Modeling X-ray Transient Spectroscopies with Advanced Multireference Methods
Modeling X-ray Transient Spectroscopies with Advanced Multireference Methods
批准号:
2312105
负责人:
Francesco Evangelista
金额:
$50.17万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-01 至 2026-05-31
中文摘要
在化学系化学理论、模型和计算方法(CTMC)计划的支持下,埃默里大学的Francesco Evangelista正在开发计算方法来模拟高活性分子与X射线辐射的相互作用。新的实验技术使用X射线在极短的时间尺度上跟踪化学反应过程中电子和原子核的动力学。这些实验还可以揭示分子如何与环境相互作用。仅从X射线实验中很难提取反应的原子机制。量子力学计算在解释X射线实验中起着重要的作用。由于电子的相关运动带来的挑战,科学家们无法准确地对许多有趣的分子进行这些计算。Evangelista和他的研究小组正在开发方法,这些方法将能够模拟最先进的实验,这些实验可以用于跟踪复杂化学环境中的反应。这个项目将创建新的开源计算机代码,这些代码实现了Evangelista开发的理论,并且可以免费获得。Evangelista团队还计划让本科生参与夏季研究,作为团队的一部分,以帮助建立未来的STEM(科学、技术、工程和数学)劳动力。在这一奖项下,Francesco Evangelista和他的团队将开发方法来计算多体关联对波函数有重要贡献的区域中分子的核心激发态。该方法将使用驱动相似重整化群(DSRG)形式来考虑动力学关联效应,从而为多种电子态产生有效的哈密顿量。该项目寻求开发一种新的技术来瞄准特定的价激发和核激发的非绝热状态,并将应用这些方法来模拟跟踪键解离过程的最先进的实验。该小组还试图通过将GAS(一般激活空间)-DSRG方法与多参考量子嵌入方法相结合,将他们的计算扩展到吸附在半导体上的分子和固态缺陷量子比特。这些技术旨在解决计算瞬变物种的全部X射线吸收光谱的问题,因为它们的分子几何和电子态随着时间的推移而演变。所提出的方法将是通用的,因为它们将同时适用于基态和价激发的起始态。更广泛地说,这些发展预计将有助于多参考理论的进步,对光化学和化学反应的相关领域具有潜在影响。这些方法可能用于模拟与量子信息科学(QIS)相关的钻石缺陷,例如,在使用X射线光谱表征固态量子比特方面。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势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
With support from the Chemical Theory, Models and Computational Methods (CTMC) program in the Division of Chemistry, Francesco Evangelista of Emory University is developing computational approaches to simulate highly reactive molecules interacting with X-ray radiation. New experimental techniques use X-rays to track the dynamics of electrons and nuclei during chemical reactions at extremely short time scales. These experiments can also reveal how molecules interact with their environment. It is difficult to extract the atomistic mechanism of reactions from X-ray experiments alone. Quantum mechanical calculations play an important role in interpreting X-ray experiments. Scientists cannot accurately perform these calculations for many interesting molecules due to the challenges created by the correlated motion of electrons. Evangelista and his research group are developing methods that will enable simulations of state-of-the-art experiments that can be used to track reactions in complex chemical environments. This project will create new open-source computer codes that implement the theories developed by Evangelista and that are freely available. The Evangelista group also plans to engage undergraduates in summer research as part of the team to help build the future STEM (science, technology, engineering and mathematics) workforce.Under this award, Francesco Evangelista and his team will develop methods to compute core-excited states for molecules in regimes where many-body correlations contribute significantly to the wave function. The approach will employ the driven similarity renormalization group (DSRG) formalism to account for dynamical correlation effects to produce an effective Hamiltonian for a manifold of electronic states. The project seeks to develop a new technique to target specific valence- and core-excited diabatic states and will apply these methods to simulate state-of-the-art experiments that track bond-dissociation processes. The group also seeks to extend their computations to molecules adsorbed on semiconductors and solid-state defect qubits by combining the GAS (general activation space)-DSRG approach with multi-reference quantum embedding methods. These techniques are intended to address the problem of computing full X-ray absorption spectra for transient species as their molecular geometry and electronic state evolve over time. The proposed methods will be general in that they will apply to both ground and valence-excited starting states. More broadly, these developments are expected contribute to the advancement of multi-reference theories with potential impact on the related areas of photochemistry and chemical reactivity. These methods are potentially deployable for the simulation of diamond defects with relevance to quantum information science (QIS) as, for example, in the use of X-ray spectroscopy for the characterization of solid-state qubits.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.
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EAGER: QAC-QSA: Can classical machine learning beat variational quantum algorithms at their own game?
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批准号:2038019
-
项目类别:Standard Grant
-
资助金额:$29.28万
-
财政年份:2020
-
负责人:Francesco Evangelista
-
依托单位:
Modeling X-ray Transient Spectroscopy with Adaptive Wavefunction Methods
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批准号:1900532
-
项目类别:Standard Grant
-
资助金额:$43.14万
-
财政年份:2019
-
负责人:Francesco Evangelista
-
依托单位:
国内基金
海外基金
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