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Analysis of Heat Dissipation and Reliability in Information Erasure: A Gaussian Mixture Approach
Saurav Talukdar1, Shreyas Bhaban2, James Melbourne2
1Department of Mechanical Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.
Entropy (Basel, Switzerland)
|December 3, 2020
Summary
This study quantifies memory imperfections using a Brownian particle model. It establishes entropy bounds for reliable information erasure and storage at minimal scales.
Area of Science:
- Physics
- Information Theory
- Statistical Mechanics
Background:
- Physically realizable memory systems are subject to imperfections.
- Modeling a bit as a Brownian particle in a double-well potential offers insights into memory behavior.
Purpose of the Study:
- To analyze the impact of imperfections on memory reliability.
- To investigate the energetics of information erasure protocols.
- To determine the minimal scale for effective erasure protocols.
Main Methods:
- Utilizing a Gaussian mixture model to study erasure energetics.
- Deriving quantitative entropy bounds for memory operations.
- Comparing erasure protocol results with mean escape times from double wells.
Main Results:
- Sharp entropy bounds rigorously justify prior heuristics.
- Quantification of heat dissipation during partially successful erasures.
- Assessment of information loss due to Gaussian overlap in memory states.
Conclusions:
- The study provides a guide for performing erasure protocols at the minimal scale.
- Reliability of information stored in memory bits is directly impacted by imperfections.
- Understanding Gaussian overlap is crucial for memory interpretability and reliability.
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