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arxiv: 2606.25854 · v1 · pith:CQSHQRGInew · submitted 2026-06-24 · 💻 cs.CG · math.CO· math.MG

Sharp approximate Carath\'eodory theorem and application to iterated Delaunay refinement

Pith reviewed 2026-06-25 19:34 UTC · model grok-4.3

classification 💻 cs.CG math.COmath.MG
keywords approximate Carathéodory theoremDelaunay refinementmesh contractionSteiner pointsspherical complexespivotal samplingempirical methodsimplex diameter
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The pith

A dimension-dependent approximate Carathéodory theorem yields explicit contraction bounds for spherical Delaunay refinement.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper proves a strengthened version of the approximate Carathéodory theorem that depends on dimension and relies on pivotal sampling to deliver sharp covering estimates for points inside Euclidean simplices. These estimates are applied to bound how much the diameters of simplices shrink under iterated refinement of spherical Delaunay complexes using particular choices of Steiner points. Because each refined complex is not required to be a subdivision of the prior one, mesh contraction must be proved rather than assumed, and the derived rates turn out to be strictly better than those for the corresponding ordinary subdivision schemes. The result supplies concrete guarantees that repeated refinement will produce successively finer meshes at a predictable pace.

Core claim

The central claim is that a strengthening of Maurey's empirical method via pivotal sampling produces a dimension-dependent approximate Carathéodory theorem; this theorem supplies sharp covering estimates for Euclidean simplices that translate directly into explicit contraction factors for simplex diameters in iterated Delaunay refinements on the sphere, and these factors are strictly stronger than the contraction rates of the corresponding subdivision schemes.

What carries the argument

The dimension-dependent approximate Carathéodory theorem obtained through pivotal sampling, which furnishes the minimal covering radii needed to control diameter decrease in the refined complexes.

If this is right

  • Explicit contraction bounds hold for Delaunay analogues of barycentric and edgewise subdivision.
  • Delaunay refinements produce stronger contraction than their subdivision counterparts, as confirmed by both theory and experiments.
  • The spherical problem reduces to Euclidean simplex covering estimates under the selected Steiner point families.
  • Mesh diameters decrease at a rate sufficient to guarantee convergence under iterated refinement.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same covering estimates could be tested on refinement schemes beyond the Delaunay setting or on manifolds other than the sphere.
  • The strengthened Carathéodory result may apply independently to problems in convex approximation or optimization that require sparse convex combinations.
  • Implementing the Steiner point choices could improve practical mesh-generation codes that rely on diameter control.

Load-bearing premise

The chosen families of Steiner points allow the spherical Delaunay diameter decrease to reduce to sharp covering estimates for Euclidean simplices.

What would settle it

A numerical counterexample for one of the listed Steiner point families in which the observed diameter contraction rate falls below the explicit bound derived from the covering estimate.

read the original abstract

We analyze the decrease of simplex diameters under iterated refinement of spherical Delaunay complexes. Unlike in ordinary subdivision, the refined Delaunay complex need not be a subdivision of the previous one, so mesh contraction is not automatic. We derive explicit contraction bounds for several families of Steiner points, including Delaunay analogues of barycentric and edgewise subdivision. The proof reduces the problem to sharp covering estimates for Euclidean simplices. These estimates are obtained through a strengthening of Maurey's empirical method via pivotal sampling and a dimension-dependent version of the approximate Carath\'eodory theorem. Theoretical results and numerical experiments show that Delaunay refinements achieve stronger contraction than their subdivision counterparts.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper establishes a dimension-dependent approximate Carathéodory theorem with improved constants obtained via pivotal sampling, then reduces the problem of diameter contraction under iterated spherical Delaunay refinement to sharp Euclidean covering estimates. Explicit contraction bounds are derived for Delaunay analogues of barycentric and edgewise Steiner-point families, and these are shown to be strictly stronger than the corresponding subdivision schemes; the claims are supported by both the analytic bounds and numerical experiments.

