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I revisit the infinite-size variant of the Density Matrix Renormalization Group (iDMRG) algorithm for obtaining a fixed-point translationally invariant matrix product wavefunction in the context of one-dimensional quantum systems. A crucial…

Strongly Correlated Electrons · Physics 2008-04-17 I. P. McCulloch

The Global Navigation Satellite System (GNSS) daily position time series are often described as the sum of stochastic processes and geophysical signals which allow studying global and local geodynamical effects such as plate tectonics,…

We generalize the Gutzwiller approximation scheme to the calculation of nontrivial matrix elements between the ground state and excited states. In our scheme, the normalization of the Gutzwiller wave function relative to a partially…

Strongly Correlated Electrons · Physics 2009-11-11 N. Fukushima , B. Edegger , V. N. Muthukumar , C. Gros

In this paper we give an introduction to the numerical density matrix renormalization group (DMRG) algorithm, from the perspective of the more general matrix product state (MPS) formulation. We cover in detail the differences between the…

Strongly Correlated Electrons · Physics 2009-11-13 Ian P. McCulloch

The projection of time-dependent variational principle (TDVP) for matrix product states enables us to perform long-time simulations of one-dimensional quantum systems with the conservation of the total energy and the norm of wave functions.…

Strongly Correlated Electrons · Physics 2019-02-25 Shimpei Goto , Ippei Danshita

The determination of the ground state of quantum many-body systems via digital quantum computers rests upon the initialization of a sufficiently educated guess. This requirement becomes more stringent the greater the system. Preparing…

Quantum Physics · Physics 2021-06-30 Bruno Murta , Joaquín Fernández-Rossier

We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple…

Strongly Correlated Electrons · Physics 2016-12-01 Katsunori Kubo , Hiroaki Onishi

In this note, we describe a method for reconstructing matrix product states from a small number of efficiently-implementable measurements. Our method is exponentially faster than standard tomography, and it can also be used to certify that…

Quantum Physics · Physics 2010-02-26 Olivier Landon-Cardinal , Yi-Kai Liu , David Poulin

We introduce Gaussian Matrix Product States (GMPS), a generalization of Matrix Product States (MPS) to lattices of harmonic oscillators. Our definition resembles the interpretation of MPS in terms of projected maximally entangled pairs,…

Quantum Physics · Physics 2012-01-20 Norbert Schuch , Michael M. Wolf , J. Ignacio Cirac

Generalized Plane Waves (GPWs) were introduced to take advantage of Trefftz methods for problems modeled by variable coefficient equations. Despite the fact that GPWs do not satisfy the Trefftz property, i.e. they are not exact solutions to…

Numerical Analysis · Mathematics 2025-09-09 Lise-Marie Imbert-Gerard

We present a novel approach to the separability problem for Gaussian quantum states of bosonic continuous variable systems. We derive a simplified necessary and sufficient separability criterion for arbitrary Gaussian states of $m$ vs $n$…

Quantum Physics · Physics 2018-02-22 Ludovico Lami , Alessio Serafini , Gerardo Adesso

The accuracy of Bayesian inference can be negatively affected by the use of inaccurate forward models. In the case of gravitational-wave inference, accurate but computationally expensive waveform models are sometimes substituted with faster…

Instrumentation and Methods for Astrophysics · Physics 2024-04-02 Miaoxin Liu , Xiao-Dong Li , Alvin J. K. Chua

For the discretization of the convective term in the Navier-Stokes equations (NSEs), the commonly used convective formulation (CONV) does not preserve the energy if the divergence constraint is only weakly enforced. In this paper, we apply…

Numerical Analysis · Mathematics 2021-12-07 Xu Li , Hongxing Rui

Understanding the interplay between electronic correlations and band topology remains a central challenge in condensed matter physics, primarily hindered by a language mismatch problem. While band topology is naturally formulated within a…

The Gromov-Wasserstein (GW) framework adapts ideas from optimal transport to allow for the comparison of probability distributions defined on different metric spaces. Scalable computation of GW distances and associated matchings on graphs…

Machine Learning · Computer Science 2021-05-05 Samir Chowdhury , David Miller , Tom Needham

Matrix product states (MPS) and `dressed' ground states of quadratic mean fields (e.g. Gutzwiller projected Slater Determinants) are both important classes of variational wave-functions. This latter class has played important roles in…

Strongly Correlated Electrons · Physics 2021-04-07 Gabriel Petrica , Bo-Xiao Zheng , Garnet Kin-Lic Chan , Bryan K. Clark

Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing benchmarks. However, the escalating scale of model parameters imposes prohibitive memory overheads during training,…

Machine Learning · Computer Science 2026-04-28 Ziqing Wen , Ping Luo , Jiahuan Wang , Kun Yuan , Dongsheng Li , Tao Sun

The van der Waals (VDW) equation of state describes a thermal equilibrium in system of particles, where both repulsive and attractive interactions between them are included. This equation predicts an existence of the 1st order liquid-gas…

Nuclear Theory · Physics 2016-08-25 V. Vovchenko , D. V. Anchishkin , M. I. Gorenstein

The property of quantum many-body systems under spatial reflection and the relevant physics of renormalization group (RG) procedure are revealed. By virtue of the matrix product state (MPS) representation, various attributes for…

Quantum Physics · Physics 2011-08-08 Li-Xiang Cen , Z. D. Wang

Despite their tremendous successes, convolutional neural networks (CNNs) incur high computational/storage costs and are vulnerable to adversarial perturbations. Recent works on robust model compression address these challenges by combining…

Machine Learning · Computer Science 2021-11-09 Hassan Dbouk , Naresh R. Shanbhag