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High-fidelity decoding of quantum error correction codes relies on an accurate experimental model of the physical errors occurring in the device. Because error probabilities can depend on the context of the applied operations, the error…

In this paper we study the numerical method for approximating the random periodic solution of semiliear stochastic evolution equations. The main challenge lies in proving a convergence over an infinite time horizon while simulating…

Probability · Mathematics 2022-05-12 Yue Wu , Chenggui Yuan

Fracton models provide examples of novel gapped quantum phases of matter that host intrinsically immobile excitations and therefore lie beyond the conventional notion of topological order. Here, we calculate optimal error thresholds for…

Quantum Physics · Physics 2022-12-06 Hao Song , Janik Schönmeier-Kromer , Ke Liu , Oscar Viyuela , Lode Pollet , M. A. Martin-Delgado

We introduce a new parameter to investigate replica symmetry breaking transitions using finite-size scaling methods. Based on exact equalities initially derived by F. Guerra this parameter is a direct check of the self-averaging character…

Statistical Mechanics · Physics 2009-10-31 E. Marinari , C. Naitza , F. Zuliani , G. Parisi , M. Picco , F. Ritort

Mean-field models of glasses that present a random first order transition exhibit highly non-trivial fluctuations. Building on previous studies that focused on the critical scaling regime, we here obtain a fully quantitative framework for…

Disordered Systems and Neural Networks · Physics 2022-08-09 Giampaolo Folena , Giulio Biroli , Patrick Charbonneau , Yi Hu , Francesco Zamponi

We derive the zero-temperature phase diagram of spin glass models with a generic fraction of ferromagnetic interactions on the Bethe lattice. We use the cavity method at the level of one-step replica symmetry breaking (1RSB) and we find…

Disordered Systems and Neural Networks · Physics 2009-11-10 Tommaso Castellani , Florent Krzakala , Federico Ricci-Tersenghi

Generalized linear models (GLMs) arise in high-dimensional machine learning, statistics, communications and signal processing. In this paper we analyze GLMs when the data matrix is random, as relevant in problems such as compressed sensing,…

Information Theory · Computer Science 2019-04-01 Jean Barbier , Florent Krzakala , Nicolas Macris , Léo Miolane , Lenka Zdeborová

For over half a century, statistical mechanics of spin glasses played as a paradigm to model and interpret disparate phenomena, ranging from quantitative biology to computer science. However, despite the extensive body of research in this…

Disordered Systems and Neural Networks · Physics 2024-11-01 Linda Albanese , Andrea Alessandrelli

This thesis includes analysis of disordered spin ensembles corresponding to Exact Cover, a multi-access channel problem, and composite models combining sparse and dense interactions. The satisfiability problem in Exact Cover is addressed…

Disordered Systems and Neural Networks · Physics 2009-05-22 Jack Raymond

Stellar oscillation codes are software instruments that evaluate the normal-mode frequencies of an input stellar model. While inter-code comparisons are often used to confirm the correctness of calculations, they are not suitable for…

Solar and Stellar Astrophysics · Physics 2025-05-29 Richard H. D. Townsend , Rianna V. Kuenzi , Jørgen Christensen-Dalsgaard

Stabilizer codes form an important class of quantum error correcting codes which have an elegant theory, efficient error detection, and many known examples. Constructing stabilizer codes of length $n$ is equivalent to constructing subspaces…

Quantum Physics · Physics 2018-06-12 Tejas Gandhi , Piyush Kurur , Rajat Mittal

A model of spinless interacting electrons in presence of randomness is examined using an extended dynamical mean-field formulation. When the interaction strength is large as compared to the Fermi energy, a low temperature glassy phase is…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. A. Pastor , V. Dobrosavljevic

We present several efficient implementations of the simulated annealing algorithm for Ising spin glasses on sparse graphs. In particular, we provide a generic code for any choice of couplings, an optimized code for bipartite graphs, and…

Disordered Systems and Neural Networks · Physics 2015-09-25 S. V. Isakov , I. N. Zintchenko , T. F. Rønnow , M. Troyer

Typical behavior of the linear programming problem (LP) is studied as a relaxation of the minimum vertex cover problem, which is a type of the integer programming problem (IP). To deal with the LP and IP by statistical mechanics, a…

Disordered Systems and Neural Networks · Physics 2014-03-31 Satoshi Takabe , Koji Hukushima

An algorithmic limit of compressed sensing or related variable-selection problems is analytically evaluated when a design matrix is given by an overcomplete random matrix. The replica method from statistical mechanics is employed to derive…

Disordered Systems and Neural Networks · Physics 2018-11-14 Tomoyuki Obuchi , Yoshinori Nakanishi-Ohno , Masato Okada , Yoshiyuki Kabashima

We consider a group synchronization problem with multiple frequencies which involves observing pairwise relative measurements of group elements on multiple frequency channels, corrupted by Gaussian noise. We study the computational phase…

Statistics Theory · Mathematics 2024-06-06 Anastasia Kireeva , Afonso S. Bandeira , Dmitriy Kunisky

We study the L\'evy spin-glass model with the replica and the cavity method. In this model each spin interacts through a finite number of strong bonds and an infinite number of weak bonds. This hybrid behaviour of L\'evy spin glasses…

Disordered Systems and Neural Networks · Physics 2010-01-29 I. Neri , F. L. Metz , D. Bollé

Gradient coding is a technique for straggler mitigation in distributed learning. In this paper we design novel gradient codes using tools from classical coding theory, namely, cyclic MDS codes, which compare favorably with existing…

Information Theory · Computer Science 2019-07-09 Netanel Raviv , Itzhak Tamo , Rashish Tandon , Alexandros G. Dimakis

The free energy of the Random Energy Model at the transition point between ferromagnetic and spin glass phases is calculated. At this point, equivalent to the decoding error threshold in optimal codes, free energy has finite size…

Statistical Mechanics · Physics 2009-11-10 David B. Saakian

Tensors are a fundamental operation in distributed computing, \emph{e.g.,} machine learning, that are commonly distributed into multiple parallel tasks for large datasets. Stragglers and other failures can severely impact the overall…

Information Theory · Computer Science 2024-10-30 Pedro Soto