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Reduced density matrices are a powerful tool in the analysis of entanglement structure, approximate or coarse-grained dynamics, decoherence, and the emergence of classicality. It is straightforward to produce a reduced density matrix with…

Quantum Physics · Physics 2020-03-09 Oleg Kabernik , Jason Pollack , Ashmeet Singh

List decoding of insertions and deletions in the Levenshtein metric is considered. The Levenshtein distance between two sequences is the minimum number of insertions and deletions needed to turn one of the sequences into the other. In this…

Information Theory · Computer Science 2017-11-20 Antonia Wachter-Zeh

The main objective of the paper is to unveil an adequate mathematics hidden behind entanglement, that is Geometric Invariant Theory. More specifically relation between these two subjects can be described by the following theses. (i) Total…

Quantum Physics · Physics 2007-05-23 Alexander Klyachko

Motivated by the approach of random linear codes, a new distance in the vector space over a finite field is defined as the logarithm of the "surface area" of a Hamming ball with radius being the corresponding Hamming distance. It is named…

Information Theory · Computer Science 2013-04-30 Shengtian Yang

Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a precoding step before the polar transform. In this scheme, the polar transform (as a mapper) and the…

Information Theory · Computer Science 2021-03-24 Mohammad Rowshan , Emanuele Viterbo

We present our public-domain software for the following tasks in sparse (or toric) elimination theory, given a well-constrained polynomial system. First, C code for computing the mixed volume of the system. Second, Maple code for defining…

Mathematical Software · Computer Science 2014-03-06 Ioannis Z. Emiris

Partial spread is important in finite geometry and can be used to construct linear codes. From the results in (Designs, Codes and Cryptography 90:1-15, 2022) by Xia Li, Qin Yue and Deng Tang, we know that if the number of the elements in a…

Information Theory · Computer Science 2023-05-10 W. Lu , X. Wu , X. W. Cao , G. J. Luo , X. P. Qin

Over the past few decades, there has been extensive research on scattered subspaces, partly because of their link to MRD codes. These subspaces can be characterized using linearized polynomials over finite fields. Within this context,…

Combinatorics · Mathematics 2024-02-26 D. Bartoli , A. Giannoni , G. Marino

Learning Spaces are certain set systems that are applied in the mathematical modeling of education. We propose a suitable compression (without loss of information) of such set systems to facilitate their logical and statistical analysis.…

Data Structures and Algorithms · Computer Science 2017-08-14 Marcel Wild

We study the polynomial functions on tensor states in $(C^n)^{\otimes k}$ which are invariant under $SU(n)^k$. We describe the space of invariant polynomials in terms of symmetric group representations. For $k$ even, the smallest degree for…

Quantum Physics · Physics 2007-05-23 Jean-Luc Brylinski , Ranee Brylinski

In [Phys. Rev. A 58, 1833 (1998)] a family of polynomial invariants which separate the orbits of multi-qubit density operators $\rho$ under the action of the local unitary group was presented. We consider this family of invariants for the…

Quantum Physics · Physics 2009-11-10 Maarten Van den Nest , Jeroen Dehaene , Bart De Moor

This paper proposes a theoretical framework on the mechanism of autoencoders. To the encoder part, under the main use of dimensionality reduction, we investigate its two fundamental properties: bijective maps and data disentangling. The…

Machine Learning · Computer Science 2022-12-13 Changcun Huang

In general, cellular phenotypes, as measured by concentrations of cellular components, involve large degrees of freedom. However, recent measurement has demonstrated that phenotypic changes resulting from adaptation and evolution in…

Populations and Evolution · Quantitative Biology 2020-03-04 Takuya U. Sato , Kunihiko Kaneko

We consider an entropy-type invariant which measures the polynomial volume growth of submanifolds under the iterates of a map, and we establish sharp uniform lower bounds of this invariant for the following classes of symplectomorphisms of…

Symplectic Geometry · Mathematics 2007-05-23 Urs Frauenfelder , Felix Schlenk

Affine Cartesian codes are defined by evaluating multivariate polynomials at a cartesian product of finite subsets of a finite field. In this work we examine properties of these codes as batch codes. We consider the recovery sets to be…

Information Theory · Computer Science 2020-05-18 Travis Baumbaugh , Haley Colgate , Timothy Jackman , Felice Manganiello

We construct a family of (n,k) convolutional codes with degree \delta in {k,n-k} that have a maximum distance profile. The field size required for our construction is of the order n^{2\delta}, which improves upon the known constructions of…

Information Theory · Computer Science 2021-12-09 Zitan Chen

The Abstraction and Reasoning Corpus challenges AI systems to perform abstract reasoning with minimal training data, a task intuitive for humans but demanding for machine learning models. Using CodeT5+ as a case study, we demonstrate how…

Artificial Intelligence · Computer Science 2025-02-04 Guilherme H. Bandeira Costa , Miguel Freire , Arlindo L. Oliveira

The main results of this paper are twofold: the first one is a matrix theoretical result. We say that a matriz is superregular if all of its minors that are not trivially zero are nonzero. Given a a times b, a larger than or equal to b,…

Information Theory · Computer Science 2016-01-13 P. J. Almeida , D. Napp , R. Pinto

In this paper, we introduce code distances, a new family of invariants for linear codes. We establish some properties and prove bounds on the code distances, and show that they are not invariants of the matroid (for a linear block code) or…

Information Theory · Computer Science 2025-09-23 Eduardo Camps-Moreno , Elisa Gorla , Hiram H. López

We describe a novel extension of subspace codes for noncoherent networks, suitable for use when the network is viewed as a communication system that introduces both dimension and symbol errors. We show that when symbol erasures occur in a…

Information Theory · Computer Science 2012-09-25 Vitaly Skachek , Olgica Milenkovic , Angelia Nedic