REVIEW 2 major objections 4 minor 61 references
A single filtering commutator can reshape a quantum control algebra to match any chosen subalgebra, while projectors compose distinct systems and two indices diagnose invariance.
Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →
A Lie-algebra toolkit that composes, preserves, and reduces Hamiltonian generator sets, including a nearest-neighbor su(2^N) generating set and a filtering-operator reduction, though the reduction proof and one error-bound derivation have gaps.
T0 review reviewed 2026-08-02 challenge →
load-bearing objection A clean composition theorem and a plausible nearest-neighbor generating set, but the paper's central reduction theorem is false as stated — the counterexample kills the unified-framework claim. the 2 major comments →
A Dynamical Lie-Algebraic Framework for Hamiltonian Engineering and Quantum Control
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
Core claim
Theorem 3 is the anchor: for a cyclic reductive DLA g_A = ⊕_{j=1}^T g_j, with target subalgebra h = ⊕_{j=1}^S g_j, choose F ∈ h whose projection onto each g_j (j ≤ S) is non-zero and non-central. Then the filtered generating set A' = {[F, A] : A ∈ A} satisfies g_{A'} ≅ h. The mechanism is that the unwanted components g_{S+1},...,g_T commute with F and are killed, while within each retained simple ideal the non-central projection F_j acts as a seed whose commutators generate all of g_j. The paper also proves a direct-sum composition theorem using mutually orthogonal spectral projectors on an auxiliary register, and gives two quantitative diagnostics — projection overlap and DLA percentage cha
What carries the argument
The dynamical Lie algebra (DLA), the closure under nested commutators of the available anti-Hermitian generators, is the object being edited. The reduction machinery is the filtering operator F: an element of the target subalgebra whose non-central projections seed each retained simple ideal; the classically computed commutators [F, A] filter the generator set. Composition uses mutually orthogonal spectral projectors Π_m of an auxiliary Hermitian operator to keep distinct DLAs independent on a shared register. Invariance uses the projection-overlap index O(P,Q), measuring how much a candidate operator's central projection lies within the existing central span, together with the relative dime
Load-bearing premise
The reduction theorem's load-bearing step is the assumption that a non-central filter operator inside any one building block of the algebra generates that entire building block even when only the original Hamiltonians' projections are used as partners; the proof validates this for the full block, not for the restricted projected set, and if that step fails the filtered generators may span only part of the target.
What would settle it
Take a cyclic generating set for g_A = su(2) ⊕ su(2) on two qubits, set h to the first su(2), choose F = iZ_1, form A' = {[F,A]}, and compute dim⟨A'⟩. If any such example gives dimension less than 3, Theorem 3's projection-step assumption fails; the paper's harmonic-oscillator example does not test this step because the projected generator set there already contains both X_j and P_j in each mode.
If this is right
- If Theorem 3 holds, any cyclic reductive DLA can be reduced to any ideal-sum subalgebra by classically computing single commutators with F, with no ancilla and no physical simulation of F required.
- DLA composition via spectral projectors lets K distinct subsystem DLAs run in parallel on the same qubits plus ⌈log K⌉ ancillas, rather than K separate copies of the system.
- The nearest-neighbor generating construction for su(2^N) gives a hardware-friendly 2N+1 generator set that preserves full controllability after reorganization.
- The projection-overlap and percentage-change indices give a quantitative pruning criterion: generators with O≈1 and D_c≈0 are algebraically redundant and can be removed without changing the reachable algebra.
- The LTFIM-to-TFIM error bound, ∥U_LTFIM(t) − U_TFIM(t)∥ ≤ C n^2 α^2 t^2, shows that approximate subalgebra reduction can be certified even in a non-cyclic example.
- The reduction construction gives a systematic route to engineering evolutions confined to decoherence-free subspaces and low-dimensional symmetry sectors, addressing a core obstacle in near-term quantum simulation.
