Quantum Computing

艾米博士的研究旨在了解并最终获得量子计算机在现实世界中的计算能力和应用。量子计算机是根据量子力学的物理定律运行的计算机。在理论层面上，量子计算有望以比最著名的经典方法更快的速度解决某些问题，其应用范围从打破传统密码学到模拟和发现新材料、药物和应对气候变化的过程。一个典型的第一个现实应用是模拟氮酶，一种参与肥料生产所需的固氮过程的酶，即使是现代超级计算机也无法模拟。氮和碳固定技术的进步将对我们应对气候变化的能力产生深远影响——仅氮固定就占全球二氧化碳排放总量的3%，占全球能源消耗的1%。在实践中，量子计算涉及到操作它们和保持系统处于无错误状态所必需的高度开销。如果不仔细计算和减少量子编译过程中涉及的开销，这些开销可能会减少或潜在地消除量子计算的优势。Amy的研究重点是编程、编译技术的开发，并最终减少量子程序的开销。在短期内，艾米博士的研究将使科学家能够对现有的量子设备进行实验、测试和验证，并评估未来量子设备的计算优势。从长远来看，现在学到的经验教训和开发的工具将使大规模通用量子计算机的编程和操作成为可能。

Dr. Amy's research aims to understand and ultimately access the real-world computational capabilities and applications of quantum computers.Quantum computers are computers which operate according to the physical laws of quantum mechanics. On a theoretical level, quantum computation promises to solve certain problems exponentially faster than the best known classical methods, with applications from breaking conventional cryptography to the simulation and discovery of new materials, drugs, and processes for fighting climate change. A canonical first real-world application is the simulation of nitrogenase, an enzyme involved in the process of nitrogen fixation needed for fertilizer production and which has resisted simulation even with modern super-computers. Advances in nitrogen and carbon fixation would have deep impacts on our ability to fight climate change --- nitrogen fixation alone accounts for up to 3% of the total CO2 emissions and 1% of the energy used worldwide.In practice, quantum computation involves a high degree of overhead necessary to operate them and maintain the system in an error-free state. Without careful accounting and reduction of the overheads involved through the process of quantum compilation, these overheads can diminish or potentially erase quantum computational advantages.Dr. Amy's research focuses on the development of techniques for programming, compiling, and ultimately reducing the overheads of quantum programs. In the short term, Dr. Amy's research will allow scientists to experiment with, test and validate currently available quantum devices, as well as assess the computational advantages of future ones. In the long term, the lessons learned and tools developed now will enable the programming and operation of large-scale, universal quantum computers.