主题：fast algorithms for fci excited states
时间：11月26日 13:00-14:30
地点：腾讯会议（会议号：794-932-223）
主持人：邵文婷 副教授
报告人简介：
李颖洲，复旦大学数学科学学院青年研究员。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，2017年至2020年在美国杜克大学数学系担任科研助理教授。设计核方法快速计算，分析cnn万有逼近，提出求解高频波方程的深度神经网络结构与学习算法；设计椭圆方程的算法，实现上万核集群高效并行；开发量子算法，在量子计算机上求解激发态问题。已在国际顶尖计算数学、应用学科杂志(acha, jctc, siopt, sisc, simax等等)发表论文40余篇。主持国家自然科学基金委面上项目、上海市基础研究特区交叉项目等。入选国家高层次海外青年人才计划、上海市高层次海外人才计划。
讲座简介：
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.