arXiv subjects

David W. Hogg

Publications and source records attributed to David W. Hogg.

At least 91 records · Page 5Linked to original sources

arXiv2019

The Implications of Local Fluctuations in the Galactic Midplane for Dynamical Analysis in the Gaia Era

Orbital properties of stars, computed from their six-dimensional phase space measurements and an assumed Galactic potential, are used to understand the structure and evolution of the Galaxy. Stellar actions, computed from orbits, have the attractive quality of being invariant under certain assumptions and are therefore used as quantitative labels of a star's orbit. We report a subtle but important systematic error that is induced in the actions as a consequence of local midplane variations expected for the Milky Way. This error is difficult to model because it is non-Gaussian and bimodal, with neither mode peaking on the null value. An offset in the vertical position of the Galactic midplane of $\sim15\,\text{pc}$ for a thin disk-like orbit or $\sim 120\,\text{pc}$ for a thick disk-like orbit induces a $25\%$ systematic error in the vertical action $J_z$. In FIRE simulations of Milky Way-mass galaxies, these variations are on the order of $\sim100\,\text{pc}$ at the solar circle. From observations of the mean vertical velocity variation of $\sim5\text{--}10\,\text{km}\,\text{s}^{-1}$ with radius, we estimate that the Milky Way midplane variations are $\sim60\text{--}170\,\text{pc}$, consistent with three-dimensional dust maps. Action calculations and orbit integrations, which assume the global and local midplanes are identical, are likely to include this induced error, depending on the volume considered. Variation in the local standard of rest or distance to the Galactic center causes similar issues. The variation of the midplane must be taken into account when performing dynamical analysis across the large regions of the disk accessible to Gaia and future missions.

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arXiv2019

Towards precise stellar ages: combining isochrone fitting with empirical gyrochronology

We present a new age-dating technique that combines gyrochronology with isochrone fitting to infer ages for FGKM main-sequence and subgiant field stars. Gyrochronology and isochrone fitting are each capable of providing relatively precise ages for field stars in certain areas of the Hertzsprung-Russell diagram: gyrochronology works optimally for cool main-sequence stars, and isochrone fitting can provide precise ages for stars near the main-sequence turnoff. Combined, these two age-dating techniques can provide precise and accurate ages for a broader range of stellar masses and evolutionary stages than either method used in isolation. We demonstrate that the position of a star on the Hertzsprung- Russell or color-magnitude diagram can be combined with its rotation period to infer a precise age via both isochrone fitting and gyrochronology simultaneously. We show that incorporating rotation periods with 5% uncertainties into stellar evolution models improves age precision for FGK stars on the main sequence, and can, on average, provide age estimates up to three times more precise than isochrone fitting alone. In addition, we provide a new gyrochronology relation, calibrated to the Praesepe cluster and the Sun, that includes a variance model to capture the rotational behavior of stars whose rotation periods do not lengthen with the square-root of time, and parts of the Hertzsprung-Russell diagram where gyrochronology has not been calibrated. This publication is accompanied by an open source Python package, stardate, for inferring the ages of main-sequence and subgiant FGKM stars from rotation periods, spectroscopic parameters and/or apparent magnitudes and parallaxes.

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arXiv2019

Applying Liouville's Theorem to Gaia Data

The Milky Way is filled with the tidally-disrupted remnants of globular clusters and dwarf galaxies. Determining the properties of these objects -- in particular, initial masses and density profiles -- is relevant to both astronomy and dark matter physics. However, most direct measures of mass cannot be applied to tidal debris, as the systems of interest are no longer in equilibrium. Since phase-space density is conserved during adiabatic phase mixing, Liouville's theorem provides a connection between stellar kinematics as measured by observatories such as Gaia and the original mass of the disrupted system. Accurately recovering the phase-space density is complicated by uncertainties resulting from measurement errors and orbital integration, which both effectively inject entropy into the system, preferentially decreasing the measured density. In this paper, we demonstrate that these two issues can be overcome. First, we measure the phase-space density of the globular cluster M4 in Gaia data, and use Liouville's theorem to derive its mass. We then show that, for tidally disrupted systems, the orbital parameters and thus phase-space density can be inferred by minimizing the phase-space entropy of cold stellar streams. This work is therefore a proof of principle that true phase-space density can be measured and the original properties of the star cluster reconstructed in systems of astrophysical interest.

