An LMT glossary

There are some overloaded and confusing terms in here. E.g. pixel/cell/beam and board/band/bank/chassis are notorious. Resolution/FWHM can be confusing too. See also the correspondence table of some overloaded terms after the glossary. See Overloaded Terms.

1MMRx

The 1mm MSIP receiver has one beam on the sky, measuring two polarizations in an USB and LSB, thus there are 4 spectra at the same position on the sky. Commisioned April 2018.

band

A coherent section of channels in frequency space. For RSR there are 6 bands, sometimes the word board is used as well, although the ordering of bands and boards is different. bands are ordered in frequency (by our convention). See also bank

bank

A set of spectrometers that cover the same IF band at the same resolution (and number of channels). There is no side-band restriction. For SEQUOIA we use two banks currently, though both need to be in the band below 100GHz or in the band above 100GHz. For the MSIP 1mm receiver there are two, although they have one in USB and one in LSB.

beam

The footprint of one receiver horn on the sky. Sequioa has a 4x4 multi-beam receiver, numbered 0 through 15. Not to be confused with the FWHM. At 115 GHz the FWHM is about 16”, at 86 GHz about 21”. The beam separation is 27.8” for Sequoia. The word pixel has also been used for beam, but this is discouraged as this has an overloaded means in our final images. See also cell.

Note that for some instruments beams are also interpreted while including other simulteanously taken data in another band/polarization

Beam Switching

This is a variation on position switching using a receiver with multiple pixels. The “Main” and “Reference” positions on the sky are calculated so that the receiver is always pointing at the source. This is most useful for point sources.

beammap

A special observing mode (always in Az-El?) where you map around a strong source, e.g. Ori-KL. Usually a small field.

board

for SLR these are the roach boards (4 or 8). For RSR they are called chassis (4). But in RSR board has also been used where band is meant, but there is a subtle difference where bands are ordered in frequency.

bufpos

WARES variable to denote what type of data is being received. bufpos: 0=on 1=off 2=sky 3=hot. A value of 100 can be added if a reference a grid posititon in a grid map needs to be made.

cell

(most people would call this a pixel, but at LMT pixel is an overloaded word also used for the beams in Sequoia. In the gridder we use –cell=. This will be the pixel size in the final FITS images.

chassis

for RSR there are 4 chassis boards, which are tuples of two beams and two polarizations (though the beams look at the same sky position here)

dasha

A python frontend to dash, currently used by TolTeca

dreampy, dreampy3

The set of python modules that you need to reduce RSR data

ECSV

(Enhanced Character Separated Values) a self-describing ascii table format popularized by astropy. See also https://github.com/astropy/astropy-APEs/blob/main/APE6.rst

FITS

(Flexible Image Transport System): the export format for data-cube, although there is also a waterfall cube (time-freq-pixel) cube available. Unclear what we will use for pure spectra. SDFITS seems overly complex. CLASS needs to be supported. Currently RSR exports ASCII tables, not even ECSV

FWHM

(Full Width Half Max): the effective resolution of the beam if normally given in FITS keywords BMAJ,BMIN,BPA. The term resolution

grid map

A sequence of spectra taken on a regular grid of sky points. In this procedure, the telescope tracks a specifc position in the grid as the “Main” position in a position switched spectrum. The procedure allows the user to defne a single integration on the “Reference” position to be used for all points or allows the user to interleave additional “Reference” spectra into the observation.

horn

Another term used for beam or pixel.

LMTSLR

The LMT Spectral Line Reduction modules you will need to reduce WARES based data.

MC

Monitor and Control system, the system that runs the online LMT system.

ObsNum

Observatation Number. This is not all, obsnum is part of the (ObsNum ,

SubObsNum , ScanNum) tuple,

but for most applications you only need to know the ObsNum

OMAyA

(One Millimeter Array Receiver for Astronomy): 200-280 GHz. 8 “pixels” (beams) on sky, each dual polarization, with two sidebands. IF can be 4-12 GHz in each sideband. This is a planned instrument.

OMAR

something with omaya? Or is this another term for OMAYA

OTF Mapping

In this procedure the telescope is scanned across the sky to sample the emission. The samples are then “gridded” into a map.

PHAMAS

(Phased Array Receiver for Millimeter Astronomy): 64 element receiver - prototype.

pixel

synonym for beam as in multi-beam. The keyword –pix_list= is used to select pixels (0..15) for processing.

plotly

dash uses plotly, which is a data analytics framework working within a browser environment.

Position Switching

This is a standard way to obtain spectra by switching between a “Main” and “Reference” position on the sky.

ProjectId

Each LMT observing proposal has a unique proposal ID assigned. An example is 2018-S1-MU-46, which contains the proposal year, session, institution and proposal number.

