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Joshua S. Speagle

Publications and source records attributed to Joshua S. Speagle.

At least 37 records · Page 2Linked to original sources

A Deep, High-Angular Resolution 3D Dust Map of the Southern Galactic Plane

We present a deep, high-angular resolution 3D dust map of the southern Galactic plane over $239^\circ < \ell < 6^\circ$ and $|b| < 10^\circ$ built on photometry from the DECaPS2 survey, in combination with photometry from VVV, 2MASS, and unWISE and parallaxes from Gaia DR3 where available. To construct the map, we first infer the distance, extinction, and stellar types of over 700 million stars using the brutus stellar inference framework with a set of theoretical MIST stellar models. Our resultant 3D dust map has an angular resolution of $1'$, roughly an order of magnitude finer than existing 3D dust maps and comparable to the angular resolution of the Herschel 2D dust emission maps. We detect complexes at the range of distances associated with the Sagittarius-Carina and Scutum-Centaurus arms in the fourth quadrant, as well as more distant structures out to a maximum reliable distance of $d \approx$ 10 kpc from the Sun. The map is sensitive up to a maximum extinction of roughly $A_V \approx 12$ mag. We publicly release both the stellar catalog and the 3D dust map, the latter of which can easily be queried via the Python package dustmaps. When combined with the existing Bayestar19 3D dust map of the northern sky, the DECaPS 3D dust map fills in the missing piece of the Galactic plane, enabling extinction corrections over the entire disk $|b| < 10^\circ$. Our map serves as a pathfinder for the future of 3D dust mapping in the era of LSST and Roman, targeting regimes accessible with deep optical and near-infrared photometry but often inaccessible with Gaia.

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SF-R You Sure? The Conflicting Role of Star Formation Rates in Constraining the Evolution of Milky Way Analogues in Cosmological Simulations

Milky Way analogues (MWAs) have long been studied by astronomers to place our Galaxy within an extragalactic context. With the power of cosmological simulations, we are now able to not only characterize MWAs today, but also watch as they evolve through cosmic time. We use the EAGLE and IllustrisTNG simulations to study a group of MWAs defined by their stellar mass (SM) and star formation rate (SFR). We trace these galaxies back along their evolution to investigate the star forming and mass assembly tracks taken by a galaxy to become a MWA today in light of these chosen parameters. We also take mock-observations of "MWAs" at $z>0$ and trace them forwards in time to determine if galaxies that looked similar to the Milky Way earlier in their evolution still look like the Milky Way today, thus quantifying a selection efficiency which could inform future observational studies of MWAs. We find that most galaxies with Milky Way-SM follow a similar evolution regardless of present-day SFR, although MWAs in IllustrisTNG generally have not quenched, leading to star formation histories that produce "too-blue" galaxies today. Additionally, we find contamination by MWA-"imposters" in our mock-observations, with low selection efficiency at high redshift due to the tight constraint requiring convergence to the Milky Way's present-day SFR. Our work suggests present-day SM may suffice as a stand-alone selection parameter and helps to clarify how MWAs should be selected, and thus will be an important reference for future studies of both simulated and observed MWAs.

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MINERVA: A NIRCam Medium Band and MIRI Imaging Survey to Unlock the Hidden Gems of the Distant Universe

We present an overview of the MINERVA survey, a 259.8 hour (prime) and 127 hour (parallel) Cycle 4 treasury program on the James Webb Space Telescope (JWST). MINERVA is obtaining 8 filter NIRCam medium band imaging (F140M, F162M, F182M, F210M, F250M, F300M, F360M, F460M) and 2 filter MIRI imaging (F1280W, F1500W) in four of the five CANDELS Extragalactic fields: UDS, COSMOS, AEGIS and GOODS-N. These fields were previously observed in Cycle 1 with 7 - 9 NIRCam filters by the PRIMER, CEERS and JADES programs. MINERVA reaches a 5$σ$ depth of 28.1 mag in F300M and covers $\sim$ 542 arcmin$^2$, increasing the area of existing JWST medium-band coverage in at least 8 bands by $\sim$ 7$\times$. The MIRI imaging reaches a 5$σ$ depth of 23.9 mag in F1280W and covers $\sim$ 275 arcmin$^2$ in at least 2 MIRI filters. When combined with existing imaging, these data will provide a photometric catalog with 20-26 JWST filters (depending on field) and 26-35 filters total, including HST. This paper presents a detailed breakdown of the filter coverage, exposure times, and field layout relative to previous observations, as well as an overview of the primary science goals of the project. These include uncovering the physics of enigmatic sources hiding in current broadband catalogs, improving systematics on stellar mass functions and number densities by factors of $\gtrsim$ 3, and resolved mapping of stellar mass and star formation at 1 $< z <$ 6. When complete, MINERVA will become an integral part of the treasury deep field imaging datasets, significantly improving population studies with well-understood completeness, robust photometric redshifts, stellar masses, and sizes, and facilitating spectroscopic follow up for decades to come.

