REVIEW 4 major objections 5 minor 1 cited by
Simulating Time Dependent and Nonlinear Classical Oscillators through Nonlinear Schr\"odingerization
T0 review · 4 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash
Pith's one-line read This paper claims that forced, time-dependent, and weakly nonlinear classical oscillator systems can be reduced—through a method it calls Nonlinear Schrödingerization—to Hermitian quantum evolution, with query cost near-linear in time and…
desk verdict The forced-oscillator reduction is a real idea, but the symmetrization step is not Hermitian, so the nonlinear theorems don't follow. 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 central object is the symmetrized Carleman operator $\hat{Q}(\eta)=\sum_i(|i\rangle\langle i|\otimes A_{i+1}+\frac{1}{\eta}|i\rangle\langle i+1|\otimes B_{i+1}+\frac{1}{\eta}|i+1\rangle\langle i|\otimes B^\dagger_{i+1})$, a Hermitian matrix built from the original linear and nonlinear coupling blocks $A_i$ and $B_i$. It carries the argument by turning the non-unitary truncated Carleman system into a norm-preserving Schrödinger evolution: the scaling $\eta$ suppresses the non-Hermitian back-action terms, and Lemma 32 gives a sufficient $\eta$ for the rescaled state $D|\hat{p}(t)\rangle$ to approximate the true Carleman state $|p(t)\rangle$ within $\epsilon$. Forced and time-dependent oscillator problems are fed into this machine by constructing higher-dimensional oscillator systems whose subspaces reproduce the desired non-conservative dynamics.
What would settle it
Take the concrete Carleman matrix $H$ from Eq. (175) with $B_i$ blocks not paired with adjoints, compute $\|e^{-iHt}\|_2$ for small $t$; if it exceeds $1+\delta$ for arbitrarily small $\delta$, or if a direct numerical integration of the symmetrized system fails to track the truncated Carleman system within the claimed $\epsilon$, then Lemma 32's bound is false and the theorems relying on it lose their support.
Extended reading notes
Core claim
The paper's central claim is that the dynamics $M\ddot{x}=-Kx+f(t)$ (forced), $M\ddot{x}=-K_1x+K_2x\otimes x$ (nonlinear), $M\ddot{x}=-K(t)x$ (time-dependent stiffness), and the combined forced time-dependent case can each be mapped to Hermitian time evolution. For the forced case, auxiliary masses with carefully chosen initial conditions enact the external force while their large mass $m_f$ suppresses back-action; perturbation theory bounds the error by $\epsilon$ once $m_f \ge (t\|K'\|\cdots)(1+\Xi(0)/\epsilon)$. For nonlinear and time-dependent cases, Carleman linearization embeds the nonlinear Schrödinger equation $|\dot{\psi}\rangle=-iH_1|\psi\rangle+H_2|\psi\rangle\otimes|\psi\rangle$ into a high-dimensional linear system, and a scaling parameter $\eta$ symmetrizes the non-Hermitian Carleman generator so that Hamiltonian simulation applies. The stated complexities are $O(\tau+\log(1/\epsilon))$ for forced oscillators with $\tau=t\sqrt{2\alpha d}$, and $O(\alpha k^2 t + k\log(\cdots))$ for nonlinear Schrödinger equations, with the Carleman truncation order $k$ logarithmic under non-resonance conditions.
Load-bearing premise
The construction depends on the assumption that the unperturbed linearized system evolves by a norm-preserving unitary; in the symmetrization lemma this is applied to a matrix that is not Hermitian, because the lower off-diagonal blocks are not the adjoints of the upper ones, and that gap is what all later error bounds inherit.
Editorial extensions
If this is right
- For forced oscillator systems, the algorithm takes $O(\tau+\log(1/\epsilon))$ oracle queries, with $\tau=t\sqrt{2\alpha d}$, and uses $O(\log(N(l+1)))$ qubits.
- Weakly nonlinear Schrödinger equations with non-increasing norm and no resonances are simulable with $O(\alpha k^2 t + k\log(\cdots))$ queries, and the Carleman truncation order is logarithmic in $T/\epsilon$ when the resonance gap $\Delta$ is large enough.
- Nonlinear oscillator networks with quadratic nonlinearities, bounded state norm, and non-resonant spectra reduce to the nonlinear Schrödinger simulation and inherit the same complexity.
- Time-dependent stiffness matrices, and time-dependent stiffness combined with external forces, are embedded in higher-dimensional nonlinear oscillator systems and then simulated with the same machinery.
