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Our research is rooted in the insight that information and the laws of physics are closely intertwined.

The close relation between information and the laws of physics has two reasons:

First, any information processing, such as transmission, storage, or computation, ultimately boils down to a physical process. Hence, it is natural to ask what information-processing possibilities quantum-mechanical laws offer. 

Second, it has turned out that certain physical facts can be more deeply understood when one studies them from the point of view of information. Examples are non-local correlations from quantum physics or the second law of thermodynamics. In this sense, the projected results of our research have both technological and fundamental science implications.

Implications for technology

It is our goal to implement important information processing primitives, e.g. in cryptography, by harnessing elementary effects occurring in nature. An important example of such a phenomenon is non-local correlations, the existence of which is a direct consequence of the laws of quantum physics, and which has been experimentally verified. Non-local correlations can occur in the joint behavior, under measurements, of the two or more parts of an entangled quantum state. They have proven useful in principle for information processing such as cryptography. It is our goal to extend the range of their possible applications, for example by suggesting schemes for efficient and practical randomness generation. Randomness is considered to be a central resource in computer science.

Scientific implications

It is also our goal to gain deeper insight into physical laws by studying them from the point of view of information. This standpoint has turned out to be fruitful in a number of examples pertaining to quantum physics and thermodynamics. Both of those theories have a statistical character, with entropy and randomness as core concepts. It is therefore natural to apply tools and concepts from information theory in those settings in order to gain deeper insight.

For more details, please see our research publications.

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Wed Jun 28 06:41:14 CEST 2017
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