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arXiv2019

The Spur and the Gap in GD-1: Dynamical evidence for a dark substructure in the Milky Way halo

We present a model for the interaction of the GD-1 stellar stream with a massive perturber that naturally explains many of the observed stream features, including a gap and an off-stream spur of stars. The model involves an impulse by a fast encounter, after which the stream grows a loop of stars at different orbital energies. At specific viewing angles, this loop appears offset from the stream track. A quantitative comparison of the spur and gap features prefers models where the perturber is in the mass range of $10^6\,\rm M_\odot$ to $10^8\,\rm M_\odot$. Orbit integrations back in time show that the stream encounter could not have been caused by any known globular cluster or dwarf galaxy with a determined orbit, and mass, size and impact-parameter arguments show that it could not have been caused by a molecular cloud in the Milky Way disk. The most plausible explanation for the gap-and-spur structure is an encounter with a dark-matter substructure, like those predicted to populate galactic halos in LCDM cosmology. However, the expected densities of LCDM subhalos in this mass range and in this part of the Milky Way are $2-3\,σ$ lower than the inferred density of the GD-1 perturber. This observation opens up the possibility that detailed observations of streams could measure the mass spectrum of dark-matter substructures and even identify individual substructures and their orbits in the Galactic halo.

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arXiv2019

Multiple components of the Jhelum stellar stream

In simple models of the Milky Way, tidally disrupting satellites produce long and thin---nearly one-dimensional---stellar streams. Using astrometric data from the Gaia second data release and photometry from the Dark Energy Survey, we demonstrate that the Jhelum stream, a stellar stream in the inner halo, is a two-dimensional structure. The spatial distribution of highly probable Jhelum members reveals a dense thin component and an associated diffuse, spatially offset component. These two spatial components have indistinguishable proper motions (at $σ\sim1\,\rm mas\,yr^{-1}$ level) and a similar ratio of blue straggler to blue horizontal branch stars, which indicates a common origin for the two components. The best-fit orbit to the narrow component (pericenter $8\,\rm kpc$, apocenter $24\,\rm kpc$), however, does not explain the wide component of the Jhelum stream. On the other hand, an older orbital wrap of Jhelum's orbit traces the Indus stream, indicating a possible connection between these two structures and additional complexity in Jhelum's formation. Substructure in the Jhelum progenitor or precession of its tidal debris in the Milky Way potential may explain the observed structure of Jhelum. Future spectroscopic data will enable discrimination between these "nature" and "nurture" formation scenarios. Jhelum adds to the growing list of cold stellar streams that display complex morphologies and promise to reveal the dynamical history of the Milky Way.

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arXiv2019

Stellar multiplicity: an interdisciplinary nexus

Our uncertainties about binary star systems (and triples and so on) limit our capabilities in literally every single one of the Thematic Areas identified for Astro2020. We need to understand the population statistics of stellar multiplicity and their variations with stellar type, chemistry, and dynamical environment: Correct interpretation of any exoplanet experiment depends on proper treatment of resolved and unresolved binaries; stellar multiplicity is a direct outcome of star and companion formation; the most precise constraints on stellar structure come from well-characterized binary systems; stellar populations heavily rely on stellar and binary evolution modeling; high-redshift galaxy radiation and reionization is controlled by binary-dependent stellar physics; compact objects are the outcomes of binary evolution; the interpretation of multi-messenger astronomy from gravitational waves, light, and neutrinos relies on understanding the products of binary star evolution; near-Universe constraints on the Hubble constant with Type Ia supernovae and gravitational-wave mergers are subject to systematics related to their binary star progenitors; local measures of dark-matter substructure masses are distorted by binary populations. In order to realize the scientific goals in each of these themes over the next decade, we therefore need to understand how binary stars and stellar multiplets are formed and distributed in the space of masses, composition, age, and orbital properties, and how the distribution evolves with time. This white paper emphasizes the interdisciplinary importance of binary-star science and advocates that coordinated investment from all astrophysical communities will benefit almost all branches of astrophysics.

