arXiv subjects

Daniel Foreman-Mackey

Publications and source records attributed to Daniel Foreman-Mackey.

At least 37 records · Page 2Linked to original sources

arXiv2022

Calibrating cosmological simulations with implicit likelihood inference using galaxy growth observables

In a novel approach employing implicit likelihood inference (ILI), also known as likelihood-free inference, we calibrate the parameters of cosmological hydrodynamic simulations against observations, which has previously been unfeasible due to the high computational cost of these simulations. For computational efficiency, we train neural networks as emulators on ~1000 cosmological simulations from the CAMELS project to estimate simulated observables, taking as input the cosmological and astrophysical parameters, and use these emulators as surrogates to the cosmological simulations. Using the cosmic star formation rate density (SFRD) and, separately, stellar mass functions (SMFs) at different redshifts, we perform ILI on selected cosmological and astrophysical parameters (Omega_m, sigma_8, stellar wind feedback, and kinetic black hole feedback) and obtain full 6-dimensional posterior distributions. In the performance test, the ILI from the emulated SFRD (SMFs) can recover the target observables with a relative error of 0.17% (0.4%). We find that degeneracies exist between the parameters inferred from the emulated SFRD, confirmed with new full cosmological simulations. We also find that the SMFs can break the degeneracy in the SFRD, which indicates that the SMFs provide complementary constraints for the parameters. Further, we find that the parameter combination inferred from an observationally-inferred SFRD reproduces the target observed SFRD very well, whereas, in the case of the SMFs, the inferred and observed SMFs show significant discrepancies that indicate potential limitations of the current galaxy formation modeling and calibration framework, and/or systematic differences and inconsistencies between observations of the stellar mass function.

astro-ph.CO↗

arXiv2022

Early Release Science of the Exoplanet WASP-39b with JWST NIRSpec G395H

Measuring the abundances of carbon and oxygen in exoplanet atmospheres is considered a crucial avenue for unlocking the formation and evolution of exoplanetary systems. Access to an exoplanet's chemical inventory requires high-precision observations, often inferred from individual molecular detections with low-resolution space-based and high-resolution ground-based facilities. Here we report the medium-resolution (R$\sim$600) transmission spectrum of an exoplanet atmosphere between 3-5 $μ$m covering multiple absorption features for the Saturn-mass exoplanet WASP-39b, obtained with JWST NIRSpec G395H. Our observations achieve 1.46x photon precision, providing an average transit depth uncertainty of 221 ppm per spectroscopic bin, and present minimal impacts from systematic effects. We detect significant absorption from CO$_2$ (28.5$σ$) and H$_2$O (21.5$σ$), and identify SO$_2$ as the source of absorption at 4.1 $μ$m (4.8$σ$). Best-fit atmospheric models range between 3 and 10x solar metallicity, with sub-solar to solar C/O ratios. These results, including the detection of SO$_2$, underscore the importance of characterising the chemistry in exoplanet atmospheres, and showcase NIRSpec G395H as an excellent mode for time series observations over this critical wavelength range.

astro-ph.EP↗

arXiv2022

Gaussian Process regression for astronomical time-series

The last two decades have seen a major expansion in the availability, size, and precision of time-domain datasets in astronomy. Owing to their unique combination of flexibility, mathematical simplicity and comparative robustness, Gaussian Processes (GPs) have emerged recently as the solution of choice to model stochastic signals in such datasets. In this review we provide a brief introduction to the emergence of GPs in astronomy, present the underlying mathematical theory, and give practical advice considering the key modelling choices involved in GP regression. We then review applications of GPs to time-domain datasets in the astrophysical literature so far, from exoplanets to active galactic nuclei, showcasing the power and flexibility of the method. We provide worked examples using simulated data, with links to the source code, discuss the problem of computational cost and scalability, and give a snapshot of the current ecosystem of open source GP software packages. Driven by further algorithmic and conceptual advances, we expect that GPs will continue to be an important tool for robust and interpretable time domain astronomy for many years to come.

