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This study investigates the quantum effects in transverse-field Ising spin glass models with rotationally invariant random interactions. The primary aim is to evaluate the validity of a quasi-static approximation that captures the…

Disordered Systems and Neural Networks · Physics 2025-10-10 Yoshinori Hara , Yoshiyuki Kabashima

This PhD thesis is organized as follows. In the first two chapters I will review some basic notions of statistical physics of disordered systems, such as random graph theory, the mean-field approximation, spin glasses and combinatorial…

Disordered Systems and Neural Networks · Physics 2019-10-15 Enrico M. Malatesta

Consider the problem of minimizing an expected logarithmic loss over either the probability simplex or the set of quantum density matrices. This problem includes tasks such as solving the Poisson inverse problem, computing the…

Optimization and Control · Mathematics 2024-03-12 Chung-En Tsai , Hao-Chung Cheng , Yen-Huan Li

In this note, we consider the multi-species Sherrington-Kirkpatrick spin glass model at its conjectured critical temperature, and we show that, when the variance profile matrix $\Delta^2$ is positive semi-definite, the variance of the free…

Probability · Mathematics 2025-01-22 Elizabeth Collins-Woodfin , Han Gia Le

We derive a variational representation for the log-normalizing constant of the posterior distribution in Bayesian linear regression with a uniform spherical prior and an i.i.d. Gaussian design. We work under the "proportional" asymptotic…

Probability · Mathematics 2022-03-16 Jiaze Qiu , Subhabrata Sen

Within the replica approach to mean-field spin-glasses the transition from ergodic high-temperature behaviour to the glassy low-temperature phase is marked by the instability of the replica-symmetric saddle-point. For general spin-glass…

Disordered Systems and Neural Networks · Physics 2015-05-19 Katharina Janzen , Andreas Engel

We establish a strict asymptotic inequality between a class of graph partition problems on the sparse End\H{o]s-R\'enyi and random regular graph ensembles with the same average degree. Along the way, we establish a variational…

Probability · Mathematics 2020-09-04 Aukosh Jagannath , Subhabrata Sen

In this paper, we study the Crisanti-Sommers variational problem, which is a variational formula for the free energy of spherical mixed $p$-spin glasses. We begin by computing the dual of this problem using a min-max argument. We find that…

Probability · Mathematics 2018-08-06 Aukosh Jagannath , Ian Tobasco

We study the Thouless-Anderson-Palmer (TAP) equations for spin glasses on the hypercube. First, using a random, approximately ultrametric decomposition of the hypercube, we decompose the Gibbs measure, $\langle\cdot\rangle_N$, into a…

Probability · Mathematics 2020-04-17 Antonio Auffinger , Aukosh Jagannath

Consider the Euclidean traveling salesman problem with $n$ random points on the plane. Suppose that one of the points is shifted to a new random location. This gives us a new optimal path. Consider such shifts for each of the $n$ points. Do…

Probability · Mathematics 2024-10-30 Sourav Chatterjee , Souvik Ray

The interpolation method for mean field spin glass models developed by Guerra and Talagrand is extended to a quantum mean field spin glass model. This extension enables us to obtain both replica-symmetric (RS) and one step replica-symmetry…

Mathematical Physics · Physics 2024-03-14 C. Itoi , K. Fujiwara , Y. Sakamoto

Afshani, Barbay and Chan (2017) introduced the notion of instance-optimal algorithm in the order-oblivious setting. An algorithm A is instance-optimal in the order-oblivious setting for a certain class of algorithms A* if the following…

Computational Geometry · Computer Science 2023-07-28 Jean Cardinal , Justin Dallant , John Iacono

The free energy landscape of the Sherrington-Kirkpatrik (SK) Ising spin glass is simple in the framework of the Thouless-Anderson-Palmer (TAP) equations as each solution (which are minima of the free energy) has associated with it a nearby…

Disordered Systems and Neural Networks · Physics 2022-03-29 T. Aspelmeier , M. A. Moore

We introduce and analyze free energy landscapes defined by associating to any point inside the sphere a free energy calculated on a thin spherical band around it, using many orthogonal replicas. This allows us to reinterpret, rigorously…

Probability · Mathematics 2023-05-23 Eliran Subag

We study the distribution of equilibrium avalanches (shocks) in Ising spin glasses which occur at zero temperature upon small changes in the magnetic field. For the infinite-range Sherrington-Kirkpatrick model we present a detailed…

Disordered Systems and Neural Networks · Physics 2013-05-30 Pierre Le Doussal , Markus Mueller , Kay Joerg Wiese

In a separable Hilbert space, we study the minimization problem of a convex smooth function with Lipschitz continuous gradient whose evaluations are corrupted by random noise. To this end, we associate a stochastic inertial system that…

Optimization and Control · Mathematics 2025-12-18 Chiara Schindler

We construct a $\mathcal{PT}$-symmetric Richardson--Gaudin models for spin-$\tfrac{1}{2}$ systems by deforming the closed integrable Hamiltonian through complex-valued transverse magnetic fields and coupling constants. By defining parity as…

Quantum Physics · Physics 2026-04-20 M. W. AlMasri

We present extended versions and give detailed proofs of results concerning percolation (using various sets of two-replica bond occupation variables) in Sherrington-Kirkpatrick spin glasses (with zero external field) that were first given…

Disordered Systems and Neural Networks · Physics 2011-11-10 J. Machta , C. M. Newman , D. L. Stein

We derive the Thouless-Anderson-Palmer (TAP) equations for the Ghatak and Sherrington model. Our derivation, based on the cavity method, holds at high temperature and at all values of the crystal field. It confirms the prediction of Yokota.

Probability · Mathematics 2021-09-01 Antonio Auffinger , Cathy Xi Chen

Marginal optima are minima or maxima of a function with many nearly flat directions. In settings with many competing optima, marginal ones tend to attract algorithms and physical dynamics. Often, the important family of marginal attractors…

Disordered Systems and Neural Networks · Physics 2024-12-03 Jaron Kent-Dobias
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