Mind the gaps: The fraught road to quantum advantage
Pith reviewed 2026-05-18 01:46 UTC · model grok-4.3
The pith
Four hurdles must be cleared to advance from noisy quantum devices to practical fault-tolerant ones.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
Quantum computing is advancing rapidly, yet substantial gaps separate today's noisy intermediate-scale quantum (NISQ) devices from tomorrow's fault-tolerant application-scale quantum (FASQ) machines. The central discovery is the identification of four related hurdles: from error mitigation to active error detection and correction, from rudimentary error correction to scalable fault tolerance, from early heuristics to mature verifiable algorithms, and from exploratory simulators to credible advantage in quantum simulation. Targeting these will accelerate progress toward broadly useful quantum computing.
What carries the argument
The four related hurdles that structure the path from noisy intermediate-scale quantum devices to fault-tolerant application-scale quantum machines.
If this is right
- Efforts should shift from error mitigation to active detection and correction to enable reliable operations.
- Research must scale rudimentary error correction up to full fault tolerance for larger systems.
- Algorithm development should move beyond early heuristics toward mature and verifiable methods.
- Quantum simulations must transition from exploratory work to showing credible advantages over classical approaches.
Where Pith is reading between the lines
- Successfully addressing these hurdles could enable quantum simulations of molecular systems that remain intractable for classical computers.
- This framing of the challenges may help align research priorities and resource allocation across different teams.
- Additional issues around software ecosystems or hardware scaling could surface once these four areas are resolved.
Load-bearing premise
The four listed hurdles are the primary barriers separating current devices from future machines, and that addressing them in sequence will accelerate progress to useful quantum computing.
What would settle it
A demonstration of broad quantum advantage in a practical task that bypasses one or more of the four transitions, such as achieving it with only error mitigation and no active correction.
read the original abstract
Quantum computing is advancing rapidly, yet substantial gaps separate today's noisy intermediate-scale quantum (NISQ) devices from tomorrow's fault-tolerant application-scale quantum (FASQ) machines. We identify four related hurdles along the road ahead: (i) from error mitigation to active error detection and correction, (ii) from rudimentary error correction to scalable fault tolerance, (iii) from early heuristics to mature, verifiable algorithms, and (iv) from exploratory simulators to credible advantage in quantum simulation. Targeting these transitions will accelerate progress toward broadly useful quantum computing.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript is a perspective article that identifies four key transitions required to bridge the gap between current noisy intermediate-scale quantum (NISQ) devices and future fault-tolerant application-scale quantum (FASQ) machines. These are: (i) shifting from error mitigation to active error detection and correction, (ii) advancing from rudimentary error correction to scalable fault tolerance, (iii) moving from early heuristics to mature and verifiable algorithms, and (iv) progressing from exploratory simulators to achieving credible advantage in quantum simulation. The paper concludes that focusing on these areas will accelerate the development of broadly useful quantum computing.
Significance. The paper synthesizes current understanding of the limitations in quantum hardware and algorithms to provide a structured roadmap. Its significance lies in offering a clear classification of challenges that could help direct research efforts in the quantum computing field. As it relies on established domain knowledge rather than new empirical or theoretical results, its value is in the perspective it offers rather than in novel findings.
minor comments (1)
- The abstract could briefly note the intended readership (e.g., experimentalists vs. theorists) to sharpen the framing of the four hurdles.
Simulated Author's Rebuttal
We thank the referee for their positive review and for recommending acceptance of the manuscript. The referee's summary accurately reflects the structure and intent of our perspective article on the four transitions from NISQ to FASQ devices.
Circularity Check
No significant circularity; perspective piece without derivation chain
full rationale
This is an expert perspective article that enumerates four high-level transitions (error mitigation to detection/correction; rudimentary correction to scalable fault tolerance; heuristics to verifiable algorithms; exploratory to credible simulation advantage) and recommends targeting them to accelerate progress. No equations, quantitative predictions, fitted parameters, or load-bearing self-citations appear in the provided text. The central claim is a domain-consensus recommendation rather than a falsifiable derivation that reduces to its own inputs by construction.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption NISQ devices suffer from noise levels that preclude direct fault-tolerant operation at scale
Lean theorems connected to this paper
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IndisputableMonolith.Foundation.DimensionForcingalexander_duality_circle_linking unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
Quantum error correction... surface code... qLDPC codes... logical error rate Plogical ≈ (0.1)(pphys/pthresh)^((d+1)/2)
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IndisputableMonolith.Cost.FunctionalEquationwashburn_uniqueness_aczel unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
Variational quantum algorithms... barren plateau phenomenon... QAOA... DQI
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
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Reference graph
Works this paper leans on
-
[1]
proposed that a machine that computes quantum properties of many strongly interacting particles should be a quantum machine rather than a conventional computer. Dirac’s claim that many-electron problems are too hard to solve (classically) is in some respects misleading. Heuristic classical algorithms for this problem, such as density functional theory [17...
