Simulating observations with MUSTANG-2¶
MUSTANG-2 is a bolometric array on the Green Bank Telescope. In this notebook we simulate an observation of a galactic cluster.
[1]:
import maria
map_filename = maria.io.fetch("maps/small_cluster.h5")
input_map = maria.map.load(
nu=930e9,
filename=map_filename, # filename
width=6/60, # width in degrees
center=(144, 12), # position in the sky
frame="ra_dec",
units="Jy/pixel", # units of the input map
)
input_map.plot()
Downloading https://github.com/thomaswmorris/maria-data/raw/master/maps/small_cluster.h5: 100%|██████████| 3.45M/3.45M [00:00<00:00, 155MB/s]
[2]:
plan = maria.get_plan(
scan_pattern="daisy", # scanning pattern
scan_options={"radius": 2/60, "speed": 0.5/60}, # in degrees
duration=1200, # integration time in seconds
sample_rate=50, # in Hz
scan_center=(144, 12), # position in the sky
frame="ra_dec",
)
plan.plot()
[3]:
instrument = maria.get_instrument("MUSTANG-2")
print(instrument)
instrument.plot()
Instrument(1 array)
├ arrays:
│ n FOV baseline bands
│ array1 217 4.2 arcmin 0 m [m2/f093]
│
└ bands:
center width η NEP NET_RJ NET_CMB \
m2/f093 86.21 GHz 20.98 GHz 0.1 30 aW√s 1.142 mK√s 1.381 mK√s
FWHM
m2/f093 9.133 arcsec
[4]:
sim = maria.Simulation(
instrument,
plan=plan,
site="green_bank",
map=input_map,
atmosphere="2d",
)
print(sim)
Downloading https://github.com/thomaswmorris/maria-data/raw/master/atmosphere/spectra/am/v2/green_bank.h5: 100%|██████████| 11.1M/11.1M [00:00<00:00, 201MB/s]
Downloading https://github.com/thomaswmorris/maria-data/raw/master/atmosphere/weather/era5/green_bank.h5: 100%|██████████| 12.0M/12.0M [00:00<00:00, 175MB/s]
Constructing atmosphere: 100%|██████████| 6/6 [00:07<00:00, 1.28s/it]
Simulation
├ Instrument(1 array)
│ ├ arrays:
│ │ n FOV baseline bands
│ │ array1 217 4.2 arcmin 0 m [m2/f093]
│ │
│ └ bands:
│ center width η NEP NET_RJ NET_CMB \
│ m2/f093 86.21 GHz 20.98 GHz 0.1 30 aW√s 1.142 mK√s 1.381 mK√s
│
│ FWHM
│ m2/f093 9.133 arcsec
├ Site:
│ region: green_bank
│ location: 38°25’59.16”N 79°50’23.28”W
│ altitude: 0.825 km
│ seasonal: True
│ diurnal: True
├ Plan:
│ start_time: 2024-02-10 06:00:00.000 +00:00
│ duration: 1200 s
│ sample_rate: 50 Hz
│ center:
│ ra: 09ʰ36ᵐ0.00ˢ
│ dec: 12°00’0.00”
│ scan_pattern: daisy
│ scan_radius: 4 arcmin
│ scan_kwargs: {'radius': 0.03333333333333333, 'speed': 0.008333333333333333}
├ Atmosphere(6 processes with 6 layers):
│ ├ spectrum:
│ │ region: green_bank
│ └ weather:
│ region: green_bank
│ altitude: 0.825 km
│ time: Feb 10 01:09:59 -05:00
│ pwv[mean, rms]: (8.097 mm, 242.9 um)
└ ProjectedMap:
shape[stokes, nu, t, y, x]: (1, 1, 1, 1000, 1000)
stokes: ['I']
nu: [0.93] THz
t: [1.74501855e+09] s
quantity: rayleigh_jeans_temperature
units: K_RJ
min: -1.831e-02
max: -1.746e-05
center:
ra: 09ʰ36ᵐ0.00ˢ
dec: 12°00’0.00”
size[y, x]: (6 arcmin, 6 arcmin)
resolution[y, x]: (360 marcsec, 360 marcsec)
memory: 8 MB
[5]:
tod = sim.run()
tod.plot()
Generating turbulence: 100%|██████████| 6/6 [00:00<00:00, 30.26it/s]
Sampling turbulence: 100%|██████████| 6/6 [00:01<00:00, 3.57it/s]
Computing atmospheric emission: 100%|██████████| 1/1 [00:02<00:00, 2.13s/it, band=m2/f093]
Sampling map: 100%|██████████| 1/1 [00:03<00:00, 3.97s/it, band=m2/f093]
Generating noise: 100%|██████████| 1/1 [00:00<00:00, 1.05it/s, band=m2/f093]
[6]:
from maria.mappers import BinMapper
mapper = BinMapper(
center=(144, 12),
frame="ra_dec",
width=6/60,
height=6/60,
resolution=0.03/60,
tod_preprocessing={
"window": {"name": "hamming"},
"remove_modes": {"modes_to_remove": [0]},
"remove_spline": {"knot_spacing": 30, "remove_el_gradient": True},
},
map_postprocessing={
"gaussian_filter": {"sigma": 1},
"median_filter": {"size": 1},
},
units="uK_RJ",
)
mapper.add_tods(tod)
output_map = mapper.run()
2025-04-22 16:17:45.387 INFO: Ran mapper for band m2/f093 in 12.73 s.
[7]:
output_map.plot()
output_map.to_fits("/tmp/simulated_mustang_map.fits")
