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Related papers: Hamiltonian Assignment for Open Quantum Systems

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In ergodic quantum systems, physical observables have a non-relaxing component if they "overlap" with a conserved quantity. In interacting microscopic models, how to isolate the non-relaxing component is unclear. We compute exact dynamical…

Statistical Mechanics · Physics 2019-11-13 Matteo Bellitti , Siddhardh Morampudi , Chris R. Laumann

In this work, we study the problems of certifying and learning quantum $k$-local Hamiltonians, for a constant $k$. Our main contributions are as follows: - Certification of Hamiltonians. We show that certifying a local Hamiltonian in…

Sampling the stationary points of a complicated potential energy landscape is a challenging problem. Here we introduce a sampling method based on relaxation from stationary points of the highest index of the Hessian matrix. We illustrate…

Statistical Mechanics · Physics 2014-07-25 Ciaran Hughes , Dhagash Mehta , David J Wales

We present a novel method to simulate the Lindblad equation, drawing on the relationship between Lindblad dynamics, stochastic differential equations, and Hamiltonian simulations. We derive a sequence of unitary dynamics in an enlarged…

Quantum Physics · Physics 2024-08-27 Zhiyan Ding , Xiantao Li , Lin Lin

We address the problem of simulating pair-interaction Hamiltonians in n node quantum networks where the subsystems have arbitrary, possibly different, dimensions. We show that any pair-interaction can be used to simulate any other by…

Quantum Physics · Physics 2023-11-27 Pawel Wocjan , Martin Roetteler , Dominik Janzing , Thomas Beth

Molecular quantum magnets adsorbed on surfaces exhibit rich spin and orbital excitations that can be probed by scanning tunneling microscopy with inelastic electron tunneling spectroscopy (STM-IETS). However, the quantitative extraction of…

Mesoscale and Nanoscale Physics · Physics 2026-01-28 Greta Lupi , Adolfo O. Fumega , Mohammad Amini , Robert Drost , Peter Liljeroth , Jose L. Lado

The rapid growth of research in exploiting machine learning to predict chaotic systems has revived a recent interest in Hamiltonian Neural Networks (HNNs) with physical constraints defined by the Hamilton's equations of motion, which…

Machine Learning · Computer Science 2021-06-02 Chen-Di Han , Bryan Glaz , Mulugeta Haile , Ying-Cheng Lai

We study the problem of learning the Hamiltonian of a quantum many-body system given samples from its Gibbs (thermal) state. The classical analog of this problem, known as learning graphical models or Boltzmann machines, is a well-studied…

Quantum Physics · Physics 2021-05-26 Anurag Anshu , Srinivasan Arunachalam , Tomotaka Kuwahara , Mehdi Soleimanifar

We show that the methods for quantification of system-environment entanglement that were recently developed for interactions that lead to pure decoherence of the system can be straightforwardly generalized to time-dependent Hamiltonians of…

Quantum Physics · Physics 2025-04-01 Małgorzata Strzałka , Radim Filip , Katarzyna Roszak

We extend random matrix theory to consider randomly interacting spin systems with spatial locality. We develop several methods by which arbitrary correlators may be systematically evaluated in a limit where the local Hilbert space dimension…

Statistical Mechanics · Physics 2020-01-08 Siddhardh C. Morampudi , Chris R. Laumann

The vast complexity is a daunting property of generic quantum states that poses a significant challenge for theoretical treatment, especially in non-equilibrium setups. Therefore, it is vital to recognize states which are locally less…

Quantum Physics · Physics 2022-07-28 Markus Schmitt , Zala Lenarčič

In recent decades the field of quantum computation has seen remarkable development. While much progress has been made toward the realization of a fully digital, scalable, and fault tolerant quantum computer, there are still many essential…

Quantum Physics · Physics 2025-07-31 Ian Pannemarsh

Accurately learning the temporal behavior of dynamical systems requires models with well-chosen learning biases. Recent innovations embed the Hamiltonian and Lagrangian formalisms into neural networks and demonstrate a significant…

Machine Learning · Computer Science 2021-10-04 Shaan Desai , Marios Mattheakis , David Sondak , Pavlos Protopapas , Stephen Roberts

This paper is concerned with variational methods for nonlinear open quantum systems with Markovian dynamics governed by Hudson-Parthasarathy quantum stochastic differential equations. The latter are driven by quantum Wiener processes of the…

Quantum Physics · Physics 2016-11-17 Igor G. Vladimirov

We propose an open-boundary molecular dynamics method in which an atomistic system is in contact with an infinite particle reservoir at constant temperature, volume and chemical potential. In practice, following the Hamiltonian adaptive…

Statistical Mechanics · Physics 2020-06-24 Maziar Heidari , Kurt Kremer , Ramin Golestanian , Raffaello Potestio , Robinson Cortes-Huerto

Measurement correlations in quantum systems can exhibit non-local behavior, a fundamental aspect of quantum mechanics with applications such as device-independent quantum information processing. However, the explicit construction of local…

Quantum Physics · Physics 2025-04-30 Nick von Selzam , Florian Marquardt

This paper is concerned with stochastic Hamiltonian systems which model a class of open dynamical systems subject to random external forces. Their dynamics are governed by Ito stochastic differential equations whose structure is specified…

Systems and Control · Computer Science 2018-06-29 Igor G. Vladimirov , Ian R. Petersen

In this paper, we present a Hamiltonian identification method for a closed quantum system whose time trace observables are measured with colored measurement noise. The dynamics of the quantum system are described by a Liouville equation…

Systems and Control · Computer Science 2020-10-20 Lingyu Tan , Daoyi Dong , Dewei Li , Shibei Xue

In this article, we introduce a framework for Hamiltonian tomography of multi-qubit systems with random noise. We adopt the quantum quench protocol to reconstruct a many-body Hamiltonian by local measurements that are distorted by random…

Quantum Physics · Physics 2021-11-30 Artur Czerwinski

We develop a computational method to learn a molecular Hamiltonian matrix from matrix-valued time series of the electron density. As we demonstrate for three small molecules, the resulting Hamiltonians can be used for electron density…

Computational Physics · Physics 2020-09-01 Harish S. Bhat , Karnamohit Ranka , Christine M. Isborn