On Manifold-Like Polyfolds as Differential Geometrical Objects with Applications in Complex Geometry

Abstract We argue for more widespread use of manifold-like polyfolds (M-polyfolds) as differential geometric objects. M-polyfolds possess a distinct advantage over differentiable manifolds, enabling a smooth and local change of dimension. To establish their utility, we introduce tensors and prove the existence of Riemannian metrics, symplectic structures, and almost complex structures within the M-polyfold framework. Drawing inspiration from a series of highly acclaimed papers by László Lempert, we are laying the foundation for advancing geometry and function theory in complex M-polyfolds.

Authors

Publication Details

Journal
Journal of Geometric Analysis
Published
2026-05-22
DOI
https://doi.org/10.1007/s12220-026-02455-4
Primary Topic
Geometric and Algebraic Topology
Type
preprint
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

On Manifold-Like Polyfolds as Differential Geometrical Objects with Applications in Complex Geometry

Håkan Samuelsson Kalm, Per Åhag, Rafał Czyż, Aron Persson
Journal of Geometric Analysis
Geometric and Algebraic Topology
preprint

On Manifold-Like Polyfolds as Differential Geometrical Objects with Applications in Complex Geometry

Håkan Samuelsson Kalm, Per Åhag, Rafał Czyż, Aron Persson
preprint en

Abstract

Abstract We argue for more widespread use of manifold-like polyfolds (M-polyfolds) as differential geometric objects. M-polyfolds possess a distinct advantage over differentiable manifolds, enabling a smooth and local change of dimension. To establish their utility, we introduce tensors and prove the existence of Riemannian metrics, symplectic structures, and almost complex structures within the M-polyfold framework. Drawing inspiration from a series of highly acclaimed papers by László Lempert, we are laying the foundation for advancing geometry and function theory in complex M-polyfolds.

Journal of Geometric AnalysisVol. 36(7)
Umeå Universitet
Openalex Percentile: Top 98%
Geometric and Algebraic Topology
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.