Quantum Computing for Natural Sciences: Technology and Applications

Quantum Computing for Natural Sciences: Technology and Applications
Date: Sun 17 Sep 2023 - Fri 22 Sep 2023
Location: IEEE Quantum Week 2023, Bellevue, Washington, USA
Register by: 10 July 2023 (Speaker Applications)
Best for: Scientists and researchers working in quantum computing for natural sciences or related fields

Workshop Description

The quest for novel and more powerful information processing methods, capable of tackling some of the hardest computational problems in the natural sciences lies at the heart of the quantum computing revolution. As technology progresses, what was originally only conceived in theory comes closer to becoming a reality. The potential applications of quantum computing in the natural sciences are vast and varied, ranging from simulating complex chemical reactions and materials to modelling biological systems and developing new drug treatments. This full-day workshop on quantum computing for natural sciences is aimed at providing participants with a comprehensive overview of the latest advancements in quantum information processing methods and their potential applications in:

  1. Fundamental physics
  2. Chemistry and materials
  3. Life sciences.

The workshop is divided into three sections, each devoted to a specific area, where experts in the respective fields will share their knowledge and provide talks on the current state-of-the-art and ongoing research efforts. The workshop aims to equip participants with a deeper understanding of the potential of quantum computing to revolutionize the natural sciences, highlighting the implications of this technology for future research and development efforts.

Workshop Audience

The workshop aims at attracting a balanced audience made up of quantum computing experts, with both academic and industry backgrounds and domain experts in the natural sciences, with a key focus on computational approaches. The workshop would be most beneficial for those who are interested in presenting, learning about, and discussing the latest advancements in quantum computing and its applications in the natural sciences. This includes, but is not limited to, researchers, scientists, software engineers and practitioners, as well as students and early-career researchers looking to expand their knowledge in this area. The workshop is also relevant to professionals from industry, government, and non-profit organizations who are interested in getting a cutting-edge overview of the state-of-the-art and potential impact of quantum computing in the natural sciences.

 

Registration Details

To register for the IEEE Quantum Week 2023 and attend our workshop, follow the instructions on the IEEE QCE23 webpage. Early registration deadline: 14 August 2023.

How to Apply

If you would like to present your work as a contributing speaker in the workshop, follow the link to the EasyChair Workshop page and submit an abstract for a contributing talk in one of the following areas:

  • Fundamental Physics (i.e., condensed matter, high-energy physics)
  • Quantum Chemistry and Materials
  • Life Sciences

Optionally EasyChair will allow you to upload supporting material with your application (called “Paper” in the webpage), but it is not mandatory.

To submit

On the EasyChair Workshop page click on ‘Author’, then under ‘New Submission’ select “ WKS20-Talk-Abstracts-QC-NatSci-Tech&Apps” follow the instructions to add author’s names, title and abstract.

The webpage will request to upload a ‘Paper’, please note that the workshop does not contain Proceedings, just upload a PDF version of your abstract or an extended abstract (optional) and submit.

The submission deadline for contributing talks abstract is 10 July 2023. Notification of acceptance 15 July 2023.

The Organising Committee

Stefano Mensa, PhD MBCS – Stefano is the Advanced Computing and Emerging Technologies Team leader at the Hartree Centre, and workstream lead for the Hartree National Centre for Digital Innovation (HNCDI) program. He oversees the development and integration of cutting-edge software that harnesses the power of quantum computing to solve complex problems. Stefano works closely with IBM Research and IBM Quantum ensuring that HNCDI provides UK businesses with the necessary skills, knowledge, and technical capability to adopt emerging digital technologies and apply them to industry and public sector challenges. Stefano holds a PhD in Theoretical and Computational Chemistry from the University of Liverpool.

Francesco Tacchino, PhD – Francesco is a Research Scientist at IBM Quantum, IBM Research Europe in Zurich. As a member of the Quantum Computational Sciences group, he works on the development and implementation of quantum algorithms for physics, chemistry and machine learning applications. Francesco received his PhD in Physics from the University of Pavia, Italy.

Mario Motta, PhD – Mario is a Research Staff Member at IBM Quantum, IBM Almaden Research Center. He is part of the Quantum Computational Sciences group and works on the design and application of quantum algorithms for electronic structure. He received a PhD in Physics from the University of Milan, Italy.

Stefan Knecht, PhD – Stefan is the Lead Quantum Chemist at Algorithmiq Ltd, Finland, and a lecturer for Theoretical Chemistry at the Department of Chemistry and Applied Biosciences at ETH Zurich. As the team lead of the quantum chemistry group at Algorithmic, Stefan coordinates the development of efficient and scaling algorithms for quantum chemistry and life-science applications within the framework of hybrid classical and quantum computing. Stefan received his PhD in Chemistry from the University of Dusseldorf, Germany and the Venia Legendi for Theoretical Chemistry from ETH Zu ̈rich, Switzerland.

Emre Sahin – Emre is a skilled Quantum Software Engineer currently working at the Hartree Centre. He is an integral member of the Hartree National Centre for Digital Innovation (HNCDI), where he collaborates with IBM to apply Quantum Machine Learning techniques in material science, drug discovery, and computational pathology. Emre has a Bachelor of Science (Honors) degree in Electric-Electronic Engineering from the Izmir Institute of Technology, where he gained expertise in developing and utilizing Machine Learning and A.I. algorithms for various platforms, including drone technologies and embedded systems for the automotive industry. Additionally, he possesses extensive experience in applied large-scale linear algebra in the High-Performance Computing (HPC) sector, where he has contributed to projects aimed at solving compute and memory-intensive problems and designing innovative scalable stochastic and hybrid mathematical techniques and algorithms.

    Further information

    For more information, please email Dr Stefano Mensa: stefano.mensa@stfc.ac.uk

     

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