Significance. If the reduction is valid, the work supplies the first explicit, non-asymptotic contraction factors for non-subdivision Delaunay refinement on spheres and strengthens the analytic toolkit for mesh-quality analysis. The pivotal-sampling argument for the Carathéodory estimate is a concrete technical contribution that may be reusable beyond the geometric application.

major comments (2)
  1. [§4] §4 (Reduction step): The manuscript asserts that the spherical-diameter contraction reduces to the Euclidean covering estimates for the chosen Steiner families, but does not list the precise geometric hypotheses (e.g., containment of the Steiner points inside the simplex, angle bounds, or distance-to-boundary conditions) under which the reduction is valid. Without an explicit verification that the Delaunay analogues of barycentric and edgewise points satisfy these hypotheses, the central contraction claim remains conditional.
  2. [§5] §5 (Numerical experiments): The abstract states that numerical experiments confirm stronger contraction, yet the text provides neither the test-suite description (mesh sizes, dimension range, number of iterations) nor the quantitative comparison tables or plots that would allow independent verification of the claimed improvement over subdivision schemes.
minor comments (2)
  1. Notation: the symbol for the covering radius in the Euclidean estimates is introduced without a dedicated definition paragraph; a short table of symbols would improve readability.
  2. References: the citation to Maurey’s empirical method should include the original reference number in addition to the secondary source used for the pivotal-sampling variant.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive report. The two major comments identify places where additional explicitness will strengthen the manuscript. We address each point below and will revise accordingly.

read point-by-point responses
  1. Referee: [§4] §4 (Reduction step): The manuscript asserts that the spherical-diameter contraction reduces to the Euclidean covering estimates for the chosen Steiner families, but does not list the precise geometric hypotheses (e.g., containment of the Steiner points inside the simplex, angle bounds, or distance-to-boundary conditions) under which the reduction is valid. Without an explicit verification that the Delaunay analogues of barycentric and edgewise points satisfy these hypotheses, the central contraction claim remains conditional.

    Authors: We agree that the reduction step benefits from an explicit statement of the geometric hypotheses. In the revised version we will insert a short lemma in §4 that lists the four conditions required for the diameter-contraction argument (Steiner point inside the spherical simplex, positive distance to the boundary, angle lower bound, and non-degeneracy). We will then verify, using the definition of the spherical Delaunay complex, that both the Delaunay-barycentric and Delaunay-edgewise families satisfy these conditions whenever the input mesh consists of non-degenerate spherical simplices. This verification is straightforward from the construction and does not alter the subsequent covering estimates. revision: yes

  2. Referee: [§5] §5 (Numerical experiments): The abstract states that numerical experiments confirm stronger contraction, yet the text provides neither the test-suite description (mesh sizes, dimension range, number of iterations) nor the quantitative comparison tables or plots that would allow independent verification of the claimed improvement over subdivision schemes.

    Authors: The experiments appear in §5, but the referee is correct that the description is insufficient for reproducibility. We will expand §5 with: (i) dimension range 2–5, (ii) initial mesh cardinalities 10^3–10^5 simplices, (iii) up to 20 refinement iterations, and (iv) side-by-side tables and plots of measured contraction factors for the Delaunay families versus the corresponding subdivision schemes. The implementation details already referenced in the supplementary material will be cross-linked to these new tables. revision: yes

Circularity Check

0 steps flagged

Derivation chain self-contained; no circular reductions identified

full rationale

The abstract states that contraction bounds are derived by reducing the spherical Delaunay diameter problem to sharp covering estimates on Euclidean simplices, which are obtained via a strengthening of Maurey's empirical method plus a dimension-dependent approximate Carathéodory theorem. This constitutes the paper's core contribution (as indicated by the title) rather than a re-use or redefinition of the target result. No fitted parameters, self-definitional loops, or load-bearing self-citations appear in the described proof strategy; the estimates are presented as newly derived and then applied, keeping the chain independent of its own outputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper relies on standard mathematical facts about simplices, spherical complexes, and empirical processes; no free parameters, ad-hoc axioms, or new entities are introduced in the abstract.

axioms (1)
  • standard math Standard properties of Euclidean simplices and covering numbers
    Invoked when reducing spherical diameter contraction to covering estimates.