Where Pith is reading between the lines
- The filtering construction suggests a general recipe for Hamiltonian pruning by symmetry: any single non-central element inside a target ideal sum can serve as F, which may extend naturally to systems beyond the paper's examples, such as fermionic or lattice models with known ideal decompositions.
- The two indices O and D_c could be used as early trainability diagnostics in variational circuits: because DLA dimension is tied to barren plateaus, monitoring these quantities during ansatz growth may give a warning before full Lie closure is computed.
- Theorem 1 could be iterated to build hierarchical tensor-product direct sums, leading to recursive parallel-simulation schemes where each block is itself a composed DLA.
- A direct testable extension is to apply the F-filtering reduction to random cyclic Pauli-string generating sets for su(2)⊕su(2) and check whether g_{A'} exactly equals the target ideal; failures would localize exactly where the proof's projection-step assumption breaks.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript develops a dynamical-Lie-algebra (DLA) framework for three generator-set operations: composition, invariance, and reduction. Theorem 1 constructs qubit-efficient direct sums of distinct DLAs via spectral projectors on an ancillary register. Theorem 2 and the surrounding section give Pauli-string constructions and two quantitative indices (projection overlap O and percentage change D_c) for approximate DLA invariance. Theorem 3 claims that, for a cyclic reductive DLA g_A=⊕_j g_j and a target subalgebra h=⊕_{j≤S}g_j, the filtered generating set A'={[F,A]: A∈A}, with F∈h having non-central projection on each g_j, satisfies g_{A'}≅h. The paper also presents numerical examples, including a harmonic-oscillator illustration and an LTFIM-to-TFIM error bound. The main novelty is the reduction result, presented as the answer to the paper's Question 3.
Significance. If valid, Theorem 1 and Theorem 2 would be useful additions: the direct-sum construction is explicit and appears sound, and the su(2^N) nearest-neighbour generator construction is a plausible improvement for hardware-aware circuit compilation. The paper is also commendable for stating clear algebraic questions and providing worked examples. However, the central reduction theorem, Theorem 3, is false as stated: there is a simple su(2) counterexample satisfying all hypotheses. Since Theorem 3 is the paper's main answer to Question 3 and anchors the claimed reduction framework, this falsification is load-bearing. The LTFIM error-bound derivation in Appendix C2 also contains an inconsistency. The paper should not be accepted in its current form.
major comments (2)
- [§III.C, Theorem 3 and Appendix C1, Eq. (C3)] The surjectivity step of Theorem 3 is invalid, and the statement is false. Consider g_A=su(2) with the cyclic generating set A={iσ_x, iσ_z}. It is cyclic: for C=[iσ_z,iσ_x]=2iσ_y, one has [iσ_x,[iσ_x,C]]∝C. Let h=su(2) and F=iσ_z, which is non-central. Then A'={[F,A]}={2iσ_y,0}, so g_{A'}=span_R{iσ_y}≅u(1), not su(2). The proof after Eq. (C3) invokes Proposition 2 for the restricted set {[F_j,π_j(A)]:A∈A}, but Proposition 2 only applies to {[F_j,Y]:Y∈g_j}. The 'therefore' step, from the existence of some Y∈g_j with [F_j,Y]≠0 to the conclusion that the projected generators generate g_j, is not justified. The su(2) example shows the claim fails even when π_j(A)=A generates g_j. Adding a commuting su(2) factor and taking F in one factor gives a proper-subalgebra version. Thus Theorem 3 (and Theorem A3) is false.
