Integer Lur'e Workflow
Order-one describing-function and continuation route, anchored by the Chua q=1 reference case.
The integer Lur’e workflow runs the describing-function route at for a system supplied in manual Lur’e form:
It is intended for reusable order-one baselines and for checking a new system before adding fractional-memory effects.
Required System Data
- vector field and parameters;
- explicit , , and ;
- classical describing function ;
- equilibria for hiddenness controls;
- preferably a Jacobian for Lyapunov calculations.
The library does not infer the Lur’e decomposition automatically.
Protocol
- Solve the Nyquist/describing-function closure for .
- Build the harmonic seed.
- Continue the residual nonlinearity from to .
- Integrate the resulting target trajectory and compute dynamic diagnostics.
- Probe neighborhoods of each equilibrium and record whether any trajectory reaches the target.
Reference Case
The implemented benchmark is the non-smooth Chua system, with a linear-by-pieces characteristic, at . The
regenerated corrected run records , ,
, a positive leading Lyapunov exponent
, and 504 equilibrium-neighborhood probes with no
TARGET hits.
See Chua Integer q=1 Reference for the model, figures, and evidence sources.
Python Entry Point
from hidden_attractors import get_system
from hidden_attractors.workflows.integer_lure import (
continue_integer_lure_seed,
final_integer_lure_attractor,
integer_lure_seed,
run_integer_lure_hiddenness_controls,
)
system = get_system("chua-nonsmooth")
seed = integer_lure_seed(system)
steps = continue_integer_lure_seed(system, seed)
target_seed, trajectory, status = final_integer_lure_attractor(
system, steps[-1].x_out
)
probes = run_integer_lure_hiddenness_controls(system, trajectory)
For the complete historical Chua artifact family, use the compatibility command documented by the package:
hidden-attractors-integer-chua --help