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Signal Analysis Synthesis Using The Quantum Fourier Transform
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Introducing quantum computing functions in J-DSP. T By making these tools available to a broader audience, we can inspire the next generation of quantum
researchers and prepare a more diverse workforce for the emerging field of quantum technologies.
The paper is accepted in IEEE ICASSP 2023.
A. Sharma, G. Uehara, V. Narayananswami, L. Miller, A. Spanias, "Signal Analysis-Synthesis Using The
Quantum Fourier Transform," Accepted IEEE ICASSP 2023, June 2023.
This paper presents the development of Quantum Fourier transform (QFT) education tools
in the object-oriented Java-DSP (J-DSP) simulation environment. More specifically,
QFT and Inverse QFT (IQFT) user-friendly J-DSP functions are developed to expose
undergraduate students to quantum computing. These functions provide opportunities
to examine QFT resolution, precision (qubits), and the effects of quantum measurement
noise. In our study, we also describe a laboratory exercise on QFT-based speech
analysis-synthesis which has been deployed in our senior-level DSP class and
in our NSF workforce development programs.
The software and the laboratory exercise are evaluated using formative and summative assessments.
References similar to this work are :
G. Uehara, V. Narayanaswamy, C. Tepedelenlioglu, A. Spanias, "Quantum Machine Learning for
Photovoltaic Topology Optimization," 2022 IEEE 13th International Conference on Information,
Intelligence, Systems & Applications (IISA), Hybrid Conference, July 2022.
M. Yarter, G. Uehara, A. Spanias, "Implementation and Analysis of Quantum Homomorphic
Encryption," 2022 IEEE 13th International Conference on Information, Intelligence, Systems &
Applications (IISA), Hybrid Conference, July 2022.
Glen Uehara, Jean Larson, Wendy Barnard, Michael Esposito, Filippo Posta, Maxwell Yarter, Aradhita
Sharma, Niki Kyriacou, Matthew Dobson, Andreas Spanias, "Undergraduate Research and Education
in Quantum Machine Learning," IEEE FIE 2022, Upsala, Oct. 2022.
G. Uehara, A. Spanias, W. Clark, "Quantum Information Processing Algorithms with Emphasis on
Machine Learning," Proc. IEEE IISA 2021, July 2021.
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