Accelerated molecular dynamics with large-time-step predictions
Project description
FlashMD: long-stride, universal prediction of molecular dynamics
This repository contains model architectures and helper functions to use transformer-based GNNs to generate MD trajectories using long time steps.
This is experimental software and should only be used if you know what you're doing. See the cookbook recipe for a usage example, and this preprint for a discussion of the theory, benchmarks, and of the potential limitations.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file flashmd-0.1.0.tar.gz.
File metadata
- Download URL: flashmd-0.1.0.tar.gz
- Upload date:
- Size: 11.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fc5127d181588830dd788759e4d90bb602b675d6997a1dc87a91c6db94f1844e
|
|
| MD5 |
2aaceb843e6648a2b697c50aa3d74e7a
|
|
| BLAKE2b-256 |
32b1fff40d22e944800a6f29586a74cec5a74b9a22402006989c9b3f55a7914c
|
File details
Details for the file flashmd-0.1.0-py3-none-any.whl.
File metadata
- Download URL: flashmd-0.1.0-py3-none-any.whl
- Upload date:
- Size: 13.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d8adf62e71f25bd5c74142cd51fff36bce908103f80c45e4b407a5c04c2eb6d8
|
|
| MD5 |
456cd7e3224ff930a006c3d44237b6ed
|
|
| BLAKE2b-256 |
58025871d49987e5b52e42930ec969468979ee68db2c384a8dbc82af9c999a9c
|
