How typical is contextuality?
- URL: http://arxiv.org/abs/2510.20722v1
- Date: Thu, 23 Oct 2025 16:39:17 GMT
- Title: How typical is contextuality?
- Authors: Vinicius P. Rossi, Beata Zjawin, Roberto D. Baldijão, David Schmid, John H. Selby, Ana Belén Sainz,
- Abstract summary: We find that contextuality is fairly common even in experiments with only a modest number of random preparations and measurements.<n>Although nonzero contextuality is quite typical, quantitatively high degrees of contextuality are not as typical.<n>We provide an open-source toolbox that outputs the typicality of contextuality as a function of parameters.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Identifying when observed statistics cannot be explained by any reasonable classical model is a central problem in quantum foundations. A principled and universally applicable approach to defining and identifying nonclassicality is given by the notion of generalized noncontextuality. Here, we study the typicality of contextuality -- namely, the likelihood that randomly chosen quantum preparations and measurements produce nonclassical statistics. Using numerical linear programs to test for the existence of a generalized-noncontextual model, we find that contextuality is fairly common: even in experiments with only a modest number of random preparations and measurements, contextuality arises with probability over 99%. We also show that while typicality of contextuality decreases as the purity (sharpness) of the preparations (measurements) decreases, this dependence is not especially pronounced, so contextuality is fairly typical even in settings with realistic noise. Finally, we show that although nonzero contextuality is quite typical, quantitatively high degrees of contextuality are not as typical, and so large quantum advantages (like for parity-oblivious multiplexing, which we take as a case study) are not as typical. We provide an open-source toolbox that outputs the typicality of contextuality as a function of tunable parameters (such as lower and upper bounds on purity and other constraints on states and measurements). This toolbox can inform the design of experiments that achieve the desired typicality of contextuality for specified experimental constraints.
Related papers
- Contextuality as an Information-Theoretic Obstruction to Classical Probability [0.0]
We show that contextual statistics certify an unavoidable obstruction to classical probabilistic descriptions.<n>Specifically, any classical model that reproduces such statistics must either embed contextual dependence into the internal state or introduce additional external labels carrying nonzero information.<n>From this viewpoint, quantum probability emerges as a canonical framework that accommodates contextual operations without requiring explicit contextual encoding.
arXiv Detail & Related papers (2026-01-28T02:02:55Z) - Boosting Temporal Sentence Grounding via Causal Inference [55.61521060331558]
Temporal Sentence Grounding aims to identify relevant moments in an untrimmed video that semantically correspond to a given textual query.<n>These spurious correlations arise from two primary factors: (1) inherent biases in the textual data, such as frequent co-occurrences of specific verbs or phrases, and (2) the model's tendency to overfit to salient or repetitive patterns in video content.<n>We propose a novel TSG framework, causal intervention and counterfactual reasoning that utilize causal inference to eliminate spurious correlations and enhance the model's robustness.
arXiv Detail & Related papers (2025-07-07T13:01:06Z) - Event-based quantum contextuality theory [9.808029647992774]
This paper overcomes the challenges faced by some known contextuality theories by establishing an event-based contextuality theory.<n>Our theory provides a precise mathematical framework for quantum contextuality, which can handle the scenarios composed of general projectors.<n>We conclude that the Kochen-Specker contextuality is equivalent to the state-independent strong contextuality for finite dimensional quantum systems.
arXiv Detail & Related papers (2024-10-21T08:55:43Z) - On the Role of Context in Reading Time Prediction [50.87306355705826]
We present a new perspective on how readers integrate context during real-time language comprehension.<n>Our proposals build on surprisal theory, which posits that the processing effort of a linguistic unit is an affine function of its in-context information content.
arXiv Detail & Related papers (2024-09-12T15:52:22Z) - Contextuality, superlocality and nonclassicality of supernoncontextuality [0.0]
We study the quantum system of two-qubit states in a scenario composed of five contexts that demonstrate contextuality in a state-dependent fashion.
We introduce a notion of nonclassicality beyond the standard contextuality, called semi-device-independent contextuality.
arXiv Detail & Related papers (2024-03-04T06:35:33Z) - Corrected Bell and Noncontextuality Inequalities for Realistic Experiments [1.099532646524593]
Contextuality is a feature of quantum correlations.
It is crucial from a foundational perspective as a nonclassical phenomenon, and from an applied perspective as a resource for quantum advantage.
We prove the continuity of a known measure of contextuality, the contextual fraction, which ensures its robustness to noise.
We then bound the extent to which these relaxations can account for contextuality, culminating in a notion of genuine contextuality, which is robust to experimental imperfections.
arXiv Detail & Related papers (2023-10-30T09:43:39Z) - Experimental test of high-dimensional quantum contextuality based on
contextuality concentration [14.374078593775309]
We show a family of noncontextuality inequalities whose maximum quantum violation grows with the dimension of the system.
Our results advance the investigation of high-dimensional contextuality, its connection to the Clifford algebra, and its role in quantum computation.
arXiv Detail & Related papers (2022-09-06T20:20:43Z) - On the probability-quality paradox in language generation [76.69397802617064]
We analyze language generation through an information-theoretic lens.
We posit that human-like language should contain an amount of information close to the entropy of the distribution over natural strings.
arXiv Detail & Related papers (2022-03-31T17:43:53Z) - Locally Typical Sampling [84.62530743899025]
We show that today's probabilistic language generators fall short when it comes to producing coherent and fluent text.<n>We propose a simple and efficient procedure for enforcing this criterion when generating from probabilistic models.
arXiv Detail & Related papers (2022-02-01T18:58:45Z) - Failures of model-dependent generalization bounds for least-norm
interpolation [39.97534972432276]
We consider bounds on the generalization performance of the least-norm linear regressor.
For a variety of natural joint distributions on training examples, any valid generalization bound must sometimes be very loose.
arXiv Detail & Related papers (2020-10-16T16:30:05Z) - Contextuality scenarios arising from networks of stochastic processes [68.8204255655161]
An empirical model is said contextual if its distributions cannot be obtained marginalizing a joint distribution over X.
We present a different and classical source of contextual empirical models: the interaction among many processes.
The statistical behavior of the network in the long run makes the empirical model generically contextual and even strongly contextual.
arXiv Detail & Related papers (2020-06-22T16:57:52Z) - Marginal likelihood computation for model selection and hypothesis
testing: an extensive review [66.37504201165159]
This article provides a comprehensive study of the state-of-the-art of the topic.
We highlight limitations, benefits, connections and differences among the different techniques.
Problems and possible solutions with the use of improper priors are also described.
arXiv Detail & Related papers (2020-05-17T18:31:58Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.