work page 2011
-
[2]
R. P. Feynman, Simulating physics with computers, Int. J. Th. Phys.21, 467 (1982)
work page 1982
-
[3]
R. P. Feynman, Quantum mechanical computers, Found. Phys. 16, 507 (1986)
work page 1986
-
[4]
Deutsch, Quantum theory, the Church-Turing principle and the universal quantum computer, Proc
D. Deutsch, Quantum theory, the Church-Turing principle and the universal quantum computer, Proc. Roy. Soc. A400, 97 (1985)
work page 1985
-
[5]
P. W. Shor, Algorithms for quantum computation: discrete logarithms and factoring, Proc. 50th Ann. Symp. Found. Comp. Sc. , 124 (1994)
work page 1994
-
[6]
Preskill, Quantum computing in the NISQ era and beyond, Quantum2, 79 (2018)
J. Preskill, Quantum computing in the NISQ era and beyond, Quantum2, 79 (2018)
work page 2018
- [7]
-
[8]
P. W. Shor, Scheme for reducing decoherence in quantum com- puter memory, Phys. Rev. A52, R2493 (1995)
work page 1995
-
[9]
P. W. Shor, Fault-tolerant quantum computation, inProceedings of 37th conference on foundations of computer science(IEEE,
-
[10]
J. Lee, D. W. Berry, C. Gidney, W. J. Huggins, J. R. McClean, N. Wiebe, and R. Babbush, Even more efficient quantum com- putations of chemistry through tensor hypercontraction, PRX Quantum2, 030305 (2021)
work page 2021
-
[11]
How to factor 2048 bit RSA integers with less than a million noisy qubits
C. Gidney, How to factor 2048 bit RSA integers with less than a million noisy qubits, (2025), arXiv:2505.15917
work page internal anchor Pith review Pith/arXiv arXiv 2048
-
[12]
Bacon, Software of QIP, by QIP, and for QIP (2022), keynote presentation at QIP 2022
D. Bacon, Software of QIP, by QIP, and for QIP (2022), keynote presentation at QIP 2022
work page 2022
-
[13]
Preskill, Beyond NISQ: The megaquop machine, ACM Trans
J. Preskill, Beyond NISQ: The megaquop machine, ACM Trans. Quant. Comp.6, 1 (2025)
work page 2025
-
[15]
King, Quantum algorithms: A call to action (2025)
R. King, Quantum algorithms: A call to action (2025)
work page 2025
-
[16]
S. Aaronson, A. M. Childs, E. Farhi, A. W. Harrow, and B. C. Sanders, Future of quantum computing, (2025), arXiv:2506.19232
-
[17]
A framework for quantum advantage,
O. Lanes, M. Beji, A. D. Corcoles, C. Dalyac, J. M. Gam- betta, L. Henriet, A. Javadi-Abhari, A. Kandala, A. Mezzacapo, C. Porter,et al., A framework for quantum advantage, (2025), arXiv:2506.20658
- [18]
-
[19]
E. Kapit, P. Love, J. Larson, A. Sornborger, E. Crane, A. Schuckert, T. Tomesh, F. Chong, and S. Kais, Roadblocks and opportunities in quantum algorithms – insights from the National Quantum Initiative Joint Algorithms Workshop, May 20-22, 2024, (2025), arXiv:2508.13973
- [20]
-
[21]
H. Haeffner, C. F. Roos, and R. Blatt, Quantum computing with trapped ions, Phys. Rep.469, 155 (2008)
work page 2008
-
[22]
J.-S. Chen, E. Nielsen, M. Ebert, V . Inlek, K. Wright, V . Chap- lin, A. Maksymov, E. Páez, A. Poudel, P. Maunz, and J. Gamble, Benchmarking a trapped-ion quantum computer with 30 qubits, Quantum8, 1516 (2024)
work page 2024
-
[23]
DeCrosset al., Computational power of random quan- tum circuits in arbitrary geometries, Phys
M. DeCrosset al., Computational power of random quan- tum circuits in arbitrary geometries, Phys. Rev. X15, 021052 (2025)
work page 2025
-
[24]
Quantum error correction below the su rface-code threshold
