Workshop on: QUANTUM INFORMATION AND FOUNDATIONS OF QUANTUM MECHANICS

Quantum Mechanics: Axiomatics and connections with Computing and Information Theory

Thermodynamic modelling of finite quantum systems
aula DOTTORATO - MARTED' 14 SETTEMBRE ore 11.00
  Jochen Rau, Goethe University in Frankfurt

>PRESENTATION: Jochen Rau studied physics at the Universities of Frankfurt (Germany) and Cambridge (UK), before receiving his Ph.D. in 1993 from Duke University (North Carolina, USA). He subsequently held postdoctoral positions at the Max Planck Institute for Nuclear Physics in Heidelberg (Germany), the European Centre for Theoretical Studies in Nuclear Physics and Related Areas in Trento (Italy), as well as the Max Planck Institute for Physics of Complex Systems in Dresden (Germany). His early work focused primarily on non-equilibrium statistical mechanics, both regarding its formal framework and specific applications to thermal field theory, as well as to nuclear, solid state and chaotic systems. Intrigued by the central role of information in statistical physics, his interest gradually shifted to pure probability and information theory in both their classical and quantum varieties. After an intermezzo in the private sector as manager and consultant for various IT, telecom and logistics corporations, as well as a brief stint as interim professor of business administration, Jochen rejoined the physics community in 2008 as a Lecturer at Goethe University in Frankfurt (Germany), where he has introduced and taught novel courses on quantum information theory, quantum computation and probability theory.

Jochen Rau
Abstract  
  Maximum entropy has long been established as a foundational principle of statistical mechanics. Recently this maximum entropy rationale has been extended to the description of small quantum systems, for example in quantum-state reconstruction from incomplete data, even though for such systems it is no longer justified to assume the thermodynamic limit, and it is not clear a priori which observables span the proper level of description. I show how in this situation the finiteness of the sample must be accounted for; how, in particular, prior knowledge continues to exert an influence on the state estimate; and how the proper level of description becomes itself a subject of statistical inference.
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