REVIEW 4 major objections 4 minor 27 references
Tight bound for the total time in digital-analog quantum computation
T0 review · 4 major / 4 minor · reviewed 2026-08-03 · deepseek-v4-flash
Pith's one-line read Digital-analog quantum computation has a tight worst-case time bound: any compatible two-body Hamiltonian can be implemented in total analog time at most T√3 times the 2-norm of the coupling ratios, and some three-coupling problems require
desk verdict The claimed √3 bound is fresh and plausible, but the all-n proof is asserted rather than shown; the paper is a promising draft, not a theorem. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The key object is the convex polytope M whose vertices are the columns of the sign matrix M, which encodes the sign flips produced by single-qubit Pauli gates sandwiching each analog block. Solving a DAQC problem b = T h^P ⊘ h^S as M t = b, t ≥ 0, is equivalent to writing b as a positive combination of those vertices; the optimal total time ∥t∥_1 is the scale factor needed to bring b onto the polytope's surface. The argument reduces the worst-case time to the minimal Euclidean distance from the origin to a facet of M, which is verified for small n to occur on the n=3 embedded tetrahedron. The recursive structure M(n+1) = [[L,L'],[M(n),M(n)]] carries the extension, with the new couplings para
What would settle it
Compute exactly, for the ZZ-Ising polytope with n=8 qubits, the minimum Euclidean distance from the origin to any facet (the columns of M are the vertices, so the closest facet gives the worst-case rescaling). If that distance, after normalizing the columns appropriately, is smaller than the corresponding distance for the embedded n=3 tetrahedron—i.e., if a problem b can be found with ∥t_opt∥_1 > T√3∥hP⊘hS∥2—then the claimed bound fails; the authors' own facet calculations stop at n=7.
Extended reading notes
Core claim
The central claim is Theorem 1: for any problem Hamiltonian H_P compatible with a source Hamiltonian H_S, an optimal DAQC schedule exists with ∥t_opt∥_1 ≤ T√3 ∥h^P ⊘ h^S∥_2, where h^P and h^S are the vectors of the Hamiltonian couplings. The proof treats the columns of the sign matrix M as vertices of a convex polytope containing the origin; any problem vector b is a positive rescaling of a surface point of that polytope, and the optimal total time equals the rescaling factor. The paper identifies the worst facets as those belonging to the smallest non-trivial system: for ZZ Hamiltonians this is n=3, where the polytope is a regular tetrahedron and the closest facets correspond to four sign p
Load-bearing premise
The proof depends on an induction step that is asserted rather than fully demonstrated: the authors assume that for any number of qubits, the worst-case problem is the n=3 all-to-all problem embedded in the larger system, with all newly added couplings set to zero; the manuscript states this explicitly and gives only a sketch for n≥8.
Editorial extensions
If this is right
- Any DAQC protocol with a compatible source Hamiltonian can be compiled with total analog time bounded by T√3 times the 2-norm of the coupling ratios, giving a direct resource estimate independent of the number of qubits except through that norm.
- The bound is tight: some all-to-all problems with only three non-zero couplings require the full amount, so the constant √3 cannot be improved without restricting the problem class.
- The result yields a two-sided characterization T∥hP⊘hS∥∞ ≤ ∥t_opt∥_1 ≤ T√3∥hP⊘hS∥2, with both endpoints achieved by explicit problems.
- For all-to-all Hamiltonians, the 2-norm of the coupling ratios grows as the square root of the number of couplings, so the worst-case DAQC time scales linearly with the number of qubits, confirming the earlier conjecture's linear scaling though with a different constant and norm.
- It also disproves a previously conjectured sharp bound based on the ∞-norm and n or n−1, providing a concrete counter-example.
- The authors argue the result carries over to arbitrary two-body Hamiltonians and to DAQC protocols with fixed or arbitrary single-qubit rotations, since Pauli-based protocols give the worst case.
Reading between the lines
- If the recursive step holds for all n, the same geometric inradius argument should extend to other gate sets and non-Pauli sign-flipping operations, giving similar √3-type constants wherever the worst-case polytope is the smallest non-trivial one.
