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Register a new userMUSTANG: 90 GHz Science with the Green Bank Telescope
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MUSTANG is a 90 GHz bolometer camera built for use as a facility instrument on the 100 m Robert C. Byrd Green Bank radio telescope (GBT). MUSTANG has an 8 by 8 focal plane array of transition edge sensor bolometers read out using time-domain multiplexed SQUID electronics. As a continuum instrument on a large single dish MUSTANG has a combination of high resolution (8) and good sensitivity to extended emission which make it very competitive for a wide range of galactic and extragalactic science. Commissioning finished in January 2008 and some of the first science data have been collected.
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The Green Bank Telescope (GBT) is the largest fully steerable radio telescope in the world and is one of our greatest tools for discovering and studying radio pulsars. Over the last decade, the GBT has successfully found over 100 new pulsars through large-area surveys. Here I discuss the two most recent---the GBT 350 MHz Drift-scan survey and the Green Bank North Celestial Cap survey. The primary science goal of both surveys is to find interesting individual pulsars, including young pulsars, rotating radio transients, exotic binary systems, and especially bright millisecond pulsars (MSPs) suitable for inclusion in Pulsar Timing Arrays, which are trying to directly detect gravitational waves. These two surveys have combined to discover 85 pulsars to date, among which are 14 MSPs and many unique and fascinating systems. I present highlights from these surveys and discuss future plans. I also discuss recent results from targeted GBT pulsar searches of globular clusters and Fermi sources.
We characterize the Millimeter Astronomy Legacy Team 90 GHz (MALT90) Survey and the Mopra telescope at 90 GHz. We combine repeated position-switched observations of the source G300.968+01.145 with a map of the same source in order to estimate the pointing reliability of the position-switched observations and, by extension, the MALT90 survey; we estimate our pointing uncertainty to be 8 arcseconds. We model the two strongest sources of systematic gain variability as functions of elevation and time-of-day and quantify the remaining absolute flux uncertainty. Corrections based on these two variables reduce the scatter in repeated observations from 12-25% down to 10-17%. We find no evidence for intrinsic source variability in G300.968+01.145. For certain applications, the corrections described herein will be integral for improving the absolute flux calibration of MALT90 maps and other observations using the Mopra telescope at 90 GHz.
We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.
We describe the design and deployment of GREENBURST, a commensal Fast Radio Burst (FRB) search system at the Green Bank Telescope. GREENBURST uses the dedicated L-band receiver tap to search over the 960$-$1920 MHz frequency range for pulses with dispersion measures out to $10^4$ pc cm$^{-3}$. Due to its unique design, GREENBURST will obtain data even when the L-band receiver is not being used for scheduled observing. This makes it a sensitive single pixel detector capable of reaching deeper in the radio sky. While single pulses from Galactic pulsars and rotating radio transients will be detectable in our observations, and will form part of the database we archive, the primary goal is to detect and study FRBs. Based on recent determinations of the all-sky rate, we predict that the system will detect approximately one FRB for every 2$-$3 months of continuous operation. The high sensitivity of GREENBURST means that it will also be able to probe the slope of the FRB source function, which is currently uncertain in this observing band.
Analysis of Kepler mission data suggests that the Milky Way includes billions of Earth-like planets in the habitable zone of their host star. Current technology enables the detection of technosignatures emitted from a large fraction of the Galaxy. We describe a search for technosignatures that is sensitive to Arecibo-class transmitters located within ~420 ly of Earth and transmitters that are 1000 times more effective than Arecibo within ~13 000 ly of Earth. Our observations focused on 14 planetary systems in the Kepler field and used the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. Each source was observed for a total integration time of 5 minutes. We obtained power spectra at a frequency resolution of 3 Hz and examined narrowband signals with Doppler drift rates between +/-9 Hz/s. We flagged any detection with a signal-to-noise ratio in excess of 10 as a candidate signal and identified approximately 850 000 candidates. Most (99%) of these candidate signals were automatically classified as human-generated radio-frequency interference (RFI). A large fraction (>99%) of the remaining candidate signals were also flagged as anthropogenic RFI because they have frequencies that overlap those used by global navigation satellite systems, satellite downlinks, or other interferers detected in heavily polluted regions of the spectrum. All 19 remaining candidate signals were scrutinized and none were attributable to an extraterrestrial source.
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