https://github.com/zhendongli2008/fPEPS

fermionic Projected Entangled Pairs States (fPEPS)
https://github.com/zhendongli2008/fPEPS

Last synced: 3 months ago
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fermionic Projected Entangled Pairs States (fPEPS)

• Host: GitHub
• URL: https://github.com/zhendongli2008/fPEPS
• Owner: zhendongli2008
• Created: 2018-10-25T21:18:17.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2018-10-25T21:52:49.000Z (about 6 years ago)
• Last Synced: 2024-07-04T02:13:29.620Z (4 months ago)
• Language: Python
• Homepage:
• Size: 43.9 KB
• Stars: 16
• Watchers: 4
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: readme

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README

        
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 Fermonic PEPS using parity conserving tensors

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 - bsarray and parray classes

 - einsum 

 - create repo

 - general parray and einsum

 - initialization of peps,

   in particular merge & transpose of parray

 - operations: mps_dot & mpo_apply_to_mps 

 - peps_dot and peps contraction

 - autograd optimization

 - Hessenberg hamiltonian - fix bug for 3*3 case [fixed for Sp*Sm]

 - autograd tested against finite difference

 - save & load PEPS => callback

 - SVD-mps/mpo compression for larger systems

 - fix bugs in  

 - Monte-Carlo - seems to be very suitable for long-range Hamiltoinan;

   we only needs to read out the coefficients  for given |n>.

   Note:  is required to avoid additional RI.

 - fermionic operations

   Starting from 2-by-2: 

    Q1: how operators are represented and act on PEPS ? 

    Q2: how  can be converted to bosonic TNS diagrams?

    Q3: particle number projector? any advantage 


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 TODOs

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 - memory issue? => larger systems

 - optimize the contraction scheme for ;

   reusing intermediates or using PEPO

 - regularize the PEPS for better numerical stability! 

   divide each by max element

 - eigenvalue optimization for small problem

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 To run it:

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 - Requirement: autograd

 

 - Download and change name for directory from fPEPS to fpeps2017.

   Go to fermions and run, e.g., peps2by2.py.