Publications by Chris Lintott

Integrating human and machine intelligence in galaxy morphology classification tasks

Monthly Notices of the Royal Astronomical Society Blackwell Publishing Inc. (2018)

MR Beck, C Scarlata, LF Fortson, CJ Lintott, BD Simmons, MA Galloway, KW Willett, H Dickinson, KL Masters, PJ Marshall, D Wright

Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution through an integration of visual and automated classifications, preserving the best features of both human and machine. We demonstrate the effectiveness of such a system through a re-analysis of visual galaxy morphology classifications collected during the Galaxy Zoo 2 (GZ2) project. We reprocess the top level question of the GZ2 decision tree with a Bayesian classification aggregation algorithm dubbed SWAP, originally developed for the Space Warps gravitational lens project. Through a simple binary classification scheme we increase the classification rate nearly 5-fold, classifying 226,124 galaxies in 92 days of GZ2 project time while reproducing labels derived from GZ2 classification data with 95.7% accuracy. We next combine this with a Random Forest machine learning algorithm that learns on a suite of nonparametric morphology indicators widely used for automated morphologies. We develop a decision engine that delegates tasks between human and machine, and demonstrate that the combined system provides at least a factor of 8 increase in the classification rate, classifying 210,803 galaxies in just 32 days of GZ2 project time with 93.1% accuracy. As the Random Forest algorithm requires a minimal amount of computation cost, this result has important implications for galaxy morphology identification tasks in the era of Euclid and other large scale surveys.

Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project.

Scientific data 5 (2018) 180124-

FM Jones, C Allen, C Arteta, J Arthur, C Black, LM Emmerson, R Freeman, G Hines, CJ Lintott, Z Macháčková, G Miller, R Simpson, C Southwell, HR Torsey, A Zisserman, T Hart

Automated time-lapse cameras can facilitate reliable and consistent monitoring of wild animal populations. In this report, data from 73,802 images taken by 15 different Penguin Watch cameras are presented, capturing the dynamics of penguin (Spheniscidae; Pygoscelis spp.) breeding colonies across the Antarctic Peninsula, South Shetland Islands and South Georgia (03/2012 to 01/2014). Citizen science provides a means by which large and otherwise intractable photographic data sets can be processed, and here we describe the methodology associated with the Zooniverse project Penguin Watch, and provide validation of the method. We present anonymised volunteer classifications for the 73,802 images, alongside the associated metadata (including date/time and temperature information). In addition to the benefits for ecological monitoring, such as easy detection of animal attendance patterns, this type of annotated time-lapse imagery can be employed as a training tool for machine learning algorithms to automate data extraction, and we encourage the use of this data set for computer vision development.

Doing Good Online: The Changing Relationships Between Motivations, Activity, and Retention Among Online Volunteers


J Cox, EY Oh, B Simmons, G Graham, A Greenhill, C Lintott, K Masters, J Woodcock

Normal black holes in bulge-less galaxies: the largely quiescent, merger-free growth of black holes over cosmic time


G Martin, S Kaviraj, M Volonteri, BD Simmons, JEG Devriendt, CJ Lintott, RJ Smethurst, Y Dubois, C Pichon

SDSS-IV MaNGA: the different quenching histories of fast and slow rotatorsSDSS-IV MaNGA: the different quenching histories of fast and slow rotators


RJ Smethurst, KL Masters, CJ Lintott, A Weijmans, M Merrifield, SJ Penny, A Aragon-Salamanca, J Brownstein, K Bundy, N Drory, DR Law, RC Nichol

Galaxy Zoo: secular evolution of barred galaxies from structural decomposition of multiband images


SJ Kruk, CJ Lintott, SP Bamford, KL Masters, BD Simmons, B Haussler, CN Cardamone, RE Hart, L Kelvin, K Schawinski, RJ Smethurst, M Vika

The K2-138 System: A Near-resonant Chain of Five Sub-Neptune Planets Discovered by Citizen Scientists


