Title:  Sub-Exponential Decay Estimates on Trace Norms of Localized Functions of Schrodinger Operators

Abstract:  In 1973, Combes and Thomas discovered a general technique for showing exponential decay of eigenfunctions. The technique involved proving the exponential decay of the resolvent of the Schrodinger operator localized between two distant regions. Since then, the technique has been applied to several types of Schrodinger operators. Recent work has also shown the Combes–Thomas method works well with trace class and Hilbert–Schmidt type operators. In this talk, we build on those results by applying the Combes–Thomas method in the trace, Hilbert–Schmidt, and other trace-type norms to prove sub-exponential decay estimates on functions of Schrodinger operators localized between two distant regions.

Title:  Compressible Navier-Stokes equations with temperature dependent dissipation

Abstract:  From its physical origin, the viscosity and heat conductivity coe!cients in compressible fluids depend on absolute temperature through power laws. The mathematical theory on the well-posedness and regularity on this setting is widely open. I will report some recent progress on this direction, with emphasis on the lower bound of temperature, and global existence of solutions in one or multiple dimensions. The relation between thermodynamics laws and Naiver-Stokes equations will also be discussed. This talk is based on joint works with Weizhe Zhang.

Title: Informatics and Modeling Platform for Stable Isotope-Resolve Metabolomics



Abstract: Recent advances in stable isotope-resolved metabolomics (SIRM) are enabling orders-of-magnitude increase in the number of observable metabolic traits (a metabolic phenotype) for a given organism or community of organisms.  Analytical experiments that take only a few minutes to perform can detect stable isotope-labeled variants of thousands of metabolites.  Thus, unique metabolic phenotypes may be observable for almost all significant biological states, biological processes, and perturbations.  Currently, the major bottleneck is the lack of data analysis that can properly organize and interpret this mountain of phenotypic data as highly insightful biochemical and biological information for a wide range of biological research applications.  To address this limitation, we are developing bioinformatic, biostatistical, and systems biochemical tools, implemented in an integrated data analysis platform, that will directly model metabolic networks as complex inverse problems that are optimized and verified by experimental metabolomics data.  This integrated data analysis platform will enable a broad application of SIRM from the discovery of specific metabolic phenotypes representing biological states of interest to a mechanism-based understanding of a wide range of biological processes with particular metabolic phenotypes.