Taylor Tube Method for Validated IVP
Pith reviewed 2026-05-10 02:30 UTC · model grok-4.3
The pith
Higher-degree Taylor Tubes generalize the Euler Tube to refine enclosures more accurately in validated IVP solvers and can reduce overall runtime when paired with bisection.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The Taylor Tube of degree p is the direct generalization of the Euler Tube; it supplies a technique for refining enclosures that improves accuracy with larger p and, when combined with bisection, yields an overall speedup on the tested problems despite the higher per-step cost.
What carries the argument
The Taylor Tube of degree p, a higher-order enclosure refinement operator that replaces the first-order Euler Tube inside the validated IVP architecture.
If this is right
- Accuracy of the computed enclosures rises monotonically with the Taylor degree p.
- When bisection is used to control step size, the net number of steps can fall enough to produce a runtime reduction.
- The same complexity-bound technique previously derived for the Euler Tube extends to the higher-degree Taylor Tube.
- The overall validated IVP solver becomes tunable by choice of p rather than fixed at the first-order case.
Where Pith is reading between the lines
- An adaptive strategy that chooses p locally according to local Lipschitz constants or enclosure widths might further improve performance.
- The same degree-raising idea could be applied to other enclosure operators used in validated numerics beyond IVPs.
- Rigorous complexity analysis for arbitrary p would clarify the asymptotic tradeoff between per-step work and global step count.
Load-bearing premise
The extra cost of computing and enclosing higher-degree Taylor expansions is more than repaid by fewer bisection steps on the problems examined.
What would settle it
A benchmark suite of IVPs in which raising p always increases total runtime because the growth in enclosure computation exceeds any drop in bisection count.
read the original abstract
We recently introduced a novel architecture for the design of validated IVP algorithms. This architecture forms the basis of our complete validated algorithm for IVP. A key subroutine in our algorithm is the \textbf{Euler Tube}: it gave a technique for refining end- and full-enclosures and is also key to deriving a complexity bound of our IVP solver. In this paper, we generalize it to \textbf{Taylor Tube} of degree $p\ge 1$. As expected, higher-degree Taylor Tubes improve accuracy. But surprisingly, our experiments show that it can also lead to an overall speedup when combined with bisection.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper generalizes the authors' prior Euler Tube construction to Taylor Tubes of degree p ≥ 1 for use as a subroutine in validated IVP solvers. It supplies explicit enclosure formulas for the higher-degree tubes, argues that they tighten end- and full-enclosures, and reports experiments showing that the accuracy gain can reduce the number of bisection steps enough to produce a net speedup on the tested problems.
Significance. If the reported timing results and enclosure bounds hold under scrutiny, the work supplies a concrete, implementable improvement to validated integration that trades per-step cost for fewer refinement steps. The explicit formulas and the empirical observation that bisection savings can dominate are the main contributions; they are scoped to the concrete IVPs examined rather than claimed as universal.
major comments (2)
- §4, the complexity argument for the base Euler Tube: the claimed O(1) cost per tube evaluation appears to assume that the interval arithmetic operations for the Taylor coefficients remain constant-time independent of p; this needs an explicit operation count that accounts for the growth in the number of coefficients with degree.
- Table 2, rows for p=3 and p=4 on the Lorenz system: the reported wall-clock times show speedup, but the table does not list the number of bisection steps or the final enclosure widths; without these, it is impossible to verify that the speedup is due to fewer bisections rather than implementation artifacts.
minor comments (2)
- The notation for the Taylor Tube enclosure operator is introduced without a clear distinction between the pointwise Taylor polynomial and its interval enclosure; a short paragraph clarifying the two would help readers.
- Several references to the earlier Euler Tube paper are given only by title; adding the arXiv identifier or journal citation would make the dependency explicit.
Simulated Author's Rebuttal
We thank the referee for the careful reading, positive assessment, and recommendation of minor revision. We address each major comment below and will revise the manuscript accordingly.
read point-by-point responses
-
Referee: §4, the complexity argument for the base Euler Tube: the claimed O(1) cost per tube evaluation appears to assume that the interval arithmetic operations for the Taylor coefficients remain constant-time independent of p; this needs an explicit operation count that accounts for the growth in the number of coefficients with degree.
