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We ask whether the knowledge of a single eigenstate of a local Hamiltonian is sufficient to uniquely determine the Hamiltonian. We present evidence that the answer is "yes" for generic local Hamiltonians, given either the ground state or an…

Quantum Physics · Physics 2019-07-10 Xiao-Liang Qi , Daniel Ranard

Quantum many body physics simulations with Matrix Product States can often be accelerated if the quantum symmetries present in the system are explicitly taken into account. Conventionally, quantum symmetries have to be determined before…

Quantum Physics · Physics 2019-10-17 Chu Guo , Dario Poletti

Understanding quantum phases of matter is a fundamental goal in physics. For pure states, the representatives of phases are the ground states of locally interacting Hamiltonians, which are also renormalization fixed points (RFPs). These RFP…

Using numerical exact diagonalization, we study matrix elements of a local spin operator in the eigenbasis of two different nonintegrable quantum spin chains. Our emphasis is on the question to what extent local operators can be represented…

Statistical Mechanics · Physics 2020-10-27 Jonas Richter , Anatoly Dymarsky , Robin Steinigeweg , Jochen Gemmer

We present a novel classical algorithm designed to learn the stabilizer group -- namely the group of Pauli strings for which a state is a $\pm 1$ eigenvector -- of a given Matrix Product State (MPS). The algorithm is based on a clever and…

Quantum Physics · Physics 2024-01-31 Guglielmo Lami , Mario Collura

We quantify the representational power of matrix product states (MPS) for entangled qubit systems by giving polynomial expressions in a pure quantum state's amplitudes which hold if and only if the state is a translation invariant matrix…

Quantum Physics · Physics 2014-09-11 Andrew Critch , Jason Morton

Local-operator entanglement (LOE) quantifies the nonlocal structure of Heisenberg operators and serves as a diagnostic of many-body chaos. We provide rigorous bounds showing when an operator can be well-approximated by a matrix-product…

Quantum Physics · Physics 2026-05-27 Neil Dowling

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

Matrix Product State (MPS) wavefunctions have many applications in quantum information and condensed matter physics. One application is to represent states in the thermodynamic limit directly, using a small set of position independent…

Statistical Mechanics · Physics 2010-08-30 L. Michel , I. P. McCulloch

We introduce an approach for exploring eigenvector localization phenomena for a class of (unbounded) selfadjoint operators. More specifically, given a target region and a tolerance, the algorithm identifies candidate eigenpairs for which…

Numerical Analysis · Mathematics 2021-06-01 Jeffrey Ovall , Robyn Reid

We study quantum states generated by a sequence of nearest neighbor bipartite entangling operations along a one-dimensional chain of spin qubits. After a single sweep of such a set of operations, the system is effectively described by a…

Quantum Physics · Physics 2017-11-01 Tahereh Abad , Klaus Mølmer , Vahid Karimipour

Quantum trajectories and superoperator algorithms implemented within the matrix product state (MPS) framework are powerful tools to simulate the real-time dynamics of open dissipative quantum systems. As for the unitary case, the reachable…

Quantum Gases · Physics 2014-11-19 Lars Bonnes , Andreas M. Läuchli

In this work, we investigate the universal representation capacity of the Matrix Product States (MPS) from the perspective of boolean functions and continuous functions. We show that MPS can accurately realize arbitrary boolean functions by…

Machine Learning · Statistics 2025-10-16 Erdong Guo , David Draper

We derive symmetry-based conditions for tight-binding Hamiltonians with flatbands to have compact localized eigenstates occupying a single unit cell. The conditions are based on unitary operators commuting with the Hamiltonian and…

Mesoscale and Nanoscale Physics · Physics 2024-11-26 Jung-Wan Ryu , Alexei Andreanov , Hee Chul Park , Jae-Ho Han

The practical success of polynomial-time tensor network methods for computing ground states of certain quantum local Hamiltonians has recently been given a sound theoretical basis by Arad, Landau, Vazirani, and Vidick. The convergence…

Statistical Mechanics · Physics 2018-02-14 Brenden Roberts , Thomas Vidick , Olexei I. Motrunich

Tensor product state (TPS) based methods are powerful tools to efficiently simulate quantum many-body systems in and out of equilibrium. In particular, the one-dimensional matrix-product (MPS) formalism is by now an established tool in…

Strongly Correlated Electrons · Physics 2018-12-03 Johannes Hauschild , Frank Pollmann

In this work, we prove that any element in the tensor product of separable infinite-dimensional Hilbert spaces can be expressed as a matrix product state (MPS) of possibly infinite bond dimension. The proof is based on the singular value…

Mathematical Physics · Physics 2025-08-12 Niilo Heikkinen

We present a general method for simulating lattice gauge theories in low dimensions using infinite matrix product states (iMPS). A central challenge in Hamiltonian formulations of gauge theories is the unbounded local Hilbert space…

Strongly Correlated Electrons · Physics 2025-08-21 Nicholas Godfrey , Ian P. McCulloch

Learning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors. While various tomographic methods such as classical shadow and MPS tomography have shown…

Limited resources motivate decomposing large-scale problems into smaller,``local" subsystems and stitching together the so-found solutions. We explore the physics underlying this approach and discuss the concept of ``local hardness", i.e.,…

Disordered Systems and Neural Networks · Physics 2025-12-24 Mutian Shen , Gerardo Ortiz , Zhiqiao Dong , Martin Weigel , Zohar Nussinov