- [Appendix C2, Eqs. (C4)-(C8)] The derivation of the LTFIM-to-TFIM error bound is internally inconsistent. The claim that H̃_γ^1(τ)=e^{iτH0}σ^z_γ e^{-iτH0} remains a single-qubit operator is actually correct, since σ^z_γ commutes with all σ^z_jσ^z_{j+1} terms and only the local σ^x_γ term contributes to the adjoint action. However, after correctly observing that [H̃_{γ1}(s), H̃_{γ2}(ν)]=0 for γ1≠γ2, the text replaces the double sum by a constant C′≈n² 'accounting for the number of non-zero commutator pairs.' The sum is zero, so Lemma A1's bound is zero; the n² factor is not derived. The final inequality (Eq. (20)) may be a valid loose bound, but the presented derivation does not establish it.
minor comments (4)
- [§IV.C, harmonic oscillators] This example lies outside the finite-dimensional hypothesis of Theorem 3: each mode is an infinite-dimensional Fock space. Moreover, the algebra generated by {iX_j,iP_j,iN_j,iS_j} contains a central element iI_j, so calling each g_j a simple Lie subalgebra is not accurate. The example should be reframed as an analogy rather than an application of Theorem 3.
- [Appendix C2] The sentence 'For γ1=γ2, the commutator is trivially zero' is not correct as a general statement: two Heisenberg-evolved operators of the same single-qubit σ^z at different times do not necessarily commute. This case is not in the sum over γ1<γ2 and should simply be omitted.
- [Eq. (10)] The notation for the product over 2<j<i is garbled ('Y' instead of a tensor product symbol) and the expression is hard to parse. Please rewrite with explicit tensor products or define the string ordering.
- [§IV.B, central-spin example] The projection overlap O(P,Q) is introduced for Pauli DLAs, but the example uses a central basis including iI_8. Clarify how the trace normalization and the orthonormal basis are chosen in this non-Pauli central space.
Circularity Check
No significant circularity: the paper's derivations are independent of their conclusions; the main risk is a correctness gap in Appendix C, not circularity.
full rationale
The paper's three main constructions are not circular. Theorem 1 is an independent extension of Lemma 1: it verifies [A⊗Π_i, B⊗Π_j]=0 for i≠j and constructs an explicit isomorphism φ_m(X)=X⊗Π_m; the conclusion g_{A'}≅⊕_m g_{A_m} is not assumed in the definition of A'. Theorem 2 relies on Proposition 1 (direct commutator computation) and external Lemma 2 (Smith et al.), and the Appendix B induction produces B'_I from B'_II by explicit nested brackets. The invariance indices in Sec. III.B.2 are definitions rather than predictions: O(P,Q)=1 is explicitly acknowledged to be a sufficient condition for Lemma 3's Condition 2, and D_c is the tautological relative dimension change, so no fitted parameter is later relabeled as a prediction. Theorem 3's reduction is the only place with a load-bearing inference: the step marked 'Therefore' in Appendix C asserts that the restricted set A'_j={[F_j,A_h^{(j)}]: A∈A} generates g_j because the full commutator set {[F_j,Y]: Y∈g_j} does (Proposition 2). This is a logical gap, and the paper's own cyclic-limitation paragraph acknowledges that non-cyclic cases fail; the cyclic hypothesis only ensures the restricted set is nonempty, not that it Lie-generates the ideal. But this is a correctness/falsifiability problem, not circularity: Proposition 2 is an independent lemma with its own proof, and the theorem's conclusion is not used as a premise. The error bound for LTFIM/TFIM uses the external product-formula bound of Bosse et al. and simplifies commutators; any error in estimating C' is an algebraic mistake, not a circular reduction. There are no self-citations by the current authors in the load-bearing chain. Therefore no Eq. X is equivalent to Eq. Y by construction, and the score is 0.
