Maya-Morphe P2: Spanda — Adaptive Bioelectric Topology Learning via Gradient-Guided Voltage Thresholds and Dynamic Edge Formation

Birla Institute of Technology and Science, Pilani

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Abstract

Maya-Morphe P2: Spanda (स्पन्द — the first pulse) extends the morphogenetic computing framework from Paper 1 to a multi-scale progressive study across 7 grid sizes, introducing learnable voltage revival thresholds via GraphSAGE-based spatial field encoding. Paper 1 asked: can voltage-driven repair beat fixed-topology? Answer: yes, 99.7% vs 0.0% FRR.Paper 2 asks: what is the optimal voltage threshold — and does it change with scale? SpandaNet replaces the fixed threshold (0.18) with an nn.Parameter trained via a differentiable soft FRR objective. Through 252 trials across 7 scales (29,056 to 266,071 actual cells), gradient descent consistently discovers ~0.163 — approximately 0.017 below Paper 1's hardcoded…

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Topics & keywords

Keywords
  • Topology (electrical circuits)
  • Gradient descent
  • Voltage
  • Control theory (sociology)
  • Differentiable function
  • Constant (computer programming)
  • Grid
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