R. Acharyaet al., Quantum error correction below the surface code threshold, (2024), arxiv:2408.13687
-
[25]
Castelvecchi, IBM releases first-ever 1,000-qubit quantum chip, Nature624, 238 (2023)
D. Castelvecchi, IBM releases first-ever 1,000-qubit quantum chip, Nature624, 238 (2023)
work page 2023
- [26]
-
[27]
H. Bernien, S. Schwartz, A. Keesling, H. Levine, A. Omran, H. Pichler, S. Choi, A. S. Zibrov, M. Endres, M. Greiner, V . Vuletic, and M. Lukin, Probing many-body dynamics on a 51-atom quantum simulator, Nature551, 579 (2017)
work page 2017
-
[28]
D. Bluvstein, S. J. Evered, A. A. Geim, S. H. Li, H. Zhou, T. Manovitz, S. Ebadi, M. Cain, M. Kalinowski, D. Hangleiter, J. P. Bonilla Ataides, N. Maskara, I. Cong, X. Gao, P. S. Rodriguez, T. Karolyshyn, G. Semeghini, M. J. Gullans, M. Greiner, V . Vuletic, and M. D. Lukin, Logical quantum processor based on reconfigurable atom arrays, Nature626, 58 (2024)
work page 2024
-
[29]
M. Saffman, T. G. Walker, and K. Mølmer, Quantum informa- tion with Rydberg atoms, Rev. Mod. Phys.82, 2313 (2010)
work page 2010
-
[30]
S. J. Evered, D. Bluvstein, M. Kalinowski, S. Ebadi, T. Manovitz, H. Zhou, S. H. Li, A. A. Geim, T. T. Wang, N. Maskara, H. Levine, G. Semeghini, M. Greiner, V . Vuleti´c, and M. D. Lukin, High-fidelity parallel entangling gates on a neutral-atom quantum computer, Nature622, 268 (2023)
work page 2023
-
[31]
High-fidelity collisional quantum gates with fermionic atoms
P. Bojovi´c, T. Hilker, S. Wang, J. Obermeyer, M. Barendregt, D. Tell, T. Chalopin, P. M. Preiss, I. Bloch, and T. Franz, High- fidelity collisional quantum gates with fermionic atoms, (2025), arXiv:2506.14711
work page internal anchor Pith review Pith/arXiv arXiv 2025
-
[32]
M. Liu, R. Shaydulin, P. Niroula, M. DeCross, S.-H. Hung, W. Y . Kon, E. Cervero-Martín, K. Chakraborty, O. Amer, S. Aaronson,et al., Certified randomness using a trapped-ion quantum processor, Nature618, 500 (2025)
work page 2025
-
[33]
Y . Kim, A. Eddins, S. Anand, K. X. Wei, E. Van Den Berg, S. Rosenblatt, H. Nayfeh, Y . Wu, M. Zaletel, K. Temme,et al., Evidence for the utility of quantum computing before fault tolerance, Nature618, 500 (2023)
work page 2023
- [34]
-
[35]
E. Knill, Leibfried, R. Reichle, J. Britton, R. B. Blakestad, J., Jost, C. Langer, R. Ozeri, S. Seidelin, and J. Wineland, Randomized benchmarking of quantum gates, Phys. Rev. A77, 012307 (2008)
work page 2008
- [36]
-
[37]
A. Hashim, L. B. Nguyen, N. Goss, B. Marinelli, R. K. Naik, T. Chistolini, J. Hines, J. Marceaux, Y . Kim, P. Gokhale, T. Tomesh, S. Chen, L. Jiang, S. Ferracin, K. Rudinger, T. Proc- tor, K. C. Young, I. Siddiqi, and R. Blume-Kohout, Practical introduction to benchmarking and characterization of quantum computers, PRX Quantum6, 030202 (2025)
work page 2025
-
[38]
IQM, IQM quantum computers achieves new technology mile- stones with 99.9% 2-qubit gate fidelity and 1 millisecond co- herence time (2024)
work page 2024
-
[39]
Google Quantum AI, Willow spec sheet (2024)
work page 2024
-
[40]
T. M. Graham, Y . Song, J. Scott, C. Poole, L. Phuttitarn, K. Jooya, P. Eichler, X. Jiang, A. Marra, B. Grinkemeyer, M. Kwon, M. Ebert, J. Cherek, M. T. Lichtman, M. Gillette, J. Gilbert, D. Bowman, T. Ballance, C. Campbell, E. D. Dahl, O. Crawford, N. S. Blunt, B. Rogers, T. Noel, and M. Saffman, Multi-qubit entanglement and algorithms on a neutral-atom ...
