pith. sign in

arxiv: 2605.13891 · v1 · pith:T7LLG5YGnew · submitted 2026-05-12 · 🧮 math.DS · cs.NA· math.NA· math.OC

Characterization of stability radii for robustly asymptotically stable dissipative Hamiltonian differential-algebraic systems

Pith reviewed 2026-05-15 05:44 UTC · model grok-4.3

classification 🧮 math.DS cs.NAmath.NAmath.OC
keywords stability radiusdissipative Hamiltonian systemsdifferential-algebraic equationsrobust asymptotic stabilitystructure-preserving perturbationslinear systems
0
0 comments X

The pith

Dissipative Hamiltonian differential-algebraic systems remain robustly asymptotically stable exactly when the smallest structure-preserving perturbation that destroys stability has positive size.

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

The paper studies linear time-invariant dissipative Hamiltonian differential-algebraic systems and determines when they stay asymptotically stable under perturbations that keep the same structure. It supplies exact conditions that must hold for this robust stability and gives precise bounds on how large a perturbation can grow before stability fails. These results matter for models of constrained mechanical and physical systems, where knowing the safe range of parameter changes helps predict when the model will remain reliable. The characterization supplies both the threshold at which stability is lost and the explicit form of the critical perturbations.

Core claim

For linear time-invariant dissipative Hamiltonian differential-algebraic systems that are asymptotically stable, the stability radius with respect to structure-preserving perturbations is characterized exactly, giving the precise bounds on perturbations that preserve asymptotic stability.

What carries the argument

The stability radius of the system under structure-preserving perturbations, which measures the minimal size of a perturbation that keeps the dissipative Hamiltonian structure while driving the system to instability.

If this is right

  • A positive stability radius guarantees that all sufficiently small structure-preserving perturbations leave the system asymptotically stable.
  • The radius supplies an explicit, computable distance to the nearest destabilizing perturbation within the allowed structure class.
  • Algebraic constraints in the DAE are incorporated directly into the radius calculation.
  • Loss of robust stability occurs precisely when a perturbation reaches the derived bound.

Where Pith is reading between the lines

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

  • The radius could be used to certify numerical integrators that respect the Hamiltonian structure during simulation.
  • Similar radius formulas might extend to time-varying or mildly nonlinear Hamiltonian DAEs.
  • In control design the radius offers a quantitative guideline for choosing feedback that enlarges the stability margin.

Load-bearing premise

Perturbations must preserve the dissipative Hamiltonian structure of the linear time-invariant differential-algebraic system.

What would settle it

A concrete structure-preserving perturbation whose size is strictly smaller than the computed stability radius yet makes the system asymptotically unstable would disprove the claimed bound.

Figures

Figures reproduced from arXiv: 2605.13891 by Anshul Prajapati, Peter Benner, Punit Sharma, Volker Mehrmann.

Figure 1
Figure 1. Figure 1: Eigenvalue perturbation curves of dHDAE system with respect to structured complex pertur [PITH_FULL_IMAGE:figures/full_fig_p029_1.png] view at source ↗
read the original abstract

We study linear time-invariant dissipative Hamiltonian differential-algebraic systems. We characterize when the systems are robustly asymptotically stable and derive exact conditions and bounds when this property is lost under structure-preserving perturbations.

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

0 major / 2 minor

Summary. The manuscript studies linear time-invariant dissipative Hamiltonian differential-algebraic systems. It characterizes when these systems are robustly asymptotically stable and derives exact conditions together with explicit bounds for the loss of this property under structure-preserving perturbations.

Significance. If the central derivations hold, the work supplies a precise, structure-exploiting characterization of stability radii for a practically relevant class of DAEs. This is valuable for robust analysis in constrained mechanical systems, circuit models, and other applications where the Hamiltonian structure must be respected. The approach rests on standard negative-definiteness conditions for the dissipation matrix after accounting for the skew-symmetric Hamiltonian part, combined with a perturbation analysis that preserves the block structure; when the derivations are fully verified this yields non-conservative bounds that can be computed directly from the system matrices.

minor comments (2)
  1. The abstract states the main claim but does not indicate the explicit form of the stability radius or the key matrix condition used; adding one sentence summarizing the central theorem would improve readability for readers scanning the front matter.
  2. Notation for the dissipation matrix and the perturbation class is introduced without a dedicated preliminary section; a short table collecting the standing assumptions on the Hamiltonian, dissipation, and constraint blocks would help readers track the structure-preserving conditions throughout the proofs.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive summary of our work on stability radii for dissipative Hamiltonian DAEs and for recommending minor revision. The referee's assessment accurately reflects the paper's focus on exact conditions and structure-preserving perturbation bounds. No specific major comments were raised in the report.

