California Institute of Technology（加州理工学院）

Ansatz-free Hamiltonian learning with Heisenberg-limited scaling

Hong-Ye Hu, Muzhou Ma, Weiyuan Gong, Qi Ye, Yu Tong, Steven T. Flammia, Susanne F. Yelin

机构 * Department of Physics, Harvard University, Cambridge, MA 02138, USA（哈佛大学物理系） ； Institute for Quantum Information and Matter, California Institute of Technology, CA 91125, USA（加州理工学院量子信息与物质研究所） ； School of Engineering and Applied Sciences, Harvard University, Allston, Massachusetts 02134, USA（哈佛大学工程与应用科学学院） ； Center for Quantum Information, IIIS, Tsinghua University, Beijing, China（清华大学信息中心） ； Department of Mathematics, Duke University, Durham, NC 27708, USA（杜克大学数学系） ； Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA（杜克大学电气与计算机工程系） ； Duke Quantum Center, Duke University, Durham, NC 27701, USA（杜克大学量子中心） ； Department of Computer Science, Virginia Tech, Alexandria, VA 22314, USA（弗吉尼亚理工大学计算机科学系） ； Phasecraft Inc., Washington DC, USA（Phasecraft公司） 纠错

Comments Updated version with expanded explanations, added pseudocode, and new numerical demonstrations. 10 pages, 4 figures. HYH and MM contributed equally

Journal ref PRX Quantum 6, 040315 (2025)

Risk-Averse Total-Reward Reinforcement Learning

Xihong Su, Jia Lin Hau, Gersi Doko, Kishan Panaganti, Marek Petrik

机构 * Department of Computer Science University of New Hampshire（计算机科学系新罕布什尔大学） ； Department of Computing & Mathematical Sciences California Institute of Technology（计算与数学科学系加州理工学院） ； Tencent AI Lab（腾讯AI实验室） 纠错

Comments The paper has been accepted by the Thirty-Ninth Annual Conference on Neural Information Processing Systems(NeurIPS 2025)