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KI-Net Conference Announcement
Recent Advances on Particle Systems in Kinetic TheoryMay 8 - 12, 2017ICES, UT-Austin |
ABSTRACTInteracting particle transport or kinetic collisional modeling was introduced in the last quarter of the nineteenth century by L. Boltzmann and J.C. Maxwell, independently, giving birth to the area of mathematical Statistical Mechanics and Thermodynamics. These types of evolution models concern a class of non-local, and non-linear integro-differential problems whose rigorous mathematical treatment and approximations are still emerging. Their applications range from rarefied elastic and inelastic gas dynamics including very low temperature regimes for quantum interactions, collisional plasmas and electron transport in nanostructures, to self-organized or social interacting dynamics. Based on a Markovian framework of birth and death processes, under the regime of molecular chaos propagation, their evolution is described by equations of non-linear collisional Boltzmann type. This event is dedicated to Sasha Bobylev's impact in the mathemtics and computations of kinetic theory. Conference WebsiteGOALSThis conference will focus on new developments on broad areas of such complex particle systems in kinetic collisional theory, focusing on recent progress in analytical and numerical methods covering form the derivation of Boltzmann flows from particle dynamics, initial and boundary value problems, regularity issues, long time dynamics and stability issues, as well as novel computational approaches. This activity is co-sponsored by the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin. REGISTRATION CLOSEDORGANIZERS |
CONFIRMED PARTICIPANTSFUNDINGA limited amount of travel and local lodging is available for researchers in the early stages of their career who want to attend the full program, especially for graduate students and post-doctoral fellows. INFORMATION FOR PARTICIPANTSICES, UT-Austin (ICES, UT) Email: gamba@math.utexas.edu CONFERENCE POSTER
ACKNOWLEDGMENTFunding provided by the NSF through the KI-net Grant. |