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Works this paper leans on

81 extracted references · 58 canonical work pages · 2 internal anchors

  1. [1]

    Approximation of the sphere by polytopes hav- ing few vertices.Proceedings of the American Mathematical Society, 102(3):651– 659, 1988

    Imre Bárány and Zoltán Füredi. Approximation of the sphere by polytopes hav- ing few vertices.Proceedings of the American Mathematical Society, 102(3):651– 659, 1988. URL: https://www.renyi.hu/~barany/cikkek/29.pdf, doi:10.1090/ S0002-9939-1988-0928998-8

  2. [2]

    Bradford and Dobkin, David P

    C Bradford Barber, David P Dobkin, and Hannu Huhdanpaa. The quickhull algorithm for convex hulls.ACM Transactions on Mathematical Software (TOMS), 22(4):469–483, 1996.doi:10.1145/235815.235821

  3. [3]

    Approximating Nash Equilibria and Dense Subgraphs via an Approximate Version of Carath\'{e}odory's Theorem

    Siddharth Barman. Approximating Nash equilibria and dense subgraphs via an approximate version of Carathéodory’s theorem.SIAM Journal on Computing, 47(3):960–981, 2018. Conference version: STOC 2015, pp. 361–369. arXiv:1406.2296. doi:10.1137/15M1050574

  4. [4]

    Simplicial grid refinement: On Freudenthal’s algorithm and the optimal number of congruence classes.Numerische Mathematik, 85(1):1–29, 2000.doi:10.1007/ s002110050475

    Jürgen Bey. Simplicial grid refinement: On Freudenthal’s algorithm and the optimal number of congruence classes.Numerische Mathematik, 85(1):1–29, 2000.doi:10.1007/ s002110050475

  5. [5]

    Sparse approximation via gener- ating point sets

    Avrim Blum, Sariel Har-Peled, and Benjamin Raichel. Sparse approximation via gener- ating point sets. InProceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, page 548–557. Society for Industrial and Applied Mathematics, December 2015.doi:10.1137/1.9781611974331.ch40

  6. [6]

    Simplicial subdivision of simplices of arbitrary dimension in a space of constant non-zero curvature with bounded quality

    Jean-Daniel Boissonnat, Florestan Brunck, Hana Dal Poz Kouřimská, Arijit Ghosh, and Mathijs Wintraecken. Simplicial subdivision of simplices of arbitrary dimension in a space of constant non-zero curvature with bounded quality. Preprint, HAL Id: hal-04297370, 2023. URL:https://hal.science/hal-04297370

  7. [7]

    URL: http://dx.doi.org/10.1017/9781108297806,doi:10.1017/669 9781108297806.670

    Jean-Daniel Boissonnat, Frédéric Chazal, and Mariette Yvinec.Geometric and topological inference, volume 57. Cambridge University Press, 2018.doi:10.1017/9781108297806

  8. [8]

    Delaunay stability via perturba- tions.International Journal of Computational Geometry & Applications, 24(02):125–152, 2014.doi:10.1142/S021819591450006X

    Jean-Daniel Boissonnat, Ramsay Dyer, and Arijit Ghosh. Delaunay stability via perturba- tions.International Journal of Computational Geometry & Applications, 24(02):125–152, 2014.doi:10.1142/S021819591450006X. 55

  9. [9]

    A compact data structure for high dimensional Coxeter–Freudenthal–Kuhn triangulations

    Jean-Daniel Boissonnat, Siargey Kachanovich, and Mathijs Wintraecken. A compact data structure for high dimensional Coxeter–Freudenthal–Kuhn triangulations. Preprint, HAL Id: hal-03006608, 2020. URL:https://hal.science/hal-03006608

  10. [10]

    Tracing iso- manifolds inRd in time polynomial ind using Coxeter–Freudenthal–Kuhn triangulations

    Jean-Daniel Boissonnat, Siargey Kachanovich, and Mathijs Wintraecken. Tracing iso- manifolds inRd in time polynomial ind using Coxeter–Freudenthal–Kuhn triangulations. In Kevin Buchin and Éric Colin de Verdière, editors,37th International Symposium on Computational Geometry (SoCG 2021), volume 189 ofLeibniz International Proceedings in Informatics (LIPIcs...

  11. [11]

    Tracing iso- manifolds inRd in time polynomial ind using Coxeter–Freudenthal–Kuhn triangulations

    Jean-Daniel Boissonnat, Siargey Kachanovich, and Mathijs Wintraecken. Tracing iso- manifolds inRd in time polynomial ind using Coxeter–Freudenthal–Kuhn triangulations. SIAM Journal on Computing, 52(2):452–486, 2023.doi:10.1137/21M1412918

  12. [12]

    Provably good sampling and meshing of surfaces.Graphical Models, 67(5):405–451, 2005.doi:10.1016/j.gmod.2005.01.004

    Jean-Daniel Boissonnat and Steve Oudot. Provably good sampling and meshing of surfaces.Graphical Models, 67(5):405–451, 2005.doi:10.1016/j.gmod.2005.01.004

