Workshop on Provable Quantum Advantage – Present and Future

可证明量子优势研讨会 — 现在与未来

基本信息

  • 批准号:
    2138059
  • 负责人:
  • 金额:
    $ 6.9万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-10-01 至 2022-09-30
  • 项目状态:
    已结题

项目摘要

For nearly three decades quantum computation has been the only known model of feasible computation capable of obtaining exponential speedups over any efficient classical computer [11,29,30]. Despite this great promise, the theoretical quantum speedups developed in the early 1990’s are very difficult to implement as they require large-scale, nearly perfect quantum experiments. While this goal may still be quite far off, the push to develop quantum computers has already yielded incredible experimental progress in high-precision control over individual quantum systems across many different quantum architectures (see e.g.,[7,10,12,34,35]). Due to these experimental developments, we have now arrived in the so-called Noisy Intermediate Scale Quantum (“NISQ”) era, in which quantum systems of 50-70 qubits are currently being built in experimental laboratories around the world. For the first time, these experiments are approaching the complexity boundary after which it is unclear how to simulate them classically in a reasonable amount of time. This indicates that these systems may have the potential to achieve quantum speedups. However, these experiments have important limitations, such as uncorrected noise, which restrict their capabilities. The first major step for the NISQ era is to implement an experimental demonstration of a computational speedup relative to any classical computer, a goal known as “quantum supremacy” [27]. This goal is a watershed moment in the history of computation and a necessary milestone on the path toward developing fully scalable quantum computers. Moreover the goal appears to be rapidly approaching, and we have already seen the first claimed demonstrations of quantum supremacy [7, 36]. These experiments have attracted much attention but there are still many aspects of the claims that not well understood. While there is some rigorous evidence that such near-term quantum experiments are able to attain exponential speedups over classical computation (see, e.g., [3,4,14]) these theoretical results do not take into account many practical facets of these experiments such as uncorrected noise. Indeed, these gaps between theory and experiment have resulted in partial rebuttals of these initial quantum supremacy claims (see e.g., [8, 22, 25, 26]). Consequently, there is a great need to rigorously understand the capabilities of these near-term quantum experiments. To do this, we propose holding a workshop focusing on the prospects for achieving large computational speedups on near-term quantum experiments. Our goal will be not only be to better understand the present generation of quantum experiments, but also to understand the capabilities of tomorrow’s quantum experiments, with a view toward the ultimate goal of implementing a quantum speedup for solving a practically useful problem. Intellectual Merit:The proposed workshop will lead to a complete understanding of the computational power of near-term quantum experiments. The focus will be on three objectives which will together help understand the power of existing quantum computers, as well as pave the road toward understanding the power of future quantum devices capable of attaining dramatic speedups for useful computational problems. In addition to being critical for the current near-term quantum era, these aims will foster interdisciplinary collaborations and lead to exciting new insights at the intersection of computer science, engineering, and experimental physics. Broader Impacts:This workshop will contribute to sustaining and enhancing the recent worldwide explosion of interest in quantum computation. The program will feature invited speakers and participants from academia, government and industry to disseminate the most recent ideas on quantum computation to a wide variety of scientific communities.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.
近三十年来,量子计算一直是唯一已知的可行计算模型,能够在任何有效的经典计算机上获得指数加速[11,29,30]。尽管如此,20世纪90年代早期开发的理论量子加速器很难实现,因为它们需要大规模,近乎完美的量子实验。虽然这一目标可能仍然相当遥远,但开发量子计算机的努力已经在许多不同量子架构上对单个量子系统进行高精度控制方面取得了令人难以置信的实验进展(例如,[7,10,12,34,35])。由于这些实验的发展,我们现在已经进入了所谓的噪声中间尺度量子(“NISQ”)时代,其中50-70量子比特的量子系统目前正在世界各地的实验室中构建。这些实验第一次接近复杂性边界,之后还不清楚如何在合理的时间内经典地模拟它们。这表明这些系统可能具有实现量子加速的潜力。然而,这些实验具有重要的局限性,例如未校正的噪声,这限制了它们的能力。NISQ时代的第一个主要步骤是实现相对于任何经典计算机的计算加速的实验演示,这一目标被称为“量子霸权”[27]。这一目标是计算历史上的分水岭,也是开发完全可扩展量子计算机道路上的一个必要里程碑。此外,这个目标似乎正在迅速接近,我们已经看到了量子霸权的第一次宣称的演示[7,36]。这些实验引起了人们的广泛关注,但这些主张的许多方面仍然没有得到很好的理解。虽然有一些严格的证据表明,这种近期量子实验能够在经典计算上实现指数加速(参见,例如,[3,4,14])这些理论结果没有考虑这些实验的许多实际方面,例如未校正的噪声。事实上,理论和实验之间的这些差距已经导致了对这些最初的量子霸权主张的部分反驳(参见例如,[8、22、25、26])。因此,非常需要严格理解这些近期量子实验的能力。为此,我们建议举办一个研讨会,重点关注在近期量子实验中实现大规模计算加速的前景。我们的目标不仅是更好地理解当前这一代量子实验,而且还要理解未来量子实验的能力,最终目标是实现量子加速来解决实际有用的问题。智力优势:拟议的研讨会将导致对近期量子实验计算能力的全面理解。重点将放在三个目标上,这三个目标将共同帮助理解现有量子计算机的能力,并为理解未来量子设备的能力铺平道路,这些量子设备能够为有用的计算问题实现显著的加速。除了对当前近期的量子时代至关重要外,这些目标还将促进跨学科合作,并在计算机科学、工程和实验物理的交叉点上产生令人兴奋的新见解。更广泛的影响:本次研讨会将有助于维持和加强最近全球对量子计算的兴趣。该计划将邀请来自学术界、政府和工业界的演讲者和参与者,向广泛的科学界传播量子计算的最新想法。该奖项反映了NSF的法定使命,并通过使用基金会的知识产权进行评估,被认为值得支持。优点和更广泛的影响审查标准。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