Axiom & Free-Parameter Ledger
axioms (9)
- standard math Reductive DLA admits direct-sum decomposition into simple ideals (Eq 15)
- standard math For a simple Lie algebra, the roots non-orthogonal to a nonzero Cartan element generate the whole root system (Prop 2 proof)
- standard math Cartan subalgebras of a simple complex Lie algebra are conjugate under inner automorphisms
- domain assumption Skew-Hermitian generators make every filtering operator F diagonalizable/semisimple
- domain assumption Theorem 3 requires the generating set A to be cyclic (Eq 6)
- domain assumption Lemma 2 of Smith et al. [23]: minimal Pauli su(2^N) generating sets and product-universal subsets
- domain assumption Lemma 3 of Zimborás et al. [22]: necessary and sufficient simulability conditions
- domain assumption Lemma A1 of Bosse et al. [31]: product-formula error bound for H=H0+αH1
- ad hoc to paper Heisenberg evolution of σ^z_γ under TFIM remains a single-qubit operator (and distinct γ operators act on disjoint qubits)
Cite this review
Pith. "Pith review of A Dynamical Lie-Algebraic Framework for Hamiltonian Engineering and Quantum Control." pith.science (2026). https://pith.science/paper/D2ROUUJQ
@misc{pith2026260304916,
author = {Pith},
title = {Pith review of: A Dynamical Lie-Algebraic Framework for Hamiltonian Engineering and Quantum Control},
year = {2026},
howpublished = {\url{https://pith.science/paper/D2ROUUJQ}},
note = {Machine review of arXiv:2603.04916}
}
read the original abstract
Determining the unitary dynamics accessible from finite Hamiltonian resources is a central problem in Hamiltonian engineering and quantum control. Dynamical Lie algebras (DLAs) connect available control Hamiltonians with the reachable dynamics, but their use as a design tool for modifying Hamiltonian generator sets remains less developed. In this work, we develop a finite-dimensional DLA framework for three generator-set operations: composition, invariance, and reduction. For composition, we construct direct sums of component DLAs using spectral projectors on an auxiliary register. For invariance, we analyze when modifications of Pauli-string generating sets preserve the generated Lie algebra, and introduce algebraic diagnostics for added generators. For reduction, we consider compact reductive DLAs and show how projection onto selected simple ideals gives reduced generating sets whose Lie closures are the corresponding ideal sums. We illustrate these results with finite-dimensional examples and numerical checks, including direct-sum dimension addition, central-spin invariance diagnostics, and DLA-based ansatz reduction for block-local Hamiltonians. The results show how DLA structure can be used to diagnose controllability and guide Hamiltonian generator design under explicit algebraic assumptions.
Figures
Reference graph
Works this paper leans on
-
[1]
Lemma 2 tells us that we can modify the generating setA → A′ while preservingsu(2 N )with no increasing of the cardinalities
Generating set of Pauli strings with the cardinality unchanged WhenL=L ′, a special case we choose is the full DLA su(2N ). Lemma 2 tells us that we can modify the generating setA → A′ while preservingsu(2 N )with no increasing of the cardinalities. LetAbe a minimal universal generating set forsu(2 N )withL= 2N+ 1, andA ⊂iP ∗ N . Here,P ∗ N denotes all Pa...
-
[2]
Generating set of Pauli strings with increasing of the cardinality Unlike the strict invariance in theL=L ′ case, forL < L′, we propose two quantitative metrics to evaluate approximate invariance, thereby overcoming the limitations in Condition (2) of Lemma 3. Lemma 3 provides two necessary and sufficient conditions for the above question preserving⟨P⟩ Li...
-
[3]
For each operator inP, usingT r(ρ † α ·iH β), we computeΠ(iH 1) = [0,1] T andΠ(iH 2) = [0,2] T , which are two linearly dependent vectors
Here J2 ∈Rbeing the interaction strengths. For each operator inP, usingT r(ρ † α ·iH β), we computeΠ(iH 1) = [0,1] T andΠ(iH 2) = [0,2] T , which are two linearly dependent vectors. Thus, the central projection span space ofPis span(Π(P)) =span{ρ 2}, and the rank of the projection ma- trix ˜Tisrank( ˜T) = 1. AddQ 1 ={iH 3}whereiH 3 =i(2σ z 1 + 0.5σx 1 σx ...
