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.

The accepted paper is :

A. Sharma, G. Uehara, V. Narayananswami, L. Miller, A. Spanias, "Signal Analysis-Synthesis Using The Quantum Fourier Transform," Accepted IEEE ICASSP 2023, June 2023.

Abstract

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.