Analysis April 2022 with lstchain v0.9.6 Pirola (cross-check)

General information

Name of the source: LHAASO J2108+5157
Brief description of the source:

- Object type : Unidentified Galactic PeVatron candidate

- Distance (pc) : Unknown

- RA, Dec in deg (ICRS): 317.22, 51.95

Analysis by Giorgio Pirola (MPP, gpirola@mpp.mgp.de)

Data-taking information (Run selection)

Run selection with the use of the notebook from Abelardo Moralejo [1]
Atmospheric transmission extracted from ELOG
Zenith < 55 deg

Summary of selection cuts:

- Wobble in (0.45, 0.55)deg

- elapsed_time > 5 min

- transmission_cut > 0.65

- pedestal charge std dev < 1.8 p.e.

- Cosmic rate > 3000 ev/s

- Cosmic rate( > 10 p.e.) > 20 ev/s

- Cosmic rate( > 30 p.e.) > 3 ev/s

- muon ring width std dev < 0.023

Run selection after cuts:

 Total wobble runs: 177
 Observation time: 51.40 hours
 Selected Runs:
 1 : 2021-06-04 : [4913, 4914, 4915, 4916, 4917]
 2 : 2021-06-05 : [4935, 4936]
 3 : 2021-06-12 : [5028, 5029, 5030, 5031]
 4 : 2021-06-30 : [5071, 5072]
 5 : 2021-07-01 : [5080, 5081, 5082, 5083, 5084]
 6 : 2021-07-02 : [5091, 5092, 5093]
 7 : 2021-07-03 : [5101, 5102, 5103, 5104, 5105, 5106, 5107, 5108]
 8 : 2021-07-04 : [5115, 5116, 5117, 5118, 5119, 5120, 5121]
 9 : 2021-07-05 : [5135, 5136, 5137, 5138, 5139, 5140, 5141, 5142]
 10 : 2021-07-15 : [5270, 5272]
 11 : 2021-08-01 : [5440, 5441, 5442]
 12 : 2021-08-03 : [5461, 5462, 5463, 5464, 5465]
 13 : 2021-08-04 : [5473, 5474, 5475, 5476, 5477, 5478, 5479, 5480]
 14 : 2021-08-05 : [5491, 5492, 5493, 5494, 5497, 5498, 5499, 5500]
 15 : 2021-08-06 : [5505, 5506, 5507, 5508, 5509, 5510, 5511, 5512, 5513, 5514, 5515, 5516, 5517]
 16 : 2021-08-08 : [5576]
 17 : 2021-08-09 : [5590, 5591]
 18 : 2021-08-10 : [5641, 5642, 5643]
 19 : 2021-08-11 : [5681, 5682, 5683, 5684, 5685, 5686, 5687]
 20 : 2021-08-12 : [5707, 5708, 5709, 5710, 5711, 5712, 5713]
 21 : 2021-08-13 : [5727]
 22 : 2021-09-01 : [5947, 5948, 5949, 5950, 5952]
 23 : 2021-09-02 : [5980, 5981, 5982, 5983, 5984, 5985, 5986, 5987, 5988, 5989, 5990, 5991]
 24 : 2021-09-03 : [5999, 6000, 6001, 6002, 6003, 6004, 6005, 6006, 6007, 6008, 6009, 6010]
 25 : 2021-09-04 : [6023, 6024, 6034, 6035, 6036, 6037, 6038]
 26 : 2021-09-05 : [6057, 6058, 6059, 6060, 6061, 6062, 6063, 6064, 6065, 6066]
 27 : 2021-09-06 : [6079, 6080, 6082, 6083, 6084, 6085]
 28 : 2021-09-07 : [6130, 6131, 6132, 6133, 6134]
 29 : 2021-09-09 : [6175, 6176, 6177, 6178, 6179, 6180, 6181, 6182, 6183]
 30 : 2021-09-11 : [6230, 6231, 6233]
 31 : 2021-09-12 : [6254, 6255, 6256, 6257]

MC information

- AllSkyMC production

- standard DL1 produced in lstmcpipe v0.7.4 (Training DiffuseGammas and Protons, Testing Ring-like gammas), and v0.8.2 (Testing DiffuseGammas)

- RFs training data reconstruction up to DL2 done manually in lstchain v0.9.6 (lstmcpipe wasn't ready for the full AllSky MC at the time of analysis), IRFs created in dev lstchain (close to v0.9.7)

- For IRFs we used only the closest (in zenith) testing nodes to the LHAASO path

Nodes used for IRFs:

- node_theta_14.984_az_355.158_

- node_theta_32.059_az_355.158_

- node_theta_43.197_az_262.712_

- node_theta_52.374_az_301.217_

Standard DL1a MC:

- Training:

/fefs/aswg/data/mc/DL1/AllSky/20220511_allsky_std/TrainingDataset/dec_4822/GammaDiffuse/
/fefs/aswg/data/mc/DL1/AllSky/20220511_allsky_std/TrainingDataset/dec_4822/Protons/

- Testing (Ring-like MC, offset 0.4 deg):

/fefs/aswg/data/mc/DL1/AllSky/20220511_allsky_std/TestingDataset

- Testing (Diffuse MC, only four nodes close to the source path in the sky):