- The polytope-inradius perspective suggests a practical way to generate hard DAQC instances: problems whose direction is perpendicular to the closest facets of M, which could be found for moderate system sizes by solving the facet-closest-point problem without full facet enumeration.
- A direct device-level test is possible on small processors: compiling the identified worst-case problems (three equal-magnitude couplings of opposite sign on three qubits) should reproduce the √3 saturation; deviations would reveal gaps between the compilation model and hardware constraints such as finite gate speed or crosstalk.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper studies digital-analog quantum computation (DAQC) and proposes a tight upper bound on the total analog evolution time required to simulate an arbitrary two-body Hamiltonian. After vectorizing Hamiltonians, the compilation problem is reduced to solving M t = b with t ≥ 0, where M is a sign-pattern matrix. The authors' main result, Theorem 1, states that for any compatible target and source Hamiltonian, ∥t_opt∥_1 ≤ T√3 ∥h^P ⊘ h^S∥_2, and that the bound is tight, realized by problems with three non-zero couplings. The proof is based on a geometric interpretation: the columns of M generate a polytope whose inradius would need to be at least 1/√3. The paper verifies the n=3 case exactly, gives numerical evidence for moderate n, and extends the claim to arbitrary two-body Hamiltonians. It also states that the previous Baßler-Heinrich-Kliesch bound is not optimal and that a counterexample is provided.
Significance. If Theorem 1 were rigorously established, the result would be a clean, parameter-free bound on DAQC time resources, scaling linearly with the number of qubits for all-to-all Hamiltonians and only polylogarithmically in the number of couplings in typical cases. The geometric reformulation in terms of the inradius of the DAQC sign-pattern polytope is appealing and could be a useful tool for future work. The paper also contains careful exact or numerical information for small system sizes. However, the central theorem for arbitrary n is not proven: the key inductive step is explicitly assumed, not derived, and no counterexample to the BHK conjecture is actually exhibited. The claimed tightness and the claimed improvement over the previous bound therefore remain unsupported. The numerical experiments are suggestive but cannot replace a proof of the general statement.
major comments (4)
- [Section II.A, proof of Theorem 1] The induction proving the bound for all n is asserted, not demonstrated. The text says, 'we assume that the worst problem corresponds to an n=3 all-to-all problem embedded in a larger system, and assume that this holds up to n qubits,' and later 'we can extend the upper bound to arbitrary n.' This does not bound the new facets introduced when adding a qubit, nor does it justify that the n=3 configuration remains the closest facet to the origin. Exact facet information is reported only for n≤7 for ZZ Hamiltonians and n≤4 for arbitrary two-body Hamiltonians. Hence Theorem 1 for general n is not proven by the manuscript.
- [Section II.A, paragraph beginning 'For any b̃'] The proof that a boundary point b̃ must have minimal 1-norm equal to 1 contains a scaling error. If M t = b̃ with ∥t∥_1 = ξ < 1, the proposed t' = (2−ξ)t satisfies ∥t'∥_1 = (2−ξ)ξ, not 1. The contradiction therefore does not follow as written. A correct argument could rescale by 1/ξ and use convexity, but that argument is not given. This is a load-bearing step in the geometric reduction.
- [Introduction and Conclusion] The paper states that the BHK conjecture is 'actually not optimal' and that a counterexample is provided, but no explicit counterexample appears. The n=3 worst-case vector b = (−α,−α,−α) gives ∥t_opt∥_1 = T√3∥b∥_2 = 3Tα, which equals the BHK bound for odd n=3 and is smaller than the BHK bound for larger n. Thus this example does not violate Conjecture 1. No explicit problem is exhibited for which ∥t_opt∥_1 exceeds the BHK bound.
- [Section II.A, arbitrary two-body Hamiltonians] The extension to arbitrary two-body Hamiltonians lacks a verified base case for n=2. The text states that n=2 is non-trivial and identifies candidate worst directions, but it does not compute the facets or the inradius for the 9-dimensional polytope. Since the subsequent argument again relies on the same assumed induction for ZZ Hamiltonians, the general theorem is not established beyond the explicitly checked small cases.
minor comments (4)
- [Abstract] The phrase 'linear dependence with the number of couplings' is inaccurate: for equal-magnitude couplings the 2-norm grows as sqrt(N_couplings), not linearly in N_couplings. The scaling is linear in the number of qubits for all-to-all Hamiltonians.