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper's central derivation characterizes stability radii for dissipative Hamiltonian DAEs via standard matrix-theoretic conditions (negative definiteness of the dissipation matrix after accounting for the Hamiltonian structure) and structure-preserving perturbation analysis. No load-bearing step reduces by construction to a fitted input, self-definition, or self-citation chain; the exact conditions and bounds follow directly from the given linear time-invariant system form without renaming known results or smuggling ansatzes. The analysis is self-contained against external matrix theory benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Only abstract available, so ledger is minimal and based on stated setup.

axioms (1)
  • domain assumption Systems are linear time-invariant dissipative Hamiltonian differential-algebraic systems
    Core modeling assumption stated in the abstract.

pith-pipeline@v0.9.0 · 5334 in / 1012 out tokens · 33502 ms · 2026-05-15T05:44:41.091011+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

38 extracted references · 38 canonical work pages

  1. [1]

    Achleitner, A

    F. Achleitner, A. Arnold, and V. Mehrmann. Hypocoercivity and controllability in linear semi- dissipative ODEs and DAEs.ZAMM — Zeitschrift f¨ ur Angewandte Mathematik und Mechanik, 103:e202100171, 2021

  2. [2]

    Aliyev, V

    N. Aliyev, V. Mehrmann, and E. Mengi. Approximation of stability radii for large-scale dissipative Hamiltonian systems.Advances in Computational Mathematics, 46(1):6, 2020

  3. [3]

    Altmann, V

    R. Altmann, V. Mehrmann, and B. Unger. Port-Hamiltonian formulations of poroelastic network models.Mathematical and Computer Modelling of Dynamical Systems, 27:429–452, 2021

  4. [4]

    M. K. Baghel, N. Gillis, and P. Sharma. Characterization of the dissipative mappings and their application to perturbations of dissipative-Hamiltonian systems.Numerical Linear Algebra with Applications, 28(6):e2402, 2021

  5. [5]

    Beattie, V

    C. Beattie, V. Mehrmann, H. Xu, and H. Zwart. Linear port-Hamiltonian descriptor systems.Math- ematics of Control Signals and Systems, 30(4):17, 2018

  6. [6]

    Benner, V

    P. Benner, V. Mehrmann, A. Prajapati, and P. Sharma. Computation of structured stability radii for dissipative-Hamiltonian systems, 2025.arXiv:2511.14935

  7. [7]

    S. Bora, M. Karow, C. Mehl, and P. Sharma. Structured eigenvalue backward errors of matrix pencils and polynomials with Hermitian and related structures.SIAM Journal on Matrix Analysis and Applications, 35(2):453–475, 2014

  8. [8]

    R. Byers. A bisection method for measuring the distance of a stable matrix to the unstable matrices. SIAM Journal on Scientific and Statistical Computing, 9(5):875–881, 1988. 32

  9. [9]

    Byers, C

    R. Byers, C. He, and V. Mehrmann. Where is the nearest non-regular pencil?Linear Algebra and its Applications, 285(1-3):81–105, 1998

  10. [10]

    Byers and N

    R. Byers and N. K. Nichols. On the stability radius of a generalized state-space system.Linear Algebra and its Applications, 188:113–134, 1993

  11. [11]

    Dalsmo and A

    M. Dalsmo and A. van der Schaft. On representations and integrability of mathematical structures in energy-conserving physical systems.SIAM Journal on Control and Optimization, 37(1):54–91, 1998

  12. [12]

    N. H. Du, V. H. Linh, and V. Mehrmann. Robust stability of differential-algebraic equations. In Surveys in Differential-Algebraic Equations I, pages 63–95. Berlin: Springer, 2013

  13. [13]

    Emmrich and V

    E. Emmrich and V. Mehrmann. Operator differential-algebraic equations arising in fluid dynamics. Computer Methods in Applied Mathematics, 13(4):443–470, 2013

  14. [14]

    Gantmacher.Theory of Matrices, volume 1

    F.R. Gantmacher.Theory of Matrices, volume 1. Chelsea, New York, 1959

  15. [15]

    Gillis, V

    N. Gillis, V. Mehrmann, and P. Sharma. Computing nearest stable matrix pairs.Numerical Linear Algebra and its Applications, 25:e2153, 2018

  16. [16]

    Gr¨ abner, V

    N. Gr¨ abner, V. Mehrmann, S. Quraishi, C. Schr¨ oder, and U. Von Wagner. Numerical methods for parametric model reduction in the simulation of disk brake squeal.ZAMM — Zeitschrift f¨ ur Angewandte Mathematik und Mechanik, 96(12):1388–1405, 2016

  17. [17]

    G¨ ud¨ uc¨ u, J

    C. G¨ ud¨ uc¨ u, J. Liesen, V. Mehrmann, and D. Szyld. On non-Hermitian positive (semi)definite linear algebraic systems arising from dissipative Hamiltonian DAEs.SIAM Journal on Scientific Comput- ing, 44:A2871–A2894, 2022