/fefs/aswg/data/mc/DL1/AllSky/20220527_src2_diffgamma/TestingDataset/GammaDiffuse/dl1_20220527_src2_diffgamma_{NODE}_merged.h5

NSB tuning parameters:

"image_modifier": {
     "increase_nsb": true,
     "extra_noise_in_dim_pixels": 0.919,
     "extra_bias_in_dim_pixels": 0.298,
     "transition_charge": 8,
     "extra_noise_in_bright_pixels": 0.972,
     "increase_psf": false,
     "smeared_light_fraction": 0.0
   },

Tuned DL1b MC:

- Training:

/fefs/aswg/data/mc/DL1/AllSky/20220524_dec_4822_tuned/TrainingDataset/dec_4822/GammaDiffuse/dl1_20220524_dec_4822_tuned_dec_4822_GammaDiffuse_merged.h5
/fefs/aswg/data/mc/DL1/AllSky/20220524_dec_4822_tuned/TrainingDataset/dec_4822/Protons/dl1_20220524_dec_4822_tuned_dec_4822_Protons_merged.h5

- Testing:

- gamma point-like

/fefs/aswg/data/mc/DL1/AllSky/20220524_dec_4822_tuned/TestingDataset/dl1_20220524_dec_4822_tuned_node_theta_{NODE}__merged.h5

- gamma diffuse

/fefs/aswg/workspace/

Random Forests (source independent):

- Models trained in lstchain v0.9.6, i.e. with "az_tel", "alt_tel" RF features

- cfg file: /fefs/aswg/workspace/giorgio.pirola/LST_analysis/lhaaso_pipe/lstchain_config_2022-05-24.json

 /fefs/aswg/data/models/AllSky/20220524_dec_4822_tuned/dec_4822

DL2 MC (testing only for IRFs):

- gamma point-like

/fefs/aswg/data/mc/DL2/AllSky/20220524_dec_4822_tuned/TestingDataset/dec_4822/{NODE}/dl2_20220524_dec_4822_tuned_node_theta_{NODE}__merged.h5

- gamma diffuse

/fefs/aswg/workspace/

DL1 data

DL1a files produced by LSTOSA (lstchain v0.9)
lstchain v0.9 tailcut8-4 (with cleaning based on pedestal RMS, dynamical cleaning)
cfg /fefs/aswg/data/real/DL1/{date}/v0.9/tailcut84/log/lstchain_config_tailcut84_v092.json

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

DL2 data

whole data sample before data selection

/fefs/aswg/workspace/giorgio.pirola/LST_analysis/lhaaso_pipe/data/DL2_ALLsky

DL3 data

Fixed cuts:

"intensity": [50, Infinity],
"width": [0, Infinity],
"length": [0, Infinity],
"r": [0, 1],
"wl": [0.1, 1],
"leakage_intensity_width_2": [0, 1.0],
"event_type": [32, 32]

IRFs

Full enclosure
Four different IRFs merged with DL2 data depending on the run zenith angle
Global cuts optimised on Crab data used
Energy dependent cuts not yet possible. For these we would need point-like IRFs produced from ring-like MC. The problem is that the LHAASO source was observed with variable offsets from 0.45 - 0.55 deg, while point-like IRFs in v0.9.6 have a hard-coded offset axis [0.3, 0.5] deg, which means that IRF cannot be used for many runs in data in gammapy analysis.
Produced in lstchain dev (close to v0.9.7)

IRF path: /fefs/aswg/workspace/jakub.jurysek/data_analysis/IRFs/v0.9.7/AllSky/

irf_allsky_{NODE}_int50_leak10_gh084_th004_diffuse.fits.gz

File:.png

DL3 files

/fefs/aswg/workspace/jakub.jurysek/data_analysis/lhaaso_J2108/DL3/v0.9.7/AllSky/int50_leak10_gh084_th004_diffuse/

High-level analysis

Theta2 distribution

- Energy dependent gammaness cuts optimized on Crab detection significance + global theta2 cut (also optimized on Crab significance, but not bin-wise)

- 3 OFF regions

- Three energy bins (blind), for E>3TeV we have 3.7 sigma

File:.png

1D Spectral analysis

2 hypothesis:

- point-like source: theta<0.2deg

- extended source: theta<0.26deg

Performed with gammapy-v0.19

bkg_maker = ReflectedRegionsBackgroundMaker(exclusion_mask=exclusion_mask,
                                           min_distance=1 * u.rad, # Minimum distance from input region
                                           max_region_number=2 # Maximum number of OFF regions
                                          )
safe_mask_masker = SafeMaskMaker(methods=["aeff-max"], aeff_percent=10)

e_reco_min = 0.1
e_reco_max = 100
e_true_min = 0.01
e_true_max = 100
energy_axis = MapAxis.from_energy_bounds(
   e_reco_min, e_reco_max, 
   nbin=2, per_decade=True, 
   unit="TeV", name="energy"
)
energy_axis_true = MapAxis.from_energy_bounds(
   e_true_min, e_true_max, 
   nbin=5, per_decade=True, 
   unit="TeV", name="energy_true"
)

Spectral fitting of stacked LST dataset
Performed for point-like source assumption
LST-1 data alone: Power-law spectral model
Joint likelihood forward folding with LHAASO SED data points: Exponential cutoff power-law spectral model