reversible_sim

Simulator for the Zero-Energy Computational Sampling paper, winner of the Best Poster Award at DNA29

https://github.com/leoorshansky/reversible_sim

Science Score: 54.0%

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CITATION.cff file
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Links to: arxiv.org
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Low similarity (4.1%) to scientific vocabulary

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Repository

Simulator for the Zero-Energy Computational Sampling paper, winner of the Best Poster Award at DNA29

Basic Info

Host: GitHub
Owner: leoorshansky
Language: Python
Default Branch: main
Homepage:
Size: 38.1 KB

Statistics

Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Releases: 0

Created over 3 years ago · Last pushed over 2 years ago

Metadata Files

Readme Citation

Simulator for the DNA29 Conference Best Poster Award Winner: "Harvesting Brownian Motion: Zero Energy Computational Sampling"

Read the paper here.

Usage

``` usage: python3 simulate.py [-h] -i TMINITIALSTATE -b TMRANDOMBITS [-t T] [-p] {lv,mc} tm_filename

Runs a simulated model on a specified Turing machine

positional arguments: {lv,mc} lv for Las Vegas, mc for Monte Carlo tm_filename

options: -h, --help show this help message and exit -i TMINITIALSTATE, --tminitialstate TMINITIALSTATE the head state to start the Turing machine in -b TMRANDOMBITS, --tmrandombits TMRANDOMBITS number of random bits to feed into the Turing machine as input -t T, --timebetweenobservations T units of time in between consecutive observations, defaults to 500 * bits^2 -p, --print-model do not run simulation, only print the computation graph of the constructed model ```

Owner

Name: Leo Orshansky
Login: leoorshansky
Kind: user
Location: Austin, TX

Website: linkedin.com/in/orshansky
Repositories: 4
Profile: https://github.com/leoorshansky

UT Austin Turing Scholar -- Interested in AI, Systems, Graphics, and more

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: Brownian Computation Simulator
message: >-
  A high level simulator of a distribution sampler driven
  entirely by brownian motion
type: software
authors:
  - given-names: Leo
    family-names: Orshansky
    affiliation: The University of Texas at Austin
    orcid: 'https://orcid.org/0009-0005-4445-7517'
repository-code: 'https://github.com/leoorshansky/reversible_sim'
keywords:
  - zero energy computation
  - distribution sampling
  - random walks

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