Quantum Dissipative Dynamics with Machine Learning
Abstract
In this talk, I will present our work on Machine Learning based Quantum Dissipative Dynamics methods such as AIQD[1] and OSTL[2]. I will also talk about our recently released MLQD package (GitHub) and QDDSET-1 (GitHub) database. The talk will be followed by a tutorial demonstrating the applicability of our methods on our MLatom@XACS cloud computing platform.
We are pleased to announce the launch of Seminars on Machine Learning in Quantum Chemistry and Quantum Computing for Quantum Chemistry (SMLQC) that are flexible online lectures and tutorials for highlighting recent developments and providing hands-on experience on the title topics as well as networking opportunities. SMLQC sessions are organized to bridge Symposia on Machine Learning and Quantum Chemistry, the first one held in 2021 in Xiamen, China (online) and the second one to be held in 2023 in Uppsala, Sweden (hybrid). The real-time interaction is enabled via a dedicated Slack workspace which already has many researchers active in the title fields.
Machine Learning and Quantum Computing for Quantum Molecular Dynamics (MLQCDyn)
Sept. 5 – 9, 2022, CECAM-FR-MOSER
The Machine Learning and Quantum Computing for Quantum Molecular Dynamics [MLQCDyn]school aims at offering state-of-the-art training in quantum molecular dynamics (QMD), machine learning (ML), and quantum computing (QC) to early-stage scientists, including PhD and postdoctoral researchers coming mainly from the molecular dynamics community. The MLQCDyn school is meant to be part of a Thematic Program of the Pascal Institute of the University Paris-Saclay that will span a total of 4 weeks and will be dedicated to the discussion of the implications of machine learning and quantum computing in the field of quantum molecular dynamics (funding for the thematic program has already been approved). The MLQCDyn school will open the Thematic Program, and some of the participants in the school (lecturers and students) will also remain for one or more of the following weeks. Such an event will strengthen the collaboration between Pascal Institute and the CECAM.
Symposium on Machine Learning in Quantum Chemistry 2021 (SMLQC-2021) has been a huge success with many great talks and discussions, chats after talks, and poster sessions! This success has prompted us to continue and expand this kind of events on request and suggestions of many participants. We will have biweekly online talks on the topic of machine learning in quantum chemistry and biannual symposia. The next edition SMLQC-2023 will be held in Uppsala, Sweden.
We have had three days filled with exciting talks by inspiring speakers presenting their work on machine learning in quantum chemistry research. In addition, I am very thankful to the speakers for hanging around after their session was over and chatting with the attendees in the breakout rooms. I definitely enjoyed this informal part of the symposium as I could see and talk so many good friends of mine like in in-person conference, and, equally importantly, meet so many new people. This sentiment is shared by many participants and as a result we have got many requests and suggestions to continue with this kind of events.
Particularly impressive was enthusiastic engagement of Prof. Roland Lindh from Uppsala University, who really deserves a badge of honor for staying around for the whole events despite a 7-hour time-zone difference! His generous offer to host the next edition SMLQC-2023 in Uppsala is greatly appreciated. I will post updates here, on Facebook via group Machine learning in chemistry, and on Twitter. I hope to see you at SMLQC-2023 in person in ca. 24 months! We plan to hold SMLQC biannually in different regions of the world.
Screenshot from the closing of SMLQC-2021
You do not need to wait another two years though, and can also join our biweekly online talks on the topic of machine learning in quantum chemistry. The talks are planned to be recorded and openly posted online. I will post updates on this soon too.
Finally, I personally would like to thank all the co-organizers and helping hands, who worked very hard overtime at late night, in the early mornings and the weekends to make the event possible and enjoyable.
