2k citations · 18.4k across the 171 of their papers we have counts for
7 papers · 1 filter
Measurement-based quantum computation from Clifford quantum cellular automata
Hendrik Poulsen Nautrup, Hans J. Briegel
Measurement-based quantum computation (MBQC) is a paradigm for quantum computation where computation is driven by local measurements on a suitably entangled resource state. In this…
Learning how to find targets in the micro-world: The case of intermittent active Brownian particles
Michele Caraglio, Harpreet Kaur, Lukas J. Fiderer +4
Finding the best strategy to minimize the time needed to find a given target is a crucial task both in nature and in reaching decisive technological advances. By considering learni…
Quantum circuit synthesis with diffusion models
Florian Fürrutter, Gorka Muñoz-Gil, Hans J. Briegel
Quantum computing has recently emerged as a transformative technology. Yet, its promised advantages rely on efficiently translating quantum operations into viable physical realizat…
Variational measurement-based quantum computation for generative modeling
Arunava Majumder, Marius Krumm, Tina Radkohl +4
Measurement-based quantum computation (MBQC) offers a fundamentally unique paradigm to design quantum algorithms. Indeed, due to the inherent randomness of quantum measurements, th…
Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning
Francesco Preti, Michael Schilling, Sofiene Jerbi +4
Shortening quantum circuits is crucial to reducing the destructive effect of environmental decoherence and enabling useful algorithms. Here, we demonstrate an improvement in such c…
Optimal foraging strategies can be learned
Gorka Muñoz-Gil, Andrea López-Incera, Lukas J. Fiderer +1
The foraging behavior of animals is a paradigm of target search in nature. Understanding which foraging strategies are optimal and how animals learn them are central challenges in…
Towards interpretable quantum machine learning via single-photon quantum walks
Fulvio Flamini, Marius Krumm, Lukas J. Fiderer +2
Variational quantum algorithms represent a promising approach to quantum machine learning where classical neural networks are replaced by parametrized quantum circuits. However, bo…