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arXiv2018

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA Derived Quantities, Data Visualization Tools and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (July 2014-July 2017). This is the third data release for SDSS-IV, and the fifteenth from SDSS (Data Release Fifteen; DR15). New data come from MaNGA - we release 4824 datacubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g. stellar and gas kinematics, emission line, and other maps) from the MaNGA Data Analysis Pipeline (DAP), and a new data visualisation and access tool we call "Marvin". The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials and examples of data use. While SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020-2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data.

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arXiv2018

The Circular Velocity Curve of the Milky Way from $5$ to $25$ kpc

We measure the circular velocity curve $v_{\rm c}(R)$ of the Milky Way with the highest precision to date across Galactocentric distances of $5\leq R \leq 25$ kpc. Our analysis draws on the $6$-dimensional phase-space coordinates of $\gtrsim 23,000$ luminous red-giant stars, for which we previously determined precise parallaxes using a data-driven model that combines spectral data from APOGEE with photometric information from WISE, 2MASS, and Gaia. We derive the circular velocity curve with the Jeans equation assuming an axisymmetric gravitational potential. At the location of the Sun we determine the circular velocity with its formal uncertainty to be $v_{\rm c}(R_{\odot}) = (229.0\pm0.2)\rm\,km\,s^{-1}$ with systematic uncertainties at the $\sim 2-5\%$ level. We find that the velocity curve is gently but significantly declining at $(-1.7\pm0.1)\rm\,km\,s^{-1}\,kpc^{-1}$, with a systematic uncertainty of $0.46\rm\,km\,s^{-1}\,kpc^{-1}$, beyond the inner $5$ kpc. We exclude the inner $5$ kpc from our analysis due to the presence of the Galactic bar, which strongly influences the kinematic structure and requires modeling in a non-axisymmetric potential. Combining our results with external measurements of the mass distribution for the baryonic components of the Milky Way from other studies, we estimate the Galaxy's dark halo mass within the virial radius to be $M_{\rm vir} = (7.25\pm0.26)\cdot 10^{11}M_{\odot}$ and a local dark matter density of $ρ_{\rm dm}(R_{\odot}) = 0.30\pm0.03\,\rm GeV\,cm^{-3}$.

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arXiv2018

Spectrophotometric parallaxes with linear models: Accurate distances for luminous red-giant stars

With contemporary infrared spectroscopic surveys like APOGEE, red-giant stars can be observed to distances and extinctions at which Gaia parallaxes are not highly informative. Yet the combination of effective temperature, surface gravity, composition, and age - all accessible through spectroscopy - determines a giant's luminosity. Therefore spectroscopy plus photometry should enable precise spectrophotometric distance estimates. Here we use the APOGEE-Gaia-2MASS-WISE overlap to train a data-driven model to predict parallaxes for red-giant branch stars with $0<\log g\leq2.2$ (more luminous than the red clump). We employ (the exponentiation of) a linear function of APOGEE spectral pixel intensities and multi-band photometry to predict parallax spectrophotometrically. The model training involves no logarithms or inverses of the Gaia parallaxes, and needs no cut on the Gaia parallax signal-to-noise ratio. It includes an L1 regularization to zero out the contributions of uninformative pixels. The training is performed with leave-out subsamples such that no star's astrometry is used even indirectly in its spectrophotometric parallax estimate. The model implicitly performs a reddening and extinction correction in its parallax prediction, without any explicit dust model. We assign to each star in the sample a new spectrophotometric parallax estimate; these parallaxes have uncertainties of a few to 15 percent, depending on data quality, which is more precise than the Gaia parallax for the vast majority of targets, and certainly any stars more than a few kpc distance. We obtain 10-percent distance estimates out to heliocentric distances of $20\,$kpc, and make global maps of the Milky Way's disk.

