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Quantum error-correcting codes (QECCs) require high encoding rate in addition to high threshold unless a sufficiently large number of physical qubits are available. The many-hypercube (MHC) codes defined as the concatenation of the…

Quantum Physics · Physics 2026-01-19 Ryota Nakai , Hayato Goto

We study a linear computation problem over a quantum multiple access channel (LC-QMAC), where $S$ servers share an entangled state and separately store classical data streams $W_1,\cdots, W_S$ over a finite field $\mathbb{F}_d$. A user aims…

Information Theory · Computer Science 2025-01-28 Lei Hu , Mohamed Nomeir , Alptug Aytekin , Yu Shi , Sennur Ulukus , Saikat Guha

This work develops a geometric framework for constructing quantum error-correcting codes from weighted projective and orbifold structures, integrating algebraic geometry, divisor theory, and the CSS stabilizer formalism. Beginning with…

Quantum Physics · Physics 2026-02-26 Tony Shaska

We restrict a degenerate quadratic form $f$ over a finite field of odd characteristic to subspaces. Thus, a quotient space related to $f$ is introduced. Then we get a non-degenerate quadratic form induced by $f$ over the quotient space.…

Information Theory · Computer Science 2022-06-17 Fei Li , Xiumei Li

Linear codes with a few weights have important applications in authentication codes, secret sharing, consumer electronics, etc.. The determination of the parameters such as Hamming weight distributions and complete weight enumerators of…

Information Theory · Computer Science 2017-11-15 Minglong Qi , Shengwu Xiong , Jingling Yuan , Wenbi Rao , Luo Zhong

We will study convolutional codes with the help of state space realizations. It will be shown that two such minimal realizations belong to the same code if and only if they are equivalent under the full state feedback group. This result…

Information Theory · Computer Science 2007-07-13 Heide Gluesing-Luerssen , Gert Schneider

In recent years several compressed indexes based on variants of the Burrows-Wheeler transformation have been introduced. Some of these index structures far more complex than a single string, as was originally done with the FM-index…

Computational Complexity · Computer Science 2019-02-27 Daniel Gibney , Sharma V. Thankachan

We explore the universality of neural encodings in convolutional neural networks trained on image classification tasks. We develop a procedure to directly compare the learned weights rather than their representations. It is based on a…

Machine Learning · Computer Science 2024-10-01 Florentin Guth , Brice Ménard

The differential structure of operator bases used in various forms of the Weyl-Wigner-Groenewold-Moyal (WWGM) quantization is analyzed and a derivative-based approach, alternative to the conventional integral-based one is developed. Thus…

Quantum Physics · Physics 2009-10-30 T. Dereli , A. Vercin

Affine Cartesian codes were first discussed by Geil and Thomsen in 2013 in a broader framework and were formally introduced by L\'opez, Renter\'ia-M\'arquez and Villarreal in 2014. These are linear error-correcting codes obtained by…

Information Theory · Computer Science 2025-05-01 Sakshi Dang , Sudhir R. Ghorpade

Weighted model counting (WMC) is a well-known inference task on knowledge bases, used for probabilistic inference in graphical models. We introduce algebraic model counting (AMC), a generalization of WMC to a semiring structure. We show…

Logic in Computer Science · Computer Science 2012-11-20 Angelika Kimmig , Guy Van den Broeck , Luc De Raedt

We investigate the AdS/CFT correspondence for higher-derivative gravity systems, and develop a formalism in which the generating functional of the boundary field theory is given as a functional that depends only on the boundary values of…

High Energy Physics - Theory · Physics 2009-11-07 Masafumi Fukuma , So Matsuura , Tadakatsu Sakai

We present Conditional Wasserstein Autoencoders (CWAEs), a framework for conditional simulation that exploits low-dimensional structure in both the conditioned and the conditioning variables. The key idea is to modify a Wasserstein…

Machine Learning · Computer Science 2026-04-06 Mohammad Al-Jarrah , Michele Martino , Marcus Yim , Bamdad Hosseini , Amirhossein Taghvaei

Signal recovery under generative neural network priors has emerged as a promising direction in statistical inference and computational imaging. Theoretical analysis of reconstruction algorithms under generative priors is, however,…

Information Theory · Computer Science 2025-10-31 Mara Daniels , Cédric Gerbelot , Florent Krzakala , Lenka Zdeborová

We propose a novel heuristic quantum algorithm for the Minimum Vertex Cover (MVC) problem based on continuous-time quantum walks (CTQWs). In this framework, the coherent propagation of a quantum walker over a graph encodes its structural…

Quantum Physics · Physics 2026-05-26 F. S. Luiz , A. K. F. Iwakami , D. H. Moraes , M. C. de Oliveira

Generative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in the near term. In this study, we build over a proposed…

Quantum Physics · Physics 2025-07-31 Mohamed Hibat-Allah , Marta Mauri , Juan Carrasquilla , Alejandro Perdomo-Ortiz

We show how to protect a stream of quantum information from decoherence induced by a noisy quantum communication channel. We exploit preshared entanglement and a convolutional coding structure to develop a theory of entanglement-assisted…

Quantum Physics · Physics 2010-05-03 Mark M. Wilde , Todd A. Brun

A weight function which $q$-generalizes the ground state wave function of the multi-component Calogero-Sutherland quantum many body system is introduced. Conjectures, and some proofs in special cases, are given for a constant term identity…

q-alg · Mathematics 2008-02-03 T. H. Baker , P. J. Forrester

Bounds on linear codes play a central role in coding theory, as they capture the fundamental trade-off between error-correction capability (minimum distance) and information rate (dimension relative to length). Classical results…

Information Theory · Computer Science 2025-09-04 Liren Lin , Guanghui Zhang , Bocong Chen , Hongwei Liu

Despite advances in deep probabilistic models, learning discrete latent representations remains challenging. This work introduces a novel method to improve inference in discrete Variational Autoencoders by reframing the inference problem…

Machine Learning · Computer Science 2025-06-11 María Martínez-García , Grace Villacrés , David Mitchell , Pablo M. Olmos