- If correct, all these classes inherit the exponential separation from classical simulation previously established for the conservative linear oscillator case.
Reading between the lines
- Editorial inference: the same perturbative embedding of non-conservative terms into larger conservative systems should apply to other linear non-unitary dynamics, such as damped oscillator networks, whenever the damping can be represented as weak coupling to a large reservoir.
- Editorial inference: the symmetrization strategy suggests a general recipe—approximate a weakly non-Hermitian generator by a Hermitian one via a single scaling parameter $\eta$—that could be tested independently on small Carleman systems before relying on the full oscillator reduction.
- Editorial inference: because the harmonic oscillator case is BQP-complete, the paper's claims, if correct, imply that the entire forced, time-dependent, and nonlinear family is classically hard to simulate even though each reduction step is only polynomial-time.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper proposes quantum algorithms for simulating forced, nonlinear, and time-dependent coupled classical oscillators. The strategy is to reduce each classical system to a nonlinear Schrödinger equation, linearize that equation by Carleman embedding, "symmetrize" the resulting non-Hermitian linear system into a Hermitian one, and simulate the Hermitian system with QSVT-based Hamiltonian simulation. The main complexity claims are Theorem 13 for forced oscillators, Theorems 15 and 16 for the nonlinear Schrödinger equation, and Theorems 18, 20, and 22 for nonlinear, time-dependent-stiffness, and time-dependent-forced oscillator systems. All of these except Theorem 13 rely on the symmetrization engine of Theorem 44, which in turn relies on Lemmas 32 and 33.
Significance. If correct, the results would substantially extend the exponential speedup of Babbush et al. for coupled harmonic oscillators to non-conservative, time-dependent, and weakly nonlinear classical systems, with complexity polynomial in the number of masses and almost linear in evolution time. The paper contains a considerable amount of explicit construction: oracle definitions, block-encoding lemmas, and reduction chains from each classical system to a nonlinear Schrödinger equation. I also note that the paper relies on external convergence results for Carleman linearization (Refs. [17,39]) and standard Hamiltonian simulation machinery, so I do not see a circularity problem. However, the central symmetrization argument is invalid as written, and that invalid argument supports essentially all of the paper's new claims; the forced-oscillator theorem is the only part that may stand independently, and even that requires a separate check of the perturbation analysis in Section 4.
major comments (4)
- [§5.1, Eq. (143) and definitions of A_i, B_i] The Carleman system in Eq. (143) is written as d|p>/dt = -i Q |p> with first block row [H1, iH2, 0, ...]. However, Section 5.1 then defines A1 = (|0><0|)^{⊗k-1} ⊗ (-iH1) and B1 = (|0><0|)^{⊗k-2} ⊗ (|0>⊗H2). Substituting these into Eq. (152) gives a top-block equation d|ψ>/dt = -H1|ψ> - i H2|ψ⊗ψ>, which differs from the target equation (6), d|ψ>/dt = -iH1|ψ> + H2|ψ⊗ψ>. This sign and factor-of-i inconsistency propagates into every subsequent use of the Carleman embedding and makes the stated reduction from a nonlinear Schrödinger equation to a linear system incorrect.
- [§5.3, Lemmas 32 and 33 and Eq. (175)] Lemma 32 applies Lemma 33 with H = ∑_l (|l><l|⊗A_{l+1} + |l><l+1|⊗B_{l+1}) in Eq. (175). Lemma 33 assumes H is block diagonal with Hermitian blocks, which is used to conclude that e^{-iHt} is norm-preserving and to obtain Eq. (182). The H in Eq. (175) is not block diagonal: it contains off-diagonal B_{l+1} blocks, and under the Section 5.1 definitions the A blocks are anti-Hermitian rather than Hermitian. Thus the premise of Lemma 33 fails, and the bound η ≥ sqrt(||hat H||) (1 + ||p(0)||/ϵ) t_s is unsupported. Since Theorem 44 invokes Lemma 32, and Theorems 15, 16, 18, 20, and 22 invoke Theorem 44, the main complexity claims of the paper do not follow from the presented proof.
