19 citations · 50 across the 10 of their papers we have counts for
10 papers
Unitary fault-tolerant encoding of Pauli states in surface codes
Luis Colmenarez, Remmy Zen, Jan Olle +2
In fault-tolerant quantum computation, the preparation of logical states is a ubiquitous subroutine, yet significant challenges persist even for the simplest states required. In th…
Reusability Report: Optimizing T-count in General Quantum Circuits with AlphaTensor-Quantum
Remmy Zen, Maximilian Nägele, Florian Marquardt
Quantum computing has the potential to solve problems that are intractable for classical computers, with possible applications in areas such as drug discovery and high-energy physi…
Automated Discovery of Gadgets in Quantum Circuits for Efficient Reinforcement Learning
Oleg M. Yevtushenko, Florian Marquardt
Reinforcement learning (RL) has proven itself as a powerful tool for the discovery of quantum circuits and quantum protocols. We have recently shown that including composite quantu…
Agentic Exploration of Physics Models
Maximilian Nägele, Florian Marquardt
The process of scientific discovery relies on an interplay of observations, analysis, and hypothesis generation. Machine learning is increasingly being adopted to address individua…
Scaling the Automated Discovery of Quantum Circuits via Reinforcement Learning with Gadgets
Jan Olle, Oleg M. Yevtushenko, Florian Marquardt
Reinforcement Learning (RL) has established itself as a powerful tool for designing quantum circuits, which are essential for processing quantum information. RL applications have t…
Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
Maximilian Nägele, Jan Olle, Thomas Fösel +2
Markov decision processes (MDPs) are used to model a wide variety of applications ranging from game playing over robotics to finance. Their optimal policy typically maximizes the e…
Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning
Remmy Zen, Jan Olle, Luis Colmenarez +3
The realization of large-scale quantum computers requires not only quantum error correction (QEC) but also fault-tolerant operations to handle errors that propagate into harmful er…
Non-Markovian feedback for optimized quantum error correction
Matteo Puviani, Sangkha Borah, Remmy Zen +2
Bosonic codes allow the encoding of a logical qubit in a single component device, utilizing the infinitely large Hilbert space of a harmonic oscillator. In particular, the Gottesma…
Optimizing ZX-Diagrams with Deep Reinforcement Learning
Maximilian Nägele, Florian Marquardt
ZX-diagrams are a powerful graphical language for the description of quantum processes with applications in fundamental quantum mechanics, quantum circuit optimization, tensor netw…
Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent
Jan Olle, Remmy Zen, Matteo Puviani +1
In the ongoing race towards experimental implementations of quantum error correction (QEC), finding ways to automatically discover codes and encoding strategies tailored to the qub…