work page 2022
-
[41]
D. A. Rower, L. Ding, H. Zhang, M. Hays, J. An, P. M. Harring- ton, I. T. Rosen, J. M. Gertler, T. M. Hazard, B. M. Niedzielski, M. E. Schwartz, S. Gustavsson, K. Serniak, J. A. Grover, and W. D. Oliver, Suppressing counter-rotating errors for fast single- qubit gates with fluxonium, PRX Quantum5, 040342 (2024)
work page 2024
-
[42]
Z. Li, P. Liu, P. Zhao, Z. Mi, H. Xu, X. Liang, T. Su, W. Sun, G. Xue, J.-N. Zhang, W. Liu, Y . Jin, and H. Yu, npj Quant. Inf. 9, 111 (2023)
work page 2023
-
[43]
A. Bengtsson, A. Opremcak, M. Khezri, D. Sank, A. Bourassa, K. J. Satzinger, S. Hong, C. Erickson, B. J. Lester, K. C. Miao, A. N. Korotkov, J. Kelly, Z. Chen, and P. V . Klimov, Model- based optimization of superconducting qubit readout, Phys. Rev. Lett.132, 100603 (2024)
work page 2024
-
[44]
Neven, Meet willow, our state-of-the-art quantum chip (2024)
H. Neven, Meet willow, our state-of-the-art quantum chip (2024)
work page 2024
-
[45]
D. Gao, D. Fan, C. Zha, J. Bei, G. Cai, J. Cai, S. Cao, F. Chen, J. Chen, K. Chen,et al., Establishing a new benchmark in quantum computational advantage with 105-qubit Zuchongzhi 3.0 processor, Phys. Rev. Lett.134, 090601 (2025)
work page 2025
-
[46]
IBM Newsroom, IBM launches its most advanced quantum computers, fueling new scientific value and progress towards quantum advantage (2024)
work page 2024
-
[47]
Y . Quek, D. S. França, S. Khatri, J. J. Meyer, and J. Eisert, Exponentially tighter bounds on limitations of quantum error, mitigation, Nature Phys.20, 1648 (2024)
work page 2024
-
[48]
T. Schuster, C. Yin, X. Gao, and N. Y . Yao, A polynomial- time classical algorithm for noisy quantum circuits, (2024), arXiv:2407.12768
- [49]
-
[50]
A. Deshpande, P. Niroula, O. Shtanko, A. V . Gorshkov, B. Fef- ferman, and M. J. Gullans, Tight bounds on the convergence of noisy random circuits to the uniform distribution, PRX Quan- tum3, 040329 (2022). 13
work page 2022
-
[51]
D. Stilck Franca and R. García-Patrón, Limitations of optimiza- tion algorithms on noisy quantum devices, Nature Phys.17, 1221 (2020)
work page 2020
-
[52]
M. Ben-Or, D. Gottesman, and A. Hassidim, Quantum refriger- ator, arXiv (2013), arXiv:1301.1995
work page internal anchor Pith review Pith/arXiv arXiv 2013
-
[53]
Simulating quantum circuits with arbitrary local noise using Pauli Propagation
A. Angrisani, A. A. Mele, M. S. Rudolph, M. Cerezo, and Z. Holmes, Simulating quantum circuits with arbitrary local noise using Pauli propagation, (2025), arxiv:2501.13101
work page internal anchor Pith review Pith/arXiv arXiv 2025
-
[54]
Z. Cai, R. Babbush, S. C. Benjamin, S. Endo, W. J. Huggins, Y . Li, J. R. McClean, and T. E. O’Brien, Quantum error mitiga- tion, Rev. Mod. Phys.95, 045005 (2023)
work page 2023
-
[55]
T. Giurgica-Tiron, Y . Hindy, R. LaRose, A. Mari, and W. J. Zeng, Digital zero noise extrapolation for quantum error miti- gation, 2020 IEEE Int. Conf. Quant. Comp. Eng. (QCE) , 306 (2020)
work page 2020
-
[56]
A. Mari, N. Shammah, and W. J. Zeng, Extending quantum probabilistic error cancellation by noise scaling, Phys. Rev. A 104, 052607 (2021)
work page 2021
-
[57]
R. LaRose, A. Mari, S. Kaiser, P. J. Karalekas, A. A. Alves, P. Czarnik, M. E. Mandouh, M. H. Gordon, Y . Hindy, A. Robert- son, P. Thakre, M. Wahl, D. Samuel, R. Mistri, M. Tremblay, N. Gardner, N. T. Stemen, N. Shammah, and W. J. Zeng, Mi- tiq: A software package for error mitigation on noisy quantum computers, Quantum6, 774 (2022)
work page 2022