Quick Look data

At the LMT there are “Quick Look” data that will be used to assess if data will be scientifically viable. Usually made available via the Shift Report website. See also Timely Analysis Products (TAP) for a view closer to the science data.

ramp

The ramp is the area where not all beams have been. Within the ramp there is thus a non-uniform coverage. The ramp covers 3 beams (not FWHM, but pixel), so about 85”. For any maps smaller than about 200” there is no good area of uniform coverage. Should have a plot of that here, and maybe compare that to a large M51 area?

resolution

this term is used in the gridder, but it’s not FWHM, it’s lambda/D. Keyword –resolution= is used If selected this way, FWHM is then set as 1.15 * resolution. But if resolution is chosen larger, what is the effective FWHM? It would be better to have a dimensionless term for resolution/pixel and a different name for resolution alltogether.

roach board

The SLR had four (4) roach boards, now eight (8), each of which writes a separate file with its own internal clock that later needs to be sync’d. In a future expansion we get 8 boards (2 pols, 2 IFs) , capable of writing 8 files. Rumor: for the 1mmRx configuration can be done on one board, hence one file (new IF switching system).

RSR

(Redshift-Search-Receiver): operates between 70 and 110 GHz in 6 separate bands of 256 channels each. Typical resolution: 100 km/s. (30 MHz) The RSR has two beams on the sky, each beam has two polarizations to form 4 independent calibrated spectra; the polarization pairs for each beam are collected through the same horn. These 4 are referred to as the 4 chassis. Salient detail: RSR does not doppler track.

runfile

A simple text file of (LMTOY pipeline) commands, one per line. Although more limiting than full programmable bash scripts, these can be executed serially by bash, or in parallel by GNU parallel or SLURM. The lmtoy script generator will produce sets of runfile’s. The webrun environment also deals with runfiles, as they are submitted to Unity via SLURM.

ScanNum

Scan Number - see ObsNum

SDFITS

Single Dish FITS format, normally used to store raw or even calibrated spectra in a FITS BINTABLE format. Each row in a BINTABLE has an attached RA,DEC (and other meta-data), plus the whole spectrum. This standard was drafted in 1995 (Liszt), and has been implemented by many telescopes (Arecibo, FAST, GBT, Parkes, ….)

SEQUOIA

85-115.6 GHz, has a 4x4 multi-beam (pixel) receiver. Can do multiple backend spectrometers tuned indepedently in a 15GHz window. In the single IF mode (before April 2023) beams 0..15 are used, but in dual IF mode, beams can be counted 0..31 to select from bank0 or bank1.

SFL

Sanson-Flamsteed projection, used in LMT FITS files (the GLS - GLobal Sinusoidal is similar to SFL).

Shift Report

See Quick Look Data

SLR

(Spectral Line Receiver) The common name for the (SEQ/1MM/OMA) instruments, since they share WARES hardware. Name is also used in lmtslr, the python module.

SLURM

A workload manager to submit jobs to a queue, in our case for Unity.

SpecFile

A netcdf file containing the calibrated spectra, ready for gridding. This is equivalent to an SDFITS file. In a future version we may replace the SpecFile with an SDFITS file.

Spectral Window

In ALMA commonly abbreviated as spw, this is closest to what we call a bank, a set of linearly spaced channels.

Spectrum

A coherent section in frequency space, with its own unique meta-data (such as polarization, ra, dec, time). Normally the smallest portion of data we can assign. A spectrum is defined by its own seting of (crval, crpix, cdelt) in a FITS WCS sense. See also Data Dimensions.

SRDP

Science Ready Data Products (SRDP) are the data produced by the pipeline that can be used to write a paper, in theory. In practice the PI will want to assess the quality, perhaps even tune some pipeline parameters, and re-run the pipeline.

SubObsNum

Sub-Observatation Number - see ObsNum

Timely Analysis Products (TAP)

The SLpipeline produces a set of Timely Analysis Products, mostly in the form of figures, for the PI to asses the quality of the data. Normally presented on a web server, though the TAP is also available as a tar file. The TAP does not contain See also SRDP. TAP is also known as the Table Access Protocal in the IVOA world. Not to be confused.

TolTec

Continuum mapping instrument

TolTeca

Python frontend for the TolTec instrument. Is dasha based.

Unity

An HPC system consisting of many compute nodes. We run the SLpipeline here, though they need to be submitted via a workload manager, called SLURM

WARES

(Wideband Arrayed ROACH Enabled Spectrometer). The spectrometer used for Sequoia/1MM/Omaya. Also used for the name of the computer that receives data from the individual roach boards in the spectrometer hardware.

webrun

Placeholder name for the futuure webbased environemnt that allows one to run pipeline on a project for science data.

