14 OCT 2019
08:00 - 10:30

Venue:

Opposite the ARAJ, Artesh Highway, Tehran, Iran
School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM),



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14 OCT 2019
11:00 - 12:00

Based on: 1812.04886[hep-ph],
Abstract: The detailed analysis of the LHC prospects at the center-of-mass enery of 14 TeV for charged electroweakino searches, decaying to leptons, in compressed supersymmetry scenarios, via exclusive photon-initiated pair production is presented. This provides a potentially increased sensitivity in comparison to inclusive channels, where the background is often overwhelming. The signal which is focused on, is the exclusive production of same-flavour muon and electron pairs, with missing energy in the final state, and with two outgoing intact protons registered by the dedicated forward proton detectors installed inassociation with ATLASand CMS. The results are presented for slepton masses of 120 - 300 GeV and slepton - neutralino mass splitting of 10 - 20 GeV, and find that the relevant backgrounds can be controlled to the level of the expected signal yields.

Larak Seminar Room

9 OCT 2019
16:00 - 17:00

Recent Advances in Thermal Energy Harvesting-Conventional and Nanostructured Thermoelectrics

Abstract:

A thermoelectric generator is a solid-state device that converts heat directly into electricity. Thermoelectric technology has made significant progress in recent years, and its potential to reduce the environmental impact of electrical power generation is retaking worldwide attention. With the new stimulations of the research community in this area, thermoelectric research has been continued in two general directions: (1) theoretical models that predict the properties and offer superior materials and structural designs, and (2) experimental efforts in finding new materials or structures that show enhanced electronic and thermal properties. These efforts have also been followed in two main directions. One has been finding new bulk materials and their further engineering to achieve higher efficiency. Some examples of this direction are the filled skutterudites, half-heusler, and clathrates. Another direction has been the use of nanostructures that improve or maintain thermoelectric power factor through quantum size effects or interface energy filtering, while their thermal conductivity is reduced through the scattering of phonons at interfaces. Some examples of these groups are BiTe/SbTe superlattices (SL) and PbTe/PbSeTe quantum dot superlattices (QDSL). After a brief overview of the science and technology of thermoelectric energy conversion, we will discuss the prospects for waste heat recovery in automobiles, industrial processes, and environmental heat harvesting for powering integrated sensors and health monitoring technologies. In particular, the role of nanotechnology for making
efficient generators will be highlighted, and recent advances will be reviewed and compared with the existing commercial devices.

9 OCT 2019
16:00 - 17:00

We consider some applications of AC as the coloring of R^n with countably many colors with no two points in rational distance getting the same color.

9 OCT 2019
11:00 - 13:00

Venue:
School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM),
Opposite the ARAJ, Artesh Highway, Tehran, Iran

Abstract:
The emergence of flexible information channels in brain networks is a fundamental question in neuroscience. Understanding the mechanisms of dynamic routing of information would have far-reaching implications in a number of disciplines ranging from biology and medicine to information technologies and engineering. In this work, we show that the presence of a node firing at a higher frequency in a network with local connections leads to the reliable transmission of signals and establishes a preferential direction of information flow. Thus, by raising the firing rate a low degree node can behave as a functional hub, spreading its activity patterns polysynaptically in the network. Therefore, in an otherwise homogeneous and undirected network, firing rate is a tunable parameter that introduces directionality and enhances the reliability of signal transmission. The intrinsic firing rate across neuronal populations may thus determine preferred routes for signal transmission that can be easily controlled by changing the firing rate in specific nodes. We show that the results are generic and the same mechanism works in the networks with more complex topology.




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9 OCT 2019
14:00 - 15:00

Computational concentration of measure and robust learning