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magbias_experiments.py
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magbias_experiments.py
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import numpy as np
#this is where we store the experiment parameters for noise:
n = 2 #n is the detection threshold (in #sigma)
FOV_SKA = 1 #[deg2]
A_SKA = 25600 #[deg2]
FOV_CLAR = 1 #[deg2]
# A_CLAR = 640 #[deg2]
A_CLAR = 160 #[deg2]
# A_CLAR = 40 #[deg2]
# A_CLAR = 10 #[deg2]
ttot = 5 * 365 * 24 #[hours], 5 years
SKA_zhangpen = { "Aeff" : 6e5, #[m2]
"Tsys" : 30*1e3, #[mK]
"t_int" : ttot * FOV_SKA / A_SKA,
"S_area": A_SKA,
"Name" : "SKA_zhangpen"
}
CLAR_zhangpen = {
"Aeff" : 5e4, #[m2]
"Tsys" : 30*1e3, #[mK]
"t_int": ttot * FOV_CLAR / A_CLAR,
"S_area": A_CLAR,
"Name" : "CLAR_zhangpen"
}
SKA = {
"mode": "single_dish",
"Ndish": 133+64,
"Tsys": 30 * 1e3, #mK
# "S_area": 7.6, #25000 sq deg = 7.6 [sterrad]
"S_area": 5.15, #fsky of 0.41 as in the multitracer paper [sterrad]
"t_int": 8760, #1 yr in [h], for comparison with hirax
"Ddish": (133 * 15 + 64 * 13.5) / (133+64), #average [m]
"Nbeam": 1,
"Name" : "SKA",
}
#bands 1 and 2 are copies of SKA with different mean Tsys:
#do not forget that they have different but overlapping frequency coverage
#numin and numax taken from /Users/amadeus/Documents/PhD/work/multitracer/experiments/SKA_Tsys/band1_Tsys.txt
SKA1 = dict(SKA)
SKA2 = dict(SKA)
SKA1["Tsys"] = 30*1e3 #very rough, underestimating at low nu - but for this analysis okay
SKA1["numin"] = 351 #[MHz]
SKA1["numax"] = 1059
SKA2["Tsys"] = 20*1e3 #overestimating slightly, more like 19 or 18
SKA2["numin"] = 966 #[MHz]
SKA2["numax"] = 1758
hirax = {
"mode": 'interferometer',
'Ndish': 1024, # No. of dishes
'Nbeam': 1, # No. of beams (for multi-pixel detectors)
'Ddish': 6., # Single dish diameter [m]
"t_int": 17520, #4 years at 50% obs fraction in [h]
'Tsys': 50.*(1e3), # System temp. [mK]
#'nu_crit': 1000., #critical frequency, UNCLEAR
'survey_dnutot': 400., # Total bandwidth of *entire* survey [MHz]
'survey_numax': 800., # Max. freq. of survey
'dnu': 0.4, # Bandwidth of single channel [MHz]
'S_area': 1.45*np.pi, # fsky = 15.000 sq. deg. * (pi/180)**2 Total survey area [radians^2]
'Dmax': 307., # Max. interferom. baseline [m]
'Dmin': 7., # Min. interferom. baseline [m]
}
cb_hirax=dict(hirax) #same but with actual baseline file.
cb_hirax.update({'n(x)': "/Users/amadeus/Documents/PhD/work/bao21cm/hirax/hirax_Ndish1024_baseline1.dat"})
hirax512 = dict(hirax)
hirax512.update({ "n(x)": "/Users/amadeus/Documents/PhD/work/bao21cm/hirax/HIRAX_Ndish529_Ndish529_baseline1.dat",
"Ndish": 529,
} )
LSST = {
"dNdz": "/Users/amadeus/Documents/PhD/work/multitracer/LSST/nz_LSST_gold_sqdeg.dat",
"rmax":27, #see bottom of page 71 in the LSST science book 0912.0201
"zmax":3.9,
'sg_file_z': '/Users/amadeus/Documents/PhD/work/MagBias/sg_data/sg_LSST_z.txt',
'sgng_file_z': '/Users/amadeus/Documents/PhD/work/MagBias/sg_data/sgng_LSST_z.txt',
'sg_file_magmax': '/Users/amadeus/Documents/PhD/work/MagBias/sg_data/sg_LSST_mag.txt',
'sgng_file_magmax': '/Users/amadeus/Documents/PhD/work/MagBias/sg_data/sgng_LSST_mag.txt',
'sg_file': '/Users/amadeus/Documents/PhD/work/MagBias/sg_data/sg_LSST.txt',
'sgng_file': '/Users/amadeus/Documents/PhD/work/MagBias/sg_data/sgng_LSST.txt', #for numerical ease, (5sg-2)*ng
'zbgmax_file_magmax': '/Users/amadeus/Documents/PhD/work/MagBias/zbgmax_data/zbgmax_LSST_mag.txt',
'zbgmax_file': '/Users/amadeus/Documents/PhD/work/MagBias/zbgmax_data/zbgmax_LSST.txt',
}
LSST_nosgfit = dict(LSST)# the same but without the sg_file
del LSST_nosgfit["sg_file"]
del LSST_nosgfit["sg_file_z"]
del LSST_nosgfit["sg_file_magmax"]