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Euler–Maruyama Scheme and Coefficient Conditions — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Algebraic Closure, Embeddings, and Separability
- Algebraic Extensions, Extension Degree, and Finite Fields
- Areas of Elementary Plane Figures
- Binary Operations, Monoids, Groups and Subgroups
- Brownian Motion Construction and Continuity
- Brownian Motion, Markov Properties and Hitting Times
- Central Limit Theorems
- Characteristic Functions Inversion and Continuity
- Compactness
- Compactness in Metric Spaces
- Complete Metrizability, Čech-Completeness, and Baire Category
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- Conditional Distributions and Regular Conditional Probability
- Conditional Expectation
- Congruences, the Integers Modulo n and the Chinese Remainder Theorem
- 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
- Convexity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Cyclic Groups and Direct Products
- Darboux, L'Hôpital, and Taylor's Theorem
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Diagonalisation and the Minimal Polynomial
- Discrete Time Martingales
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Divisibility, Greatest Common Divisors and Bézout's Identity
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Euler–Maruyama Scheme and Coefficient Conditions
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Probability and the Probabilistic Method
- Forward Itô SDE Well-Posedness
- Foundations of the Real Numbers for Analysis
- Fourier Transform Convolution and Approximate Identities
- Fubini and Change of Variables
- Function Space Topologies and the Exponential Law
- Fundamental Trigonometric Identities
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Hausdorff via the Diagonal
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Improper and Parameter-Dependent Multiple Integrals
- Improper Integrals
- Independence Borel Cantelli and Zero One Laws
- Infinite Product Measures and Kolmogorov Extension
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Itos Formula and Brownian Martingales
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Martingale Inequalities and Convergence
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Modes of Convergence for Random Variables
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Partitions of Unity and Paracompactness
- Pointwise Extended-Real Function Products
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Primes, Euclid's Lemma and the Fundamental Theorem of Arithmetic
- Probability Spaces Random Variables and Expectation
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Radon Measures and the Riesz Markov Kakutani Theorem
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Signed and Complex Measures Hahn and Jordan
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Splitting Fields
- Subspaces, Products, and Quotients
- Suprema and Infima
- Sylow's Theorems, p-Groups and Nilpotent Groups
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Exponential Function
- The Fundamental Theorem of Algebra
- The Fundamental Theorem of Finite Abelian Groups
- The Galois Correspondence
- The Inverse and Implicit Function Theorems
- The Ito Integral with Respect to Brownian Motion
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- The Radon Nikodym Theorem and Lebesgue Decomposition
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Urysohn's Lemma and the Tietze Extension Theorem
- Vector Spaces, Linear Subspaces, Span and Direct Sums
- Weak Convergence Tightness and Representation
2 · Summary
Objective
The first example computes the grid recursion and continuous interpolation for a scalar additive-noise equation with an exact path and finite moments. The second checks a superlinear drift against the global Lipschitz and linear-growth hypotheses, showing precisely why the uniform-moment theorem does not apply.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
Euler–Maruyama for a constant-coefficient additive-noise equation
Facts & Assumptions
Given: AC, , for an integer , and . Work on a complete filtered probability space whose filtration is right-continuous and contains every null subset in . Let be a scalar standard Brownian motion adapted to this filtration, with independent of for every . Take and .
The Euler–Maruyama step is . Euler–Maruyama recursion
On , the interpolation is . Euler–Maruyama step process and continuous interpolation
The uniform-moment theorem bounds whenever . Euler–Maruyama uniform moments and interpolation increments
The Itô integral of the constant integrand equals the Brownian increment. Ito integral for square-integrable predictable processes
A strong solution is an adapted continuous process satisfying the finite-coordinate Itô equation indistinguishably. Itô SDE data and strong solution
The finite-energy Itô-integral process has a continuous martingale version, and any two such continuous versions agree at all times on a measurable probability-one event. The Ito integral process has a continuous martingale version
AC is inherited from the Brownian-motion and Itô-integral interfaces; the explicit calculation below makes no choice. The Axiom of Choice
Example
Consider the scalar additive-noise equation on . The coefficients are constant, and for each the uniform mesh has steps of length .
Verification
The functions and are jointly Borel, globally Lipschitz in state with constant , and satisfy the stated linear-growth bound with a finite . Their time increments vanish, so the required half-Hölder time modulus holds. The deterministic initial value is -measurable, independent of future Brownian increments, and has every finite moment.
From [F1], induction gives . Substituting the coefficients into [F2] gives on every interval. By [F4], at every fixed time the candidate path satisfies the integral equation. The continuous-version theorem [F6] and equality at all rational times identify these processes indistinguishably; hence [F5] makes this adapted continuous candidate a strong solution. Any strong solution with the same data equals directly from the constant-coefficient equation, so this is the exact path.
The initial value has every finite moment. Applying [F3] for each finite therefore proves finite moments of the grid, step, and interpolated processes uniformly in and . The explicit identity from step 1.2 also identifies the exact path. AC in [A1] is inherited from the cited interfaces; no choice enters these computations.
A superlinear drift outside the Euler–Maruyama moment contract
Facts & Assumptions
Given: AC, a scalar state, a scalar Brownian increment, and the coefficient pair , .
The shared contract requires globally Lipschitz coefficients in state and a uniform linear-growth bound. Euler–Maruyama recursion
The uniform-moment theorem applies only under the coefficient and initial-value hypotheses of the shared contract. Euler–Maruyama uniform moments and interpolation increments
AC is inherited from the Brownian interface; no choice is made in the coefficient calculation. The Axiom of Choice
Example
For the scalar coefficient pair and , the drift is superlinear: its magnitude grows faster than . This is an example about the hypotheses of the Euler–Maruyama moment theorem; it makes no claim about strong existence, instability, or convergence for this particular equation.
Verification
The diffusion is globally Lipschitz and has linear growth. For the drift, as , so no finite linear-growth constant exists. Also , so no finite global Lipschitz constant exists.
Since both required drift conditions fail, the uniform-moment theorem [F2] cannot be invoked for this coefficient pair. The conclusion is only that its stated hypotheses are absent; no contrary convergence or moment claim follows. AC in [A1] is inherited and no choice is used.