https://github.com/cometscome/ctaux_julia

Continuous-time auxiliary-field quantum Monte Carlo method. See, E. Gull et al., EPL 82, 57003 (2008)
https://github.com/cometscome/ctaux_julia

Last synced: about 1 month ago
JSON representation

Continuous-time auxiliary-field quantum Monte Carlo method. See, E. Gull et al., EPL 82, 57003 (2008)

• Host: GitHub
• URL: https://github.com/cometscome/ctaux_julia
• Owner: cometscome
• Created: 2017-10-24T13:30:24.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2023-09-24T09:03:06.000Z (about 1 year ago)
• Last Synced: 2024-10-13T19:39:24.528Z (2 months ago)
• Language: Jupyter Notebook
• Size: 168 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Continuous-time auxiliary-field Quantum Monte Carlo method for Anderson impurity model with Bethe-lattice-bath electrons

See, E. Gull et al., EPL 82, 57003 (2008)

Yuki Nagai, Ph.D 10/24/2017(MM/DD/YY)

This code was made by Julia 0.6.0.

# Note: This code with Julia 0.6.0 is 6 times slower than that with Fortran90.

If you know how to speedup this code, please tell me.

The code was revised for Julia 0.7. 

# The code in Julia 0.7 is 5 times slower than that with Fortran90. 

# update (2023/09/24)

I wrote new code for Julia 1.9.3. The code is ctaux_faster.jl

The benchmark (MacBookPro M2 Max)

Original code Julia 0.7 (ctaux.jl)

```

 19.759999 seconds (208.14 M allocations: 11.827 GiB, 0.94% gc time)

```

Old code rewritten for Julia 1.9.3 (ctaux_juliav1.9.jl):

```

 15.258614 seconds (170.55 M allocations: 10.790 GiB, 1.24% gc time, 0.11% compilation time)

```

New code in Julia 1.9.3 (ctaux_faster.jl)

```

 10.448534 seconds (2.05 k allocations: 123.203 KiB)

```