- [Section II] Typo: 'Firsly' should be 'Firstly'.
- [Eq. (7), notation] The notation M ∈ M_{d,d'}(±1) is nonstandard; it would be clearer to state that M is a d×d' matrix with ±1 entries and full row rank.
- [Section II.B and figures] The description of the numerical generation of 'green' problems is imprecise ('close to the axes' with 'a maximum of 6 nonzero elements'). Please specify the exact distribution to make the numerical results reproducible.
Circularity Check
No circular derivation; the all-n induction is asserted rather than proved, which is a rigor gap, not a circular reduction.
full rationale
The paper's central bound ||t_opt||_1 ≤ T√3||h^P ⊘ h^S||_2 is derived from a geometric inradius claim about the DAQC sign-pattern polytope. The n=3 case is computed exactly (regular tetrahedron). For larger n, the proof attempts an induction, but explicitly states 'we assume that the worst problem corresponds to an n=3 all-to-all problem embedded in a larger system, and assume that this holds up to n qubits' (Section II.A). This is an unproven assumption used as the inductive step, not a circular use of the theorem's conclusion: the theorem's upper bound and tightness would follow if the assumption were proved, but the paper does not prove it. This is a completeness/rigor gap, not a reduction by construction. The self-citation to Ref. [22] for the fact that the sign-pattern columns span R^d and the polytope contains the origin is independent support (prior work established universality, not the time bound), so it does not constitute circularity. Numerical checks are confirmatory and do not fit parameters into the bound. No fitted input is renamed as a prediction, and no result is forced by definition or by a self-citation chain. Thus no circular step is exhibited.
Assumptions & free parameters
assumptions (3)
- domain assumption For any compatible H_P and H_S, the columns of the sign-pattern matrix M span R^d and the origin lies in the interior of their convex hull (universality of DAQC).
- ad hoc to paper The Euclidean inradius of the DAQC polytope is at least 1/√3 for all n.
- standard math The polyhedral gauge (minimal 1-norm of positive coefficients) of a boundary point is 1.
Cite this review
Pith. "Pith review of Tight bound for the total time in digital-analog quantum computation." pith.science (2026). https://pith.science/paper/QIH532TZ
@misc{pith2026251211619,
author = {Pith},
title = {Pith review of: Tight bound for the total time in digital-analog quantum computation},
year = {2026},
howpublished = {\url{https://pith.science/paper/QIH532TZ}},
note = {Machine review of arXiv:2512.11619}
}
read the original abstract
Digital-analog quantum computing (DAQC) is a universal computational paradigm that combines the evolution under an entangling Hamiltonian with the application of single-qubit gates. Since any unitary operation can be decomposed into a sequence of evolutions generated by two-body Hamiltonians, DAQC is inherently well-suited for realizing such operations. Suboptimal upper bounds for the total time required to perform these evolutions have been previously proposed. Here, we improve these limits by providing a tight bound for this crucial parameter, which shows a linear dependence with the number of couplings. This result enables a precise estimation of the time resources needed for quantum simulations and quantum algorithms implemented within the DAQC framework, facilitating a rigorous comparison with other approaches.
Figures
Reference graph
Works this paper leans on
-
[22]
or fixed rotation angles [6, 22, 23], as the protocols composed of Pauli gates are the worst of the three. This allows us to estimate the time resources needed to perform a simulation with DAQC, further allowing us to compare it with the time needed for its DQC counterpart. We provide an answer to an open question and confirm the previous intuition regard...
