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We investigate the list decodability of symbol-pair codes in the present paper. Firstly, we show that list decodability of every symbol-pair code does not exceed the Gilbert-Varshamov bound. On the other hand, we are able to prove that with…

Information Theory · Computer Science 2018-06-26 Shu Liu , Chaoping Xing , Chen Yuan

We show that for those lattices of Voronoi's first kind, a vector of shortest nonzero Euclidean length can computed in polynomial time by computing a minimum cut in a graph.

Information Theory · Computer Science 2012-01-26 Robby McKilliam , Alex Grant

The strongly correlated systems we use to realise quantum error-correcting codes may give rise to high-weight, problematic errors. Encouragingly, we can expect local quantum error-correcting codes with no string-like logical operators $-$…

Quantum Physics · Physics 2021-07-14 Georgia M. Nixon , Benjamin J. Brown

The Gilbert-Varshamov bound (non-constructively) establishes the existence of binary codes of distance $1/2 -\epsilon$ and rate $\Omega(\epsilon^2)$ (where an upper bound of $O(\epsilon^2\log(1/\epsilon))$ is known). Ta-Shma [STOC 2017]…

Data Structures and Algorithms · Computer Science 2020-11-12 Fernando Granha Jeronimo , Dylan Quintana , Shashank Srivastava , Madhur Tulsiani

Let C_n be the origin-containing cluster in subcritical percolation on the lattice (1/n) Z^d, viewed as a random variable in the space Omega of compact, connected, origin-containing subsets of R^d, endowed with the Hausdorff metric delta.…

Probability · Mathematics 2007-05-23 Yevgeniy Kovchegov , Scott Sheffield

We derive a new estimate of the size of finite sets of points in metric spaces with few distances. The following applications are considered: (1) we improve the Ray-Chaudhuri--Wilson bound of the size of uniform intersecting families of…

Combinatorics · Mathematics 2011-04-29 Alexander Barg , Oleg R. Musin

The Johnson-Lindenstrauss lemma allows dimension reduction on real vectors with low distortion on their pairwise Euclidean distances. This result is often used in algorithms such as $k$-means or $k$ nearest neighbours since they only use…

Optimization and Control · Mathematics 2015-07-06 Ky Vu , Pierre-Louis Poirion , Leo Liberti

Error-correcting codes are one of the most fundamental objects in pseudorandomness, with applications in communication, complexity theory, and beyond. Codes are useful because of their ability to support decoding, which is the task of…

Information Theory · Computer Science 2024-08-28 Shashank Srivastava

Minimal codes are linear codes where all non-zero codewords are minimal, i.e., whose support is not properly contained in the support of another codeword. The minimum possible length of such a $k$-dimensional linear code over $\mathbb{F}_q$…

Combinatorics · Mathematics 2025-06-06 Vladimir Chubenko , Sascha Kurz

Neural network decoding algorithms are recently introduced by Nachmani et al. to decode high-density parity-check (HDPC) codes. In contrast with iterative decoding algorithms such as sum-product or min-sum algorithms in which the weight of…

Information Theory · Computer Science 2018-09-14 Mohammad-Reza Sadeghi , Farzane Amirzade , Daniel Panario , Amin Sakzad

The classical family of $[n,k]_q$ Reed-Solomon codes over a field $\F_q$ consist of the evaluations of polynomials $f \in \F_q[X]$ of degree $< k$ at $n$ distinct field elements. In this work, we consider a closely related family of codes,…

Information Theory · Computer Science 2015-03-19 Venkatesan Guruswami , Carol Wang

An efficient, low-complexity, soft-output detector for general lattices is presented, based on their Tanner graph (TG) representations. Closest-point searches in lattices can be performed as non-binary belief propagation on associated TGs;…

Information Theory · Computer Science 2012-05-29 Dumitru Mihai Ionescu , Haidong Zhu

Lifted Reed-Solomon codes are a natural affine-invariant family of error-correcting codes which generalize Reed-Muller codes. They were known to have efficient local-testing and local-decoding algorithms (comparable to the known algorithms…

Information Theory · Computer Science 2017-08-09 Alan Guo , Swastik Kopparty

An analogue of the Euclidean algorithm for square matrices of size 2 with integral non-negative entries and strictly positive determinant $n$ defines a finite set $\mathcal{R}(n)$ of Euclid-reduced matrices corresponding to elements of…

Number Theory · Mathematics 2022-09-21 Roland Bacher

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

We present a geometric approach towards derandomizing the Isolation Lemma by Mulmuley, Vazirani, and Vazirani. In particular, our approach produces a quasi-polynomial family of weights, where each weight is an integer and quasi-polynomially…

Data Structures and Algorithms · Computer Science 2018-05-08 Rohit Gurjar , Thomas Thierauf , Nisheeth K. Vishnoi

In this work, we consider efficient maximum-likelihood decoding of linear block codes for small-to-moderate block lengths. The presented approach is a branch-and-bound algorithm using the cutting-plane approach of Zhang and Siegel (IEEE…

Information Theory · Computer Science 2014-04-29 Michael Helmling , Eirik Rosnes , Stefan Ruzika , Stefan Scholl

Matrix ellipsoids provide a standard framework for representing bounded uncertainties in data-driven control. Since noise models for sequential observations are naturally represented as the Minkowski sum of multiple matrix ellipsoids,…

Optimization and Control · Mathematics 2026-04-22 Taira Kaminaga , Hampei Sasahara

CSS codes are in one-to-one correspondance with length 3 chain complexes. The latter are naturally endowed with a tensor product $\otimes$ which induces a similar operation on the former. We investigate this operation, and in particular its…

Information Theory · Computer Science 2018-09-26 Benjamin Audoux , Alain Couvreur

The need for efficiently comparing and representing datasets with unknown alignment spans various fields, from model analysis and comparison in machine learning to trend discovery in collections of medical datasets. We use manifold learning…

Machine Learning · Statistics 2022-07-13 Tal Shnitzer , Mikhail Yurochkin , Kristjan Greenewald , Justin Solomon
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