Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis

Soohyun Park; Hao Feng; Won Joon Yun; Chanyoung Park; Youn Kyu Lee; Soyi Jung; Joongheon Kim

doi:10.1109/ICDCS57875.2023.00116

Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis

Soohyun Park
, Hao Feng
, Won Joon Yun
, Chanyoung Park
, Youn Kyu Lee
, Soyi Jung
, Joongheon Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

This paper proposes an efficient quantum train engine (EQuaTE), a novel tool for quantum machine learning software which plots gradient variances to check whether our quantum neural network (QNN) falls into local minima (called barren plateaus in QNN). EQuaTE can be realized via dynamic analysis of the undetermined probabilistic qubit states. Furthermore, the proposed EQuaTE is capable of HCI-based visual feedback such that software engineers can recognize barren plateaus via visualization, allowing the modification of QNN based on this information.

Original language	English
Title of host publication	Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems, ICDCS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1009-1012
Number of pages	4
ISBN (Electronic)	9798350339864
DOIs	https://doi.org/10.1109/ICDCS57875.2023.00116
Publication status	Published - 2023
Event	43rd IEEE International Conference on Distributed Computing Systems, ICDCS 2023 - Hong Kong, China Duration: 2023 Jul 18 → 2023 Jul 21

Publication series

Name	Proceedings - International Conference on Distributed Computing Systems
Volume	2023-July

Conference

Conference	43rd IEEE International Conference on Distributed Computing Systems, ICDCS 2023
Country/Territory	China
City	Hong Kong
Period	23/7/18 → 23/7/21

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus subject areas

Software
Hardware and Architecture
Computer Networks and Communications

Access to Document

10.1109/ICDCS57875.2023.00116

Cite this

Park, S., Feng, H., Yun, W. J., Park, C., Lee, Y. K., Jung, S., & Kim, J. (2023). Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis. In Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems, ICDCS 2023 (pp. 1009-1012). (Proceedings - International Conference on Distributed Computing Systems; Vol. 2023-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDCS57875.2023.00116

Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis. / Park, Soohyun; Feng, Hao; Yun, Won Joon et al.
Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems, ICDCS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 1009-1012 (Proceedings - International Conference on Distributed Computing Systems; Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, S, Feng, H, Yun, WJ, Park, C, Lee, YK, Jung, S & Kim, J 2023, Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis. in Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems, ICDCS 2023. Proceedings - International Conference on Distributed Computing Systems, vol. 2023-July, Institute of Electrical and Electronics Engineers Inc., pp. 1009-1012, 43rd IEEE International Conference on Distributed Computing Systems, ICDCS 2023, Hong Kong, China, 23/7/18. https://doi.org/10.1109/ICDCS57875.2023.00116

Park S, Feng H, Yun WJ, Park C, Lee YK, Jung S et al. Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis. In Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems, ICDCS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 1009-1012. (Proceedings - International Conference on Distributed Computing Systems). doi: 10.1109/ICDCS57875.2023.00116

Park, Soohyun ; Feng, Hao ; Yun, Won Joon et al. / Demo : EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis. Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems, ICDCS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 1009-1012 (Proceedings - International Conference on Distributed Computing Systems).

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abstract = "This paper proposes an efficient quantum train engine (EQuaTE), a novel tool for quantum machine learning software which plots gradient variances to check whether our quantum neural network (QNN) falls into local minima (called barren plateaus in QNN). EQuaTE can be realized via dynamic analysis of the undetermined probabilistic qubit states. Furthermore, the proposed EQuaTE is capable of HCI-based visual feedback such that software engineers can recognize barren plateaus via visualization, allowing the modification of QNN based on this information.",

author = "Soohyun Park and Hao Feng and Yun, \{Won Joon\} and Chanyoung Park and Lee, \{Youn Kyu\} and Soyi Jung and Joongheon Kim",

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Demo: EQuaTE: Efficient Quantum Train Engine Design and Demonstration for Dynamic Software Analysis

Abstract

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Bibliographical note

ASJC Scopus subject areas

Access to Document

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