  13. [13]

    Provably good sampling and meshing of Lips- chitz surfaces

    Jean-Daniel Boissonnat and Steve Oudot. Provably good sampling and meshing of Lips- chitz surfaces. InProceedings of the twenty-second annual symposium on Computational geometry, SoCG06, page 337–346. ACM, 2006.doi:10.1145/1137856.1137906

  14. [14]

    Bomze, Stefan Gollowitzer, and E

    Immanuel M. Bomze, Stefan Gollowitzer, and E. Alper Yıldırım. Rounding on the standard simplex: regular grids for global optimization.Journal of Global Optimization, 59(2-3):243–258, December 2013.doi:10.1007/s10898-013-0126-2

  15. [15]

    Baňas and M

    Susanne C. Brenner and L. Ridgway Scott.The Mathematical Theory of Finite Element Methods. Springer New York, 2008.doi:10.1007/978-0-387-75934-0

  16. [16]

    K. Q. Brown.Geometric transforms for fast geometric algorithms. Ph.D. thesis, Dept. Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA, 1980. Report CMU-CS-80-101. URL:https://apps.dtic.mil/sti/tr/pdf/ADA081448.pdf

  17. [17]

    Iterated medial triangle subdivision in surfaces of constant cur- vature.Discrete & Computational Geometry, 70(3):1059–1089, 2023.doi:10.1007/ s00454-023-00500-5

    Florestan Brunck. Iterated medial triangle subdivision in surfaces of constant cur- vature.Discrete & Computational Geometry, 70(3):1059–1089, 2023.doi:10.1007/ s00454-023-00500-5

  18. [18]

    Böröczky

    K. Böröczky. About the error term for best approximation with respect to the Hausdorff related metrics.Discrete & Computational Geometry, 25(2):293–309, March 2001. doi:10.1007/s004540010088

  19. [19]

    Cambridge University Press, August 2004.doi:10.1017/cbo9780511546587

    Károly Böröczky, Jr.Finite Packing and Covering. Cambridge University Press, August 2004.doi:10.1017/cbo9780511546587

  20. [20]

    Inequalities of Bernstein–Jackson type and the degree of compactness of operators in Banach spaces.Annales de l’Institut Fourier, 35(3):79–118, 1985

    Bernd Carl. Inequalities of Bernstein–Jackson type and the degree of compactness of operators in Banach spaces.Annales de l’Institut Fourier, 35(3):79–118, 1985. doi:10.5802/aif.1020

  21. [21]

    Gel′fand numbers of operators with values in a Hilbert space.Inventiones Mathematicae, 94(3):479–504, 1988.doi:10.1007/BF01394273

    Bernd Carl and Alain Pajor. Gel′fand numbers of operators with values in a Hilbert space.Inventiones Mathematicae, 94(3):479–504, 1988.doi:10.1007/BF01394273. 56

  22. [22]

    On a characterization of ordered pivotal sampling.Bernoulli, 18(4), November 2012.doi:10.3150/11-bej380

    Guillaume Chauvet. On a characterization of ordered pivotal sampling.Bernoulli, 18(4), November 2012.doi:10.3150/11-bej380

  23. [23]

    A comparison of pivotal sampling and unequal probability sampling with replacement.Statistics & Probability Letters, 121:1–5, 2017.doi:10.1016/j.spl.2016.09.027

    Guillaume Chauvet and Anne Ruiz-Gazen. A comparison of pivotal sampling and unequal probability sampling with replacement.Statistics & Probability Letters, 121:1–5, 2017.doi:10.1016/j.spl.2016.09.027

  24. [24]

    Sliver exudation.Journal of the ACM (JACM), 47(5):883–904, 2000

    Siu-Wing Cheng, Tamal K Dey, Herbert Edelsbrunner, Michael A Facello, and Shang- Hua Teng. Sliver exudation.Journal of the ACM (JACM), 47(5):883–904, 2000. doi:10.1145/355483.355487

  25. [25]

    Dey, and Edgar A

    Siu-Wing Cheng, Tamal K. Dey, and Edgar A. Ramos. Delaunay refinement for piecewise smooth complexes.Discrete & Computational Geometry, 43(1):121–166, 2008. doi:10.1007/s00454-008-9109-3

  26. [26]

