Hi everyone, in this post I would like to tell you about the work I’m starting within the CMS collaboration.
For the non experts but passionates, CMS (acronym for Compact Muon Solenoid) is one of the big experiments at CERN and it aims at detecting the products of collisions between bunches of protons accelerated by the Large Hadron Collider LHC at high energy (13 TeV in the center of mass system reached recently).
Everyone who is part of the collaboration, especially the new entries like me, has to work for a certain period of time on some pledges, namely a service work for the experiment. The realization of this task allows people who worked on it to sign the scientific articles from the collaboration.
Since CMS is an experiment for high energy physics, it needs a suitable structure to fit well the needs deriving from a highly particle-crowded environment. It has a cylindrical shape (with the axis of the cylinder coincident with the beam axis) and it is made up of several specific layers, according to the different properties of interaction of the various particles with the material of the detector. The most internal one is the tracker, and its task is to record the paths taken by the charged particles (curved because of the presence of a magnetic field).
In turn, the tracker is made up of two parts: the pixel detector (the most internal part) and the strip detector. My pledges in CMS are concerned with the latter.
The Silicon Strip Tracker (SST) hosts 10 million microstrips divided into four inner barrel (TIB) layers assembled in shells with two inner disks (TID) – at the bases of the cylinder -, one outer barrel (TOB) consisting of six concentric layers and two end-caps (TEC). In Fig. 1 the barrel SST and one of the end-caps are shown.
I will work on the three steps of the low level reconstruction: the strip unpacker, the strip clusterizer, and the strip CPE (Cluster Parameter Estimator).
The raw data output from each SST FED (Front End Driver, namely the readout electronics) encodes the basic hit information necessary for the tracking. These raw data need to be interpreted and the hit information to be extracted (known as digis). This process is the so called unpacking of the data.
Then, the local hit reconstruction is defined in two subsequent steps: the clustering and the hit conversion (i.e. the incorporation of the geometrical position of the hit).
The clustering process consists in grouping together neighbouring and gain-corrected digis via a dedicated algorithm.
The clusters created are translated into possible hit measurements in the hit conversion, and this is done with a cluster parameter estimator algorithm. The hits are assigned a position and a corresponding uncertainty in the local coordinate frame of the silicon module.
In Fig. 2 you can see schematically the software design for local reconstruction in the SST.
With this last step, the local reconstruction procedure in the SST is done!
Hope this post gave you at least a rough idea of what I will work on. For eventual questions, I’m here!