astro-ph.IM↗

arXiv2022

flowMC: Normalizing-flow enhanced sampling package for probabilistic inference in Jax

flowMC is a Python library for accelerated Markov Chain Monte Carlo (MCMC) leveraging deep generative modeling. It is built on top of the machine learning libraries JAX and Flax. At its core, flowMC uses a local sampler and a learnable global sampler in tandem to efficiently sample posterior distributions. While multiple chains of the local sampler generate samples over the region of interest in the target parameter space, the package uses these samples to train a normalizing flow model, then uses it to propose global jumps across the parameter space. The flowMC sampler can handle non-trivial geometry, such as multimodal distributions and distributions with local correlations. The key features of flowMC are summarized in the following list: * Since flowMC is built on top of JAX, it supports gradient-based samplers through automatic differentiation such as MALA and Hamiltonian Monte Carlo (HMC). * flowMC uses state-of-the-art normalizing flow models such as Rational-Quadratic Splines to power its global sampler. These models are very efficient in capturing important features within a relatively short training time. * Use of accelerators such as GPUs and TPUs are natively supported. The code also supports the use of multiple accelerators with SIMD parallelism. * By default, Just-in-time (JIT) compilations are used to further speed up the sampling process. * We provide a simple black box interface for the users who want to use flowMC by its default parameters, yet provide at the same time an extensive guide explaining trade-offs while tuning the sampler parameters. The tight integration of all the above features makes flowMC a highly performant yet simple- to-use package for statistical inference.

astro-ph.IM↗

arXiv2022

The Initial Magnetic Field Distribution in AB Stars

Stars are born with magnetic fields, but the distribution of their initial field strengths remains uncertain. We combine observations with theoretical models of magnetic field evolution to infer the initial distribution of magnetic fields for AB stars in the mass range of 1.6 - 3.4 M$_{\odot}$. We tested a variety of distributions with different shapes and found that a distribution with a mean of $\sim$800 G and a full width of $\sim$600 G is most consistent with the observed fraction of strongly magnetized stars as a function of mass. Our most-favored distribution is a Gaussian with a mean of $μ$ = 770 G and standard deviation of $σ$ = 146 G. Independent approaches to measure the typical field strength suggest values closer to 2 - 3 kG, a discrepancy that could suggest a mass-dependent and bimodal initial field distribution, or an alternative theoretical picture for the origin of these magnetic fields.

astro-ph.SR↗

arXiv2022

A Generative Model for Quasar Spectra

We build a multi-output generative model for quasar spectra and the properties of their black hole engines, based on a Gaussian process latent-variable model. This model treats every quasar as a vector of latent properties such that the spectrum and all physical properties of the quasar are associated with non-linear functions of those latent parameters; the Gaussian process kernel functions define priors on the function space. Our generative model is trained with a justifiable likelihood function that allows us to treat heteroscedastic noise and missing data correctly, which is crucial for all astrophysical applications. It can predict simultaneously unobserved spectral regions, as well as the physical properties of quasars in held-out test data. We apply the model to rest-frame ultraviolet and optical quasar spectra for which precise black hole masses (based on reverberation mapping measurements) are available. Unlike reverberation-mapping studies, which require multi-epoch data, our model predicts black hole masses from single-epoch spectra, even with limited spectral coverage. We demonstrate the capabilities of the model by predicting black hole masses and unobserved spectral regions. We find that we predict black hole masses at close to the best possible accuracy.

astro-ph.GA↗

arXiv2022

A Mirage or an Oasis? Water Vapor in the Atmosphere of the Warm Neptune TOI-674 b

We report observations of the recently discovered warm Neptune TOI-674 b (5.25 \rearth{}, 23.6 \mearth{}) with the Hubble Space Telescope's Wide Field Camera 3 instrument. TOI-674 b is in the Neptune desert, an observed paucity of Neptune-size exoplanets at short orbital periods. Planets in the desert are thought to have complex evolutionary histories due to photoevaporative mass loss or orbital migration, making identifying the constituents of their atmospheres critical to understanding their origins. We obtained near-infrared transmission spectroscopy of the planet's atmosphere with the G141 grism. After extracting, detrending, and fitting the spectral lightcurves to measure the planet's transmission spectrum, we used the petitRADTRANS atmospheric spectral synthesis code to perform retrievals on the planet's atmosphere to identify which absorbers are present. These results show moderate evidence for increased absorption at 1.4 $μ$m due to water vapor at 2.9$σ$ (Bayes factor = 15.8), as well as weak evidence for the presence of clouds at 2.2$σ$ (Bayes factor = 4.0). TOI-674 b is a strong candidate for further study to refine the water abundance, which is poorly constrained by our data. We also incorporated new TESS short-cadence optical photometry, as well as Spitzer/IRAC data, and re-fit the transit parameters for the planet. We find the planet to have the following transit parameters: $R_p/R_* = 0.1135\pm0.0006$, $T_0 = 2458544.523792\pm0.000452$ BJD, and $P = 1.977198\pm0.00007$ d. These measurements refine the planet radius estimate and improve the orbital ephemerides for future transit spectroscopy observations of this highly intriguing warm Neptune.

