A discrete fractional Grönwall inequality for dissipative systems via resolvent kernel estimate

We establish a discrete fractional Gronwall inequality for dissipative systems with time-dependent forcing. For completely positive discretizations, we bound individual resolvent entries by integrals of the continuous response kernel, under controlled perturbation to the L1 weights and a stepsize restriction. The proof constructs a supersolution for each resolvent column. The resulting Mittag-Leffler weights retain both the decay of initial data and the historical contributions of forcing. The framework covers L1 and several standard schemes on uniform meshes. For linear subdiffusion, it yields decay-preserving L1 error estimates separating first order and $(2-α)$ order contributions, with stronger long-time decay under additional solution regularity.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.34827
Primary Topic
Fractional Differential Equations Solutions
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

A discrete fractional Grönwall inequality for dissipative systems via resolvent kernel estimate

Yunxiao Liu, Lei Li, Jiwei Zhang
arXiv (Cornell University)
Fractional Differential Equations Solutions
preprint

A discrete fractional Grönwall inequality for dissipative systems via resolvent kernel estimate

Yunxiao Liu, Lei Li, Jiwei Zhang
preprint en

Abstract

We establish a discrete fractional Gronwall inequality for dissipative systems with time-dependent forcing. For completely positive discretizations, we bound individual resolvent entries by integrals of the continuous response kernel, under controlled perturbation to the L1 weights and a stepsize restriction. The proof constructs a supersolution for each resolvent column. The resulting Mittag-Leffler weights retain both the decay of initial data and the historical contributions of forcing. The framework covers L1 and several standard schemes on uniform meshes. For linear subdiffusion, it yields decay-preserving L1 error estimates separating first order and $(2-α)$ order contributions, with stronger long-time decay under additional solution regularity.

arXiv (Cornell University)
Fractional Differential Equations Solutions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon