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Stochastic Quantum Algorithms for Quantum Simulation
Stochastic Quantum Algorithms for Quantum Simulation  / Joseph Henry Peetz
Stochastic Quantum Algorithms for Quantum Simulation

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20260311091520.5
ISBN  
9798315793137
DDC  
530.12
저자명  
Peetz, Joseph Henry
서명/저자  
Stochastic Quantum Algorithms for Quantum Simulation / Joseph Henry Peetz
발행사항  
[Sl] : University of California, Los Angeles, 2025
형태사항  
1 electronic resource (121 pages)
주기사항  
Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
주기사항  
Advisors: Narang, Prineha; Leibrandt, David R. Committee members: Palsberg, Jens; Campbell, Wesley C.
학위논문주기  
- Ph.D. : University of California, Los Angeles, 2025.
초록/해제  
요약Simulating physical systems on quantum devices is one of the most promising applications of quantum technology. This dissertation introduces several quantum algorithms aimed at accelerating the realization of useful simulations on quantum computers. An overall theme is the use of classical randomness as a resource in quantum algorithm design. This perspective enables the decomposition of complex, coherent evolutions into simple, independent components. Below, we outline the structure of the dissertation and briefly summarize the most significant contributions. System-environment interactions play an important role in the dynamics of many quantum systems, giving rise to phenomena such as dissipation, decoherence, and relaxation. Current quantum approaches to simulating these effects are practically challenging because they typically require many ancilla qubits and extensive controlled sequences. In Chapter 1, we introduce a hybrid quantum-classical approach for simulating a class of open system dynamics called random-unitary channels. These channels naturally decompose into a convex combination of unitary evolutions, which can be efficiently sampled and run as independent, ancilla-free circuits. We implement simulations of open quantum systems up to dozens of qubits and with large channel ranks on IBM hardware.In Chapter 2, we extend this stochastic approach to general quantum channels, which we simulate using ensembles of low-depth, single-ancilla circuits. We demonstrate the efficiency of this method by preparing damped, many-qubit GHZ states on IBM hardware. The technique further inspires two Hamiltonian simulation algorithms with asymptotic independence of the spectral precision, reducing resource requirements by several orders of magnitude for a benchmark system.In Chapter 3, we introduce stochastic Zassenhaus expansions (SZEs), a class of ancilla-free quantum algorithms for Hamiltonian simulation. These algorithms map nested Zassenhaus formulas onto quantum gates and then employ randomized sampling to minimize circuit depths. Unlike Suzuki-Trotter product formulas, which grow exponentially long with approximation order, the nested commutator structures of SZEs enable high-order formulas for many systems of interest. For a 10-qubit transverse-field Ising model, we construct an 11th-order SZE with 42x fewer CNOTs than the standard 10th-order product formula. Further, we empirically demonstrate regimes where SZEs reduce simulation errors by many orders of magnitude.In Chapter 4, we propose a dissipative algorithm to prepare the Gibbs state of commuting Hamiltonians, with extensions to general systems. The algorithm prepares the Gibbs state of a spanning tree subgraph of a Hamiltonian in linear time. It then probabilistically implements the remaining interactions as perturbations to this tree. The circuit depth scales linearly in the total number of interactions, making it amenable to near-term applications. For low temperatures, the runtime scales exponentially with the frustration of the ground state, enabling the efficient simulation of a broad class of low-frustration systems. In particular, this gives a linear-time quantum algorithm for finding the ground state of commuting, frustration-free Hamiltonians.
언어주기  
English
일반주제명  
Physics
일반주제명  
Quantum physics
일반주제명  
Theoretical physics
일반주제명  
Computational physics
키워드  
Gibbs state preparation
키워드  
Ground state preparation
키워드  
Hamiltonian simulation
키워드  
Open quantum systems
키워드  
Quantum algorithms
키워드  
Quantum information
기타저자  
University of California, Los Angeles Physics 0666
기본자료저록  
Dissertations Abstracts International. 86-12B.
전자적 위치 및 접속  
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■24510▼aStochastic  Quantum  Algorithms  for  Quantum  Simulation  ▼cJoseph  Henry  Peetz
■260    ▼a[Sl]▼bUniversity  of  California,  Los  Angeles▼c2025
■264  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2025
■300    ▼a1  electronic  resource  (121  pages)
■336    ▼atext▼btxt▼2rdacontent
■337    ▼acomputer▼bc▼2rdamedia
■338    ▼aonline  resource▼bcr▼2rdacarrier
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-12,  Section:  B.
■500    ▼aAdvisors:  Narang,  Prineha;  Leibrandt,  David  R.    Committee  members:  Palsberg,  Jens;  Campbell,  Wesley  C.
