QuantumBW Colloquium

Design Automation Tools and Software for Quantum Computing

Designing and realizing quantum computing applications in a scalable fashion requires automated, efficient, and user-friendly software tools that cater to the needs of end users, engineers, and physicists. Many of the problems to be tackled are similar to design problems from the classical realm for which sophisticated design automation tools have been developed in the last decades. The Munich Quantum Toolkit (MQT) is a collection of open-source software tools for quantum computing developed by the Chair for Design Automation at TUM, which uses this design automation expertise to provide solutions for design tasks across the entire quantum software stack. This entails high-level support for end users, efficient methods for the classical simulation, compilation, and verification of quantum circuits, tools for quantum error correction, and more. This talk will cover selected highlights across the broad spectrum of the MQT and its history.

Useful quantum computing in the NISQ Era

Is your quantum computer working?

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