Matthew P. Harrigan, Tanuj Khattar, Charles Yuan, Anurudh Peduri, Noureldin Yosri, Fionn D. Malone, Ryan Babbush, Nicholas C. Rubin
{"title":"Expressing and Analyzing Quantum Algorithms with Qualtran","authors":"Matthew P. Harrigan, Tanuj Khattar, Charles Yuan, Anurudh Peduri, Noureldin Yosri, Fionn D. Malone, Ryan Babbush, Nicholas C. Rubin","doi":"arxiv-2409.04643","DOIUrl":null,"url":null,"abstract":"Quantum computing's transition from theory to reality has spurred the need\nfor novel software tools to manage the increasing complexity, sophistication,\ntoil, and fallibility of quantum algorithm development. We present Qualtran, an\nopen-source library for representing and analyzing quantum algorithms. Using\nappropriate abstractions and data structures, we can simulate and test\nalgorithms, automatically generate information-rich diagrams, and tabulate\nresource requirements. Qualtran offers a standard library of algorithmic\nbuilding blocks that are essential for modern cost-minimizing compilations. Its\ncapabilities are showcased through the re-analysis of key algorithms in\nHamiltonian simulation, chemistry, and cryptography. Architecture-independent\nresource counts output by Qualtran can be forwarded to our implementation of\ncost models to estimate physical costs like wall-clock time and number of\nphysical qubits assuming a surface-code architecture. Qualtran provides a\nfoundation for explicit constructions and reproducible analysis, fostering\ngreater collaboration within the growing quantum algorithm development\ncommunity.","PeriodicalId":501197,"journal":{"name":"arXiv - CS - Programming Languages","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Programming Languages","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Quantum computing's transition from theory to reality has spurred the need
for novel software tools to manage the increasing complexity, sophistication,
toil, and fallibility of quantum algorithm development. We present Qualtran, an
open-source library for representing and analyzing quantum algorithms. Using
appropriate abstractions and data structures, we can simulate and test
algorithms, automatically generate information-rich diagrams, and tabulate
resource requirements. Qualtran offers a standard library of algorithmic
building blocks that are essential for modern cost-minimizing compilations. Its
capabilities are showcased through the re-analysis of key algorithms in
Hamiltonian simulation, chemistry, and cryptography. Architecture-independent
resource counts output by Qualtran can be forwarded to our implementation of
cost models to estimate physical costs like wall-clock time and number of
physical qubits assuming a surface-code architecture. Qualtran provides a
foundation for explicit constructions and reproducible analysis, fostering
greater collaboration within the growing quantum algorithm development
community.