Interface AdjointGradientDescentOptions

Tolerance for ||c(p, x)|| = 0. Default: 1e-6

Analytical ∂c/∂p. Size constraintCount × parameterCount.

Analytical ∂c/∂x. Must be square (constraintCount === stateCount). Ill-conditioned Jacobians can be sensitive; raise regularization if needed.

Analytical ∂f/∂p. Used instead of finite differences when provided.

Analytical ∂f/∂x. Used instead of finite differences when provided.

Log level for detailed logging output. Controls which log messages are displayed:

• DEBUG: Detailed progress information (cost, gradient norm, step size, etc.)
• INFO: Convergence messages and important state changes
• WARN: Warnings (singular matrix, max iterations reached, line search failure, etc.)
• ERROR: Fatal errors (currently not used, reserved for future extensions)

If verbose is true and logLevel is not specified, logLevel defaults to INFO. If both logLevel and verbose are specified, logLevel takes precedence. Default: undefined (no logging)

Maximum number of iterations before stopping. Default: 1000

Callback function called at each iteration for progress monitoring. Useful for debugging and monitoring convergence.

Base Tikhonov regularization for solves involving ∂c/∂x. Default: 0 (an automatic floor may still apply when the Jacobian is singular)

Step size (learning rate) for gradient descent. If not provided, line search will be used to determine step size. Default: undefined (use line search)

Finite-difference step for derivatives with respect to parameters. Default: 1e-6

Finite-difference step for derivatives with respect to states. Default: 1e-6

Tolerance for convergence check (gradient norm, step size, etc.). Default: 1e-6

Levenberg-Marquardt and constrained Levenberg-Marquardt prefer tolGradient / tolStep / tolResidual. If those are omitted, this value is used as a common fallback.

Use line search to determine optimal step size. Default: true

Enable verbose logging for debugging. When true, detailed information is logged to console. Default: false