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  1. NTU Theses and Dissertations Repository
  2. 理學院
  3. 物理學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94627
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor高英哲zh_TW
dc.contributor.advisorYing-Jer Kaoen
dc.contributor.author曹統zh_TW
dc.contributor.authorTung Tsaoen
dc.date.accessioned2024-08-16T17:10:43Z-
dc.date.available2024-08-17-
dc.date.copyright2024-08-16-
dc.date.issued2024-
dc.date.submitted2024-08-12-
dc.identifier.citationRoman Orus. A practical introduction to tensor networks: Matrix product states and projected entangled pair states. Annals of Physics, 349, 06 2013.
Ulrich Schollwöck. The density-matrix renormalization group in the age of matrix product states. Annals of Physics, 326(1):96–192, 2011. January 2011 Special Issue.
J. Eisert, M. Cramer, and M. B. Plenio. Colloquium: Area laws for the entanglement entropy. Rev. Mod. Phys., 82:277–306, Feb 2010.
Guifré Vidal. Efficient classical simulation of slightly entangled quantum computations. Phys. Rev. Lett., 91:147902, Oct 2003.
R. Orús and G. Vidal. Infinite time-evolving block decimation algorithm beyond unitary evolution. Phys. Rev. B, 78:155117, Oct 2008.
James Dborin. Implementing Tensor Network Algorithms on Quantum Computers.2023.
Sheng-Hsuan Lin, Rohit Dilip, Andrew G. Green, Adam Smith, and Frank Poll- mann. Real- and imaginary-time evolution with compressed quantum circuits. PRX Quantum, 2:010342, Mar 2021.
Manuel Rudolph, Jing Chen, Jacob Miller, Atithi Acharya, and Alejandro Perdomo Ortiz. Decomposition of matrix product states into shallow quantum circuits. 09 2022.
F. Barratt, James Dborin, Matthias Bal, Vid Stojevic, Frank Pollmann, and A. Green. Parallel quantum simulation of large systems on small nisq computers. npj Quantum Information, 7:79, 05 2021.
Stefano Barison, Filippo Vicentini, and Giuseppe Carleo. An efficient quantum algorithm for the time evolution of parameterized circuits. Quantum, 5:512, 07 2021.
Farrokh Vatan and Colin Williams. Optimal quantum circuits for general two-qubit gates. Phys. Rev. A, 69:032315, Mar 2004.
Gavin Crooks. Gradients of parameterized quantum gates using the parameter-shift rule and gate decomposition. 05 2019.
Andrea Mari, Thomas Bromley, and Nathan Killoran. Estimating the gradient and higher-order derivatives on quantum hardware. Physical Review A, 103, 01 2021.
Ali Javadi-Abhari, Matthew Treinish, Kevin Krsulich, Christopher J. Wood, Jake Lishman, Julien Gacon, Simon Martiel, Paul D. Nation, Lev S. Bishop, Andrew W. Cross, Blake R. Johnson, and Jay M. Gambetta. Quantum computing with Qiskit, 2024.
I-Chi Chen, Benjamin Burdick, Y. Yao, Peter P. Orth, and Thomas Iadecola. Error- mitigated simulation of quantum many-body scars on quantum computers with pulse-level control. Physical Review Research, 4, 10 2022.
James Spall. An overview of the simultaneous perturbation method for efficient optimization. 02 2001.
Ken M. Nakanishi, Keisuke Fujii, and Synge Todo. Sequential minimal optimization for quantum-classical hybrid algorithms. Phys. Rev. Res., 2:043158, Oct 2020.
M. Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, and Patrick Coles. Cost function dependent barren plateaus in shallow parametrized quantum circuits. Nature Communications, 12, 03 2021.
Adam Smith, M. Kim, Frank Pollmann, and Johannes Knolle. Simulating quantum many-body dynamics on a current digital quantum computer. npj Quantum Information, 5, 12 2019.
Thomas Alexander, Naoki Kanazawa, Daniel J Egger, Lauren Capelluto, Christopher J Wood, Ali Javadi-Abhari, and David C McKay. Qiskit pulse: programming quantum computers through the cloud with pulses. Quantum Science and Technology, 5(4):044006, aug 2020.