Authors: We appreciate the referee's observation. The O(1) claim in §4 applies specifically to the Euler Tube (p=1), where the number of Taylor coefficients is a fixed constant and each interval operation is treated as constant time. For the generalized Taylor Tubes, the number of coefficients grows linearly with p, so the per-tube cost is O(p) arithmetic operations. We will revise §4 to include an explicit operation count that makes this dependence on p transparent, while preserving the overall complexity bound for the IVP solver when p is regarded as a fixed parameter. revision: yes
-
Referee: Table 2, rows for p=3 and p=4 on the Lorenz system: the reported wall-clock times show speedup, but the table does not list the number of bisection steps or the final enclosure widths; without these, it is impossible to verify that the speedup is due to fewer bisections rather than implementation artifacts.
Authors: We agree that the additional data would strengthen the empirical claims and enable direct verification. In the revised version we will augment Table 2 (and, where appropriate, other tables) with columns reporting the number of bisection steps performed and the final enclosure widths for each degree p on the Lorenz system. This will make explicit that the observed speedups result from fewer bisections enabled by tighter enclosures. revision: yes
Circularity Check
Minor self-citation to prior Euler Tube work; new generalization and experiments are independent
full rationale
The paper generalizes the authors' prior Euler Tube construction to Taylor Tubes of degree p with explicit enclosure formulas and reports experimental timing results showing net speedup under bisection for tested IVPs. The central claims rest on these new constructions and observations rather than reducing by construction to fitted parameters or prior results. The self-citation to the Euler Tube paper supports the base architecture and complexity bound but is not load-bearing for the higher-degree formulas or the empirical speedup claim, which is presented as an observed fact outside any derivation. No equations equate new outputs to inputs by definition, and the work remains self-contained against the supplied experimental benchmarks.
Axiom & Free-Parameter Ledger
axioms (1)
- standard math Taylor theorem with remainder provides a rigorous enclosure for the solution flow
invented entities (1)
-
Taylor Tube
no independent evidence
Reference graph
Works this paper leans on
-
[2]
Corliss, G.F.: Survey of interval algorithms for ordinary differential equations. Appl.Math.Comp. 31 (1989)
work page 1989
-
[3]
Springer-Verlag, Berlin, second revised edn
Hairer, E., N rsett, S.P., Wanner, G.: Solving Ordinary Differential Equations I: Nonstiff Problems. Springer-Verlag, Berlin, second revised edn. (2008)
work page 2008
-
[4]
In: Floudas, C.A., Pardalos, P.M
Moore, R.: Interval A nalysis: Differential E quations. In: Floudas, C.A., Pardalos, P.M. (eds.) Encyclopedia of Optimization, pp. 1686--1689. Springer, 2nd edn. (2009)
work page 2009
-
[5]
Applied Mathematics and Computation 105(1), 21--68 (1999)
Nedialkov, N.S., Jackson, K.R., Corliss, G.F.: Validated solutions of initial value problems for ordinary differential equations. Applied Mathematics and Computation 105(1), 21--68 (1999)
work page 1999
-
[6]
Nedialkov, N.S.: Computing Rigorous Bounds on the Solution of an Initial Value Problem for an Ordinary Differential Equation. Ph.D. thesis, Department of Computer Science, University of Toronto (1999)
work page 1999
-
[7]
Neumaier, A.: Global, rigorous, and realistic bounds for the solution of dissipative differential equations. Part I: Theory . Computing 52, 315--336 (1994)
work page 1994
-
[8]
Physics Letters A 57(5), 397--398 (1976)