arXiv 2020
-
[1]
Quan- tum simulation,
Iulia Georgescu, Sahel Ashhab, and Franco Nori, “Quan- tum simulation,” Rev. Mod. Phys.86, 153–185 (2014)
2014
-
[2]
Universality in quantum computation,
David Elieser Deutsch, Adriano Barenco, and Artur Ek- ert, “Universality in quantum computation,” Proc. Roy. Soc. Lond. A Math.449, 669–677 (1995)
1995
-
[3]
A quantum-dot array as model for copper-oxide superconductors: A dedicated quantum simulator for the many-fermion problem,
Efstratios Manousakis, “A quantum-dot array as model for copper-oxide superconductors: A dedicated quantum simulator for the many-fermion problem,” Journal of Low Temperature Physics126, 1501–1513 (2002)
2002
-
[4]
Effective quantum spin sys- tems with trapped ions,
D. Porras and J. I. Cirac, “Effective quantum spin sys- tems with trapped ions,” Phys. Rev. Lett.92, 207901 (2004)
2004
-
[5]
Universal quantum compu- tation and simulation using any entangling hamiltonian and local unitaries,
Jennifer L. Dodd, Michael A. Nielsen, Michael J. Brem- ner, and Robert T. Thew, “Universal quantum compu- tation and simulation using any entangling hamiltonian and local unitaries,” Phys. Rev. A65, 040301(R) (2002)
2002
-
[6]
Digital- analog quantum computation,
Adrian Parra-Rodriguez, Pavel Lougovski, Lucas Lamata, Enrique Solano, and Mikel Sanz, “Digital- analog quantum computation,” Phys. Rev. A101, 022305 (2020)
2020
-
[7]
Enhanced connectivity of quantum hardware with digital-analog control,
Asier Galicia, Borja Ramón, Enrique Solano, and Mikel Sanz, “Enhanced connectivity of quantum hardware with digital-analog control,” Phys. Rev. Res.2, 033103 (2020). 7
2020
Show all 27 references
-
[8]
Mitigating noise in digital and digital–analog quantum computation,
Paula García-Molina, Ana Martin, Mikel Garcia de An- doin, and Mikel Sanz, “Mitigating noise in digital and digital–analog quantum computation,” Communications Physics7, 321 (2024)
2024
-
[9]
Bench- marking digital–analog quantum computation for the in- homogeneous two-body ising model,
Vicente Pina Canelles, Manuel G Algaba, Hermanni Hei- monen, Miha Papič, Mario Ponce, Jami Rönkkö, Man- ish J Thapa, Inés de Vega, and Adrian Auer, “Bench- marking digital–analog quantum computation for the in- homogeneous two-body ising model,” Quantum Science and Technology1...
2025
-
[10]
Digital-analog quantum algorithm for the quan- tum Fourier transform,
Ana Martin, Lucas Lamata, Enrique Solano, and Mikel Sanz, “Digital-analog quantum algorithm for the quan- tum Fourier transform,” Phys. Rev. Res.2, 013012 (2020)
2020
-
[11]
Digital- analog co-design of the Harrow-Hassidim-Lloyd algo- rithm,
Ana Martin, Ruben Ibarrondo, and Mikel Sanz, “Digital- analog co-design of the Harrow-Hassidim-Lloyd algo- rithm,” Phys. Rev. Appl.19, 064056 (2023)
2023
-
[12]
Lyapunov con- trolled counterdiabatic quantum optimization,
Pranav Chandarana, Koushik Paul, Kasturi Ranjan Swain, Xi Chen, and Adolfo del Campo, “Lyapunov con- trolled counterdiabatic quantum optimization,” (2024), arXiv:2409.12525 [quant-ph]
2024 arXiv
-
[13]
Digital-analog quantum convolutional neural networks for image classification,
Anton Simen, Carlos Flores-Garrigos, Narendra N. Hegade, Iraitz Montalban, Yolanda Vives-Gilabert, Eric Michon, Qi Zhang, Enrique Solano, and José D. Martín- Guerrero, “Digital-analog quantum convolutional neural networks for image classification,” Phys. Rev. Res.6, L042060 (2024)
2024
-
[14]
Digital-analog quantum simula- tions with superconducting circuits,
