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We study numerically the properties of local low-energy excitations in the two-dimensional Ising spin glass. Given the ground state, we determine the lowest-lying connected cluster of flipped spins containing one given spin, either with a…

Disordered Systems and Neural Networks · Physics 2009-11-10 Ludovic Berthier , A. P. Young

The low lying excited states of the three-dimensional minimum matching problem are studied numerically. The excitations' energies grow with their size and confirm the droplet picture. However, some low energy, infinite size excitations…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. Houdayer , O. C. Martin

The energy of a droplet of linear extent l in the droplet theory of spin glasses goes as l^{\theta} for large l. It is shown by numerical studies of large droplets in two-dimensional systems that this formula needs to be modified by the…

Disordered Systems and Neural Networks · Physics 2009-11-07 A. K. Hartmann , M. A. Moore

We study numerically the local low-energy excitations in the 3-d Edwards-Anderson model for spin glasses. Given the ground state, we determine the lowest-lying connected cluster of flipped spins with a fixed volume containing one given…

Disordered Systems and Neural Networks · Physics 2009-11-07 J. Lamarcq , J. -P. Bouchaud , O. C. Martin , M. Mezard

We investigate the nature of the low-energy, large-scale excitations in the three-dimensional Edwards-Anderson Ising spin glass with Gaussian couplings and free boundary conditions, by studying the response of the ground state to a…

Disordered Systems and Neural Networks · Physics 2009-11-07 Matteo Palassini , Frauke Liers , Michael Juenger , A. P. Young

The energy of a droplet of linear extent L in the ``droplet theory'' of spin glasses goes as $L^{\theta}$ for large L. It is argued that this formula needs to be modified by the addition of a scaling correction $L^{-\omega}$ in order to…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. A. Moore

Low-energy excitations play a key role in all condensed-matter systems, yet there is limited understanding of their nature in glasses, where they correspond to local rearrangements of groups of particles. Here we introduce an algorithm to…

Soft Condensed Matter · Physics 2024-08-27 Wencheng Ji , Massimo Pica Ciamarra , Matthieu Wyart

We study large-scale, low-energy excitations in the Ising spin glass with Gaussian interactions in two-dimensions at zero temperature, using an optimization algorithm to determine exact ground states. Periodic boundary conditions are…

Disordered Systems and Neural Networks · Physics 2009-11-07 A. K. Hartmann , A. P. Young

Using mappings to computer-science problems and by applying sophisticated algorithms, one can study numerically many problems much better compared to applying standard approaches like Monte Carlo simulations. Here, using calculations of…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. K. Hartmann

Recently, Bauke and Mertens conjectured that the local statistics of energies in random spin systems with discrete spin space should in most circumstances be the same as in the random energy model. Here we give necessary conditions for this…

Disordered Systems and Neural Networks · Physics 2007-05-23 Anton Bovier , Irina Kurkova

Results are presented for the geometry of low-energy excitations in the one-dimensional Ising spin chain with power-law interactions, in which the model parameters are chosen to yield a finite spin-glass transition temperature. Both…

Disordered Systems and Neural Networks · Physics 2007-05-23 Helmut G. Katzgraber , A. P. Young

The features of turbulence modulation produced by a heavy loaded suspension of small solid particles or liquid droplets are discussed by using a physically-based regularisation of particle-fluid interactions. The approach allows a robust…

Fluid Dynamics · Physics 2017-04-05 P. Gualtieri , F. Battista , C. M. Casciola

We study the behavior of droplets for two dimensional Ising spin glasses with Gaussian interactions. We use an exact matching algorithm which enables study of systems with linear dimension L up to 240, which is larger than is possible with…

Disordered Systems and Neural Networks · Physics 2009-11-10 A. K. Hartmann , M. A. Moore

We investigate the energetics of droplets sourced by the thermal fluctuations in a system undergoing a first-order transition. In particular, we confine our studies to two dimensions with explicit calulations in the plane and on the sphere.…

Statistical Mechanics · Physics 2018-06-27 Eric M. Horsley , Maxim O. Lavrentovich , Randall D. Kamien

In amorphous materials, groups of particles can rearrange locally into a new stable configuration. Such elementary excitations are key as they determine the response to external stresses, as well as to thermal and quantum fluctuations. Yet,…

Soft Condensed Matter · Physics 2022-04-26 Wencheng Ji , Tom W. J. de Geus , Elisabeth Agoritsas , Matthieu Wyart

Recently, Bauke and Mertens conjectured that the local statistics of energies in random spin systems with discrete spin space should in most circumstances be the same as in the random energy model. Here we give necessary conditions for this…

Disordered Systems and Neural Networks · Physics 2009-11-11 Anton Bovier , Irina Kurkova

We address the question of geometrical as well as energetic properties of local excitations in mean field Ising spin glasses. We study analytically the Random Energy Model and numerically a dilute mean field model, first on tree-like…

Disordered Systems and Neural Networks · Physics 2007-05-23 F. Krzakala , G. Parisi

Energy landscapes are high-dimensional surfaces representing the dependence of system energy on variable configurations, which determine crucially the system's emergent behavior but are difficult to be analyzed due to their high-dimensional…

Disordered Systems and Neural Networks · Physics 2024-05-24 Ho Fai Po , Chi Ho Yeung

The random-field Ising model (RFIM), one of the basic models for quenched disorder, can be studied numerically with the help of efficient ground-state algorithms. In this study, we extend these algorithm by various methods in order to…

Disordered Systems and Neural Networks · Physics 2015-05-13 M. Zumsande , A. K. Hartmann

Using Monte Carlo simulations, we have studied the relaxation of energy of the three-dimensional Ising spin-glass model in aging process. Our finite-size-scaling analysis on the isothermal energy decay after the quench suggests strongly…

Disordered Systems and Neural Networks · Physics 2009-10-31 Tatsuo Komori , Hajime Yoshino , Hajime Takayama
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