26 citations · 35 across the 5 of their papers we have counts for
5 papers
Getting large-scale quantum neural networks ready for quantum hardware
Mario Boneberg, Simon Kochsiek, Igor Lesanovsky
Quantum neural networks generalize classical artificial neural networks into the quantum domain. They are formulated as parameterized quantum circuits which are optimized by measur…
Training the classification capability of large-scale quantum cellular automata
Mario Boneberg, Simon Kochsiek, Gabriele Perfetto +1
In the vicinity of a phase transition ergodicity can be broken. Here, different initial many-body configurations evolve towards one of several fixed points, which are macroscopical…
Non-linear classification capability of quantum neural networks due to emergent quantum metastability
Mario Boneberg, Federico Carollo, Igor Lesanovsky
The power and expressivity of deep classical neural networks can be attributed to non-linear input-output relations. Such non-linearities are at the heart of many computational tas…
Dissipative quantum many-body dynamics in (1+1)D quantum cellular automata and quantum neural networks
Mario Boneberg, Federico Carollo, Igor Lesanovsky
Classical artificial neural networks, built from perceptrons as their elementary units, possess enormous expressive power. Here we investigate a quantum neural network architecture…
Quantum fluctuations and correlations in open quantum Dicke models
Mario Boneberg, Igor Lesanovsky, Federico Carollo
In the vicinity of ground-state phase transitions quantum correlations can display non-analytic behavior and critical scaling. This signature of emergent collective effects has bee…