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New bounds on classification error rates for the error-correcting output code (ECOC) approach in machine learning are presented. These bounds have exponential decay complexity with respect to codeword length and theoretically validate the…

Machine Learning · Computer Science 2021-09-21 Hieu D. Nguyen , Mohammed Sarosh Khan , Nicholas Kaegi , Shen-Shyang Ho , Jonathan Moore , Logan Borys , Lucas Lavalva

We study the competition between ferromagnetic and spin glass phases using a system of coupled infinite-range Ising and Sherrington-Kirkpatrick models. We obtain the replica-symmetric solution for the free energy of this system in terms of…

Disordered Systems and Neural Networks · Physics 2023-06-28 Fateme Izadi , Reza Sepehrinia

We consider the spherical spin glass model defined by a combination of the pure 2-spin spherical Sherrington-Kirkpatrick Hamiltonian and the ferromagnetic Curie-Weiss Hamiltonian. In the large system limit, there is a two-dimensional phase…

Probability · Mathematics 2018-10-17 Jinho Baik , Ji Oon Lee , Hao Wu

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

Optimizing a high-dimensional non-convex function is, in general, computationally hard and many problems of this type are hard to solve even approximately. Complexity theory characterizes the optimal approximation ratios achievable in…

Statistical Mechanics · Physics 2020-09-25 Ahmed El Alaoui , Andrea Montanari

We introduce the Random Subsequence Model, a spin glass model on pairs of random strings $(X,Y) \in \{0,1\}^N \times \{0,1\}^M$ whose partition function counts subsequence embeddings of $Y$ into $X$. We study two variants: the null model,…

Information Theory · Computer Science 2026-04-09 Ryan Jeong , Francisco Pernice

We extend the classical edge-triangle Exponential Random Graph Model (ERGM) to an inhomogeneous setting in which vertices carry types determined by an underlying partition. This leads to a block-structured ERGM where interaction parameters…

Probability · Mathematics 2026-02-19 Elena Magnanini

Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information. The ability of random circuits to approximate any…

Quantum Physics · Physics 2023-03-23 Minzhao Liu , Junyu Liu , Yuri Alexeev , Liang Jiang

Universal bounds for the potential energy of weighted spherical codes are obtained by linear programming. The universality is in the sense of Cohn-Kumar -- every attaining code is optimal with respect to a large class of potential functions…

Metric Geometry · Mathematics 2024-12-20 Sergiy Borodachov , Peter Boyvalenkov , Peter Dragnev , Douglas Hardin , Edward Saff , Maya Stoyanova

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 study for random quantum spin systems the energy gap between the ground and first excited states to clarify a relation to the spin-glass-paramagnetic phase transition. We find that for the transverse Sherrington-Kirkpatrick model the…

Disordered Systems and Neural Networks · Physics 2010-07-30 Kazutaka Takahashi , Yoshiki Matsuda

Number-conserved subspace encoding reduces resources needed for quantum simulations, but scalable complexity trade-off bounds for $M$ modes and $N$ particles with $\mathcal{O}(N\log M)$ qubits have remained unknown. We study…

Quantum Physics · Physics 2025-09-23 M. H. Cheng , Yu-Cheng Chen , Qian Wang , V. Bartsch , M. S. Kim , Alice Hu , Min-Hsiu Hsieh

Using tools developed in a recent work by Shen and the second author, in this paper we carry out an in-depth study on the average decoding error probability of the random matrix ensemble over the erasure channel under three decoding…

Information Theory · Computer Science 2024-04-23 Chin Hei Chan , Fang-Wei Fu , Maosheng Xiong

We study the structural constraint of random scale-free networks that determines possible combinations of the degree exponent $\gamma$ and the upper cutoff $k_c$ in the thermodynamic limit. We employ the framework of graphicality…

Statistical Mechanics · Physics 2015-03-20 Yongjoo Baek , Daniel Kim , Meesoon Ha , Hawoong Jeong

We consider the problem of universal decoding for arbitrary unknown channels in the random coding regime. For a given random coding distribution and a given class of metric decoders, we propose a generic universal decoder whose average…

Information Theory · Computer Science 2016-11-17 Neri Merhav

We consider algorithmic determination of the $n$-dimensional Sherrington-Kirkpatrick (SK) spin glass model ground state free energy. It corresponds to a binary maximization of an indefinite quadratic form and under the \emph{worst case}…

Disordered Systems and Neural Networks · Physics 2025-07-15 Mihailo Stojnic

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

It is shown that fully-parallel encoding and decoding schemes with asymptotic block error probability that scales as $O\left(f\left(n\right)\right)$ have Thompson energy that scales as $\Omega\left(\sqrt{\ln f\left(n\right)}n\right)$. As…

Information Theory · Computer Science 2016-02-15 Christopher G. Blake , Frank R. Kschischang

Topological quantum error-correcting codes are a promising candidate for building fault-tolerant quantum computers. Decoding topological codes optimally, however, is known to be a computationally hard problem. Various decoders have been…

Quantum Physics · Physics 2020-04-01 Milap Sheth , Sara Zafar Jafarzadeh , Vlad Gheorghiu

The surface code is a promising platform for a quantum memory, but its threshold under coherent errors remains incompletely understood. We study maximum-likelihood decoding of the square-lattice surface code in the presence of single-qubit…

Statistical Mechanics · Physics 2026-05-05 Stephen W. Yan , Yimu Bao , Sagar Vijay