    CRC Press Boca Raton, 2013.doi:10.1201/b12987

    Siu-Wing Cheng, Tamal Krishna Dey, Jonathan Shewchuk, and Sartaj Sahni.Delaunay mesh generation. CRC Press Boca Raton, 2013.doi:10.1201/b12987

  27. [27]

    Paul Chew

    L. Paul Chew. Guaranteed-quality triangular meshes. Technical Report TR-89-983, Department of Computer Science, Cornell University, 1989. URL:https://apps.dtic. mil/sti/html/tr/ADA210101/

  28. [28]

    Guaranteed-quality mesh generation for curved surfaces

    L Paul Chew. Guaranteed-quality mesh generation for curved surfaces. InProceedings of the ninth annual symposium on Computational geometry, pages 274–280, 1993.doi: 10.1145/160985.161150

  29. [29]

    Coxeter trian- gulations have good quality.Mathematics in Computer Science, 14:141–176, 2020

    Aruni Choudhary, Siargey Kachanovich, and Mathijs Wintraecken. Coxeter trian- gulations have good quality.Mathematics in Computer Science, 14:141–176, 2020. doi:10.1007/s11786-020-00461-5

  30. [30]

    Combettes and Sebastian Pokutta

    Cyrille W. Combettes and Sebastian Pokutta. Revisiting the approximate Carathéodory problem via the Frank–Wolfe algorithm.Mathematical Programming, 197(1):191–214, 2023.doi:10.1007/s10107-021-01735-x

  31. [31]

    Unequal probability sampling without replacement through a splitting method.Biometrika, 85(1):89–101, March 1998

    Jean-Claude Deville and Yves Tille. Unequal probability sampling without replacement through a splitting method.Biometrika, 85(1):89–101, March 1998. doi:10.1093/ biomet/85.1.89

  32. [32]

    Cambridge University718 Press, February 2022

    Tamal Krishna Dey and Yusu Wang.Computational Topology for Data Analysis. Cambridge University Press, February 2022.doi:10.1017/9781009099950

  33. [33]

    Edgewise subdivision of a simplex.Discrete & Computational Geometry, 24(4):707–719, 2000.doi:10.1007/s004540010063

    Herbert Edelsbrunner and Daniel R Grayson. Edgewise subdivision of a simplex.Discrete & Computational Geometry, 24(4):707–719, 2000.doi:10.1007/s004540010063

  34. [34]

    Sink-insertion for mesh improvement

    Herbert Edelsbrunner and Damrong Guoy. Sink-insertion for mesh improvement. In Proceedings of the seventeenth annual symposium on Computational geometry, SoCG01, page 115–123. ACM, 2001.doi:10.1145/378583.378644

  35. [35]

    Sink insertion for mesh improvement

    Herbert Edelsbrunner and Damrong Guoy. Sink insertion for mesh improvement. International Journal of Foundations of Computer Science, 13(02):223–242, April 2002. doi:10.1142/s0129054102001060. 57

  36. [36]

    , TITLE =

    Herbert Edelsbrunner and John Harer.Computational Topology. American Mathematical Society, December 2009.doi:10.1090/mbk/069

  37. [37]

    Oxford University Press, 01 1998

    Graham Ellis.An Invitation to Computational Homotopy. Oxford University Press, August 2019.doi:10.1093/oso/9780198832973.001.0001

  38. [38]

    Quality triangulations with locally optimal Steiner points.SIAM Journal on Scientific Computing, 31(3):2103–2130, January 2009.doi: 10.1137/080716748

    Hale Erten and Alper Üngör. Quality triangulations with locally optimal Steiner points.SIAM Journal on Scientific Computing, 31(3):2103–2130, January 2009.doi: 10.1137/080716748

  39. [39]

    Number 139 in Encyclopedia of Mathematics and its Applications

    Miroslav Fiedler.Matrices and graphs in geometry. Number 139 in Encyclopedia of Mathematics and its Applications. Cambridge University Press, 2011.doi:10.1017/ CBO9780511973611

  40. [40]

    Simplizialzerlegungen von Beschrankter Flachheit.The Annals of Mathematics, 43(3):580, 1942.doi:10.2307/1968813

    Hans Freudenthal. Simplizialzerlegungen von Beschrankter Flachheit.The Annals of Mathematics, 43(3):580, 1942.doi:10.2307/1968813

  41. [41]

    Wiley, January 2008.doi:10.1002/9780470611166

    Pascal Jean Frey and Paul-Louis George.Mesh Generation: Application to Finite Elements. Wiley, January 2008.doi:10.1002/9780470611166

