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Generalized contextuality refers to our inability of explaining measurement statistics using a context-independent probabilistic and ontological model. On the other hand, measurement statistics can also be modeled using the framework of…

Quantum Physics · Physics 2021-03-03 Farid Shahandeh

We study a family of distributors-induced bicategorical models of lambda-calculus, proving that they can be syntactically presented via intersection type systems. We first introduce a class of 2-monads whose algebras are monoidal categories…

Logic in Computer Science · Computer Science 2021-05-06 Federico Olimpieri

We extend the theoretical framework of proof mining by establishing general logical metatheorems that allow for the extraction of the computational content of theorems with prima facie "non-computational" proofs from probability theory,…

Logic · Mathematics 2026-01-14 Morenikeji Neri , Nicholas Pischke

We develop the operational semantics of an untyped probabilistic lambda-calculus with continuous distributions, as a foundation for universal probabilistic programming languages such as Church, Anglican, and Venture. Our first contribution…

Programming Languages · Computer Science 2017-01-24 Johannes Borgström , Ugo Dal Lago , Andrew D. Gordon , Marcin Szymczak

Within the framework of quantum mechanics over a quadratic extension of the non-Archimedean field of p-adic numbers, we provide a definition of a quantum state relying on a general algebraic approach and on a p-adic model of probability…

Mathematical Physics · Physics 2023-06-06 Paolo Aniello , Stefano Mancini , Vincenzo Parisi

Let $G$ be a second countable, locally compact groupoid with Haar system, and let $\mathcal{A}$ be a bundle of $C^{\ast}$-algebras defined over the unit space of $G$ on which $G$ acts continuously. We determine conditions under which the…

Operator Algebras · Mathematics 2007-05-23 Igor Fulman , Paul S. Muhly , Dana P. Williams

Imprecise probability is concerned with uncertainty about which probability distributions to use. It has applications in robust statistics and machine learning. We look at programming language models for imprecise probability. Our…

Programming Languages · Computer Science 2024-10-31 Jack Liell-Cock , Sam Staton

We introduce the notion of a relative pseudomonad, which generalises the notion of a pseudomonad, and define the Kleisli bicategory associated to a relative pseudomonad. We then present an efficient method to define pseudomonas on the…

Category Theory · Mathematics 2019-05-16 Marcelo Fiore , Nicola Gambino , Martin Hyland , Glynn Winskel

The monad of convex sets of probability distributions is a well-known tool for modelling the combination of nondeterministic and probabilistic computational effects. In this work we lift this monad from the category of sets to the category…

Logic in Computer Science · Computer Science 2020-05-18 Matteo Mio , Valeria Vignudelli

The principle behind algebraic language theory for various kinds of structures, such as words or trees, is to use a compositional function from the structures into a finite set. To talk about compositionality, one needs some way of…

Logic in Computer Science · Computer Science 2015-02-18 Mikołaj Bojańczyk

Monads are extensively used nowadays to abstractly model a wide range of computational effects such as nondeterminism, statefulness, and exceptions. It turns out that equipping a monad with a (uniform) iteration operator satisfying a set of…

Logic in Computer Science · Computer Science 2016-03-08 Sergey Goncharov , Stefan Milius , Christoph Rauch

In this paper we consider probabilistic normed spaces as defined by Alsina, Sklar, and Schweizer, but equipped with non necessarily continuous triangle functions. Such spaces endow a generalized topology that is Fr\'echet-separable,…

General Topology · Mathematics 2010-08-09 Bernardo Lafuerza-Guillen , Jose L. Rodriguez

We present a novel, yet rather simple construction within the traditional framework of Scott domains to provide semantics to probabilistic programming, thus obtaining a solution to a long-standing open problem in this area. Unlike current…

Programming Languages · Computer Science 2025-01-28 Pietro Di Gianantonio , Abbas Edalat

The asymptotic correspondence between the probability mass function of the $q$-deformed multinomial distribution and the $q$-generalised Kullback-Leibler divergence, also known as Tsallis relative entropy, is established. The probability…

Statistical Mechanics · Physics 2025-03-10 Keisuke Okamura

This work introduces a notion of approximate probabilistic trace equivalence for labelled Markov chains, and relates this new concept to the known notion of approximate probabilistic bisimulation. In particular this work shows that the…

Logic in Computer Science · Computer Science 2017-04-28 Gaoang Bian , Alessandro Abate

Coalgebras generalize various kinds of dynamical systems occuring in mathematics and computer science. Examples of systems that can be modeled as coalgebras include automata and Markov chains. We will present a coalgebraic representation of…

Logic in Computer Science · Computer Science 2014-08-04 Frank Roumen

Computational effects are commonly modelled by monads, but often a monad can be presented by an algebraic theory of operations and equations. This talk is about monads and algebraic theories for languages for inference, and their…

Logic in Computer Science · Computer Science 2023-12-29 Cristina Matache , Sean Moss , Sam Staton , Ariadne Si Suo

A long-standing open problem in the semantics of programming languages supporting probabilistic choice is to find a commutative monad for probability on the category DCPO. In this paper we present three such monads and a general…

Logic in Computer Science · Computer Science 2021-07-29 Xiaodong Jia , Bert Lindenhovius , Michael Mislove , Vladimir Zamdzhiev

This paper concerns the verification of continuous-time polynomial spline trajectories against linear temporal logic specifications (LTL without 'next'). Each atomic proposition is assumed to represent a state space region described by a…

Logic in Computer Science · Computer Science 2022-01-24 Daniel Selvaratnam , Michael Cantoni , J. M. Davoren , Iman Shames

For a partially ordered set $(S, \mathord\preceq)$, the order (monotone) dimension is the minimum cardinality of total orders (respectively, real-valued order monotone functions) on $S$ that characterize the order $\preceq$. In this paper…

Quantum Physics · Physics 2022-11-11 Yui Kuramochi
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