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Lattice Hamiltonian systems underpin models across condensed matter, nonlinear optics, and biophysics, yet learning their dynamics from data is obstructed by two unknowns: the interaction topology and whether node dynamics are homogeneous.…

Machine Learning · Computer Science 2026-04-28 Ru Geng , Panayotis Kevrekidis , Yixian Gao , Hong-Kun Zhang , Jian Zu

We propose a hybrid quantum-classical algorithm to compute approximate solutions of binary combinatorial problems. We employ a shallow-depth quantum circuit to implement a unitary and Hermitian operator that block-encodes the weighted…

Quantum Physics · Physics 2023-06-16 Natacha Kuete Meli , Florian Mannel , Jan Lellmann

We propose a non-perturbative numerical approach to calculate the spectrum of a many-body Hamiltonian with time and momentum resolution by exactly recreating a scattering event using the time-dependent Schr\"odinger equation. Akin an actual…

Strongly Correlated Electrons · Physics 2021-01-04 Krissia Zawadzki , Luhang Yang , Adrian E. Feiguin

New algorithm of the finite lattice method is presented to generate the high-temperature expansion series of the Ising model. It enables us to obtain much longer series in three dimensions when compared not only to the previous algorithm of…

High Energy Physics - Lattice · Physics 2009-11-07 H. Arisue , T. Fujiwara

This work outlines a Lattice Boltzmann Method (LBM) for geometrically and constitutively nonlinear solid mechanics to simulate large deformations under dynamic loading conditions. The method utilizes the moment chain approach, where the…

Computational Engineering, Finance, and Science · Computer Science 2025-07-02 Henning Müller , Erik Faust , Alexander Schlüter , Ralf Müller

The quantum phase transition of the one-dimensional long-range transverse-field Ising model is explored by combining the quantum Monte Carlo method and stochastic parameter optimization, specifically achieved by tuning correlation ratios so…

Statistical Mechanics · Physics 2024-12-05 Sora Shiratani , Synge Todo

Although there is an extensive literature on the eigenvalues of high-dimensional sample covariance matrices, much of it is specialized to independent components (IC) models -- in which observations are represented as linear transformations…

Statistics Theory · Mathematics 2023-05-05 Siyao Wang , Miles E. Lopes

We propose the use of non-parametric, graph-based tests to assess the distributional balance of covariates in observational studies with multi-valued treatments. Our tests utilize graph structures ranging from Hamiltonian paths that connect…

Methodology · Statistics 2022-08-11 Eric A. Dunipace

We study the properties of the entanglement spectrum in gapped non-interacting non-Hermitian systems, and its relation to the topological properties of the system Hamiltonian. Two different families of entanglement Hamiltonians can be…

Mesoscale and Nanoscale Physics · Physics 2020-01-06 Loïc Herviou , Nicolas Regnault , Jens H. Bardarson

We consider geometric multigrid methods for the solution of linear systems arising from isogeometric discretizations of elliptic partial differential equations. For classical finite elements, such methods are well known to be fast solvers…

Numerical Analysis · Mathematics 2017-05-16 Clemens Hofreither , Stefan Takacs , Walter Zulehner

Spectroscopic tools are fundamental for the understanding of complex quantum systems. Here we demonstrate high-precision multi-band spectroscopy in a graphene-like lattice using ultracold fermionic atoms. From the measured band structure,…

We consider nearest neighbor spacing distributions of composite ensembles of levels. These are obtained by combining independently unfolded sequences of levels containing only few levels each. Two problems arise in the spectral analysis of…

Data Analysis, Statistics and Probability · Physics 2009-11-07 A. Y. Abul-Magd , H. L. Harney , M. H. Simbel , H. A. Weidenmueller

Machine learning methods are powerful in distinguishing different phases of matter in an automated way and provide a new perspective on the study of physical phenomena. We train a Restricted Boltzmann Machine (RBM) on data constructed with…

Statistical Mechanics · Physics 2020-09-23 Shotaro Shiba Funai , Dimitrios Giataganas

. The choice of a suitable random matrix model of a complex system is very sensitive to the nature of its complexity. The statistical spectral analysis of various complex systems requires, therefore, a thorough probing of a wide range of…

Statistical Mechanics · Physics 2009-10-31 Pragya Shukla

Degeneracies near the real axis in a complex-extended parameter space of a hermitian Hamiltonian are studied. We present a method to measure distributions of such degeneracies on the Riemann sheet of a selected level and apply it in…

Quantum Physics · Physics 2008-11-26 P. Cejnar , S. Heinze , M. Macek

One-dimensional all-bands-flat lattices are networks with all bands being flat and highly degenerate. They can always be diagonalized by a finite sequence of local unitary transformations parameterized by a set of angles \(\theta_{i}\). In…

Disordered Systems and Neural Networks · Physics 2023-07-13 Sanghoon Lee , Sergej Flach , Alexei Andreanov

The energy level spacing distribution of a tight-binding hamiltonian is monitored across the mobility edge for a fixed disorder strength. Any mixing of extended and localized levels is avoided in the configurational averages, thus…

Disordered Systems and Neural Networks · Physics 2009-10-30 Fabio Siringo , Giovanni Piccitto

We apply the Broad Histogram Method to an Ising system in the context of the recently reformulated Generalized Thermostatistics, and we claim it to be a very efficient simulation tool for this non-extensive statistics. Results are obtained…

Statistical Mechanics · Physics 2015-06-25 A. R. Lima , J. S. Sá Martins , T. J. P. Penna

Photonic Ising Machines constitute an emergent new paradigm of computation, geared towards tackling combinatorial optimization problems that can be reduced to the problem of finding the ground state of an Ising model. Spatial Photonic Ising…

We develop a novel algorithm for large-scale holographic reconstruction of 3D particle fields. Our method is based on a multiple-scattering beam propagation method (BPM) combined with sparse regularization that enables recovering dense 3D…

Optics · Physics 2021-05-24 Hao Wang , Waleed Tahir , Jiabei Zhu , Lei Tian
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