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arXiv2018

Detection of the Milky Way spiral arms in dust from 3D mapping

Large stellar surveys are sensitive to interstellar dust through the effects of reddening. Using extinctions measured from photometry and spectroscopy, together with three-dimensional (3D) positions of individual stars, it is possible to construct a three-dimensional dust map. We present the first continuous map of the dust distribution in the Galactic disk out to 7 kpc within 100 pc of the Galactic midplane, using red clump and giant stars from SDSS APOGEE DR14. We use a non-parametric method based on Gaussian Processes to map the dust density, which is the local property of the ISM rather than an integrated quantity. This method models the dust correlation between points in 3D space and can capture arbitrary variations, unconstrained by a pre-specified functional form. This produces a continuous map without line-of-sight artefacts. Our resulting map traces some features of the local Galactic spiral arms, even though the model contains no prior suggestion of spiral arms, nor any underlying model for the Galactic structure. This is the first time that such evident arm structures have been captured by a dust density map in the Milky Way. Our resulting map also traces some of the known giant molecular clouds in the Galaxy and puts some constraints on their distances, some of which were hitherto relatively uncertain.

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arXiv2018

Multi-Messenger Astrophysics: Harnessing the Data Revolution

The past year has witnessed discovery of the first identified counterparts to a gravitational wave transient (GW 170817A) and a very high-energy neutrino (IceCube-170922A). These source identifications, and ensuing detailed studies, have realized longstanding dreams of astronomers and physicists to routinely carry out observations of cosmic sources by other than electromagnetic means, and inaugurated the era of "multi-messenger" astronomy. While this new era promises extraordinary physical insights into the universe, it brings with it new challenges, including: highly heterogeneous, high-volume, high-velocity datasets; globe-spanning cross-disciplinary teams of researchers, regularly brought together into transient collaborations; an extraordinary breadth and depth of domain-specific knowledge and computing resources required to anticipate, model, and interpret observations; and the routine need for adaptive, distributed, rapid-response observing campaigns to fully exploit the scientific potential of each source. We argue, therefore, that the time is ripe for the community to conceive and propose an Institute for Multi-Messenger Astrophysics that would coordinate its resources in a sustained and strategic fashion to efficiently address these challenges, while simultaneously serving as a center for education and key supporting activities. In this fashion, we can prepare now to realize the bright future that we see, beyond, through these newly opened windows onto the universe.

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arXiv2018

Hierarchical modeling and statistical calibration for photometric redshifts

The cosmological exploitation of modern photometric galaxy surveys requires both accurate (unbiased) and precise (narrow) redshift probability distributions derived from broadband photometry. Existing methodologies do not meet those requirements. Standard template fitting delivers interpretable models and errors, but lacks flexibility to learn inaccuracies in the observed photometry or the spectral templates. Machine learning addresses those issues, but requires representative training data, and the resulting models and uncertainties cannot be interpreted in the context of a physical model or outside of the training data. We present a hierarchical modeling approach simultaneously addressing the issues of flexibility, interpretability, and generalization. It combines template fitting with flexible (machine learning-like) models to correct the spectral templates, model their redshift distributions, and recalibrate the photometric observations. By optimizing the full posterior distribution of the model and solving for its (thousands of) parameters, one can perform a global statistical calibration of the data and the SED model. We apply this approach to the public Dark Energy Survey Science Verification data, and show that it provides more accurate and compact redshift posterior distributions than existing methods, as well as insights into residual photometric and SED systematics. The model is causal, makes predictions for future data (e.g., additional photometric bandpasses), and its internal parameters and components are interpretable. This approach does not formally require the training data to be complete or representative; in principle it can even work in regimes in which few or no spectroscopic redshifts are available.

