This workshop presents software and algorithmic developments for quantum chemistry across the NISQ (Noisy Intermediate-Scale Quantum), early fault-tolerant, and fault-tolerant regimes, using Kvantify Qrunch as a common software stack. The workshop will illustrate how different algorithms, simulation approaches, and computational resources can be used as quantum computing progresses from current noisy devices toward fault-tolerant architectures.
A DNA-inspired π-stacking system will be used as the common application throughout the workshop, providing a consistent use case across all three regimes. We will cover BEAST-VQE (Bosonic Electron Approximation Systematic Treatment - Variational Quantum Eigensolver flavour developed by Kvantify) for NISQ applications, SqDrift-based approaches (a resource-efficient, randomized quantum simulation method) for early fault-tolerant computing, and Quantum Phase Estimation for the fault-tolerant regime, together with scalable GPU-based simulation capabilities available in Qrunch.
Contents
- NISQ: Introduction to BEAST-VQE and application to π-stacking, including simulator and quantum-hardware results.
- GPU-based tensor-network simulation in Qrunch, including single- and multi-GPU calculations.
- Early fault-tolerant: Introduction to SqDrift and Kvantify’s SqDrift variation, with direct comparison on the π-stacking system.
- Multi-QPU opportunities for SqDrift-based approaches (simulations).
- Fault-tolerant: Quantum Phase Estimation applied to the same π-stacking problem and the role of VQE in state preparation.
Prerequisites
Basic knowledge of quantum chemistry or quantum computing and basic Python experience are recommended.
Hands-On
Participants will set up and run a BEAST calculation with Qrunch’s scalable simulator for a selected molecular system.
Content Level
The content level of the course is broken down as:
Beginner's content:
25%
Intermediate content:
38%
Advanced content:
37%
Language
English
Lecturers
Pier Paolo Poier (Kvantify)
Prices and Eligibility
The course is open and free of charge for people from academia and industry.
Registration
Please register with your official e-mail address to prove your affiliation.
Withdrawal Policy
See Withdrawal
Fees
Free of charge
Pre-required logistics
Basic knowledge of quantum chemistry or quantum computing and basic Python experience are recommended.