Quantum simulation of non-Markovian dynamical systems
- URL: http://arxiv.org/abs/2608.13533v1
- Date: Thu, 13 Aug 2026 17:49:20 GMT
- Title: Quantum simulation of non-Markovian dynamical systems
- Abstract summary: Existing quantum algorithms for simulating dynamical systems simulate Markovian dynamics.<n>We develop quantum algorithms for non-Markovian dynamical systems where the system's future evolution depends on its past history.
- Score: 0.38233569758620045
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Existing quantum algorithms for simulating dynamical systems -- from Hamiltonian simulation to linear and nonlinear differential equations solvers -- simulate Markovian dynamics, in which the system's future evolution depends solely on its current state. We turn our attention to developing quantum algorithms for non-Markovian dynamical systems where the system's future evolution depends on its past history and thus has memory. Specifically, we develop efficient algorithms for linear Volterra integro-differential equations (VIDEs) with a convolution memory kernel that output a quantum state encoding the state description over a time interval or at a particular time. Given efficient circuits for the problem inputs, our algorithms achieve an exponential speedup in system size over existing classical algorithms. We develop an algorithm for general kernels assuming that $\textsf{M} < 1$, where $\textsf{M}$ characterizes the strength of the memory term relative to the dissipation of the Markovian part of the dynamics. We complement this with lower bounds for general-kernel VIDEs when $\textsf{M} \geq 1$, showing that the problem becomes intractable for a family of systems. However, by specializing to structured kernels which admit concise decompositions over exponentials, we develop efficient quantum algorithms even when $\textsf M \geq 1$ by converting the VIDE into a larger set of ODEs, a procedure which we call Markovianization. As an application of the overall framework, we discuss the Mori-Zwanzig formalism used in open quantum systems and fluid dynamics. Overall, our results expand the range of dynamical systems that quantum computers can simulate efficiently.
Related papers
- Efficient quantum algorithm for linear matrix differential equations and applications to open quantum systems [0.007807026251125201]
We present an efficient, nearly optimal quantum algorithm for solving linear matrix differential equations.<n>For unitary or dissipative dynamics, the algorithm computes an entry of the solution matrix with query $widetildemathcalO(mathcalL t/)$.<n>We demonstrate the utility of the algorithm through an end-to-end application, namely the simulation of dissipative dynamics for non-interacting fermions.
arXiv Detail & Related papers (2026-05-15T17:11:07Z) - Efficient construction of time-invariant process tensors for simulating high-dimensional non-Markovian open quantum systems [0.0]
We propose a new algorithm for computing process tensors--matrix product operator (MPO) representations.<n>MPO representations capture the environment influence--which achieves greatly enhanced computational scalings with system size.<n>The algorithm we introduce not only allows for capturing non-Markovian dynamics in large open quantum systems, but also further extends all the existing capabilities of process tensors.
arXiv Detail & Related papers (2026-03-06T20:02:43Z) - Quantum Differential Equation Solvers with Low State Preparation Cost: Eliminating the Time Dependence in Dissipative Equations [2.5677613431426978]
We propose efficient quantum algorithms for simulating linear dissipative differential equations.<n>The key idea of our algorithms is to perform the simulation only over an effective time period when the dynamics has not significantly dissipated yet.
arXiv Detail & Related papers (2025-08-21T02:17:21Z) - Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems [49.819436680336786]
We propose an efficient transformed Gaussian process state-space model (ETGPSSM) for scalable and flexible modeling of high-dimensional, non-stationary dynamical systems.<n>Specifically, our ETGPSSM integrates a single shared GP with input-dependent normalizing flows, yielding an expressive implicit process prior that captures complex, non-stationary transition dynamics.<n>Our ETGPSSM outperforms existing GPSSMs and neural network-based SSMs in terms of computational efficiency and accuracy.
arXiv Detail & Related papers (2025-03-24T03:19:45Z) - Quantum Simulation of Nonlinear Dynamical Systems Using Repeated Measurement [42.896772730859645]
We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations.
We apply this approach to the classic logistic and Lorenz systems in both integrable and chaotic regimes.
arXiv Detail & Related papers (2024-10-04T18:06:12Z) - Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems [77.88054335119074]
We use FNOs to model the evolution of random quantum spin systems.
We apply FNOs to a compact set of Hamiltonian observables instead of the entire $2n$ quantum wavefunction.
arXiv Detail & Related papers (2024-09-05T07:18:09Z) - Nonlinear dynamics as a ground-state solution on quantum computers [39.58317527488534]
We present variational quantum algorithms (VQAs) that encode both space and time in qubit registers.
The spacetime encoding enables us to obtain the entire time evolution from a single ground-state computation.
arXiv Detail & Related papers (2024-03-25T14:06:18Z) - The cost of solving linear differential equations on a quantum computer: fast-forwarding to explicit resource counts [0.0]
We give the first non-asymptotic computation of the cost of encoding the solution to general linear ordinary differential equations into quantum states.
We show that the stability properties of a large class of classical dynamics allow their fast-forwarding.
We find that the history state can always be output with complexity $O(T1/2)$ for any stable linear system.
arXiv Detail & Related papers (2023-09-14T17:25:43Z) - Simulating Markovian open quantum systems using higher-order series
expansion [1.713291434132985]
We present an efficient quantum algorithm for simulating the dynamics of Markovian open quantum systems.
Our algorithm is conceptually cleaner, and it only uses simple quantum primitives without compressed encoding.
arXiv Detail & Related papers (2022-12-05T06:02:50Z) - Efficient Fully-Coherent Quantum Signal Processing Algorithms for
Real-Time Dynamics Simulation [3.3917542048743865]
We develop fully-coherent simulation algorithms based on quantum signal processing (QSP)
We numerically analyze these algorithms by applying them to the simulation of spin dynamics of the Heisenberg model.
arXiv Detail & Related papers (2021-10-21T17:56:33Z) - Quantum algorithms for quantum dynamics: A performance study on the
spin-boson model [68.8204255655161]
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator.
variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware.
We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
arXiv Detail & Related papers (2021-08-09T18:00:05Z) - Fixed Depth Hamiltonian Simulation via Cartan Decomposition [59.20417091220753]
We present a constructive algorithm for generating quantum circuits with time-independent depth.
We highlight our algorithm for special classes of models, including Anderson localization in one dimensional transverse field XY model.
In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.
arXiv Detail & Related papers (2021-04-01T19:06:00Z) - Fast and differentiable simulation of driven quantum systems [58.720142291102135]
We introduce a semi-analytic method based on the Dyson expansion that allows us to time-evolve driven quantum systems much faster than standard numerical methods.
We show results of the optimization of a two-qubit gate using transmon qubits in the circuit QED architecture.
arXiv Detail & Related papers (2020-12-16T21:43:38Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.