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We prove that the empirical density of states of quantum spin glasses on arbitrary graphs converges to a normal distribution as long as the maximal degree is negligible compared with the total number of edges. This extends the recent…

Mathematical Physics · Physics 2016-10-25 László Erdős , Dominik Schröder

Low-energy estimation and state preparation for general $k$-local Hamiltonians are fundamental challenges in quantum complexity theory. For constant relative accuracy, Buhrman et al. (PRL 2025) recently broke the natural Grover bound…

Quantum Physics · Physics 2026-05-19 Ranitha Mataraarachchi , François Le Gall , Suguru Tamaki

Quantum simulation is a promising application of future quantum computers. Product formulas, or Trotterization, are the oldest and still remain an appealing method to simulate quantum systems. For an accurate product formula approximation,…

Quantum Physics · Physics 2024-11-04 Chi-Fang , Chen , Fernando G. S. L. Brandão

We present a numerical study of ground states of the dilute versions of the Sherrington-Kirkpatrick (SK) mean-field spin glass. In contrast to so-called "sparse" mean-field spin glasses that have been studied widely on random networks of…

Disordered Systems and Neural Networks · Physics 2022-04-21 Stefan Boettcher

In this paper we develop a method introduced by one of us to study metastable states in spin glasses. We consider a `potential function' defined as the free energy of a system at a given temperature $T$ constrained to have a fixed overlap…

Condensed Matter · Physics 2009-10-28 S. Franz , G. Parisi

It has been observed recently that various spin chain Hamiltonians admit special zero energy "crosscap" eigenstates. These states are made up of maximally entangled Bell pairs prepared on antipodal sites of a periodic chain. We generalize…

Statistical Mechanics · Physics 2025-03-21 Márton Mestyán , Balázs Pozsgay

We present an algorithm for finding ground states of two dimensional spin glass systems based on ideas from matrix product states in quantum information theory. The algorithm works directly at zero temperature and defines an approximate…

Disordered Systems and Neural Networks · Physics 2009-11-13 M. B. Hastings

We propose a tensor-network (TN) approach for solving classical optimization problems that is inspired by spectral filtering and sampling on quantum states. We first shift and scale an Ising Hamiltonian of the cost function so that all…

Quantum Physics · Physics 2026-02-09 Ryo Watanabe , Joseph Tindall , Shohei Miyakoshi , Hiroshi Ueda

We consider the random fluctuations of the free energy in the $p$-spin version of the Sherrington-Kirkpatrick model in the high temperature regime. Using the martingale approach of Comets and Neveu as used in the standard SK model combined…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Bovier , I. Kurkova , M. Loewe

We consider a generic system composed of a fixed number of particles distributed over a finite number of energy levels. We make only general assumptions about system's properties and the entropy. System's constraints other than fixed number…

Probability · Mathematics 2020-03-12 Tomasz M. Łapiński

We investigate the entanglement within a system undergoing a random, local process. We find that there is initially a phase of very fast generation and spread of entanglement. At the end of this phase the entanglement is typically maximal.…

Quantum Physics · Physics 2009-11-13 O. C. O. Dahlsten , R. Oliveira , M. B. Plenio

A system composed of identical spins and described by a quantum mechanical pure state is analyzed within the statistical framework presented in Part I of this work. We explicitly derive the typical values of the entropy, of the energy, and…

Quantum Physics · Physics 2010-07-22 Barbara Fresch , Giorgio J. Moro

Stability against perturbation is a highly nontrivial property of quantum systems and is often a requirement to define new phases. In most systems where stability can be rigorously established, only static perturbations are considered;…

Quantum Physics · Physics 2025-10-17 Hongye Yu , Tzu-Chieh Wei

Consider a Hermitian operator $A$ acting on a complex Hilbert space of dimension $2^n$. We show that when $A$ has small degree in the Pauli expansion, or in other words, $A$ is a local $n$-qubit Hamiltonian, its operator norm can be…

Quantum Physics · Physics 2026-04-10 Lars Becker , Joseph Slote , Alexander Volberg , Haonan Zhang

In classical physics, entropy quantifies the randomness of large systems, where the complete specification of the state, though possible in theory, is not possible in practice. In quantum physics, despite its inherently probabilistic…

Quantum Physics · Physics 2022-09-28 Davi Geiger , Zvi Kedem

Many theoretical expressions of dissipation along non-equilibrium processes have been proposed. However, they have not been fully verified by experiments. Especially for systems strongly interacting with environments the connection between…

Statistical Mechanics · Physics 2019-12-03 Ketan Goyal , Xian He , Ryoichi Kawai

We analyze the properties of the energy landscape of {\it finite-size} fully connected p-spin-like models whose high temperature phase is described, in the thermodynamic limit, by the schematic Mode Coupling Theory of super-cooled liquids.…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Crisanti , F. Ritort

We investigate thermodynamics of a single classical particle placed in a spherical box of a finite radius $R$ and subject to a superposition of a $N-$dimensional Gaussian random potential and the parabolic potential with the curvature…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yan V. Fyodorov , H. -J. Sommers

We consider the ability of local quantum dynamics to solve the energy matching problem: given an instance of a classical optimization problem and a low energy state, find another macroscopically distinct low energy state. Energy matching is…

Disordered Systems and Neural Networks · Physics 2018-06-20 C. L. Baldwin , C. R. Laumann

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