LASER WoP Talk No. 2 – Quantum Computing - Use Cases

Until the next LASER World of PHOTONICS in Munich, April 26-29, 2022, we are promoting knowledge exchange and communication in the industry through a new webinar series. The latest continuation of that was the second webinar on Wednesday, November 17, 2021. The focus here was on quantum computing and initial experiences on its areas of application.

Video recording LASER WoP Talk No. 2

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Dr. Daniel J. Egger: Use Cases for quantum computers

Gate based quantum computers are expected to help solves problems in quantum chemistry, machine learning, finance, and combinatorial optimization.

In his presentation Dr. Egger explored several examples of use cases such as financial risk analysis, classification, and quantum chemistry."

About Dr. Daniel Egger:

Dr. Daniel J. Egger is a Research Staff Member working at IBM Quantum, IBM Research – Zurich. His research focusses on the control of quantum computers and on the practical ap-plications of quantum algorithms in finance and optimization. Dr. Egger joined IBM in 2016. From 2014 to 2016 he worked in the asset management industry as a risk manager. He earned a PhD in theoretical physics in 2014 for his work on quantum simulations and optimal control of quantum computers based on superconducting qubits.


Dr. Sofia Vallecorsa: Quantum Computing at CERN - preliminary results of first pilot projects

CERN has recently started its Quantum Technology Initiative in order to investigate the use of quantum technologies in High Energy Physics (HEP). A three-year roadmap and research programme has been defined in collaboration with the HEP and quantum-technology research communities.

In this context, initial pilot projects have been set up at CERN in collaboration with other HEP institutes worldwide on Quantum Computing and Quantum Machine Learning in particular. These projects, are studying basic prototypes of quantum algorithms, which are being evaluated by LHC experiments for different types of workloads. The talk of Dr. Vallecorsa provides an overview of recent results obtained by the different studies, including applications in areas ranging from accelerator beams optimization to data analysis and classification.

About Dr. Sofia Vallecorsa:

Dr. Sofia Vallecorsa is a CERN physicist with extensive experience on software development in the High Energy Physics domain. She obtained her PhD at the University of Geneva and worked on different experiments, from CDF to IceCube and ATLAS. Dr. Vallecorsa coordinates the Quantum Computing area of the CERN Quantum Technology Initiative, recently established. She is also responsible for Deep Learning and Quantum Computing research within CERN openlab which is a unique public-private partnership between CERN and leading ICT companies. Before joining openlab, Dr. Vallecorsa has been responsible for the development of Deep Learning based technologies for the simulation of particle transport through detectors at CERN and she has worked on code modernization projects in the field of Monte Carlo simulation.

Moderator: Dr. Fabio Scafirimuto

Dr. Fabio Scafirimuto has obtained his PhD from ETH in 2019 while working at IBM Research on Cavity Quantum Electrodynamics. He then moved to IBM Quantum working on education, outreach and community activities as Europe and Africa Team Lead for the IBM Quantum and Qiskit Community Team.