R \"o ssler, O.: An equation for continuous chaos. Physics Letters A 57(5), 397--398 (1976)
work page 1976
-
[11]
Validated Numerics: A short intro to rigorous computations
Warwick Tucker. Validated Numerics: A short intro to rigorous computations
- [12]
- [13]
-
[14]
Ramon E. Moore. Interval Analysis
- [15]
- [16]
-
[17]
Condensing Multivalued Maps and Semilinear Differential Inclusions in Banach Spaces
Kamenskii, Mikhail I. Condensing Multivalued Maps and Semilinear Differential Inclusions in Banach Spaces
-
[18]
Sainz and Joaquim Armengol and Remei Calm and Pau Herrero and Lambert Jorba and Josep Vehi
Miguel A. Sainz and Joaquim Armengol and Remei Calm and Pau Herrero and Lambert Jorba and Josep Vehi. Modal interval analysis : new tools for numerical information
-
[19]
Luc Jaulin and Michel Kieffer and Olivier Didrit and Eric Walter. Applied Interval Analysis With Examples in Parameter and State Estimation, Robust Control and Robotics
-
[20]
Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems
Ernst Hairer and Gerhard Wanner. Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems
- [21]
-
[22]
Ernst Hairer and Syvert P. N rsett and Gerhard Wanner. Solving Ordinary Differential Equations I: Nonstiff Problems
-
[23]
R. A. Anguelov. Aspects of Interval Analysis applied to Initial-Value Problems for Ordinary Differential Equations and Hyperbolic Partial Differential Equations
-
[24]
Towards More Efficient Interval Analysis: Corner Forms and a Remainder Interval Newton Method
Marcel Gavriliu. Towards More Efficient Interval Analysis: Corner Forms and a Remainder Interval Newton Method. doi:doi:10.7907/C196-9R88
-
[25]
Bounding Polynomials and Rational Functions in the Tensorial and Simplicial B ernstein Forms
Tareq Hamadneh. Bounding Polynomials and Rational Functions in the Tensorial and Simplicial B ernstein Forms
-
[26]
Qian, Gang and Sural, Shamik and Gu, Yuelong and Pramanik, Sakti , title=. Proc. ACM Symposium on Applied Computing (SAC'04) , pages =
-
[27]
Differential Inclusions and Target Problems
Marc Quincampoix. Differential Inclusions and Target Problems. SIAM J. Control and Optimization. doi:https://doi.org/10.1137/0330020
- [28]
-
[29]
R.A. Lorentz. Multivariate H ermite interpolation by algebraic polynomials: A survey. J. Comp. and Applied Math
-
[30]
Error bounds for polynomial tensor product interpolation
Bernhard M \"o ner and Ulrich Reif. Error bounds for polynomial tensor product interpolation. Computing
-
[31]
G. Birkhoff and M. H. Schultz and Richard Steven Varga. Piecewise H ermite interpolation in One and two variables with applications to partial differential equations. Numerische Mathematik. doi:10.1007/BF02161845
-
[32]
G. Birkhoff and G. Fix. Accurate Eigenvalue Computations for Elliptic Problems. Numerical Solution of Elliptic Problems
-
[33]
P. G. Ciarlet and P. A. Raviart. General L agrange and H ermite interpolation in ^n with applications to finite element methods. Archive for Rational Mechanics and Analysis
-
[34]
S. Lagrange and N. Delanoue and L. Jaulin , title =. Reliable Computing , number = 5, volume = 13, pages =
-
[35]
Raena Farhadsefat and Ji r \' i Rohn and Taher Lotfi. Norms of Interval Matrices
-
[36]
Forty Necessary and Sufficient Conditions for Regularity of Interval Matrices: A Survey
Jiri Rohn. Forty Necessary and Sufficient Conditions for Regularity of Interval Matrices: A Survey. Electronic J. of Linear Algebra
-
[37]
Systems of Linear Interval Equations
Jiri Rohn. Systems of Linear Interval Equations. Linear Algebra and Its Applic
-
[38]
Determinants of interval matrices
Jaroslav Hor\' a c ek and Milan Hlad\' k and Josef Mat e jka. Determinants of interval matrices. Electron. J. Linear Algebra. 2018. doi:10.13001/1081-3810.3719
-
[39]
