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Project Summary

High-mass stars (M > 8 M_Sun), though rarer than low-mass stars, are nevertheless a dominant source of energy and chemical enrichment in the interstellar medium (ISM). Because massive stars are rarer and form in denser, more opaque gas, their formation is more difficult to observe and is less well understood than for low-mass stars. Considering that high-mass stars form in dense (n~10⁴ cm^-3) molecular clumps (M=200-5000 M_Sun, R~1 pc), the study of these clumps is important. Thus, we have undertaken RAMPS to help answer some of the open questions concerning high-mass star formation.

RAMPS is particularly well suited to help answer three open questions.

1. How do high-mass star-forming clumps evolve? We can estimate the evolutionary state of a clump from its mid-infrared emission. The figure below shows the 3.6 µm (blue) and 8 µm (green) emission from GLIMPSE (Churchwell et al. 2009), the 24 µm (red) emission from MIPSGAL (Carey et al. 2009), and RAMPS NH₃(1,1) integrated intensity contours in white. We will separate the clumps RAMPS detects into three categories: “quiescent” (mid-infrared dark), “protostellar” (compact 24 µm emission), and “H II region” (extended 8µm emission). In addition to tracing the dense gas where high-mass stars form, the NH₃ inversion lines can estimate several important quantities. In local thermodynamic equilibrium, these NH₃ lines provide us with the gas temperature, the NH₃ column density, and the turbulent velocity dispersion. We will then investigate how these quantities, as well as the presence of H₂O and CH₃OH masers, change as a function of evolutionary state. 
2. What is the role of filaments in high-mass star formation? Infrared and radio continuum surveys of the Galactic plane have shown that filamentary structures are common in the ISM, but the role these filaments play is still uncertain. With RAMPS we can deduce the velocity dispersion, the linear mass density, and the spacing of clumps along filaments, information that can help us better understand the structure and fragmentation of filaments.
3. What is the Galactic distribution of star formation and evolved stars? Through measured clump velocities, NH₃ lines also provide kinematic distances. While a single velocity may correspond to two possible distances, the kinematic distance ambiguity can be resolved by the presence or absence of H I absorption/self-absorption (Whitaker et al. 2017). With the Galactic coordinates and distance to each detected clump, we can determine the 3D Galactic distribution of high-mass star-forming clumps. In addition to tracing active star formation, H₂O masers also trace the asymptotic giant branch (AGB) star population. Thus, RAMPS can also provide some information on the spatial distribution of AGB stars in the Galaxy.

Team Members

• James Jackson (PI)
• Taylor Hogge
• Ian Stephens
• Scott Whitaker
• Jonathan Foster
• Matthew Camarata
• D. Anish Roshi
• James Di Francesco
• Steven Longmore
• Robert Loughnane
• Toby Moore
• Jill Rathborne
• Patricio Sanhueza
• Andrew Walsh

Reference

Please use the following reference for RAMPS data in your publication:
\bibitem[Hogge et al.(2018)]{2018ApJS..237…27H} Hogge, T., Jackson, J., Stephens, I., et al.\ 2018, \apjs, 237, 27

Acknowledgement

Please use the following acknowledgement in any publication that makes use of RAMPS data:
This publication makes use of molecular line data from the Radio Ammonia Mid-Plane Survey (RAMPS). RAMPS is supported by the National Science Foundation under grant AST-1616635.

How to use the GUI

To use the GUI enter ‘gbt-rfi-gui’ at the command line on any GBO linux computer.

Select your desired frequency range by selecting the receiver you are interested in. For most receivers simply selecting the receiver is sufficient to select the full range of that band. For the Prime Focus receivers please input the frequency range of your desired receiver at the start and end frequency text boxes (ie 290-390 MHz for Prime Focus 342).

If you would like a subset of the receiver band, input the desired frequency range in the start and end frequency text boxes, noting that the frequency is in MHz.

