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The intended model of the homotopy type theories used in Univalent Foundations is the infinity-category of homotopy types, also known as infinity-groupoids. The problem of higher structures is that of constructing the homotopy types needed…

Logic · Mathematics 2018-07-09 Ulrik Buchholtz

Category theory unifies mathematical concepts, aiding comparisons across structures by incorporating objects and morphisms, which capture their interactions. It has influenced areas of computer science such as automata theory, functional…

Category Theory · Mathematics 2024-02-09 Nima Rasekh , Niels van der Weide , Benedikt Ahrens , Paige Randall North

From the ancient Einstein-Podolsky-Rosen paradox to the recent Sorkin-type impossible measurements problem, the contradictions between relativistic causality, quantum non-locality, and quantum measurement have persisted. Based on quantum…

Quantum Physics · Physics 2025-10-03 Kaixun Tu , Qing Wang

Causality among events is widely recognized as a most fundamental structure of spacetime, and causal sets have been proposed as discrete models of the latter in the context of quantum gravity theories, notably in the Causal Set Programme.…

Computational Physics · Physics 2010-04-20 Tommaso Bolognesi

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

Naturally occurring diagrams in algebraic topology are commutative up to homotopy, but not on the nose. It was quickly realized that very little can be done with this information. Homotopy coherent category theory arose out of a desire to…

Category Theory · Mathematics 2023-01-12 Emily Riehl

Systems displaying quantum topological order feature robust characteristics that are very attractive to quantum computing schemes. Topological quantum field theories have proven to be powerful in capturing the quintessential attributes of…

Mesoscale and Nanoscale Physics · Physics 2024-08-15 P. Vojta , G. Ortiz , Z. Nussinov

The supercharacter theory of algebra groups gave us a representation theoretic realization of the Hopf algebra of symmetric functions in noncommuting variables. The underlying representation theoretic framework comes equipped with two…

Combinatorics · Mathematics 2018-10-04 Farid Aliniaeifard , Nathaniel Thiem

There has been a recent surge of interest within the field of quantum foundations regarding incorporating ideas from general relativity and quantum gravity. However, many quantum information tools remain agnostic to the underlying…

Quantum Physics · Physics 2026-01-14 Matthias Salzger , John H. Selby

We present a unified framework for categorical systems theory which packages a collection of open systems, their interactions, and their maps into a symmetric monoidal loose right module of systems over a symmetric monoidal double category…

Category Theory · Mathematics 2025-05-30 Sophie Libkind , David Jaz Myers

Categorical Universal Logic is a theory of monad-relativised hyperdoctrines (or fibred universal algebras), which in particular encompasses categorical forms of both first-order and higher-order quantum logics as well as classical,…

Quantum Physics · Physics 2014-12-31 Yoshihiro Maruyama

The notion of computability closure has been introduced for proving the termination of the combination of higher-order rewriting and beta-reduction. It is also used for strengthening the higher-order recursive path ordering. In the present…

Logic in Computer Science · Computer Science 2007-05-23 Frédéric Blanqui

It is shown that a coherent understanding of all quantized phenomena, including those governed by unitary evolution equations as well as those related to irreversible quantum measurements, can be achieved in a scenario of successive…

Quantum Physics · Physics 2007-12-31 Xiaolei Zhang

As quantum computers become real, it is high time we come up with effective techniques that help programmers write correct quantum programs. In classical computing, formal verification and sound static type systems prevent several classes…

Programming Languages · Computer Science 2021-09-10 Kartik Singhal , John Reppy

It can be argued that the ordinary description of the reversible quantum process between two one-to-one correlated measurement outcomes is incomplete because, by not specifying the direction of causality, it allows causal structures that…

Quantum Physics · Physics 2023-11-02 Giuseppe Castagnoli

Mechanistic interpretability aims to reverse engineer neural networks by uncovering which high-level algorithms they implement. Causal abstraction provides a precise notion of when a network implements an algorithm, i.e., a causal model of…

Machine Learning · Computer Science 2025-03-17 Theodora-Mara Pîslar , Sara Magliacane , Atticus Geiger

There have been several post-hoc explanation approaches developed to explain pre-trained black-box neural networks. However, there is still a gap in research efforts toward designing neural networks that are inherently explainable. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-07-01 Subash Khanal , Benjamin Brodie , Xin Xing , Ai-Ling Lin , Nathan Jacobs

Two quantum theories which look different but are secretly describing the same low-energy physics are said to be dual to each other. When realized in the Topological Holography formalism, duality corresponds to changing the gapped boundary…

Strongly Correlated Electrons · Physics 2025-08-12 Robijn Vanhove , Vibhu Ravindran , David T. Stephen , Xiao-Gang Wen , Xie Chen

We study the notion of causal orders for the cases of (classical and quantum) circuits and spacetime events. We show that every circuit can be immersed into a classical spacetime, preserving the compatibility between the two causal…

Quantum Physics · Physics 2020-06-08 Nikola Paunkovic , Marko Vojinovic

Hyperparameters play a critical role in machine learning. Hyperparameter tuning can make the difference between state-of-the-art and poor prediction performance for any algorithm, but it is particularly challenging for structure learning…

Machine Learning · Computer Science 2024-02-21 Damian Machlanski , Spyridon Samothrakis , Paul Clarke
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