Skoltech Space Center is happy to invite you to the seminar “Planets, Comets, Galaxies and Beyond: a Journey Through Our Universe”
Speaker: Dr. Giuseppe Cataldo, NASA Goddard Space Flight Center
Category Archives: Seminars
Seminar: “The Global Land Cover Monitoring Using Earth Observations From Space”
Skoltech Space Center is happy to invite you to the seminar “The Global Land Cover Monitoring Using Earth Observations From Space”
Speaker: Dr. Sc., Prof. Sergey Bartalev, Russian Academy of Sciences’ Space Research Institute
Abstract
The Earth Observations (EO) from Space provides a unique opportunity to obtain up-to-date information on the land cover for natural resources management and global change science. Optical satellite sensors currently provide the primary data source to derive information on land cover/land use and vegetation biophysical properties and their dynamics as essential input into forest and agricultural management, carbon cycle and climate change modeling, biodiversity conservation. Recent advances in satellite monitoring provide a number of data sets contributing to the research and applications goals, such as:
• Coarse to moderate spatial resolution data (100m-1km), e.g., SPOT-Vegetation, Terra/Aqua-MODIS, Sentinel-3 and Proba-V, which provide up to daily global observations;
• High spatial resolution data (10-30m), e.g., Landsat-OLI, Sentinel-2, which provide observations every 10-15 days.
A number of land cover data products of national and global coverage have been developed using mainly coarse to moderate resolution satellite data. The recent scientific achievements have resulted in new EO data processing and analysis methods and techniques developments, such as follows:
• pre-processing methods focused on clouds effects filtering, topographic normalization, EO data time-series reconstruction, etc.;
• land cover/land use recognition metrics based on inter- and intra-seasonal changes of land spectral properties derived from EO data time-series;
• locally-adaptive EO data classification methods for land cover mapping over large areas.
In particular a set of advanced Russia-wide maps with focus at generic land cover, croplands, forest species and biomass has been derived from MODIS time-series data of 250m spatial resolution using new image pre-processing and locally-adaptive classification methods. However, for quantifying land cover and, in particular, for measuring land use related changes, high spatial resolution data is needed. Ongoing land cover mapping efforts are focused on the higher spatial resolution land cover datasets. Creation of world-class global land cover products requires development of automated EO data processing chain, which could provide annual update of the maps in order to serve forest and agricultural management as well as Earth science needs.
Speaker introduction
Sergey Bartalev has PhD degree and Doctor of Sciences degree in remote sensing and experimental physics. His research interests are focused at the development of automated methods for land cover mapping and monitoring over large areas using Earth observation data. Prof. Sergey Bartalev is Head of Terrestrial Ecosystems Monitoring Laboratory at the Space Research Institute of Russian Academy of Sciences (Moscow, Russia). He is actively involved into development of the remote sensing method for the agricultural monitoring in Russia.
Seminar: Hydrodynamic description of electron transport in high mobility semiconductors
Skoltech Center of Photonics & Quantum Materials is pleased to invite you to the seminar “Hydrodynamic description of electron transport in high mobility semiconductors”
Speaker: Prof. Anton Andreev, University of Washington, Seattle, USA
Abstract
I will argue that electron transport in high mobility semiconductors at moderately low temperatures may be described using a hydrodynamic approach. The hydrodynamic flow that arises in this case is markedly different from the Stokes flow. The passage of electric current induces temperature gradient that are linear in the current. As a result, the resistivity of the system is determined not only by the viscosity of the system but also by its thermal conductivity.
We are looking forward to seeing you at the seminar.
Course: “Graphical Models of Statistical Inference”
We are happy to invite you to join the course “Graphical Models of Statistical Inference” by Prof. Michael Chertkov (Skoltech Adjunct Professor) planned for Term 1A.
When: 13/15/17 September, 5 PM
Where: IITP RUS (Kharkevich Institute) Bolshoy Karetny per. 19, build.1, Moscow
Course Description:
This course is recommended for IT students, as well as other specialization students, interested in learning about modern theoretical and practical approaches to analysis of big data sets with reach statistical correlations expressed through graphs, matrices, tensors and related. The course is light on rigorous proofs, but rich on statistics and physics intuition.
This mini-course will consist of the following six lectures:
- Graphical Models (Language) and Structured Statistical Inference (problem formulations) in Computer Science, Information Theory and Physics (intro).
- Computational Complexity & Algorithms (Deterministic & Stochastic). Statistical Inference as an Optimization — from Partition Function and Marginal Probabilities to Free Energy (Kublack-Leibler Functional).
- Mean-Field, Belief Propagation, Linear Programming — Variational Approaches, Relaxations, Lower and Upper Bounds. Exact & Heuristic approaches. Iterative Algorithms.
- Modern Analysis and Algorithmic Tools. Review of Loop Series, Cummulant Expansions, Computational Trees, Graph Cover & Monte-Carlo Approaches.
- Examples of Tractable Graphical Models: (a) Network Flows; (b) Attractive (Ferromagnetic) Ising Models; (c) Matching Models; (d) Planar (det-reducable) Models; (e) Gaussian Graphical Models.
- Open Problems. Various Applications, e.g. in Machine Learning, Energy, Bio and Social Systems. Connections/links to other areas of research in modern theoretical engineering.
Pre-requisites:
This is an advanced level course suitable for second year M.Sc. and Ph.D. students. Some prior experience in Probability Theory, Statistics, Statistical Mechanics or Machine Learning (at least one credited course) is recommended.