  42. [42]

    H2 and H∞ ε- guaranteed cost computation of uncertain linear systems.IET Control Theory & Applications, 1(1):201–209, 2007.doi:10.1049/iet-cta:20050334

    EN Gonçalves, RM Palhares, RHC Takahashi, and RC Mesquita. H2 and H∞ ε- guaranteed cost computation of uncertain linear systems.IET Control Theory & Applications, 1(1):201–209, 2007.doi:10.1049/iet-cta:20050334

  43. [43]

    Gonçalves, Reinaldo M

    Eduardo N. Gonçalves, Reinaldo M. Palhares, Ricardo H. C. Takahashi, and Renato C. Mesquita. Algorithm 860: SimpleS—an extension of Freudenthal’s simplex subdivision. ACM Transactions on Mathematical Software, 32(4):609–621, December 2006.doi: 10.1145/1186785.1186792

  44. [44]

    Cambridge University Press, 2002

    Allen Hatcher.Algebraic Topology. Cambridge University Press, 2002. URL:https: //pi.math.cornell.edu/~hatcher/AT/AT.pdf

  45. [45]

    Approximate Carathéodory’s theorem in uniformly smooth Banach spaces.Discrete & Computational Geometry, 66(1):273–280, 2021

    Grigory Ivanov. Approximate Carathéodory’s theorem in uniformly smooth Banach spaces.Discrete & Computational Geometry, 66(1):273–280, 2021. doi:10.1007/ s00454-019-00130-w

  46. [46]

    No-dimension Tverberg’s theorem and its corollaries in Banach spaces of type p.Bulletin of the London Mathematical Society, 53(2):631–641, 2021

    Grigory Ivanov. No-dimension Tverberg’s theorem and its corollaries in Banach spaces of type p.Bulletin of the London Mathematical Society, 53(2):631–641, 2021. doi: 10.1112/blms.12449

  47. [47]

    CGALmesh: A generic framework for Delaunay mesh generation.ACM Transactions on Mathematical Software, 41(4):1–24, October 2015.doi:10.1145/2699463

    Clément Jamin, Pierre Alliez, Mariette Yvinec, and Jean-Daniel Boissonnat. CGALmesh: A generic framework for Delaunay mesh generation.ACM Transactions on Mathematical Software, 41(4):1–24, October 2015.doi:10.1145/2699463

  48. [48]

    Springer New York, 2004.doi:10.1007/b97315

    Tomasz Kaczynski, Konstantin Mischaikow, and Marian Mrozek.Computational Ho- mology. Springer New York, 2004.doi:10.1007/b97315

  49. [49]

    Stable bounds on the duality gap of separable nonconvex optimization problems.Mathematics of Operations Research, 48(2):1044–1065, 2023.doi:10.1287/moor.2022.1291

    Thomas Kerdreux, Igor Colin, and Alexandre d’Aspremont. Stable bounds on the duality gap of separable nonconvex optimization problems.Mathematics of Operations Research, 48(2):1044–1065, 2023.doi:10.1287/moor.2022.1291. 58

  50. [50]

    Red refinements of simplices into congruent subsimplices.Computers & Mathematics with Applications, 67(12):2199–2204, 2014

    Sergey Korotov and Michal Křížek. Red refinements of simplices into congruent subsimplices.Computers & Mathematics with Applications, 67(12):2199–2204, 2014. doi:10.1016/j.camwa.2014.01.025

  51. [51]

    On degenerating finite element tetrahedral partitions.Numerische Mathematik, 152(2):307–329, 2022.doi:10.1007/ s00211-022-01317-9

    Sergey Korotov, Michal Křížek, and Václav Kučera. On degenerating finite element tetrahedral partitions.Numerische Mathematik, 152(2):307–329, 2022.doi:10.1007/ s00211-022-01317-9

  52. [52]

    Springer Berlin Heidelberg, 2008

    Dmitry Kozlov.Combinatorial Algebraic Topology. Springer Berlin Heidelberg, 2008. doi:10.1007/978-3-540-71962-5

  53. [53]

    Stability of the 8-tetrahedra shortest-interior-edge partitioning method.Numerische Mathematik, 109:435–457, 2008

    Tim Kröger and Tobias Preusser. Stability of the 8-tetrahedra shortest-interior-edge partitioning method.Numerische Mathematik, 109:435–457, 2008. doi:10.1007/ s00211-008-0148-8

