東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Design and Optimization in Near-Term Quantum Computation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Design and Optimization in Near-Term Quantum Computation./
作者:	Bapat, Aniruddha A.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	304 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
Contained By:	Dissertations Abstracts International83-04B.
標題:	Quantum physics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28712775
ISBN:	9798460477739

Design and Optimization in Near-Term Quantum Computation.
Bapat, Aniruddha A.

Design and Optimization in Near-Term Quantum Computation. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 304 p.

Source: Dissertations Abstracts International, Volume: 83-04, Section: B.

Thesis (Ph.D.)--University of Maryland, College Park, 2021.

This item must not be sold to any third party vendors.

Quantum computers have come a long way since conception, and there is still a long way to go before the dream of universal, fault-tolerant computation is realized. In the near term, quantum computers will occupy a middle ground that is popularly known as the "Noisy, Intermediate-Scale Quantum" (or NISQ) regime. The NISQ era represents a transition in the nature of quantum devices from experimental to computational. There is significant interest in engineering NISQ devices and NISQ algorithms in a manner that will guide the development of quantum computation in this regime and into the era of fault-tolerant quantum computing.In this thesis, we study two aspects of near-term quantum computation. The first of these is the design of device architectures, covered in Chapters 2, 3, and 4. We examine different qubit connectivities on the basis of their graph properties, and present numerical and analytical results on the speed at which large entangled states can be created on nearest-neighbor grids and graphs with modular structure. Next, we discuss the problem of permuting qubits among the nodes of the connectivity graph using only local operations, also known as routing. Using a fast quantum primitive to reverse the qubits in a chain, we construct a hybrid, quantum/classical routing algorithm on the chain. We show via rigorous bounds that this approach is faster than any SWAP-based algorithm for the same problem.The second part, which spans the final three chapters, discusses variational algorithms, which are a class of algorithms particularly suited to near-term quantum computation. Two prototypical variational algorithms, quantum adiabatic optimization (QAO) and the quantum approximate optimization algorithm (QAOA), are studied for the difference in their control strategies. We show that on certain crafted problem instances, bang-bang control (QAOA) can be as much as exponentially faster than quasistatic control (QAO). Next, we demonstrate the performance of variational state preparation on an analog quantum simulator based on trapped ions. We show that using classical heuristics that exploit structure in the variational parameter landscape, one can find circuit parameters efficiently in system size as well as circuit depth. In the experiment, we approximate the ground state of a critical Ising model with long-ranged interactions on up to 40 spins. Finally, we study the performance of Local Tensor, a classical heuristic algorithm inspired by QAOA on benchmarking instances of the MaxCut problem, and suggest physically motivated choices for the algorithm hyperparameters that are found to perform well empirically. We also show that our implementation of Local Tensor mimics imaginary-time quantum evolution under the problem Hamiltonian.

ISBN: 9798460477739Subjects--Topical Terms:

726746
Quantum physics.
Subjects--Index Terms:

Architectures

Design and Optimization in Near-Term Quantum Computation.
LDR:04020nmm a2200397 4500 001 2344664
005 20220531064620.5
008 241004s2021 ||||||||||||||||| ||eng d
020 $a 9798460477739
035 $a (MiAaPQ)AAI28712775
035 $a AAI28712775
040 $a MiAaPQ $c MiAaPQ
100 1 $a Bapat, Aniruddha A. $0 (orcid)0000-0001-9489-9165 $3 3683456
245 1 0 $a Design and Optimization in Near-Term Quantum Computation.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 304 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
500 $a Advisor: Gorshkov, Alexey V.;Jordan, Stephen P.
502 $a Thesis (Ph.D.)--University of Maryland, College Park, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Quantum computers have come a long way since conception, and there is still a long way to go before the dream of universal, fault-tolerant computation is realized. In the near term, quantum computers will occupy a middle ground that is popularly known as the "Noisy, Intermediate-Scale Quantum" (or NISQ) regime. The NISQ era represents a transition in the nature of quantum devices from experimental to computational. There is significant interest in engineering NISQ devices and NISQ algorithms in a manner that will guide the development of quantum computation in this regime and into the era of fault-tolerant quantum computing.In this thesis, we study two aspects of near-term quantum computation. The first of these is the design of device architectures, covered in Chapters 2, 3, and 4. We examine different qubit connectivities on the basis of their graph properties, and present numerical and analytical results on the speed at which large entangled states can be created on nearest-neighbor grids and graphs with modular structure. Next, we discuss the problem of permuting qubits among the nodes of the connectivity graph using only local operations, also known as routing. Using a fast quantum primitive to reverse the qubits in a chain, we construct a hybrid, quantum/classical routing algorithm on the chain. We show via rigorous bounds that this approach is faster than any SWAP-based algorithm for the same problem.The second part, which spans the final three chapters, discusses variational algorithms, which are a class of algorithms particularly suited to near-term quantum computation. Two prototypical variational algorithms, quantum adiabatic optimization (QAO) and the quantum approximate optimization algorithm (QAOA), are studied for the difference in their control strategies. We show that on certain crafted problem instances, bang-bang control (QAOA) can be as much as exponentially faster than quasistatic control (QAO). Next, we demonstrate the performance of variational state preparation on an analog quantum simulator based on trapped ions. We show that using classical heuristics that exploit structure in the variational parameter landscape, one can find circuit parameters efficiently in system size as well as circuit depth. In the experiment, we approximate the ground state of a critical Ising model with long-ranged interactions on up to 40 spins. Finally, we study the performance of Local Tensor, a classical heuristic algorithm inspired by QAOA on benchmarking instances of the MaxCut problem, and suggest physically motivated choices for the algorithm hyperparameters that are found to perform well empirically. We also show that our implementation of Local Tensor mimics imaginary-time quantum evolution under the problem Hamiltonian.
590 $a School code: 0117.
650 4 $a Quantum physics. $3 726746
650 4 $a Physics. $3 516296
650 4 $a Computer engineering. $3 621879
650 4 $a Computer science. $3 523869
653 $a Architectures
653 $a NISQ
653 $a Optimization
653 $a Quantum computation
653 $a Variational algorithms
653 $a Noisy, Intermediate-Scale Quantum
690 $a 0599
690 $a 0605
690 $a 0984
690 $a 0464
710 2 $a University of Maryland, College Park. $b Physics. $3 1266199
773 0 $t Dissertations Abstracts International $g 83-04B.
790 $a 0117
791 $a Ph.D.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28712775