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Related papers: $TimeEvolver$: A Program for Time Evolution With I…

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The real- and imaginary-time evolution of quantum states are powerful tools in physics, chemistry, and beyond, to investigate quantum dynamics, prepare ground states or calculate thermodynamic observables. On near-term devices, variational…

Quantum Physics · Physics 2024-02-27 Julien Gacon , Jannes Nys , Riccardo Rossi , Stefan Woerner , Giuseppe Carleo

An efficient Krylov subspace algorithm for computing actions of the $\varphi$ matrix function for large matrices is proposed. This matrix function is widely used in exponential time integration, Markov chains and network analysis and many…

Numerical Analysis · Mathematics 2020-10-20 Mike A. Botchev , Leonid A. Knizhnerman , Eugene E. Tyrtyshnikov

Variational compression can significantly lower implementation overheads for encoding the time evolution of Hamiltonians into quantum circuits. However, they usually lack global convergence guarantees and well-established scaling behavior.…

We propose a numerical method for approximate calculations of the time evolution of point particle systems given only the system's Hamiltonian function and initial conditions. The method both generates and solves the equations of motion…

Computational Physics · Physics 2022-12-27 José M. L. Amoreira , Luís J. M. Amoreira

Simulating the time-evolution of quantum mechanical systems is BQP-hard and expected to be one of the foremost applications of quantum computers. We consider classical algorithms for the approximation of Hamiltonian dynamics using…

This work discusses a variational approach to determining the time evolution operator. We directly see a glimpse of how a generalization of the quantum geometric tensor for unitary operators plays a central role in parameter evolution. We…

Quantum Physics · Physics 2025-04-15 Michael Vogl

Nonequilibrium time evolution of large quantum systems is a strong candidate for quantum advantage. Variational quantum algorithms have been put forward for this task, but their quantum optimization routines suffer from trainability and…

Quantum Physics · Physics 2024-07-12 Refik Mansuroglu , Felix Fischer , Michael J. Hartmann

We study quantum dynamics generated by time-dependent Hamiltonians in Krylov space, the minimal subspace in which the evolution takes place. We establish a direct link between dynamics in the time-dependent Krylov subspace and the…

Quantum Physics · Physics 2026-05-18 András Grabarits , E. Medina-Guerra , Adolfo del Campo

We describe a method for removing the numerical errors in the modeling of linear evolution equations that are caused by approximating the time derivative by a finite difference operator. The method is based on integral transforms realized…

Numerical Analysis · Mathematics 2021-09-15 Jens Wittsten , Erik F. M. Koene , Fredrik Andersson , Johan O. A. Robertsson

Quantum systems governed by time-dependent Hamiltonians pose significant challenges for the accurate computation of unitary time-evolution operators, which are essential for predicting quantum state dynamics. In this work, we introduce a…

Quantum Physics · Physics 2026-01-21 Antonio Guerra , Daniel Uzcategui-Contreras , Aldo Delgado , Esteban S. Gómez

Quantum metrology allows for measuring properties of a quantum system at the optimal Heisenberg limit. However, when the relevant quantum states are prepared using digital Hamiltonian simulation, the accrued algorithmic errors will cause…

Quantum Physics · Physics 2024-02-28 Gumaro Rendon , Jacob Watkins , Nathan Wiebe

We present the problem of approximating the time-evolution operator $e^{-i\hat{H}t}$ to error $\epsilon$, where the Hamiltonian $\hat{H}=(\langle G|\otimes\hat{\mathcal{I}})\hat{U}(|G\rangle\otimes\hat{\mathcal{I}})$ is the projection of a…

Quantum Physics · Physics 2019-07-17 Guang Hao Low , Isaac L. Chuang

The (tolerant) Hamiltonian locality testing problem, introduced in [Bluhm, Caro,Oufkir `24], is to determine whether a Hamiltonian $H$ is $\varepsilon_1$-close to being $k$-local (i.e. can be written as the sum of weight-$k$ Pauli…

Quantum Physics · Physics 2025-05-13 John Kallaugher , Daniel Liang

Learning about a Hamiltonian $H$ from its time evolution $e^{-iHt}$ is a fundamental task in quantum science. A flurry of recent work has developed powerful new algorithms with provable guarantees for this task, for a variety of natural…

Quantum Physics · Physics 2026-04-20 Ziyun Chen , Jerry Li , Joseph Slote

We consider the problem of estimating parameters in large-scale weakly nonlinear inverse problems for which the underlying governing equations is a linear, time-dependent, parabolic partial differential equation. A major challenge in…

Numerical Analysis · Mathematics 2016-05-04 Tania Bakhos , Arvind K. Saibaba , Peter K. Kitanidis

Heisenberg time evolution under a chaotic many-body Hamiltonian $H$ transforms an initially simple operator into an increasingly complex one, as it spreads over Hilbert space. Krylov complexity, or `K-complexity', quantifies this growth…

High Energy Physics - Theory · Physics 2021-06-30 E. Rabinovici , A. Sánchez-Garrido , R. Shir , J. Sonner

An important aspect in understanding the dynamics in the context of deparametrized models of LQG is to obtain a sufficient control on the quantum evolution generated by a given Hamiltonian operator. More specifically, we need to be able to…

General Relativity and Quantum Cosmology · Physics 2017-08-02 Mehdi Assanioussi , Jerzy Lewandowski , Ilkka Mäkinen

Covariant Lyapunov vectors (CLVs) are useful in multiple applications, but the optimal time windows needed to accurately compute these vectors are yet unclear. To remedy this, we investigate two methods for determining when to safely…

Chaotic Dynamics · Physics 2026-04-14 Jean-Jacq du Plessis , Malcolm Hillebrand , Charalampos Skokos

We present a quantum algorithm for approximating the real time evolution $e^{-iHt}$ of an arbitrary $d$-sparse Hamiltonian to error $\epsilon$, given black-box access to the positions and $b$-bit values of its non-zero matrix entries. The…

Quantum Physics · Physics 2019-07-15 Guang Hao Low

We consider the problem of learning the evolution operator for the time-dependent Schr\"{o}dinger equation, where the Hamiltonian may vary with time. Existing neural network-based surrogates often ignore fundamental properties of the…

Machine Learning · Statistics 2026-04-07 Yash Patel , Unique Subedi , Ambuj Tewari