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UID:d6f6295ad0029aa3951091375b67af04
CATEGORIES:Mathematical Physics Seminar
CREATED:20220919T164440
SUMMARY:Controlling Networks: Fundamentals and applications to brain science
LOCATION:Zoom
DESCRIPTION:Abstract : The ultimate proof of our understanding of biological or technol
 ogical systems is reflected in our ability to control them. While control t
 heory offers mathematical tools to steer engineered and natural systems tow
 ards a desired state, we lack a framework to control complex self-organized
  systems. Here I will explore the controllability of an arbitrary complex n
 etwork, identifying the set of driver nodes whose time-dependent control ca
 n guide the system’s entire dynamics. Virtually all technological and biolo
 gical networks must be able to control their internal processes. Given that
 , issues related to control deeply shape the topology and the vulnerability
  of real systems. Consequently, unveiling the control principles of real ne
 tworks, the goal of our research, forces us to address series of fundamenta
 l questions pertaining to our understanding of complex systems. Finally, I 
 will discuss how control principles inform our ability to predict neurons i
 nvolved in specific processes in the brain, offering an avenue to experimen
 tally falsify and test the predictions of network control.\n
X-ALT-DESC;FMTTYPE=text/html:<p style="text-align: left;">Abstract : The ultimate proof of our understan
 ding of biological or technological systems is reflected in our ability to 
 control them. While control theory offers mathematical tools to steer engin
 eered and natural systems towards a desired state, we lack a framework to c
 ontrol complex self-organized systems. Here I will explore the controllabil
 ity of an arbitrary complex network, identifying the set of driver nodes wh
 ose time-dependent control can guide the system’s entire dynamics. Virtuall
 y all technological and biological networks must be able to control their i
 nternal processes. Given that, issues related to control deeply shape the t
 opology and the vulnerability of real systems. Consequently, unveiling the 
 control principles of real networks, the goal of our research, forces us to
  address series of fundamental questions pertaining to our understanding of
  complex systems. Finally, I will discuss how control principles inform our
  ability to predict neurons involved in specific processes in the brain, of
 fering an avenue to experimentally falsify and test the predictions of netw
 ork control.</p>
CONTACT:Albert-László Barabási - Northeastern University and Harvard University
DTSTAMP:20260928T122831
DTSTART;TZID=America/New_York:20220921T104500
DTEND;TZID=America/New_York:20220921T114500
SEQUENCE:0
TRANSP:OPAQUE
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