A Deep Neural Network Based Reverse Radio Spectrogram Search Algorithm

Modern radio astronomy instruments generate vast amounts of data, and the increasingly challenging radio frequency interference (RFI) environment necessitates ever-more sophisticated RFI rejection algorithms. The "needle in a haystack" nature of searches for transients and technosignatures requires us to develop methods that can determine whether a signal of interest has unique properties, or is a part of some larger set of pernicious RFI. In the past, this vetting has required onerous manual inspection of very large numbers of signals. In this paper we present a fast and modular deep learning algorithm to search for lookalike signals of interest in radio spectrogram data. First, we trained a B-Variational Autoencoder on signals returned by an energy detection algorithm. We then adapted a positional embedding layer from classical Transformer architecture to a embed additional metadata, which we demonstrate using a frequency-based embedding. Next we used the encoder component of the B-Variational Autoencoder to extract features from small (~ 715,Hz, with a resolution of 2.79Hz per frequency bin) windows in the radio spectrogram. We used our algorithm to conduct a search for a given query (encoded signal of interest) on a set of signals (encoded features of searched items) to produce the top candidates with similar features. We successfully demonstrate that the algorithm retrieves signals with similar appearance, given only the original radio spectrogram data. This algorithm can be used to improve the efficiency of vetting signals of interest in technosignature searches, but could also be applied to a wider variety of searches for "lookalike" signals in large astronomical datasets.Comment: 8 pages, 8 figure

Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science

(abridged for arXiv) With the first direct detection of gravitational waves, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) has initiated a new field of astronomy by providing an alternate means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual classifier. The resulting classification and characterization should help LIGO scientists to identify causes of glitches and subsequently eliminate them from the data or the detector entirely, thereby improving the rate and accuracy of gravitational-wave observations. We demonstrate these methods using a small subset of data from LIGO's first observing run.Comment: 27 pages, 8 figures, 1 tabl

Planet Hunters: The First Two Planet Candidates Identified by the Public using the Kepler Public Archive Data

Planet Hunters is a new citizen science project, designed to engage the public in an exoplanet search using NASA Kepler public release data. In the first month after launch, users identified two new planet candidates which survived our checks for false- positives. The follow-up effort included analysis of Keck HIRES spectra of the host stars, analysis of pixel centroid offsets in the Kepler data and adaptive optics imaging at Keck using NIRC2. Spectral synthesis modeling coupled with stellar evolutionary models yields a stellar density distribution, which is used to model the transit orbit. The orbital periods of the planet candidates are 9.8844 \pm0.0087 days (KIC 10905746) and 49.7696 \pm0.00039 (KIC 6185331) days and the modeled planet radii are 2.65 and 8.05 R\oplus. The involvement of citizen scientists as part of Planet Hunters is therefore shown to be a valuable and reliable tool in exoplanet detection.Comment: Submitted to MNRAS, added 1 line to table

Planetary Candidates Observed by Kepler, III: Analysis of the First 16 Months of Data

New transiting planet candidates are identified in sixteen months (May 2009 - September 2010) of data from the Kepler spacecraft. Nearly five thousand periodic transit-like signals are vetted against astrophysical and instrumental false positives yielding 1,091 viable new planet candidates, bringing the total count up to over 2,300. Improved vetting metrics are employed, contributing to higher catalog reliability. Most notable is the noise-weighted robust averaging of multi-quarter photo-center offsets derived from difference image analysis which identifies likely background eclipsing binaries. Twenty-two months of photometry are used for the purpose of characterizing each of the new candidates. Ephemerides (transit epoch, T_0, and orbital period, P) are tabulated as well as the products of light curve modeling: reduced radius (Rp/R*), reduced semi-major axis (d/R*), and impact parameter (b). The largest fractional increases are seen for the smallest planet candidates (197% for candidates smaller than 2Re compared to 52% for candidates larger than 2Re) and those at longer orbital periods (123% for candidates outside of 50-day orbits versus 85% for candidates inside of 50-day orbits). The gains are larger than expected from increasing the observing window from thirteen months (Quarter 1-- Quarter 5) to sixteen months (Quarter 1 -- Quarter 6). This demonstrates the benefit of continued development of pipeline analysis software. The fraction of all host stars with multiple candidates has grown from 17% to 20%, and the paucity of short-period giant planets in multiple systems is still evident. The progression toward smaller planets at longer orbital periods with each new catalog release suggests that Earth-size planets in the Habitable Zone are forthcoming if, indeed, such planets are abundant.Comment: Submitted to ApJS. Machine-readable tables are available at http://kepler.nasa.gov, http://archive.stsci.edu/kepler/results.html, and the NASA Exoplanet Archiv

