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Register a new userALMA Temporal Phase Stability and the Effectiveness of Water Vapor Radiometer
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Atacama Large Millimeter/submillimeter Array (ALMA) will be the world largest mm/submm interferometer, and currently the Early Science is ongoing, together with the commissioning and science verification (CSV). Here we present a study of the temporal phase stability of the entire ALMA system from antennas to the correlator. We verified the temporal phase stability of ALMA using data, taken during the last two years of CSV activities. The data consist of integrations on strong point sources (i.e., bright quasars) at various frequency bands, and at various baseline lengths (up to 600 m). From the observations of strong quasars for a long time (from a few tens of minutes, up to an hour), we derived the 2-point Allan Standard Deviation after the atmospheric phase correction using the 183 GHz Water Vapor Radiometer (WVR) installed in each 12 m antenna, and confirmed that the phase stability of all the baselines reached the ALMA specification. Since we applied the WVR phase correction to all the data mentioned above, we also studied the effectiveness of the WVR phase correction at various frequencies, baseline lengths, and weather conditions. The phase stability often improves a factor of 2 - 3 after the correction, and sometimes a factor of 7 improvement can be obtained. However, the corrected data still displays an increasing phase fluctuation as a function of baseline length, suggesting that the dry component (e.g., N2 and O2) in the atmosphere also contributes the phase fluctuation in the data, although the imperfection of the WVR phase correction cannot be ruled out at this moment.
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We report on laboratory test results of the Compact Water Vapor Radiometer (CWVR) prototype for the NSFs Karl G. Jansky Very Large Array (VLA), a five-channel design centered around the 22 GHz water vapor line. Fluctuations in precipitable water vapor cause fluctuations in atmospheric brightness emission, which are assumed to be proportional to phase fluctuations of the astronomical signal seen by an antenna. Water vapor radiometry consists of using a radiometer to measure variations in the atmospheric brightness emission to correct for the phase fluctuations. The CWVR channel isolation requirement of < -20 dB is met, indicating < 1% power leakage between any two channels. Gain stability tests indicate that Channel 1 needs repair, and that the fluctuations in output counts for Channel 2 to 5 are negatively correlated to the CWVR enclosure ambient temperature, with a change of ~ 405 counts per 1 degree C change in temperature. With temperature correction, the single channel and channel difference gain stability is < 2 x 10^-4, and the observable gain stability is < 2.5 x 10^-4 over t = 2.5 - 10^3 sec, all of which meet the requirements. Overall, the test results indicate that the CWVR meets specifications for dynamic range, channel isolation, and gain stability to be tested on an antenna. Future work consists of building more CWVRs and testing the phase correlations on the VLA antennas to evaluate the use of WVR for not only the VLA, but also the Next Generation Very Large Array (ngVLA).
The Atacama Large millimetre/submillimetre Array (ALMA) makes use of water vapour radiometers (WVR), which monitor the atmospheric water vapour line at 183 GHz along the line of sight above each antenna to correct for phase delays introduced by the wet component of the troposphere. The application of WVR derived phase corrections improve the image quality and facilitate successful observations in weather conditions that were classically marginal or poor. We present work to indicate that a scaling factor applied to the WVR solutions can act to further improve the phase stability and image quality of ALMA data. We find reduced phase noise statistics for 62 out of 75 datasets from the long-baseline science verification campaign after a WVR scaling factor is applied. The improvement of phase noise translates to an expected coherence improvement in 39 datasets. When imaging the bandpass source, we find 33 of the 39 datasets show an improvement in the signal-to-noise ratio (S/N) between a few to ~30 percent. There are 23 datasets where the S/N of the science image is improved: 6 by <1%, 11 between 1 and 5%, and 6 above 5%. The higher frequencies studied (band 6 and band 7) are those most improved, specifically datasets with low precipitable water vapour (PWV), <1mm, where the dominance of the wet component is reduced. Although these improvements are not profound, phase stability improvements via the WVR scaling factor come into play for the higher frequency (>450 GHz) and long-baseline (>5km) observations. These inherently have poorer phase stability and are taken in low PWV (<1mm) conditions for which we find the scaling to be most effective. A promising explanation for the scaling factor is the mixing of dry and wet air components, although other origins are discussed. We have produced a python code to allow ALMA users to undertake WVR scaling tests and make improvements to their data.
Time-variable absorption by water vapor in Earths atmosphere presents an important source of systematic error for a wide range of ground-based astronomical measurements, particularly at near-infrared wavelengths. We present results from the first study on the temporal and spatial variability of water vapor absorption at Apache Point Observatory (APO). We analyze $sim$400,000 high-resolution, near-infrared ($H$-band) spectra of hot stars collected as calibration data for the APO Galactic Evolution Explorer (APOGEE) survey. We fit for the optical depths of telluric water vapor absorption features in APOGEE spectra and convert these optical depths to Precipitable Water Vapor (PWV) using contemporaneous data from a GPS-based PWV monitoring station at APO. Based on simultaneous measurements obtained over a 3$^{circ}$ field of view, we estimate that our PWV measurement precision is $pm0.11$ mm. We explore the statistics of PWV variations over a range of timescales from less than an hour to days. We find that the amplitude of PWV variations within an hour is less than 1 mm for most (96.5%) APOGEE field visits. By considering APOGEE observations that are close in time but separated by large distances on the sky, we find that PWV is homogeneous across the sky at a given epoch, with 90% of measurements taken up to 70$^{circ}$ apart within 1.5 hr having $Delta,rm{PWV}<1.0$ mm. Our results can be used to help simulate the impact of water vapor absorption on upcoming surveys at continental observing sites like APO, and also to help plan for simultaneous water vapor metrology that may be carried out in support of upcoming photometric and spectroscopic surveys.
We report on the measurements of telluric water vapor made with the instrument FIFI-LS on SOFIA. Since November 2018, FIFI-LS has measured the water vapor overburden with the same measurement setup on each science flight with about 10 data points throughout the flight. This created a large sample of 469 measurements at different locations, flight altitudes and seasons. The paper describes the measurement principle in detail and provides some trend analysis on the 3 parameters. This presents the first systematic analysis with SOFIA based on in situ observations.
Ice-water, water-vapor interfaces and ice surface are studied by molecular dynamics simulations with the SPC/E model of water molecules having the purpose to estimate the profiles of electrostatic potential across the interfaces. We have proposed a methodology for calculating the profiles of electrostatic potential based on a trial particle, which showed good agreement for the case of electrostatic potential profile of the water-vapor interface of TIP4P model calculated in another way. The measured profile of electrostatic potential for the pure ice-water interface decreases towards the liquid bulk region, which is in agreement with simulations of preferential direction of motion of Li$^{+}$ and F$^{-}$ solute ions at the liquid side of the ice-water interface. These results are discussed in connection with the Workman-Reynolds effect.
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