152 research outputs found

    Fast and scalable Gaussian process modeling with applications to astronomical time series

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    The growing field of large-scale time domain astronomy requires methods for probabilistic data analysis that are computationally tractable, even with large datasets. Gaussian Processes are a popular class of models used for this purpose but, since the computational cost scales, in general, as the cube of the number of data points, their application has been limited to small datasets. In this paper, we present a novel method for Gaussian Process modeling in one-dimension where the computational requirements scale linearly with the size of the dataset. We demonstrate the method by applying it to simulated and real astronomical time series datasets. These demonstrations are examples of probabilistic inference of stellar rotation periods, asteroseismic oscillation spectra, and transiting planet parameters. The method exploits structure in the problem when the covariance function is expressed as a mixture of complex exponentials, without requiring evenly spaced observations or uniform noise. This form of covariance arises naturally when the process is a mixture of stochastically-driven damped harmonic oscillators -- providing a physical motivation for and interpretation of this choice -- but we also demonstrate that it can be a useful effective model in some other cases. We present a mathematical description of the method and compare it to existing scalable Gaussian Process methods. The method is fast and interpretable, with a range of potential applications within astronomical data analysis and beyond. We provide well-tested and documented open-source implementations of this method in C++, Python, and Julia.Comment: Updated in response to referee. Submitted to the AAS Journals. Comments (still) welcome. Code available: https://github.com/dfm/celerit

    Inferring probabilistic stellar rotation periods using Gaussian processes

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    Variability in the light curves of spotted, rotating stars is often non-sinusoidal and quasi-periodic --- spots move on the stellar surface and have finite lifetimes, causing stellar flux variations to slowly shift in phase. A strictly periodic sinusoid therefore cannot accurately model a rotationally modulated stellar light curve. Physical models of stellar surfaces have many drawbacks preventing effective inference, such as highly degenerate or high-dimensional parameter spaces. In this work, we test an appropriate effective model: a Gaussian Process with a quasi-periodic covariance kernel function. This highly flexible model allows sampling of the posterior probability density function of the periodic parameter, marginalising over the other kernel hyperparameters using a Markov Chain Monte Carlo approach. To test the effectiveness of this method, we infer rotation periods from 333 simulated stellar light curves, demonstrating that the Gaussian process method produces periods that are more accurate than both a sine-fitting periodogram and an autocorrelation function method. We also demonstrate that it works well on real data, by inferring rotation periods for 275 Kepler stars with previously measured periods. We provide a table of rotation periods for these 1132 Kepler objects of interest and their posterior probability density function samples. Because this method delivers posterior probability density functions, it will enable hierarchical studies involving stellar rotation, particularly those involving population modelling, such as inferring stellar ages, obliquities in exoplanet systems, or characterising star-planet interactions. The code used to implement this method is available online.Comment: Submitted to MNRAS. Replaced 27/06/2017: corrections made to koi_periods.cs

    Reprogramming cellular fate using defined factors

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."March 2009."Includes bibliographical references.Embryonic stem (ES) cells have a vast therapeutic potential given their pluripotency, or the ability to differentiate into tissues from all three germ layers. One of the ultimate goals of regenerative medicine is to isolate pluripotent stem cells from patients. Nuclear reprogramming offers the possibility of creating patient-specific cell lines, thus abrogating the need for immunosuppressants following cell transplantation therapy. It was recently reported that the forced expression of four transcription factors, Oct4, Sox2, c-Myc and Klf4 can induce a pluripotent state in somatic cells, without the need for embryo destruction. The work presented here aims to characterize reprogramming using defined factors and provide insight into the mechanisms governing this process. It also seeks to identify transient cues to induce reprogramming in somatic cells, alleviating the need for virally transduced transcription factors that hinder its eventual clinical use.by Ruth K. Foreman.Ph.D