-
[4]
DLA Reduction ,21 ,,, LieLiHiHiH g iHtiHt eet 0)( Hamiltonian Learning ? ? l l l L l l HHH 1 1.Parallel Architecture
-
[5]
Compiler Optimization
-
[6]
6: Guiding physical circuit design via theoretical DLA modifications
Circuit Pruning iHtetU )(U(t) Hamiltonian Simulation for a given H Unitary Dynamics Find the true Hamiltonian generating unitary dynamics H FIG. 6: Guiding physical circuit design via theoretical DLA modifications. the ratio of the weak longitudinal field to the dominant inter- action strength. The details to derive this error bound is in Appendix C 2....
-
[7]
Fring and M
A. Fring and M. H. Moussa, Unitary quantum evolution for time-dependent quasi-Hermitian systems with nonobservable Hamiltonians, Phys. Rev. A93, 042114 (2016)
2016
-
[8]
Y . Lai, J. Liang, H. Müller-Kirsten, and J.-G. Zhou, Time evolu- tion of quantum systems with time-dependent Hamiltonian and the invariant Hermitian operator, J. Phys. A: Math. Gen.29, 1773 (1996)
1996
-
[9]
Y . Cao, S. Jin, and N. Liu, Quantum simulation for time- dependent Hamiltonians-with applications to non-autonomous ordinary and partial differential equations, J. Phys. A: Math. Theor.58, 155304 (2025)
2025
-
[10]
Y . Cao, S. Jin, and N. Liu, Unifying framework for quantum simulation algorithms for time-dependent Hamiltonian dynam- ics, Phys. Rev. Res.7, 043186 (2025)
2025
-
[11]
Pal and K
K. Pal and K. Pal, Time-dependent Hamiltonians and geome- try of operators generated by them, Phys. Rev. E111, 014104 (2025)
2025
-
[12]
Mizuta and K
K. Mizuta and K. Fujii, Optimal Hamiltonian simulation for time-periodic systems, Quantum7, 962 (2023)
2023
-
[13]
Ramakrishna and H
V . Ramakrishna and H. Rabitz, Relation between quantum com- puting and quantum controllability, Phys. Rev. A54, 1715 (1996)
1996
-
[14]
Gago-Encinas, T
F. Gago-Encinas, T. Hartung, D. M. Reich, K. Jansen, and C. P. Koch, Determining the ability for universal quantum comput- ing: Testing controllability via dimensional expressivity, Quan- tum7, 1214 (2023)
2023
-
[15]
D’Alessandro,Introduction to quantum control and dynam- ics(Chapman and Hall/CRC, 2021)
D. D’Alessandro,Introduction to quantum control and dynam- ics(Chapman and Hall/CRC, 2021)
2021
-
[16]
D’Alessandro and Y
D. D’Alessandro and Y . Isik, Controllability of the periodic quantum Ising spin chain and the Onsager algebra, J. Phys. A: Math. Theor.58, 115202 (2025)
2025
-
[17]
Schirmer, I
S. Schirmer, I. Pullen, and A. Solomon, Identification of dy- namical Lie algebras for finite-level quantum control systems, J. Phys. A: Math. Gen.35, 2327 (2002)
2002
-
[18]
Ragone, B
M. Ragone, B. N. Bakalov, F. Sauvage, A. F. Kemper, C. Or- tiz Marrero, M. Larocca, and M. Cerezo, A Lie algebraic the- ory of barren plateaus for deep parameterized quantum circuits, Nat. Commun.15, 7172 (2024)
2024
-
[19]
Fontana, D
E. Fontana, D. Herman, S. Chakrabarti, N. Kumar, R. Yalovet- zky, J. Heredge, S. H. Sureshbabu, and M. Pistoia, Characteriz- ing barren plateaus in quantum ansätze with the adjoint repre- sentation, Nat. Commun.15, 7171 (2024)
