https://github.com/jarvist/longsnakemoan
Codes to predict DoS of a polymer chain in vacuum with Python Tightbinding (Huckel model)
https://github.com/jarvist/longsnakemoan
disorder polymer-chain tight-binding urbach-tail
Last synced: 8 months ago
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Codes to predict DoS of a polymer chain in vacuum with Python Tightbinding (Huckel model)
- Host: GitHub
- URL: https://github.com/jarvist/longsnakemoan
- Owner: jarvist
- Created: 2014-02-24T12:00:54.000Z (over 12 years ago)
- Default Branch: master
- Last Pushed: 2018-01-05T10:25:06.000Z (over 8 years ago)
- Last Synced: 2025-04-14T10:52:29.241Z (about 1 year ago)
- Topics: disorder, polymer-chain, tight-binding, urbach-tail
- Language: Python
- Homepage:
- Size: 156 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
LongSnakeMoan
=============
Codes to predict DoS of a polymer chain in vacuum with a one-dimensional tightbinding (Huckel model).
## Installation
The codes are still slightly dependent on the 'pythtb' module from Rutgers university (http://physics.rutgers.edu/pythtb/). Almost none of this library is used, but it's definitely recommended if you're interested in tight binding!
You can try and install this library automatically by pip,
```
pip install pythtb
```
Codes written by Jarvist Moore Frost 2012-2014.
Work based on this code was presented at MRS Boston 2012 (O8.08), slides are
here:
https://speakerdeck.com/jarvist/beta-phase
The code should produce live plots like this:
The continuation of this work (2013 onwards), including a Sturm-sequency based linear-in-time and constant-in-memory 1D Hamiltonian solver was continued in the Julia language elsewhere:
https://github.com/jarvist/Teclo.jl