- [§5.3, Lemma 32 and definition of D|hat p>] With the stated definitions, |hat w_i> = η^{-(k-i)}|w_i> and D = diag(η^{k-1}I, ..., I), we have D|hat p> = ∑_i |i-1>⊗|w_i> = |p> exactly. Therefore the claimed approximation ∥D|hat p> - |p>∥ ≤ ϵ is an identity, not a convergence statement. The subsequent error bound in Theorem 44, written as ∥T|φ> - |p>∥ ≤ ϵ with T = ℵD, is then also vacuous because T|φ> = D|hat p> = |p> by construction. The symmetrization error needs to be defined with an internally consistent scaling of the Carleman variables; as written, the proof does not establish any approximation.
- [§5.5, Theorem 44 and projection probability] Theorem 44 states that the probability of projecting onto the first Carleman block is p1 ∈ O((⟨ψ(t)|ψ(t)⟩/β)(1-βη²)) and adds that 'one can always rescale the nonlinear Schrödinger equation to ensure βη² < 1'. This rescaling claim is not justified in the proof: rescaling |ψ> also changes the norm of H2 and hence the Carleman truncation order and the definition of η through Eq. (220). Since βη² < 1 is an input condition for the stated probability bound, the proof needs to show that the rescaling is compatible with the other assumptions of the theorem, and it does not.
minor comments (5)
- [Throughout] The name 'Carlemann' is consistently misspelled; the standard spelling is 'Carleman'.
- [§5.3, Lemma 34] Lemma 34 writes hat H_1 = i|1><0|⊗B_1† and hat H_2 = i|2><1|⊗B_2†, but Lemma 32 defines hat H without the factor i. The factor i should be reconciled between the two statements.
- [§4.3, Theorem 13] The proof of Theorem 13 contains an unclear phrase 'requireG =O(...)' with a missing space, and Proposition 29's derivation of E/E_sys contains the dimensionally inconsistent expression O(N f_max^2 l^3 t/ϵ^2); these need clarification.
- [§4.1, Eq. (26)] Eq. (26) writes M¨x = K0x + γK'x, while the oscillator definitions in Section 2 use M¨x = -Kx. The sign conventions for K0 and K' should be stated consistently, because the perturbation result Theorem 25 is stated in terms of K0 and K'.
- [§5.4, Lemmas 41 and 42] Lemma 41 constructs a block encoding of A_i = (|0><0|)^{⊗k-i}⊗(-i(⊕_{i-1}H1)), while Lemma 42 cites the same block-encoding construction U(⊕_{i-1}(-iH1)) for the B_i matrix, which should instead involve H2. This appears to be a copy-and-paste error and makes the stated block-encoding constants unreliable.
Circularity Check
No significant circularity: the derivation chain rests on external Carleman error bounds and standard Hamiltonian simulation results, not on fitted parameters or self-referential premises.
full rationale
The paper's claimed reductions are self-contained against independent benchmarks. The forced-oscillator result (Theorem 13) is built from an explicit embedding into a larger conservative oscillator system (Theorem 27) with perturbation bounds (Theorem 25) whose auxiliary initial conditions are chosen to match the forcing terms, not fitted after the fact. The nonlinear-Schrodinger results (Theorems 15, 16, 18, 20, 22) all rest on Theorem 44, whose Carleman truncation order is inherited from external convergence analyses [17, 39] and whose Hamiltonian simulation cost uses standard QSVT/block-encoding machinery [18]. The symmetrization parameter eta is chosen by a sufficient error bound (Lemma 32/33), not tuned to reproduce the final complexity claim. The only self-citation ([8], used to motivate impossibility of general nonlinear quantum dynamics) is not load-bearing for any theorem. A separate mathematical-soundness concern exists: Lemma 32 invokes Lemma 33 with an H that appears non-Hermitian under the printed A_i definitions, and Theorem 44 states without proof that one can always rescale so that beta*eta^2 < 1. Those are correctness risks, not circular reductions: they do not equate an output with an input by definition, and no fitted parameter is renamed as a prediction. Accordingly, no circular step can be exhibited and the appropriate score is 0.
Assumptions & free parameters
free parameters (3)
- Auxiliary mass m_f (gamma = 1/m_f) =
Chosen large, e.g., m_f >= t ||K'|| ||T|| ||M^{-1/2}|| (1 + Xi(0)/epsilon)
- Symmetrization scale eta =
sqrt(||H2|| k(k+1)/2 (1 + beta(1-beta^k)/((1-beta)epsilon)) t)
- Rescaling of initial conditions to make beta < 1 =
beta < 1 after rescaling by a constant
assumptions (6)
- domain assumption Oracle access model for matrix elements, initial state preparation, and sparse access (Definitions 4, 6, 8, 11).