2024
-
[20]
J. R. McClean, S. Boixo, V . N. Smelyanskiy, R. Babbush, and H. Neven, Barren plateaus in quantum neural network training landscapes, Nat. Commun.9, 4812 (2018)
2018
-
[21]
Larocca, S
M. Larocca, S. Thanasilp, S. Wang, K. Sharma, J. Bia- monte, P. J. Coles, L. Cincio, J. R. McClean, Z. Holmes, and M. Cerezo, Barren plateaus in variational quantum computing, Nat. Rev. Phys. , 1 (2025)
2025
-
[22]
Wiebe, C
N. Wiebe, C. Granade, C. Ferrie, and D. G. Cory, Hamiltonian learning and certification using quantum resources, Phys. Rev. Lett.112, 190501 (2014)
2014
-
[23]
G. Aguilar, S. Cichy, J. Eisert, and L. Bittel, Full classification of Pauli Lie algebras, arXiv:2408.00081 (2024)
Pith/arXiv arXiv 2024
-
[24]
E. Kökcü, R. Wiersema, A. F. Kemper, and B. N. Bakalov, Clas- sification of dynamical Lie algebras generated by spin interac- tions on undirected graphs, arXiv:2409.19797 (2024)
Pith/arXiv arXiv 2024
-
[25]
S. Kazi, M. Larocca, M. Farinati, P. J. Coles, M. Cerezo, and R. Zeier, Analyzing the quantum approximate optimization al- gorithm: Ansätze, symmetries, and Lie algebras, PRX Quan- tum6, 040345 (2025)
2025
-
[26]
D. Rabinovich, A. Kardashin, and S. Adhikary, On the role of overparametrization in quantum approximate optimization, arXiv:2508.10086 (2025)
Pith/arXiv arXiv 2025
-
[27]
J. Allcock, M. Santha, P. Yuan, and S. Zhang, On generat- ing direct powers of dynamical Lie algebras, arXiv:2506.05733 (2025)
Pith/arXiv arXiv 2025
-
[28]
Zimborás, R
Z. Zimborás, R. Zeier, T. Schulte-Herbrüggen, and D. Burgarth, Symmetry criteria for quantum simulability of effective interac- tions, Phys. Rev. A92, 042309 (2015)
2015
-
[29]
I. D. Smith, M. Cautrès, D. T. Stephen, and H. Poulsen Nautrup, Optimally generatingsu(2 n)using Pauli strings, Phys. Rev. Lett.134, 200601 (2025)
2025
-
[30]
Barratt, J
F. Barratt, J. Dborin, M. Bal, V . Stojevic, F. Pollmann, and A. G. Green, Parallel quantum simulation of large systems on small NISQ computers, npj Quantum Inf.7, 79 (2021)
2021
-
[31]
N. Diaz, P. Braccia, M. Larocca, J. Matera, R. Rossignoli, and M. Cerezo, Parallel-in-time quantum simulation via Page and Wootters quantum time, Phys. Rev. Res.7, 033294 (2025)
2025
-
[32]
Y . Nam, N. J. Ross, Y . Su, A. M. Childs, and D. Maslov, Auto- mated optimization of large quantum circuits with continuous parameters, npj Quantum Inf.4, 23 (2018)
2018
-
[33]
R. Iten, R. Moyard, T. Metger, D. Sutter, and S. Woerner, Exact and practical pattern matching for quantum circuit optimiza- tion, ACM Trans. Quantum Comput.3, 1 (2022)
2022
-
[34]
Y . Viswanathan, O. Adjoua, C. Feniou, S. Badreddine, and J.-P. Piquemal, An optimal framework for constructing Lie- algebra generator pools: application to variational quantum 12 eigensolvers for chemistry, arXiv:2511.22593 (2025)
Pith/arXiv arXiv 2025
-
[35]
D. A. Lidar, I. L. Chuang, and K. B. Whaley, Decoherence free subspaces for quantum computation, Phys. Rev. Lett.81, 2594 (1998)
1998
-
[36]
G. Xu, J. Zhang, D. Tong, E. Sjöqvist, and L. Kwek, Nona- diabatic holonomic quantum computation in decoherence-free subspaces, Phys. Rev. Lett.109, 170501 (2012)
