Welcome to powspechi!¶
A package of power spectral fun for heavy-ion physics!
There is a plethora of high energy physics articles out there which describes the matter formed in the collisions of heavy-ions as akin to the primordial universe. Such matter is, after all, an extremely hot and dense soup of quarks and gluons, just like the first moments after the Big Bang.
On that note, our oldest window into the creation of the universe are photons that freely streamed after the first atoms were formed. These photons compose the cosmic microwave background (CMB), from which cosmologists have been able to glean not only information on the metric of the universe, but also on its dark matter and energy compositions.
When considering the quark-gluon plasma (QGP) created in accelerators and the CMB, their analyses comprise on studying how left-over debris are distributed. In other words, what are the preferred directions of emission of the resulting particles? How can these anisotropies help in the understanding of said phenomena?
This project combines CMB methods with QGP debris, an exploration which resulted in the works: “Angular power spectrum of heavy ion collisions”, by M. Machado, P.H. Damgaard, J.J. Gaardhoeje and C. Bourjau, and its follow-up “Heavy ion anisotropies: a closer look at the angular power spectrum”, by M. Machado. Both deal with ALICE public data on Pb-Pb collisions from 2010 extracted through the mALICE framework.
Dive into the angular power spectrum analysis of heavy-ions by submitting your favorite 3+1D-model data,
experimental data itself, or simple MC-simulated particle distributions! Through the powspechi package,
which is coupled to HEALPix, one can map hadrons onto the surface of a sphere, calculate their angular
power spectra and perform the necessary corrections. Just install the package and try out the tutorial!
Note
The resulting angular power spectra will always be given as a dictionary. Single and averaged spectra follow the schematic formats below:
single_powspec = {'full': numpy.array(), 'mdz': numpy.array()}
avg_powspec = {'full': [numpy.mean(), numpy.std()], 'mdz': [numpy.mean(), numpy.std()]}
where ‘full’ and ‘mdz’ correspond to \(C_{\ell}\) and \(C^{m\neq0}_{\ell}\), respectively. The
latter quantities are defined in powspec_calc.maps2cld.
Tutorial¶
Explore the angular power spectrum analysis of a data set of simply simulated particle distributions by downloading the tutorial.zip file. It is over 200 MB due to the data set itself. It is also possible to visualize the tutorial notebook with all of its plots through Jupyter nbviewer by clicking here.