astro-ph.EP↗

arXiv2022

The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package

The Astropy Project supports and fosters the development of open-source and openly-developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package $\texttt{astropy}$, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates for the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project.

astro-ph.IM↗

arXiv2022

The 3D Galactocentric velocities of Kepler stars: marginalizing over missing RVs

Precise Gaia measurements of positions, parallaxes, and proper motions provide an opportunity to calculate 3D positions and 2D velocities (i.e. 5D phase-space) of Milky Way stars. Where available, spectroscopic radial velocity (RV) measurements provide full 6D phase-space information, however there are now and will remain many stars without RV measurements. Without an RV it is not possible to directly calculate 3D stellar velocities, however one can infer 3D stellar velocities by marginalizing over the missing RV dimension. In this paper, we infer the 3D velocities of stars in the Kepler field in Cartesian Galactocentric coordinates (vx, vy, vz). We directly calculate velocities for around a quarter of all Kepler targets, using RV measurements available from the Gaia, LAMOST and APOGEE spectroscopic surveys. Using the velocity distributions of these stars as our prior, we infer velocities for the remaining three-quarters of the sample by marginalizing over the RV dimension. The median uncertainties on our inferred vx, vy, and vz velocities are around 4, 18, and 4 km/s, respectively. We provide 3D velocities for a total of 148,590 stars in the Kepler field. These 3D velocities could enable kinematic age-dating, Milky Way stellar population studies, and other scientific studies using the benchmark sample of well-studied Kepler stars. Although the methodology used here is broadly applicable to targets across the sky, our prior is specifically constructed from and for the Kepler field. Care should be taken to use a suitable prior when extending this method to other parts of the Galaxy.

astro-ph.GA↗

arXiv2022

The unpopular Package: a Data-driven Approach to De-trend TESS Full Frame Image Light Curves

The majority of observed pixels on the Transiting Exoplanet Survey Satellite (TESS) are delivered in the form of full frame images (FFI). However, the FFIs contain systematic effects such as pointing jitter and scattered light from the Earth and Moon that must be removed before downstream analysis. We present unpopular, an open-source Python package to de-trend TESS FFI light curves based on the causal pixel model method. Under the assumption that shared flux variations across multiple distant pixels are likely to be systematics, unpopular removes these common (i.e., popular) trends by modeling the systematics in a given pixel's light curve as a linear combination of light curves from many other distant pixels. To prevent overfitting we employ ridge regression and a train-and-test framework where the data points being de-trended are separated from those used to obtain the model coefficients. We also allow for simultaneous fitting with a polynomial model to capture any long-term astrophysical trends. We validate our method by de-trending different sources (e.g., supernova, tidal disruption event, exoplanet-hosting star, fast rotating star) and comparing our light curves to those obtained by other pipelines when appropriate. We also show that unpopular is able to preserve sector-length astrophysical signals, allowing for the extraction of multi-sector light curves from the FFI data. The unpopular source code and tutorials are freely available online.

astro-ph.IM↗

arXiv2022

An Aligned Orbit for the Young Planet V1298 Tau b

The alignment of planetary orbits with respect to the stellar rotation preserves information on their dynamical histories. Measuring this angle for young planets help illuminate the mechanisms that create misaligned orbits for older planets, as different processes could operate over timescales ranging from a few Myr to a Gyr. We present spectroscopic transit observations of the young exoplanet V1298 Tau b; we update the age of V1298 Tau to be $28\pm4$ Myr based on Gaia EDR3 measurements. We observed a partial transit with Keck/HIRES and LBT/PEPSI, and detected the radial velocity anomaly due to the Rossiter-McLaughlin effect. V1298 Tau~b has a prograde, well-aligned orbit, with $λ= 4_{-10}^{+7 \circ}$. By combining the spectroscopically-measured $v\sin i_{\star}$ and the phtometrically-measured rotation period of the host star we also find that the orbit is aligned in 3D, $ψ= 8_{-7}^{+4 \circ}$ deg. Finally, we combine our obliquity constraints with a previous measurement for the interior planet V1298 Tau c to constrain the mutual inclination between the two planets to be $i_{\mathrm{mut}}=0^{\circ} \pm 19^{\circ}$. This measurements adds to the growing number of well-aligned planets at young ages, hinting that misalignments may be generated over timescales of longer than tens of Myr. The number of measurements, however, is still small, and this population may not be representative of the older planets that have been observed to date. We also present the derivation of the relationship between $i_{\mathrm{mut}}$, $λ$, and $i$ for two planets.

