6 citations · 6 across the 1 of their papers we have counts for
9 papers
Tropical Tensor Network for Ground States of Spin Glasses
Jin-Guo Liu, Lei Wang, Pan Zhang
We present a unified exact tensor network approach to compute the ground state energy, identify the optimal configuration, and count the number of solutions for spin glasses. The m…
Differentiate Everything with a Reversible Embeded Domain-Specific Language
Jin-Guo Liu, Taine Zhao
Reverse-mode automatic differentiation (AD) suffers from the issue of having too much space overhead to trace back intermediate computational states for back-propagation. The tradi…
Automatic differentiation of dominant eigensolver and its applications in quantum physics
Hao Xie, Jin-Guo Liu, Lei Wang
We investigate the automatic differentiation of dominant eigensolver where only a small proportion of eigenvalues and corresponding eigenvectors are obtained. Backpropagation throu…
Solving Quantum Statistical Mechanics with Variational Autoregressive Networks and Quantum Circuits
Jin-Guo Liu, Liang Mao, Pan Zhang +1
We extend the ability of unitary quantum circuits by interfacing it with classical autoregressive neural networks. The combined model parametrizes a variational density matrix as a…
Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design
Xiu-Zhe Luo, Jin-Guo Liu, Pan Zhang +1
We introduce Yao, an extensible, efficient open-source framework for quantum algorithm design. Yao features generic and differentiable programming of quantum circuits. It achieves…
Differentiable Programming Tensor Networks
Hai-Jun Liao, Jin-Guo Liu, Lei Wang +1
Differentiable programming is a fresh programming paradigm which composes parameterized algorithmic components and trains them using automatic differentiation (AD). The concept eme…