K2-288Bb: A Small Temperate Planet in a Low-mass Binary System Discovered by Citizen Scientists

Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.Observations from the Kepler and K2 missions have provided the astronomical community with unprecedented amounts of data to search for transiting exoplanets and other astrophysical phenomena. Here, we present K2-288, a low-mass binary system (M2.0 ± 1.0; M3.0 ± 1.0) hosting a small (R p = 1.9 R ⊕), temperate (T eq = 226 K) planet observed in K2 Campaign 4. The candidate was first identified by citizen scientists using Exoplanet Explorers hosted on the Zooniverse platform. Follow-up observations and detailed analyses validate the planet and indicate that it likely orbits the secondary star on a 31.39-day period. This orbit places K2-288Bb in or near the habitable zone of its low-mass host star. K2-288Bb resides in a system with a unique architecture, as it orbits at >0.1 au from one component in a moderate separation binary (a proj ~ 55 au), and further follow-up may provide insight into its formation and evolution. Additionally, its estimated size straddles the observed gap in the planet radius distribution. Planets of this size occur less frequently and may be in a transient phase of radius evolution. K2-288 is the third transiting planet system identified by the Exoplanet Explorers program and its discovery exemplifies the value of citizen science in the era of Kepler, K2, and the Transiting Exoplanet Survey Satellite

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Galaxy Formation Theory

We review the current theory of how galaxies form within the cosmological framework provided by the cold dark matter paradigm for structure formation. Beginning with the pre-galactic evolution of baryonic material we describe the analytical and numerical understanding of how baryons condense into galaxies, what determines the structure of those galaxies and how internal and external processes (including star formation, merging, active galactic nuclei etc.) determine their gross properties and evolution. Throughout, we highlight successes and failings of current galaxy formation theory. We include a review of computational implementations of galaxy formation theory and assess their ability to provide reliable modelling of this complex phenomenon. We finish with a discussion of several "hot topics" in contemporary galaxy formation theory and assess future directions for this field.Comment: 58 pages, to appear in Physics Reports. This version includes minor corrections and a handful of additional reference

Planet Hunters TESS. V. A Planetary System Around a Binary Star, Including a Mini-Neptune in the Habitable Zone

We report on the discovery and validation of a transiting long-period mini-Neptune orbiting a bright (V = 9.0 mag) G dwarf (TOI 4633; R = 1.05 R ⊙, M = 1.10 M ⊙). The planet was identified in data from the Transiting Exoplanet Survey Satellite by citizen scientists taking part in the Planet Hunters TESS project. Modelling of the transit events yields an orbital period of 271.9445 ± 0.0040 days and radius of 3.2 ± 0.20 R ⊕. The Earth-like orbital period and an incident flux of 1.56−0.16+0.20 F ⊕ places it in the optimistic habitable zone around the star. Doppler spectroscopy of the system allowed us to place an upper mass limit on the transiting planet and revealed a non-transiting planet candidate in the system with a period of 34.15 ± 0.15 days. Furthermore, the combination of archival data dating back to 1905 with new high angular resolution imaging revealed a stellar companion orbiting the primary star with an orbital period of around 230 yr and an eccentricity of about 0.9. The long period of the transiting planet, combined with the high eccentricity and close approach of the companion star makes this a valuable system for testing the formation and stability of planets in binary systems

The K2-138 system:a near-resonant chain of five sub-neptune planets discovered by citizen scientists

K2-138 is a moderately bright (V = 12.2, K = 10.3) main-sequence K star observed in Campaign 12 of the NASA K2 mission. It hosts five small (1.6–3.3 ${R}_{\oplus }$) transiting planets in a compact architecture. The periods of the five planets are 2.35, 3.56, 5.40, 8.26, and 12.76 days, forming an unbroken chain of near 3:2 resonances. Although we do not detect the predicted 2–5 minute transit timing variations (TTVs) with the K2 timing precision, they may be observable by higher-cadence observations with, for example, Spitzer or CHEOPS. The planets are amenable to mass measurement by precision radial velocity measurements, and therefore K2-138 could represent a new benchmark system for comparing radial velocity and TTV masses. K2-138 is the first exoplanet discovery by citizen scientists participating in the Exoplanet Explorers project on the Zooniverse platform