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arXiv2018

Science Impacts of the SPHEREx All-Sky Optical to Near-Infrared Spectral Survey II: Report of a Community Workshop on the Scientific Synergies Between the SPHEREx Survey and Other Astronomy Observatories

SPHEREx is a proposed NASA MIDEX mission selected for Phase A study. SPHEREx would carry out the first all-sky spectral survey in the near infrared. At the end of its two-year mission, SPHEREx would obtain 0.75-to-5$μ$m spectra of every 6.2 arcsec pixel on the sky, with spectral resolution R>35 and a 5-$σ$ sensitivity AB$>$19 per spectral/spatial resolution element. More details concerning SPHEREx are available at http://spherex.caltech.edu. The SPHEREx team has proposed three specific science investigations to be carried out with this unique data set: cosmic inflation, interstellar and circumstellar ices, and the extra-galactic background light. Though these three themes are undoubtedly compelling, they are far from exhausting the scientific output of SPHEREx. Indeed, SPHEREx would create a unique all-sky spectral database including spectra of very large numbers of astronomical and solar system targets, including both extended and diffuse sources. These spectra would enable a wide variety of investigations, and the SPHEREx team is dedicated to making the data available to the community to enable these investigations, which we refer to as Legacy Science. To that end, we have sponsored two workshops for the general scientific community to identify the most interesting Legacy Science themes and to ensure that the SPHEREx data products are responsive to their needs. In February of 2016, some 50 scientists from all fields met in Pasadena to develop these themes and to understand their implications for the SPHEREx mission. The 2016 workshop highlighted many synergies between SPHEREx and other contemporaneous astronomical missions, facilities, and databases. Consequently, in January 2018 we convened a second workshop at the Center for Astrophysics in Cambridge to focus specifically on these synergies. This white paper reports on the results of the 2018 SPHEREx workshop.

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arXiv2018

Measuring Radial Orbit Migration in the Milky Way Disk

We develop and apply a model to quantify the global efficiency of radial orbit migration among stars in the Milky Way disk. This model parameterizes the possible star formation and enrichment histories, radial birth profiles, and combines them with a migration model that relates present-day orbital radii to birth radii through a Gaussian probability, broadening with age $τ$ as $σ_\mathrm{RM8}~\sqrt{τ/8{~\mathrm{Gyr}}}$. Guided by observations, we assume that stars are born with an initially tight age--metallicity relation at given radius, which becomes subsequently scrambled by radial orbit migration, thereby providing a direct observational constraint on radial orbit migration strength $σ_\mathrm{RM8}$. We fit this model with MCMC to the observed age--metallicity distribution of low-$α$ red clump stars with Galactocentric radii between 5 and 14 kpc from APOGEE DR12, sidestepping the complex spatial selection function and accounting for the considerable age uncertainties. This simple model reproduces well the observed data, and we find a global (in radius and time) radial orbit migration efficiency in the Milky Way of $σ_\mathrm{RM8}=3.6\pm 0.1$ kpc when marginalizing over all other model aspects. This shows that radial orbit migration in the Milky Way's main disk is indeed rather strong, in line with theoretical expectations: stars migrate by about a half-mass radius over the age of the disk. The model finds the Sun's birth radius at $\sim 5.2$ kpc. If such strong radial orbit migration is typical, this mechanism plays indeed an important role in setting the structural regularity of disk galaxies.

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arXiv2018

Inference of stellar parameters from brightness variations

It has been demonstrated that the time variability of a star's brightness at different frequencies can be used to infer its surface gravity, radius, mass, and age. With large samples of light curves now available from Kepler and K2, and upcoming surveys like TESS, we wish to quantify the overall information content of this data and identify where the information resides. As a first look into this question we ask which stellar parameters we can predict from the brightness variations in red-giant stars data and to what precision, using a data-driven model. We demonstrate that the long-cadence (30-minute) Kepler light curves for 2000 red-giant stars can be used to predict their $T_{\rm eff}$ and $\log g$. Our inference makes use of a data-driven model of a part of the autocorrelation function (ACF) of the light curve, where we posit a polynomial relationship between stellar parameters and the ACF pixel values. We find that this model, trained using 1000 stars, can be used to recover the temperature $T_{\rm eff}$ to $<$100 K, the surface gravity to $<$ 0.1 dex, and the asteroseismic power-spectrum parameters $\rm ν_{max}$ and $\rm Δν$ to $<11$ $μ$Hz and $<0.9$ $μ$Hz ($\lesssim$ 15\%). We recover $T_{\rm eff}$ from range of time-lags 0.045 $<$ $T_{\rm lag}$ $<$ 370 days and the $\log g$, $\rm ν_{max}$ and $\rm Δν$ from the range 0.045 $<$ $T_{\rm lag}$ $<$ 35 days. We do not discover any information about stellar metallicity. The information content of the data about each parameter is empirically quantified using this method, enabling comparisons to theoretical expectations about convective granulation.

