Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Grant Miller is active.

Publication


Featured researches published by Grant Miller.


Monthly Notices of the Royal Astronomical Society | 2016

WASP-92b, WASP-93b and WASP-118b: three new transiting close-in giant planets

K. L. Hay; Andrew Collier-Cameron; A. P. Doyle; G. Hébrard; I. Skillen; D. R. Anderson; S. C. C. Barros; D. J. A. Brown; F. Bouchy; R. Busuttil; P. Delorme; Laetitia Delrez; O. Demangeon; R. F. Díaz; Michaël Gillon; Y. Gómez Maqueo Chew; E. González; C. Hellier; S. Holmes; J. F. Jarvis; Emmanuel Jehin; Y. C. Joshi; U. Kolb; M. Lendl; P. F. L. Maxted; James McCormac; Grant Miller; A. Mortier; E. Pallé; Don Pollacco

We present the discovery of three new transiting giant planets, first detected with the WASP telescopes, and establish their planetary nature with follow up spectroscopy and ground-based photometric lightcurves. WASP-92 is an F7 star, with a moderately inflated planet orbiting with a period of 2.17 days, which has Rp = 1.461 ± 0.077RJ and Mp = 0.805 ± 0.068MJ. WASP-93b orbits its F4 host star every 2.73 days and has Rp = 1.597 ± 0.077RJ and Mp = 1.47 ± 0.029MJ. WASP-118b also has a hot host star (F6) and is moderately inflated, where Rp = 1.440 ± 0.036RJ and Mp = 0.513 ± 0.041MJ and the planet has an orbital period of 4.05 days. They are bright targets (V = 13.18, 10.97 and 11.07 respectively) ideal for further characterisation work, particularly WASP-118b, which is being observed by K2 as part of campaign 8. WASP-93b is expected to be tidally migrating outwards, which is divergent from the tidal behaviour of the majority of hot Jupiters discovered.


Monthly Notices of the Royal Astronomical Society | 2017

A transient search using combined human and machine classifications

D. Wright; Chris Lintott; S. J. Smartt; K. W. Smith; L. Fortson; L. Trouille; Campbell Allen; Melanie Beck; Mark C. Bouslog; Amy Boyer; K. C. Chambers; H. Flewelling; Will Granger; E. A. Magnier; Adam McMaster; Grant Miller; James E. O'Donnell; Brooke Simmons; Helen Spiers; John L. Tonry; Marten Veldthuis; R. J. Wainscoat; C. Waters; Mark Willman; Zach Wolfenbarger; Dave R. Young

Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been put into the development of automatic algorithms, but surveys still rely on human review of targets. This paper presents an integrated system for the identification of supernovae in data from Pan-STARRS1, combining classifications from volunteers participating in a citizen science project with those from a convolutional neural network. The unique aspect of this work is the deployment, in combination, of both human and machine classifications for near real-time discovery in an astronomical project. We show that the combination of the two methods outperforms either one used individually. This result has important implications for the future development of transient searches, especially in the era of Large Synoptic Survey Telescope and other large-throughput surveys.


Icarus | 2017

Planet Four: Terrains – Discovery of araneiforms outside of the South Polar layered deposits

Megan E. Schwamb; K.-M. Aye; Ganna Portyankina; Candice J. Hansen; Campbell Allen; Sarah Allen; F. Calef; Simone Duca; Adam McMaster; Grant Miller

Abstract We present the results of a systematic mapping of seasonally sculpted terrains on the South Polar region of Mars with the Planet Four: Terrains (P4T) online citizen science project. P4T enlists members of the general public to visually identify features in the publicly released Mars Reconnaissance Orbiter Context Camera (CTX) images. In particular, P4T volunteers are asked to identify: (1) araneiforms (including features with a central pit and radiating channels known as ‘spiders’); (2) erosional depressions, troughs, mesas, ridges, and quasi-circular pits characteristic of the South Polar Residual Cap (SPRC) which we collectively refer to as ‘Swiss cheese terrain’, and (3) craters. In this work we present the distributions of our high confidence classic spider araneiforms and Swiss cheese terrain identifications in 90 CTX images covering 11% of the South polar regions at latitudes ≤ − 75° N. We find no locations within our high confidence spider sample that also have confident Swiss cheese terrain identifications. Previously spiders were reported as being confined to the South Polar Layered Deposits (SPLD). Our work has provided the first identification of spiders at locations outside of the SPLD, confirmed with high resolution HiRISE (High Resolution Imaging Science Experiment) imaging. We find araneiforms on the Amazonian and Hesperian polar units and the Early Noachian highland units, with 75% of the identified araneiform locations in our high confidence sample residing on the SPLD. With our current coverage, we cannot confirm whether these are the only geologic units conducive to araneiform formation on the Martian South Polar region. Our results are consistent with the current CO 2 jet formation scenario with the process exploiting weaknesses in the surface below the seasonal CO 2 ice sheet to carve araneiform channels into the regolith over many seasons. These new regions serve as additional probes of the conditions required for channel creation in the CO 2 jet process.


