Multiagent Consensus Equilibrium in Molecular Structure Determination
Multiagent Consensus Equilibrium in Molecular Structure Determination
复制标题
分子结构测定中的多主体一致性平衡
DOI：
10.1021/acs.jpca.0c07282
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Simpson, Garth J.
中科院分区：
文献类型：
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作者：
Ulcickas, James R.W.;Cao, Ziyi;Rong, Jiayue;Bouman, Charles A.;Slipchenko, Lyudmila V.;Buzzard, Gregery T.;Simpson, Garth J.
多智能体共识平衡（MACE）的整合实验观测的分子结构确定的约束和系统的合并多个计算架构。MACE建立在同时确定多个实验和/或计算代理之间的平衡点的基础上;返回的状态描述（例如，分子结构的原子坐标）表示每个流形的交叉点，并且不等同于每个试剂的平均最佳状态。直接从微波光谱测量确定的惯性矩用于说明MACE评估合并实验和量子化学建模的机制。报告的MACE结果将每个从头算试剂的联合收割机梯度下降优化与基于预测的惯性张量与实验测量的惯性矩的均方根偏差预测化学结构的试剂相结合。成功地实现了几个小分子的模型融合，以及较大的分子丙酮缩酮。融合模型的惯性矩，欠定预测的结构，低成本的计算方法产生的结构确定性能相比，标准的计算方法，如MP2/cc-pVTZ和更大的协议与实验观测。
Multiagent consensus equilibrium (MACE) is demonstrated for the integration of experimental observables as constraints in molecular structure determination and for the systematic merging of multiple computational architectures. MACE is founded on simultaneously determining the equilibrium point between multiple experimental and/or computational agents; the returned state description (e.g., atomic coordinates for molecular structure) represents the intersection of each manifold and is not equivalent to the average optimum state for each agent. The moment of inertia, determined directly from microwave spectroscopy measurements, serves to illustrate the mechanism through which MACE evaluations merge experimental and quantum chemical modeling. MACE results reported combine gradient descent optimization of each ab initio agent with an agent that predicts the chemical structure based on root-mean-square deviation of the predicted inertia tensor with experimentally measured moments of inertia. Successful model fusion for several small molecules was achieved as well as the larger molecule solketal. Fusing a model of moment of inertia, an underdetermined predictor of structure, with low cost computational methods yielded structure determination performance comparable to standard computational methods such as MP2/cc-pVTZ and greater agreement with experimental observables.