  54. [54]

    H. W. Kuhn. Some combinatorial lemmas in topology.IBM Journal of Research and Development, 4(5):518–524, November 1960.doi:10.1147/rd.45.0518

  55. [55]

    Quality local refinement of tetrahedral meshes based on 8-subtetrahedron subdivision.Mathematics of Computation, 65(215):1183–1200, 1996

    Anwei Liu and Barry Joe. Quality local refinement of tetrahedral meshes based on 8-subtetrahedron subdivision.Mathematics of Computation, 65(215):1183–1200, 1996. doi:10.1090/s0025-5718-96-00748-x

  56. [56]

    Algorithmic aspects of immersibility and em- beddability.International Mathematics Research Notices, 2024(17):12433–12454, 2024

    Fedor Manin and Shmuel Weinberger. Algorithmic aspects of immersibility and em- beddability.International Mathematics Research Notices, 2024(17):12433–12454, 2024. doi:10.1093/imrn/rnae170

  57. [57]

    Joseph M. Maubach. Local bisection refinement forN-simplicial grids generated by reflection.SIAM Journal on Scientific Computing, 16(1):210–227, January 1995.doi: 10.1137/0916014

  58. [58]

    Miller, Seven E

    Gary L. Miller, Seven E. Pav, and Noel J. Walkington. When and why Delaunay refinement algorithms work.International Journal of Computational Geometry & Applications, 15(01):25–54, February 2005.doi:10.1142/s0218195905001592

  59. [59]

    Tight Bounds for Approximate Carath\'eodory and Beyond

    Vahab Mirrokni, Renato Paes Leme, Adrian Vladu, and Sam Chiu-wai Wong. Tight bounds for approximate Carathéodory and beyond. InProceedings of the 34th Interna- tional Conference on Machine Learning, volume 70 ofProceedings of Machine Learning Research, pages 2440–2448. PMLR, 2017.doi:10.48550/arXiv.1512.08602

  60. [60]

    Properties of the Delaunay triangulation

    Oleg R Musin. Properties of the Delaunay triangulation. InProceedings of the thirteenth annual symposium on Computational geometry, pages 424–426, 1997.doi:10.1145/ 262839.263061

  61. [61]

    Maria Elizabeth G. Ong. Uniform refinement of a tetrahedron.SIAM Journal on Scientific Computing, 15(5):1134–1144, 1994.doi:10.1137/0915070

  62. [62]

    Meshing volumes with curved boundaries.Engineering with Computers, 26(3):265–279, May 2010

    Steve Oudot, Laurent Rineau, and Mariette Yvinec. Meshing volumes with curved boundaries.Engineering with Computers, 26(3):265–279, May 2010. doi:10.1007/ s00366-009-0166-x. 59

  63. [63]

    Remarques sur un résultat non publié de B

    Gilles Pisier. Remarques sur un résultat non publié de B. Maurey. InSéminaire d’Analyse Fonctionnelle 1980–1981. École Polytechnique, Palaiseau, 1981. Exp. No. V, 13 pp

  64. [64]

    Plaza and G.F

    A. Plaza and G.F. Carey. Local refinement of simplicial grids based on the skele- ton.Applied Numerical Mathematics, 32(2):195–218, February 2000.doi:10.1016/ s0168-9274(99)00022-7

  65. [65]

    Optimality of the Delaunay triangulation inRd

    Vadakkedathu T Rajan. Optimality of the Delaunay triangulation inRd. InProceedings of the Seventh Annual Symposium on Computational Geometry, SCG ’91, page 357–363, New York, NY, USA, 1991. Association for Computing Machinery. doi:10.1145/ 109648.109688

  66. [66]

    Optimality of the Delaunay triangulation inRd.Discrete & Computational Geometry, 12(2):189–202, 1994.doi:10.1007/BF02574375

    Vadakkedathu T Rajan. Optimality of the Delaunay triangulation inRd.Discrete & Computational Geometry, 12(2):189–202, 1994.doi:10.1007/BF02574375

  67. [67]

    Approximate Carathéodory bounds via discrepancy theory, 2022.arXiv:2207.03614,doi:10.48550/arXiv.2207.03614

    Victor Reis and Thomas Rothvoss. Approximate Carathéodory bounds via discrepancy theory, 2022.arXiv:2207.03614,doi:10.48550/arXiv.2207.03614