JL Christiansen, IJM Crossfield, G Barentsen, CJ Lintott, T Barclay, BD Simmons, E Petigura, JE Schlieder, CD Dressing, A Vanderburg, C Allen, A McMaster, G Miller, M Veldthuis, S Allen, Z Wolfenbarger, B Cox, J Zemiro, AW Howard, J Livingston, E Sinukoff, T Catron, A Grey, JJE Kusch, I Terentev, M Vales, MH Kristiansen

The First Post-Kepler Brightness Dips of KIC 8462852


TS Boyajian, R Alonso, A Ammerman, D Armstrong, AA Ramos, K Barkaoui, TG Beatty, Z Benkhaldoun, P Benni, RO Bentley, A Berdyugin, S Berdyugina, S Bergeron, A Bieryla, MG Blain, AC Blanco, EHL Bodman, A Boucher, M Bradley, SM Brincat, TG Brink, J Briol, DJA Brown, J Budaj, A Burdanov, B Cale, MA Carbo, RC Garcia, WJ Clark, GC Clayton, JL Clem, PH Coker, EM Cook, CM Copperwheat, JL Curtis, RM Cutri, B Cseh, CH Cynamon, AJ Daniels, JRA Davenport, HJ Deeg, R De Lorenzo, T De Jaeger, J-B Desrosiers, J Dolan, DJ Dowhos, F Dubois, R Durkee, S Dvorak, L Easley, N Edwards, TG Ellis, E Erdelyi, S Ertel, RG Farfan, J Farihi, AV Filippenko, E Foxell, D Gandolfi, F Garcia, F Giddens, M Gillon, J-L Gonzalez-Carballo, C Gonzalez-Fernandez, JIG Hernandez, KA Graham, KA Greene, J Gregorio, N Hallakoun, O Hanyecz, GR Harp, GW Henry, E Herrero, CF Hildbold, D Hinzel, G Holgado, B Ignacz, I Ilyin, VD Ivanov, E Jehin, HE Jermak, S Johnston, S Kafka, C Kalup, E Kardasis, S Kaspi, GM Kennedy, F Kiefer, CL Kielty, D Kessler, H Kiiskinen, TL Killestein, RA King, V Kollar, H Korhonen, C Kotnik, R Konyves-Toth, L Kriskovics, N Krumm, V Krushinsky, E Kundra, F-R Lachapelle, D LaCourse, P Lake, K Lam, GP Lamb, D Lane, MW Lau, P Lewin, C Lintott, C Lisse, L Logie, N Longeard, ML Villanueva, EW Ludington, A Mainzer, L Malo, C Maloney, A Mann, A Mantero, M Marengo, J Marchant, MJM Gonzalez, JR Masiero, JC Mauerhan, J McCormac, A McNeely, HYA Meng, M Miller, LA Molnar, JC Morales, BM Morris, MW Muterspaugh, D Nespral, CR Nugent, KM Nugent, A Odasso, D O'Keeffe, A Oksanen, JM O'Meara, A Ordasi, H Osborn, JJ Ott, JR Parks, DR Perez, V Petriew, R Pickard, A Pal, P Plavchan, D Pollacco, FP Nunez, FJ Pozuelos, S Rau, S Redfield, H Relles, I Ribas, J Richards, JLO Saario, EJ Safron, JM Sallai, K Sarneczky, BE Schaefer, CF Schumer, M Schwartzendruber, MH Siegel, APV Siemion, BD Simmons, JD Simon, S Simon-Diaz, ML Sitko, H Socas-Navarro, A Sodor, D Starkey, IA Steele, G Stone, KG Strassmeier, RA Street, T Sullivan, J Suomela, JJ Swift, GM Szabo, R Szabo, R Szakats, T Szalai, AM Tanner, B Toledo-Padron, T Tordai, AHMJ Triaud, JD Turner, JH Ulowetz, M Urbanik, S Vanaverbeke, A Vanderburg, K Vida, BP Vietje, J Vinko, K Von Braun, EO Waagen, D Walsh, CA Watson, RC Weir, K Wenzel, CW Plaza, MW Williamson, JT Wright, MC Wyatt, W Zheng, G Zsidi

