Brief Introduction
Provides a unified perspective connecting equilibrium statistical mechanics with stochastic neural networks and quantum computing.
Description
A unique course that connects three diverse fields using the unifying concept of a state-space with 2^N dimensions defined by N binary bits. We start from the seminal concepts of statistical mechanics like entropy, free energy and the law of equilibrium that have been developed with the purpose of describing interacting systems occurring in nature. We then move to the concept of Boltzmann machines (BM) which are interacting systems cleverly engineered to solve important problems in machine learning. Finally, we move to engineered quantum systems stressing the phenomenon of quantum interference which can lead to awesome computing power.
Knowledge
- Boltzmann Law
- Boltzmann Machines
- Transition Matrix
- Quantum Boltzmann Law
- Quantum Gates
Boltzmann Law: Physics to Computing
- 0.0
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Provides a unified perspective connecting equilibrium statistical mechanics with stochastic neural networks and quantum computing. Boltzmann Law Boltzmann Machines Transition Matrix...
Exploring Renewable Energy Schemes
- 4.7
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What do you picture when you hear the term “renewable energy? ” Do you imagine fields of solar panels, giant windmills, or huge hydroelectric dams?...
Statistical Molecular Thermodynamics
- 4.9
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This introductory physical chemistry course examines the connections between molecular properties and the behavior of macroscopic chemical systems. Module 1 Video 1....
