QCIS-FF: Quantum Computing & Information Science Faculty Fellow at Tufts University

QCIS-FF：量子计算

基本信息

批准号：
2013062
负责人：
Jeffrey Foster
金额：
$ 75万
依托单位：
Tufts University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2013062&HistoricalAwards=false
关键词：
QCIS FF Quantum Computing &amp

项目摘要

Current quantum computers cannot outperform conventional supercomputers on real-world problems. Future quantum computers will be able to solve problems important to materials science and chemistry, to code-breaking and to machine learning. Which features of a problem make it a good target for a quantum computer, and what resources quantum computers use to solve problems faster, are difficult and poorly understood questions. This project will make possible the hire of a theoretical computer scientist working in quantum information at Tufts University. This hire will contribute to research in quantum information science and to training the next generation of quantum information scientists who will go on to achieve the goals of the National Quantum Initiative (NQI) act. The new Faculty hire in Computer Science at Tufts University will work on questions in quantum algorithms and the use of existing, near-term and far-future quantum computers. The search for quantum algorithms, distinct quantum complexity classes, and other theoretical computer science topics are central to quantum information. Currently algorithms are known in the areas of number theory, computational algebra, quantum simulation from quantum chemistry to high energy physics, quantum optimization and machine learning. Questions of current interest span the range of future quantum computers from near term to far future. They include the search for algorithms that can provide a quantum advantage on near-term machines with 50-100 qubits but which lack error correction, the so-called Noisy Intermediate Scale Quantum (NISQ) devices. They also include the search for completely new quantum algorithms for large-scale quantum computers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

当前的量子计算机在解决现实问题时无法超越传统的超级计算机。未来的量子计算机将能够解决对材料科学和化学、密码破译和机器学习很重要的问题。问题的哪些特征使其成为量子计算机的良好目标，以及量子计算机使用哪些资源来更快地解决问题，都是困难且知之甚少的问题。该项目将使塔夫茨大学聘用一名从事量子信息工作的理论计算机科学家成为可能。此次聘用将有助于量子信息科学研究，并培训下一代量子信息科学家，他们将继续实现国家量子计划（NQI）法案的目标。塔夫茨大学计算机科学系新聘的教师将致力于研究量子算法以及现有、近期和远期量子计算机的使用问题。对量子算法、不同量子复杂性类别和其他理论计算机科学主题的搜索是量子信息的核心。目前，算法在数论、计算代数、从量子化学到高能物理的量子模拟、量子优化和机器学习等领域广为人知。当前感兴趣的问题涵盖了从近期到遥远未来的未来量子计算机的范围。其中包括寻找能够在具有 50-100 个量子位但缺乏纠错的近期机器上提供量子优势的算法，即所谓的噪声中尺度量子 (NISQ) 设备。它们还包括为大规模量子计算机寻找全新的量子算法。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。