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We describe Space Warps, a novel gravitational lens discovery service that yields samples of high purity and completeness through crowd-sourced visual inspection. Carefully produced colour composite images are displayed to volunteers via a web- based classification interface, which records their estimates of the positions of candidate lensed features. Images of simulated lenses, as well as real images which lack lenses, are inserted into the image stream at random intervals; this training set is used to give the volunteers instantaneous feedback on their performance, as well as to calibrate a model of the system that provides dynamical updates to the probability that a classified image contains a lens. Low probability systems are retired from the site periodically, concentrating the sample towards a set of lens candidates. Having divided 160 square degrees of Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging into some 430,000 overlapping 82 by 82 arcsecond tiles and displaying them on the site, we were joined by around 37,000 volunteers who contributed 11 million image classifications over the course of 8 months. This Stage 1 search reduced the sample to 3381 images containing candidates; these were then refined in Stage 2 to yield a sample that we expect to be over 90% complete and 30% pure, based on our analysis of the volunteers performance on training images. We comment on the scalability of the SpaceWarps system to the wide field survey era, based on our projection that searches of 10$^5$ images could be performed by a crowd of 10$^5$ volunteers in 6 days.
The Laser Interferometer Space Antenna (LISA) will open three decades of gravitational wave (GW) spectrum between 0.1 and 100 mHz, the mHz band. This band is expected to be the richest part of the GW spectrum, in types of sources, numbers of sources, signal-to-noise ratios and discovery potential. When LISA opens the low-frequency window of the gravitational wave spectrum, around 2034, the surge of gravitational-wave astronomy will strongly compel a subsequent mission to further explore the frequency bands of the GW spectrum that can only be accessed from space. The 2020s is the time to start developing technology and studying mission concepts for a large-scale mission to be launched in the 2040s. The mission concept would then be proposed to Astro2030. Only space based missions can access the GW spectrum between 10 nHz and 1 Hz because of the Earths seismic noise. This white paper surveys the science in this band and mission concepts that could accomplish that science. The proposed small scale activity is a technology development program that would support a range of concepts and a mission concept study to choose a specific mission concept for Astro2030. In this white paper, we will refer to a generic GW mission beyond LISA as bLISA.
In this paper we develop a new unsupervised machine learning technique comprised of a feature extractor, a convolutional autoencoder (CAE), and a clustering algorithm consisting of a Bayesian Gaussian mixture model (BGM). We apply this technique to visual band space-based simulated imaging data from the Euclid Space Telescope using data from the Strong Gravitational Lenses Finding Challenge. Our technique promisingly captures a variety of lensing features such as Einstein rings with different radii, distorted arc structures, etc, without using predefined labels. After the clustering process, we obtain several classification clusters separated by different visual features which are seen in the images. Our method successfully picks up $sim$63 percent of lensing images from all lenses in the training set. With the assumed probability proposed in this study, this technique reaches an accuracy of $77.25pm 0.48$% in binary classification using the training set. Additionally, our unsupervised clustering process can be used as the preliminary classification for future surveys of lenses to efficiently select targets and to speed up the labelling process. As the starting point of the astronomical application using this technique, we not only explore the application to gravitationally lensed systems, but also discuss the limitations and potential future uses of this technique.
How should we invest our available resources to best sustain astronomys track record of discovery, established over the past few decades? Two strong hints come from (1) our history of astronomical discoveries and (2) literature citation patterns that reveal how discovery and development activities in science are strong functions of team size. These argue that progress in astronomy hinges on support for a diversity of research efforts in terms of team size, research tools and platforms, and investment strategies that encourage risk taking. These ideas also encourage us to examine the implications of the trend toward big team science and survey science in astronomy over the past few decades, and to reconsider the common assumption that progress in astronomy always means trading up to bigger apertures and facilities. Instead, the considerations above argue that we need a balanced set of investments in small- to large-scale initiatives and team sizes both large and small. Large teams tend to develop existing ideas, whereas small teams are more likely to fuel the future with disruptive discoveries. While large facilities are the value investments that are guaranteed to produce discoveries, smaller facilities are the growth stocks that are likely to deliver the biggest science bang per buck, sometimes with outsize returns. One way to foster the risk taking that fuels discovery is to increase observing opportunity, i.e., create more observing nights and facilitate the exploration of science-ready data.
We propose a new mission called Space Project for Astrophysical and Cosmological Exploration (SPACE) as part on the ESA long term planning Voyage 2050 programme. SPACE will study galaxy evolution at the earliest times, with the key goals of charting the formation of the heavy elements, measuring the evolution of the galaxy luminosity function, tracing the build-up of stellar mass in galaxies over cosmic time, and finding the first super-massive black holes (SMBHs) to form. The mission will exploit a unique region of the parameter space, between the narrow ultra-deep surveys with HST and JWST, and shallow wide-field surveys such as Roman Space Telescope and EUCLID, and should yield by far the largest sample of any current or planned mission of very high redshift galaxies at z > 10 which are sufficiently bright for detailed follow-up spectroscopy. Crucially, we propose a wide-field spectroscopic near-IR + mid-IR capability which will greatly enhance our understanding of the first galaxies by detecting and identifying a statistical sample of the first galaxies and the first SMBH, and to chart the metal enrichment history of galaxies in the early Universe - potentially finding signatures of the very first stars to form from metal-free primordial gas. The wide-field and wavelength range of SPACE will also provide us a unique opportunity to study star formation by performing a wide survey of the Milky Way in the near-IR + mid-IR. This science project can be enabled either by a stand-alone ESA-led M mission or by an instrument for an L mission (with ESA and/or NASA, JAXA and other international space agencies) with a wide-field (sub-)millimetre capability at wavelength > 500 microns.
This paper describes outstanding issues in astrophysics and cosmology that can be solved by astronomical observations in a broad spectral range from far infrared to millimeter wavelengths. The discussed problems related to the formation of stars and planets, galaxies and the interstellar medium, studies of black holes and the development of the cosmological model can be addressed by the planned space observatory Millimetron (the Spectr-M project) equipped with a cooled 10-m mirror. Millimetron can operate both as a single-dish telescope and as a part of a space-ground interferometer with very long baseline.