ガウス混合端点のためのリフト付きシュレーディンガー橋:射影ギャップと経路空間の障害
Lifted Schr\"odinger Bridges for Gaussian Mixture Endpoints: Projection Gaps and Path-Space Obstructions
ガウス混合分布間の確率的密度制御を、各軌道にラベルを付加したリフト空間で解き、射影後のギャップとその消失条件を解析した論文。
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著者: Siddhartha Ganguly, George Rapakoulias, Panagiotis Tsiotras
分類: math.OC, cs.LG, cs.RO, cs.SY, eess.SY
原文アブストラクト
We study stochastic density control between Gaussian-mixture endpoint distributions under Brownian prior dynamics. Since the direct Schr\"odinger bridge between Gaussian mixtures is generally not available in closed form, we introduce a lifted path-space construction in which each trajectory is augmented with a source--target component label. Consequently, the problem decomposes into Gaussian component-to-component Schr\"odinger bridges with explicit marginal, drift, and cost formulas, while the mixture-level assignment reduces to a finite-dimensional entropic coupling problem with a Sinkhorn scaling form. We then analyze the projection obtained by discarding or forgetting the label. By construction, the projected law satisfies the original Gaussian-mixture endpoint constraints, but its relative entropy generally differs from the lifted relative entropy by a nonnegative conditional label-information gap. This gap reveals a path-space obstruction: the lifted optimizer cannot, in general, be identified with the direct unlabeled Schr\"odinger bridge after projection. We also derive the posterior-averaged Markov drift associated with the projected marginal flow, prove a kinetic-energy upper bound, and identify a common path-potential condition under which the projection gap vanishes. Several numerical illustrations showing density and shape control are recorded for a self-contained exposition.
