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Related papers: Topological Effects in Neural Network Field Theory

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The lattice definition of the two-dimensional topological quantum field theory [Fukuma, {\em et al}, Commun.~Math.~Phys.\ {\bf 161}, 157 (1994)] is generalized to arbitrary (not necessarily orientable) compact surfaces. It is shown that…

High Energy Physics - Theory · Physics 2009-10-28 Vahid Karimipour , Ali Mostafazadeh

We propose an identification of the conformal field theory underlying Lipatov's spin-chain model of high-energy scattering in perturbative QCD. It is a twisted N=2 supersymmetric topological field theory, which arises as the limiting case…

High Energy Physics - Phenomenology · Physics 2009-09-11 John Ellis , N. E. Mavromatos

Topological defects and smooth excitations determine the properties of systems showing collective order. We introduce a generic non-singular field theory that comprehensively describes defects and excitations in systems with $O(n)$ broken…

Soft Condensed Matter · Physics 2023-08-03 Vidar Skogvoll , Jonas Rønning , Marco Salvalaglio , Luiza Angheluta

These notes are based on the lecture the author gave at the workshop 'Geometry of Strings and Fields' held at Nordita, Stockholm. In these notes, I shall cover some topics in both the perturbative and non-perturbative aspects of the…

High Energy Physics - Theory · Physics 2012-01-27 Jian Qiu

We characterise the dynamics of neuronal activity, in terms of field theory, using neural units placed on a 2D-lattice modelling the cortical surface. The electrical activity of neuronal units was analysed with the aim of deriving a neural…

Neurons and Cognition · Quantitative Biology 2023-08-22 Gerald K. Cooray , Vernon Cooray , Karl Friston

We develop techniques to compute higher loop string amplitudes for twisted $N=2$ theories with $\hat c=3$ (i.e. the critical case). An important ingredient is the discovery of an anomaly at every genus in decoupling of BRST trivial states,…

High Energy Physics - Theory · Physics 2009-09-17 M. Bershadsky , S. Cecotti , H. Ooguri , C. Vafa

We describe how a spin-foam state sum model can be reformulated as a quantum field theory of spin networks, such that the Feynman diagrams of that field theory are the spin-foam amplitudes. In the case of open spin networks, we obtain a new…

General Relativity and Quantum Cosmology · Physics 2009-11-07 A. Mikovic

We introduce a systematic mathematical language for describing fixed point models and apply it to the study to topological phases of matter. The framework is reminiscent of state-sum models and lattice topological quantum field theories,…

Quantum Physics · Physics 2022-07-28 A. Bauer , J. Eisert , C. Wille

This paper is second in the series, following Pranav et al. (2019), focused on the characterization of geometric and topological properties of 3D Gaussian random fields. We focus on the formalism of persistent homology, the mainstay of…

Cosmology and Nongalactic Astrophysics · Physics 2021-09-21 Pratyush Pranav

Quantization of coordinates leads to the non-commutative product of deformation quantization, but is also at the roots of string theory, for which space-time coordinates become the dynamical fields of a two-dimensional conformal quantum…

High Energy Physics - Theory · Physics 2008-11-26 Sebastian Guttenberg , Manfred Herbst , Maximilian Kreuzer , Radoslav Rashkov

A quantum scalar field theory with spacetime-dependent coupling is studied. Surprisingly, while translation invariance is explicitly broken in the classical theory, momentum conservation is recovered at the quantum level for some specific…

High Energy Physics - Theory · Physics 2014-01-29 Gianluca Calcagni , Giuseppe Nardelli

Topology in momentum space is the main characteristics of the ground states of a system at zero temperature, the quantum vacua. The gaplessness of fermions in bulk, on the surface or inside the vortex core is protected by topology.…

High Energy Physics - Phenomenology · Physics 2013-08-30 G. E. Volovik

We construct deformation invariants of $2|1$-dimensional Euclidean field theories valued in a cohomology theory approximating topological modular forms. This implies several results anticipated by Stolz and Teichner and gives the first…

Algebraic Topology · Mathematics 2023-03-17 Daniel Berwick-Evans

The irreducible complexity of natural phenomena has led Graph Neural Networks to be employed as a standard model to perform representation learning tasks on graph-structured data. While their capacity to capture local and global patterns is…

Machine Learning · Computer Science 2024-02-13 Lorenzo Giusti

In these lectures, we review the main properties of the topological theory obtained by twisting the N=2 two-dimensional superconformal algebra, associated to supersymmetric string compactifications. In particular, we describe a set of…

High Energy Physics - Theory · Physics 2008-11-26 I. Antoniadis , S. Hohenegger

Three dimensional topological field theories associated with the three dimensional version of Abelian and non-Abelian Seiberg-Witten monopoles are presented. These three dimensional monopole equations are obtained by a dimensional reduction…

High Energy Physics - Theory · Physics 2008-02-03 Yűji Ohta

Topological quantum field theories can be used as a powerful tool to probe geometry and topology in low dimensions. Chern-Simons theories, which are examples of such field theories, provide a field theoretic framework for the study of knots…

High Energy Physics - Theory · Physics 2007-05-23 R. K. Kaul

We propose a novel network measure of topological invariants, called small-worldness, for identifying topological phase transitions of quantum and classical spin models. Small-worldness is usually defined in the study of social networks…

Statistical Mechanics · Physics 2014-05-09 Chung-Pin Chou , Ming-Chiang Chung

In recent years the idea that not only the configuration space of particles, i.e. spacetime, but also the corresponding momentum space may have nontrivial geometry has attracted significant attention, especially in the context of quantum…

High Energy Physics - Theory · Physics 2016-06-28 Jakub Mielczarek , Tomasz Trzesniewski

These lecture notes introduce some topics of classical statistical physics, particularly those that are relevant for neural networks and deep learning. Statistical physics is treated as a branch of probability theory or statistics, with the…

Disordered Systems and Neural Networks · Physics 2026-05-12 Olaf Hohm
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