QuantumBW Colloquium

Is your quantum computer working?

Useful quantum computing in the NISQ Era

Mesoscopic physics challenges (in) superconducting quantum devices

The dawn of quantum fault-tolerance

Molecules for Quantum Technologies

Quantum computing meets quantum chemistry: A potential new era of simulation and study

Quantum information processing with trapped ions – state of the art, perspectives, and recent applications

Do quantum computers have applications in optimization and machine learning?

Quantum computing promises advantages for a number of structured computational problems. While the idea of quantum computing is not new, only within the last a bit more than five years protagonists have set out to actually build such devices to a reasonable scale. The quantum computers we have today are still somewhat noisy and not huge - but then, such devices seemed inconceivable not very long ago, creating an exciting state of affairs. This also comes along with lots of expectations and some hype. This talk will go on a journey deciphering what we can reasonably expect from such machines in the near future. It will present some exciting perspectives concerning achieving industrially relevant applications in machine learning and optimization. It will also debunk some of the most unreasonable of expectations and provide a reality check of what can be achieved for noisy devices. Overall, this will give rise to a ride through the landscape of one of the most exciting and promising future technologies.

Does provable absence of barren plateaus imply classical simulability?

The potentials and bottlenecks of state-of-the-art quantum machine learning algorithms

Variational quantum algorithms: training and expressivity considerations from CERN

THE QUANTUM LÄND: Quantum computing with trapped neutral atoms - made in Stuttgart