BL Lacertae August 2021

General information

Name of the source: BL Lacertae
Brief description of the source:
- IBL / LBL
- highly variable
- z = 0.069
- RA: 22 02 43.3 (hh mm ss), Dec: +42 16 40 (dd mm ss)
- RA, Dec in deg (ICRS): 330.68038, 42.277772

Analysis by Chaitanya Priyadarshi ((IFAE - cpriyadarshi@ifae.es)

Data-taking information

See https://www.lst1.iac.es/wiki/index.php/BLLac#Data-taking_information

Monte Carlo information

For getting a closer data-MC comparison, we produce MC data along various sky positions (nodes) as a preliminary method to facilitate better Random Forest model for the reconstruction and to interpolate IRFs from various sky positions to the target position of each Observation Run.

DL1 data

This includes whether you use LSTOSA, specific versions of lstchain, dllab scripts, cleaning levels, and calibration information.

DL1a files produced by LSTOSA (lstchain v0.9)

original real DL1a data

/fefs/aswg/data/real/DL1/{Date}/v0.9/tailcut84/

lstchain v0.9 tailcut8-4 (with cleaning based on pedestal RMS, dynamical cleaning)

 /fefs/aswg/data/real/DL1/20210808/v0.9/tailcut84/log/lstchain_config_tailcut84_v092.json

MC nodes: tailcut8-4 (with cleaning based on pedestal RMS), dynamic cleaning, NSB tuning

 /fefs/aswg/data/mc/DL1/AllSky/20220601_dec3476_tuned/{Testing, Training}Dataset/

Random forest

Here we use the TrainingDataset nodes, selected along the declination path (or closer to) of the selected source (BL Lac here). The "dec3476" part in the production ID refers to the declination angle of +34.76 deg. In this new RF model production, we include zenith and azimuth pointing parameters as well.

lstchain v0.9.6dev source-independent, dynamic cleaning, NSB tuning

 /fefs/aswg/data/models/AllSky/20220601_dec3476_tuned/

For IRF interpolation

Here we create an almost uniform grid of nodes of sky positions for TestingDataset MC, so as to facilitate IRF interpolation in the parameter space of cos zenith and the sin of angle (delta) between the geomagnetic field and the particle shower direction. IRF interpolation is performed using pyirf v0.7.

Link to MC DL2 files used:

/fefs/aswg/data/mc/DL2/AllSky/20220601_dec3476_tuned/TestingDataset/

Particle types: ring-wobble gamma (offset range = [0.3999, 0.4001] deg)

DL2 data

/fefs/aswg/workspace/chaitanya.priyadarshi/real_data/AGN/BLLac/v09x/tailcut84/DL2/real/src_indep/20220601_dec3476/{Date}

DL3 data selection

For energy-dependent cuts

Information about your DL3 data selection.

intensity > 50
r: [0, 1]
wl: [0.01, 1]
leakage_intensity_width_2: [0, 1]

source-independent
- gh_efficiency: 0.8
- theta_containment: 0.8

High-level analysis

lstchain Tools to generate source-independent IRF and DL3
Science Tool: gammapy 0.20.1
point-like IRF, 1D analysis

For DL3 data reduction to DL4 dataset,

OFF regions selected - 1 Wobble
Safe Energy mask for systematics - Yes (only for Aug 8)
Energy axes -
- True: 10 GeV to 100 TeV with 10 bins per decade
- Reco: 10 GeV to 10 TeV with 5 (10 for Aug 8) bins per decade

DL4 dataset plots for full August

DL4 dataset plots for Aug 8

For spectral analysis,

Model used - Log Parabola
Reference energy used by calculating the decorrelation energy with a Power Law fit, 124 (125 for Aug 8) GeV
Spectral Fit energy range - 10 GeV to 10 TeV with 5 (10 for Aug 8) bins per decade
Spectral fit with gammapy default optimization - minuit

For LC,