Astrophysics

We demonstrate the blind interferometric detection and localization of two fast radio bursts (FRBs) with 2- and 25-arcsecond precision on the 400-m baseline between the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and the CHIME Pathfinder. In the same spirit as very long baseline interferometry (VLBI), the telescopes were synchronized to separate clocks, and the channelized voltage (herein referred to as "baseband") data were saved to disk with correlation performed offline. The simultaneous wide field of view and high sensitivity required for blind FRB searches implies a high data rate -- 6.5 terabits per second (Tb/s) for CHIME and 0.8 Tb/s for the Pathfinder. Since such high data rates cannot be continuously saved, we buffer data from both telescopes locally in memory for ≈40 s, and write to disk upon receipt of a low-latency trigger from the CHIME Fast Radio Burst Instrument (CHIME/FRB). The ≈200 deg 2 field of view of the two telescopes allows us to use in-field calibrators to synchronize the two telescopes without needing either separate calibrator observations or an atomic timing standard. In addition to our FRB observations, we analyze bright single pulses from the pulsars B0329+54 and B0355+54 to characterize systematic localization errors. Our results demonstrate the successful implementation of key software, triggering, and calibration challenges for CHIME/FRB Outriggers: cylindrical VLBI outrigger telescopes which, along with the CHIME telescope, will localize thousands of single FRB events to 50 milliarcsecond precision.

This paper presents a system-level engineering approach for the preliminary coverage performance analysis and the design of a generic Global Navigation Satellite System (GNSS) constellation. This analysis accounts for both the coverage requirements and the robustness to transient or catastrophic failures of the constellation. The European GNSS, Galileo, is used as reference case to prove the effectiveness of the proposed tool. This software suite, named GNSS Coverage Analysis Tool (G-CAT), requires as input the state vector of each satellite of the constellation and provides the performance of the GNSS constellation in terms of coverage. The tool offers an orbit propagator, an attitude propagator, an algorithm to identify the visibility region on the Earth's surface from each satellite, and a counter function to compute how many satellites are in view from given locations on the Earth's surface. Thanks to its low computational burden, the tool can be adopted to compute the optimal number of satellites per each orbital plane by verifying if the coverage and accuracy requirements are fulfilled under the assumption of uniform in-plane angular spacing between coplanar satellites.

The gravitational wave detector of higher sensitivity and greater bandwidth is required for future gravitational wave astronomy and cosmology. Here we present a new type broadband high frequency laser interferometer gravitational wave detector utilizing polarization of light as signal carrier. Except for Fabry-Perot cavity arms we introduce dual power recycling to further amplify the gravitational wave signals. A novel method of weak measurement amplification is used to amplify signals for detection and to guarantee the long-term run of detector. Equipped with squeezed light, the proposed detector is shown sensitive enough within the window from 100Hz to several kHz, making it suitable for the study of high frequency gravitational wave sources. With zero-area Sagnac topology, the detector has the potential to realize quantum non-demolition measurement. The detector presented here is expected to provide an alternative way of exploring the possible ground-base gravitational wave detector for the need of future research.

The Gaia mission is delivering exquisite astrometric data for 1.47 billion sources, which are revolutionizing many fields in astronomy. For a small fraction of these sources the astrometric solutions are poor, and the reported values and uncertainties may not apply. For many analyses it is important to recognize and excise these spurious results, commonly done by means of quality flags in the Gaia catalog. Here we devise and apply a path to separating 'good' from 'bad' astrometric solutions that is an order-of-magnitude cleaner than any single flag: we achieve a purity of 99.7% and a completeness of 97.6% as validated on our test data. We devise an extensive sample of manifestly bad astrometric solutions: sources whose inferred parallax is 'negative' at >= 4.5 sigma; and a corresponding sample of presumably good solutions: the sources in HEALPix patches of the sky that do not contain extremely negative parallaxes. We then train a neural net that uses 14 pertinent Gaia catalog entries to discriminate these two samples, captured in a single 'astrometric fidelity' parameter. An extensive and diverse set of verification tests show that our approach to assessing astrometric fidelity works very cleanly also in the regime where no negative parallaxes are involved; its main limitations are in the very low S/N regime. Our astrometric fidelities for all EDR3 can be queried via the Virtual Observatory. In the spirit of open science, we make our code and training/validation data public, so that our results can be easily reproduced.

A compact green astro-comb with 43-GHz repetition rate is developed based on a Ti:Sapphire optical frequency comb (OFC) and a mode-selecting cavity. The OFC's large repetition rate of 1.6 GHz eases the requirements for the mode-selecting cavity. Unnecessary frequency-modes of the OFC are suppressed down to 5? 10 ?? at 535 nm - 550 nm using a single mode-selecting cavity with 70-MHz linewidth. The radial velocity precision ???.4 m/s is achieved at the High Dispersion Echelle Spectrosraph for the Okayama 188-cm telescope of the National Astronomical Observatory of Japan using our astro-comb. With further improvements of the mode-selecting cavity and removal of fiber modal noises, our system will provide a simple, compact, and precise astro-comb setup in visible wavelength region.

