MS 8: Accelerating Simulations through Quantum Computing


Miriam Schulte
Johannes Kästner

Johannes Kästner

In recent years, quantum computing has emerged from an appealing new idea of building revolutionary new compute hardware to constructing actual target systems for algorithm development in many application domains, in particular simulations and machine learning. In the current NISQ (noisy intermediate scale) phase in quantum computing, large simulations are far from being reliably executable on quantum systems as a whole. However, recent results indicate that quantum systems may be used in a heterogeneous architecture, complementing conventional CPU-GPU-based architectures to accelerate simulations. These insights can fundamentally challenge best practices in higher-level algorithm design and influence the development of novel algorithms in many areas of application ranging from computational chemistry over structural mechanics to stochastic modeling. This minisymposium aims at bringing together researchers focussing on such innovative algorithms combining conventional architectures with quantum devices to accelerate real-world simulations.

Friday, 6 October 2023, 11:00-12:30 pm

Robustness of quantum algorithms against coherent control errors

Daniel Fink, Julian Berberich
(University of Stuttgart)

11:00 - 11:30 am

Quantum Computational Fluid Dynamics Matthias Möller, Merel A. Schalkers
(TU Delft)
11:30 - 11:50 am
Accelerating Simulations using Hybrid Quantum-Classical Machine Learning Hamzeh Kraus & Rahul Banerjee
(TWT GmbH Science & Innovation)
11:50 - 12:10 pm
Polymer Physics by Quantum Computing Cristian Micheletti
(Scuola Internazionale Superiore di Studi Avanzati)
12:10 - 12:30
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