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Constrained dynamics shake and rattle — Examples
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Connectedness
- Constrained dynamics shake and rattle
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Countability and Uncountability
- Darboux, L'Hôpital, and Taylor's Theorem
- Determinants of Matrices over a Commutative Ring
- Direct Matrix Factorisations: LU, Cholesky and QR
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Hamiltonian Monte Carlo and leapfrog correction
- Implicit stiff time stepping and algebraic error
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Nonlinear equations and Newton methods
- Order, Zorn's Lemma, and the Axiom of Choice
- Picard-Lindelöf and First-Order Ordinary Differential Equations
- Polynomial Rings, the Division Algorithm and Roots
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Symplectic Manifolds, Moser Stability, and Darboux–Weinstein Theory
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Inverse and Implicit Function Theorems
- The Inverse Function Theorem Completed
- The Riemann Integral: Definition and Integrability
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
The examples compute RATTLE for a free rigid bond and derive the constrained multiplier for a pendulum. A pair of nearly dependent constraints shows how the multiplier Schur matrix loses uniform conditioning while each fixed system remains regular. The final example separates scaled solver residuals from their state error and gives the global accumulation envelope on a compact phase tube after local consistency restoration; a fixed residual tolerance alone does not certify convergence as the step is refined.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
The constrained pendulum multiplier follows from tangency
Example
For a planar pendulum of mass and rod length , let , , and . If and , the multiplier in the constrained equations is At the bottom rest state , , this gives and zero acceleration.
Facts & Assumptions
Given: , the constraint and potential in the Example, and consistent data , .
Regular holonomic phase space and constrained dynamics: and , where .
The constrained Hamiltonian vector field has a unique local flow: these equations define the unique local constrained flow for consistent data in the regular chart.
Verification
Here , , , and . Substitution into [F1] gives .
At and , the multiplier is . The acceleration is ; moreover and , so this is a consistent equilibrium of the local flow [F2].
RATTLE gives an exact step and a cubic phase defect for a free rigid bond
Example
Let , , , and . Start from and , and take . The selected exact RATTLE step has Its position constraint and momentum tangency are exact. The exact constrained flow rotates by angle , whereas RATTLE rotates by , so the one-step phase defect is as .
Facts & Assumptions
Given: , the circle constraint, the free-particle potential, initial data, and step range in the Example.
Regular holonomic phase space and constrained dynamics: consistency is and .
Scaled classical RATTLE step map: the exact position and momentum updates use the two force-level multipliers and impose and .
The constrained Hamiltonian vector field has a unique local flow: consistent data evolve by and .
Multivariable Taylor formula with a Lagrange remainder along a line segment: a scalar function on a convex interval has its degree-two Taylor polynomial with a cubic Lagrange remainder.
Verification
The initial data are consistent because and . The position multiplier equation gives ; choosing yields the stated , whose squared norm is . This multiplier tends to , the position branch center.
With , the final RATTLE equation gives the stated ; has the same limit , so the unique local branch selects this root. Direct multiplication gives and , so both exact constraints hold.
The continuous multiplier is , hence the exact flow is and . This solves [F3] and agrees with the initial data. The RATTLE position angle is . Taylor's theorem [F4] on gives . Since is fixed, the angle defect is as stated.
Nearly dependent constraints make the multiplier solve ill conditioned
Example
For , take and The Jacobian has full row rank for every fixed , but has smallest eigenvalue . Thus the inverse multiplier bound in the RATTLE residual estimate is not uniform as the constraints approach dependence. At the rank hypothesis fails.
Facts & Assumptions
Given: The family , , and the RATTLE multiplier matrix in the Example.
Regular holonomic phase space and constrained dynamics: regularity requires full row rank of and invertibility of .
Scaled RATTLE residuals bound the finite solve trajectory error: on a fixed compact phase tube, residual-to-state constants depend in particular on uniform inverse bounds for the multiplier matrices; each fixed is regular, but these inverse bounds are not uniform as .
Verification
The two rows and of are linearly independent exactly when . Their Gram matrix is the displayed , whose trace is and determinant is .
