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I know the quantum master equation, but I wonder if for the aim of a better understanding/interpretation a full classical probability formulation of QT isn't at least somewhat useful. And as far as i can see, i can't find any major obstacles other then terminology.vanhees71 said:I'm not sure about why you bring "Markov" in. The system's state is described by the corresponding reduced statistical operator, i.e., by tracing out the measurement device+environment part. The result is a quantum master equation, which usually is not a Markov process. Often it can be approximated by a Markov process, leading to some Lindblad equation for the time evolution of the system
1. Measurement
What brings me to Markov is however not the regular time evolution (which the quantum master equation describes) but measurement. The way calculation of probabilities work in projective measurements has the same signature as a discrete time Markov chain. Basically all i am saying is that you can build a stochastic matrix out of the rule 6 (as linked above) - or a Markov kernel if that is done for the entire state space. Nothing more is needed to define a discrete time Markov chain. But it would then describe only a single measurement in a single experimental setup and nothing else. Is there any argument about that?
2. Undisturbed time evolution
When it comes to the quantum master equation it is a huge simplification utilizing the linear formulation of the time evo of states - but due to Born's rule you cannot fully utilize the linearity of the state space and linearity of ensemble probabilities at the same time.
However, any time evolution of a deterministic system can still be written in terms of a Markov process. All you need is the Markov property that the time evolution depends only on the current state and not the history how it got there. That seems to be the case in QT and the time evo outside of measurement is actually deterministic, right?
Now let's be clear that in QT the state space H is continuous and not discrete. So the master equation for such system is usually given by the Fokker Planck equation. Now the dimension of the Hilbert space is infinite so... it's a highly dimensional problem. However, the deterministic nature means we only have a drift term to worry about with no diffusion ##D (a_{n,t},t)=\frac 1 2 \sigma^2 (a_{n,t},t)=0## (where ##a_{n,t}## is the amplitude for the state ##\Psi_n##). Hmm, if we write in terms of the amplitudes of the Hamiltonian eigenstates basis, it's actually not difficult to solve since we have only a trivial drift ##\mu (a_{n,t}, t) = iE_n \hbar^{-1}##.
So that would be the formal master equation for a continuously distributed ensemble given by a probability density ##\rho(a_1, a_2, ...)## over complex amplitudes for each basis state (we would have to limit it to a finite number of states/dimension for a probability density to exist, but whatever). For that matter it works the same for electrodynamics as it would for QT - but only for as long as there is no measurement which messes this up.
That said i have no idea how QT actually deals with any non trivial ensembles like the continuously distributed case i have above. Just don't see how a density matrix is able to handle such a case. Are such ensembles of no interest in QT?
You could potentially dump this down to a discrete state space of interest enabling a simpler matrix representation in some simplified cases and using other trickery.
3. Total time evolution
Lastly those two types of very different processes - measurement and undisturbed time evolution - have to be properly merged together to obtain the full "master equation" of QT for an experiment. For me that task sounds very much like what Markov decision processes can do.
That's it
So i hope that helped a little. Which of the 3 points is causing the biggest trouble to follow?
Thanks, will have to look into it. Anyhow, your link does not work for me. I get a "DOI not found".vanhees71 said:H.-P. Breuer and F. Petruccione, The theory of open quantum systems, Oxford University Press, Oxford, New York (2002).
Another technique, I'm more familiar with is to start with the real-time Green's function technique to derive the Kadanoff Baym equations which then can be reduced to semiclassical quantum transport equations through gradient expansion:
W. Cassing, From Kadanoff-Baym dynamics to off-shell parton transport, Eur. Phys. J. ST 168, 3 (2009),
https://doi.org/10.1140/epjst.
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