Starts 19 Jun 2024
Ends 21 Jun 2024
Central European Time
Workshop on Classical and Quantum Machine Learning for Condensed Matter Physics | (smr 3948)
Online -
Online
To watch the Workshop in Live - Streaming:
Day 1 on YouTube CLICK HERE
Day 2 on YouTube CLICK HERE
Day 3 on YouTube CLICK HERE
An ICTP Online Meeting
Speakers:
Contributed talk: Applicants who want to give a contributed talk are asked to submit an abstract. Please use the ICTP templates that are available below for download.
Registration: There is no registration fee.
Day 1 on YouTube CLICK HERE
Day 2 on YouTube CLICK HERE
Day 3 on YouTube CLICK HERE
An ICTP Online Meeting
The workshop will be held for three days
from 10am to 3pm CEST for each day
from 10am to 3pm CEST for each day
This workshop aims to provide an overview of machine learning (ML) and quantum computing (QC) techniques, in particular, to solve condensed matter physics problems. The workshop will also give the participants a hands-on experience of some useful ML+QC packages.
In recent years, classical ML techniques have been applied to analyze vast datasets, uncover hidden patterns, and predict material properties with unprecedented accuracy. Concurrently, the advent of QC promises to revolutionize the field by harnessing the computational power of quantum computers to tackle complex quantum many-body problems.
In this workshop, we will listen to some presentations from leading researchers and young researchers who have been exploring classical ML, quantum ML, and other quantum-related research, which could be beneficial for the development of condensed matter physics. During the workshop, participants will also be equipped with hands-on sessions for learning cutting-edge tools of quantum ML.
Topics:
- Classical machine learning approaches for condensed matter physics, such as supervised and unsupervised learning, deep learning, and reinforcement learning
- Applications of classical machine learning in materials discovery, phase transitions, electronic structure prediction, and beyond
- Quantum computing and quantum machine learning algorithms, along with their potential to address fundamental challenges in physics and engineering, particularly in condensed matter physics, including simulating quantum many-body systems and solving optimization problems
- Hybrid classical-quantum computing techniques for enhancing computational efficiency and accuracy
- Challenges and limitations in applying machine learning techniques to physics problems
- Future prospects and directions for advancing the synergy between classical and quantum techniques, especially in condensed matter physics research
Speakers:
Khoirul ANWAR, Telkom University, Indonesia
Cica GUSTIANI, Sorbonne Université, France
Cica GUSTIANI, Sorbonne Université, France
Muhammad Yusrul HANNA, BRIN, Indonesia
Mingda LI, MIT, USA
Mingda LI, MIT, USA
Andriyan B. SUKSMONO, ITB, Indonesia
The accepted participants will be provided with the Zoom meeting link and
Discord community invitation through their emails by June 12, 2024.
Discord community invitation through their emails by June 12, 2024.
Contributed talk: Applicants who want to give a contributed talk are asked to submit an abstract. Please use the ICTP templates that are available below for download.
Registration: There is no registration fee.
**DEADLINE: 05/06/2024**
Organizers
Muhammad Aziz MAJIDI (UI, Indonesia), Ahmad Ridwan Tresna NUGRAHA (BRIN, Indonesia), Agustinus Agung NUGROHO (ITB, Indonesia), Edi SUPRAYOGA (BRIN, Indonesia), Sasfan Arman WELLA (BRIN, Indonesia), Local Organiser: Ali Hassanali (ICTP)