Siegfried M. Rump. Verified bounds for the determinant of real or complex point or interval matrices. J. Comp. and Appl. Math. doi:https://doi.org/10.1016/j.cam.2019.112610
-
[40]
C. V. Pao. Logarithmic Derivates of a Square Matrix. Linear Algebra and its Appl
-
[41]
Torsten Strom. On Logarithmic Norms. SIAM Journal on Numerical Analysis
-
[42]
M. Vidyasagar. On matrix measures and convex L iapunov functions. J. Mathematical Analysis and Applic
-
[43]
Gustaf S \" o derlind. The logarithmic norm. History and modern theory. BIT Numerical Mathematics
-
[44]
Global, Rigorous, and Realistic Bounds for the Solution of Dissipative Differential Equations
Arnold Neumaier. Global, Rigorous, and Realistic Bounds for the Solution of Dissipative Differential Equations. Part I: Theory. Computing
-
[45]
Global, rigorous and realistic bounds for the solution of dissipative differential equations
Arnold Neumaier. Global, rigorous and realistic bounds for the solution of dissipative differential equations. P art I : Theory
-
[46]
Rigorous Sensitivity Analysis for Parameter-Dependent Systems of Equations
Arnold Neumaier. Rigorous Sensitivity Analysis for Parameter-Dependent Systems of Equations. J. Math. Anal. Appl
-
[47]
The Wrapping Effect, Ellipsoid Arithmetic, Stability and Confidence Regions
Arnold Neumaier. The Wrapping Effect, Ellipsoid Arithmetic, Stability and Confidence Regions. Computing Supplementum
-
[48]
Manchester and Mark Tobenkin and John W
Russ Tedrake and Ian R. Manchester and Mark Tobenkin and John W. Roberts. LQR-Trees : Feedback Motion Planning via Sum-of-Squares Verification. Intl. J. Robotics Research
-
[49]
Funnel libraries for real-time robust feedback motion planning
Majumdar, Anirudha and Tedrake, Russ. Funnel libraries for real-time robust feedback motion planning. Int'l J. of Robotics Research. doi:10.1177/0278364917712421
-
[51]
Computing Funnels Using Numerical Optimization Based Falsifiers , journal =
Jir. Computing Funnels Using Numerical Optimization Based Falsifiers , journal =. 2109.11420 , year =
-
[52]
E.Adams and W.F. Ames. On Contracting Interval Iterations for Nonlinear Problems in ^n , Part I : Theory. Nonlinear Analysis, Theory, Methods & Applic
-
[53]
R.E. Moore. Interval A nalysis: Differential E quations. Encyclopedia of Optimization
-
[55]
Hans J. Stetter , editor =. Validated Solution of Initial Value Problems for. Computer Arithmetic and Self-Validating Numerical Methods , series =. doi:10.1016/B978-0-12-708245-5.50014-2 , biburl =
-
[56]
Corliss and Andreas Griewank and Petra Henneberger and Gabriela Kirlinger and Florian A
George F. Corliss and Andreas Griewank and Petra Henneberger and Gabriela Kirlinger and Florian A. Potra and Hans J. Stetter , editor =. High-Order Stiff. Numerical Analysis and Its Applications, First International Workshop, WNAA'96, Rousse, Bulgaria, June 24-26, 1996, Proceedings , series =. doi:10.1007/3-540-62598-4\_85 , year =
-
[57]
G. F. Corliss. Survey of Interval Algorithms for ordinary differential equations. Appl.Math.Comp
-
[58]
George F. Corliss and Robert Rihm. Validating an A Priori Enclosure Using High-Order T aylor Series. Scientific Computing, Computer Arithmetic, and Validated Numerics
-
[59]
Nedialko Stoyanov Nedialkov. Computing Rigorous Bounds on the Solution of an Initial Value Problem for an Ordinary Differential Equation
- [60]
-
[61]
K.R. Jackson and N. S. Nedialkov. Some Recent Advances in Validated Methods for IVPs for ODEs. Applied Numerical Mathematics
-
[62]
N. S. Nedialkov and K. R. Jackson and and J. D. Pryce. An Effective High-Order Interval Method for Validating Existence and Uniqueness of the Solution of an IVP for an ODE. Reliable Computing
-
[63]
M. Neher and K.R. Jackson and N.S. Nedialkov. On Taylor model based integration of ODEs. SIAM J. on Numerical Analysis
-
[64]
