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One-step ODE Consistency and Local Error
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Binary Operations, Monoids, Groups and Subgroups
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Connectedness
- 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
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Metric Spaces
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- Picard-Lindelöf and First-Order Ordinary Differential Equations
- Power Series and Real-Analytic Functions
- 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
- Series: Convergence and the Nonnegative Tests
- Subspaces, Products, and Quotients
- Suprema and Infima
- The Derivative and the Mean Value Theorems
- The Exponential Function
- 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
Summary
Define the local defect and uniform order of a one-step method, together with the one-step Lipschitz bound used to compare inputs in a compact time-state set. Prove the uniform local defect for every admitted start time and step, and the stability bound for forward Euler under explicit component and Jacobian bounds. This page makes no global convergence claim and does not infer higher order from a method's name.
3 · Logical flowchart
4 · Definitions, theorems and proofs
One-step ODE methods, local defect, uniform order, and step stability
Definition
Let , let be open, and consider a first-order IVP and solution in the sense of First-order systems, initial value problems, and solutions on intervals. A one-step method is a family of maps , defined for admitted times , positive step sizes , and states , whose value is the method's approximation at time from the single input state at time . It does not use earlier numerical states.
If is an exact solution on an interval containing , the local defect is
Let be a fixed compact time-state set. The method has uniform local order on along if there are constants and , independent of the admitted starting time and step , such that
whenever the exact solution graph on and the associated method time-state inputs, stages, and outputs under consideration lie in . Here is a positive integer and is the Euclidean norm of The Euclidean inner product on .
The method has one-step Lipschitz stability on with constant if
for every admitted step size , admitted time , and input states with . This is a bound on the change in one step; it is separate from absolute or linear stability regions and does not itself assert a global error estimate.
A vector field along an ODE solution has an explicit derivative bound
Statement
Let , let be open, let have continuous first partial derivatives, and let solve on an open interval . Fix with such that for every . Suppose finite constants satisfy for all
Define and . Then is continuous on , differentiable on , and
Facts & Assumptions
Given: The open ODE domain, continuous first partial derivatives, solution on , and the displayed componentwise bounds.
First-order systems, initial value problems, and solutions on intervals: an IVP solution is differentiable, its graph lies in the open domain, and it satisfies .
If all partial derivatives exist on a neighbourhood and are continuous at a point, then the map is totally differentiable there with Jacobian derivative: continuous first partial derivatives give total differentiability with derivative matrix equal to the Jacobian.
Total differentiability gives a local increment bound and therefore continuity: total differentiability implies continuity.
The chain rule for total derivatives: : the derivative of a composition is the composition of the total derivatives.
Proof
By [F2]–[F3], is continuous on . Since , the derivative of is continuous on ; hence is continuously differentiable and the path has derivative .
For each , the component map is totally differentiable, so [F4] applied to gives the displayed derivative formula. The bounds give for every . Continuity of on follows from continuity of and .
Forward Euler has uniform local order one and a one-step Lipschitz bound
Statement
Let , , and let be an open time-state domain whose fibers are open and convex. Let be compact. Let have continuous first partial derivatives, and suppose is a solution of , , on an open interval containing , with graph on contained in . For each local defect under consideration, require the Euler input and output time-state pairs to lie in ; the exact solution segment already lies in .
For , assume finite constants satisfy throughout
Here is the matrix with entries , and the last inequality defines the operator bound used below. The forward Euler map is . Then, with , for every and with whose Euler input and output pairs lie in , its local defect satisfies
so it has uniform local order one on along , with . For every , every admitted , and every ,
This is a local defect and one-step stability result. It does not assert a global error estimate or an order for any other named method.
Facts & Assumptions
Given: The stated open ODE domain with open convex state fibers, continuous first partial derivatives and bounds, the solution through on an open interval containing , the compact set containing its graph and the Euler time-state pairs under consideration, and the definition of uniform local order.
One-step ODE methods, local defect, uniform order, and step stability: ; uniform local order one means a uniform defect; one-step Lipschitz stability is the displayed bound.
First-order systems, initial value problems, and solutions on intervals: an IVP has open time-state domain, and a solution is differentiable on an interval, has graph in the domain, and satisfies and its initial value.
If all partial derivatives exist on a neighbourhood and are continuous at a point, then the map is totally differentiable there with Jacobian derivative: continuous first partial derivatives give a total derivative whose matrix is the Jacobian of those partials.
Total differentiability gives a local increment bound and therefore continuity: total differentiability implies continuity at each point.
A convex subset of contains every line segment between two of its points: a convex set contains the segment between each pair of its points; each open convex state fiber has this property.
On a convex open set, a uniform bound implies : on an open convex Euclidean set, a uniform derivative bound implies .
Every Picard–Lindelöf initial value problem has one maximal solution on an open interval: a continuous vector field locally Lipschitz in the state variable has a unique maximal IVP solution. The given derivative bound and [F3]–[F6] provide that local Lipschitz condition on each state fiber.
A vector field along an ODE solution has an explicit derivative bound: along an exact solution, has derivative bounded by .
A first-order initial value problem is equivalent to its Volterra integral equation: for any initial time on the solution interval, the solution satisfies .
The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with : if a real function is continuous on a closed interval and differentiable in its interior, its endpoint difference is its derivative at an interior point times the interval length.
The Euclidean inner product on : for , .
Cauchy-Schwarz with its equality case, the triangle inequality for , the parallelogram law and polarisation: for , the Euclidean norm satisfies .
Proof
By [F3]–[F4], is totally differentiable and continuous on , with state derivative matrix . On each open convex fiber , the derivative bound and [F5]–[F6] make -Lipschitz. Thus the hypotheses of [F7] hold and the IVP has a unique maximal solution; the given solution agrees with it throughout .
Fix any and with satisfying the stated compact-set condition, and fix a component . Define for . The exact path segment lies in , so [F8] gives on .
For each , [F10] applied to on yields ; at the same inequality is equality.
Apply [F9] to the IVP restarted at ; then . Euler's output from the exact state is , so . Using [step 2.1] gives . Squaring the component bounds, summing, and using [F11] gives the asserted Euclidean norm estimate. Its constant is independent of and , proving uniform local order one under [F1].
For any admitted , , and , [F3] identifies the derivative of with ; [F5]–[F6] give . Therefore [F12] gives , which is the one-step stability bound in [F1] for inputs in .
Remarks
The defect proof is choice-free and uses only the time-along-flow chain rule and the componentwise integral remainder. The Taylor supplier is used by the scalar linear example, not needed to prove this theorem. The global error recurrence in the cited numerical-analysis sources is outside this item.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Ernst Hairer, course notes, Chapter III: Équations Différentielles Ordinaires
- MIT OpenCourseWare, 18.330 Introduction to Numerical Analysis (Spring 2012), Chapter 5
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, Julia Edition, Section 6.2
- Ernst Hairer, course notes, Chapter III: Équations Différentielles Ordinaires, Section III.2
- Ernst Hairer, course notes, Chapter III: Équations Différentielles Ordinaires, Sections III.2–III.3
- MIT OpenCourseWare, 18.330 Introduction to Numerical Analysis (Spring 2012), Chapter 5, Sections 5.2.1–5.2.2
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, Julia Edition, Sections 6.2.1–6.2.2