We present a comprehensive analysis of the performance of noise-reduction (``denoising'') algorithms to determine whether they provide advantages in source detection on extragalactic survey images. The methods under analysis are Perona-Malik filtering, Bilateral filter, Total Variation denoising, Structure-texture image decomposition, Non-local means, Wavelets, and Block-matching. We tested the algorithms on simulated images of extragalactic fields with resolution and depth typical of the Hubble, Spitzer, and Euclid Space Telescopes, and of ground-based instruments. After choosing their best internal parameters configuration, we assess their performance as a function of resolution, background level, and image type, also testing their ability to preserve the objects fluxes and shapes. We analyze in terms of completeness and purity the catalogs extracted after applying denoising algorithms on a simulated Euclid Wide Survey VIS image, on real H160 (HST) and K-band (HAWK-I) observations of the CANDELS GOODS-South field. Denoising algorithms often outperform the standard approach of filtering with the Point Spread Function (PSF) of the image. Applying Structure-Texture image decomposition, Perona-Malik filtering, the Total Variation method by Chambolle, and Bilateral filtering on the Euclid-VIS image, we obtain catalogs that are both more pure and complete by 0.2 magnitudes than those based on the standard approach. The same result is achieved with the Structure-Texture image decomposition algorithm applied on the H160 image. The advantage of denoising techniques with respect to PSF filtering increases at increasing depth. Moreover, these techniques better preserve the shape of the detected objects with respect to PSF smoothing. Denoising algorithms provide significant improvements in the detection of faint objects and enhance the scientific return of current and future extragalactic surveys.

XTE J1810-197 (J1810) was the first magnetar identified to emit radio pulses, and has been extensively studied during a radio-bright phase in 2003 − 2008. It is estimated to be relatively nearby compared to other Galactic magnetars, and provides a useful prototype for the physics of high magnetic fields, magnetar velocities, and the plausible connection to extragalactic fast radio bursts. Upon the re-brightening of the magnetar at radio wavelengths in late 2018, we resumed an astrometric campaign on J1810 with the Very Long Baseline Array, and sampled 14 new positions of J1810 over 1.3 years. The phase calibration for the new observations was performed with two phase calibrators that are quasi-colinear on the sky with J1810, enabling substantial improvement of the resultant astrometric precision. Combining our new observations with two archival observations from 2006, we have refined the proper motion and reference position of the magnetar and have measured its annual geometric parallax, the first such measurement for a magnetar. The parallax of 0.40±0.05 mas corresponds to a most probable distance 2.5 +0.4 −0.3 kpc for J1810. Our new astrometric results confirm an unremarkable transverse peculiar velocity of ≈200km s −1 for J1810, which is only at the average level among the pulsar population. The magnetar proper motion vector points back to the central region of a supernova remnant (SNR) at a compatible distance at ≈70 kyr ago, but a direct association is disfavored by the estimated SNR age of ~3 kyr.

The natural night sky brightness is a relevant input for monitoring the light pollution evolution at observatory sites, by subtracting it from the overall sky brightness determined by direct measurements. It is also instrumental for assessing the expected darkness of the pristine night skies. The natural brightness of the night sky is determined by the sum of the spectral radiances coming from astrophysical sources, including zodiacal light, and the atmospheric airglow. The resulting radiance is modified by absorption and scattering before it reaches the observer. Therefore, the natural night sky brightness is a function of the location, time and atmospheric conditions. We present in this work GAMBONS (GAia Map of the Brightness Of the Natural Sky), a model to map the natural night brightness of the sky in cloudless and moonless nights. Unlike previous maps, GAMBONS is based on the extra-atmospheric star radiance obtained from the Gaia catalogue. The Gaia-DR2 archive compiles astrometric and photometric information for more than 1.6 billion stars up to G = 21 magnitude. For the brightest stars, not included in Gaia-DR2, we have used the Hipparcos catalogue instead. After adding up to the star radiance the contributions of the diffuse galactic and extragalactic light, zodiacal light and airglow, and taking into account the effects of atmospheric attenuation and scattering, the radiance detected by ground-based observers can be estimated. This methodology can be applied to any photometric band, if appropriate transformations from the Gaia bands are available. In particular, we present the expected sky brightness for V (Johnson), and visual photopic and scotopic passbands.

The Dark Matter Particle Explorer (DAMPE) is a space-borne particle detector and cosmic ray observatory in operation since 2015, designed to probe electrons and gamma rays from a few GeV to 10 TeV energy, as well as cosmic protons and nuclei up to 100 TeV. Among the main scientific objectives is the precise measurement of the cosmic electron+positron flux, which due to the very large proton background in orbit requires a powerful particle identification method. In the past decade, the field of machine learning has provided us the needed tools. This paper presents a neural network based approach to cosmic electron identification and proton rejection and showcases its performances based on simulated Monte Carlo data. The neural network reaches significantly lower background than the classical, cut-based method for the same detection efficiency, especially at highest energies. A good matching between simulations and real data completes the picture.

The Birmingham Solar Oscillations Network (BiSON) is a collection of ground-based automated telescopes observing oscillations of the Sun. The network has been operating since the early 1990s. We present development work on a prototype next generation observation platform, BiSON:NG, based almost entirely on inexpensive off-the-shelf components, and where the footprint is reduced to a size that can be inexpensively installed on the roof of an existing building. Continuous development is essential in ensuring that automated networks such as BiSON are well placed to observe the next solar cycle and beyond.