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Trial wavefunctions that can be represented by summing over locally-coupled degrees of freedom are called tensor network states (TNSs); they have seemed difficult to construct for two-dimensional topological phases that possess protected…

Mesoscale and Nanoscale Physics · Physics 2015-11-25 J. Dubail , N. Read

In stochastic modeling, there has been a significant effort towards finding predictive models that predict a stochastic process' future using minimal information from its past. Meanwhile, in condensed matter physics, matrix product states…

Quantum Physics · Physics 2019-02-05 Chengran Yang , Felix C. Binder , Varun Narasimhachar , Mile Gu

We study the second-order quantum phase-transition of massive real scalar field theory with a quartic interaction ($\phi^4$ theory) in (1+1) dimensions on an infinite spatial lattice using matrix product states (MPS). We introduce and apply…

High Energy Physics - Lattice · Physics 2014-05-16 Ashley Milsted , Jutho Haegeman , Tobias J. Osborne

Self-consistent dynamical approximations for strongly correlated fermion systems are particularly successful in capturing the dynamical competition of local correlations. In these, the effect of spatially extended degrees of freedom is…

Strongly Correlated Electrons · Physics 2014-06-12 Andrey E. Antipov , Emanuel Gull , Stefan Kirchner

We describe a matrix product state (MPS) extension for the Fermionic Quantum Emulator (FQE) software library. We discuss the theory behind symmetry adapted matrix product states for approximating many-body wavefunctions of spin-1/2…

Matrix product states (MPS) are a central language for one-dimensional quantum matter and a practical target for near-term quantum simulators and variational algorithms. Yet, while substantial effort has focused on preparing MPS with…

Quantum Physics · Physics 2026-04-21 Hyunho Cha , Subin Kim , Jungwoo Lee

The study of frustration-free Hamiltonians and their relation to finite bond-dimension matrix product states (MPS) has a long tradition. However, fractional quantum Hall (FQH) states do not quite fit into this theme since the known MPS…

Strongly Correlated Electrons · Physics 2024-02-06 Matheus Schossler , Li Chen , Alexander Seidel

Lattice gauge theories (LGTs) provide a powerful framework for studying non-perturbative phenomena in gauge theories. However, conventional approaches such as Monte Carlo (MC) simulations in imaginary time are limited, as they do not allow…

High Energy Physics - Lattice · Physics 2025-12-17 Itay Gomelski , Jonathan Elyovich , Ariel Kelman , Erez Zohar , Patrick Emonts

Matrix-product state (MPS) skeletons are connected networks of Hamiltonians with exact MPS ground states that underlie a phase diagram. Such skeletons have previously been found in classes of free-fermion models. For the…

Quantum Physics · Physics 2025-11-11 Imogen Camp , Nick G. Jones

Correlated electron states are at the root of many important phenomena including unconventional superconductivity (USC), where electron-pairing arises from repulsive interactions. Computing the properties of correlated electrons, such as…

A generalization of matrix product states (MPS) is introduced which is suitable for describing interacting quantum systems in two and three dimensions. These scale-renormalized matrix-product states (SR-MPS) are based on a course-graining…

Strongly Correlated Electrons · Physics 2010-10-13 Anders W. Sandvik

We consider the problem of approximating ground states of one-dimensional quantum systems within the two most common variational ansatzes, namely the mean field ansatz and Matrix Product States. We show that both for mean field and for…

Quantum Physics · Physics 2010-07-20 Norbert Schuch , J. Ignacio Cirac

Tensor network states, especially Matrix Product States (MPS), are crucial tools for studying how particles in large quantum systems are entangled with each other. MPS are particularly effective for modeling systems in one-dimensional…

High Energy Physics - Theory · Physics 2025-02-03 Niloofar Vardian

Tensor network quantum states are powerful tools for strongly correlated systems, tailored to capture local correlations such as in ground states with entanglement area laws. When applying tensor network states to interacting fermionic…

Strongly Correlated Electrons · Physics 2025-01-10 Ang-Kun Wu , Benedikt Kloss , Wladislaw Krinitsin , Matthew T. Fishman , J. H. Pixley , E. M. Stoudenmire

Gaussian matrix product states are obtained as the outputs of projection operations from an ancillary space of M infinitely entangled bonds connecting neighboring sites, applied at each of N sites of an harmonic chain. Replacing the…

Quantum Physics · Physics 2007-05-23 Gerardo Adesso , Marie Ericsson

Gauged fermionic projected entangled pair states (GFPEPS) and their Gaussian counterpart (GGFPEPS) are a novel type of lattice gauge theory Ansatz state that combine ideas from the Monte Carlo and tensor network communities. In particular,…

High Energy Physics - Lattice · Physics 2025-10-08 Gertian Roose , Erez Zohar

In the last few years, the methods of constructive Fermionic Renormalization Group have been successfully applied to the study of the scaling limit of several two-dimensional statistical mechanics models at the critical point, including:…

Probability · Mathematics 2019-10-23 Alessandro Giuliani , Fabio Lucio Toninelli

Magic states, pivotal for universal quantum computation via classically simulable Clifford gates, often undergo decomposition into resourceless stabilizer states, facilitating simulation through classical means. This approach yields three…

Quantum Physics · Physics 2025-09-09 Joshua Cudby , Sergii Strelchuk

One-dimensional massive quantum particles (or 1+1-dimensional random walks) with short-ranged multi-particle interactions are studied by exact renormalization group methods. With repulsive pair forces, such particles are known to scale as…

Condensed Matter · Physics 2015-06-25 M. Lassig

The Gaussian process state space model (GPSSM) is a non-linear dynamical system, where unknown transition and/or measurement mappings are described by GPs. Most research in GPSSMs has focussed on the state estimation problem, i.e.,…

Machine Learning · Statistics 2017-11-08 Stefanos Eleftheriadis , Thomas F. W. Nicholson , Marc Peter Deisenroth , James Hensman