Park, Seung - Revision history

Mahnsoo.Choi at 00:47, 12 August 2026

2026-08-12T00:47:05Z

← Older revision		Revision as of 00:47, 12 August 2026
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	Seung Park received his B.S. in Physics from Korea University in 2016 and his Ph.D. in Physics from the same university in 2025, with a thesis on improving variational quantum algorithms. He is currently a postdoctoral researcher at Yonsei University. His research interests include quantum machine learning, variational quantum algorithms, quantum simulation, and other near-term quantum algorithms.		Seung Park received his B.S. in Physics from Korea University in 2016 and his Ph.D. in Physics from the same university in 2025, with a thesis on improving variational quantum algorithms. He is currently a postdoctoral researcher at Yonsei University. His research interests include quantum machine learning, variational quantum algorithms, quantum simulation, and other near-term quantum algorithms.

			[[Category:Speakers]]
			[[Category:Old Members]]

	==Dual-channel multi-product formula==		==Dual-channel multi-product formula==
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	Product formula (PF) is a promising approach for simulating quantum systems on near-term digital quantum computers. Achieving a desired simulation precision typically requires a polynomially increasing number of Trotter steps, which remains challenging due to the limited capabilities of current quantum hardware. To alleviate this issue, algorithmic error-mitigation techniques such as the multi-product formula (MPF) have been introduced to suppress Trotter errors under restricted hardware resources. In this work, we propose a dual-channel MPF protocol that utilizes the average of a PF and its reversed-sequence counterpart without increasing circuit depth. Our method enables the target simulation precision to be reached with approximately half the circuit depth compared to conventional MPF schemes. This provides substantial error reduction on noisy hardware while implementing a well-conditioned MPF. We also demonstrate our algorithm through numerical simulations under a noise model, showing that our proposal achieves significantly smaller errors.		Product formula (PF) is a promising approach for simulating quantum systems on near-term digital quantum computers. Achieving a desired simulation precision typically requires a polynomially increasing number of Trotter steps, which remains challenging due to the limited capabilities of current quantum hardware. To alleviate this issue, algorithmic error-mitigation techniques such as the multi-product formula (MPF) have been introduced to suppress Trotter errors under restricted hardware resources. In this work, we propose a dual-channel MPF protocol that utilizes the average of a PF and its reversed-sequence counterpart without increasing circuit depth. Our method enables the target simulation precision to be reached with approximately half the circuit depth compared to conventional MPF schemes. This provides substantial error reduction on noisy hardware while implementing a well-conditioned MPF. We also demonstrate our algorithm through numerical simulations under a noise model, showing that our proposal achieves significantly smaller errors.

	[[Category:~~Speakers]]~~		[[Category: Quantum Technology Workshop 2026]]
	~~[[Category:Old Members~~]]

Mahnsoo.Choi: /* Dual-channel multi-product formula */

2026-08-09T14:40:39Z

Dual-channel multi-product formula

← Older revision		Revision as of 14:40, 9 August 2026
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	==Dual-channel multi-product formula==		==Dual-channel multi-product formula==

	* Speaker:		* Speaker: [[Park, Seung\|Seung Park]] (Yongsei University, Korea)
	* Event: [[Quantum Technology Workshop 2026]]		* Event: [[Quantum Technology Workshop 2026]]

Mahnsoo.Choi at 14:38, 9 August 2026

2026-08-09T14:38:59Z

← Older revision		Revision as of 14:38, 9 August 2026
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	Seung Park received his B.S. in Physics from Korea University in 2016 and his Ph.D. in Physics from the same university in 2025, with a thesis on improving variational quantum algorithms. He is currently a postdoctoral researcher at Yonsei University. His research interests include quantum machine learning, variational quantum algorithms, quantum simulation, and other near-term quantum algorithms.		Seung Park received his B.S. in Physics from Korea University in 2016 and his Ph.D. in Physics from the same university in 2025, with a thesis on improving variational quantum algorithms. He is currently a postdoctoral researcher at Yonsei University. His research interests include quantum machine learning, variational quantum algorithms, quantum simulation, and other near-term quantum algorithms.

			==Dual-channel multi-product formula==

			* Speaker:
			* Event: [[Quantum Technology Workshop 2026]]

			Product formula (PF) is a promising approach for simulating quantum systems on near-term digital quantum computers. Achieving a desired simulation precision typically requires a polynomially increasing number of Trotter steps, which remains challenging due to the limited capabilities of current quantum hardware. To alleviate this issue, algorithmic error-mitigation techniques such as the multi-product formula (MPF) have been introduced to suppress Trotter errors under restricted hardware resources. In this work, we propose a dual-channel MPF protocol that utilizes the average of a PF and its reversed-sequence counterpart without increasing circuit depth. Our method enables the target simulation precision to be reached with approximately half the circuit depth compared to conventional MPF schemes. This provides substantial error reduction on noisy hardware while implementing a well-conditioned MPF. We also demonstrate our algorithm through numerical simulations under a noise model, showing that our proposal achieves significantly smaller errors.

	[[Category:Speakers]]		[[Category:Speakers]]
	[[Category:Old Members]]		[[Category:Old Members]]

Mahnsoo.Choi at 05:40, 31 May 2026

2026-05-31T05:40:55Z

← Older revision		Revision as of 05:40, 31 May 2026
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	[[Category:Speakers]]		[[Category:Speakers]]
	~~[[Category:Members]]~~
	[[Category:Old Members]]		[[Category:Old Members]]

Mahnsoo.Choi at 05:40, 31 May 2026

2026-05-31T05:40:34Z

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 [[Image:spark_profile.jpg|right|thumb]]
-<blockquote>
+Seung Park received his B.S. in Physics from Korea University in 2016 and his Ph.D. in Physics from the same university in 2025, with a thesis on improving variational quantum algorithms. He is currently a postdoctoral researcher at Yonsei University. His research interests include quantum machine learning, variational quantum algorithms, quantum simulation, and other near-term quantum algorithms.
 [[Category:Members]]

Mahnsoo.Choi at 06:55, 10 September 2018

2018-09-10T06:55:53Z

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	~~{{Warning\|Nothing serious!}}~~

	[[Image:spark_profile.jpg\|right\|thumb]]		[[Image:spark_profile.jpg\|right\|thumb]]

Mahnsoo.Choi at 06:55, 10 September 2018

2018-09-10T06:55:03Z

← Older revision		Revision as of 06:55, 10 September 2018
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			{{Warning\|Nothing serious!}}

	[[Image:spark_profile.jpg\|right\|thumb]]		[[Image:spark_profile.jpg\|right\|thumb]]

Spark at 10:32, 25 July 2016

2016-07-25T10:32:49Z

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			[[Image:spark_profile.jpg\|right\|thumb]]

	<blockquote>		<blockquote>

Mahnsoo.Choi at 03:26, 19 July 2016

2016-07-19T03:26:42Z

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	* Phone: 02-3290-4202		* Phone: 02-3290-4202
	* E-mail: [mailto:spark9144@gmail.com spark9144(a)gmail.com]		* E-mail: [mailto:spark9144@gmail.com spark9144(a)gmail.com]

			[[Category:Members]]

Mahnsoo.Choi: Mahnsoo.choi moved page Seung Park to Park, Seung

2016-07-17T13:08:36Z

Mahnsoo.choi moved page Seung Park to Park, Seung

← Older revision		Revision as of 13:08, 17 July 2016
(No difference)