使用 Qualtran 表达和分析量子算法
Expressing and Analyzing Quantum Algorithms with Qualtran
AI总结：
本文介绍开源库 Qualtran，通过抽象、数据结构和标准构建模块支持量子算法的表示、模拟、图示生成与资源估算，并在多类关键算法上展示可复现分析能力。
摘要：
量子计算从理论走向现实的转变，催生了对新型软件工具的需求，以管理量子算法开发中日益增长的复杂性、精密性、繁重工作和易错性。我们提出 Qualtran，这是一个用于表示和分析量子算法的开源库。借助适当的抽象和数据结构，我们能够模拟和测试算法、自动生成信息丰富的图示，并将资源需求制成表格。Qualtran 提供了一个由算法构建模块组成的标准库，这些模块对于现代的成本最小化编译至关重要。其能力通过对 Hamiltonian 模拟、化学和密码学中关键算法的重新分析得到展示。Qualtran 输出的与架构无关的资源计数可转发给我们的成本模型实现，以在假设 surface-code 架构的情况下估计物理成本，例如挂钟时间和物理量子比特数量。Qualtran 为显式构造和可复现分析提供了基础，促进了不断壮大的量子算法开发社区内部更深入的协作。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