astro-ph.EP↗

arXiv2022

A Bayesian Population Model for the Observed Dust Attenuation in Galaxies

Dust plays a pivotal role in determining the observed spectral energy distribution (SED) of galaxies. Yet our understanding of dust attenuation is limited and our observations suffer from the dust-metallicity-age degeneracy in SED fitting (single galaxies), large individual variances (ensemble measurements), and the difficulty in properly dealing with uncertainties (statistical considerations). In this study, we create a population Bayesian model to rigorously account for correlated variables and non-Gaussian error distributions and demonstrate the improvement over a simple Bayesian model. We employ a flexible 5-D linear interpolation model for the parameters that control dust attenuation curves as a function of stellar mass, star formation rate (SFR), metallicity, redshift, and inclination. Our setup allows us to determine the complex relationships between dust attenuation and these galaxy properties simultaneously. Using Prospector fits of nearly 30,000 3D-HST galaxies, we find that the attenuation slope ($n$) flattens with increasing optical depth ($τ$), though less so than in previous studies. $τ$ increases strongly with SFR, though when $\log~{\rm SFR}\lesssim 0$, $τ$ remains roughly constant over a wide range of stellar masses. Edge-on galaxies tend to have larger $τ$ than face-on galaxies, but only for $\log~M_*\gtrsim 10$, reflecting the lack of triaxiality for low-mass galaxies. Redshift evolution of dust attenuation is strongest for low-mass, low-SFR galaxies, with higher optical depths but flatter curves at high redshift. Finally, $n$ has a complex relationship with stellar mass, highlighting the intricacies of the star-dust geometry. We have publicly released software (https://github.com/Astropianist/DustE) for users to access our population model.

astro-ph.GA↗

arXiv2022

The Thresher: Lucky Imaging without the Waste

In traditional lucky imaging (TLI), many consecutive images of the same scene are taken with a high frame-rate camera, and all but the sharpest images are discarded before constructing the final shift-and-add image. Here we present an alternative image analysis pipeline -- The Thresher -- for these kinds of data, based on online multi-frame blind deconvolution. It makes use of all available data to obtain a best estimate of the astronomical scene in the context of reasonable computational limits; it does not require prior estimates of the point-spread functions in the images, or knowledge of point sources in the scene that could provide such estimates. Most importantly, the scene it aims to return is the optimum of a justified scalar objective based on the likelihood function. Because it uses the full set of images in the stack, The Thresher outperforms TLI in signal-to-noise; as it accounts for the individual-frame PSFs, it does this without loss of angular resolution. We demonstrate the effectiveness of our algorithm on both simulated data and real Electron-Multiplying CCD images obtained at the Danish 1.54m telescope (hosted by ESO, La Silla). We also explore the current limitations of the algorithm, and find that for the choice of image model presented here, non-linearities in flux are introduced into the returned scene. Ongoing development of the software can be viewed at https://github.com/jah1994/TheThresher.

astro-ph.IM↗

arXiv2022

V1298 Tau with TESS: Updated Ephemerides, Radii, and Period Constraints from a Second Transit of V1298 Tau e

V1298 Tau is a young (20-30 Myr) solar-mass K star hosting four transiting exoplanets with sizes between 0.5 - 0.9 $R_J$. Given the system's youth, it provides a unique opportunity to understand the evolution of planetary radii at different separations in the same stellar environment. V1298 Tau was originally observed 6 years ago during K2 Campaign 4. Now, V1298 Tau has been re-observed during the extended mission of NASA's Transiting Exoplanet Survey Satellite (TESS). Here, we present new photometric observations of V1298 Tau from the 10-minute TESS Full-Frame Images. We use the TESS data to update the ephemerides for V1298 Tau bcde as well as compare newly observed radii to those measured from the K2 light curve, finding shallower transits for V1298 Tau bcd in the redder TESS bandpass at the $1-2σ$ level. We suspect the difference in radii is due to starspot-crossing events or contamination from nearby faint stars on the same pixels as V1298 Tau. Additionally, we catch a second transit of V1298 Tau e and present a new method for deriving the marginalized posterior probability of a planet's period from two transits observed years apart. We find the highest probability period for V1298 Tau e to be in a near 2:1 mean motion resonance with V1298 Tau b which, if confirmed, could make V1298 Tau bcde a 4 planet resonant chain. V1298 Tau is the target of several ongoing and future observations. These updated ephemerides will be crucial for scheduling future transit observations and interpreting future Doppler tomographic or transmission spectroscopy signals.

astro-ph.EP↗

arXiv2021

Mapping stellar surfaces III: An Efficient, Scalable, and Open-Source Doppler Imaging Model