Lucas Lamata, Adrian Parra-Rodriguez, Mikel Sanz, and Enrique Solano, “Digital-analog quantum simula- tions with superconducting circuits,” Adv. Phys. X3, 1457981 (2018)
2018
-
[15]
Digital-analog quantum simula- tions using the cross-resonance effect,
Tasio Gonzalez-Raya, Rodrigo Asensio-Perea, Ana Mar- tin, Lucas C. Céleri, Mikel Sanz, Pavel Lougovski, and Eugene F. Dumitrescu, “Digital-analog quantum simula- tions using the cross-resonance effect,” PRX Quantum2, 020328 (2021)
2021
-
[16]
Digital-analog quan- tum genetic algorithm using rydberg-atom arrays,
Aleix Llenas and Lucas Lamata, “Digital-analog quan- tum genetic algorithm using rydberg-atom arrays,” Phys. Rev. A110, 042603 (2024)
2024
-
[17]
Digital-analog coun- terdiabatic quantum optimization with trapped ions,
Shubham Kumar, Narendra N Hegade, Murilo Hen- rique de Oliveira, Enrique Solano, Alejandro Gomez Ca- david, and F Albarrán-Arriagada, “Digital-analog coun- terdiabatic quantum optimization with trapped ions,” Quantum Science and Technology10, 015023 (2024)
2024
-
[18]
Hybriddigital-analogsimulationofmany-body dynamics with superconducting qubits,
Danila V. Babukhin, Andrey A. Zhukov, and Walter V. Pogosov,“Hybriddigital-analogsimulationofmany-body dynamics with superconducting qubits,” Phys. Rev. A 101, 052337 (2020)
2020
-
[19]
Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconductingprocessor,
Ming Gong, He-Liang Huang, Shiyu Wang, Chu Guo, Shaowei Li, Yulin Wu, Qingling Zhu, Youwei Zhao, Shao- jun Guo, Haoran Qian, Yangsen Ye, Chen Zha, Fusheng Chen, Chong Ying,et al., “Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconductingp...
2023
-
[20]
Implementing arbitrary ising models with a trapped-ion quantum processor,
Yao Lu, Wentao Chen, Shuaining Zhang, Kuan Zhang, Jialiang Zhang, Jing-Ning Zhang, and Kihwan Kim, “Implementing arbitrary ising models with a trapped-ion quantum processor,” (2025)
2025
-
[21]
Generalized Trotter’s formula and sys- tematic approximants of exponential operators and inner derivations with applications to many-body problems,
Masuo Suzuki, “Generalized Trotter’s formula and sys- tematic approximants of exponential operators and inner derivations with applications to many-body problems,” Commun. Math. Phys.51, 183–190 (1976)
1976
-
[23]
Digital-analog quantum computation with arbi- trary two-body hamiltonians,
Mikel Garcia-de Andoin, Álvaro Saiz, Pedro Pérez- Fernández, Lucas Lamata, Izaskun Oregi, and Mikel Sanz, “Digital-analog quantum computation with arbi- trary two-body hamiltonians,” Phys. Rev. Res.6, 013280 (2024)
2024
-
[24]
General, effi- cient, and robust hamiltonian engineering,
P. Baßler, M. Heinrich, and M. Kliesch, “General, effi- cient, and robust hamiltonian engineering,” (2025)
2025
-
[25]
Impact and mitiga- tion of hamiltonian characterization errors in digital- analogquantumcomputation,
Mikel Garcia de Andoin, Alatz Álvarez Ahedo, Adrián Franco Rubio, and Mikel Sanz, “Impact and mitiga- tion of hamiltonian characterization errors in digital- analogquantumcomputation,” (2025),arXiv:2505.03642 [quant-ph]
2025
-
[26]
Time-optimal multi-qubit gates: Complexity, effi- cient heuristic and gate-time bounds,
Pascal Baßler, Markus Heinrich, and Martin Kli- esch, “Time-optimal multi-qubit gates: Complexity, effi- cient heuristic and gate-time bounds,” Quantum8, 1279 (2024)
2024
-
[27]
Generating all ver- tices of a polyhedron is hard,
Leonid Khachiyan, Endre Boros, Konrad Borys, Khaled Elbassioni, and Vladimir Gurvich, “Generating all ver- tices of a polyhedron is hard,” Discrete & Computational Geometry39, 174–190 (2008)
2008
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