{
  "id": "1907.08186",
  "version": "v1",
  "published": "2019-07-18T17:57:17.000Z",
  "updated": "2019-07-18T17:57:17.000Z",
  "title": "Neural Quantum States of frustrated magnets: generalization and sign structure",
  "authors": [
    "Tom Westerhout",
    "Nikita Astrakhantsev",
    "Konstantin S. Tikhonov",
    "Mikhail Katsnelson",
    "Andrey A. Bagrov"
  ],
  "categories": [
    "cond-mat.dis-nn",
    "cond-mat.str-el",
    "quant-ph"
  ],
  "abstract": "Neural quantum states (NQS) attract a lot of attention due to their potential to serve as variational wave functions for quantum many-body systems. Here we study the main factors governing the applicability of NQS to frustrated magnets. We consider exact ground states of several moderately sized spin Hamiltonians solvable by means of exact diagonalization. We have found that it is the sign structure that is responsible for the difficulty of the variational approach, especially in frustrated regime. We show that, if a neural network is exposed to a small fraction of signs of the ground state wave function during training, its generalization accuracy, i.e. the capability to learn from a limited number of samples and correctly predict signs on the rest of the Hilbert space basis, drops as the frustration increases (the network fails to generalize in the most difficult cases). When a larger portion of the space is used for training, the generalization accuracy undergoes a sharp transition, and the network approximates the ground state with high precision. We conclude that the main issue to be addressed at this stage, in order to bring the method of NQS to the point where it can be used to simulate realistic models, is that of generalization rather than expressibility.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2019-07-18T17:57:17.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "neural quantum states",
      "sign structure",
      "frustrated magnets",
      "sized spin hamiltonians solvable",
      "ground state wave function"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}