QCIS-FF: Quantum Computing & Information Science Faculty Fellow at Tufts University
QCIS-FF: Quantum Computing & Information Science Faculty Fellow at Tufts University
批准号:
2013062
负责人:
Jeffrey Foster
金额:
$75.0万
依托单位:
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
项目状态:
已结题
起止时间:
2021-09-01 至 2024-08-31
中文摘要
在现实世界的问题上,目前的量子计算机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至关重要的问题。问题的哪些特征使其成为量子计算机的好目标,以及量子计算机使用哪些资源来更快地解决问题,这些都是难以理解的问题。这个项目将使塔夫茨大学聘请一位从事量子信息研究的理论计算机科学家成为可能。此次招聘将有助于量子信息科学的研究,并培养下一代量子信息科学家,他们将继续实现国家量子倡议(NQI)法案的目标。塔夫茨大学计算机科学系的新员工将研究量子算法以及现有、近期和未来量子计算机的使用问题。对量子算法、不同的量子复杂性类和其他理论计算机科学主题的研究是量子信息的核心。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都很有名。当前感兴趣的问题跨越了未来量子计算机的范围,从近期到遥远的未来。其中包括寻找能够在近期拥有50-100个量子比特但缺乏纠错的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。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
DOI:
10.22331/q-2022-12-19-877
发表时间:
2022-07
期刊:
Quantum
影响因子:
6.4
作者:
[Ulysse Chabaud;A. Deshpande;S. Mehraban]
通讯作者:
Ulysse Chabaud;A. Deshpande;S. Mehraban
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