-
[58]
J. R. McClean, Z. Jiang, N. C. Rubin, R. Babbush, and H. Neven, Decoding quantum errors with subspace expansions, Nature Comm.11, 636 (2020)
work page 2020
-
[59]
F. B. Maciejewski, Z. Zimborás, and M. Oszmaniec, Mitigation of readout noise in near-term quantum devices by classical post-processing based on detector tomography, Quantum4, 257 (2020)
work page 2020
- [60]
-
[61]
Exponen- tially tighter bounds on limitations of quantum er- ror mitigation,
R. Takagi, S. Endo, S. Minagawa, and M. Gu, Fundamental lim- its of quantum error mitigation, npj Quant. Inf.8, 114 (2022), arXiv:2210.11505
-
[62]
On the importance of er- ror mitigation for quantum computation,
D. Aharonov, O. Alberton, I. Arad, Y . Atia, E. Bairey, Z. Brak- erski, I. Cohen, O. Golan, I. Gurwich, O. Kenneth,et al., On the importance of error mitigation for quantum computation, (2025), arXiv:2503.17243
-
[63]
Reliable high-accuracy error mitigation for utility-scale quantum circuits
D. Aharonov, O. Alberton, I. Arad, Y . Atia, E. Bairey, M. B. Dov, A. Berkovitch, Z. Brakerski, I. Cohen, E. Fuchs,et al., Re- liable high-accuracy error mitigation for utility-scale quantum circuits, (2025), arXiv:2508.10997
work page internal anchor Pith review Pith/arXiv arXiv 2025
- [64]
-
[65]
A. Seif, Z.-P. Cian, S. Zhou, S. Chen, and L. Jiang, Shadow distillation: Quantum error mitigation with classical shadows for near-term quantum processors, PRX Quantum4, 010303 (2023)
work page 2023
-
[66]
W. J. Huggins, S. McArdle, T. E. O’Brien, J. Lee, N. C. Rubin, S. Boixo, K. B. Whaley, R. Babbush, and J. R. McClean, Vir- tual distillation for quantum error mitigation, Phys. Rev. X11, 041036 (2021)
work page 2021
-
[67]
Koczor, Exponential error suppression for near-term quan- tum devices, Phys
B. Koczor, Exponential error suppression for near-term quan- tum devices, Phys. Rev. X11, 031057 (2021)
work page 2021
-
[68]
E. Onorati, J. Kitzinger, J. Helsen, M. Ioannou, A. H. Werner, I. Roth, and J. Eisert, Noise-mitigated randomized mea- surements and self-calibrating shadow estimation, (2024), arXiv:2403.04751
- [69]
-
[70]
M. A. Wahl, A. Mari, N. Shammah, W. J. Zeng, and G. S. Ravi, Zero noise extrapolation on logical qubits by scaling the error correction code distance, 2023 IEEE Int. Conf. Quant. Comp. Eng. (QCE)1, 888 (2023)
work page 2023
- [71]
- [72]
-
[73]
B. M. Terhal, Quantum error correction for quantum memories, Rev. Mod. Phys.87, 307 (2015)
work page 2015
-
[74]
E. T. Campbell, B. M. Terhal, and C. Vuillot, Roads towards fault-tolerant universal quantum computation, Nature549, 172 (2017)
work page 2017
-
[75]
Roffe, Quantum error correction: An introductory guide, Contemp
J. Roffe, Quantum error correction: An introductory guide, Contemp. Phys.60, 226 (2019)
work page 2019
-
[76]
A. M. Steane, Error correcting codes in quantum theory, Phys. Rev. Lett.77, 793 (1996)
work page 1996
-
[77]
D. Aharonov and M. Ben-Or, Fault-tolerant quantum compu- tation with constant error, STOC ’97: Proc. 29th Ann. ACM Symp. Th. Comp. , 176
- [78]
-
[79]
Preskill, Reliable quantum computers, Proc
J. Preskill, Reliable quantum computers, Proc. Roy. Soc. Lond. A454, 385 (1998)
work page 1998
-
[80]
B. Eastin and E. Knill, Restrictions on transversal encoded quantum gate sets, Phys. Rev. Lett.102, 110502 (2009)
work page 2009
-
[81]
A. Y . Kitaev, Anyons in an exactly solved model and beyond, Ann. Phys.321, 2 (2006)
work page 2006
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