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Stopping sets, and in particular their numbers and sizes, play an important role in determining the performance of iterative decoders of linear codes over binary erasure channels. In the 2004 Shannon Lecture, McEliece presented an…

Information Theory · Computer Science 2007-07-13 Khaled A. S. Abdel-Ghaffar , Jos H. Weber

Different choices of quantum error-correcting codes can reduce the demands on the physical hardware needed to build a quantum computer. To achieve the full potential of a code, we must develop practical decoding algorithms that can correct…

Quantum Physics · Physics 2025-06-18 Zohar Schwartzman-Nowik , Benjamin J. Brown

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

We analyze two approaches to quantum state transfer in solid-state spin systems. First, we consider unpolarized spin-chains and extend previous analysis to various experimentally relevant imperfections, including quenched disorder,…

In this paper, we present an adaptive reweighted sparse belief propagation (AR-SBP) decoder for polar codes. The AR-SBP technique is inspired by decoders that employ the sum-product algorithm for low-density parity-check codes. In…

Information Theory · Computer Science 2024-04-09 R. M. Oliveira , R. C. de Lamare

Departing from traditional communication theory where decoding algorithms are assumed to perform without error, a system where noise perturbs both computational devices and communication channels is considered here. This paper studies…

Information Theory · Computer Science 2010-05-31 Lav R. Varshney

Achieving security against adversaries with unlimited computational power is of great interest in a communication scenario. Since polar codes are capacity achieving codes with low encoding-decoding complexity and they can approach perfect…

Information Theory · Computer Science 2018-01-23 Amirsina Torfi , Sobhan Soleymani , Siamak Aram , Vahid Tabataba Vakili

We present a technique of proving lower bounds for noisy computations. This is achieved by a theorem connecting computations on a kind of randomized decision trees and sampling based algorithms. This approach is surprisingly powerful, and…

Computational Complexity · Computer Science 2015-03-03 Chinmoy Dutta , Jaikumar Radhakrishnan

Most existing works of polar codes focus on the analysis of block error probability. However, in many scenarios, bit error probability is also important for evaluating the performance of channel codes. In this paper, we establish a new…

Information Theory · Computer Science 2022-04-18 Bolin Wu , Kai Niu , Jincheng Dai

We present a numerical analysis of the entropy rate and statistical complexity related to the spin flip dynamics of the 2D Ising Ferromagnet at different temperatures T. We follow an information theoretic approach and test three different…

Statistical Mechanics · Physics 2012-07-02 O. Melchert , A. K. Hartmann

The numerical solution of differential equations using neural networks has become a central topic in scientific computing, with Physics-Informed Neural Networks (PINNs) emerging as a powerful paradigm for both forward and inverse problems.…

Machine Learning · Computer Science 2026-01-28 Kazuaki Tanaka , Kohei Yatabe

The surface code is one the most promising alternatives for implementing fault-tolerant, large-scale quantum information processing. Its high threshold for single-qubit errors under stochastic noise is one of its most attrative features. We…

Quantum Physics · Physics 2014-10-29 Pejman Jouzdani , E. Novais , I. S. Tupitsyn , Eduardo R. Mucciolo

An important part of the information theory folklore had been about the output statistics of codes that achieve the capacity and how the empirical distributions compare to the output distributions induced by the optimal input in the channel…

Information Theory · Computer Science 2026-01-19 Alptug Aytekin , Mohamed Nomeir , Lei Hu , Sennur Ulukus

In this paper we apply the formalism of translation invariant (continuous) matrix product states in the thermodynamic limit to $(1+1)$ dimensional critical models. Finite bond dimension bounds the entanglement entropy and introduces an…

Quantum Physics · Physics 2015-06-18 Vid Stojevic , Jutho Haegeman , I. P. McCulloch , L. Tagliacozzo , Frank Verstraete

Benefiting from performance advantages under short code lengths, polar codes are well-suited for certain scenarios, such as the future Internet of Things (IoT) applications that require high reliability and low power. Existing list flip…

Information Theory · Computer Science 2025-04-01 Yansong Lv , Jingxin Dai , Yuhuan Wang , Hang Yin , Zhanxin Yang

Quantum reading provides a general framework where to formulate the statistical discrimination of quantum channels. Several paths have been taken for such a problem. However, there is much to be done in the avenue of optimizing channel…

Information Theory · Computer Science 2022-06-22 Francisco Revson F. Pereira , Stefano Mancini

We demonstrate singlet-triplet readout and parity readout allowing to distinguish T0 and the polarized triplet states. We achieve high fidelity spin readout with an average fidelity above $99.9\%$ for a readout time of $20~\mu$s and $99\%$…

We develop a method to transform a collection of higher-dimensional spin systems from the thermal state with a very high temperature of a local spin-s Hamiltonian to a low-lying energy eigenstate of the same. The procedure utilizes an…

Quantum Physics · Physics 2024-09-16 Debkanta Ghosh , Tanoy Kanti Konar , Aditi Sen De

The stabilization of a quantum computer by repeated error correction can be reduced almost entirely to repeated preparation of blocks of qubits in quantum codeword states. These are multi-particle entangled states with a high degree of…

Quantum Physics · Physics 2007-05-23 Andrew M. Steane

In this paper, we applied a deep neural network to study the issue of knowledge transferability between statistical mechanics models. The following computer experiment was conducted. A convolutional neural network was trained to solve the…

Disordered Systems and Neural Networks · Physics 2024-11-21 Diana Sukhoverkhova , Lev Shchur