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The fermionic quantum emulator (FQE) is a collection of protocols for emulating quantum dynamics of fermions efficiently taking advantage of common symmetries present in chemical, materials, and condensed-matter systems. The library is…

Evaluating quantum algorithms at utility-scale - involving more than 100 qubits - is a key step toward advancing real-world applications of quantum computing. In this study, we benchmark seven state-of-the-art quantum emulators employing…

While general quantum many-body systems require exponential resources to be simulated on a classical computer, systems of non-interacting fermions can be simulated exactly using polynomially scaling resources. Such systems may be of…

Strongly Correlated Electrons · Physics 2019-12-18 Norbert Schuch , Bela Bauer

We introduce a functional matrix product state (FMPS) based method for simulating the real-space representation of continuous-variable (CV) quantum computation. This approach efficiently simulates non-Gaussian CV systems by leveraging their…

Quantum Physics · Physics 2026-03-26 Andreas Bock Michelsen , Frederik K. Marqversen , Michael Kastoryano

We investigate the use of matrix product states (MPS) to approximate ground states of critical quantum spin chains with periodic boundary conditions (PBC). We identify two regimes in the (N,D) parameter plane, where N is the size of the…

Statistical Mechanics · Physics 2013-02-08 B. Pirvu , G. Vidal , F. Verstraete , L. Tagliacozzo

In this work, we report, for the first time, an implementation of fermionic auxiliary-field quantum Monte Carlo (AFQMC) using matrix product state (MPS) trial wavefunctions, dubbed MPS-AFQMC. Calculating overlaps between an MPS trial and…

Chemical Physics · Physics 2025-01-13 Tong Jiang , Bryan O'Gorman , Ankit Mahajan , Joonho Lee

Encoding classical data in a quantum state is a key prerequisite of many quantum algorithms. Recently matrix product state (MPS) methods emerged as the most promising approach for constructing shallow quantum circuits approximating input…

Recent work by Wu {\em et al.} [arXiv:1910.11011] proposed a numerical method, so-called matrix product operator-matrix product state (MPO-MPS) method, by which several types of quantum many-body wave functions, in particular, the projected…

Strongly Correlated Electrons · Physics 2020-04-29 Hui-Ke Jin , Hong-Hao Tu , Yi Zhou

As in the density matrix renormalization group (DMRG) method, approximating many-body wave function of electrons using a matrix product state (MPS) is a promising way to solve electronic structure problems. The expressibility of an MPS is…

Quantum Physics · Physics 2023-01-18 Yi Fan , Jie Liu , Zhenyu Li , Jinlong Yang

Numerical simulations are a powerful tool to study quantum systems beyond exactly solvable systems lacking an analytic expression. For one-dimensional entangled quantum systems, tensor network methods, amongst them Matrix Product States…

Quantum Gases · Physics 2018-02-28 Daniel Jaschke , Michael L. Wall , Lincoln D. Carr

In this work, we develop a stochastic matrix product state (stoMPS) approach that combines the MPS technique and Monte Carlo samplings and can be applied to simulate quantum lattice models down to low temperature. In particular, we exploit…

Strongly Correlated Electrons · Physics 2023-12-08 Jianxin Gao , Yuan Gao , Qiaoyi Li , Wei Li

In the era of noisy intermediate scale quantum (NISQ) hardware, digital quantum computers are limited to shallow circuits on the order of a thousand layers due to system noise and qubit decoherence. Thus, every step of a simulation must be…

Quantum Physics · Physics 2026-02-26 Michael Hite

We present ffsim, an open-source software library for fast simulation of fermionic quantum circuits. ffsim exploits conservation of particle number and the z component of spin, symmetries present in a wide range of fermionic systems, to…

Clifford circuits Augmented Matrix Product States (CAMPS) was recently proposed to leverage the advantages of both Clifford circuits and Matrix Product States (MPS). Clifford circuits can support large entanglement and can be efficiently…

Strongly Correlated Electrons · Physics 2025-01-03 Jiale Huang , Xiangjian Qian , Mingpu Qin

Data representation in quantum state space offers an alternative function space for machine learning tasks. However, benchmarking these algorithms at a practical scale has been limited by ineffective simulation methods. We develop a quantum…

Quantum Physics · Physics 2024-11-15 Mekena Metcalf , Pablo Andrés-Martínez , Nathan Fitzpatrick

QwaveMPS is an open-source Python library for simulating one-dimensional quantum many-body waveguide systems using matrix product states (MPS). It provides a user-friendly interface for constructing, evolving, and analyzing quantum states…

Quantum Physics · Physics 2026-02-26 Sofia Arranz Regidor , Matthew Kozma , Stephen Hughes

Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, quantum resource is too scarce to support these…

Quantum Physics · Physics 2023-03-08 Honghui Shang , Yi Fan , Li Shen , Chu Guo , Jie Liu , Xiaohui Duan , Fang Li , Zhenyu Li

A generic method to investigate many-body continuous-variable systems is pedagogically presented. It is based on the notion of matrix product states (so-called MPS) and the algorithms thereof. The method is quite versatile and can be…

Strongly Correlated Electrons · Physics 2013-05-29 S. Iblisdir , R. Orus , J. I. Latorre

The matrix product state (MPS) belongs to the most important mathematical models in, for example, condensed matter physics and quantum information sciences. However, to realize an $N$-qubit MPS with large $N$ and large entanglement on a…

Quantum Physics · Physics 2020-03-11 Shi-Ju Ran

Tensor networks establish an adaptable framework for the emulation of quantum circuits. By partitioning exponentially large registers and gates into smaller tensors, this unlocks fast transformations through tensor algebra, and grants fine…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-13 Jakub Adamski , Oliver Thomson Brown
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