2012
-
[37]
J. L. Bosse, A. M. Childs, C. Derby, F. M. Gambetta, A. Mon- tanaro, and R. A. Santos, Efficient and practical Hamiltonian simulation from time-dependent product formulas, Nat. Com- mun.16, 2673 (2025)
2025
-
[38]
N. M. Linke, D. Maslov, M. Roetteler, S. Debnath, C. Fig- gatt, K. A. Landsman, K. Wright, and C. Monroe, Experimen- tal comparison of two quantum computing architectures, Proc. Natl. Acad. Sci. U.S.A.114, 3305 (2017)
2017
-
[39]
Zulehner, A
A. Zulehner, A. Paler, and R. Wille, An efficient methodol- ogy for mapping quantum circuits to the IBM QX architectures, IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.38, 1226 (2018)
2018
-
[40]
Kulshrestha, X
A. Kulshrestha, X. Liu, H. Ushijima-Mwesigwa, B. Bach, and I. Safro, QAdaPrune: Adaptive parameter pruning for training variational quantum circuits, in2024 IEEE Int. Conf. Quantum Comput. Eng. (QCE), V ol. 2 (IEEE, 2024) pp. 120–125
2024
-
[41]
Larocca, N
M. Larocca, N. Ju, D. García-Martín, P. J. Coles, and M. Cerezo, Theory of overparametrization in quantum neural networks, Nat. Comput. Sci.3, 542 (2023)
2023
-
[42]
J. E. Humphreys,Introduction to Lie algebras and representa- tion theory, V ol. 9 (Springer Science & Business Media, 2012)
2012
-
[43]
S. L. Braunstein and P. Van Loock, Quantum information with continuous variables, Rev. Mod. Phys.77, 513 (2005)
2005
-
[44]
Weedbrook, S
C. Weedbrook, S. Pirandola, R. García-Patrón, N. J. Cerf, T. C. Ralph, J. H. Shapiro, and S. Lloyd, Gaussian quantum informa- tion, Rev. Mod. Phys.84, 621 (2012)
2012
-
[45]
Stinchcombe, Ising model in a transverse field
R. Stinchcombe, Ising model in a transverse field. I. Basic the- ory, J. Phys. C: Solid State Phys.6, 2459 (1973)
1973
-
[46]
S. I. Mohtashim, A. Das, T. Chatterjee, and F. T. Chowdhury, A near-term quantum simulation of the transverse field Ising model hints at glassy dynamics, Eur. Phys. J. Spec. Top. , 1 (2025)
2025
-
[47]
O. d. A. Bonfim, B. Boechat, and J. Florencio, Ground-state properties of the one-dimensional transverse Ising model in a longitudinal magnetic field, Phys. Rev. E99, 012122 (2019)
2019
-
[48]
M. L. Goh, M. Larocca, L. Cincio, M. Cerezo, and F. Sauvage, Lie-algebraic classical simulations for quantum computing, Phys. Rev. Res.7, 033266 (2025)
2025
-
[49]
Tindall and D
J. Tindall and D. Sels, Confinement in the transverse field Ising model on the heavy hex lattice, Phys. Rev. Lett.133, 180402 (2024)
2024
-
[50]
R. D. Somma, R. King, R. Kothari, T. E. O’Brien, and R. Bab- bush, Shadow hamiltonian simulation, Nature Communications 16, 2690 (2025)
2025
-
[51]
Q. Zhao, Y . Zhou, A. F. Shaw, T. Li, and A. M. Childs, Hamil- tonian simulation with random inputs, Physical Review Letters 129, 270502 (2022)
2022
-
[52]
Q. Zhao, Y . Zhou, and A. M. Childs, Entanglement accelerates quantum simulation, Nature Physics21, 1338 (2025)
2025
-
[53]
Chakraborty, Implementing any linear combination of uni- taries on intermediate-term quantum computers, Quantum8, 1496 (2024)