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ChronoFlow: A Data-Driven Model for Gyrochronology

Gyrochronology is a technique for constraining stellar ages using rotation periods, which change over a star's main sequence lifetime due to magnetic braking. This technique shows promise for main sequence FGKM stars, where other methods are imprecise. However, the observed dispersion in rotation rates for similar coeval stars has historically been difficult to characterize. To properly understand this complexity, we have assembled the largest standardized data catalog of rotators in open clusters to date, consisting of $\approx$8,000 stars across 30 open clusters/associations spanning ages of 1.5 Myr to 4 Gyr. We have also developed ChronoFlow: a flexible data-driven model which accurately captures observed rotational dispersion. We show that ChronoFlow can be used to accurately forward model rotational evolution, and to infer both cluster and individual stellar ages. We recover cluster ages with a statistical uncertainty of 0.06 dex ($\approx$15%), and individual stellar ages with a statistical uncertainty of 0.7 dex. Additionally, we conducted robust systematic tests to analyze the impact of extinction models, cluster membership, and calibration ages. These contribute an additional 0.06 dex of uncertainty in cluster age estimates, resulting in a total error budget of 0.08 dex. We apply ChronoFlow to estimate ages for M34, NGC 2516, NGC 6709, and the Theia 456 stellar stream. Our results show that ChronoFlow can precisely estimate the ages of coeval stellar populations, and constrain ages for individual stars. Furthermore, its predictions may be used to inform physical spin down models. ChronoFlow is publicly available at https://github.com/philvanlane/chronoflow.

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Measuring $σ_8$ using DESI Legacy Imaging Surveys Emission-Line Galaxies and Planck CMB Lensing and the Impact of Dust on Parameter Inference

Measuring the growth of structure is a powerful probe for studying the dark sector, especially in light of the $σ_8$ tension between primary CMB anisotropy and low-redshift surveys. This paper provides a new measurement of the amplitude of the matter power spectrum, $σ_8$, using galaxy-galaxy and galaxy-CMB lensing power spectra of Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Emission-Line Galaxies and the $\textit{Planck}$ 2018 CMB lensing map. We create an ELG catalog composed of $24$ million galaxies and with a purity of $85\%$, covering a redshift range $0 < z < 3$, with $z_{\rm mean} = 1.09$. We implement several novel systematic corrections, such as jointly modeling the contribution of imaging systematics and photometric redshift uncertainties to the covariance matrix. We also study the impacts of various dust maps on cosmological parameter inference. We measure the cross-power spectra over $f_{\rm sky} = 0.25$ with a signal-to-background ratio of up to $ 30σ$. We find that the choice of dust maps to account for imaging systematics in estimating the ELG overdensity field has a significant impact on the final estimated values of $σ_8$ and $Ω_{\rm M}$, with far-infrared emission-based dust maps preferring $σ_8$ to be as low as $0.702 \pm 0.030$, and stellar-reddening-based dust maps preferring as high as $0.719 \pm 0.030$. The highest preferred value is at $\sim 3 σ$ tension with the $\textit{Planck}$ primary anisotropy results. These findings indicate a need for tomographic analyses at high redshifts and joint modeling of systematics.

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Deriving Stellar Properties, Distances, and Reddenings using Photometry and Astrometry with BRUTUS

We present brutus, an open source Python package for quickly deriving stellar properties, distances, and reddenings to stars based on grids of stellar models constrained by photometric and astrometric data. We outline the statistical framework for deriving these quantities, its implementation, and various Galactic priors over the 3-D distribution of stars, stellar properties, and dust extinction (including $R_V$ variation). We establish a procedure to empirically calibrate MIST v1.2 isochrones by using open clusters to derive corrections to the effective temperatures and radii of the isochrones, which reduces systematic errors on the lower main sequence. We also describe and apply a method to estimate photometric offsets between stellar models and observed data using nearby, low-reddening field stars. We perform a series of tests on mock and real data to examine parameter recovery with MIST under different modeling assumptions, illustrating that brutus is able to recover distances and other stellar properties using optical to near-infrared photometry and astrometry. The code is publicly available at https://github.com/joshspeagle/brutus.

