RosneT：一个面向核外量子计算仿真的块张量代数库
RosneT: A Block Tensor Algebra Library for Out-of-Core Quantum Computing Simulation
摘要：
随着更强大的量子计算机的出现，对更大的量子模拟的需求已经增加。随着资源量随着目标系统的规模呈指数级增长，张量网络作为一个最佳框架出现，我们用张量因子分解表示量子态。随着张量网络的范围增加，需要HPC工具进行操作的中间张量的大小也会增加。中型电路的模拟不能适合本地存储器，张量的分布式收缩的解决方案是稀缺的。在这项工作中，我们提出了RosnetT，一个分布式的，核心外块张量代数库。我们使用PyCOMPSs编程模型将张量操作转换为COMPSs运行时处理的任务集合，目标是在现有和即将推出的Exascale超级计算机中执行。我们报告的结果验证我们的方法显示良好的可扩展性，在高达53量子位的量子线路的模拟。
英文摘要：
With the advent of more powerful Quantum Computers, the need for larger Quantum Simulations has boosted. As the amount of resources grows exponentially with size of the target system Tensor Networks emerge as an optimal framework with which we represent Quantum States in tensor factorizations. As the extent of a tensor network increases, so does the size of intermediate tensors requiring HPC tools for their manipulation. Simulations of medium-sized circuits cannot fit on local memory, and solutions for distributed contraction of tensors are scarce. In this work we present RosneT, a library for distributed, out-of-core block tensor algebra. We use the PyCOMPSs programming model to transform tensor operations into a collection of tasks handled by the COMPSs runtime, targeting executions in existing and upcoming Exascale supercomputers. We report results validating our approach showing good scalability in simulations of Quantum circuits of up to 53 qubits.
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。
