Cosmic Ray Neutron Spectroscopy and Local Variables simultaneous measurement studies throughout Chile. Northern Chile Experimental Campaigns: Maricunga, Las Campanas Observatory, San Pedro de Atacama and Chapiquilta

This dataset was acquired during a series of experimental campaigns carried out in 2023–2024 to measure cosmic-ray neutron fluxes alongside various local environmental variables at multiple sites in northern Chile. The primary objective is to investigate how integral neutron fluxes—spanning thermal, epithermal, fast, and high-energy ranges—vary in response to changes in temperature, atmospheric pressure, soil moisture, air humidity, and other site-specific conditions.

The dataset is provided in a ROOT file using the RDataFrame format. It contains 15-minute time-correlated measurements of neutron counting rates from 16 individual detectors, as well as concurrent readings of local environmental variables. This structure enables detailed correlation and trend analyses, facilitating future investigations into the interplay between cosmic-ray neutron fluxes and local environmental factors.

From ROOT to  Python Pandas 

#!/usr/bin/env python3

import uproot
import pandas as pd
import numpy as np

#loading .root file
file_lco = uproot.open("Chapiquilta_timegrid_15_ndet_11_data_complete_update.root")

# ~ ROOT files, directories, and trees are like Python dicts with keys() and values()
# Showing the ROOT Tree name
print(file_lco.keys())

#Reading the ROOT Tree with the already read name
tree_lco = file_lco["Chapiquilta_data_tree"]

#Showing branch names
print(tree_lco.keys())

# ROOT Tree to Python PANDAS Data Frame
df_lco = tree_lco.arrays(['BP_mbar_corrected', 'SP_mbar', 'SVPW_mbar', 'AH', 'DewP_C', 'binCenter_D01', 'NEUrate_D01', 'binCenter_D02', 'NEUrate_D02', 'binCenter_D03', 'NEUrate_D03', 'binCenter_D04', 'NEUrate_D04', 'binCenter_D05', 'NEUrate_D05', 'binCenter_D06', 'NEUrate_D06', 'binCenter_D07', 'NEUrate_D07', 'binCenter_D08', 'NEUrate_D08', 'binCenter_D09', 'NEUrate_D09', 'binCenter_D10', 'NEUrate_D10', 'binCenter_D11', 'NEUrate_D11', 'binCenter_D12', 'NEUrate_D12', 'binCenter_D13', 'NEUrate_D13', 'binCenter_D14', 'NEUrate_D14', 'binCenter_D15', 'NEUrate_D15', 'binCenter_D16', 'NEUrate_D16', 'WS_ms_S_WVT', 'WindDir_DU_WVT', 'BP_mbar_Avg', 'RH_Min', 'AirTC_Avg', 'Rain_mm_acc', 'SlrW_Avg', 'PuntoRocio_Avg', 'VWC_5cm', 'Perm_5cm', 'EC_5cm', 'TC_5cm', 'VWC_10cm', 'Perm_10cm', 'EC_10cm', 'TC_10cm', 'VWC_20cm', 'Perm_20cm', 'EC_20cm', 'TC_20cm', 'VWC_30cm', 'Perm_30cm', 'EC_30cm', 'TC_30cm', 'VWC_40cm', 'Perm_40cm', 'EC_40cm', 'TC_40cm', 'VWC_50cm', 'Perm_50cm', 'EC_50cm', 'TC_50cm', 'Altitude', 'Latitude_A', 'Latitude_B', 'Longitude_A', 'Longitude_B', 'err_event', 'ratio_intg_th_ep', 'ratio_intg_th_fs', 'ratio_intg_fs_ep', 'ratio_intg_th_total', 'err_ratio_intg_th_ep', 'err_ratio_intg_th_fs', 'err_ratio_intg_fs_ep', 'err_ratio_intg_th_total', 'sum_intg_fs_ep', 'sum_intg_fs_ep_he', 'err_sum_intg_sum_fs_ep', 'err_sum_intg_sum_fs_ep_he', 'ratio_intg_th_sum_fs_ep', 'ratio_intg_th_sum_fs_ep_he', 'err_ratio_intg_th_sum_fs_ep', 'err_ratio_intg_th_sum_fs_ep_he', 'time_in_s', 'event_id', 'Intg_total', 'Intg_th', 'Intg_ep', 'Intg_fs', 'Intg_he', 'ratio_th_tot', 'ratio_ep_tot', 'ratio_fs_tot', 'ratio_he_tot', 'eta_th', 'eta_ep', 'eta_fs', 'err_intg_total', 'err_intg_total_upper', 'err_intg_total_lower', 'err_intg_th', 'err_intg_th_upper', 'err_intg_th_lower', 'err_intg_ep', 'err_intg_ep_upper', 'err_intg_ep_lower', 'err_intg_fs', 'err_intg_fs_upper', 'err_intg_fs_lower', 'err_intg_he', 'err_intg_he_upper', 'err_intg_he_lower', 'err_ratio_th_tot', 'err_ratio_th_tot_upper', 'err_ratio_th_tot_lower', 'err_ratio_ep_tot', 'err_ratio_ep_tot_upper', 'err_ratio_ep_tot_lower', 'err_ratio_fs_tot', 'err_ratio_fs_tot_upper', 'err_ratio_fs_tot_lower', 'err_ratio_he_tot', 'err_ratio_he_tot_upper', 'err_ratio_he_tot_lower', 'err_eta_th', 'err_eta_th_upper', 'err_eta_th_lower', 'err_eta_ep', 'err_eta_ep_upper', 'err_eta_ep_lower', 'err_eta_fs', 'err_eta_fs_upper', 'err_eta_fs_lower', 'flux_intg_MC', 'err_flux_intg_MC', 'flux_intg_median_MC', 'err_flux_intg_upper_MC', 'err_flux_intg_lower_MC', 'effective_dose', 'err_effective_dose', 'err_effective_dose_upper', 'err_effective_dose_lower', 'ambient_dose_equivalent', 'err_ambient_dose_equivalent', 'err_ambient_dose_equivalent_upper', 'err_ambient_dose_equivalent_lower'],library="pd")

A complete detailed article is on preparation, nevertheless if you need  further details please do not hesitate to contact us

[e-mail] (Francisco Molina)

[e-mail] (Franco López Usquiano)