Die Innovationsinitiative QuantumBW startet das neue landesweite »QuantumBW Colloquium« auf dem Campus des Fraunhofer-Institutszentrums Stuttgart. Ziel des Colloquiums ist es, den wissenschaftlichen Austausch über Hardware- und Algorithmik-Themen im Bereich Quantencomputing zu fördern, die neuesten Entwicklungen auf diesem Gebiet vorzustellen und den Gedanken des »Co-Developments« von Quantenlösungen voranzutreiben.
Neben der Frage wie die nächste Generation der Computer realisiert wird, ist es ebenso spannend wofür man die »Next-Generation-Computer« einsetzen kann. Vielversprechende Anwendung finden diese in der Kryptographie, im Machine Learning und in der Optimierung. Aufgrund der aktuell noch verrauschten, kleinen Systeme der NISQ-Ära (Noisy Intermediate Scale), ist insbesondere die Klasse der variationellen Quantenalgorithmen interessant. Diese und weitere Themen wie Quantenfehlerkorrektur, Barren Plateaus und Quantum Advantage beleuchten wir im Colloquium an den folgenden Terminen:
Large-scale quantum computers hold the promise to efficiently solve some computationally hard problems, for which efficient solutions are intractable on classical computers. To date, the construction of scalable fault-tolerant quantum computers remains a fundamental scientific and technological challenge. In this talk, we will first introduce basic concepts of quantum computing and quantum error correction, which allows one to protect quantum information during storage and processing, by redundant encoding of quantum information in logical qubits formed of multiple physical qubits. We will then discuss recent progress in the area of quantum topological quantum error correction, based on new theory concepts and collaborative experimental breakthroughs in state-of-the-art physical quantum processors, including trapped ions, Rydberg atoms and superconducting qubits. These results mark exciting first steps into the era of early fault-tolerant quantum computing with logical qubits.
Superconducting quantum bits, or qubits, are at the forefront of quantum computing research. Harnessing the low loss properties of superconductors and the nonlinearity of Josephson junctions, qubits can be engineered to exist in quantum superposition states and they can be entangled, promising a new paradigm in information processing. By controlling and measuring these fragile quantum states, the community eventually aims to implement powerful quantum algorithms, which on some applications have a much more favorable scaling compared to classical counterparts. However, many challenges persist in maintaining coherence, mitigating noise, and enhancing gate fidelity. I will discuss three mesoscopic physics phenomena which significantly complicate the task of engineering coherent superconducting hardware: ionizing radiation interactions with the microelectronic qubit device substrate, long lived and uncontrolled two-level systems which imprint a memory in the qubit's environment, and fluctuations in the transparency of aluminum oxide tunnel barriers which are at the heart of Josephson junctions.
We will describe digital, analog, and digital-analog quantum computing paradigms. Furthermore, we will discuss the possibility of reaching quantum advantage for industry use cases with current quantum computers in trapped ions, superconducting circuits, neutral atoms, and photonic systems.
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.