Galaxy Zoo: Morphological Classification of Galaxy Images from the Illustris Simulation


H Dickinson, L Fortson, C Lintott, C Scarlata, K Willett, S Bamford, M Beck, C Cardamone, M Galloway, B Simmons, W Keel, S Kruk, K Masters, M Vogelsberger, P Torrey, GF Snyder

Getting Connected: An Empirical Investigation of the Relationship Between Social Capital and Philanthropy Among Online Volunteers

Nonprofit and Voluntary Sector Quarterly (2018)

J Cox, EY Oh, B Simmons, G Graham, A Greenhill, C Lintott, K Masters, R Meriton

© The Author(s) 2018. The concept of social capital has attracted much attention from researchers and policy makers, largely due to links with positive social outcomes and philanthropic acts such as volunteering and donations. However, a rapid growth in Internet technologies and social media networks has fundamentally affected the formation of social capital, as well as the way in which it potentially associates with prosocial behaviors. This study uses unique data from a survey of online volunteers to explore the interrelationships between social capital and a mix of self-reported and observed philanthropic activities in both online and offline settings. Our results show that while social capital levels associate strongly with offline donations, there are key differences in the relationships between social capital and volunteering in online and offline settings. Using two-stage least squares (2SLS) regression analysis to control for endogeneity, we also infer a number of causal relationships between social capital and philanthropy.

Radio Galaxy Zoo: A Search for Hybrid Morphology Radio Galaxies


AD Kapinska, I Terentev, OI Wong, SS Shabala, H Andernach, L Rudnick, L Storer, JK Banfield, KW Willett, F de Gasperin, CJ Lintott, AR Lopez-Sanchez, E Middelberg, RP Norris, K Schawinski, N Seymour, B Simmons

Galaxy Zoo: the interplay of quenching mechanisms in the group environment


RJ Smethurst, CJ Lintott, SP Bamford, RE Hart, SJ Kruk, KL Masters, RC Nichol, BD Simmons

Galaxy Zoo: finding offset discs and bars in SDSS galaxies


SJ Kruk, CJ Lintott, BD Simmons, SP Bamford, CN Cardamone, L Fortson, RE Hart, B Haussler, KL Masters, RC Nichol, K Schawinski, RJ Smethurst

Galaxy Zoo: star formation versus spiral arm number

Monthly Notices of the Royal Astronomical Society 468 (2017) 1850-1863

RE Hart, SP Bamford, KRV Casteels, SJ Kruk, CJ Lintott, KL Masters

Supermassive black holes in disc-dominated galaxies outgrow their bulges and co-evolve with their host galaxies


BD Simmons, RJ Smethurst, C Lintott

Fading AGN Candidates: AGN Histories and Outflow Signatures

Astrophysical Journal 835 (2017)

WC Keel, CJ Lintott, WP Maksym, VN Bennert, SD Chojnowski, A Moiseev, A Smirnova, K Schawinski, LF Sartori, CM Urry, A Pancoast, M Schirmer, B Scott, C Showley, K Flatland

