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This paper analyzes the notion of causality in a conceptual model, mainly as applied in software engineering. Conceptual system modeling can be considered a three-level process that begins with building a static structural description to…

Software Engineering · Computer Science 2020-05-07 Sabah Al-Fedaghi

Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a…

Quantum Physics · Physics 2017-07-04 Ämin Baumeler , Stefan Wolf

We develop a new interpretation of quantum theory by combining insights from extended Wigner's friend scenarios and quantum causal modelling. In this interpretation, which synthesizes ideas from relational quantum mechanics and consistent…

Quantum Physics · Physics 2024-02-01 Nick Ormrod , Jonathan Barrett

Structural Causal Models (SCMs) provide a popular causal modeling framework. In this work, we show that SCMs are not flexible enough to give a complete causal representation of dynamical systems at equilibrium. Instead, we propose a…

Artificial Intelligence · Computer Science 2019-08-07 Tineke Blom , Stephan Bongers , Joris M. Mooij

Universality of quantum mechanics -- its applicability to physical systems of quite different nature and scales -- indicates that quantum behavior can be a manifestation of general mathematical properties of systems containing…

Mathematical Physics · Physics 2010-11-03 Vladimir V. Kornyak

The theory of causal fermion systems is a recent approach to fundamental physics. Giving quantum mechanics, general relativity and quantum field theory as limiting cases, it is a candidate for a unified physical theory. The dynamics is…

Mathematical Physics · Physics 2019-09-25 Felix Finster

We investigate the universality of correlation functions of chaotic and disordered quantum systems as an external parameter is varied. A new, general scaling procedure is introduced which makes the theory invariant under reparametrizations.…

Condensed Matter · Physics 2010-03-09 P. Leboeuf , M. Sieber

Identifying the causal structures between two statistically correlated events has been widely investigated in many fields of science. While some of the well-studied classical methods are carefully generalized to quantum version of causal…

Quantum Physics · Physics 2022-03-08 Feixiang Xu , Jia-Yi Lin , Ben Wang , Tao Jiang , Shengjun Wu , Wei Wang , Lijian Zhang

Understanding the physical world fundamentally relies on the assumption that events are temporally ordered, with past events serving as causes for future ones. However, quantum mechanics permits events to occur in a superposition of causal…

Quantum Physics · Physics 2025-08-07 Dengke Qu , Quan Lin , Lei Xiao , Xiang Zhan , Peng Xue

We study different notions of quantum correlations in multipartite systems of distinguishable and indistinguishable particles. Based on the definition of quantum coherence for a single particle, we consider two possible extensions of this…

Quantum Physics · Physics 2017-09-27 Jan Sperling , Armando Perez-Leija , Kurt Busch , Ian A. Walmsley

If gravity respects quantum mechanics, it is important to identify the essential postulates of a quantum framework capable of incorporating gravitational phenomena. Such a construct likely requires elimination or modification of some of the…

Quantum Physics · Physics 2008-11-26 Steven B. Giddings

We study how to implement and transform frame perspectives for quantum processes in the process-matrix formalism. We argue that, for pure processes, the causal reference frames (CRF)and time-delocalized subsystems (TDS) formalisms should be…

Quantum Physics · Physics 2026-04-06 Luca Apadula , Alexei Grinbaum , Časlav Brukner

The identification of causal relations is a cornerstone of the scientific method. Traditional approaches to this task are based on classical statistics. However, such classical approaches do not apply in the quantum domain, where a broader…

Quantum Physics · Physics 2022-09-26 Giulio Chiribella , Swati

The theory of quantum gravity is aimed to fuse general relativity with quantum theory into a more fundamental framework. The space of quantum gravity provides both the non-fixed causality of general relativity and the quantum uncertainty of…

Quantum Physics · Physics 2020-03-12 Laszlo Gyongyosi , Sandor Imre

Because of the non-locality of quantum entanglement, realist approaches to completing quantum mechanics have implications for our conception of space. Quantum gravity also is expected to predict phenomena in which the locality of classical…

History and Philosophy of Physics · Physics 2018-06-01 Lee Smolin

General Relativity traces the evolution of our Universe back to a Big Bang singularity. To probe physics before the singularity -- if indeed there is a ``before'' -- we must turn to quantum gravity. The Causal Set approach to quantum…

General Relativity and Quantum Cosmology · Physics 2021-09-27 Bruno Valeixo Bento , Stav Zalel

We propose an approach to quantum theory based on the energetic causal sets, introduced in Cort\^{e}s and Smolin (2013). Fundamental processes are causal sets whose events carry momentum and energy, which are transmitted along causal links…

General Relativity and Quantum Cosmology · Physics 2016-02-22 Marina Cortês , Lee Smolin

We show that quantum theory allows for transformations of black boxes that cannot be realized by inserting the input black boxes within a circuit in a pre-defined causal order. The simplest example of such a transformation is the classical…

Quantum Physics · Physics 2013-10-29 G. Chiribella , G. M. D'Ariano , P. Perinotti , B. Valiron

A causal set is a partially ordered set on a countably infinite ground-set such that each element is above finitely many others. A natural extension of a causal set is an enumeration of its elements which respects the order. We bring…

Probability · Mathematics 2011-09-22 Graham Brightwell , Malwina Luczak

Recent years have seen rapid progress at the intersection between causality and machine learning. Motivated by scientific applications involving high-dimensional data, in particular in biomedicine, we propose a deep neural architecture for…

Machine Learning · Computer Science 2022-12-12 Kai Lagemann , Christian Lagemann , Bernd Taschler , Sach Mukherjee