The study of stellar surfaces can reveal information about the chemical composition, interior structure, and magnetic properties of stars. It is also critical to the detection and characterization of extrasolar planets, in particular those targeted in extreme precision radial velocity (EPRV) searches, which must contend with stellar variability that is often orders of magnitude stronger than the planetary signal. One of the most successful methods to map the surfaces of stars is Doppler imaging, in which the presence of inhomogeneities is inferred from subtle line shape changes in high resolution stellar spectra. In this paper, we present a novel, efficient, and closed-form solution to the problem of Doppler imaging of stellar surfaces. Our model explicitly allows for incomplete knowledge of the local (rest frame) stellar spectrum, allowing one to learn differences from spectral templates while simultaneously mapping the stellar surface. It therefore works on blended lines, regions of the spectrum where line formation mechanisms are not well understood, or stars whose spots have intrinsically different spectra from the rest of the photosphere. We implement the model within the open source starry framework, making it fast, differentiable, and easy to use in both optimization and posterior inference settings. As a proof-of-concept, we use our model to infer the surface map of the brown dwarf WISE 1049-5319B, finding close agreement with the solution of Crossfield et al. (2014). We also discuss Doppler imaging in the context of EPRV studies and describe an interpretable spectral-temporal Gaussian process for stellar spectral variability that we expect will be important for EPRV exoplanet searches.

astro-ph.SR↗

arXiv2021

HD 183579b: A Warm Sub-Neptune Transiting a Solar Twin Detected by TESS

We report the discovery and characterization of a transiting warm sub-Neptune planet around the nearby bright ($V=8.75$ mag, $K=7.15$ mag) solar twin HD 183579, delivered by the Transiting Exoplanet Survey Satellite (TESS). The host star is located $56.8\pm0.1$ pc away with a radius of $R_{\ast}=0.97\pm0.02\ R_{\odot}$ and a mass of $M_{\ast}=1.03\pm0.05\ M_{\odot}$. We confirm the planetary nature by combining space and ground-based photometry, spectroscopy, and imaging. We find that HD 183579b (TOI-1055b) has a radius of $R_{p}=3.53\pm0.13\ R_{\oplus}$ on a $17.47$ day orbit with a mass of $M_{p}=11.2\pm5.4\ M_{\oplus}$ ($3σ$ mass upper limit of $27.4\ M_{\oplus}$). HD 183579b is the fifth brightest known sub-Neptune planet system in the sky, making it an excellent target for future studies of the interior structure and atmospheric properties. By performing a line-by-line differential analysis using the high resolution and signal-to-noise ratio HARPS spectra, we find that HD 183579 joins the typical solar twin sample, without a statistically significant refractory element depletion.

astro-ph.EP↗

arXiv2021

TOI-1259Ab -- a gas giant planet with 2.7% deep transits and a bound white dwarf companion

We present TOI-1259Ab, a 1.0 Rjup gas giant planet transiting a 0.71 Rsun K-dwarf on a 3.48 day orbit. The system also contains a bound white dwarf companion TOI-1259B with a projected distance of approximately 1600 AU from the planet host. Transits are observed in nine TESS sector and are 2.7 per cent deep - among the deepest known - making TOI-1259Ab a promising target for atmospheric characterization. Our follow-up radial velocity measurements indicate a variability of semiamplitude K = 71 m/s, implying a planet mass of 0.44 Mjup. By fitting the spectral energy distribution of the white dwarf we derive a total age of 4.08 (+1.21 -0.53) Gyr for the system. The K-dwarf's light curve reveals a rotational variability with a period of 28 days, which implies a gyrochronology age broadly consistent with the white dwarf's total age.

astro-ph.EP↗

arXiv2021

exoplanet: Gradient-based probabilistic inference for exoplanet data & other astronomical time series

"exoplanet" is a toolkit for probabilistic modeling of astronomical time series data, with a focus on observations of exoplanets, using PyMC3 (Salvatier et al., 2016). PyMC3 is a flexible and high-performance model-building language and inference engine that scales well to problems with a large number of parameters. "exoplanet" extends PyMC3's modeling language to support many of the custom functions and probability distributions required when fitting exoplanet datasets or other astronomical time series. While it has been used for other applications, such as the study of stellar variability, the primary purpose of "exoplanet" is the characterization of exoplanets or multiple star systems using time-series photometry, astrometry, and/or radial velocity. In particular, the typical use case would be to use one or more of these datasets to place constraints on the physical and orbital parameters of the system, such as planet mass or orbital period, while simultaneously taking into account the effects of stellar variability.

astro-ph.IM↗