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In combinatorics, the probabilistic method is a very powerful tool to prove the existence of combinatorial objects with interesting and useful properties. Explicit constructions of objects with such properties are often very difficult, or…

Computational Complexity · Computer Science 2007-05-23 Luca Trevisan

It is currently unknown whether the laws of physics permit time travel into the past. While general relativity indicates the theoretical possibility of causality violation, it is now widely accepted that a theory of quantum gravity must…

Quantum Physics · Physics 2014-01-03 Jacques Pienaar

An analysis of the path-integral approach to quantum theory motivates the hypothesis that two experiments with the same classical action should have dual ontological descriptions. If correct, this hypothesis would not only constrain…

Quantum Physics · Physics 2011-08-04 K. B. Wharton , D. J. Miller , Huw Price

Of all basic principles of classical physics, realism should arguably be the last to be given up when seeking a better interpretation of quantum mechanics. We examine the de Broglie-Bohm pilot wave theory as a well developed example of a…

Quantum Physics · Physics 2020-12-22 Eliahu Cohen , Marina Cortês , Avshalom C. Elitzur , Lee Smolin

Although models are built on the basis of some observations of reality, the concepts that derive theoretically from their definitions as well as from their characteristics and properties are not necessarily direct consequences of these…

Discrete Mathematics · Computer Science 2011-11-11 Mathilde Noual , Sylvain Sené

A hopping model for molecular motors is presented consisting of a state with asymmetric hopping rates with period 2 and a state with uniform hopping rates. State changes lead to a stationary unidirectional current of a particle. The current…

Statistical Mechanics · Physics 2015-06-25 H. Ambaye , K. W. Kehr

The ability to perform causal and counterfactual reasoning are central properties of human intelligence. Decision-making systems that can perform these types of reasoning have the potential to be more generalizable and interpretable.…

Artificial Intelligence · Computer Science 2021-06-28 Daniel McDuff , Yale Song , Jiyoung Lee , Vibhav Vineet , Sai Vemprala , Nicholas Gyde , Hadi Salman , Shuang Ma , Kwanghoon Sohn , Ashish Kapoor

Discovering causal relationships from observational data is a challenging task that relies on assumptions connecting statistical quantities to graphical or algebraic causal models. In this work, we focus on widely employed assumptions for…

Methodology · Statistics 2024-03-20 Jonas Wahl , Urmi Ninad , Jakob Runge

Recent authors have proposed analyzing conditional reasoning through a notion of intervention on a simulation program, and have found a sound and complete axiomatization of the logic of conditionals in this setting. Here we extend this…

Artificial Intelligence · Computer Science 2018-07-31 Duligur Ibeling

Foundation models for structured time series data must contend with a fundamental challenge: observations often conflate the true underlying physical phenomena with systematic distortions introduced by measurement instruments. This…

Machine Learning · Computer Science 2025-07-09 Jeroen Audenaert , Daniel Muthukrishna , Paul F. Gregory , David W. Hogg , V. Ashley Villar

Toy models have been used to separate important features of quantum computation from the rich background of the standard Hilbert space model. Category theory, on the other hand, is a general tool to separate components of mathematical…

Quantum Physics · Physics 2010-06-08 Dusko Pavlovic

For want of a more natural proposal, it is generally assumed that the back-reaction of a quantised matter field on a classical metric is given by the expectation value of its energy-momentum tensor, evaluated in a specified state. This…

General Relativity and Quantum Cosmology · Physics 2015-06-25 L. Sriramkumar

The landscape of causal relations that can hold among a set of systems in quantum theory is richer than in classical physics. In particular, a pair of time-ordered systems can be related as cause and effect or as the effects of a common…

Quantum Physics · Physics 2017-07-20 Katja Ried , Jean-Philippe W. MacLean , Robert W. Spekkens , Kevin J. Resch

The ability to interpret the mental state of another agent based on its behavior, also called Theory of Mind (ToM), is crucial for humans in any kind of social interaction. Artificial systems, such as intelligent assistants, would also…

Artificial Intelligence · Computer Science 2019-09-24 Jan Pöppel , Stefan Kopp

It is shown that a paradigm of classical statistical mechanics --- the thermalization of a Brownian particle --- has a low-dimensional, deterministic analogue: when a heavy, slow system is coupled to fast deterministic chaos, the resultant…

chao-dyn · Physics 2016-08-31 Christopher Jarzynski

Causal discovery algorithms allow for the inference of causal structures from probabilistic relations of random variables. A natural field for the application of this tool is quantum mechanics, where a long-standing debate about the role of…

Quantum Physics · Physics 2018-04-19 R. Rossi

Collective behavior in animals has long been modeled through self-propelled particle models, which reproduce striking group-level phenomena through abstract interaction forces. Yet these models are fundamentally descriptive: they leave open…

Robotics · Computer Science 2026-05-19 Vito Mengers , Bao Duc Cao , Oliver Brock

For the classical mind, quantum mechanics is boggling enough; nevertheless more bizarre behavior could be imagined, thereby concentrating on propositional structures (empirical logics) that transcend the quantum domain. One can also…

Quantum Physics · Physics 2017-01-09 Karl Svozil

Quantum games have proposed a new point of view for the solution of the classical problems and dilemmas in game theory. Certain quantization relationships can be proposed with the objective that a game can be generalized into a quantum…

Quantum Physics · Physics 2016-12-12 Esteban Guevara Hidalgo

Causality plays an important role in understanding intelligent behavior, and there is a wealth of literature on mathematical models for causality, most of which is focused on causal graphs. Causal graphs are a powerful tool for a wide range…

Artificial Intelligence · Computer Science 2024-12-23 Scott Garrabrant , Matthias Georg Mayer , Magdalena Wache , Leon Lang , Sam Eisenstat , Holger Dell