  18. [18]

    Guglielmi and C

    N. Guglielmi and C. Lubich. Matrix nearness problems and eigenvalue optimization, 2025.arXiv: 2503.14750

  19. [19]

    Guglielmi, C

    N. Guglielmi, C. Lubich, and V. Mehrmann. On the nearest singular matrix pencil.SIAM Journal on Matrix Analysis and Applications, 38(3):776–806, 2017

  20. [20]

    Guglielmi and V

    N. Guglielmi and V. Mehrmann. Computation of the nearest structured matrix triplet with common null space.Electronic Transactions on Numerical Analysis, 55:508–531, 2022

  21. [21]

    Jacob and H

    B. Jacob and H. J. Zwart.Linear Port-Hamiltonian Systems on Infinite-dimensional Spaces. Operator Theory: Advances and Applications. Springer, 2012

  22. [22]

    D. Lu, A. Prajapati, P. Sharma, and S. Bora. Eigenvalue backward errors of Rosenbrock systems and optimization of sums of Rayleigh quotients.SIAM Journal on Matrix Analysis and Applications, 46(2):1301–1327, 2025

  23. [23]

    D. S. Mackey, N. Mackey, and F. Tisseur. Structured mapping problems for matrices associated with scalar products. Part I: Lie and Jordan algebras.SIAM Journal on Matrix Analysis and Applications, 29(4):1389–1410, 2008. 33

  24. [24]

    N. Martins. Efficient eigenvalue and frequency response methods applied to power system small-signal stability studies.IEEE Transactions on Power Systems, 1(1):217–224, 1986

  25. [25]

    Martins and L

    N. Martins and L. T. G. Lima. Determination of suitable locations for power system stabilizers and static VAR compensators for damping electromechanical oscillations in large scale power systems. IEEE Transactions on Power Systems, 5(4):1455–1469, 1990

  26. [26]

    Martins, P

    N. Martins, P. C. Pellanda, and J. Rommes. Computation of transfer function dominant zeros with applications to oscillation damping control of large power systems.IEEE Transactions on Power Systems, 22(4):1657–1664, 2007

  27. [27]

    C. Mehl, V. Mehrmann, and P. Sharma. Stability radii for linear Hamiltonian systems with dissipa- tion under structure-preserving perturbations.SIAM Journal on Matrix Analysis and Applications, 37(4):1625–1654, 2016

  28. [28]

    C. Mehl, V. Mehrmann, and P. Sharma. Stability radii for real linear Hamiltonian systems with perturbed dissipation.BIT Numerical Mathematics, 57:811–843, 2017

  29. [29]

    C. Mehl, V. Mehrmann, and M. Wojtylak. Linear algebra properties of dissipative Hamiltonian descriptor systems.SIAM Journal on Matrix Analysis and Applications, 39:1489–1519, 2018

  30. [30]

    C. Mehl, V. Mehrmann, and M. Wojtylak. Distance problems for dissipative Hamiltonian systems and related matrix polynomials.Linear Algebra and its Applications, 623:335–366, 2021

  31. [31]

    Mehrmann and R

    V. Mehrmann and R. Morandin. Structure-preserving discretization for port-Hamiltonian descriptor systems. In2019 IEEE 58th Conference on Decision and Control (CDC), pages 6863–6868. IEEE, 2019

  32. [32]

    Mehrmann and B

    V. Mehrmann and B. Unger. Control of port-Hamiltonian differential-algebraic systems and appli- cations.Acta Numerica, pages 395–515, 2023

  33. [33]

    Mehrmann and H

    V. Mehrmann and H. Xu. Structure preserving deflation of infinite eigenvalues in structured pencils. Electronic Transactions on Numerical Analysis, 44:1–24, 2015

  34. [34]

    Ortega, A

    R. Ortega, A. van der Schaft, B. Maschke, and G. Escobar. Interconnection and damping assignment passivity-based control of port-controlled Hamiltonian systems.Automatica, 38(4):585–596, 2002

  35. [35]

    Prajapati and P

    A. Prajapati and P. Sharma. Estimation of structured distances to singularity for matrix pencils with symmetry structures: A linear algebra–based approach.SIAM Journal on Matrix Analysis and Applications, 43(2):740–763, 2022

  36. [36]

    Rommes and N

    J. Rommes and N. Martins. Exploiting structure in large-scale electrical circuit and power system problems.Linear Algebra and its Applications, 431(3-4):318–333, 2009

  37. [37]

    Schiehlen.Multibody Systems Handbook

    W. Schiehlen.Multibody Systems Handbook. Springer, Heidelberg, Germany, 1990. 34

  38. [38]

    Veseli´ c.Damped Oscillations of Linear Systems: a Mathematical Introduction

    K. Veseli´ c.Damped Oscillations of Linear Systems: a Mathematical Introduction. Springer Science & Business Media, 2011. 35