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An astonishing feature of higher-order quantum theory is that it can accommodate indefinite causal order. In the simplest bipartite setting, there exist signaling correlations for which it is fundamentally impossible to ascribe a definite…

Quantum Physics · Physics 2024-11-05 Jessica Bavaresco , Ämin Baumeler , Yelena Guryanova , Costantino Budroni

Language is contextual as meanings of words are dependent on their contexts. Contextuality is, concomitantly, a well-defined concept in quantum mechanics where it is considered a major resource for quantum computations. We investigate…

Computation and Language · Computer Science 2021-08-02 Daphne Wang , Mehrnoosh Sadrzadeh , Samson Abramsky , Victor H. Cervantes

Many frameworks exist to infer cause and effect relations in complex nonlinear systems but a complete theory is lacking. A new framework is presented that is fully nonlinear, provides a complete information theoretic disentanglement of…

Methodology · Statistics 2022-01-12 Peter Jan van Leeuwen , Michael DeCaria , Nachiketa Chakaborty , Manuel Pulido

We propose a layered hierarchical architecture called UCLA (Universal Causality Layered Architecture), which combines multiple levels of categorical abstraction for causal inference. At the top-most level, causal interventions are modeled…

Artificial Intelligence · Computer Science 2022-12-20 Sridhar Mahadevan

One of the key ways in which quantum mechanics differs from relativity is that it requires a fixed background reference frame for spacetime. In fact, this appears to be one of the main conceptual obstacles to uniting the two theories.…

Quantum Physics · Physics 2022-11-30 Lachlan Parker , Fabio Costa

"Causal Dynamical Triangulations" (CDT) represent a lattice regularization of the sum over spacetime histories, providing us with a non-perturbative formulation of quantum gravity. The ultraviolet fixed points of the lattice theory can be…

High Energy Physics - Theory · Physics 2015-06-15 J. Ambjorn , A. Goerlich , J. Jurkiewicz , R. Loll

The purpose of the current paper is twofold: to provide a conceptual link between the quantization framework based on Lie integration of algebroids proposed by N.P. Landsman in the book "Mathematical Topics between Classical and Quantum…

Mathematical Physics · Physics 2020-12-15 Jan Marcin Głowacki

Causal set theory provides a model of discrete spacetime in which spacetime events are represented by elements of a causal set---a locally finite, partially ordered set in which the partial order represents the causal relationships between…

High Energy Physics - Theory · Physics 2010-10-28 Steven Johnston

Some mathematical theories in physics justify their explanatory superiority over earlier formalisms by the clarity of their postulates. In particular, axiomatic reconstructions drive home the importance of the composition rule and the…

Quantum Physics · Physics 2015-10-26 Alexei Grinbaum

Quantum processes with indefinite causal structure emerge when we wonder which are the most general evolutions, allowed by quantum theory, of a set of local systems which are not assumed to be in any particular causal order. These processes…

Quantum Physics · Physics 2024-02-07 Luca Apadula , Alessandro Bisio , Paolo Perinotti

In this chapter a general mathematical framework for probabilistic theories of operationally understood circuits is laid out. Circuits are comprised of operations and wires. An operation is one use of an apparatus and a wire is a…

Quantum Physics · Physics 2010-06-04 Lucien Hardy

Quantum theory departs from classical probabilistic theories in foundational ways. These departures--termed quantumness here--power quantum information and computation. This thesis charts the role of discrete structures in assessing…

Quantum Physics · Physics 2025-12-22 Ravi Kunjwal

In this paper, a modified formulation of generalized probabilistic theories that will always give rise to the structure of Hilbert space of quantum mechanics, in any finite outcome space, is presented and the guidelines to how to extend…

General Physics · Physics 2022-09-19 Raed M. Shaiia

Group field theory is a background-independent approach to quantum gravity whose starting point is the definition of a quantum field theory on an auxiliary group manifold (not interpreted as spacetime, but rather as the finite-dimensional…

General Relativity and Quantum Cosmology · Physics 2025-04-10 Steffen Gielen

This work establishes a robust mathematical foundation for compositional System Dynamics modeling, leveraging category theory to formalize and enhance the representation, analysis, and composition of system models. Here, System Dynamics…

Systems and Control · Electrical Eng. & Systems 2025-09-24 Xiaoyan Li , Evan Patterson , Patricia L. Mabry , Nathaniel D. Osgood

Causal inequalities are bounds on correlations obtained when operations take place in a causal sequence, i.e. in which the background time or definite causal structure pre-exists such that every operation is either in the future, in the…

Quantum Physics · Physics 2015-09-22 Caslav Brukner

We study a collection of discrete Markov chains related to the causal set approach to modeling discrete theories of quantum gravity. The transition probabilities of these chains satisfy a general covariance principle, a causality principle,…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Avner Ash , Patrick McDonald

Instead of formulating the state space of a quantum field theory over one big Hilbert space, it has been proposed by Kijowski to describe quantum states as projective families of density matrices over a collection of smaller, simpler…

General Relativity and Quantum Cosmology · Physics 2016-12-28 Suzanne Lanéry , Thomas Thiemann

Theories of natural language and concepts have been unable to model the flexibility, creativity, context-dependence, and emergence, exhibited by words, concepts and their combinations. The mathematical formalism of quantum theory has…

Artificial Intelligence · Computer Science 2016-09-09 Diederik Aerts , Jan Broekaert , Liane Gabora , Sandro Sozzo

Real-world problems, for example in climate applications, often require causal reasoning on spatially gridded time series data or data with comparable structure. While the underlying system is often believed to behave similarly at different…

Machine Learning · Computer Science 2026-02-16 Martin Rabel , Jakob Runge
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