Research

Our research is focused on the study models for quantum information processing and fundamental aspects of quantum information theory. This includes interdisciplinary work that aims to study the prospect of artificial intelligence in the context of quantum mechanics. If you are interested, you can watch Hans Briegel talk about our research on explainable AI in science on YouTube (presentation delivered at the SFB BeyondC Conference 2022).

Current Topics of Interest

Artificial Intelligence & Learning

Measurement-based Quantum Computation

Behavioural Biology and Quantum Biology

Connecting quantum devices to harness their full power is the next step to establish useful applications of quantum technologies. This can happen over short and medium distances, e.g. to connect quantum computers or quantum sensors, or over long distances, with the ultimate goal to develop a quantum internet spanning the whole planet. Such a quantum internet does not only promise secure communication, but also makes quantum applications broadly accessible.

We develop protocols and methods to realize such networks, where establishing, distributing and utilizing multipartite entangled states is of central importance. To this aim, we design and investigate protocols for entanglement purification, entanglement certification and state distribution for different entangled resource states. We tackle these questions not only from a fundamental perspective, but also take practical problems and limitations – decoherence, noise and imperfections – into account, and study their influence and means to mitigate them. Our approach is focused on so-called entanglement-based quantum networks, where pre-established entanglement serves as a resource to perform network tasks and fulfill network requests. We are also interested in the design of such networks from a conceptual perspective, where we propose stack models and protocols beyond the physical layer. Furthermore, we pursue an approach to make quantum networks genuine quantum, by allowing for a quantum control plane with the possibility to perform tasks in coherent superposition – which may offer new and unexplored possibilities.

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Measuring quantities is at the heart of all Natural Sciences, but is also of central importance for technological applications. Using quantum systems for this task promises a vastly more efficient use of available resources, where a quadratic improvement in achievable precision is possible – the so-called Heisenberg limit. However, the influence of noise and imperfections threatens this quantum advantage, and it is hence relevant to investigate the effect of imperfections, and find ways to mitigate and overcome noise.

We are interested in the development of sensing protocols for different tasks, where we study optimal resource states and protocols, as well as noise effects and ways to overcome them. Of particular relevance are quantum sensor networks, where multiple sensors at different positions are combined to form a sensor network that is capable to directly sense spatially correlated quantities – e.g. field gradients or a signal from a specific source. Such sensor network can be of small scale, e.g. multiple ions in a single ion trap, but also of global scale where sensors may be located at different locations several (thousand) kilometers apart. We have found schemes to make such sensor networks sensitive only to particular signals solely by choosing proper entangled states, while being insensitive to signals with a different spatial correlation – and hence also to noise of this kind. Multipartite entangled states are of central importance in this respect, and we aim to identify suitable states, find their optimal usage and ways to generate, maintain and utilize them.

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In addition, we are also interested in quantum computation, with a focus on measurement-based quantum computation. In this computational model, a pre-prepared resource state is manipulated solely by single qubit measurements to establish a desired target state – and perform a computation. This offers not only a conceptually different approach to quantum computation, but also a potential practical advantage, e.g. an improved error resilience or more efficient implementation. We study applications of such measurement-based techniques in different contexts, including for quantum communication, error correction or in variational quantum eigensolvers. We are also concerned with the influence of noise and imperfections, where we develop efficient methods to study noise effects in protocols, as well as ways to overcome and mitigate noise. To this aim we utilize the coherent superposition of different processes, e.g. gates or circuits, which allows one to reduce the effective noise. Currently we consider quantum information processing schemes utilizing high-dimensional systems (qudits), and investigate possible advantages of such an approach. We also investigate qubit-qudit hybrid systems, i.e. develop a qudit enhanced qubit information processing.

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Since the early days of quantum mechanics physicists have speculated about the possibility of seeing quantum effects at a macroscopic scale. Schrödinger’s cat, a macroscopic system that is in a coherent superposition state of two macroscopically distinguishable states (“dead” and “alive”), is perhaps the best known example where the puzzling features of quantum mechanics are highlighted. With the experimental progress in many fields, such entertaining thought experiments have actually become a real possibility.

We are interested in studying and assessing such large-scale entangled states with respect to their effective size (i.e., to obtain a measure for macroscopicity), their stability under noise and decoherence, and the possibility to actually prepare and detect them. The very same features that make a state a macroscopic quantum superposition seem to fundamentally hinder their experimental detection. We would like to better understand this and find possible ways to circumvent such problems, e.g., by using encodings.

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Current Grants

  • Explainable AI and the role of agency in science (PI: Hans Briegel); funded by the Austrian Science Fund (FWF) (Wittgenstein Award, WIT9503323)
  • Artificial agency and learning in quantum environments (PI: Hans Briegel); funded by the European Union (ERC Advanced Grant, No. 101055129)
  • Limits and potential of distributed quantum metrology (PI: Wolfgang Dür); funded by the Austrian Science Fund (FWF) (P36009-N).
  • The future of creativity in basic research: Can artificial agents be authors of scientific discoveries? (PI: Hans Briegel; together with PI Thomas Müller, Konstanz University); funded by the German Volkswagen Foundation (Az:97721).
  • Quantum- and classical simulation of quantum networks (PI: Wolfgang Dür); funded by the Austrian Science Fund (FWF) (P36010-N). Finanziert von der Europäischen Union - NextGenerationEU.
  • Models for quantum computing and learning (PI: Hans Briegel); funded by the Austrian Science Fund (FWF) in the framework of the SFB BeyondC (F7102). 
  • Projective simulation with optical frequency combs: a continuous-variable approach to graph states (PI: Fulvio Flamini); Erwin Schrödinger Center for Quantum Science & Technology (ESQ Discovery Programme). 
  • Seeker: The world of quantum technology in a card game (PI: Hendrik Poulsen Nautrup); funded by the Austrian Science Fund (FWF) under the Science Communication Programme WISSKOMM (WKP165).
  • We also participate in the FWF Doctoral Programme Atoms, Light, and Molecules (Faculty Member: Hans Briegel), funded by the Austrian Science Fund (DK-ALM). 
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