Arrays

An Array is a set of detectors, either at the same point in space distributed across some field of view (e.g. a bolometric camera) or distributed in space looking at the same point on the sky (e.g. an interferometer). To generate a custom Array we specify a configuration as a dict, for example as

from maria import Array

my_array = {"n": 217,
            "field_of_view": 0.5, # in degrees
            "primary_size": 10, # in meters
            "bands": ["act/pa5/f090", "act/pa5/f150"]}

Array.from_config(my_array).plot()

(Source code, png, hires.png, pdf)

where the bands parameter is a list of either Band object or a string corresponding to a pre-defined band.

Note

The items in the list supplied as the bands parameter can be a Band object, a dict, or a str. The following are all valid bands:

band_1 = Band(center=150, width=30, NET_RJ=1e-5)

band_2 = {"center": 90, "width": 30, "NEP": 1e-15}

band_3 = "act/pa5/f150"

Hint

To see all available pre-defined bands, run print(maria.all_bands). For documentation on how to define a custom band, refer to the Bands section.

We can then generate an Instrument as

from maria import Instrument

instrument = Instrument(arrays=[my_array])

which generates an array of 1000 multichroic detectors (a detector per band per array position).

Note

The items in the arrays list can be an Array object, a dict, or a str. The following are all valid arrays that can be in an arrays list:

array_1 =  {"n": 217,
           "field_of_view": 0.5, # in degrees
           "primary_size": 10, # in meters
           "bands": ["act/pa5/f090", "act/pa5/f150"]}

array_2 = Array.from_config(array_1)

array_3 = "so/sat-wafer"

We can also leave the number of detectors n implicit and define an array with a given field of view as

array = {"primary_size": 10,
         "field_of_view": 0.5,
         "bands": [band_1, band_2]}

Here, maria will infer the number of detectors by packing the field of view with beams of a given resolution (determined by the primary_size and bands parameters). By default, the spacing between the beams will be 1.5 times the FWHM, but we can adjust the ratio with the beam_spacing parameter.

Multiple arrays

Many instruments are made up of individual subarrays that set next to each other on the focal plane. We can create an instrument made of identical subarrays with

from maria import Instrument

array = {"primary_size": 5,
         "field_of_view": 1.0,
         "bands": ["act/pa5/f090", "act/pa5/f150"]}

subarray_left = {"focal_plane_offset": (-1, 0), **array}
subarray_right = {"focal_plane_offset": (1, 0), **array}

instrument = Instrument(arrays=[subarray_left, subarray_right])

instrument.plot()

(Source code, png, hires.png, pdf)

Polarized arrays

We can define an array with polarized detectors as

array = {"n": 1000,
         "field_of_view": 0.5,
         "primary_size": 10,
         "polarized": True,
         "bands": [my_band]}

which will generate two orthogonally polarized detectors per band per array position.

Array shapes and packings

By default, the generated array is hexagonal with a triangular packing. We can change both of these with the shape and packing parameters. Consider

from maria import Array

octagonal_array = {"n": 1005,
                   "shape": "octagon",
                   "packing": "square",
                   "field_of_view": 0.5, # in degrees
                   "primary_size": 25, # in meters
                   "bands": ["act/pa5/f090", "act/pa5/f150"]}

Array.from_config(octagonal_array).plot()

(Source code, png, hires.png, pdf)

or

from maria import Array

flower_array = {"n": 400,
            "shape": "circle",
            "packing": "sunflower",
            "field_of_view": 0.5, # in degrees
            "primary_size": 10, # in meters
            "bands": ["act/pa5/f090", "act/pa5/f150"]}

Array.from_config(flower_array).plot()

(Source code, png, hires.png, pdf)

To generate a long, thin array, we parametrize the array in terms of the numbers of rows and columns:

from maria import Array

stripe_array = {"n_col": 5,
                "n_row": 25,
                "shape": "square",
                "packing": "triangular",
                "field_of_view": 0.5,
                "primary_size": 15,
                "bands": ["act/pa5/f090", "act/pa5/f150"]}

Array.from_config(stripe_array).plot()

(Source code, png, hires.png, pdf)