Learning to find order in disorder

Abstract

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.

arXiv comment9 pages, 6 figures, 3 tables

References in corpus (33)

• Exchange Monte Carlo Method and Application to Spin Glass Simulations
• Topological quantum memory
• Machine learning phases of matter
• Learning phase transitions by confusion
• Machine Learning Phases of Strongly Correlated Fermions
• Universality in three-dimensional Ising spin glasses: A Monte Carlo study
• Detection of phase transition via convolutional neural network
• Strong Resilience of Topological Codes to Depolarization
• Error Threshold for Color Codes and Random 3-Body Ising Models
• Absence of an Almeida-Thouless line in Three-Dimensional Spin Glasses
• Study of the de Almeida-Thouless line using power-law diluted one-dimensional Ising spin glasses
• Probing the Almeida-Thouless line away from the mean-field model
• Disappearance of the de Almeida-Thouless line in six dimensions
• Ising spin glass transition in magnetic field out of mean-field
• Behavior of Ising Spin Glasses in a Magnetic Field
• Thermodynamic glass transition in a spin glass without time-reversal symmetry
• Spin glasses in a field: Three and four dimensions as seen from one space dimension
• Replica symmetry breaking in and around six dimensions
• The three dimensional Ising spin glass in an external magnetic field: the role of the silent majority
• Tricolored Lattice Gauge Theory with Randomness: Fault-Tolerance in Topological Color Codes
• Spin Glass in a Field: a New Zero-Temperature Fixed Point in Finite Dimensions
• Dynamical transition in the D = 3 Edwards-Anderson spin glass in an external magnetic field
• Ising Spin Glasses in a Magnetic Field
• Phase transition encoded in neural network
• Optimal error correction in topological subsystem codes
• Scaling Analysis of Domain-Wall Free-Energy in the Edwards-Anderson Ising Spin Glass in a Magnetic Field
• 4D Spin Glasses in Magnetic Field Have a Mean Field like Phase
• Learning a Local Symmetry with Neural-Networks
• The 1/m expansion in spin glasses and the de Almeida-Thouless line
• Self-Duality and Phase Structure of the 4D Random-Plaquette Z_2 Gauge Model
• Evidence against an Almeida-Thouless line in disordered systems of Ising dipoles
• Spin glasses in a field show a phase transition varying the distance among real replicas (and how to exploit it to find the critical line in a field)
• Inference of hidden structures in complex physical systems by multi-scale clustering

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• Emergence of a finite-size-scaling function in the supervised learning of the Ising phase transition
• Machine learning in physics: The pitfalls of poisoned training sets