利用资源估计进行量子计算应用开发
Utilizing Resource Estimation for the Development of Quantum Computing Applications
AI总结：
针对当前量子计算硬件有限、用户仅能测试玩具规模实例的问题，提出在现有工作流中加入资源估计步骤，支持用户提前评估现实规模量子应用的需求与优化方向。
摘要：
近年来，量子计算在软件与硬件领域均取得了长足进展。但要释放量子计算机解决经典计算机无法高效求解问题的能力，规模化量子计算必不可少。遗憾的是，量子模拟器受限于其指数级复杂度，同时当前可用的量子计算硬件仍相当有限（尽管发展路线图给出了颇具吸引力的前景）。因此，为评估量子计算应用，终端用户仍常受限于玩具规模的问题实例（且这类实例通常未考虑纠错），这严重阻碍了现实世界量子计算应用的开发与评估。\n本研究展示了如何利用资源估计（Resource Estimation）改善这一现状。我们提出可在现有依赖模拟和/或执行的工作流中补充估计步骤，使终端用户能够：（1）当下即可考量现实世界规模的问题实例（同时纳入纠错方案及相应所需的硬件资源）；（2）开始在整个设计空间内探索这类实例的潜在优化方向；（3）结合硬件发展趋势假设，得出更具依据、更合理的设计空间参数。总体而言，即便执行对应任务的硬件尚未问世，该方法已能让终端用户当下就验证未来量子计算应用的潜在价值。
英文摘要：
Quantum computing has made considerable progress in recent years in both software and hardware. But to unlock the power of quantum computers in solving problems that cannot be efficiently solved classically, quantum computing at scale is necessary. Unfortunately, quantum simulators suffer from their exponential complexity and, at the same time, the currently available quantum computing hardware is still rather limited (even if roadmaps make intriguing promises). Hence, in order to evaluate quantum computing applications, end-users are still frequently restricted to toy-size problem instances (which additionally often do not take error correction into account). This substantially hinders the development and assessment of real-world quantum computing applications. In this work, we demonstrate how to utilize Resource Estimation to improve this situation. We show how the current workflow (relying on simulation and/or execution) can be complemented with an estimation step, allowing that end-users (1) actually can consider real-world problem instances already today (also considering error correction schemes and correspondingly required hardware resources), (2) can start exploring possible optimizations of those instances across the entire design space, and (3) can incorporate hypotheses of hardware development trends to derive more informed and, thus, better design space parameters. Overall, this enables end-users already today to check out the promises of possible future quantum computing applications, even if the corresponding hardware to execute them is not available yet.
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