”. Phys. Rev. Lett.120, 050505 (2018). 9

    2018

  28. [36]

    Demonstration of the trapped-ion quantum ccd computer architecture

    J. M. Pino, J. M. Dreiling, C. Figgatt, J. P. Gaebler, S. A. Moses, M. S. Allman, C. H. Baldwin, M. Foss-Feig, D. Hayes, K. Mayer, C. Ryan-Anderson, and B. Neyenhuis. “Demonstration of the trapped-ion quantum ccd computer architecture”. Nature592, 209–213 (2021)

    2021

  29. [37]

    Quantum supremacy using a programmable superconducting processor

    Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C. Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando G. S. L. Brandao, David A. Buell, Brian Burkett, Yu Chen, Zijun Chen, Ben Chiaro, Roberto Collins, William Court- ney, Andrew Dunsworth, Edward Farhi, Brooks...

    2019

  30. [38]

    Random quantum circuits

    Matthew P.A. Fisher, Vedika Khemani, Adam Nahum, and Sagar Vijay. “Random quantum circuits”. Annual Review of Condensed Matter Physics14, 335–379 (2023)

    2023

  31. [39]

    Dynamically Generated Logical Qubits

    Matthew B. Hastings and Jeongwan Haah. “Dynamically Generated Logical Qubits”. Quantum 5, 564 (2021)

    2021

  32. [40]

    Solving the quantum many-body problem with artificial neural networks

    Giuseppe Carleo and Matthias Troyer. “Solving the quantum many-body problem with artificial neural networks”. Science 355, 602–606 (2017). arXiv:https://www.science.org/doi/pdf/10.1126/science.aag2302

    2017 doi

  33. [41]

    Quantum machine learning without any quantum

    Ewin Tang. “Quantum machine learning without any quantum”. PhD thesis. U. Washington, Seattle. (2023)

    2023

  34. [42]

    A practical introduction to tensor networks: Matrix product states and projected entangled pair states

    Román Orús. “A practical introduction to tensor networks: Matrix product states and projected entangled pair states”. Annals of Physics349, 117–158 (2014)

    2014

  35. [43]

    Quantum error correction with only two extra qubits

    Rui Chao and Ben W. Reichardt. “Quantum error correction with only two extra qubits”. Phys. Rev. Lett.121, 050502 (2018). 10

    2018

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.