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Is Poscidyn for me?

Poscidyn is for researchers and engineers who model nonlinear oscillators in Python and want efficient time-domain simulation or experiment-like frequency-response curves. It is especially useful when many related simulations make JAX batching worthwhile.

It is a good fit when you:

  • work with modal oscillator models and harmonic excitation;
  • need trajectories, response amplitudes, phases, or scalar response measures;
  • want to explore sensitivity to initial conditions and possible coexisting attracting responses;
  • value a compact Python workflow that can run on JAX-supported CPU or GPU backends.

It is not yet the right primary tool when you need certified branch following, bifurcation detection, stability/Floquet analysis, non-smooth hybrid dynamics, or a broad library of excitation types. Those are active design directions, not supported promises. See status and roadmap.

Start with the first frequency sweep if this matches your use case. Read limitations before using a selected synthetic path as a scientific result.