English
Related papers

Related papers: Exploiting emergent symmetries in disorder-average…

200 papers

Symmetric extensions are essential in quantum mechanics, providing a lens to investigate the correlations of entangled quantum systems and to address challenges like the quantum marginal problem. Though semi-definite programming (SDP) is a…

Quantum Physics · Physics 2025-03-25 Youning Li , Chao Zhang , Shi-Yao Hou , Zipeng Wu , Xuanran Zhu , Bei Zeng

Neuronal ensemble activity, including coordinated and oscillatory patterns, exhibits hallmarks of nonequilibrium systems with time-asymmetric trajectories to maintain their organization. However, assessing time asymmetry from neuronal…

Neurons and Cognition · Quantitative Biology 2025-12-12 Ken Ishihara , Hideaki Shimazaki

A transfer matrix scaling technique is developed for randomly diluted systems, and applied to the site-diluted Ising model on a square lattice in two dimensions. For each allowed disorder configuration between two adjacent columns, the…

Condensed Matter · Physics 2009-10-22 S. L. A. de Queiroz , R. B. Stinchcombe

Quantum chaos in many-body systems provides a bridge between statistical and quantum physics with strong predictive power. This framework is valuable for analyzing properties of complex quantum systems such as energy spectra and the…

Linear differential equations are ubiquitous in science and engineering. Quantum computers can simulate quantum systems, which are described by a restricted type of linear differential equations. Here we extend quantum simulation algorithms…

Quantum Physics · Physics 2014-02-21 Dominic W. Berry

The analysis of symmetry in quantum systems is of utmost theoretical importance, useful in a variety of applications and experimental settings, and is difficult to accomplish in general. Symmetries imply conservation laws, which partition…

Quantum Physics · Physics 2023-10-20 Caleb Rotello , Eric B. Jones , Peter Graf , Eliot Kapit

Discovering pragmatic and efficient approaches to construct $\varepsilon$-approximations of quantum operators such as real (imaginary) time-evolution propagators in terms of the basic quantum operations (gates) is challenging. Prior…

Quantum Physics · Physics 2024-10-31 Yan Wang , Sarah Chehade , Eugene Dumitrescu

The supersymmetry method has proven to be a very powerful tool of study of the statistical properties of energy levels and eigenfunctions in disordered and chaotic systems. The aim of these lectures is to present a tutorial introduction to…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alexander D. Mirlin

The parallel dynamics of extremely diluted symmetric Q-Ising neural networks is studied for arbitrary Q using a probabilistic approach. In spite of the extremely diluted architecture the feedback correlations arising from the symmetry…

Disordered Systems and Neural Networks · Physics 2015-06-25 D. Bolle , G. Jongen , G. M. Shim

Quantum systems inside high-Q cavities offer an excellent testbed for the control of emergent symmetries induced by light and their interplay with quantum matter. Recently several developments in cavity experiments with neutral atoms and…

Quantum Physics · Physics 2026-03-24 Santiago F. Caballero-Benitez

We consider time evolution of order parameters and entanglement asymmetries in the ferromagnetic phase of the transverse-field Ising chain. One side of the system is prepared in a ferromagnetic ground state and the other side either in…

Statistical Mechanics · Physics 2025-05-22 Vanja Marić , Florent Ferro , Maurizio Fagotti

While there are various approaches to benchmark physical processors, recent findings have focused on computational phase transitions. This is due to several factors. Importantly, the hardest instances appear to be well-concentrated in a…

Quantum Physics · Physics 2021-04-08 Hariphan Philathong , Vishwa Akshay , Ksenia Samburskaya , Jacob Biamonte

We study dynamical signatures of quantum chaos in one of the most relevant models in many-body quantum mechanics, the Bose-Hubbard model, whose high degree of symmetries yields a large number of invariant subspaces and degenerate energy…

Quantum Physics · Physics 2020-09-16 Javier de la Cruz , Sergio Lerma-Hernandez , Jorge G. Hirsch

Considering disordered electron systems we suggest a scheme that allows us to include an electron-electron interaction into a supermatrix sigma-model. The method is based on replacing the initial model of interacting electons by a fully…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 G. Schwiete , K. B. Efetov

The main aim of this work is to present two different methodologies for configuration averaging in disordered systems. The Recursion method is suitable for the calculation of spatial or self-averaging, while the Augmented space formalism…

We present an algorithm which explores permutation symmetries to describe the time evolution of agent-based epidemic models. The main idea to improve computation times relies on restricting the stochastic process to one sector of the vector…

Populations and Evolution · Quantitative Biology 2016-09-28 Gilberto M. Nakamura , Ana Carolina P. Monteiro , George C. Cardoso , Alexandre S. Martinez

The theory of large deviations is already the natural language for the statistical physics of equilibrium and non-equilibrium. In the field of disordered systems, the analysis via large deviations is even more useful to describe within a…

Disordered Systems and Neural Networks · Physics 2021-05-12 Cecile Monthus

Symmetries impose structure on the Hilbert space of a quantum mechanical model. The mathematical units of this structure are the irreducible representations of symmetry groups and I consider how they function as conceptual units of…

Quantum Physics · Physics 2018-01-29 N. L. Harshman

Reliable numerical computation of quantum dynamics is a fundamental challenge when the long-ranged quantum entanglement plays essential roles as in the cases governed by quantum criticality in strongly correlated systems. Here we apply a…

Quantum Physics · Physics 2025-01-24 Ryui Kaneko , Masatoshi Imada , Yoshiyuki Kabashima , Tomi Ohtsuki

Variational quantum machine learning is an extensively studied application of near-term quantum computers. The success of variational quantum learning models crucially depends on finding a suitable parametrization of the model that encodes…

‹ Prev 1 3 4 5 6 7 10 Next ›