Regularization of the superposition principle: Potential theory meets Fokker-Planck equations

This paper advances the superposition principle for Fokker-Planck equations by constructing a full-fledged right Markov process under general measurability conditions, thereby resolving the open problem of establishing the strong Markov property and enabling new probabilistic solutions to the parabolic Dirichlet problem and flow constructions for both linear and nonlinear cases, including the generalized porous media equation.

Lucian Beznea, Iulian Cîmpean, Michael Röckner2026-03-06🔢 math

Optimization with Parametric Variational Inequality Constraints on a Moving Set

This paper investigates optimization problems constrained by parametric variational inequalities on moving sets by establishing the Lipschitz continuity of the solution function and automatic metric regularity, and proposes a Smoothing Implicit Gradient Algorithm (SIGA) that is proven to converge to a stationary point and validated through real-world portfolio management applications.

Xiaojun Chen, Jin Zhang, Yixuan Zhang2026-03-06🔢 math

Worst-case LpL_p-approximation of periodic functions using median lattice algorithms

This paper proves that a median lattice algorithm, which aggregates multiple rank-1 lattice sampling rules via componentwise median, achieves high-probability, nearly optimal worst-case LpL_p-approximation rates for multivariate periodic functions in weighted Korobov spaces, with dimension-independent constants for LL_\infty under specific weight summability conditions.

Zexin Pan, Mou Cai, Josef Dick + 2 more2026-03-06🔢 math

Besov regularity of solutions to the Dirichlet problem for the Bessel (p,s)(p,s)-Laplacian

This paper establishes global Besov regularity estimates for weak solutions to the Dirichlet problem of a fractional pp-Laplacian defined via the Riesz fractional gradient by combining Lions-Calderón spaces, Besov embeddings, and an adapted Nirenberg difference quotient method, yielding specific regularity indices that depend on the interplay between the order ss and the exponent pp in both superquadratic and subquadratic regimes.

Juan Pablo Borthagaray, Leandro M. Del Pezzo, José Camilo Rueda Niño2026-03-06🔢 math

Bayes with No Shame: Admissibility Geometries of Predictive Inference

This paper demonstrates that predictive inference is governed by four distinct, pairwise non-nested admissibility geometries—Blackwell risk dominance, anytime-valid supermartingales, marginal coverage, and Cesàro approachability—each offering a unique certificate of optimality and proving that admissibility is irreducibly relative to the chosen criterion rather than a universal property.

Nicholas G. Polson, Daniel Zantedeschi2026-03-06🔢 math