Accelerated Quantum Supercomputing with CUDA-Q

Contents

As hybrid quantum–classical computing continues to mature, the ability to program heterogeneous architectures has become essential. This tutorial provides a deep dive into CUDA-Q, NVIDIA’s open-source platform for heterogeneous quantum-classical computing. Participants will learn how to leverage GPU acceleration to simulate quantum circuits, develop hybrid algorithms, and prepare for execution on current and future quantum hardware.

Technical focus areas:

• Algorithmic Implementation: A detailed look at implementing the Quantum Fourier Transform (QFT), focusing on fundamental principles, GPU-accelerated simulation, and performance benchmarking.
• Practical Applications: Moving beyond theory, the tutorial covers practical applications of GPU-acceleration in quantum computing through overviews and interactive hands-on examples.
• Hybrid AI & Machine Learning: An exploration of "AI for Quantum," where participants will program a Hybrid Neural Network using CUDA-Q, demonstrating the synergy between machine learning and quantum circuits.
• Advanced Simulation Techniques: How to leverage Tensor Networks to scale quantum algorithm simulations efficiently on classical supercomputing hardware.

Takeaways:

By the conclusion of the workshop, attendees will have a practical understanding of how to utilize LRZ’s computing services to develop, optimize, and scale quantum-classical applications. This tutorial equips researchers with the tools needed to push the boundaries of quantum simulation and hybrid algorithm design using the industry-leading CUDA-Q platform.

Prerequisites

This tutorial is intended for computational scientists, quantum algorithm researchers, and software engineers familiar with Python who wish to harness GPU acceleration for quantum computing research.

Hands-On

Content is presented in interactive sessions with demos and hands-on exercises. Participants are expected to bring their own laptops. There are no PCs installed in the seminar room!

Content Level

The content level of the course is broken down approximately as:

Beginner's content:	2,5h	~40%
Intermediate content:	2,0h	~30%
Advanced content:	2,0h	~30%
Community-targeted content:	0,0h	0%

Language

English

Lecturers

Esperanza Cuenca Gómez (NVIDIA), Dr. Mario Hernandez Vera (LRZ), Tobias Bauer (LRZ)

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

Legal Notices

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Register now

Course	Accelerated Quantum Supercomputing with CUDA-Q
Number	hqct1w25
Available places	14
Date	18.02.2026 – 18.02.2026
Price	EUR 0.00
Location	Leibniz Rechenzentrum Boltzmannstr. 1 85748 Garching b. München
Room	Seminarraum 2
Registration deadline	04.02.2026 23:59
E-mail	[email protected]