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UID:178@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20260121T150000
DTEND;TZID=Asia/Kolkata:20260121T160000
DTSTAMP:20260114T054105Z
URL:https://cds.iisc.ac.in/events/m-tech-research-thesis-colloquium-cds-di
 fferential-algebraic-equationdae-based-model-of-avalanche-dynamics-in-ag-h
 bn-memristor-and-reservoir-computing/
SUMMARY:M.Tech Research Thesis {Colloquium}: CDS: "Differential-Algebraic E
 quation(DAE) based model of Avalanche Dynamics in Ag-hBN memristor and Res
 ervoir Computing."
DESCRIPTION:DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES\nM.Tech Research 
 Thesis Colloquium\n\n\n\nSpeaker : Mr. Jayanta Pari\nS.R. Number : 06-18-0
 1-10-12-22-2-22270\nTitle : " Differential-Algebraic Equation(DAE) based m
 odel of Avalanche Dynamics in Ag-hBN memristor and Reservoir Computing."\n
 Research Supervisor : Prof. Soumyendu Raha\nDate &amp\; Time : January 21\
 , 2026\, 15.00 PM\nVenue : # 202 CDS Class Room\n\n\n\nABSTRACT\n\nMemrist
 ive devices based on percolative tunnelling networks exhibit complex colle
 ctive dynamics arising from the interaction of many nanoscale conductive p
 aths. In particular\, Ag–hBN memristive systems have been experimentally
  shown to display avalanche-like current fluctuations and signatures of se
 lf-organized criticality. However\, the internal mechanisms responsible fo
 r these emergent behaviours are difficult to access experimentally due to 
 the highly disordered and hidden nature of the network. This thesis develo
 ps a mathematical and computational framework to model and analyse avalanc
 he dynamics in such memristive networks and to explore their potential for
  reservoir computing.\n\nThe device is modeled as a graph of nodes and edg
 es\, where each edge represents a tunnelling or filamentary conduction cha
 nnel whose conductance evolves in time. Kirchhoff’s circuit laws are enf
 orced through an algebraic constraint\, while the internal filament dynami
 cs are described by nonlinear differential equations\, leading to a couple
 d differential–algebraic equation (DAE) system. Proper boundary conditio
 ns are imposed to ensure a well-posed\, index-1 formulation suitable for s
 table numerical integration. Joule heating–induced filament dissolution 
 is incorporated through a discrete update rule.\n\nNumerical simulations a
 re performed for both two-dimensional and quasi-three-dimensional network 
 geometries. The resulting conductance time series exhibits intermittent bu
 rst-like activity. Statistical analysis of these fluctuations reveals powe
 r-law distributions of avalanche size and duration\, long-range temporal c
 orrelations\, and consistency with crackling-noise scaling relations.\n\nT
 he same DAE-based framework is then used as a physical reservoir for tempo
 ral information processing. A scalar input signal is applied as a sequence
  of voltages to multiple input nodes\, and the resulting currents at multi
 ple output nodes form a high-dimensional reservoir state. Linear readout t
 raining is performed using ridge regression to evaluate performance on ben
 chmark temporal tasks. The results demonstrate that the intrinsic dynamics
  of percolative memristive networks can simultaneously support avalanche c
 riticality and reservoir computing. All these highlight a direct connectio
 n between material-level dynamics and computation in neuromorphic systems.
 \n\n\n\nALL ARE WELCOME
CATEGORIES:Events,MTech Research Thesis Colloquium
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