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Register a new userWide Bandwidth Considerations for ALMA Band 2
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One of the main considerations in the ALMA Development Roadmap for the future of operations beyond 2030 is to at least double its on-sky instantaneous bandwidth capabilities. Thanks to the technological innovations of the past two decades, we can now produce wider bandwidth receivers than were foreseen at the time of the original ALMA specifications. In several cases, the band edges set by technology at that time are also no longer relevant. In this memo, we look into the scientific advantages of beginning with Band 2 when implementing such wideband technologies. The Band 2 receiver system will be the last of the original ALMA bands, completing ALMAs coverage of the atmospheric windows from 35-950 GHz, and is not yet covered by any other ALMA receiver. New receiver designs covering and significantly extending the original ALMA Band 2 frequency range (67-90 GHz) can now implement these technologies. We explore the scientific and operational advantages of a receiver covering the full 67-116 GHz atmospheric window. In addition to technological goals, the ALMA Development Roadmap provides 3 new key science drivers for ALMA, to probe: 1) the Origins of Galaxies, 2) the Origins of Chemical Complexity, and 3) the Origins of Planets. In this memo, we describe how the wide RF Band 2 system can help achieve these goals, enabling several high-profile science programmes to be executed uniquely or more effectively than with separate systems, requiring an overall much lower array time and achieving more consistent calibration accuracy: contiguous broad-band spectral surveys, measurements of deuterated line ratios, and more generally fractionation studies, improved continuum measurements (also necessary for reliable line flux measurements), simultaneous broad-band observations of transient phenomena, and improved bandwidth for 3 mm very long baseline interferometry (VLBI).
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We discuss the science drivers for ALMA Band 2 which spans the frequency range from 67 to 90 GHz. The key science in this frequency range are the study of the deuterated molecules in cold, dense, quiescent gas and the study of redshifted emission from galaxies in CO and other species. However, Band 2 has a range of other applications which are also presented. The science enabled by a single receiver system which would combine ALMA Bands 2 and 3 covering the frequency range 67 to 116 GHz, as well as the possible doubling of the IF bandwidth of ALMA to 16 GHz, are also considered.
We extend profile domain pulsar timing to incorporate wide-band effects such as frequency-dependent profile evolution and broadband shape variation in the pulse profile. We also incorporate models for temporal variations in both pulse width and in the separation in phase of the main pulse and interpulse. We perform the analysis with both nested sampling and Hamiltonian Monte Carlo methods. In the latter case we introduce a new parameterisation of the posterior that is extremely efficient in the low signal-to-noise regime and can be readily applied to a wide range of scientific problems. We apply this methodology to a series of simulations, and to between seven and nine yr of observations for PSRs J1713$+$0747, J1744$-$1134, and J1909$-$3744 with frequency coverage that spans 700-3600MHz. We use a smooth model for profile evolution across the full frequency range, and compare smooth and piecewise models for the temporal variations in DM. We find the profile domain framework consistently results in improved timing precision compared to the standard analysis paradigm by as much as 40% for timing parameters. Incorporating smoothness in the DM variations into the model further improves timing precision by as much as 30%. For PSR J1713+0747 we also detect pulse shape variation uncorrelated between epochs, which we attribute to variation intrinsic to the pulsar at a level consistent with previously published analyses. Not accounting for this shape variation biases the measured arrival times at the level of $sim$30ns, the same order of magnitude as the expected shift due to gravitational-waves in the pulsar timing band.
The Premiale Project Science and Technology in Italy for the upgraded ALMA Observatory - iALMA has the goal of strengthening the scientific, technological and industrial Italian contribution to the Atacama Large Millimeter/submillimeter Array (ALMA), the largest ground based international infrastructure for the study of the Universe in the microwave. One of the main objectives of the Science Working Group (SWG) inside iALMA, the Work Package 1, is to develop the Italian contribution to the Science Case for the ALMA Band 2 or Band 2+3 receiver. ALMA Band 2 receiver spans from ~67 GHz (bounded by an opaque line complex of ozone lines) up to 90 GHz which overlaps with the lower frequency end of ALMA Band 3. Receiver technology has advanced since the original definition of the ALMA frequency bands. It is now feasible to produce a single receiver which could cover the whole frequency range from 67 GHz to 116 GHz, encompassing Band 2 and Band 3 in a single receiver cartridge, a so called Band 2+3 system. In addition, upgrades of the ALMA system are now foreseen that should double the bandwidth to 16 GHz. The science drivers discussed below therefore also discuss the advantages of these two enhancements over the originally foreseen Band 2 system.
Wide field small aperture telescopes (WFSATs) are mainly used to obtain scientific information of point--like and streak--like celestial objects. However, qualities of images obtained by WFSATs are seriously affected by the background noise and variable point spread functions. Developing high speed and high efficiency data processing method is of great importance for further scientific research. In recent years, deep neural networks have been proposed for detection and classification of celestial objects and have shown better performance than classical methods. In this paper, we further extend abilities of the deep neural network based astronomical target detection framework to make it suitable for photometry and astrometry. We add new branches into the deep neural network to obtain types, magnitudes and positions of different celestial objects at the same time. Tested with simulated data, we find that our neural network has better performance in photometry than classical methods. Because photometry and astrometry are regression algorithms, which would obtain high accuracy measurements instead of rough classification results, the accuracy of photometry and astrometry results would be affected by different observation conditions. To solve this problem, we further propose to use reference stars to train our deep neural network with transfer learning strategy when observation conditions change. The photometry framework proposed in this paper could be used as an end--to--end quick data processing framework for WFSATs, which can further increase response speed and scientific outputs of WFSATs.
We present the $H$-band spectral line lists adopted by the Apache Point Observatory Galactic Evolution Experiment (APOGEE). The APOGEE line lists comprise astrophysical, theoretical, and laboratory sources from the literature, as well as newly evaluated astrophysical oscillator strengths and damping parameters. We discuss the construction of the APOGEE line list, which is one of the critical inputs for the APOGEE Stellar Parameters and Chemical Abundances Pipeline, and present three differe
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