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The magnetic properties of solids are typically analyzed in terms of Heisenberg models where the electronic structure is approximated by interacting localized spins. However, even in such models the evaluation of thermodynamic properties…

Materials Science · Physics 2025-01-31 Varun Rajeev Pavizhakumari , Thorbjørn Skovhus , Thomas Olsen

The need for Hamiltonians with many-body interactions arises in various applications of quantum computing. However, interactions beyond two-body are difficult to realize experimentally. Perturbative gadgets were introduced to obtain…

Quantum Physics · Physics 2016-08-03 Yigit Subasi , Christopher Jarzynski

The difficulty of simulating quantum dynamics depends on the norm of the Hamiltonian. When the Hamiltonian varies with time, the simulation complexity should only depend on this quantity instantaneously. We develop quantum simulation…

Quantum Physics · Physics 2020-04-21 Dominic W. Berry , Andrew M. Childs , Yuan Su , Xin Wang , Nathan Wiebe

Given a time-independent Hamiltonian $\widetilde H$, one can construct a time-dependent Hamiltonian $H_t$ by means of the gauge transformation $H_t=U_t \widetilde H \, U^\dagger_t-i\, U_t\, \partial_t U_t^\dagger$. Here $U_t$ is the unitary…

Quantum Physics · Physics 2021-08-04 Oleksandr Gamayun , Oleg Lychkovskiy

The physics of a closed quantum mechanical system is governed by its Hamiltonian. However, in most practical situations, this Hamiltonian is not precisely known, and ultimately all there is are data obtained from measurements on the system.…

We investigate the feasibility of simulating different model Hamiltonians used in high-temperature superconductivity. We briefly discuss the most common models and then focus on the simulation of the so-called t-J-U Hamiltonian using…

Quantum Physics · Physics 2007-05-23 Alexander Klein , Dieter Jaksch

Constructing robust simulators is essential for asking "what if?" questions and guiding policy in critical domains like healthcare and logistics. However, existing methods often struggle, either failing to generalize beyond historical data…

Machine Learning · Computer Science 2025-06-12 Samuel Holt , Max Ruiz Luyten , Antonin Berthon , Mihaela van der Schaar

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…

This paper proposes a probabilistic Bayesian formulation for system identification (ID) and estimation of nonseparable Hamiltonian systems using stochastic dynamic models. Nonseparable Hamiltonian systems arise in models from diverse…

Dynamical Systems · Mathematics 2022-09-19 Harsh Sharma , Nicholas Galioto , Alex A. Gorodetsky , Boris Kramer

We investigate the classical counterpart of an effective Hamiltonian for a strongly trimerized kagome lattice. Although the Hamiltonian only has a discrete symmetry, the classical groundstate manifold has a continuous global rotational…

Statistical Mechanics · Physics 2007-05-23 A. Honecker , D. C. Cabra , H. -U. Everts , P. Pujol , F. Stauffer

We investigate the problem of determining the Hamiltonian of a locally interacting open-quantum system. To do so, we construct model estimators based on inverting a set of stationary, or dynamical, Heisenberg-Langevin equations of motion…

Quantum Physics · Physics 2020-08-19 Eugene F. Dumitrescu , Pavel Lougovski

The Hamiltonian formalism plays a central role in classical and quantum physics. Hamiltonians are the main tool for modelling the continuous time evolution of systems with conserved quantities, and they come equipped with many useful…

Machine Learning · Computer Science 2020-02-17 Peter Toth , Danilo Jimenez Rezende , Andrew Jaegle , Sébastien Racanière , Aleksandar Botev , Irina Higgins

Monte Carlo simulation using the standard single-spin flip algorithm often fails to sample over the entire configuration space at low temperatures for frustrated spin systems. A typical example is a class of spin-ice type Ising models. In…

Statistical Mechanics · Physics 2011-09-30 Hiroshi Shinaoka , Yusuke Tomita , Yukitoshi Motome

We present a purely numerical approach in Cartesian grid, for efficient computation of Hartree-Fock (HF) exchange contribution in the HF and density functional theory models. This takes inspiration from a recently developed algorithm [Liu…

Chemical Physics · Physics 2019-04-05 Abhisek Ghosal , Tanmay Mandal , Amlan K. Roy

Simulating the time evolution of quantum field theories given some Hamiltonian $H$ requires developing algorithms for implementing the unitary operator e^{-iHt}. A variety of techniques exist that accomplish this task, with the most common…

Particle collisions at accelerators such as the Large Hadron Collider, recorded and analyzed by experiments such as ATLAS and CMS, enable exquisite measurements of the Standard Model and searches for new phenomena. Simulations of collision…

We construct an effective Hamiltonian via Monte Carlo from a given action. This Hamiltonian describes physics in the low energy regime. We test it by computing spectrum, wave functions and thermodynamical observables (average energy and…

Quantum Physics · Physics 2009-10-31 H. Jirari , H. Kröger , X. Q. Luo , K. J. M. Moriarty

In this paper, we consider the task of efficiently computing the numerical solution of evolutionary complex Ginzburg--Landau equations on Cartesian product domains with homogeneous Dirichlet/Neumann or periodic boundary conditions. To this…

Numerical Analysis · Mathematics 2024-06-19 Marco Caliari , Fabio Cassini

This paper uses the capabilities of latent diffusion models (LDMs) to generate realistic RGB human-object interaction scenes to guide humanoid loco-manipulation planning. To do so, we extract from the generated images both the contact…

Robotics · Computer Science 2025-04-24 Ilyass Taouil , Haizhou Zhao , Angela Dai , Majid Khadiv

Self-learning hybrid Monte Carlo (SLHMC) is a first-principles simulation that allows for exact ensemble generation on potential energy surfaces based on density functional theory. The statistical sampling can be accelerated with the…

Disordered Systems and Neural Networks · Physics 2021-07-28 Keita Kobayashi , Yuki Nagai , Mitsuhiro Itakura , Motoyuki Shiga