Graduation Year
2025
Date of Submission
12-2024
Document Type
Campus Only Senior Thesis
Degree Name
Bachelor of Arts
Department
Physics
Reader 1
Sarah Marzen
Reader 2
Kevin Setter
Terms of Use & License Information
Rights Information
© 2024 Ruiyang Ni
Abstract
A reservoir computer is a neural network model that uses past information to predict a system’s future states. Recently, Quantum Reservoir Computing (QRC) has emerged as a promising research area, with studies suggesting that QRC may offer greater efficiency compared to classical reservoirs. This paper aims to investigate the applicability of quantum reservoirs and their advantages over classical reservoirs by proposing a possible reservoir. Specifically, we model a quantum harmonic oscillator (the reservoir), with its angular frequency ω modulated by the position s of a classical noisy damped harmonic oscillator (the system). Our anticipated results, demonstrate the proposed reservoir should exhibit superior prediction accuracy compared to classical reservoirs. This improvement is attributable to the infinite-dimensionality of quantum reservoirs, which enables greater information storage. While classical reservoirs can be manipulated to achieve high dimensionality, an infinite-dimensional quantum reservoir retains the capability to store significantly more information. These anticipated results open avenues for further exploration of different quantum systems as reservoirs, such as entangled qubit pairs, and their potential applications.
Recommended Citation
Ni, Ruiyang, "A Minimalistic Approach to Quantum Reservoir Computing: The Power of a Single Quantum Oscillator" (2025). CMC Senior Theses. 3841.
https://scholarship.claremont.edu/cmc_theses/3841
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.