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Neural-network quantum state study of the long-range antiferromagnetic Ising chain

arXiv 2308.09709 ↗First posted 18 Aug 2023cond-mat.stat-mech cond-mat.quant-gas cs.LGcited by 0

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Abstract (arXiv)

We investigate quantum phase transitions in the transverse field Ising chain with algebraically decaying long-range (LR) antiferromagnetic interactions using the variational Monte Carlo method with the restricted Boltzmann machine employed as a trial wave function ansatz. First, we measure the critical exponents and the central charge through the finite-size scaling analysis, verifying the contrasting observations in the previous tensor network studies. The correlation function exponent and the central charge deviate from the short-range (SR) Ising values at a small decay exponent αLR, while the other critical exponents examined are very close to the SR Ising exponents regardless of αLR examined. However, in the further test of the critical Binder ratio, we find that the universal ratio of the SR limit does not hold for αLR < 2, implying a deviation in the criticality. On the other hand, we find evidence of the conformal invariance breakdown in the conformal field theory (CFT) test of the correlation function. The deviation from the CFT description becomes more pronounced as αLR decreases, although a precise breakdown threshold is yet to be determined.

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References · 7

  1. 2019Ab-Initio Solution of the Many-Electron Schr"odinger Equation with Deep Neural Networkscited by 200
  2. 2019Deep neural network solution of the electronic Schr"odinger equationcited by 127
  3. 2018Quantum Entanglement in Deep Learning Architecturescited by 50
  4. 2017Neural-Network Quantum States, String-Bond States, and Chiral Topological Statescited by 31
  5. 2017Equivalence of restricted Boltzmann machines and tensor network statescited by 27
  6. 2021Neural tensor contractions and the expressive power of deep neural quantum statescited by 21
  7. 2020Neural network wave functions and the sign problemcited by 20

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