N. S. Nedialkov and K. R. Jackson and G. F. Corliss. Validated solutions of initial value problems for ordinary differential equations. Applied Mathematics and Computation
-
[65]
Y. F. Chang and G. F. Corliss. ATOMFT : Solving ODE s and DAE s using T aylor Series. Comp.Math.Appl
-
[66]
Mathematical Centre Tracts ,publisher=
The solution of initial value problems using interval arithmetic: formulation and analysis of an algorithm ,author=. Mathematical Centre Tracts ,publisher=
-
[67]
Topics in validated computations: Proc
Interval methods for initial value problems in ODEs , author=. Topics in validated computations: Proc. of the IMACS-GAMM Int'l Workshop on Validated Computations , series=
-
[68]
K. Makino and M. Berz. Higher order verified inclusions of multidimensional systems by T aylor models. Nonlinear Analysis: Theory, Methods & Applications
-
[69]
Computation and Application of T aylor Polynomials with Interval Remainder Bounds
Martin Berz and Georg Hoffst \"a tter. Computation and Application of T aylor Polynomials with Interval Remainder Bounds. J. Reliable Computing
-
[70]
A study of rigorous ODE integrators for multi-scale set-oriented computations
Tomoyuki Miyaji and Pawel Pilarczyk and Marcio Gameiro and Hiroshi Kokubu and Konstantin Mischaikow. A study of rigorous ODE integrators for multi-scale set-oriented computations. Appl. Num. Math
-
[71]
Olivier Bournez and Daniel S. Gra\' c a and Amaury Pouly. Solving Analytic Differential Equations in Polynomial Time over Unbounded Domains. MFCS'11: Proc. 36th Int'l Conf. Math. Foundations of Computer Sci
-
[72]
A. Edalat and M. Krznarić and A. Lieutier , title =. Electronic Notes in Theoretical Computer Science , volume =. doi:https://doi.org/10.1016/S1571-0661(03)50005-6 , url =
-
[73]
Y. F. Chang and G. Corliss. Ratio Test for Convergence Ratio-Like and Recurrence Relation Tests for Convergence of Series. IMA J. of Appl.Math. doi:https://doi.org/10.1093/imamat/25.4.349
-
[74]
G. Corliss and Y.F. Chang. Solving ordinary differential equations using T aylor series. ACM Trans. Math.Software
-
[75]
kv -- a C++ Library for Verified Numerical Computation
Masahide Kashiwagi. kv -- a C++ Library for Verified Numerical Computation
-
[76]
Preconditioning of T aylor models, implementation and test cases
Florian B \"u nger. Preconditioning of T aylor models, implementation and test cases. Nonlinear Theory and its Applications, IEICE
-
[77]
Florian B. A. J. Comp. and Appl. Math. , volume =. doi:https://doi.org/10.1016/j.cam.2019.112511 , abstract =
-
[78]
Rigorous reachability analysis and domain decomposition of Taylor models
Martin Berz and Kyoko Makino. Rigorous reachability analysis and domain decomposition of Taylor models. Numerical Software Verification. doi:10.1007/978-3-319-63501-9\_7
-
[79]
Rigorous numerics for ODEs using Chebyshev series and domain decomposition
Jan Bouwe van den Berg and Ray Sheombarsing. Rigorous numerics for ODEs using Chebyshev series and domain decomposition. Journal of Computational Dynamics. doi:10.3934/jcd.2021015
-
[80]
VNODE-LP : Interval Solver for IVP in ODE
-
[81]
N. S. Nedialkov. Implementing a Rigorous ODE Solver through Literate Programming. M odeling, D esign, and S imulation of Systems with Uncertainties
-
[82]
N. S. Nedialkov and K. R. Jackson. An Interval H ermite- O breschkoff Method for Computing Rigorous Bounds on the Solution of an Initial Value Problem for an Ordinary Differential Equation. Reliable Computing
-
[83]
N.S. Nedialkov and K.R. Jackson and J.D. Pryce. An effective high-order interval method for validating existence and uniqueness of the solution of an IVP for an ODE. Reliable Computing
-
[84]
R.J. Lohner. Einschlie ung der L \"o sung gew \"o hnlicher Anfangs -- und Randwertaufgaben und Anwendungen
-
[85]
Florent Br \'e hard. 43rd
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.