The quadratic formula gives its eigenvalues . Rationalizing the smaller one gives , so and .
Consequently no single residual-to-multiplier constant works for this family as ; this is consistent with [F2], whose uniform estimates assume a fixed compact chart with uniformly bounded . At the two rows coincide, so [F1]'s full-rank hypothesis fails.
A fixed RATTLE residual budget allows an O(epsilon) drift envelope
Example
Fix compact phase tubes in a convex phase-coordinate chart with closure inside a regular chart, and . Put and suppose the exact-solve RATTLE iterates from the common initial state stay in for the grids considered. Suppose every finite RATTLE solve succeeds, its branch iterates stay in the selected local balls over , and its scaled residuals are bounded by a fixed sufficiently small . After each output apply the consistency retraction from Holonomic phase residuals control distance to the consistent phase manifold before the next step. For sufficiently small , the restored trajectory stays in and has an global error envelope relative to exact-solve RATTLE; refinement alone does not force this upper bound to vanish. If both scaled residual tolerances are instead , the global solver contribution is , while the unprojected solver outputs have position and tangency residuals and . These are upper bounds; they do not assert a matching lower bound or that residual tolerances alone certify forward error.
Facts & Assumptions
Given: The compact phase tubes and fixed horizon in the Example, step , successful finite RATTLE solves with multiplier iterates in the selected branch balls, the consistency restoration specified there, and the scaled residual hypotheses.
Scaled RATTLE residuals bound the finite solve trajectory error: on a compact phase tube, for the restored trajectory per-step perturbations are bounded by ; scaled residuals yield an global error relative to exact-solve RATTLE.
Scaled RATTLE equations have unique local multiplier branches: on a compact phase tube the selected exact map is smooth in local coordinates with uniformly bounded derivatives and is the identity at .
On a convex open set, a uniform bound implies : a uniform derivative bound on a convex chart gives the corresponding Lipschitz bound.
Implicit residuals and their update and derivative units: a residual norm is not a forward-error estimate without a separate inverse or stability bound.
Verification
For at every step, [F1] gives, until a first exit from , the recurrence for the restored trajectory. Iteration yields . Choose so this is less than the coordinate distance from to the boundary of ; then no first exit occurs, and the uniform upper-bound envelope holds. It need not shrink as .
If instead , [F1] makes each additive perturbation at most , and the same sum gives global error ; for sufficiently small this is below the tube margin, so again there is no first exit. The unscaled residuals are and .
These bounds rely on the inverse and stability estimates in [F1]. As [F4] states, the residual-tolerance status alone is not a forward-error certificate; the explicit consistency restoration is also part of this repeated-step example.
Sources
- Ernst Hairer, Christian Lubich, and Gerhard Wanner, Geometric Numerical Integration, 2nd ed., Chapter VII.1.1, p. 237
- Robert I. McLachlan, Klas Modin, Olivier Verdier, and Matt Wilkins, Geometric Generalisations of SHAKE and RATTLE, Foundations of Computational Mathematics 14 (2014), 339–370, §5.1
- Ernst Hairer, Christian Lubich, and Gerhard Wanner, Geometric Numerical Integration, 2nd ed., Chapter VII.1.4, pp. 245–246
- Robert I. McLachlan, Klas Modin, Olivier Verdier, and Matt Wilkins, Geometric Generalisations of SHAKE and RATTLE, Foundations of Computational Mathematics 14 (2014), 339–370
- Ernst Hairer, Christian Lubich, and Gerhard Wanner, Geometric Numerical Integration, 2nd ed., Chapter VII.1.4, pp. 245–247
- Robert I. McLachlan, Klas Modin, Olivier Verdier, and Matt Wilkins, Geometric Generalisations of SHAKE and RATTLE, Foundations of Computational Mathematics 14 (2014), 339–370, §5.2
- Robert I. McLachlan, Klas Modin, Olivier Verdier, and Matt Wilkins, Geometric Generalisations of SHAKE and RATTLE, Foundations of Computational Mathematics 14 (2014), 339–370, §4.3