■5021  ▼bPh.D.▼cUniversity  of  California,  Los  Angeles▼d2025.
■520    ▼aSimulating  physical  systems  on  quantum  devices  is  one  of  the  most  promising  applications  of  quantum  technology.  This  dissertation  introduces  several  quantum  algorithms  aimed  at  accelerating  the  realization  of  useful  simulations  on  quantum  computers.  An  overall  theme  is  the  use  of  classical  randomness  as  a  resource  in  quantum  algorithm  design.  This  perspective  enables  the  decomposition  of  complex,  coherent  evolutions  into  simple,  independent  components.  Below,  we  outline  the  structure  of  the  dissertation  and  briefly  summarize  the  most  significant  contributions.  System-environment  interactions  play  an  important  role  in  the  dynamics  of  many  quantum  systems,  giving  rise  to  phenomena  such  as  dissipation,  decoherence,  and  relaxation.  Current  quantum  approaches  to  simulating  these  effects  are  practically  challenging  because  they  typically  require  many  ancilla  qubits  and  extensive  controlled  sequences.  In  Chapter  1,  we  introduce  a  hybrid  quantum-classical  approach  for  simulating  a  class  of  open  system  dynamics  called  random-unitary  channels.  These  channels  naturally  decompose  into  a  convex  combination  of  unitary  evolutions,  which  can  be  efficiently  sampled  and  run  as  independent,  ancilla-free  circuits.  We  implement  simulations  of  open  quantum  systems  up  to  dozens  of  qubits  and  with  large  channel  ranks  on  IBM  hardware.In  Chapter  2,  we  extend  this  stochastic  approach  to  general  quantum  channels,  which  we  simulate  using  ensembles  of  low-depth,  single-ancilla  circuits.  We  demonstrate  the  efficiency  of  this  method  by  preparing  damped,  many-qubit  GHZ  states  on  IBM  hardware.  The  technique  further  inspires  two  Hamiltonian  simulation  algorithms  with  asymptotic  independence  of  the  spectral  precision,  reducing  resource  requirements  by  several  orders  of  magnitude  for  a  benchmark  system.In  Chapter  3,  we  introduce  stochastic  Zassenhaus  expansions  (SZEs),  a  class  of  ancilla-free  quantum  algorithms  for  Hamiltonian  simulation.  These  algorithms  map  nested  Zassenhaus  formulas  onto  quantum  gates  and  then  employ  randomized  sampling  to  minimize  circuit  depths.  Unlike  Suzuki-Trotter  product  formulas,  which  grow  exponentially  long  with  approximation  order,  the  nested  commutator  structures  of  SZEs  enable  high-order  formulas  for  many  systems  of  interest.  For  a  10-qubit  transverse-field  Ising  model,  we  construct  an  11th-order  SZE  with  42x  fewer  CNOTs  than  the  standard  10th-order  product  formula.  Further,  we  empirically  demonstrate  regimes  where  SZEs  reduce  simulation  errors  by  many  orders  of  magnitude.In  Chapter  4,  we  propose  a  dissipative  algorithm  to  prepare  the  Gibbs  state  of  commuting  Hamiltonians,  with  extensions  to  general  systems.  The  algorithm  prepares  the  Gibbs  state  of  a  spanning  tree  subgraph  of  a  Hamiltonian  in  linear  time.  It  then  probabilistically  implements  the  remaining  interactions  as  perturbations  to  this  tree.  The  circuit  depth  scales  linearly  in  the  total  number  of  interactions,  making  it  amenable  to  near-term  applications.  For  low  temperatures,  the  runtime  scales  exponentially  with  the  frustration  of  the  ground  state,  enabling  the  efficient  simulation  of  a  broad  class  of  low-frustration  systems.  In  particular,  this  gives  a  linear-time  quantum  algorithm  for  finding  the  ground  state  of  commuting,  frustration-free  Hamiltonians.
■546    ▼aEnglish
■590    ▼aSchool  code:  0031
■650  4▼aPhysics
■650  4▼aQuantum  physics
■650  4▼aTheoretical  physics
■650  4▼aComputational  physics
■653    ▼aGibbs  state  preparation
■653    ▼aGround  state  preparation
■653    ▼aHamiltonian  simulation
■653    ▼aOpen  quantum  systems
■653    ▼aQuantum  algorithms
■653    ▼aQuantum  information
■7102  ▼aUniversity  of  California,  Los  Angeles▼bPhysics  0666.▼edegree  granting  institution.
■7201  ▼aNarang,  Prineha▼edegree  supervisor.
■7201  ▼aLeibrandt,  David  R.▼edegree  supervisor.
■7730  ▼tDissertations  Abstracts  International▼g86-12B.
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357979▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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