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arXiv2018

An Ultraviolet-Optical Color-Metallicity relation for Red Clump Stars using GALEX and Gaia

Although core helium-burning red clump (RC) stars are faint at ultraviolet wavelengths, their ultraviolet-optical color is a unique and accessible probe of their physical properties. Using data from the GALEX All Sky Imaging Survey, Gaia Data Release 2 and the SDSS APOGEE DR14 survey, we find that spectroscopic metallicity is strongly correlated with the location of an RC star in the UV-optical color magnitude diagram. The RC has a wide spread in (NUV - G)$_0$ color, over 4 magnitudes, compared to a 0.7-magnitude range in (G$_{BP}$ - G$_{RP}$)$_0$. We propose a photometric, dust-corrected, ultraviolet-optical (NUV - G)$_0$ color-metallicity [Fe/H] relation using a sample of 5,175 RC stars from APOGEE. We show that this relation has a scatter of 0.28 dex and is easier to obtain for large, wide-field samples than spectroscopic metallicities. Importantly, the effect may be comparable to the spread in RC color attributed to extinction in other studies.

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arXiv2018

The information content in cold stellar streams

Cold stellar streams---produced by tidal disruptions of clusters---are long-lived, coherent dynamical features in the halo of the Milky Way. Due to their different ages and different positions in phase space, different streams tell us different things about the Galaxy. Here we employ a Cramer--Rao (CRLB) or Fisher-matrix approach to understand the quantitative information content in eleven known streams (ATLAS, GD-1, Hermus, Kwando, Orinoco, PS1A, PS1C, PS1D, PS1E, Sangarius and Triangulum). This approach depends on a generative model, which we have developed previously, and which permits calculation of derivatives of predicted stream properties with respect to Galaxy and stream parameters. We find that in simple analytic models of the Milky Way, streams on eccentric orbits contain the most information about the halo shape. For each stream, there are near-degeneracies between dark-matter-halo properties and parameters of the bulge, the disk, and the stream progenitor, but simultaneous fitting of multiple streams will constrain all parameters at the percent level. At this precision, simulated dark matter halos deviate from simple analytic parametrizations, so we add an expansion of basis functions to give the gravitational potential more freedom. As freedom increases, the information about the halo reduces overall, and it becomes more localized to the current position of the stream. In the limit of high model freedom, a stellar stream appears to measure the local acceleration at its current position; this motivates thinking about future non-parametric approaches. The CRLB formalism also permits us to assess the value of future measurements of stellar velocities, distances, and proper motions. We show that kinematic measurements of stream stars are essential for producing competitive constraints on the distribution of dark matter, which bodes well for stream studies in the age of Gaia.

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arXiv2018

Binary companions of evolved stars in APOGEE DR14: Search method and catalog of ~5,000 companions

Multi-epoch radial velocity measurements of stars can be used to identify stellar, sub-stellar, and planetary-mass companions. Even a small number of observation epochs can be informative about companions, though there can be multiple qualitatively different orbital solutions that fit the data. We have custom-built a Monte Carlo sampler (The Joker) that delivers reliable (and often highly multi-modal) posterior samplings for companion orbital parameters given sparse radial-velocity data. Here we use The Joker to perform a search for companions to 96,231 red-giant stars observed in the APOGEE survey (DR14) with $\geq 3$ spectroscopic epochs. We select stars with probable companions by making a cut on our posterior belief about the amplitude of the stellar radial-velocity variation induced by the orbit. We provide (1) a catalog of 320 companions for which the stellar companion properties can be confidently determined, (2) a catalog of 4,898 stars that likely have companions, but would require more observations to uniquely determine the orbital properties, and (3) posterior samplings for the full orbital parameters for all stars in the parent sample. We show the characteristics of systems with confidently determined companion properties and highlight interesting systems with candidate compact object companions.

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