� 2017. The American Astronomical Society. All rights reserved. We consider the energy budgets and radiative history of eight fading active galactic nuclei (AGNs), identified from an energy shortfall between the requirements to ionize very extended (radius > 10 kpc) ionized clouds and the luminosity of the nucleus as we view it directly. All show evidence of significant fading on timescales of ≈50,000 yr. We explore the use of minimum ionizing luminosity Q ion derived from photoionization balance in the brightest pixels in Hα at each projected radius. Tests using presumably constant Palomar-Green QSOs, and one of our targets with detailed photoionization modeling, suggest that we can derive useful histories of individual AGNs, with the caveat that the minimum ionizing luminosity is always an underestimate and subject to uncertainties about fine structure in the ionized material. These consistency tests suggest that the degree of underestimation from the upper envelope of reconstructed Q ion values is roughly constant for a given object and therefore does not prevent such derivation. The AGNs in our sample show a range of behaviors, with rapid drops and standstills; the common feature is a rapid drop in the last ≈2 � 10 4 yr before the direct view of the nucleus. The e-folding timescales for ionizing luminosity are mostly in the thousands of years, with a few episodes as short as 400 yr. In the limit of largely obscured AGNs, we find additional evidence for fading from the shortfall between even the lower limits from recombination balance and the maximum luminosities derived from far-infrared fluxes. We compare these long-term light curves, and the occurrence of these fading objects among all optically identified AGNs, to simulations of AGN accretion; the strongest variations over these timespans are seen in models with strong and local (parsec-scale) feedback. We present Gemini integral-field optical spectroscopy, which shows a very limited role for outflows in these ionized structures. While rings and loops of emission, morphologically suggestive of outflow, are common, their kinematic structure shows some to be in regular rotation. UGC 7342 exhibits local signatures of outflows < 300 km s -1 , largely associated with very diffuse emission, and possibly entraining gas in one of the clouds seen in Hubble Space Telescope images. Only in the Teacup AGN do we see outflow signatures of the order of 1000 km s -1 . In contrast to the extended emission regions around many radio-loud AGNs, the clouds around these fading AGNs consist largely of tidal debris being externally illuminated but not displaced by AGN outflows.

Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science.

Classical and quantum gravity 34 (2017)

M Zevin, S Coughlin, S Bahaadini, E Besler, N Rohani, S Allen, M Cabero, K Crowston, AK Katsaggelos, SL Larson, TK Lee, C Lintott, TB Littenberg, A Lundgren, C Østerlund, JR Smith, L Trouille, V Kalogera

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 alternative 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. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. 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 time-frequency representations 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.

Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS


BD Simmons, C Lintott, KW Willett, KL Masters, JS Kartaltepe, B Haussler, S Kaviraj, C Krawczyk, SJ Kruk, DH McIntosh, RJ Smethurst, RC Nichol, C Scarlata, K Schawinski, CJ Conselice, O Almaini, HC Ferguson, L Fortson, W Hartley, D Kocevski, AM Koekemoer, A Mortlock, JA Newman, SP Bamford, NA Grogin, RA Lucas, NP Hathi, E McGrath, M Peth, J Pforr, Z Rizer, S Wuyts, G Barro, EF Bell, M Castellano, T Dahlen, A Dekel, J Ownsworth, SM Faber, SL Finkelstein, A Fontana, A Galametz, R Grutzbauch, D Koo, J Lotz, B Mobasher, M Mozena, M Salvato, T Wiklind

Transforming Libraries and Archives through Crowdsourcing

D-Lib Magazine 23 (2017)

V Van Hyning, S Blickhan, L Trouille, C Lintott

This article will showcase the aims and research goals of the project entitled "Transforming Libraries and Archives through Crowdsourcing", recipient of a 2016 Institute for Museum and Library Services grant. This grant will be used to fund the creation of four bespoke text and audio transcription projects which will be hosted on the Zooniverse, the world-leading research crowdsourcing platform. These transcription projects, while supporting the research of four separate institutions, will also function as a means to expand and enhance the Zooniverse platform to better support galleries, libraries, archives and museums (GLAM institutions) in unlocking their data and engaging the public through crowdsourcing.

SDSS IV MaNGA: Discovery of an Ha Blob Associated with a Dry Galaxy Pair-Ejected Gas or a "Dark" Galaxy Candidate?


L Lin, J-H Lin, C-H Hsu, H Fu, S Huang, SF Sanchez, S Gwyn, JD Gelfand, E Cheung, K Masters, S Peirani, W Rujopakarn, DV Stark, F Belfiore, MS Bothwell, K Bundy, A Hagen, L Hao, S Huang, D Law, C Li, C Lintott, R Maiolino, A Roman-Lopes, W-H Wang, T Xiao, F Yuan, D Bizyaev, E Malanushenko, N Drory, JG Fernandez-Trincado, Z Pace, K Pan, D Thomas