S. Chakraborty, Implementing any linear combination of uni- taries on intermediate-term quantum computers, Quantum8, 1496 (2024)
2024
-
[54]
J. Wang, S. Paesani, R. Santagati, S. Knauer, A. A. Gentile, N. Wiebe, M. Petruzzella, J. L. O’brien, J. G. Rarity, A. Laing, et al., Experimental quantum Hamiltonian learning, Nat. Phys. 13, 551 (2017)
2017
-
[55]
A. Gu, L. Cincio, and P. J. Coles, Practical Hamiltonian learning with unitary dynamics and Gibbs states, Nat. Commun.15, 312 (2024)
2024
-
[56]
Heightman, E
T. Heightman, E. Jiang, and A. Acín, Solving the quantum many-body Hamiltonian learning problem with neural differ- ential equations, Quantum Sci. Technol.10, 045072 (2025)
2025
-
[57]
B. C. Hall,Quantum Theory for Mathematicians(Springer, New York, 2013) pp. 333–366. Appendix A: DLA composition Theorem A1.ConsiderKdynamical generating setsA m = {Am,1, Am,2, . . . , Am,Lm },m= 1,2, . . . , K, where each Am generates a dynamical Lie algebrag Am. Letχbe a Her- mitian operator withKdistinct eigenvaluesλ 1, λ2, . . . , λK, and letΠ 1,Π 2, ....
2013
-
[58]
IfF /∈Z(g), then the Lie subalgebraS F ={[F, X]| X∈g}generated by the first-order commutators satisfies ⟨SF ⟩Lie,R =g
Cyclic DLA Proposition 4.Assumegis a simple Lie algebra overR. IfF /∈Z(g), then the Lie subalgebraS F ={[F, X]| X∈g}generated by the first-order commutators satisfies ⟨SF ⟩Lie,R =g. Proof.Asgis simple, we may invoke the standard root space decomposition relative to a Cartan subalgebrag 0 [36]. For anyX∈g, the root space decomposition gives X=H+ X α cαEα, ...
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LetF ′ =ϕ(F)
=g 0. LetF ′ =ϕ(F). SinceF∈g ′ 0, we haveF ′ ∈g 0. Consider the setS F ′ ={[F ′, Y]|Y∈g}. By the former result, we get ⟨SF ′⟩Lie,R =g. 14 Using the property thatϕis a Lie algebra homomorphism pre- serving brackets, we relateS F ′ back toS F , SF ′ ={[ϕ(F), Y]|Y∈g} ={[ϕ(F), ϕ(X)]|X∈g} ={ϕ([F, X])|X∈g} =ϕ(S F ). Therefore, the algebra generated byS F satisf...
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Non-cyclic DLAs: Derivation of an upper bound for LTFIM and TFIM Lemma A1.[31] ForH=H 0 +αH 1 whereH 1 =Pr γ=1 H γ 1 , the approximate evolution operator Uapx(t) =e −itH0 rY γ=1 eitH0 e−it(H0+αH γ 1 ) approximates the exact evolutionU(t) =e −itH with the error bound ∥U(t)−U apx(t)∥ ≤α2 ˆ t 0 dν ˆ ν 0 ds·(C4) rX γ1<γ2=1 ∥[ ˜H γ1 1 (s), ˜H γ2 1 (ν)]∥,(C5) w...
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Thus, the sum overγ 1 < γ2 simplifies to a constantC ′, which accounts for the number of non-zero commutator pairs
Forγ 1 =γ 2, the commutator is trivially zero. Thus, the sum overγ 1 < γ2 simplifies to a constantC ′, which accounts for the number of non-zero commutator pairs. For LTFIM- TFIM,C ′ ≈n 2, since there are n 2 ∼n 2/2pairs ofγ 1 < γ2. Because all commutators∥[ ˜H γ1 1 (s), ˜H γ2 1 (ν)]∥are bounded by a constant, denoted asC ′, then we have ∥ULT F IM(t)−U T ...
This paper was first reviewed by deepseek-v4-flash on August 2, 2026.
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