- domain assumption Time-dependent forces and stiffnesses admit finite Fourier expansions f_i(t)=sum_j f_ij cos(omega_ij t + phi_ij) and k_ij(t)=sum_l alpha_ij,l cos(omega_ij,l t + phi_ij,l).
- domain assumption Masses are positive and stiffness matrices are positive semidefinite for all t.
- ad hoc to paper Norm-non-increasing condition Re(<psi|H2|psi tensor psi>) <= 0 for the nonlinear Schrodinger equation.
- domain assumption Non-resonance gap Delta > 0 and R_r < 1.
- standard math External Carleman truncation error bounds from [17] and Theorem 1.1 of [39].
invented entities (1)
-
Auxiliary and fictitious masses added to the oscillator system
Cite this review
Pith. "Pith review of Simulating Time Dependent and Nonlinear Classical Oscillators through Nonlinear Schr\"odingerization." pith.science (2026). https://pith.science/paper/T4MXNBJV
@misc{pith2026250517170,
author = {Pith},
title = {Pith review of: Simulating Time Dependent and Nonlinear Classical Oscillators through Nonlinear Schr\"odingerization},
year = {2026},
howpublished = {\url{https://pith.science/paper/T4MXNBJV}},
note = {Machine review of arXiv:2505.17170}
}
abstract
We present quantum algorithms for simulating the dynamics of a broad class of classical oscillator systems containing $2^n$ coupled oscillators (Eg: $2^n$ masses coupled by springs), including those with time-dependent forces, time-varying stiffness matrices, and weak nonlinear interactions. This generalization of the Harmonic oscillator simulation algorithm is achieved through an approach that we call ``Nonlinear Schr\"{o}dingerization'', which involves reduction of the dynamical system to a nonlinear Schr\"{o}dinger equation and then reduced to a time-independent Schrodinger Equation through perturbative techniques. The linearization of the equation is performed using an approach that allows the dynamics of a nonlinear Schr\"odinger equation to be approximated as a linear Schr\"odinger equation in a higher dimensional space. This allows Hamiltonian Simulation algorithms to be applied to simulate the dynamics of resulting system. When the properties of the classical dynamical systems can be efficiently queried, and when the initial state can be efficiently prepared, the complexity of our quantum algorithm is polynomial in $n$, and almost linear in evolution time for most dynamical systems. Our work extends the applicability of quantum algorithms to simulate the dynamics of non-conservative and nonlinear classical systems, addressing key limitations in previous approaches.
Figures
Forward citations
Cited by 1 Pith paper
-
Quantum Elastic Network Models and their Application to Graphene
A quantum algorithm for coupled oscillators is adapted to elastic network models, with an efficient connectivity oracle for graphene and applications to heat transfer and rippling — at the cost of a coarse two-bucket ...
Reference graph
Works this paper leans on
-
[1]
Quantumalgorithmforlinearnon-unitary dynamicswithnear-optimaldependenceonallparameters
DongAn,AndrewMChilds,andLinLin.“Quantumalgorithmforlinearnon-unitary dynamicswithnear-optimaldependenceonallparameters”.In: arXiv preprint arXiv:2312.03916 (2023)
arXiv 2023
-
[2]
Dong An, Jin-Peng Liu, and Lin Lin. “Linear combination of hamiltonian simulation for nonunitary dynamics with optimal state preparation cost”. In:Physical Review Letters 131.15 (2023), p. 150603
work page 2023
-
[3]
Exponential quantum speedup in simulating coupled classical oscillators
Ryan Babbush et al. “Exponential quantum speedup in simulating coupled classical oscillators”. In:arXiv preprint arXiv:2303.13012(2023)
arXiv 2023
-
[4]
High-order quantum algorithm for solving linear differential equations
Dominic W Berry. “High-order quantum algorithm for solving linear differential equations”. In: Journal of Physics A: Mathematical and Theoretical47.10 (2014), p. 105301
work page 2014
-
[5]
Dominic W. Berry, Andrew M. Childs, and Robin Kothari. “Quantum algorithm for linear differential equations with exponentially improved dependence on precision”. In: Commun. Math. Phys.356 (2017), pp. 1–17.doi: 10.1007/s00220-017-3002-y
