BEGIN:VCALENDAR VERSION:2.0 PRODID:ILLC Website X-WR-TIMEZONE:Europe/Amsterdam BEGIN:VTIMEZONE TZID:Europe/Amsterdam X-LIC-LOCATION:Europe/Amsterdam BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19700329T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19701025T030000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:/NewsandEvents/Archives/2021/newsitem/12803/10 -June-2021-DIEP-Seminars-Casper-van-Elteren DTSTAMP:20210603T161516 SUMMARY:DIEP Seminars, Casper van Elteren ATTENDEE;ROLE=Speaker:Casper van Elteren (UvA) DTSTART;TZID=Europe/Amsterdam:20210610T110000 LOCATION:Zoom DESCRIPTION:Understanding dynamical systems is a f undamental problem for the 21st century. Despite t he prima facie differences and purposes of many re al-world networks, previous research shows several universal characteristics in networks properties such as the small-world phenomenon, fat-tail degre e and feedback loops. This has led to the common b ut often implicit assumption that the connectednes s of a node in the network is proportional to its dynamic importance. For example in epidemic resear ch, high degree nodes or "super-spreaders" are ass ociated to dominant epidemic risk and therefore de serve special attention. Yet prior research shows that the shared universality in network characteri stics is not shared in the dynamic or functional p roperties of many real-world systems. In this tal k I will explore the relation between local intera ctions and macroscopic properties of a system thro ugh the lens of statistical physics and informatio n theory. In particular, I will show novel methods on determining the so-called driver node in compl ex systems, and how tipping points can be studied from an information theoretical perspective. (webs ite + slides: https://cvanelteren.github.io/talk/d iep2021/) X-ALT-DESC;FMTTYPE=text/html:\n
Understanding dynamical systems is a fundamental problem for the 21st century. Despite the prima facie di fferences and purposes of many real-world networks , previous research shows several universal charac teristics in networks properties such as the small -world phenomenon, fat-tail degree and feedback lo ops. This has led to the common but often implicit assumption that the connectedness of a node in th e network is proportional to its dynamic importanc e. For example in epidemic research, high degree n odes or "super-spreaders" are associated to dominant epidemic risk and therefore deserve s pecial attention. Yet prior research shows that th e shared universality in network characteristics i s not shared in the dynamic or functional properti es of many real-world systems.
\n\nIn this talk I will explore the relation between local in teractions and macroscopic properties of a system through the lens of statistical physics and inform ation theory. In particular, I will show novel met hods on determining the so-called driver node in c omplex systems, and how tipping points can be stud ied from an information theoretical perspective. ( website + slides: https://cva nelteren.github.io/talk/diep2021/)
URL:https://www.d-iep.org/diep-seminars CONTACT:Soroush Rafiee Rad at soroush.r.rad at gma il.com END:VEVENT END:VCALENDAR