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Contextuality provides a unifying paradigm for nonclassical aspects of quantum probabilities and resources of quantum information. Unfortunately, most forms of quantum contextuality remain experimentally unexplored due to the difficulty of…

Quantum Physics · Physics 2016-03-02 Adán Cabello

Connections between the resource theories of coherence and purity (or non-uniformity) are well known for discrete-variable, finite-dimensional, quantum systems. We establish analogous results for continuous-variable systems, in particular…

Quantum Physics · Physics 2021-11-17 Giulio Gianfelici , Hermann Kampermann , Dagmar Bruß

We explore generalizations of some integrated learning and optimization frameworks for data-driven contextual stochastic optimization that can adapt to heteroscedasticity. We identify conditions on the stochastic program, data generation…

Optimization and Control · Mathematics 2021-01-11 Rohit Kannan , Güzin Bayraksan , James Luedtke

This is a non-technical introduction into theory of contextuality. More precisely, it presents the basics of a theory of contextuality called Contextuality-by-Default (CbD). One of the main tenets of CbD is that the identity of a random…

Probability · Mathematics 2022-01-13 Ehtibar N. Dzhafarov

We study uncertainty quantification for contextual stochastic optimization, focusing on weighted sample average approximation (wSAA), which uses machine-learned relevance weights based on covariates. Although wSAA is widely used for…

Optimization and Control · Mathematics 2025-10-14 Yanyuan Wang , Xiaowei Zhang

Recent work on the logical structure of non-locality has constructed scenarios where observations of multi-partite systems cannot be adequately described by compositions of non-signaling subsystems. In this paper we apply these frameworks…

Computer Science and Game Theory · Computer Science 2015-12-10 William Zeng , Philipp Zahn

The difficulty in manipulating quantum resources deterministically often necessitates the use of probabilistic protocols, but the characterization of their capabilities and limitations has been lacking. We develop a general approach to this…

Quantum Physics · Physics 2022-03-22 Bartosz Regula

This paper is a brief overview of the concepts involved in measuring the degree of contextuality and detecting contextuality in systems of binary measurements of a finite number of objects. We discuss and clarify the main concepts and…

Quantum Physics · Physics 2016-01-21 Ehtibar N. Dzhafarov , Janne V. Kujala , Victor H. Cervantes

Recent years have seen new general notions of contextuality emerge. Most of these employ context-independent symbols to represent random variables in different contexts. As an example, the operational theory of Spekkens [1] treats an…

Quantum Physics · Physics 2020-11-16 Mojtaba Aliakbarzadeh , Kirsty Kitto

Causal nonseparability refers to processes where events take place in a coherent superposition of different causal orders. These may be the key resource for experimental violations of causal inequalities and have been recently identified as…

Quantum Physics · Physics 2019-12-16 Márcio M. Taddei , Ranieri V. Nery , Leandro Aolita

Planning as heuristic search is one of the most successful approaches to classical planning but unfortunately, it does not extend trivially to Generalized Planning (GP). GP aims to compute algorithmic solutions that are valid for a set of…

Artificial Intelligence · Computer Science 2023-01-27 Javier Segovia-Aguas , Sergio Jiménez , Anders Jonsson

In quantum mechanics, not everything that can be observed can be observed simultaneously. Observational data exhibits \emph{contextuality} -- a generalisation of nonlocality -- if the result of an observation is necessarily dependent on…

Quantum Physics · Physics 2026-03-13 Ask Ellingsen

Contextuality is the leading notion of nonclassicality for a single system. However, an experimental demonstration requires finding procedures that are operationally equivalent, which might seem impossible to achieve exactly. Here I focus…

Quantum Physics · Physics 2018-08-08 Matthew F. Pusey

We present a complete reasoning principle for contextual equivalence in an untyped probabilistic language. The language includes continuous (real-valued) random variables, conditionals, and scoring. It also includes recursion, since the…

Programming Languages · Computer Science 2018-07-10 Mitchell Wand , Ryan Culpepper , Theophilos Giannakopoulos , Andrew Cobb

A general theory of resource-bounded measurability and measure is developed. Starting from any feasible probability measure $\nu$ on the Cantor space $\C$ and any suitable complexity class $C \subseteq \C$, the theory identifies the subsets…

Computational Complexity · Computer Science 2012-02-01 Jack Lutz

We present a new connection between self-adjusting binary search trees (BSTs) and heaps, two fundamental, extensively studied, and practically relevant families of data structures. Roughly speaking, we map an arbitrary heap algorithm within…

Data Structures and Algorithms · Computer Science 2019-01-01 László Kozma , Thatchaphol Saranurak

The superposition principle lies at the heart of many non-classical properties of quantum mechanics. Motivated by this, we introduce a rigorous resource theory framework for the quantification of superposition of a finite number of linear…

Quantum Physics · Physics 2017-12-19 T. Theurer , N. Killoran , D. Egloff , M. B. Plenio

We provide a unified operational framework for the study of causality, non-locality and contextuality, in a fully device-independent and theory-independent setting. Our work has its roots in the sheaf-theoretic framework for contextuality…

Quantum Physics · Physics 2023-07-31 Stefano Gogioso , Nicola Pinzani

A resource theory imposes a preorder over states, with one state being above another if the first can be converted to the second by a free operation, and where the set of free operations defines the notion of resourcefulness under study. In…

Quantum Physics · Physics 2024-07-16 Yìlè Yīng , Tomáš Gonda , Robert Spekkens

Recently there has been a surge of interest in operations research (OR) and the machine learning (ML) community in combining prediction algorithms and optimization techniques to solve decision-making problems in the face of uncertainty.…

Optimization and Control · Mathematics 2025-11-11 Utsav Sadana , Abhilash Chenreddy , Erick Delage , Alexandre Forel , Emma Frejinger , Thibaut Vidal
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