-
[6]
Quantum algorithm for time-dependent differential equations using Dyson series
Dominic W Berry and Pedro CS Costa. “Quantum algorithm for time-dependent differential equations using Dyson series”. In:Quantum 8 (2024), p. 1369
work page 2024
-
[7]
Efficient quantum algorithms for simulating sparse Hamil- tonians
Dominic W. Berry et al. “Efficient quantum algorithms for simulating sparse Hamil- tonians”. In: Communications in Mathematical Physics270.2 (2007), pp. 359–371. doi: 10.1007/s00220-006-0150-x. eprint:quant-ph/0508139. 76
arXiv 2007
-
[8]
Quantum and classical algorithms for nonlinear unitary dynamics
Noah Brüstle and Nathan Wiebe. “Quantum and classical algorithms for nonlinear unitary dynamics”. In:arXiv preprint arXiv:2407.07685(2024)
work page Pith review arXiv 2024
Show all 39 references
-
[9]
Application of the theory of linear integral equations to systems of nonlinear differential equations
Torsten Carleman. “Application of the theory of linear integral equations to systems of nonlinear differential equations”. In: (1932)
1932
-
[10]
Quantum algorithm for systems of linear equations with exponentially improved dependence on precision
Andrew M Childs, Robin Kothari, and Rolando D Somma. “Quantum algorithm for systems of linear equations with exponentially improved dependence on precision”. In: SIAM Journal on Computing46.6 (2017), pp. 1920–1950
2017
-
[11]
Hamiltonian simulation using linear combi- nations of unitary operations
Andrew M. Childs and Nathan Wiebe. “Hamiltonian simulation using linear combi- nations of unitary operations”. In:Quantum Information & Computation12.11-12 (2012), pp. 901–924
2012
-
[12]
Preconditioned quantum linear system algorithm
B David Clader, Bryan C Jacobs, and Chad R Sprouse. “Preconditioned quantum linear system algorithm”. In:Physical review letters110.25 (2013), p. 250504
2013
-
[14]
Quantum algorithm for simulating the wave equation
Pedro CS Costa, Stephen Jordan, and Aaron Ostrander. “Quantum algorithm for simulating the wave equation”. In:Physical Review A99.1 (2019), p. 012323
2019
-
[15]
Calculating response functions of coupled oscillators using quan- tum phase estimation
Sven Danz et al. “Calculating response functions of coupled oscillators using quan- tum phase estimation”. In:arXiv preprint arXiv:2405.08694(2024)
2024
-
[16]
Quantum mechanical computers
Richard Feynman. “Quantum mechanical computers”. In:Optics news11.2 (1985), pp. 11–20
1985
-
[17]
Explicit error bounds for Carleman lineariza- tion
Marcelo Forets and Amaury Pouly. “Explicit error bounds for Carleman lineariza- tion”. In:arXiv preprint arXiv:1711.02552(2017)
2017 arXiv
-
[18]
Quantum singular value transformation and beyond: expo- nential improvements for quantum matrix arithmetics
András Gilyén et al. “Quantum singular value transformation and beyond: expo- nential improvements for quantum matrix arithmetics”. In:Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing. 2019, pp. 193–204
2019
-
[19]
Quantum algorithm for linear systems of equations
Aram W Harrow, Avinatan Hassidim, and Seth Lloyd. “Quantum algorithm for linear systems of equations”. In:Physical review letters103.15 (2009), p. 150502
2009
-
[20]
Classical Electrodynamics
John David Jackson. Classical Electrodynamics. 3rd. New York: Wiley, 1998.isbn: 047130932X
1998
-
[21]
The cost of solving linear differential equations on a quan- tum computer: fast-forwarding to explicit resource counts
David Jennings et al. “The cost of solving linear differential equations on a quan- tum computer: fast-forwarding to explicit resource counts”. In:Quantum 8 (2024), p. 1553
2024
-
[22]
On Schr\
Shi Jin, Nana Liu, and Chuwen Ma. “On Schr\" odingerization based quantum algo- rithms for linear dynamical systems with inhomogeneous terms”. In:arXiv preprint arXiv:2402.14696 (2024)
2024 arXiv
-
[23]
Quantum Simulation of Partial Differential Equa- tions via Schrödingerization