Youngseok Kim, Christopher Wood, Theodore Yoder, Seth Merkel, Jay Gambetta, Kristan Temme, and Abhinav Kandala. Scalable error mitigation for noisy quantum circuits produces competitive expectation values. 08 2021.
I-Chi Chen, Benjamin Burdick, Yongxin Yao, Peter P. Orth, and Thomas Iadecola. Error-mitigated simulation of quantum many-body scars on quantum computers with pulse-level control. Phys. Rev. Res., 4:043027, Oct 2022.
Nathan Earnest, Caroline Tornow, and Daniel J. Egger. Pulse-efficient circuit transpilation for quantum applications on cross-resonance-based hardware. Phys. Rev. Res., 3:043088, Oct 2021.
Fabian H L Essler and Maurizio Fagotti. Quench dynamics and relaxation in isolated integrable quantum spin chains. Journal of Statistical Mechanics: Theory and Experiment, 2016(6):064002, jun 2016.
Joseph Vovrosh, Kiran E. Khosla, Sean Greenaway, Christopher Self, M. S. Kim, and Johannes Knolle. Simple mitigation of global depolarizing errors in quantum simulations. Phys. Rev. E, 104:035309, Sep 2021.
David Linteau, Stefano Barison, Netanel H. Lindner, and Giuseppe Carleo. Adaptive projected variational quantum dynamics. Phys. Rev. Res., 6:023130, May 2024.
Shiro Tamiya and Hayata Yamasaki. Stochastic gradient line bayesian optimization for efficient noise-robust optimization of parameterized quantum circuits. npj Quantum Information, 8:90, 07 2022.
Baptiste Anselme Martin, Thomas Ayral, François Jamet, Marko J. Rančić, and Pas- cal Simon. Combining matrix product states and noisy quantum computers for quantum simulation. 2024.
Luke Causer, Felix Jung, Asimpunya Mitra, Frank Pollmann, and Adam Gammon- Smith. Scalable simulation of nonequilibrium quantum dynamics via classically optimized unitary circuits. Phys. Rev. Res., 6:033062, Jul 2024.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94627-
dc.description.abstract操作和測量量子系統方面在過去幾年取得了顯著進展,這使得量子計算成為一個充滿潛力的研究領域,其中涵蓋了多體物理等多個主題。張量網絡(TNs)顯示出強大的數值技術,可以有效捕捉量子糾纏和相關性,其中,矩陣積態(MPS)是最常用的框架。MPS可以轉換為參數化的量子電路,並與時間演化算符結合,從而構建基於MPS的混合量子經典演算法。本論文對這種方法進行了深入探討,並展示了使用IBM噪音模型的模擬數據。然而,由於缺乏大規模量子錯誤更正,這種變分量子時間演化算法難以在真實量子處理器上實施。因此,我們提出了一種方法,直接對初始態施加時間演化算符。在減少量子閘數量後,我們在IBM量子計算機上實現了這些量子電路,並結合了全域去極化錯誤緩解方式。我們成功捕捉了易辛模型(TFIM)磁化強度的主要頻率,這也是本論文的最後部分。zh_TW
dc.description.abstractOver the past few years, we have seen remarkable progress in our ability to manipulate and measure quantum systems, which makes quantum computing an exciting area of research on various themes including many-body physics. Tensor networks (TNs) have recently shown powerful numerical techniques that capture quantum entanglement and correlations. Among all the TN methods, matrix product state (MPS) is the most widely used framework and it also ensures the use of TNs is a parameterized wavefunctions. MPS can be transformed into parameterized quantum circuit, and combined with time evolution operator, hybrid quantum-classical algorithm base on MPS can be constructed. This thesis provides a more in-depth exploration of this method. And the data of simulations using the noise model of IBM real device were also exhibited in this thesis. Nevertheless, this variational quantum time evolution algorithm can barely be implemented on real quantum processors due to the lack of large-scale quantum error correction. Thus, we propose a time evolution method by directly impose time evolution operator on initial state. After reducing the number of quantum gates, we implement the quantum circuits on IBM quantum computers. Combined with error mitigation technique of global depolarizing errors, the dominant frequency of the transverse field Ising model (TFIM) can be captured and this is the last part of this thesis.en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-16T17:10:43Z