  68. [68]

    Van Kreveld and B

    Laurent Rineau and Mariette Yvinec. A generic software design for Delaunay refinement meshing.Computational Geometry, 38(1-2):100–110, 2007. doi:10.1016/j.comgeo. 2006.11.008

  69. [69]

    Mesh refinement processes based on the generalized bisection of simplices.SIAM Journal on Numerical Analysis, 21(3):604–613, 1984.doi:10.1137/ 0721042

    Maria-Cecilia Rivara. Mesh refinement processes based on the generalized bisection of simplices.SIAM Journal on Numerical Analysis, 21(3):604–613, 1984.doi:10.1137/ 0721042

  70. [70]

    A Delaunay refinement algorithm for quality 2-dimensional mesh genera- tion.Journal of Algorithms, 18(3):548–585, 1995.doi:10.1006/jagm.1995.1021

    Jim Ruppert. A Delaunay refinement algorithm for quality 2-dimensional mesh genera- tion.Journal of Algorithms, 18(3):548–585, 1995.doi:10.1006/jagm.1995.1021

  71. [71]

    Tetrahedral mesh generation by Delaunay refinement

    Jonathan Richard Shewchuk. Tetrahedral mesh generation by Delaunay refinement. In Proceedings of the fourteenth annual symposium on Computational geometry - SCG ’98, SCG ’98, page 86–95. ACM Press, 1998.doi:10.1145/276884.276894

  72. [72]

    Delaunay refinement algorithms for triangular mesh genera- tion.Computational Geometry, 22(1-3):21–74, May2002.doi:10.1016/s0925-7721(01) 00047-5

    Jonathan Richard Shewchuk. Delaunay refinement algorithms for triangular mesh genera- tion.Computational Geometry, 22(1-3):21–74, May2002.doi:10.1016/s0925-7721(01) 00047-5

  73. [73]

    Locally equiangular triangulations.The Computer Journal, 21(3):243–245, 1978.doi:10.1093/comjnl/21.3.243

    Robin Sibson. Locally equiangular triangulations.The Computer Journal, 21(3):243–245, 1978.doi:10.1093/comjnl/21.3.243

  74. [74]

    CGAL Editorial Board, 6.1 edition, 2025

    The CGAL Project.CGAL User and Reference Manual. CGAL Editorial Board, 6.1 edition, 2025. URL:https://doc.cgal.org/6.1/Manual/packages.html

  75. [75]

    Simplicial Approximation to CW Complexes with Spherical Delaunay Triangulations

    Raphaël Tinarrage. Simplicial Approximation to CW Complexes with Spherical Delaunay Triangulations. In Hee-Kap Ahn, Michael Hoffmann, and Amir Nayyeri, editors,42nd International Symposium on Computational Geometry (SoCG 2026), volume 367 of Leibniz International Proceedings in Informatics (LIPIcs), pages 93:1–93:22, Dagstuhl, Germany, 2026. Schloss Dagst...

  76. [76]

    C.D. Toth, J. O’Rourke, and J.E. Goodman.Handbook of Discrete and Com- putational Geometry (3rd ed.). Chapman and Hall/CRC, November 2017. doi: 10.1201/9781315119601

  77. [77]

    Cambridge University Press, 2nd edition, 2026

    Roman Vershynin.High-Dimensional Probability: An Introduction with Applications in Data Science. Cambridge University Press, 2nd edition, 2026. URL:https://www. math.uci.edu/~rvershyn/papers/HDP-book/HDP-2.pdf

  78. [78]

    Computer Graphics Forum , author =

    K. Weiss and L. De Floriani. Simplex and diamond hierarchies: Models and ap- plications.Computer Graphics Forum, 30(8):2127–2155, November 2011. doi: 10.1111/j.1467-8659.2011.01853.x

  79. [79]

    Successive subdivisions of tetrahedra and multigrid methods on tetrahedral meshes.Houston J

    Shangyou Zhang. Successive subdivisions of tetrahedra and multigrid methods on tetrahedral meshes.Houston J. Math, 21(3):541–556, 1995. URL: https://drive. google.com/file/d/15wC5RaMkmrsFobsoLCaMdW_aG9rUVzQe/view

  80. [80]

    Zomorodian.Topology for Computing

    Afra J. Zomorodian.Topology for Computing. Cambridge University Press, January 2005.doi:10.1017/cbo9780511546945

Showing first 80 references.