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Projected contact dynamics and explicit projection Euler step
Definition
Let , let be nonempty, closed, and convex, and let be the unique nearest point in to , whose existence and uniqueness are Every point has a unique nearest point in a nonempty closed Euclidean convex set. For , set for , set . On this is the outward normal cone of Scaled KKT residual and convex normal cone. The projection variational inequality of Metric projection onto a closed convex set satisfies the variational inequality says exactly when and .
For , a solution of the projected contact dynamics with forcing and initial state is an absolutely continuous map satisfying Equivalently, . For an integer , put , , and define the exact explicit projection Euler nodes by starting from . Its affine interpolant joins consecutive nodes linearly on each interval .
For a map , absolutely continuous means that each coordinate is absolutely continuous in the scalar sense of Absolute continuity on a compact interval, and is the vector of coordinate derivatives, from The derivative of at a point that is a limit point of , and differentiability on a set, wherever they all exist. The solution condition requires a Lebesgue-null set such that for every all coordinate derivatives exist and the displayed inclusion holds. Here almost every is relative to Lebesgue measure from Lebesgue measurable sets, the family , and the restricted set function , with the convention of Measure-null sets and almost-everywhere statements relative to a measure.
Depends on
- Scaled KKT residual and convex normal cone
- Metric projection onto a closed convex set satisfies the variational inequality
- Every point has a unique nearest point in a nonempty closed Euclidean convex set
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Absolute continuity on a compact interval
- The derivative $f'(c) = \lim_{x \to c} \frac{f(x) - f(c)}{x - c}$ of $f : A \to \mathbb{R}$ at a point $c \in A$ that is a limit point of $A$, and differentiability on a set
- Measure-null sets and almost-everywhere statements relative to a measure
- Lebesgue measurable sets, the family $\mathcal{L}(\mathbb{R}^n)$, and the restricted set function $\lambda_n$
Used by
- Projected Euler with certified inexact projection solves Algorithm
- A stiff penalty equation defeats a fixed explicit step Example
- Projected Euler for a constrained overdamped particle Example
- Solutions of projected contact dynamics are unique under the inherited choice assumptions Lemma
- The convex normal-cone operator is maximal monotone and its resolvent is projection Lemma
- A square-root global error bound for projected Euler with certified projection tolerances Theorem
- Existence and uniqueness for projected dynamics and convergence of projection Euler under countable and dependent choice Theorem
Dependency tree · two levels
39 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- David E. Stewart, Dynamics with Inequalities: Impacts and Hard Constraints (standard reference, not scraped)
- Dimitri P. Bertsekas, 6.253 Convex Analysis and Optimization, Complete Lecture Notes (standard reference, not scraped)