Signal Analysis-Synthesis Using the Quantum Fourier Transform

Aradhita Sharma; Glen Uehara; Vivek Narayanaswamy; Leslie Miller; Andreas Spanias

doi:10.1109/ICASSP49357.2023.10096524

Signal Analysis-Synthesis Using the Quantum Fourier Transform

Aradhita Sharma, Glen Uehara, Vivek Narayanaswamy, Leslie Miller, Andreas Spanias

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

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.

Original language	English (US)
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
DOIs	https://doi.org/10.1109/ICASSP49357.2023.10096524
State	Published - 2023
Externally published	Yes
Event	48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023 - Rhodes Island, Greece Duration: Jun 4 2023 → Jun 10 2023

Keywords

Java-DSP
quantum Fourier transform
quantum noise
qubits
speech analysis-synthesis

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP49357.2023.10096524

Cite this

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title = "Signal Analysis-Synthesis Using the Quantum Fourier Transform",

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.",

keywords = "Java-DSP, quantum Fourier transform, quantum noise, qubits, speech analysis-synthesis",

author = "Aradhita Sharma and Glen Uehara and Vivek Narayanaswamy and Leslie Miller and Andreas Spanias",

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AU - Uehara, Glen

AU - Narayanaswamy, Vivek

AU - Miller, Leslie

AU - Spanias, Andreas

PY - 2023

Y1 - 2023

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AB - 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.

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KW - quantum Fourier transform

KW - quantum noise

KW - qubits

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JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

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Y2 - 4 June 2023 through 10 June 2023

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Signal Analysis-Synthesis Using the Quantum Fourier Transform

Abstract

Keywords

ASJC Scopus subject areas

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