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dc.description.provenanceMade available in DSpace on 2024-08-16T17:10:43Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontentsAcknowledgements i
摘要 iii
Abstract v
Contents vii
List of Figures ix
Chapter 1 Introduction 1
1.1 Background and Motivation 1
1.2 Outline of the Thesis 1
Chapter 2 Tensor Network and Matrix Product State 3
2.1 Tensor Network 3
2.2 Matrix Product State(MPS) 6
2.2.1 MPS Canonical Form 10
2.3 Represent MPS as Quantum Circuits(QMPS) 12
Chapter 3 Variational Time Evolving QMPS 15
3.1 Time Evolution with projected–Variational Quantum Algorithm(pVQA) 16
3.2 Optimization Method 19
3.2.1 Parameter Shift Rule 19
Acknowledgements 3
摘要 5
Abstract 7
Contents 9
List of Figures 11
Chapter 1 Introtduction 1
1.1 Background and Motivation 1
1.2 Outline of the Thesis 1
Chapter 2 Tensor Network and Matrix Product State 3
2.1 Tensor Network 3
2.2 Matrix Product State(MPS) 6
2.2.1 MPS Canonical Form 10
2.3 Represent MPS as Quantum Circuits(QMPS) 12
Chapter 3 Variational Time Evolving QMPS 15
3.1 Time Evolution with projected–Variational Quantum Algorithm(pVQA) 16
3.2 Optimization Method 19
3.2.1 Parameter Shift Rule 19
Acknowledgements 3
摘要 5
Abstract 7
Contents 9
List of Figures 11
Chapter 1 Introtduction 1
1.1 Background and Motivation 1
1.2 Outline of the Thesis 1
Chapter 2 Tensor Network and Matrix Product State 3
2.1 Tensor Network 3
2.2 Matrix Product State(MPS) 6
2.2.1 MPS Canonical Form 10
2.3 Represent MPS as Quantum Circuits(QMPS) 12
Chapter 3 Variational Time Evolving QMPS 15
3.1 Time Evolution with projected–Variational Quantum Algorithm(pVQA) 16
3.2 Optimization Method 19
3.2.1 Parameter Shift Rule 19
3.2.2 Gradient-Based Method and Results 21
3.2.2.1 Results 22
3.2.2.2 Simultaneous Perturbation Stochastic Approximation (SPSA) and Results 24
3.2.3 Gradient Free Method 28
3.3 Local Cost Function and Results 31
3.4 Noise Model Simulation Results 35
Chapter 4 Time Evolving TN 37
4.1 Quantum Time Evolution 37
4.1.1 Suzuki-Trotter Decomposition 38
4.1.2 RZZ gate 39
4.1.2.1 CNOT Gates Decomposition 40
4.1.2.2 Cross-Resonance Gate 41
4.2 Implementation on IBM Processor 41
4.2.1 Global Depolarizing Error Mitigation and Results 42
4.2.2 Gates Reduction and Results 44
4.2.3 Cross-Resonance Gate and Results 49
Chapter 5 Conclusion and Outlook 51
References 53
-
dc.language.isoen-
dc.title張量網路時間演化演算法在量子電路上之實踐zh_TW
dc.titleTensor Network Time Evolution Algorithm on Quantum Deviceen
dc.typeThesis-
dc.date.schoolyear112-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee林瑜琤;許琇娟zh_TW
dc.contributor.oralexamcommitteeYu-Cheng Lin;Hsiu-Chuan Hsuen
dc.subject.keyword張量網路,矩陣積態,易辛模型,混和量子古典演算法,Trotter-Suzuki 分解,zh_TW
dc.subject.keywordTensor networks,Matrix product state,Transverse field Ising model,Hybrid quantum-classical algorithm,Trotter-Suzuki decomposition,en
dc.relation.page56-
dc.identifier.doi10.6342/NTU202403774-
dc.rights.note未授權-
dc.date.accepted2024-08-13-
dc.contributor.author-college理學院-
dc.contributor.author-dept物理學系-
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