SPICE Mie [mi:]. Dmitry Chirkin, UW Madison. Updates to ppc and spice. PPC: Randomized the simulation based on system time (with us resolution) Added the implementation of the simple approximate Mie scattering function
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Dmitry Chirkin, UW Madison
oversized ~ 5 times
Flashing 63-50 63-48
do not track back to detected DOM
do not track after detection
no ovesize delta correction!
do not check causality
Also known as the Liu scattering function
Introduced by Jon Miller
Single radius particles, described better as smaller angles by SAM
flashing 63-50 64-50
1. For some starting values, find best values of lsca ~ labs.
2. Find best values of py, toff, fSAM, asca, aabs, llhtot, …
py photon yield factor
toff global time offset (rising edge of the flasher pulse)
fSAM fraction of SAM contribution to the scattering function
asca scaling of scattering coefficient
aabs scaling of absorption coefficient
3. Repeat until converged (~3 iterations)
4. Refine the fit with lsca and labs independent from each other
Full likelihood with timing
60 x 250 events
with 10 event/flasher
In the dust peak
With 10 events/flasher, 250 in dust peak
With 250 events/flasher everywhere
Minimum is in the same place with both likelihoods!