Classify Growth Rates for Wolfram Models
Author
Jatin Kansal
Title
Classify Growth Rates for Wolfram Models
Description
The objective of the project is to formally classify the observed growth rates into different categories and try to find Wolfram Models with non-linear and non-exponential growth rates.
Category
Essays, Posts & Presentations
Keywords
Wolfram Models, Growth Rates, Fundamental Theory of Physics
URL
http://www.notebookarchive.org/2020-07-6h98gnu/
DOI
https://notebookarchive.org/2020-07-6h98gnu
Date Added
2020-07-14
Date Last Modified
2020-07-14
File Size
478.46 kilobytes
Supplements
Rights
Redistribution rights reserved
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WOLFRAM SUMMER SCHOOL 2020
Classifying Growth Rates for Wolfram Models
Classifying Growth Rates for Wolfram Models
Jatin Kansal
Minerva Schools at KGI
Abstract:
Objective:
Wolfram Physics Models are one of the newest and promising direction to explore the Fundamental Theory of Physics. One of the properties of the models is their growth. Most of the models seem to grow at exponential or linear scales. The objective here is to formally classify the observed growth rates into different categories and try to find Wolfram Models with non-linear and non-exponential growth rates.
Results:
We ran the Wolfram Models for various signatures and found only Linear and Exponential growth rates. These growth rates were not perfect and had some variations, but the overall growth rates fitted almost perfectly in the linear and exponential models. A function called WolframModelInterestingRules[] was created to automatically filter out rules with “purely linear” and “purely exponential” growth rates.
Objective:
Wolfram Physics Models are one of the newest and promising direction to explore the Fundamental Theory of Physics. One of the properties of the models is their growth. Most of the models seem to grow at exponential or linear scales. The objective here is to formally classify the observed growth rates into different categories and try to find Wolfram Models with non-linear and non-exponential growth rates.
Results:
We ran the Wolfram Models for various signatures and found only Linear and Exponential growth rates. These growth rates were not perfect and had some variations, but the overall growth rates fitted almost perfectly in the linear and exponential models. A function called WolframModelInterestingRules[] was created to automatically filter out rules with “purely linear” and “purely exponential” growth rates.
Wolfram Community Post (material for blog post)
Wolfram Community Post (material for blog post)
As a first step to classify the growth rates, I decided to create a function which would remove all the “uninteresting” rules automatically and leave us with only a fraction of the original number of rules to check. Hence, I created the function WolframModelIterestingRules.
The function WolframModelInterestingRules
The function WolframModelInterestingRules
Classification of observed growth rates
Classification of observed growth rates
Future Work
Future Work
Code Repository
Code Repository
Acknowledgements
Acknowledgements
Complete project work
Complete project work
As a first step to classify the growth rates, I decided to create a function which would remove all the “uninteresting” rules automatically and leave us with only a fraction of the original number of rules to check. Hence, I created the function WolframModelIterestingRules.
The function WolframModelInterestingRules
The function WolframModelInterestingRules
Classification of observed growth rates
Classification of observed growth rates
Future Work
Future Work
Code Repository
Code Repository
Acknowledgements
Acknowledgements
Keywords
Keywords
◼
Wolfram Models
◼
Fundamental Theory of Physics
◼
Growth Rates
Acknowledgment
Acknowledgment
Mentor: Jack Heimrath
A huge thanks to Jack for helping out with all the details from the nitty-gritty details to major problems.
Jesse Friedman has been of instrumental help in optimizing my code and functions.
A major thanks to Stephen Wolfram and Wolfram Research for running my very heavy code on AWS.
Jesse Friedman has been of instrumental help in optimizing my code and functions.
A major thanks to Stephen Wolfram and Wolfram Research for running my very heavy code on AWS.
References
References
Cite this as: Jatin Kansal, "Classify Growth Rates for Wolfram Models" from the Notebook Archive (2020), https://notebookarchive.org/2020-07-6h98gnu
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