Speaker: Prof. Suriyanarayanan Vaikuntanathan
University of Chicago
Department of Chemistry
Title: “Enhanced associative memory, classification and
learning with active dynamics.”
Day and Date: Wednesday, January 25, 2023
Time: 5.00 pm.
Venue: Room no. 350, Chemistry Department
Second floor, Annex
Abstract Motivated by advances in the field of active matter where
non-equilibrium forcing has been shown to activate new assembly pathways,
here we study how non-equilibrium driving in prototypical memory
formation models can affect their information processing capabilities.
Our results reveal that activity can provide a new and surprisingly
general way to dramatically improve the memory and information processing
performance of the above described systems without the need for additional
interactions or changes in connectivity. Non-equilibrium dynamics can
allow these systems to have memory capacity, assembly or pattern
recognition properties, and learning ability, in excess of their
corresponding equilibrium counterparts. Counter-intuitively, in some
cases, dynamics with non-equilibrium noise-sources can even have a higher
memory capacity than zero temperature equilibrium systems that are not
subject to any noise. Our results demonstrate the generality of the
enhancement of memory capacity arising from non-equilibrium, active
dynamics. These results are of significance to a variety of processes that
take place under nonequilibrium dynamics, and involve information storage
and retrieval, as well as in silico learning and memory forming systems
for which nonequilibrium dynamics may provide an approach for modulating
memory formation.