CDS&E: Two-electron Reduced Density Matrices in Quantum Chemistry and Physics
CDS
基本信息
- 批准号:2155082
- 负责人:
- 金额:$ 50万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
With this award, the Chemical Theory, Models and Computational Methods (CTMC) program in the Division of Chemistry is supporting Professor David A. Mazziotti of the University of Chicago to develop new methods for treating many-electron quantum systems to study problems in chemistry and materials. Many new molecules and materials that are critically important to improving society are so complex that they are difficult to study with conventional methods. Mazziotti and his research group will pursue novel quantum chemistry algorithms that exploit the pairwise nature of the electronic interactions in combination with recent advances in quantum computing, machine learning, and optimization to predict the energies and other properties of molecules and materials with increased efficiency. The work has the potential to be transformative in that it aims to enable applications to more complex chemical systems, opening new vistas for computational research in chemistry and materials. Mazziotti and his group will also drive educational and outreach activities including a quantum computing and machine learning curricula for chemistry, an interactive videoconference-based lecture series on quantum chemistry, and an online science journal for high school students. Accurate and yet efficient computation of molecules and materials with correlated electrons remains one of the outstanding problems in science and engineering. Catalyzed by recent discoveries in quantum computation, machine learning, and optimization theory, Mazziotti and his research group aim to improve predictive capabilities for correlated molecules and materials by exploring the combination of these recent advances with reduced density matrix (RDM) theory. They will develop RDM algorithms for general quantum systems with correlated electrons via new, emergent paradigms in quantum computing, machine learning, and/or optimization, going beyond recent classical algorithms based on approximate functionals or N-representability conditions. These novel formulations will use quantum computing, machine learning, and/or optimization to avoid the explicit classical construction and storage of the many-electron wave function, and therefore, they will raise new possibilities for treating strongly correlated systems that are beyond the reach of current approaches. The proposed work is timely: recently, quantum computers have been developed with significant improvements in their qubit-numbers and fidelity, and machine learning has been applied successfully to applications in image and speech recognition, natural language processing, autonomous driving, and chemistry. Mazziotti and his group will apply existing and proposed two-electron RDM methods to predict and optimize strongly correlated molecular systems and processes of importance in chemistry and physics.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.
有了这个奖项,化学系的化学理论,模型和计算方法(CTMC)计划正在支持教授大卫A。他与芝加哥大学的Mazziotti合作,开发处理多电子量子系统的新方法,以研究化学和材料问题。 许多对改善社会至关重要的新分子和材料非常复杂,难以用传统方法进行研究。 Mazziotti和他的研究小组将追求新的量子化学算法,该算法利用电子相互作用的成对性质,结合量子计算,机器学习和优化的最新进展,以更高的效率预测分子和材料的能量和其他性质。 这项工作具有变革性的潜力,因为它旨在使应用程序能够应用于更复杂的化学系统,为化学和材料的计算研究开辟新的前景。 Mazziotti和他的团队还将推动教育和推广活动,包括化学量子计算和机器学习课程,基于交互式视频会议的量子化学系列讲座,以及面向高中生的在线科学期刊。 对具有关联电子的分子和材料的精确而有效的计算仍然是科学和工程中的突出问题之一。在量子计算,机器学习和优化理论的最新发现的催化下,Mazziotti和他的研究小组旨在通过探索这些最新进展与约化密度矩阵(RDM)理论的结合来提高相关分子和材料的预测能力。 他们将通过量子计算,机器学习和/或优化中的新的新兴范例,为具有相关电子的一般量子系统开发RDM算法,超越基于近似泛函或N-可表示性条件的最近经典算法。这些新的公式将使用量子计算,机器学习和/或优化来避免多电子波函数的显式经典构造和存储,因此,它们将为处理超出当前方法范围的强相关系统提出新的可能性。 建议的工作是及时的:最近,量子计算机已经在其量子比特数和保真度方面得到了显著的改进,并且机器学习已经成功地应用于图像和语音识别、自然语言处理、自动驾驶和化学中的应用。 Mazziotti和他的团队将应用现有的和提出的双电子RDM方法来预测和优化化学和物理学中重要的强相关分子系统和过程。该奖项反映了NSF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。
项目成果
期刊论文数量(12)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Intrinsic glassy-metallic transport in an amorphous coordination polymer
- DOI:10.1038/s41586-022-05261-4
- 发表时间:2022-10-26
- 期刊:
- 影响因子:64.8
- 作者:Xie, Jiaze;Ewing, Simon;Anderson, John S.
- 通讯作者:Anderson, John S.
Quantum simulation of quantum phase transitions using the convex geometry of reduced density matrices
- DOI:10.1103/physreva.106.012434
- 发表时间:2022-07
- 期刊:
- 影响因子:2.9
- 作者:Samuel Warren;LeeAnn M. Sager-Smith;D. Mazziotti
- 通讯作者:Samuel Warren;LeeAnn M. Sager-Smith;D. Mazziotti
Potential for exciton condensation in a highly conductive amorphous polymer
高导电性无定形聚合物中激子凝聚的潜力
- DOI:10.1103/physrevmaterials.7.045001
- 发表时间:2023
- 期刊:
- 影响因子:3.4
- 作者:Schouten, Anna O.;Klevens, Jordan E.;Sager-Smith, LeeAnn M.;Xie, Jiaze;Anderson, John S.;Mazziotti, David A.
- 通讯作者:Mazziotti, David A.
Exciton-Condensate-Like Amplification of Energy Transport in Light Harvesting
光收集中能量传输的类激子凝聚放大
- DOI:10.1103/prxenergy.2.023002
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Schouten, Anna O.;Sager-Smith, LeeAnn M.;Mazziotti, David A.
- 通讯作者:Mazziotti, David A.
Reducing the Quantum Many-Electron Problem to Two Electrons with Machine Learning
通过机器学习将量子多电子问题简化为两个电子
- DOI:10.1021/jacs.2c07112
- 发表时间:2022
- 期刊:
- 影响因子:15
- 作者:Sager-Smith, LeeAnn M.;Mazziotti, David A.
- 通讯作者:Mazziotti, David A.
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David Mazziotti其他文献
David Mazziotti的其他文献
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{{ truncateString('David Mazziotti', 18)}}的其他基金
EAGER‐QAC‐QSA: Quantum Chemistry with Mean-field Cost from Semidefinite Programming on Quantum Computing Devices
EAGER – QAC – QSA:量子计算设备上半定编程的具有平均场成本的量子化学
- 批准号:
2035876 - 财政年份:2020
- 资助金额:
$ 50万 - 项目类别:
Standard Grant
CDS&E: Two-electron Reduced Density Matrices in Quantum Chemistry and Physics
CDS
- 批准号:
1565638 - 财政年份:2016
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
Two-electron Reduced Density Matrices in Quantum Chemistry and Physics
量子化学和物理中的二电子约化密度矩阵
- 批准号:
1152425 - 财政年份:2012
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
CAREER: Direct Determination of Two-electron Reduced Density Matrices for Many-electron Atoms and Molecules
职业:直接测定多电子原子和分子的二电子约化密度矩阵
- 批准号:
0644888 - 财政年份:2007
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
Positive Semidefinite Programming for Many-body Quantum Mechanics with Applications to Physical and Chemical Systems
多体量子力学正半定规划及其在物理和化学系统中的应用
- 批准号:
0315988 - 财政年份:2003
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
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