Awesome
<div align="center"> <img align="middle" src="_assets/logo.png" width="300" alt="logo"/> </div>Solving Quantum Statistical Mechanics with Variational Autoregressive Networks and Quantum Circuits
Setup
Typing ] in a Julia REPL, and then
pkg> dev https://github.com/wangleiphy/BetaVQE.jl.git
To make sure BetaVQE is installed properly, type
pkg> test BetaVQE
Run
Run this to train the transverse field Ising model, open a terminal and type
$ cd ~/.julia/dev/BetaVQE
$ julia --project runner.jl learn 2 2 2.0 2.0
For Windows operation system, the Julia develop folder might be different.
This utility accepts the following arguments
- nx::Int=2, lattice size in x direction,
- ny::Int=2, lattice size in y direction,
- Γ::Real=1.0, the strength of transverse field,
- β::Real=1.0, inverse temperature,
and keyword arguments
- depth::Int=5, circuit depth,
- nsamples::Int=1000, the batch size used in training,
- nhiddens::Vector{Int}=[500], dimension of the VAN's hidden layer,
- lr::Real=0.01, the learning rate of the ADAM optimizer,
- niter::Int=500, number of iteration,
- cont::Bool=false, continue from checkpoint if true.