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Motivated by the compound ${\rm LiHo}_x{\rm Y}_{1-x}{\rm F}_4$, we consider the Ising chain with random couplings and in the presence of simultaneous random transverse and longitudinal fields, and study its low-energy properties at zero…

Disordered Systems and Neural Networks · Physics 2023-03-07 Tamás Pető , Ferenc Iglói , István A. Kovács

We study the effect of spatial correlations in the quenched disorder on random quantum magnets at and near a quantum critical point. In the random transverse field Ising systems disorder correlations that decay algebraically with an…

Disordered Systems and Neural Networks · Physics 2009-10-31 H. Rieger , F. Igloi

A short introduction is given on the functional renormalization group method, putting emphasis on its nonperturbative aspects. The method enables to find nontrivial fixed points in quantum field theoretic models which make them free from…

High Energy Physics - Theory · Physics 2014-08-15 Sandor Nagy

With the help of a smooth scaling and coarse-graining approach of observables, developed recently by us in the context of so-called fluctuation operators (inspired by prior work of Verbeure et al) we perform a rigorous renormalisation group…

Mathematical Physics · Physics 2007-05-23 Manfred Requardt

The spin-1/2 quantum anisotropic XY spin chain in a transverse random magnetic field parallel to the z axis is numerically studied by means of the density-matrix renormalization group. The dependence of the spontaneous magnetization and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Juozapavicius , L. Urba , S. Caprara , A. Rosengren

We develop a new renormalization group approach to the large-N limit of matrix models. It has been proposed that a procedure, in which a matrix model of size (N-1) \times (N-1) is obtained by integrating out one row and column of an N…

High Energy Physics - Theory · Physics 2015-06-05 Shoichi Kawamoto , Tsunehide Kuroki , Dan Tomino

Strong Disorder Renormalization for the Random Transverse Field Ising model leads to a complicated topology of surviving clusters as soon as $d>1$. Even if one starts from a Cayley tree, the network of surviving renormalized clusters will…

Disordered Systems and Neural Networks · Physics 2012-10-19 Cecile Monthus , Thomas Garel

We study the renormalization group flow in general quantum field theories with quenched disorder, focusing on random quantum critical points. We show that in disorder-averaged correlation functions the flow mixes local and non-local…

Strongly Correlated Electrons · Physics 2018-08-22 Vladimir Narovlansky , Ofer Aharony

We study the critical behavior and phase diagram of the $d$-dimensional random field O(N) model by means of the nonperturbative functional renormalization group approach presented in the preceding paper. We show that the dimensional…

Statistical Mechanics · Physics 2011-07-20 Matthieu Tissier , Gilles Tarjus

The interplay between disorder, quantum fluctuations and dissipation is studied in the random transverse Ising chain coupled to a dissipative Ohmic bath with a real space renormalization group. A typically very large length scale, L*, is…

Disordered Systems and Neural Networks · Physics 2007-05-23 Gregory Schehr , Heiko Rieger

We consider the quantum Ising chain with uniformly distributed random antiferromagnetic couplings $(1 \le J_i \le 2)$ and uniformly distributed random transverse fields ($\Gamma_0 \le \Gamma_i \le 2\Gamma_0$) in the presence of a…

Disordered Systems and Neural Networks · Physics 2020-02-05 Péter Lajkó , Jean-Christian Anglès d'Auriac , Heiko Rieger , Ferenc Iglói

We present a systematic study to test a recently introduced phenomenological renormalization group, proposed to coarse-grain data of neural activity from their correlation matrix. The approach allows, at least in principle, to establish…

Statistical Mechanics · Physics 2020-05-11 Giorgio Nicoletti , Samir Suweis , Amos Maritan

The Ma-Dasgupta-Hu renormalization group (RG) scheme is used to study singular quantities in the Griffiths phase of random quantum spin chains. For the random transverse-field Ising spin chain we have extended Fisher's analytical solution…

Statistical Mechanics · Physics 2009-10-31 Ferenc Igloi , Robert Juhasz , Peter Lajko

We employ the machinery of smooth scaling and coarse-graining of observables, developed recently by us in the context of so-called fluctuation operators (inspired by prior work of Verbeure et al) to make a rigorous renormalisation group…

Mathematical Physics · Physics 2007-05-23 Manfred Requardt

We develop a time-dependent real-space renormalization-group approach which can be applied to Hamiltonians with time-dependent random terms. To illustrate the renormalization-group analysis, we focus on the quantum Ising Hamiltonian with…

Disordered Systems and Neural Networks · Physics 2019-01-30 Peter Mason , Alexandre Zagoskin , Joseph Betouras

Two replicas of a 2D Ising model are coupled by frustrated spin-spin interactions. It is known that this inter-layer coupling is marginal and that the bulk critical behavior belongs to the Ashkin-Teller (AT) universality class, as the…

Statistical Mechanics · Physics 2026-05-06 Christophe Chatelain

By means of free fermionic techniques combined with multiple precision arithmetic we study the time evolution of the average magnetization, $\overline{m}(t)$, of the random transverse-field Ising chain after global quenches. We observe…

Disordered Systems and Neural Networks · Physics 2017-04-05 Gergo Roosz , Yu-Cheng Lin , Ferenc Igloi

The renormalization group (RG) is an essential technique in statistical physics and quantum field theory, which considers scale-invariant properties of physical theories and how these theories' parameters change with scaling. Deep learning…

Statistical Mechanics · Physics 2023-08-23 Kelsie Taylor

Some recent results showed that renormalization group can be considered as a promising framework to address open issues in data analysis. In this work, we focus on one of these aspects, closely related to principal component analysis for…

High Energy Physics - Theory · Physics 2022-03-04 Vincent Lahoche , Dine Ousmane Samary , Mohamed Tamaazousti

In this work we combine quantum renormalization group approaches with deep artificial neural networks for the description of the real-time evolution in strongly disordered quantum matter. We find that this allows us to accurately compute…

Disordered Systems and Neural Networks · Physics 2021-07-28 Heiko Burau , Markus Heyl