William Fefferman其他文献

William Fefferman的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('William Fefferman', 18)}}的其他基金

CAREER: Near-term quantum computing: achieving quantum advantage, and next steps
职业:近期量子计算:实现量子优势以及后续步骤
  • 批准号:
    2044923
  • 财政年份:
    2020
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Continuing Grant

相似海外基金

EAGER: Building a Provable Differentially Private Real-time Data-blind ML Algorithm: A case study on Enhancing STEM Student Engagement in Online Learning
EAGER:构建可证明的差分隐私实时数据盲机器学习算法:关于增强 STEM 学生在线学习参与度的案例研究
  • 批准号:
    2329919
  • 财政年份:
    2023
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Standard Grant
Provable, Explainable, Efficient, Robust Deep Neural Network for Large-scale Multimedia Retrieval
用于大规模多媒体检索的可证明、可解释、高效、鲁棒的深度神经网络
  • 批准号:
    22KF0369
  • 财政年份:
    2023
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
IMR: MM-1B: Longitudinal End-device based Performance Measurement of Cellular Networks with Provable Privacy
IMR:MM-1B:具有可证明隐私的蜂窝网络基于纵向终端设备的性能测量
  • 批准号:
    2319277
  • 财政年份:
    2023
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Broad-Spectrum Facial Image Protection with Provable Privacy Guarantees
合作研究:SaTC:核心:中:具有可证明隐私保证的广谱面部图像保护
  • 批准号:
    2301014
  • 财政年份:
    2022
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Standard Grant
CAREER: Federated Learning: Statistical Optimality and Provable Security
职业:联邦学习:统计最优性和可证明的安全性
  • 批准号:
    2144593
  • 财政年份:
    2022
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Continuing Grant
Private Data Exploration with Provable Guarantees
具有可证明保证的私人数据探索
  • 批准号:
    RGPIN-2019-04770
  • 财政年份:
    2022
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Discovery Grants Program - Individual
Towards Provable Security of Real-world Servers: Where Online Learning Meets Server Retrofitting
实现现实服务器的可证明安全性:在线学习与服务器改造的结合
  • 批准号:
    2140175
  • 财政年份:
    2022
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Standard Grant
CAREER: Provable Patching of Deep Neural Networks
职业:可证明的深度神经网络修补
  • 批准号:
    2048123
  • 财政年份:
    2021
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Broad-Spectrum Facial Image Protection with Provable Privacy Guarantees
合作研究:SaTC:核心:中:具有可证明隐私保证的广谱面部图像保护
  • 批准号:
    2114141
  • 财政年份:
    2021
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Standard Grant
CRII: AF: Optimization and sampling algorithms with provable generalization and runtime guarantees, with applications to deep learning
CRII:AF:具有可证明的泛化性和运行时保证的优化和采样算法,以及深度学习的应用
  • 批准号:
    2104528
  • 财政年份:
    2021
  • 资助金额:
    $ 6.9万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了