Instrument Trigger and Event Processing

The final Fermi-LAT data sample is a result of the triggering and filtering processes done both on-board Fermi and on the ground. This begins at the DAQ level12, after which the particle interactions are reconstructed. These events are then analysed and defined based on the various event classification scheme described further on in this section.

Before proceeding with this section, it is important to highlight the necessary ter- minology used when processing Fermi-LAT data. As a γ-ray photon is incident on the detector, there are three ways in which it may be described. These are as follows:

photon

A photon describes the discrete γ-ray particle which is incident on the detector and

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is not yet affected by the instrument response.

event

An event is characterised as the response of the instrument when it detects the particle. This can consist of two possibilities. An event could be the response of the detector on an incident γ-ray photon or charged particle. An event could also be due to the response of the detector to noise that appears as a charged particle.

count

A count is the result when an event is classified as being due to an incident γ-ray photon. The number of counts depend on the detector response, the trigger and event processing pipeline which result in the count being characterised by detector modified observables. It must be noted that there is a possibility some photons are undetected or sometimes rejected as being part of the background. At the same time, counts could also be produced by non-astrophysical background events. The triggering and event-processing pipelines are described in detail in (153). How- ever, a brief account of this is presented here, followed by the Fermi-LAT event classifi- cation procedures.

Fermi-LAT data which are transmitted to the ground have undergone triggering and

filtering processes by the DAQ. The TKR modules, CAL and ACD are all involved in determining whether or not a trigger or a signal is observed and to distinguish if this trigger is a result of an incoming γ-ray photon, charged particles entering the Fermi- LAT from inside the field of view or backsplash events due to multiple-scattering in the TKR and CAL modules (236; 153). When the TKR detects a signal over a threshold value, this flags that a potential trigger is present in the tower. The CAL modules then distinguish if this potential trigger is at low energies, typically when the signal in any of the CAL crystal ends crosses the low-energy trigger threshold of∼ 100 MeV, or high energies, typically when the signal in the CAL crosses the high energy threshold of∼ 1 GeV (153). The triggering is then followed by the filtering process. There are three filtering algorithms, namelyGAMMA,HIPandDIAGNOSTIC. TheGAMMAfilter algorithm

filters γ-ray events. This algorithm processes events by running several tests on the triggered event. These tests are categorised into steps which will accept or reject the triggered event based on a predetermined criteria. In particular theGAMMA algorithm

accepts events which have total energy (deposited in the CAL) that is greater than the programmable threshold (set at 20 GeV) (153). The HIP and DIAGNOSTIC algorithms

are designed for calibration purposes of the CAL and monitor the performance of the sensors respectively. The event filtering process includes (but is not limited to) rejecting events from cosmic rays, accepting all events which have a total energy deposited in the CAL of < 20 GeV, reject events with energy deposited in the CAL of < 100 MeV that has patterns in the TKR which are unlikely to produce a track and reject all events without at least one rudimentary track (153).

The cuts applied in the filtering process may cause the rejection of some important events, particularly events which deposit all their energy in the TKR (either because they miss the CAL or they range out before reaching the CAL), or events which do not have reconstructed tracks but have information in the CAL which enables only an estimate of the event direction, thus decreasing the angular resolution of the event due to the lack of information from the TKR13(153).

The next process involves reconstruction by the CAL, TKR and the ACD. The first level is the energy evaluation by the CAL reconstruction algorithms. This is followed by the TKR reconstruction that serves to reconstruct the trajectories of the events detected by the calorimeter. The ACD reconstruction then estimates the energy deposited on each of the ACD tiles and ribbons and associates this with the tracks in the TKR. At this stage, the rejection of events caused by charged particles entering the detector from within the field of view is performed. Events which have reconstructed tracks all the way to the edge of the TKR module and points to an active region of the ACD which has significant deposited energy (which are too large to be classified as backsplash from the CAL) or less sensitive areas in the ACD (corners, gaps or between tiles) are filtered and classified as background14(153). The rejection of the charged particle background removes∼ 95% of downlinked data, in which∼ 10% of the γ-ray sample is lost (153).

Event trigger and filtering then lead to event classification processes. There are four event classes within the PASS7REP event classification scheme used in this work. The

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This may be the result of γ-ray photons entering the LAT at large incident angles, missing most of the tracker or resulting in broader scattering as it interacts with a larger cross-section of the converter-tracker planes (153).

14_{It must be noted that misclassification of γ-rays as charged particles can occur during very bright solar}

event classification system is nested such that each event class is a subset of the previ- ous event class. The succeeding event class will have stricter selection cuts compared to its previous class. As such, each event class is determined fundamentally by the types of constraints placed on the reconstruction of the events. The constraints which deter- mine these classification cuts are the quality of the energy and direction reconstruction, probability of γ-rays from various event analysis (this step follows the reconstruction process), and the overall probabilities of γ-rays from the final classification step of the event analysis (153).

P7TRANSIENT

Based on the selection criteria, this event class has the least number of cuts, hence it is the least pure of the event classes. This is only used for the analysis of transient sources such as γ-ray bursts. The cuts applied for this event class should maintain a high efficiency for γ-rays while limiting residual background rate15_{to only a few}

Hz (153).

P7SOURCE

This event class is a subset of theP7TRANSIENTand is used for single point source

analysis over long temporal periods and thus, has more stringent constraints than theP7TRANSIENTevent class. Further to this, residual cosmic ray background can

be modelled as an isotropic component and thus will be accounted for in the final output. For the P7SOURCE event class a background rate of less than ∼ 1 Hz in

the LAT field of view is required in order to maintain a high signal-to-background ratio that would not compromise source detection and characterisation. This event class is used for the analysis of all Fermi-LAT data presented in this thesis.

15_{The background rate represents LAT trigger rates due to charged particles or cosmic rays (typically}

P7CLEAN

A subset of the P7SOURCE class, this is used for the analysis of both source and

diffuse γ-ray emission which require tighter cuts to reduce background contami- nation to∼ 0.1 Hz in the LAT field of view. This enables the background contami- nation to be at levels below the extragalactic γ-ray background at all energies. The contribution from the total Galactic diffuse background is∼ 1 Hz, most of which is localised along the Galactic plane (153).

P7ULTRACLEAN

As with theP7CLEAN, this is also used in the analysis of the extragalactic diffuse

γ-ray emission. As such, even tighter cuts than that used for theP7CLEANis used in order to reduce background contamination even further below the extragalactic

γ-ray background rate (the residual contamination of P7ULTRACLEAN is ∼ 40% lower than that present inP7CLEANat 100 MeV)16. This helps avoid the presence

of artificial spectral features in the data (153).