Overloaded Terms

Terms used in the code may not exactly match terms used by the develpers of the instruments. Here we clarify those overloaded terms in the form of a table

Table of some overloaded terms

code term	RSR term	SLR term	comments
beam	pixel?	pixel	multi-beam receiver
cell	n/a	cell	size of a sky pixel in gridding, usually 2-3 times smaller than the resolution
band	board	bank	spectrometer window
n/a	chassis	n/a	tuple of (pol,beam)
channel	channel	channel	with a simple FREQ WCS{crval,crpix,cdelt}

Data Dimensions

This section is not meant to describe either the RAW (netCDF) or SDFITS format, but the storage model we have in mind to be encapsulated in a Python class.

A unified data storage of LMT spectra would (naturally) break up the spectra, such that each spectrum has a different time, beam, band, polarization, etc. Each spectrum can be described as a set of sequential channels, described with a single (crval,crpix,cdelt)) WCS. In Python row-major array notation where the most slowly varying dimension comes first this could be written as an NDarray:

data[ntime, nbeam, npol, nband, nchan]

where we added the ntime and nchan as the slowest resp. fastest running dimension in this row-major (python/C) notation.

Note

For those used to GBTIDL plnum = npol, ifnum = nband, and fdnum = nband. Arguably different scans can act as as ntime, although each scan will often have several snapshots inside of them. ?? intnum

Overloaded words, including GBT lingo:

plnum   pol
fdnum   feed     beam    pixel
ifnum   window   band

Taking out those an observation can be seen as a set of spectra:

spectrum[nbeam, npol, nband]

This exactly matches the concepts used in an SDFITS file, although in the general definition of SDFITS there is no assumption of the data being able to be stored in an NDarray type array, where the more general

sdfits_data[naxis2, ndata]

where in general ndata=nchan, but dialect with ndata = npol * nchan are seen in the wild (FAST, Parkes). The FITS name naxis2 is the number of rows, which is the product of time,beam,band,pol in our case.

Taking an inventory of current and known future LMT Spectral Line instruments:

• RSR: two beams, two pols, 6 bands, though the term chassis is used to point at any tuple of (beam,pol). So here we have nbeam=2, npol=2,nband=6, nchan=256 and ntime it typically 10-20. Each beam happens to look at the same sky position here.

Note

If an instrument like RSR would multiplex the (beam,pol) pairs, this would be a challenge to the assumption of homogeneity, and the SDFITS model would be more appropriate.

• 1MM: one beam, two pols, two sidebands. So here we have nbeam=1, bpol=2, nband=2, nchan=2k

• SEQ: 16 beams (though 4 beams per roach board, and each roach board has its own time) in one band (they also call it bank) and one polarization. Thus nbeam=16, npol=1, nband=1. Once the 2nd IF will be installed, 32 beams will be recognized by the software, but organizationally it is easier to to think of 16 beams and 2 bands.

Note

The timestamps for the different roach boards make it impossible to store the data in a multi-dimensional array, unless (typicall one) integration is removed. Keeping all data would require data[ntime4, 1, 1, 1, nchan] for SEQ.

• OMA 8 beams, 2 bands (banks), 2 polarizations.

• B4R 4 XFFTS boards, 2.5 GHz/board: 1 beam, 2 bands (USB and LSB), 2 polarizations (XX and YY)

Note that FAST is the only known case that stores data as data[ntime, nchan, npol], where nchan is not the fastest running dimension, but npol. Technically this appears to be the case such that they can vary nchan per row.

We thus arrive at the following summary for the multi-dimensional data[] array:

data[ntime, nbeam, npol, nband, nchan]

in the table we leave out the ntime dimension

Table of data dimensions of LMT SLR instruments

data	nbeam	npol	nband	nchan	comment
RSR	2	2	6	256	(pol,beam) tuples are the 4 chassis. 6 overlapping bands make one final spectrum
SEQ	16	1	1 (2)	2k, 4k, 8k	beams have time issue, perhaps ntime ~ ntime * nbeam, and nbeam=1. Future will have 2 bands
OMA	8	2	2	2k, 4k, 8k	Future instrument, with 4 more roach boards (USB+LSB)
1MMRx	1	2	2	2k, 4k, 8k	band: 2 IF’s in USB/LSB
B4R	1	2	2	32k	Japanese 2mm receiver

Single Dish Math

The meat of Single Dish math is getting the system temperature

\[T_{sys} = T_{amb} { { SKY } \over { HOT - SKY } }\]

and using this system temperature, calculating the signal by comparing an ON and OFF position, assuming there is only sky in the OFF:

\[T_A = T_{sys} { { ON - OFF } \over {OFF} }\]

All of these have values for each channel. How exactly the \(T_{sys}\) is computed (scalar, vector, mean/median) is something we generally leave open.

Observing: ObsNum / SubObsNum / ScanNum

An observation with a single dish such as LMT is done via proposals, which gets assigned a proposal ID, associated with the P.I. name. An example of such is 2018-S1-MU-46

An observation is that divided in a set a ObsNum ‘s, which can be hierchically divided up in SubObsNum’s and ScanNum’s. When an observing script executes, each source will gets its own ObsNum, though calibration data often gets another ObsNum.