machine learning

Time-dependent variational principle for open quantum systems with artificial neural networks

Time-dependent variational principle for open quantum systems with artificial neural networks Descriptions of Open Quantum Systems (OQS) In a quantum mechanical description, the state of a system is either given by a wave function $\psi$ or the density matrix $\rho$.

Variational ground state search on the BrainScaleS-2 neuromorphic hardware

In this talk Robert presents results on variational ground state search with the BrainScaleS-2 neuromorphic hardware.

Neural-network quantum state tomography in a two-qubit experiment

Can we run quantum circuits on ultra-cold atom devices?

In this blog-post, we present our path and thoughts towards using ultra-cold atom experiments for quantum computation. They are the result of a two month internship where we studied the feasibility of such an undertaking in our group. Many associate only universal devices, especially qubit devices, to be valid quantum computers. We show how we think of our ultra-cold atoms in terms of quantum circuits and implement first steps in the software framework [PennyLane](https://pennylane.ai/).

Exploring and Benchmarking Quantum-assisted Neural Networks with Qubit Layers

The aim of this work is to explore practical implementations of Quantum and Quantum-assisted Machine Learning algorithms and benchmark potential benefits of utilizing quantum phenomena in Quantum-assisted Neural Networks with qubit layers. Two known …