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Subsystems of composite quantum systems are described by reduced density matrices, or quantum marginals. Important physical properties often do not depend on the whole wave function but rather only on the marginals. Not every collection of…

Quantum Physics · Physics 2014-10-31 Michael Walter

We introduce $k$-local quasi-quantum states: a superset of the regular quantum states, defined by relaxing the positivity constraint. We show that a $k$-local quasi-quantum state on $n$ qubits can be 1-1 mapped to a distribution of…

Quantum Physics · Physics 2025-01-27 Itai Arad , Miklos Santha

A central challenge in quantum simulation is to prepare low-energy states of strongly interacting many-body systems. In this work, we study the problem of preparing a quantum state that optimizes a random all-to-all, sparse or dense, spin…

Quantum Physics · Physics 2024-11-06 Joao Basso , Chi-Fang Chen , Alexander M. Dalzell

In this thesis, we present optimization tools for different problems in quantum information theory. First, we introduce an algorithm for quantum estate estimation. The algorithm consists of orthogonal projections on intersecting…

Quantum Physics · Physics 2022-04-19 Daniel Uzcategui Contreras

Variational quantum eigensolvers offer a small-scale testbed to demonstrate the performance of error mitigation techniques with low experimental overhead. We present successful error mitigation by applying the recently proposed symmetry…

We show how to optimally reduce the local Hilbert basis of lattice quantum many-body (QMB) Hamiltonians. The basis truncation exploits the most relevant eigenvalues of the estimated single-site reduced density matrix (RDM). It is accurate…

Strongly Correlated Electrons · Physics 2025-09-23 Peter Majcen , Giovanni Cataldi , Pietro Silvi , Simone Montangero

Self-testing refers to a device-independent way to uniquely identify the state and the measurement for uncharacterized quantum devices. The only information required comprises the number of measurements, the number of outputs of each…

Quantum Physics · Physics 2019-07-16 Xinhui Li , Yukun Wang , Yunguang Han , Fei Gao , Qiaoyan Wen

We present a technique for reducing the computational requirements by several orders of magnitude in the evaluation of semidefinite relaxations for bounding the set of quantum correlations arising from finite-dimensional Hilbert spaces. The…

Quantum Physics · Physics 2019-02-22 Armin Tavakoli , Denis Rosset , Marc-Olivier Renou

Given a mixture of states, finding a way to optimally discriminate its elements is a prominent problem in quantum communication theory. In this paper, we will address mixtures of density operators that are unitarily equivalent via elements…

Mathematical Physics · Physics 2024-02-09 Alberto Acevedo , Janek Wehr

Reduced density matrices (RDMs) are fundamental in quantum information processing, allowing the computation of local observables, such as energy and correlation functions, without the exponential complexity of fully characterizing quantum…

Quantum Physics · Physics 2025-06-13 Zherui Jerry Wang , David Dechant , Yash J. Patel , Jordi Tura

We consider the problem of minimum-error quantum state discrimination for single-qubit mixed states. We present a method which uses the Helstrom conditions constructively and analytically; this algebraic approach is complementary to…

Quantum Physics · Physics 2017-09-25 Graeme Weir , Stephen M. Barnett , Sarah Croke

The quantum many-body problem can be rephrased as a variational determination of the two-body reduced density matrix, subject to a set of N-representability constraints. The mathematical problem has the form of a semidefinite program. We…

Strongly Correlated Electrons · Physics 2011-10-27 B. Verstichel , H. van Aggelen , D. Van Neck , P. Bultinck , S. De Baerdemacker

An efficient numerical method is developed using the matrix product formalism for computing the properties at finite energy densities in one-dimensional (1D) many-body localized (MBL) systems. Arguing that any efficient (possibly quantum)…

Disordered Systems and Neural Networks · Physics 2015-08-20 Yichen Huang

Density matrix downfolding (DMD) is a technique for regressing low-energy effective Hamiltonians from quantum many-body Hamiltonians. One limiting factor in the accuracy of classical implementations of DMD is the presence of…

Solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be complex. Here, based on energy variance, we propose a variational method for solving the…

Quantum Physics · Physics 2024-02-21 Xu-Dan Xie , Zheng-Yuan Xue , Dan-Bo Zhang

Understanding extreme non-locality in many-body quantum systems can help resolve questions in thermostatistics and laser physics. The existence of symmetry selection rules for Hamiltonians with non-decaying terms on infinite-size lattices…

Strongly Correlated Electrons · Physics 2020-06-01 S. N. Saadatmand

We investigate whether the presence or absence of correlations between subsystems of an N-partite quantum system is solely constrained by the non-negativity and monotonicity of mutual information. We argue that this relatively simple…

Quantum states are represented by positive semidefinite Hermitian operators with unit trace, known as density matrices. An important subset of quantum states is that of separable states, the complement of which is the subset of…

Mathematical Physics · Physics 2020-12-04 Grigoriy Blekherman , H. M. Bharath

Self-testing is a phenomenon where the use of specific quantum states or measurements can be inferred solely from the correlations they generate. We introduce a universal method for conducting robustness analysis in the self-testing of…

Quantum Physics · Physics 2026-03-23 Shin-Liang Chen , Nikolai Miklin

Solving quantum many-body systems is one of the most significant regimes where quantum computing applies. Currently, as a hardware-friendly computational paradigms, variational algorithms are often used for finding the ground energy of…

Quantum Physics · Physics 2026-02-10 Yong Liu , Guangyao Huang , Yizhi Wang , Junjie Wu