Monte-Carlo Simulations and Applications in Machine Learning, Option Pricing, and Quantum Processes
DOI:
https://doi.org/10.54097/5yrtzt20Keywords:
Monte-Carlo simulation; Machine learning; Optical pricing; Quantum process.Abstract
As a matter of fact, Monte Carlo simulations have evolved as a powerful computational tool with applications spanning various domains in recent years, thanks to the rapid development of computation ability. With this in mind, this research paper explores the application of Monte Carlo simulations in machine learning, optical pricing, and physical quantum processes. To be specific, this study will discuss the methodology of Monte Carlo simulations, present simulation results, and highlight the significance of employing these simulations in diverse fields. Additionally, this study will summary the historical development of Monte Carlo simulations, provide a literature review of main application scenarios, as well as outline the motivation behind this research. At the same time, it will address the current limitations of Monte Carlo simulations in these applications and offer insights into future prospects for usage. Overall, these results shed light on guiding further exploration of implementation in the state-of-art fields.
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