7 papers
Large-Language-Model Discovery of Quantum LDPC Codes through Structured Concept Evolution
Zidu Liu, Florian Marquardt
Quantum computers could outperform classical machines on important problems, but only if the errors that pervade quantum hardware can be corrected at scale. Quantum low-density par…
Uncovering Latent Structures in Robust Pulse Sequences: A Model-Based Reinforcement Learning Approach for Adaptable Quantum Control
Tobias Kiermeyer, Thomas Heydenreich, Léo Van Damme +3
Real-time adaptive control of quantum systems requires rapid generation of robust, high-fidelity pulses across a continuous range of operating conditions. Standard optimization alg…
Comment on "A General Framework for Constructing Local Hidden-state Models to Determine the Steerability"
Nick von Selzam, Florian Marquardt
We point out that the method presented in a recent arXiv article by Jia et al. (arXiv:2512.21848) for constructing local hidden-state models closely follows the framework we develo…
Quantum feedback control with a transformer neural network architecture
Pranav Vaidhyanathan, Florian Marquardt, Mark T. Mitchison +1
Attention-based neural networks such as transformers have revolutionized various fields such as natural language processing, genomics, and vision. Here, we demonstrate the use of t…
Reinforcement Learning for Quantum Technology
Marin Bukov, Florian Marquardt
Many challenges arising in Quantum Technology can be successfully addressed using a set of machine learning algorithms collectively known as reinforcement learning (RL), based on a…
Quantum computing and artificial intelligence: status and perspectives
Giovanni Acampora, Andris Ambainis, Natalia Ares +36
This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could supp…