For registration, please contact Skoltech Education Office at
Seminar: “Using a multiscale tip asymptotic solution for a numerical modeling of a hydraulic fracture growth”
Professor Egor Dontsov
Skoltech Center for Hydrocarbon Recovery is pleased to invite you to a seminar by professor Egor Dontsov from the Department of Civil and Environmental Engineering, University of Houston.
The topic of the seminar is “Using a multiscale tip asymptotic solution for a numerical modeling of a hydraulic fracture growth”.
Seminar Abstract:
Hydraulic fracturing is a method for stimulating oil and gas wells, in which a viscous fluid is injected into a rock formation to produce high conductivity channels. Modeling of the hydraulic fracturing includes fluid balance inside the crack, fluid leak-off into the formation, elastic equilibrium of cracked rock, and a propagation criterion. One peculiar feature of this problem is the multiscale behavior in the crack tip region. In particular, the applicability region of the classical square root solution stemming from the linear elastic fracture mechanics is often smaller than the typical mesh size, which occurs due to the presence of a viscous fluid. As a result, in order to obtain an accurate numerical solution on a relatively coarse mesh, there is a necessity to use the tip asymptotic solution, which has an increased validity region as compared to the classical solution.
This tip asymptotic solution that captures the near-tip behavior can be obtained by solving the problem of a semi-infinite hydraulic fracture that propagates steadily under plane strain elastic conditions. A closed form approximate solution for such problem, which describes the multiscale near tip behavior for the case of a Newtonian fluid and Carter’s leak-off model, has been obtained in Dontsov&Peirce, JFM (2015). This development allowed us to implement the multiscale asymptotic solution as a propagation condition in a numerical simulator to obtain accurate results. In particular, the obtained asymptote is used for a single planar fracture, and for a multiple planar hydraulic fractures that propagate simultaneously from a single wellbore.
The numerical scheme utilizes a fixed rectangular mesh, level set method for tracking the moving fracture front, and an implicit time integration scheme. Results indicate the necessity of using the tip asymptote for obtaining accurate numerical solution, since qualitatively different asymptotes are used in various parts of the same fracture that propagate with different velocities.
Seminar: “Local and non-local magnetic correlations in iron, nickel, and iron pnictides”
Skoltech Center for Photonics and Quantum Materials is pleased to invite you to a seminar titled “Local and non-local magnetic correlations in iron, nickel, and iron pnictides”.
Speaker: Prof. Andrey Katanin, Mikheev Institute of Metal Physics, Ekaterinburg.
Abstract
Investigations of ferromagnetism of iron and nickel attracts a lot of attention because of both, theoretical and practical interest to these substances. To explain physical properties of iron and nickel, it is important to answer the question whether local moments exist in these materials. We consider this problem within the ab initio LDA+DMFT approach with continuous-time quantum Monte Carlo solver (with Ising or SU(2) symmetry of the Hund exchange), considering in particular orbitally-resolved contributions to one- and two-particle properties. For alpha-iron we find the well-defined local moments, which appear due to Hund exchange. We also show that at low temperatures in the paramagnetic phase the subsystem of t2g states is close to the spin freezing transition, which accompany earlier found non-quasiparticle form of eg states. Furthermore, we discuss application of the spin-fermion model to treat the non-local degrees of freedom, which allow us to calculate the magnetic exchange interaction, reproduce correctly Curie temperature and the energy of the alpha phase. In gamma- (fcc) iron we find that the magnetic properties at not too low temperatures T>1000K can be described in terms of temperature-dependent effective local moments, yielding relatively narrow peaks in the real part of the local dynamic magnetic susceptibility, which static part fulfills the Curie-Weiss law. At the same time, at low temperatures gamma-iron (which is realized in precipitates) is better described in terms of itinerant picture. In nickel we show that the local moments appear due to the giant van Hove singularity of the density of states. We also compare these results with the calculations of local magnetic properties of iron pnictide compound LaFeAsO.
5th Workshop on Combinatorics of Moduli Spaces, Hurwitz Numbers, and Cohomological Field Theories
Skoltech Center for Advanced Studies is happy to participate in the 5th Workshop on “Combinatorics of Moduli Spaces, Hurwitz Numbers, and Cohomological Field Theories”, and to conduct a part of the workshop agenda at the venue of the Skolkovo Institute of Science and Technology (Skoltech).
Skoltech’s part will take place on Saturday, June 11 in room 408.
The program
10:00-10:50 Chaiho Rim (Sogang Univ., Korea): Matrix model for irregular conformal block and spectral curve
11:00-11:40 V. Kulikov (Steklov Math. Inst., Moscow): On rigid plane curves
coffee break
12:00-12:50 T. Nakanishi (Nagoya Univ., Japan): Generalized cluster algebras and dilogarithms of higher degrees
closing
CDISE Seminar: Process Science in the Age of Big Software
Friday, 27 May 2016
11:00 – 12:00 in Room 148 (note that the room is different from usual)
Dr. Vladimir Rubin, Dr. Rubin IT Consulting
Process Science in the Age of Big Software
Nowadays, data science is one of the most rapidly emerging interdisciplinary fields creating thousands of new jobs. People surrounded by machines are involved in the “Internet of events“, including the Internet of things, the Internet of content, and the social networks; they continuously produce enormous amounts of data. This event data can be used not only for detecting data dependencies and patterns, but also for deriving process models. The area, which deals with discovering processes from event data, is called “process mining”. Process mining bridges the gap between classical data science and process management and constitutes the substance of a new discipline called “process science”.
In this talk, we introduce the methods of process mining; show how process mining helps to analyze and to create “big software” using the event data generated by the information systems at runtime. At the end we point out several industrial challenges, which call for the necessity of combining the areas of process and data science, architecture of information systems and agile approaches.