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We introduce the use of neural networks as classifiers on classical disordered systems with no spatial ordering. In this study, we implement a convolutional neural network trained to identify the spin-glass state in the three-dimensional Edwards-Anderson Ising spin-glass model from an input of Monte Carlo sampled configurations at a given temperature. The neural network is designed to be flexible with the input size and can accurately perform inference over a small sample of the instances in the test set. Using the neural network to classify instances of the three-dimensional Edwards-Anderson Ising spin-glass in a (random) field we show that the inferred phase boundary is consistent with the absence of an Almeida-Thouless line.
How atoms in covalent solids rearrange over a medium-range length-scale during amorphization is a long pursued question whose answer could profoundly shape our understanding on amorphous (a-) networks. Based on ab-intio calculations and reverse Monte
For a variety of quenched random spin systems on an Apollonian network, including ferromagnetic and antiferromagnetic bond percolation and the Ising spin glass, we find the persistence of ordered phases up to infinite temperature over the entire rang
The local order units of dense simple liquid are typically three dimensional (close packed) clusters: hcp, fcc and icosahedrons. We show that the fluid demonstrates the superstable tetrahedral local order up to temperatures several orders of magnitud
We consider noninteracting electrons coupled to laser fields, and study perturbatively the effects of the lattice potential involving disorder on the harmonic components of the electric current, which are sources of high-order harmonic generation (HH
We study transport properties of graphene with anisotropically distributed on-site impurities (adatoms) that are randomly placed on every third line drawn along carbon bonds. We show that stripe states characterized by strongly suppressed back-scatte