Bessel Function Analysis of Nesterov's ODE in N-Player Quadratic Games
Abstract
We analyze Nesterov's accelerated gradient descent (NAGD) for Nash equilibrium seeking in N-player quadratic games. While the continuous-time NAGD dynamics -- the Su--Boyd--Cand\`es ODE -- are well understood for convex optimization, their behavior with non-symmetric pseudo-gradient matrices arising in games has not been characterized precisely. We establish spectral characterizations via Bessel function modal analysis: the equilibrium is unstable whenever any eigenvalue of the pseudo-gradient matrix G lies outside R≥ 0, and all trajectories converge when every eigenvalue lies in R≥ 0 and G is diagonalizable. Remarkably, complex eigenvalues with positive real parts, which ensure stability for first-order gradient dynamics, induce exponential instability in NAGD. This reveals that the momentum mechanism enabling O(1/t2) convergence in optimization can be detrimental for equilibrium seeking in non-potential games.
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