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In the operational approach to general probabilistic theories one distinguishes two spaces, the state space of the "elementary systems" and the physical space in which "laboratory devices" are embedded. Each of those spaces has its own…

Quantum Physics · Physics 2013-07-16 Borivoje Dakic , Caslav Brukner

The aim of this paper is to discuss a recent result which shows that probabilistic inference in the presence of (unknown) causal mechanisms can be tractable for models that have traditionally been viewed as intractable. This result was…

Artificial Intelligence · Computer Science 2022-02-08 Adnan Darwiche

We consider probabilistic circuits working over the real numbers, and using arbitrary semialgebraic functions of bounded description complexity as gates. In particular, such circuits can use all arithmetic operations +, -, x, /,…

Computational Complexity · Computer Science 2020-12-24 Stasys Jukna

Any function can be constructed using a hierarchy of simpler functions through compositions. Such a hierarchy can be characterized by a binary rooted tree. Each node of this tree is associated with a function which takes as inputs two…

Machine Learning · Computer Science 2019-10-23 Roozbeh Farhoodi , Khashayar Filom , Ilenna Simone Jones , Konrad Paul Kording

Higher-order quantum theory is an extension of quantum theory where one introduces transformations whose input and output are transformations, thus generalizing the notion of channels and quantum operations. The generalization then goes…

Quantum Physics · Physics 2019-05-28 Alessandro Bisio , Paolo Perinotti

In this paper we develop an operational formulation of General Relativity similar in spirit to existing operational formulations of Quantum Theory. To do this we introduce an operational space (or op-space) built out of scalar fields. A…

General Relativity and Quantum Cosmology · Physics 2016-08-26 Lucien Hardy

The relationship between mathematics and physics has long been an area of interest and speculation. Subscribing to the recent definition by Tegmark, we present a mathematical structure involving the only division rings - the real,…

General Physics · Physics 2009-08-17 Lester C. Welch

We present a framework to formally describe probabilistic system behavior and symbolically reason about it. In particular we aim at reasoning about possible failures and fault tolerance. We regard systems which are composed of different…

Software Engineering · Computer Science 2015-03-20 Jan Olaf Blech

Dynamical systems---by which we mean machines that take time-varying input, change their state, and produce output---can be wired together to form more complex systems. Previous work has shown how to allow collections of machines to…

Category Theory · Mathematics 2020-06-12 David I. Spivak

Tensor networks and circuits are widely used data structures to represent pseudo-Boolean functions. These two formalisms have been studied primarily in separate communities, and this paper aims to establish equivalences between them. We…

In the paper is discussed complete probabilistic description of quantum systems with application to multiqubit quantum computations. In simplest case it is a set of probabilities of transitions to some fixed set of states. The probabilities…

Quantum Physics · Physics 2007-05-23 Alexander Yu. Vlasov

Numerous formalisms and dedicated algorithms have been designed in the last decades to model and solve decision making problems. Some formalisms, such as constraint networks, can express "simple" decision problems, while others are designed…

Artificial Intelligence · Computer Science 2011-10-13 C. Pralet , T. Schiex , G. Verfaillie

Circuit algebras are a symmetric analogue of Jones's planar algebras introduced to study finite-type invariants of virtual knotted objects. Circuit algebra structures appear, in different forms, across mathematics. This paper provides a…

Quantum Algebra · Mathematics 2025-02-21 Sophie Raynor

We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use of deep neural networks.…

Neural and Evolutionary Computing · Computer Science 2016-12-05 Kenton W. Murray , Jayant Krishnamurthy

We address the decision problem for a fragment of real analysis involving differentiable functions with continuous first derivatives. The proposed theory, besides the operators of Tarski's theory of reals, includes predicates for…

Logic in Computer Science · Computer Science 2025-06-16 Domenico Cantone , Gianluca Cincotti

Functionals are an important research subject in Mathematics and Computer Science as well as a challenge in Information Technologies where the current programming paradigm states that only symbolic computations are possible on higher order…

Logic · Mathematics 2018-09-13 Stanislaw Ambroszkiewicz

By discussing several examples, the theory of generalized functional models is shown to be very natural for modeling some situations of reasoning under uncertainty. A generalized functional model is a pair (f, P) where f is a function…

Artificial Intelligence · Computer Science 2013-02-08 Paul-Andre Monney

We present a simple categorical framework for the treatment of probabilistic theories, with the aim of reconciling the fields of Categorical Quantum Mechanics (CQM) and Operational Probabilistic Theories (OPTs). In recent years, both CQM…

Quantum Physics · Physics 2018-03-05 Stefano Gogioso , Carlo Maria Scandolo

We provide a reformulation of finite dimensional quantum theory in the circuit framework in terms of mathematical axioms, and a reconstruction of quantum theory from operational postulates. The mathematical axioms for quantum theory are the…

Quantum Physics · Physics 2011-08-26 Lucien Hardy

Quantum information science is a source of task-related axioms whose consequences can be explored in general settings encompassing quantum mechanics, classical theory, and more. Quantum states are compendia of probabilities for the outcomes…

Quantum Physics · Physics 2007-05-23 Howard Barnum