qutip

To simulate open quantum systems and decoherence in Python, you can use the mesolve Lindblad master equation solver with defined collapse operators to model dissipation and track state evolution over time.

Yes, you can model quantum trajectories and quantum jumps using the mcsolve functionality, which simulates measurement backaction and stochastic dynamics without requiring you to build a custom solver.

The best way to simulate unitary evolution for a closed quantum system is to use the sesolve Schrödinger dynamics solver to track state evolution and compute observables across a defined time grid.

Yes, this approach supports advanced quantum dynamics including non-Markovian HEOM and Floquet methods for handling periodic-drive scenarios and complex memory effects in quantum optics research.

To visualize quantum states after simulation, you can generate Bloch sphere, Wigner, and Fock distribution plots directly from the output density matrices and expectation values produced by the solvers.

Yes, you can calculate steady states, fidelity, and entropy for damped harmonic oscillators by defining the Hamiltonian and collapse operators, then applying expectation value and correlation analysis workflows.