on 26-05-2017
Rupert Ursin (IQOQI - Vienna, Austrian Academy of Sciences)
Friday 26/05/2017, 14:00
Room P1, Mathematics Building, IST
Models of quantum systems on curved space-times lack sufficient experimental verification. Some speculative theories suggest that quantum properties, such as entanglement, may exhibit entirely different behavior to purely classical systems. By measuring this effect or lack thereof, we can test the hypotheses behind several such models. For instance, as predicted by Ralph and coworkers [T C Ralph, G J Milburn, and T Downes, Phys. Rev. A, 79(2):22121, 2009, T C Ralph and J Pienaar, New Journal of Physics, 16(8):85008, 2014], a bipartite entangled system could decohere if each particle traversed through a different gravitational field gradient. We propose to study this effect in a ground to space uplink scenario. We extend the above theoretical predictions of Ralph and coworkers and discuss the scientific consequences of detecting/failing to detect the predicted gravitational decoherence. We present a detailed mission design of the European Space Agency's (ESA) Space QUEST (Space - Quantum Entanglement Space Test) mission, and study the feasibility of the mission schema.
Quantum Computation and Information Seminar
http://math.tecnico.ulisboa.pt/seminars/qci/index.php.en?action=next
Support: Phys-Info (IT), SQIG (IT) and CAMGSD, with support from FCT, FEDER and EU FP7, namely via the Doctoral Programme in the Physics and Mathematics of Information (DP-PMI), and projects PEst-OE/EEI/LA0008/2013, QuSim, and PAPETS (323901).
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on 19-05-2017
Supported by FCT (Portugal) under contract PTDC/EEIPRO/0426/2014
Dynamics-based Invariants for Multi-Camera Video Understanding
Prof. Octavia Camps - Northeastern University, U. S. A.
Venue: GA2 Pavilhão Central, New room
North Tower, floor 7, Alameda campus, IST, 19 May 2017, 14h30
The power of geometric invariants to provide solutions to computer vision problems has been recognized for a long time. On the other hand, dynamics-based invariants are often overlooked. Yet, visual data come in streams: videos are temporal sequences of frames, images are ordered sequences of rows of pixels and contours are chained sequences of edges. In this talk, I will discuss the key role that systems theory can play in timely extracting and exploiting dynamics-based invariants to capture actionable information that is very sparsely encoded in high dimensional data streams.
The central theme of this approach is the use of dynamical models, and their associated invariants, as an information-encoding paradigm. We will show that embedding problems in the conceptual world of dynamical systems makes available a rich, extremely powerful resource base, leading to robust solutions, or, in cases where the underlying problem is intrinsically hard, to computationally tractable approximations with sub optimality certificates. We will illustrate these ideas in the context of two practical applications: crowd-sourcing video and human re-identification.
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