Contracting Arbitrary Tensor Networks
This repo contains the numpy and pytorch implementations of the algorithm proposed in arXiv:1912.03014 for approximately contracting arbitrary tensor networks. Several examples are included for demonstrating the performance of our algorithm.
- Spin glasses on a regular random graph with
$50$ spins, degree$3$ , and$\beta=0.1$
python lnz_np.py -n 50 -beta 0.1 -k 3 -graph rrg -seed 1 -Dmax 20 -chi 500 -Jij randn -fvs -mf
- 2d ferromagnetic Ising model on a
$10\times 10$ squared lattice,$\beta=0.2$
python lnz_np.py -n 10 -beta 0.2 -graph 2dsquare -select 1 -seed 1 -Dmax 50 -chi 500 -node mps -Jij ferro -reverse 1 -compress
- Sherrington-Kirkpatrick model (fully connected, couplings following Gaussian distribution) with
$20$ spins.
python lnz_np.py -n 20 -beta 0.2 -graph complete -seed 1 -Dmax 50 -chi 500 -Jij sk -reverse 0 -compress -fvs -mf
- Spin glasses on a small-world network with
$50$ spins, degree$4$ , re-connecting probability$0.4$
python lnz_np.py -n 50 -beta 0.2 -k 4 -graph sw -select 1 -seed 1 -Dmax 50 -chi 500 -node mps -Jij randn -reverse 1 -compress -fvs -mf
- Contract a circuit with
$10\times 10=100$ qubits, with depth (1+8+1), as stored in graphs/supremacy2d100-d10-seed1-rank3-new...., with physical bond dimension$D=600$ and inner bond dimension$\chi=1500$
First run pip install fire, then
python ./qc.py -graph supremacy2d100-d10-seed1-rank3-new -Dmax 600 -chi 1500