Shi Jin, Nana Liu, and Yue Yu. “Quantum Simulation of Partial Differential Equa- tions via Schrödingerization”. In:Physical Review Letters133.23 (2024), p. 230602
2024
-
[24]
Improvedquantumalgorithmsforlinearandnonlineardifferentialequa- tions
HariKrovi.“Improvedquantumalgorithmsforlinearandnonlineardifferentialequa- tions”. In:Quantum 7 (2023), p. 913
2023
-
[25]
L. D. Landau and E. M. Lifshitz.Mechanics. 3rd. Vol. 1. Butterworth-Heinemann,
-
[26]
Potential quantum advantage for simulation of fluid dynamics
Xiangyu Li et al. “Potential quantum advantage for simulation of fluid dynamics”. In: Physical Review Research7.1 (2025), p. 013036. 77
2025
-
[27]
Efficient quantum algorithm for dissipative nonlinear differen- tial equations
Jin-Peng Liu et al. “Efficient quantum algorithm for dissipative nonlinear differen- tial equations”. In:Proceedings of the National Academy of Sciences118.35 (2021), e2026805118
2021
-
[28]
Universal quantum simulators
Seth Lloyd. “Universal quantum simulators”. In:Science 273.5278 (1996), pp. 1073– 1078
1996
-
[29]
Quantum algorithm for nonlinear differential equations
Seth Lloyd et al. “Quantum algorithm for nonlinear differential equations”. In:arXiv preprint arXiv:2011.06571 (2020)
2020 arXiv
-
[30]
Hamiltonian Simulation by Qubitization
Guang Hao Low and Isaac L. Chuang. “Hamiltonian Simulation by Qubitization”. In: Quantum 3 (2019), p. 163.doi: 10.22331/q-2019-07-12-163. arXiv:1610.06546 [quant-ph]
2019 arXiv
-
[31]
Nonlinear quantum search using the Gross– Pitaevskii equation
David A Meyer and Thomas G Wong. “Nonlinear quantum search using the Gross– Pitaevskii equation”. In:New Journal of Physics15.6 (2013), p. 063014
2013
-
[32]
Rate coherence and event coherence in the visual cortex: a neuronal model of object recognition
Hartmut Neven and Ad Aertsen. “Rate coherence and event coherence in the visual cortex: a neuronal model of object recognition”. In:Biological Cybernetics67 (1992), pp. 309–322. doi: 10.1007/BF02414887
1992 doi
-
[33]
Explicit quantum circuit for simu- lating the advection-diffusion-reaction dynamics
Claudio Sanavio, Enea Mauri, and Sauro Succi. “Explicit quantum circuit for simu- lating the advection-diffusion-reaction dynamics”. In:IEEE Transactions on Quan- tum Engineering(2025)
2025
-
[34]
Shadow hamiltonian simulation
Rolando D Somma et al. “Shadow hamiltonian simulation”. In:Nature Communi- cations 16.1 (2025), p. 2690
2025
-
[35]
Solving Free Fermion Problems on a Quantum Computer
Maarten Stroeks et al. “Solving Free Fermion Problems on a Quantum Computer”. In: arXiv preprint arXiv:2409.04550(2024)
2024
-
[36]
Quantum algorithms for systems of linear equations inspired by adiabatic quantum computing
Yiğit Subaşı, Rolando D Somma, and Davide Orsucci. “Quantum algorithms for systems of linear equations inspired by adiabatic quantum computing”. In:Physical review letters122.6 (2019), p. 060504
2019
-
[37]
Quantum algorithms based on the block-encoding frame- work for matrix functions by contour integrals
Souichi Takahira et al. “Quantum algorithms based on the block-encoding frame- work for matrix functions by contour integrals”. In:arXiv preprint arXiv:2106.08076 (2021)
2021 arXiv
-
[38]
Bright Wilson, J
E. Bright Wilson, J. C. Decius, and Paul C. Cross.Molecular Vibrations: The Theory of Infrared and Raman Vibrational Spectra. New York: Dover Publications, 1980. isbn: 048663941X
1980
-
[39]
Quantum Algorithms for Nonlin- ear Dynamics: Revisiting Carleman Linearization with No Dissipative Conditions
Hsuan-Cheng Wu, Jingyao Wang, and Xiantao Li. “Quantum Algorithms for Nonlin- ear Dynamics: Revisiting Carleman Linearization with No Dissipative Conditions”. In: arXiv preprint arXiv:2405.12714(2024)
2024 arXiv
-
[40]
Further improving quantum algorithms for non- linear differential equations
Jin Xue, Andrew M. Childs, et al. “Further improving quantum algorithms for non- linear differential equations”. In:arXiv preprint arXiv:2312.09518(2023). 78
2023 arXiv
Reviewed August 7, 2026 · model on record in the stance chip above.
Discussion (0). Sign in to comment.