Fast Algorithms for FCI excited states

发布时间:2023年11月08日 作者:潘克家   阅读次数:[]

报告题目:Fast Algorithms for FCI excited states

报告人:李颖洲研究员 复旦大学



摘要:An efficient excited state method, named xCDFCI, in the configuration interaction framework, is proposed. xCDFCI extends the unconstrained nonconvex optimization problem in CDFCI to a multicolumn version, for low-lying excited states computation. The optimization problem is addressed via a tailored coordinate descent method. In each iteration, a determinant is selected based on an approximated gradient, and coefficients of all states associated with the selected determinant are updated. A deterministic compression is applied to limit memory usage. We test xCDFCI applied to H2O and N2 molecules under the cc-pVDZ basis set. For both systems, five low-lying excited states in the same symmetry sector are calculated together with the ground state. xCDFCI also produces accurate binding curves of carbon dimer in the cc-pVDZ basis with 10−2 mHa accuracy, where the ground state and four excited states in the same symmetry sector are benchmarked.

李颖洲,复旦大学数学科学学院青年研究员,入选国家级青年人才计划。2012年于复旦大学取得学士学位,2017年于美国斯坦福大学取得计算数学博士学位,之后2017年至2020年在美国杜克大学数学系担任科研助理教授。其科研领域包括:快速算法设计、高性能计算与并行计算、量子计算、机器学习等。多篇论文发表在ACHA,SISC,SIMAX,JCP等计算数学权威期刊和JCTC,Nano Lett.等应用领域权威期刊上。

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