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DTSTART;TZID=America/New_York:20190313T171500
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SUMMARY:On the geometry and topology of initial data sets in General Relativity
DESCRIPTION:Speaker: Greg Galloway (University of Miami) \nTitle: On the geometry and topology of initial data sets in General Relativity \nAbstract: A theme of long standing interest (to the speaker!) concerns the relationship between the topology of spacetime and the occurrence of singularities (causal geodesic incompleteness). Many results concerning this center around the notion of topological censorship\, which has to do with the idea that the region outside all black holes (and white holes) should be simple. The aim of the results to be presented is to provide support for topological censorship at the pure initial data level\, thereby circumventing difficult issues of global evolution. The proofs rely on the recently developed theory of marginally outer trapped surfaces\, which are natural spacetime analogues of minimal surfaces in Riemannian geometry. The talk will begin with a brief overview of general relativity and topological censorship. The talk is based primarily on joint work with various collaborators: Lars Andersson\, Mattias Dahl\, Michael Eichmair and Dan Pollack.
URL:https://cmsa.fas.harvard.edu/event/2-13-2019-colloquium/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-031319-791x1024-1.png
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DTSTART;TZID=America/New_York:20190320T163000
DTEND;TZID=America/New_York:20190320T173000
DTSTAMP:20240507T204308Z
CREATED:20240212T105115Z
LAST-MODIFIED:20240507T204308Z
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SUMMARY:Quality Externalities on Platforms: The Case of Airbnb
DESCRIPTION:Speaker:  Sonia Jaffe  (Microsoft) \nTitle: Quality Externalities on Platforms: The Case of Airbnb \nAbstract:  We explore quality externalities on platforms: when buyers have limited information\, a seller’s quality affects whether her buyers return to the platform\, thereby impacting other sellers’ future business. We propose an intuitive measure of this externality\, applicable across a range of platforms. Guest Return Propensity (GRP) is the aggregate propensity of a seller’s customers to return to the platform. We validate this metric using Airbnb data: matching customers to listings with a one standard deviation higher GRP causes them to take 17% more subsequent trips. By directing buyers to higher-GRP sellers\, platforms may be able to increase overall seller surplus. (Joint work with Peter Coles\, Steven Levitt\, and Igor Popov.)
URL:https://cmsa.fas.harvard.edu/event/3-20-2019-colloquium/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=application/pdf:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-032019.pdf
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DTSTART;TZID=America/New_York:20190327T171500
DTEND;TZID=America/New_York:20190327T181500
DTSTAMP:20240514T181829Z
CREATED:20240212T110407Z
LAST-MODIFIED:20240514T181829Z
UID:10002031-1553706900-1553710500@cmsa.fas.harvard.edu
SUMMARY:Hyperbolic geometry of the olfactory space
DESCRIPTION:Speaker: Tatyana Sharpee (Salk Institute for Biological Studies) \nTitle: Hyperbolic geometry of the olfactory space \nAbstract: The sense of smell can be used to avoid poisons or estimate a food’s nutrition content because biochemical reactions create many by-products. Thus\, the presence of certain bacteria in the food becomes associated with the emission of certain volatile compounds. This perspective suggests that it would be convenient for the nervous system encode odors based on statistics of their co-occurrence within natural mixtures rather than based on the chemical structure per se. I will discuss how this statistical perspective makes it possible to map odors to points in a hyperbolic space. Hyperbolic coordinates have a long but often underappreciated history of relevance to biology. For example\, these coordinates approximate distance between species computed along dendograms\, and more generally between points within hierarchical tree-like networks. We find that these coordinates\, which were generated purely based on the statistics of odors in the natural environment\, provide a contiguous map of human odor pleasantness. Further\, a separate analysis of human perceptual descriptions of smells indicates that these also generate a three dimensional hyperbolic representation of odors. This match in geometries between natural odor statistics and human perception can help to minimize distortions that would otherwise arise when mapping odors to perception. We identify three axes in the perceptual space that are aligned with odor pleasantness\, its molecular boiling point and acidity. Because the perceptual space is curved\, one can predict odor pleasantness by knowing the coordinates along the molecular boiling point and acidity axes. \n  \n 
URL:https://cmsa.fas.harvard.edu/event/3-27-2019-colloquium/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-032719.png
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