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Markov chains provide a foundational framework for modeling sequential stochastic processes, with the transition probability matrix characterizing the dynamics of state evolution. While classical estimation methods such as maximum…

Methodology · Statistics 2025-07-11 Agamani Saha , Souvik Roy

We study unital operator spaces endowed with a partially defined product. We give a matrix-norm characterization of such products that allows for a representation theorem where the partial product is realized as composition of operators on…

Operator Algebras · Mathematics 2025-11-07 Adam Dor-On , Travis B. Russell

We provide an axiomatic approach for studying support varieties of objects in a triangulated category via the action of a tensor triangulated category, where the tensor product is not necessarily symmetric. This is illustrated by examples,…

K-Theory and Homology · Mathematics 2019-05-23 Aslak Bakke Buan , Henning Krause , Nicole Snashall , Oeyvind Solberg

We verify a conjecture of Etingof and Ostrik, stating that an algebra object in a finite tensor category is exact if and only if it is a finite direct product of simple algebras. Towards that end, we introduce an analogue of the Jacobson…

Representation Theory · Mathematics 2025-01-22 Kevin Coulembier , Mateusz Stroiński , Tony Zorman

We introduce the notion of continuous frame in n-Hilbert space which is a generalization of discrete frame in n-Hilbert space. The tensor product of Hilbert spaces is a very important topic in mathematics. Here we also introduce the concept…

Functional Analysis · Mathematics 2024-03-07 Prasenjit Ghosh , T. K. Samanta

We classify all continuous tensor product systems of Hilbert spaces which are ``infinitely divisible" in the sense that they have an associated logarithmic structure. These results are applied to the theory of E_0 semigroups to deduce that…

funct-an · Mathematics 2008-02-03 William Arveson

We study infinite-horizon robust Markov decision processes (MDPs) on continuous state spaces with structured rectangular ambiguity set. The proposed ambiguity set falls within the convex hull of unknown generating kernels. We utilize the…

Optimization and Control · Mathematics 2026-05-28 Mengmeng Li , Yifan Hu , Daniel Kuhn , Yan Li

We study stratification, that is the classification of localizing tensor ideal subcategories by geometric means, in the context of Kasparov's equivariant KK-theory of C*-algebras. We introduce a straightforward countable analog of the…

K-Theory and Homology · Mathematics 2026-01-21 Ivo Dell'Ambrogio , Rubén Martos

A proto-quantum space is a (general) matricially normed space in the sense of Effros and Ruan presented in a `matrix-free' language. We show that these spaces have a special (projective) tensor product possessing the universal property with…

Functional Analysis · Mathematics 2017-06-05 A. Ya. Helemskii

In this paper, we propose an axiomatic definition for a tensor product categorification. A tensor product categorification is an abelian category with a categorical action of a Kac-Moody algebra g in the sense of Rouquier or Khovanov-Lauda…

Representation Theory · Mathematics 2025-04-28 Ivan Losev , Ben Webster

We extend Gleason's theorem to the two-dimensional Hilbert space of a qubit by invoking the standard axiom that describes composite quantum systems. The tensor-product structure allows us to derive density matrices and Born's rule for $d=2$…

Quantum Physics · Physics 2025-11-20 Vincenzo Fiorentino , Stefan Weigert

Modular tensor categories are generalizations of the representation categories of quantum groups at roots of unity axiomatizing the properties necessary to produce 3-dimensional TQFTs. Although other constructions have since been found,…

Quantum Algebra · Mathematics 2007-05-23 Eric C. Rowell

It is known that the spatial product of two product systems is intrinsic. Here we extend this result by analyzing subsystems of the tensor product of product systems. A relation with cluster systems is established. In a special case, we…

Functional Analysis · Mathematics 2015-02-12 Mithun Mukherjee

Many natural and engineered systems can be modeled as discrete state Markov processes. Often, only a subset of states are directly observable. Inferring the conditional probability that a system occupies a particular hidden state, given the…

Signal Processing · Electrical Eng. & Systems 2023-01-04 Daniel Chen , Alexander G. Strang , Andrew W. Eckford , Peter J. Thomas

The aim of this note is to introduce a notion of dynamical entropy, which we call infinite-product entropy, for probability measures on (countable) infinite cartesian product of any measurable space with itself. The idea behind the…

Probability · Mathematics 2024-10-29 Maysam Maysami Sadr , Mina Shahrestani , Danial Bouzarjomehri Amnieh

The machine learning community has recently put effort into quantized or low-precision arithmetics to scale large models. This paper proposes performing probabilistic inference in the quantized, discrete parameter space created by these…

Machine Learning · Computer Science 2025-08-20 Aleksanteri Sladek , Martin Trapp , Arno Solin

Infinitary operations, such as products indexed by countably infinite linear orders, arise naturally in the context of fundamental groups and groupoids. Despite the fact that the usual binary operation of the fundamental group determines…

Algebraic Topology · Mathematics 2020-04-14 Jeremy Brazas

Starting from a (small) rigid C$^*$-tensor category $\mathscr{C}$ with simple unit, we construct von Neumann algebras associated to each of its objects. These algebras are factors and can be either semifinite (of type II$_1$ or II$_\infty$,…

Operator Algebras · Mathematics 2019-08-06 Luca Giorgetti , Wei Yuan

We show a general relation between the spatially disjoint product of probability density functions and the sum of their Fisher information metric tensors. We then utilise this result to give a method for constructing the probability density…

Information Theory · Computer Science 2015-04-14 T. Clingman , Jeff Murugan , Jonathan P. Shock

Many problems in high-dimensional statistics appear to have a statistical-computational gap: a range of values of the signal-to-noise ratio where inference is information-theoretically possible, but (conjecturally) computationally…

Statistics Theory · Mathematics 2024-04-30 Dmitriy Kunisky , Cristopher Moore , Alexander S. Wein
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