On the stability of multigraded Betti numbers and Hilbert functions
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Abstract (arXiv)
Multigraded Betti numbers are one of the simplest invariants of multiparameter persistence modules. This invariant is useful in theory -- it completely determines the Hilbert function of the module and the isomorphism type of the free modules in its minimal free resolution -- as well as in practice -- it is easy to visualize and it is one of the main outputs of current multiparameter persistent homology software, such as RIVET. However, to the best of our knowledge, no bottleneck stability result with respect to the interleaving distance has been established for this invariant so far, and this potential lack of stability limits its practical applications. We prove a stability result for multigraded Betti numbers, using an efficiently computable bottleneck-type dissimilarity function we introduce. Our notion of matching is inspired by recent work on signed barcodes, and allows matching bars of the same module in homological degrees of different parity, in addition to matchings bars of different modules in homological degrees of the same parity. Our stability result is a combination of Hilbert's syzygy theorem, Bjerkevik's bottleneck stability for free modules, and a novel stability result for projective resolutions. We also prove, in the 2-parameter case, a 1-Wasserstein stability result for Hilbert functions with respect to the 1-presentation distance of Bjerkevik and Lesnick.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Dec 2021.
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Citing papers per year: 2023: 2; 2024: 1; 2025: 2.
5 papers.
- 2023Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measurescited by 15
- 2023Euler Characteristic Tools For Topological Data Analysiscited by 13
- 2024EMP: Effective Multidimensional Persistence for Graph Representation Learningcited by 4
- 2025CuMPerLay: Learning Cubical Multiparameter Persistence Vectorizationscited by 1
- 2025MCbiF: Measuring Topological Autocorrelation in Multiscale Clusterings via 2-Parameter Persistent Homologycited by 1
- 2025MCbiF: Measuring Topological Autocorrelation in Multiscale Clusterings via 2-Parameter Persistent Homology16 Oct 2025
- 2025CuMPerLay: Learning Cubical Multiparameter Persistence Vectorizations14 Oct 2025
- 2024EMP: Effective Multidimensional Persistence for Graph Representation Learning24 Jan 2024
- 2023Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures6 Jun 2023
- 2023Euler Characteristic Tools For Topological Data Analysis24 Mar 2023