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A two-interval shooting residual has a block-bidiagonal sensitivity Jacobian
Example
For on two intervals of length , define shooting nodes and residuals , , and . This uses the exact parameterized ODE flow covered locally by Parameter-dependent ODE flows have the variational tangent on a common tube. On the shooting solution set, take terminal objective .
Facts & Assumptions
Given: , , the two exact-flow intervals, and the finite shooting graph.
The parameterized ODE flow has its variational tangent when its uniqueness and common-tube hypotheses hold (Parameter-dependent ODE flows have the variational tangent on a common tube).
The reverse recursion computes the exact gradient of a finite state-step objective (The reverse recursion is the exact gradient of a finite state-step objective).
The exponential is smooth with derivative equal to itself, is positive, satisfies , and is increasing (The exponential function is smooth and , The exponential is positive and satisfies , The exponential function is strictly increasing).
The chain and product rules differentiate the displayed functions; a continuous function on an interval with zero interior derivative is constant (The chain rule for total derivatives: , Sums, scalar multiples, products and quotients: , , , and when , A function continuous on an interval whose derivative vanishes at every interior point of is constant on ; consequently two such functions with the same derivative differ by a constant).
Verification
The function satisfies and . Conversely, for any solution with this initial value, the product and chain rules give . By [F4] this product is constantly on its solution interval, and positivity and the reciprocal identity in [F3] imply . Thus the displayed solution exists globally and is unique.
Verify the actual common-tube hypotheses locally at any . Fix and restrict the parameters to , . For , Treat as the flow parameter, with initial map and field on . The bounded convex open set has compact closure inside that field's domain and contains all these trajectories for and the restricted parameters. The field and initial map are . Step 1.1 supplies existence and uniqueness, so [F1] applies. Each shooting interval uses this same argument with its own initial node; since there are two intervals, a common finite bound may also be taken.
The exact interval map is therefore . Differentiate the residuals with respect to and , writing : The state Jacobian is lower bidiagonal, and the parameter column contains the two local flow sensitivities.
Solving gives , , and . Direct differentiation yields . The discrete adjoint for the two flow steps seeds , then gives and ; its parameter sum is . Thus the reverse gradient agrees with the differentiated shooting solution.
Depends on
- Parameter-dependent ODE flows have the variational tangent on a common tube
- The reverse recursion is the exact gradient of a finite state-step objective
- The exponential function is smooth and $(\exp)'=\exp$
- The exponential is positive and satisfies $\exp(-x)=1/\exp(x)$
- The exponential function is strictly increasing
- The chain rule for total derivatives: $D(g\circ f)(a)=Dg(f(a))\circ Df(a)$
- Sums, scalar multiples, products and quotients: $(f+g)'(c) = f'(c) + g'(c)$, $(\alpha f)'(c) = \alpha f'(c)$, $(fg)'(c) = f'(c)g(c) + f(c)g'(c)$, and $(f/g)'(c) = \bigl(f'(c)g(c) - f(c)g'(c)\bigr)/g(c)^{2}$ when $g(c) \ne 0$
- A function continuous on an interval $I$ whose derivative vanishes at every interior point of $I$ is constant on $I$; consequently two such functions with the same derivative differ by a constant
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
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Sources
- William W. Hager, Runge-Kutta methods in optimal control and the transformed adjoint system, §§2–3 (standard reference, not scraped)
- Michael B. Giles and Niles A. Pierce, An Introduction to the Adjoint Approach to Design, §2.4 (standard reference, not scraped)