Collapse models with non-white noises II: particle-density coupled noises

Physics – Quantum Physics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Latex, 43 pages; versions 2&3 have minor editorial revisions

Scientific paper

10.1088/1751-8113/41/39/395308

We continue the analysis of models of spontaneous wave function collapse with stochastic dynamics driven by non-white Gaussian noise. We specialize to a model in which a classical "noise" field, with specified autocorrelator, is coupled to a local nonrelativistic particle density. We derive general results in this model for the rates of density matrix diagonalization and of state vector reduction, and show that (in the absence of decoherence) both processes are governed by essentially the same rate parameters. As an alternative route to our reduction results, we also derive the Fokker-Planck equations that correspond to the initial stochastic Schr\"odinger equation. For specific models of the noise autocorrelator, including ones motivated by the structure of thermal Green's functions, we discuss the qualitative and qantitative dependence on model parameters, with particular emphasis on possible cosmological sources of the noise field.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Collapse models with non-white noises II: particle-density coupled noises does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Collapse models with non-white noises II: particle-density coupled noises, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Collapse models with non-white noises II: particle-density coupled noises will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-42842

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.