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Gaussian fermionic matrix product states (GfMPS) form a class of ansatz quantum states for 1d systems of noninteracting fermions. We show, for a simple critical model of free hopping fermions, that: (i) any GfMPS approximation to its ground…

Quantum Physics · Physics 2022-12-28 Adrián Franco-Rubio , J. Ignacio Cirac

We propose a novel variational ansatz for the ground-state preparation of the $\mathbb{Z}_2$ lattice gauge theory (LGT) in quantum simulators. It combines dissipative and unitary operations in a completely deterministic scheme with a…

Quantum Physics · Physics 2024-08-28 Jesús Cobos , David F. Locher , Alejandro Bermudez , Markus Müller , Enrique Rico

Projected Entangled Pair States (PEPS) are a promising ansatz for the study of strongly correlated quantum many-body systems in two dimensions. But due to their high computational cost, developing and improving PEPS algorithms is necessary…

Quantum Physics · Physics 2014-09-05 Michael Lubasch , J. Ignacio Cirac , Mari-Carmen Bañuls

Tensor network methods have progressed from variational techniques based on matrix-product states able to compute properties of one-dimensional condensed-matter lattice models into methods rooted in more elaborate states such as projected…

Strongly Correlated Electrons · Physics 2021-08-23 C. Krumnow , L. Veis , J. Eisert , Ö. Legeza

Lattice Monte Carlo (MC) simulations and the functional Renormalization Group (RG) are powerful approaches that allow for quantitative studies of non-perturbative phenomena such as bound-state formation, spontaneous symmetry breaking and…

High Energy Physics - Lattice · Physics 2025-03-19 Niklas Zorbach , Jan Philipp Klinger , Owe Philipsen , Jens Braun

We develop an automated variational method for inference in models with Gaussian process (GP) priors and general likelihoods. The method supports multiple outputs and multiple latent functions and does not require detailed knowledge of the…

Machine Learning · Statistics 2018-11-06 Edwin V. Bonilla , Karl Krauth , Amir Dezfouli

The stochastic volatility model is a popular tool for modeling the volatility of assets. The model is a nonlinear and non-Gaussian state space model, and consequently is difficult to fit. Many approaches, both classical and Bayesian, have…

Methodology · Statistics 2019-07-22 Chen Gong , David S. Stoffer

Expectation propagation (EP) is a family of algorithms for performing approximate inference in probabilistic models. The updates of EP involve the evaluation of moments -- expectations of certain functions -- which can be estimated from…

Machine Learning · Statistics 2024-10-30 Jonathan So , Richard E. Turner

We discuss several methods that improve the partial-global stochastic Metropolis (PGSM) algorithm for smeared link staggered fermions. We present autocorrelation time measurements and argue that this update is feasible even on reasonably…

High Energy Physics - Lattice · Physics 2009-11-07 Anna Hasenfratz , Andrei Alexandru

Gaussian processes are a key component of many flexible statistical and machine learning models. However, they exhibit cubic computational complexity and high memory constraints due to the need of inverting and storing a full covariance…

Machine Learning · Statistics 2025-10-07 Teemu Härkönen , Sara Wade , Kody Law , Lassi Roininen

Lattice gauge theories describe fundamental phenomena in nature, but calculating their real-time dynamics on classical computers is notoriously difficult. In a recent publication [Nature 534, 516 (2016)], we proposed and experimentally…

Most Probable Explanation (MPE) inference in Probabilistic Graphical Models (PGMs) is a fundamental yet computationally challenging problem arising in domains such as diagnosis, planning, and structured prediction. In many practical…

Artificial Intelligence · Computer Science 2026-02-03 Brij Malhotra , Shivvrat Arya , Tahrima Rahman , Vibhav Giridhar Gogate

Multi-task/Multi-output learning seeks to exploit correlation among tasks to enhance performance over learning or solving each task independently. In this paper, we investigate this problem in the context of Gaussian Processes (GPs) and…

Machine Learning · Statistics 2018-05-10 Weitong Ruan , Eric L. Miller

We investigate a proposal for the construction of models with chiral fermions on the lattice using staggered fermions. In this approach the gauge invariance is broken by the coupling of the staggered fermions to the gauge fields. Motivated…

High Energy Physics - Lattice · Physics 2009-10-22 Wolfgang Bock , Jan Smit , Jeroen C. Vink

Gauge fixing is a frequent task encountered in practical lattice gauge theory calculations. We review the performance characteristics of some standard gauging procedures for non-abelian gauge theories, implemented on the parallel machines…

High Energy Physics - Lattice · Physics 2007-05-23 H. Suman , K. Schilling

The Gaussian graphical model (GGM) incorporates an undirected graph to represent the conditional dependence between variables, with the precision matrix encoding partial correlation between pair of variables given the others. To achieve…

Methodology · Statistics 2023-07-03 Yueqi Qian , Xianghong Hu , Can Yang

Chiral Spin Liquids (CSL) based on spin-1/2 fermionic Projected Entangled Pair States (fPEPS) are considered on the square lattice. First, fPEPS approximants of Gutzwiller-projected Chern insulators (GPCI) are investigated by Variational…

Strongly Correlated Electrons · Physics 2025-02-04 Sasank Budaraju , Didier Poilblanc , Sen Niu

We present an operational procedure to transform global symmetries into local symmetries at the level of individual quantum states, as opposed to typical gauging prescriptions for Hamiltonians or Lagrangians. We then construct a compatible…

Quantum Physics · Physics 2015-03-05 Jutho Haegeman , Karel Van Acoleyen , Norbert Schuch , J. Ignacio Cirac , Frank Verstraete

While gauge symmetry is a well-established requirement for representing topological orders in projected entangled-pair state (PEPS), its impact on the properties of low-lying excited states remains relatively unexplored. Here we perform…

Strongly Correlated Electrons · Physics 2024-09-11 Yi Tan , Ji-Yao Chen , Didier Poilblanc , Jia-Wei Mei

We present a new lattice Monte Carlo approach developed for studying large numbers of strongly interacting nonrelativistic fermions, and apply it to a dilute gas of unitary fermions confined to a harmonic trap. Our lattice action is highly…

High Energy Physics - Lattice · Physics 2011-11-04 Michael G. Endres , David B. Kaplan , Jong-Wan Lee , Amy N. Nicholson