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Symmetries are key properties of physical models and of experimental designs, but any proposed symmetry may or may not be realized in nature. In this paper, we introduce a practical and general method to test such suspected symmetries in…

High Energy Physics - Phenomenology · Physics 2022-08-25 Rupert Tombs , Christopher G. Lester

Symmetry is one of the most central concepts in physics, and it is no surprise that it has also been widely adopted as an inductive bias for machine-learning models applied to the physical sciences. This is especially true for models…

Chemical Physics · Physics 2024-12-23 Marcel F. Langer , Sergey N. Pozdnyakov , Michele Ceriotti

When an object moves smoothly across a field of view, the identify of the object is unchanged, but the activation pattern of the photoreceptors on the retina changes drastically. One of the major computational roles of our visual system is…

Neurons and Cognition · Quantitative Biology 2014-04-23 Minjoon Kouh

Theoretical models of neuronal function consider different mechanisms through which networks learn, classify and discern inputs. A central focus of these models is to understand how associations are established amongst neurons, in order to…

Neurons and Cognition · Quantitative Biology 2015-05-19 Harold P. de Vladar , Eörs Szathmáry

Spontaneous symmetry breaking (SSB) is key for our understanding of phase transitions and the spontaneous emergence of order. Photonics provide versatile systems to study SSB. In this work, we report that for a two-dimensional (2D) periodic…

In a physical neural system, learning rules must be local both in space and time. In order for learning to occur, non-local information must be communicated to the deep synapses through a communication channel, the deep learning channel. We…

Neural and Evolutionary Computing · Computer Science 2017-12-25 Pierre Baldi , Peter Sadowski , Zhiqin Lu

Perhaps the most important aspect of symmetry in physics is the idea that a state does not need to have the same symmetries as the theory that describes it. This phenomenon is known as spontaneous symmetry breaking. In these lecture notes,…

High Energy Physics - Theory · Physics 2019-12-16 Aron J. Beekman , Louk Rademaker , Jasper van Wezel

PT-symmetric systems can have a real spectrum even when their Hamiltonian is non-hermitian, but develop a complex spectrum when the degree of non-hermiticity increases. Here we utilize random-matrix theory to show that this spontaneous…

Quantum Physics · Physics 2011-06-24 Henning Schomerus

Entanglement asymmetry has emerged as a powerful tool for characterizing symmetry breaking in quantum many-body systems. In this Letter, we explore how symmetry is dynamically broken through the lens of entanglement asymmetry in two…

Quantum Physics · Physics 2025-09-26 Hui Yu , Zi-Xiang Li , Shi-Xin Zhang

A semiclassical picture of spontaneous symmetry breaking in light front field theory is formulated. It is based on a finite-volume quantization of self-interacting scalar fields obeying antiperiodic boundary conditions. This choice avoids a…

High Energy Physics - Theory · Physics 2008-12-18 L. Martinovic

Integrating sensory inputs with prior beliefs from past experiences in unsupervised learning is a common and fundamental characteristic of brain or artificial neural computation. However, a quantitative role of prior knowledge in…

Disordered Systems and Neural Networks · Physics 2020-06-19 Tianqi Hou , Haiping Huang

In nature, symmetry governs regularities, while symmetry breaking brings texture. In artificial neural networks, symmetry has been a central design principle to efficiently capture regularities in the world, but the role of symmetry…

Machine Learning · Computer Science 2021-11-03 Hidenori Tanaka , Daniel Kunin

A recent breakthrough in biologically-plausible normative frameworks for dimensionality reduction is based upon the similarity matching cost function and the low-rank matrix approximation problem. Despite clear biological interpretation,…

Neurons and Cognition · Quantitative Biology 2025-06-09 Veronica Centorrino , Francesco Bullo , Giovanni Russo

Neural networks with recurrent asymmetric couplings are important to understand how episodic memories are encoded in the brain. Here, we integrate the experimental observation of wide synaptic integration window into our model of sequence…

Neurons and Cognition · Quantitative Biology 2023-02-10 Zijian Jiang , Ziming Chen , Tianqi Hou , Haiping Huang

Lateral inhibition models coupled with Hebbian plasticity have been shown to learn factorised causal representations of input stimuli, for instance, oriented edges are learned from natural images. Currently, these models require the…

Neurons and Cognition · Quantitative Biology 2025-01-07 Henrique Reis Aguiar , Matthias H. Hennig

We show how a Hopfield network with modifiable recurrent connections undergoing slow Hebbian learning can extract the underlying geometry of an input space. First, we use a slow/fast analysis to derive an averaged system whose dynamics…

Neurons and Cognition · Quantitative Biology 2011-02-02 Mathieu N. Galtier , Olivier D. Faugeras , Paul C. Bressloff

Although normal homologous brain structures are approximately symmetrical by definition, they also have shape differences due to e.g. natural ageing. On the other hand, neurodegenerative conditions induce their own changes in this…

Neurons and Cognition · Quantitative Biology 2023-06-29 Duilio Deangeli , Emmanuel Iarussi , Juan Pablo Princich , Mariana Bendersky , Ignacio Larrabide , José Ignacio Orlando

Spontaneous symmetry breaking is a general principle, that constitutes the underlying concept of a vast number of physical phenomena ranging from ferromagnetism and superconductivity in condensed matter physics to the Higgs mechanism in the…

High Energy Physics - Theory · Physics 2015-03-13 Tomas Brauner

Spontaneous symmetry breaking (SSB) is responsible for structure formation in scenarios ranging from condensed matter to cosmology. SSB is broadly understood in terms of perturbations to the Hamiltonian governing the dynamics or to the…

Quantum Physics · Physics 2019-09-02 Luis Pedro García-Pintos , Diego Tielas , Adolfo del Campo

We extend the well-known theoretical treatment of the spontaneous symmetry breaking (SSB) in two-component systems, combining linear coupling and self-attractive nonlinearity, to a system in which the linear coupling competes with repulsive…

Pattern Formation and Solitons · Physics 2020-08-12 Hidetsugu Sakaguchi , Boris A. Malomed