The Astronomical Journal | 2001

Ubvi and ha photometry of the h & chi persei cluster

Stefan C. Keller; Eva K. Grebel; Kenneth M. Yoss; Grant Miller

UBVI and Ha photometry is presented for 17319 stars in vicinity of the young double cluster h & chi Persei. Our photometry extends over a 37arcmin x 1arcdeg field centered on the association. We construct reddening contours within the imaged field. We find that the two clusters share a common distance modulus of 11.75


The Astronomical Journal | 2018

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

Jessie L. Christiansen; Ian J. M. Crossfield; Geert Barentsen; Chris Lintott; Thomas Barclay; Brooke Simmons; Erik A. Petigura; Joshua E. Schlieder; Courtney D. Dressing; Andrew Vanderburg; Campbell Allen; Adam McMaster; Grant Miller; Martin Veldthuis; Sarah Allen; Zach Wolfenbarger; Brian Cox; Julia Zemiro; Andrew W. Howard; J. Livingston; Evan Sinukoff; Timothy Catron; Andrew Grey; Joshua J. E. Kusch; Ivan Terentev; Martin Vales; Martti H. Kristiansen

\pm


Scientific Data | 2018

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

Fiona M. Jones; Campbell Allen; Carlos Arteta; Joan Arthur; Caitlin Black; Louise Emmerson; Robin Freeman; Greg Hines; Chris Lintott; Zuzana Macháčková; Grant Miller; Rob Simpson; Colin Southwell; Holly R. Torsey; Andrew Zisserman; Tom Hart

0.05 and ages of log age(yr) = 7.1


Journal of Science Communication | 2018

Appealing to different motivations in a message to recruit citizen scientists: results of a field experiment

Tae Kyoung Lee; Kevin Crowston; Mahboobeh Harandi; Carsten S. Østerlund; Grant Miller

\pm


Icarus | 2018

Planet Four: Probing Springtime Winds on Mars by Mapping the Southern Polar CO2 Jet Deposits

K.-Michael Aye; Megan E. Schwamb; Ganna Portyankina; Candice J. Hansen; Adam McMaster; Grant Miller; Brian Carstensen; Christopher Snyder; Michael Parrish; Stuart Lynn; Chuhong Mai; David Miller; Robert J. Simpson; Arfon M. Smith

0.1. From the V-Ha colour, a measure of the Ha emission strength, we conduct a survey for emission line objects within the association. We detect a sample of 33 Be stars, 8 of which are new detections. We present a scenario of evolutionary enhancement of the Be phenomenon to account for the peak in Be fraction towards the top of the main-sequence in the population of h & chi Persei and similar young clusters.


international joint conference on artificial intelligence | 2016

Intervention strategies for increasing engagement in crowdsourcing: platform, predictions, and experiments

Avi Segal; Ya'akov Gal; Ece Kamar; Eric Horvitz; Alex Bowyer; Grant Miller

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⊕) 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.


conference on computer supported cooperative work | 2017

Recruiting Messages Matter: Message Strategies to Attract Citizen Scientists

Tae Kyoung Lee; Kevin Crowston; Carsten S. Østerlund; Grant Miller

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.

Collaboration


Dive into the Grant Miller's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Brooke Simmons

University of California

View shared research outputs
Top Co-Authors

Avatar

Candice J. Hansen

Planetary Science Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Ganna Portyankina

University of Colorado Boulder

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge