Re: stochastic wave-function evolution of the quantum Langevin equation

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ANIRUDDHA CHAKRABORTY

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Oct 3, 2025, 1:57:09 PM10/3/25
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I guess it should be mesolve for solving Lindblad equation but Linblad is Markovian (i.e time correlation is much smaller than system evolution time) 

Aniruddha

On Fri, Oct 3, 2025, 11:12 AM hamids...@gmail.com <hamids...@gmail.com> wrote:
Hii all,

I need to simulate Eq.  4 in the picture below, and i  don't know which functions (mesolve, mcsolve, smesolve, ssesolve) i  have to use for my simulation. Please, I need someone to help me. 

Thank  you  

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Éric Giguère

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Oct 5, 2025, 4:24:17 PM10/5/25
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There is no solver for that exact equation, you will need to force it...

sesolve could be used with:

noise_array =  np.random.randn(N_dts) # **0.5?
H = H0 - 0.5j * L.dag() @ L +1j * L * Coefficient(lambda t, noise: noise, args={"noise": noise_array[0])

solver = SESolver(H, options={ "method": "vern7", "interpolate": False}) # Default "adams" method remember data between steps.
solver.start(psi_0, t_0)
for i, t in enumerate(np.linspace(t_0, t_final, dt)):
    state = solver.step(t + dt, args={"noise": noise_array[i]}) # evolve from t to t+dt and return the state at t+dt.

This will do the evolution with in chunks of `dt` with a different noise value for each steps.
`"interpolate": False` with verner method ensure each steps start from a clean state with the new noise value.

With just the limited info you shared, this seems a somewhat easy and promising method.



    




On Friday, October 3, 2025 at 8:53:05 PM UTC-4 hamids...@gmail.com wrote:
First of all, I would like to thank you for your  reply.   But how  can I implement   the white noise using  mesolve 
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Éric Giguère

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Oct 7, 2025, 1:20:19 PM10/7/25
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It's close to yours, but there are extra terms. It would be the same if the `e_n` were zeros.
(dW is the white noise).

You should check that the right physic is simulated for your problem. 


On Tuesday, October 7, 2025 at 10:01:49 AM UTC-4 hamids...@gmail.com wrote:
Hi there,
I've been using the ssesolve function (qt.ssesolve(
                H,
                psi0,              
                t_list,
                sc_ops=[L_stochastic],  # Single collapse operator
                e_ops=e_ops,
                heterodyne=True,
                ntraj=500,  # Increased for better statistics
                options={
                    "dt": 0.0125,  # Larger time step for stability
                    "store_measurement": True,
                   
                   "store_states": False,

                    "map": "serial",  # Use serial for stability
                    "normalize_output": True,
                    "method": "platen"  # Explicit method specification
                }
            ))  for my quantum simulation work, and I've obtained results that are generally in line with what I need. However, I've encountered an unexpected behavior: when comparing results for γ=0 (no dissipation) versus γ≠0 (with dissipation), the SRE (Symmetric Relative Entropy) values for γ=0 are lower than those with γ≠0.
Based on my understanding, I would expect the opposite trend. Please help me understand why this might be happening or suggest ways to investigate this further.
Thank you for your assistance

Le lun. 6 oct. 2025 à 08:43, Hamid Sakhouf <hamids...@gmail.com> a écrit :
Thank you so much. This equation form this paper: https://arxiv.org/abs/2501.10349v1

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