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Starting from the full--shift on a finite alphabet $A$, mingling some symbols of $A$, we obtain a new full shift on a smaller alphabet $B$. This amalgamation defines a factor map from $(A^{\mathbb N},T_A)$ to $(B^{\mathbb N},T_B)$, where…

Dynamical Systems · Mathematics 2009-10-30 Jean-Rene Chazottes , Edgardo Ugalde

Diamond "lattices" are sequences of recursively-defined graphs that provide a network of directed pathways between two fixed root nodes, $A$ and $B$. The construction recipe for diamond graphs depends on a branching number $b\in \mathbb{N}$…

Probability · Mathematics 2017-09-06 Jeremy Clark

We consider critical points of the spherical pure $p$-spin spin glass model with Hamiltonian…

Probability · Mathematics 2024-06-19 Eliran Subag , Ofer Zeitouni

We investigate the structure of Parisi measures, the functional order parameters of mixed p-spin models in mean field spin glasses. In the absence of external field, we prove that a Parisi measure satisfies the following properties. First,…

Probability · Mathematics 2013-03-18 Antonio Auffinger , Wei-Kuo Chen

The main result of this work is the proof of the boundedness of the Ornstein-Uhlenbeck semigroup $ \{T_t \}_{t\geq 0} $ in $ {\mathbb R}^d $ on Gaussian variable Lebesgue spaces under a condition of regularity on $p(\cdot)$ following…

Classical Analysis and ODEs · Mathematics 2019-11-18 Jorge Moreno , Ebner Pineda , Wilfredo Urbina

We explore supersymmetric theories in which the Higgs mass is boosted by the non-decoupling D-terms of an extended $U(1)_X$ gauge symmetry, defined here to be a general linear combination of hypercharge, baryon number, and lepton number.…

High Energy Physics - Phenomenology · Physics 2015-06-05 Clifford Cheung , Hannes L. Roberts

The effects of random magnetic fields are considered in an Ising spin-glass model defined in the limit of infinite-range interactions. The probability distribution for the random magnetic fields is a double Gaussian, which consists of two…

Statistical Mechanics · Physics 2009-11-13 N. Crokidakis , F. D. Nobre

Let $\Sigma_{A}$ be a topologically mixing shift of finite type, let $\sigma:\Sigma_{A}\to\Sigma_{A}$ be the usual left-shift, and let $\mu$ be the Gibbs measure for a H\"{o}lder continuous potential that is not cohomologous to a constant.…

Dynamical Systems · Mathematics 2022-09-07 Demi Allen , Simon Baker , Balázs Bárány

Models of spin glasses are studied with a phase transition discontinuous in the Parisi order parameter. It is assumed that the leading order corrections to the thermodynamic limit of the high temperature free energy are due to the existence…

Condensed Matter · Physics 2009-10-22 Matteo Campellone

Parameter estimation is a fundamental challenge in machine learning, crucial for tasks such as neural network weight fitting and Bayesian inference. This paper focuses on the complexity of estimating translation $\boldsymbol{\mu} \in…

Machine Learning · Computer Science 2025-01-20 Valentio Iverson , Stephen Vavasis

Modern construction of uniform confidence bands for nonparametric densities (and other functions) often relies on the classical Smirnov-Bickel-Rosenblatt (SBR) condition; see, for example, Gin\'{e} and Nickl [Probab. Theory Related Fields…

Statistics Theory · Mathematics 2014-09-24 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

We revisit the work of Mitter and Newton on an information-theoretic interpretation of Bayes' formula through the Gibbs variational principle. This formulation allowed them to pose nonlinear estimation for diffusion processes as a problem…

Optimization and Control · Mathematics 2024-05-02 Maxim Raginsky

We consider the disordered monomer-dimer model on cylinder graphs $\mathcal{G}_n$, i.e., graphs given by the Cartesian product of the line graph on $n$ vertices, and a deterministic graph. The edges carry i.i.d. random weights, and the…

Probability · Mathematics 2024-06-21 Partha S. Dey , Kesav Krishnan

A discrimination problem consists of $N$ linearly independent pure quantum states $\Phi=\{\ket{\phi_i}\}$ and the corresponding occurrence probabilities $\eta=\{\eta_i\}$. To any such problem we associate, up to a permutation over the…

Quantum Physics · Physics 2023-11-09 Seyed Arash Ghoreishi , Seyed Javad Akhtarshenas , Mohsen Sarbishaei

Nonparametric Bayesian models are used routinely as flexible and powerful models of complex data. Many times, a statistician may have additional informative beliefs about data distribution of interest, e.g., its mean or subset components,…

Methodology · Statistics 2022-11-08 Bingjing Tang , Vinayak Rao

We show that introducing an exponential cut-off on a suitable Sobolev norm facilitates the proof of quasi-invariance of Gaussian measures with respect to Hamiltonian PDE flows and allows us to establish the exact Jacobi formula for the…

Analysis of PDEs · Mathematics 2022-07-04 Giuseppe Genovese , Renato Lucà , Nikolay Tzvetkov

We study the relative entropy density for generalized Gibbs measures. We first show its existence and obtain a familiar expression in terms of entropy and relative energy for a class of ``almost Gibbsian measures'' (almost sure continuity…

Probability · Mathematics 2007-05-23 Christof Kulske , Arnaud Le Ny , Frank Redig

In the study of stochastic PDEs with colored, non-trace class space-time noise, one frequently encounters Gaussian series of the form $$g \sum_{n\geq 1} \gamma_n \mu_n f_n, $$ where $(\gamma_n)_{n}$ is a sequence of standard independent…

Probability · Mathematics 2026-05-26 Antonio Agresti , Fabian Germ , Mark Veraar

The continuous random energy model (CREM) is a toy model of disordered systems introduced by Bovier and Kurkova in 2004 based on previous work by Derrida and Spohn in the 80s. In a recent paper by Addario-Berry and Maillard, they raised the…

Probability · Mathematics 2023-08-03 Fu-Hsuan Ho

The existing investigations on the complexity are extended. In addition to the Edward-Anderson Parameter q_2 the fourth moment q_4 of the magnetizations m_i is included to the set of constrained variables and the constrained complexity is…

Disordered Systems and Neural Networks · Physics 2020-03-16 T. Plefka