University of Trento

About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Context (language use). The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.

Superfluidity of polaritons in semiconductor microcavities

Abstract: Similar to atoms in cold gases, exciton–polaritons in semiconductor microcavities can undergo Bose–Einstein condensation. A striking consequence of the appearance of macroscopic coherence in these systems is superfluidity. Now, clear evidence for such behaviour has been found in an exciton–polariton condensate. Superfluidity, the ability of a quantum fluid to flow without friction, is one of the most spectacular phenomena occurring in degenerate gases of interacting bosons. Since its first discovery in liquid helium-4 (refs 1, 2), superfluidity has been observed in quite different systems, and recent experiments with ultracold trapped atoms have explored the subtle links between superfluidity and Bose–Einstein condensation3,4,5. In solid-state systems, it has been anticipated that exciton–polaritons in semiconductor microcavities should behave as an unusual quantum fluid6,7,8, with unique properties stemming from its intrinsically non-equilibrium nature. This has stimulated the quest for an experimental demonstration of superfluidity effects in polariton systems9,10,11,12,13. Here, we report clear evidence for superfluid motion of polaritons. Superfluidity is investigated in terms of the Landau criterion and manifests itself as the suppression of scattering from defects when the flow velocity is slower than the speed of sound in the fluid. Moreover, a Cerenkov-like wake pattern is observed when the flow velocity exceeds the speed of sound. The experimental findings are in quantitative agreement with predictions based on a generalized Gross–Pitaevskii theory12,13, and establish microcavity polaritons as a system for exploring the rich physics of non-equilibrium quantum fluids.

Segmentation as selective search for object recognition

Abstract: For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt segmentation as a selective search by reconsidering segmentation: We propose to generate many approximate locations over few and precise object delineations because (1) an object whose location is never generated can not be recognised and (2) appearance and immediate nearby context are most effective for object recognition. Our method is class-independent and is shown to cover 96.7% of all objects in the Pascal VOC 2007 test set using only 1,536 locations per image. Our selective search enables the use of the more expensive bag-of-words method which we use to substantially improve the state-of-the-art by up to 8.5% for 8 out of 20 classes on the Pascal VOC 2010 detection challenge.

Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO, Advanced Virgo and KAGRA

Abstract: We present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron star systems, which are the most promising targets for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and 90% credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5– 20 deg2 requires at least three detectors of sensitivity within a factor of ∼2 of each other and with a broad frequency bandwidth. When all detectors, including KAGRA and the third LIGO detector in India, reach design sensitivity, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.

MaltParser: A language-independent system for data-driven dependency parsing

Abstract: Parsing unrestricted text is useful for many language technology applications but requires parsing methods that are both robust and efficient. MaltParser is a language-independent system for data-driven dependency parsing that can be used to induce a parser for a new language from a treebank sample in a simple yet flexible manner. Experimental evaluation confirms that MaltParser can achieve robust, efficient and accurate parsing for a wide range of languages without language-specific enhancements and with rather limited amounts of training data.

Advances in the Dempster-Shafer theory of evidence

Abstract: Partial table of contents: DEMPSTER-SHAFER THEORY OF EVIDENCE: GENERAL ISSUES. Measures of Uncertainty in the Dempster-Shafer Theory of Evidence (G. Klir). Comparative Beliefs (S. Wong, et al.). Calculus with Linguistic Probabilities and Beliefs (M. Lamata & S. Moral). FUZZIFICATION OF DEMPSTER-SHAFER THEORY OF EVIDENCE. Rough Membership Functions (Z. Pawlak & A. Skowron). DEMPSTER-SHAFER THEORY IN DECISION MAKING AND OPTIMIZATION. Decision Analysis Using Belief Functions (T. Strat). Interval Probabilities Induced by Decision Problems (T. Whalen). DEMPSTER-SHAFER THEORY FOR THE MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS. Using Dempster-Shafer's Belief-Function Theory in Expert Systems (P. Shenoy). Nonmonotonic Reasoning with Belief Structures (R. Yager). Index.