To select a start date of your desired time range you can either type in a date or use the drop down arrow to select from a calendar. The same method is used for selecting an end date. Note that you will be restricted to a year maximum for data retrieval. If there are no sessions for your desired receiver in the given time range the date will be shifted to a new range that includes sessions. Please note for long time ranges the GUI may take some time to populate the plots.

You have the option of saving the data from these plots in a csv file by ticking the “save data from plot” box before plotting with the requested arguments.

Two plots will appear for your selected arguments. The first is an “Averaged RFI Environment at Green Bank Observatory”. This plot averages the scans in the time range provided to create a line plot. You may manipulate this plot using standard methods, e.g. using the mouse to zoom in, saving plots, and other methods used for a matplotlib generated plot. The plot originally shows the data with Frequency in MHz across the x-axis and an averaged intensity in Janksys on the y-axis zoomed in to show a range of -10 to 500 Janskys. A data summary is also provided at the top of this plot.

The second plot is a color plot for each of the RFI sessions that occurred during the requested time period. This plot provides a look at the log of the flux (in Janskys) over the frequency range of the receiver per session instance.

Common Science Uses

1. When planning for a proposal for time on the Green Bank Telescope one can use this GUI to get an idea of the spectral occupancy as seen by the GBT receivers and appropriately plan observations around the current RFI.
2. When observing, one can use this GUI to understand if the RFI observed is commonplace for that region of the band.
3. In the data reduction process, this GUI can be used to help flag or identify potential RFI sources in the data.

Background on RFI Scans

RFI scans are performed routinely by the operators during gaps between astronomical observations. The aim of the technique is to do the best job of monitoring narrow-band RFI coming from the horizon (which comes at the cost of monitoring changes in the RFI from satellites, nearby planes, etc.). The GBT, which can’t point below an elevation of 5 deg (typically many beamwidths), has very little sensitivity to horizon-based RFI in its forward direction. The sidelobes in the forward direction are also not uniform. The telescope is much more sensitive to radiation that comes from the horizon and that enters the sidelobes of the feeds. To make the sensitivity of the feed patterns uniform around the horizon we position the elevation of the antenna so that the flange of the feed is parallel to the horizon. The feed sidelobes also have uniform sensitivity as they cover a very large solid angle. Gregorian receivers require a different elevation than PF receivers to put the feeds into this orientation. However, the single telescope feed arm will introduce azimuthal diffraction patterns on top of the feed sidelobe patterns. To smooth out this azimuthal dependence, the telescope moves at near its top speed from Az=0 to 180 (or Az=180 to 0 if that’s a more efficient route). With this tactic, one can’t expect the monitoring of RFI that comes from the forward direction (satellites, etc.) to be anything more than hit and miss. Please note that some RFI in the X-band range may be due to satellites and because of the data reduction process this may seem worse than actuality. Please talk to your project friend with any concerns about RFI in this band.

The data reduction uses the average of the raw bandpass data across the full slew and the average of the two polarizations (if the receiver has dual polarization). The raw bandpasses are put through a high-pass filter (with an upper frequency of 0.1 channels-1), which removes the overall bandpass shape. The use of a high-pass filter does the best job of depicting narrow-band RFI (our primary aim), but which comes at the cost of compromising the detection of wide-band RFI if it is significantly wider than about 10 channels.

Since the noise diode flickers throughout the observing, the bandpass power is converted into units of antenna temperatures using the ratio of the detected total power to the change in power when the diode is on. Since observers want to know the level at which the RFI would contaminate their observations, the signal strength observers would see is mimicked by converting Ta to Jy using the antenna’s main-beam gain.

The scripts used to process RFI plots for baseline removal, etc. are based on those listed below. This list contains links to these scripts.

• scalUtils.pro
• rfiDisplay.pro

If you would like the raw data of RFI scans please contact the GB helpdesk for data retrieval at help.nrao.edu.

This system has been automated to ingest into a database, updating every 24 hours ensuring scans that have been taken by the telescope are accessible within a 24 hour period.