    An Evaluation of the Developmental Reading Program at South Dakota State College

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    In the past twenty years, much interest has been shown in the student who is handicapped in learning because of reading problems, whether of speed or comprehension or both. Attempts are being made in many colleges throughout the nation to set up reading laboratories for remedial training of these students. Since most educators assume a close correlation between reading comprehension and success in college, there is hope that by improvement of reading, more students may be able to continue and complete their college careers. The primary objective of the study is to evaluate the help given by the developmental reading course to students low in reading comprehension. The problem of evaluating a reading program is a complex one. In the first place, the program deals with two groups of students – those required to take the course and those elect the course. In the second place, the benefits derived from a developmental reading course are difficult to measure. In the third place, many variables which concern the success or lack of success of a college student cannot be controlled, such as motivation, emotional disturbances, economic and financial problem, difficulty of other course work, and health problems. A basic procedure was set up to involve a four-step investigation, each step revealing information about the Developmental Reading Program and lending its information to the next step until the fourth, final, and conclusive step. The results were then studied and final observations and conclusions made about the value of the developmental reading program to students at South Dakota State College, and also what expansions or revisions could be employed to make the course more meaningful and more valuable

    In this Day and Age: An Empirical Gyrochronology Relation for Partially and Fully Convective Single Field Stars

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    Gyrochronology, the field of age-dating stars using mainly their rotation periods and masses, is ideal for inferring the ages of individual main-sequence stars. However, due to the lack of physical understanding of the complex magnetic fields in stars, gyrochronology relies heavily on empirical calibrations that require consistent and reliable stellar age measurements across a wide range of periods and masses. In this paper, we obtain a sample of consistent ages using the gyro-kinematic age-dating method, a technique to calculate the kinematics ages of stars. Using a Gaussian Process model conditioned on ages from this sample (~ 1 - 14 Gyr) and known clusters (0.67 - 3.8 Gyr), we calibrate the first empirical gyrochronology relation that is capable of inferring ages for single, main-sequence stars between 0.67 Gyr to 14 Gyr. Cross-validating and testing results suggest our model can infer cluster and asteroseismic ages with an average uncertainty of just over 1 Gyr. With this model, we obtain gyrochronology ages for ~ 100,000 stars within 1.5 kpc of the Sun with period measurements from Kepler and ZTF, and 384 unique planet host stars.Comment: Submitted to AJ. Missing citations welcom

    Detecting Solar System Analogs through Joint Radial Velocity/Astrometric Surveys

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    Earth-mass exoplanets on year-long orbits and cool gas giants (CGG) on decade-long orbits lie at the edge of current detection limits. The Terra Hunting Experiment (THE) will take nightly radial velocity (RV) observations on HARPS3 of at least 40 bright nearby G and K dwarfs for 10 years, with a target 1σ\sigma measurement error of \sim0.3 m/s, in search of exoplanets that are Earth-like in mass and temperature. However, RV observations can only provide minimum mass estimates, due to the mass-inclination degeneracy. Astrometric observations of these same stars, with sufficient precision, could break this degeneracy. Gaia will soon release \sim100-200 astrometric observations of the THE stars with a 10 year baseline and \sim34.2 μ\muas 1σ\sigma along-scan measurement error. The Nancy Grace Roman Space Telescope will be capable of precision astrometry using its wide field imager (target \sim5-20 μ\muas 1σ\sigma measurement error for bright stars) and could extend the astrometric observational baseline to \sim25 years. We simulate and model an observing program that combines data from these three telescopes. We find that (1) THE RVs and Gaia astrometry can detect Earth-like and CGG-like exoplanets around bright Sun-like stars at 10 parsecs and that (2) adding Roman astrometry improves the detection precision for CGG masses and periods by a factor up to \sim10 and \sim4, respectively. Such a survey could provide insight into the prevalence of Solar System analogs, exoplanet architectures reminiscent of the mass and orbital separation hierarchy of our Solar System, for the nearest Sun-like stars.Comment: 21 pages, 10 figures. Revised based on comments from anonymous reviewer at AAS Journals. Code available at https://github.com/dyahalomi/rv_and_astrometr
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