Tenǝʇ.jl

A Julia library for Tensor Networks. Tenet can be executed both at local environments and on large supercomputers. Its goals are,

• Expressiveness Simple to use. 👶
• Flexibility Extend it to your needs. 🔧
• Performance Goes brr... fast. 🏎️

A video of its presentation at JuliaCon 2023 can be seen here:

Features

• Optimized Tensor Network contraction, powered by EinExprs
• Tensor Network slicing/cuttings
• Automatic Differentiation of TN contraction
• Distributed contraction
• Quantum Tensor Networks
  • Matrix Product States (MPS)
  • Matrix Product Operators (MPO)
  • Tree Tensor Networks (TTN)
  • Projected Entangled Pair States (PEPS)
  • Multiscale Entanglement Renormalization Ansatz (MERA)
• Numerical Tensor Network algorithms
  • Tensor Renormalization Group (TRG)
  • Density Matrix Renormalization Group (DMRG)
• Local Tensor Network transformations
  • Hyperindex converter
  • Rank simplification
  • Diagonal reduction
  • Anti-diagonal gauging
  • Column reduction
  • Split simplification
• 2D & 3D visualization of large networks, powered by Makie
• Translation from quantum circuits, powered by Quac