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Mapping the Milky Way in 5-D with 170 Million Stars

We present "augustus", a catalog of distance, extinction, and stellar parameter estimates to 170 million stars from $14\,{\rm mag} < r < 20\,{\rm mag}$ and with $|b| > 10^\circ$ drawing on a combination of optical to near-IR photometry from Pan-STARRS, 2MASS, UKIDSS, and unWISE along with parallax measurements from \textit{Gaia} DR2 and 3-D dust extinction maps. After applying quality cuts, we find 125 million objects have "high-quality" posteriors with statistical distance uncertainties of $\lesssim 10\%$ for objects with well-constrained stellar types. This is a substantial improvement over distance estimates derived from Gaia parallaxes alone and in line with results from previous work. We find the fits are able to accurately reproduce the de-reddened Gaia color-magnitude diagram, which serves as a useful consistency check of our results. We show that we are able to clearly detect large, kinematically-coherent substructures in our data relative to the input priors, including the Monoceros Ring and the Sagittarius stream, attesting to the quality of the catalog. Our results are publicly available at doi:10.7910/DVN/WYMSXV. An accompanying interactive visualization can be found at http://allsky.s3-website.us-east-2.amazonaws.com.

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SPYGLASS. VI. Feedback-Driven Star Formation in the Circinus Complex

Young associations provide a record that traces the star formation process, and the youngest populations connect progenitor gas dynamics to the resulting stellar populations. We therefore conduct the first comprehensive overview of the Circinus Complex, an under-studied and massive ($\sim$1500 M$_{\odot}$) region consisting of approximately 3100 recently formed stars alongside the Circinus Molecular Cloud (CMC). We find a clear age pattern in the contiguous central region (CirCe), where younger stars are found further from the massive central cluster, and where the velocities are consistent with uniform expansion. By comparing this structure to an analogous STARFORGE simulation, we find that the age structure and dynamics of the association are consistent with star formation in two stages: the global collapse of the parent cloud that builds the $500 M_{\odot}$ central cluster ASCC 79, followed by triggered star formation in a shell swept up after the first massive stars form. We also find that filaments with a range of distances from the central cluster can naturally produce multi-generational age sequences due to differences in feedback strength and exposure. Outlying populations show velocities consistent with formation independent from the CirCe region, but with similar enough velocities that they may be difficult to distinguish from one another later in their expansion. We therefore provide a new alternative view of sequential star formation that relies on feedback from a single central cluster rather than the multiple sequential generations that are traditionally invoked, while also providing insight into the star formation history of older populations.

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Closing the stellar labels gap: Stellar label independent evidence for [$α/M$] information in Gaia BP/RP spectra

Data-driven models for stellar spectra which depend on stellar labels suffer from label systematics which decrease model performance: the "stellar labels gap". To close the stellar labels gap, we present a stellar label independent model for Gaia BP/RP spectra. We develop a novel implementation of a variational auto-encoder, which learns to generate an XP spectrum and accompanying 'scatter' without relying on stellar labels. We demonstrate that our model achieves competitive XP spectra reconstructions in comparison to stellar label dependent models. We find that our model learns stellar properties directly from the data itself. We then apply our model to XP/APOGEE giant stars to study the [$α$/M] information in Gaia XP. We provide strong evidence that the XP spectra contain meaningful [$α$/M] information by demonstrating that our model learns the $α$-bimodality, without relying on stellar label correlations for stars with $T_{\rm eff} <$ 5000 K, while also being sensitive to the anomalous abundances of Gaia-Enceladus stars. We publicly release our trained model, codebase and data. Importantly, our stellar label independent model can be implemented for any/all XP spectra because our model performance scales with training object density, not training label density.

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The first catalog of candidate white dwarf-main sequence binaries in open star clusters: A new window into common envelope evolution

Close binary systems are the progenitors to both Type Ia supernovae and the compact object mergers that can be detected via gravitational waves. To achieve a binary with a small radial separation, it is believed that the system likely undergoes common envelope (CE) evolution. Despite its importance, CE evolution may be one of the largest uncertainties in binary evolution due to a combination of computational challenges and a lack of observed benchmarks where both the post-CE and pre-CE conditions are known. Identifying post-CE systems in star clusters can partially circumvent this second issue by providing an independent age constraint on the system. For the first time, we conduct a systematic search for white dwarf (WD) and main-sequence (MS) binary systems in 299 Milky Way open star clusters. Coupling Gaia DR3 photometry and kinematics with multi-band photometry from Pan-STARRS1 and 2MASS, we apply a machine learning based approach and find 52 high-probability candidates in 38 open clusters. For a subset of our systems, we present follow-up spectroscopy from the Gemini and Lick Observatories and archival light curves from TESS, Kepler/K2 and the Zwicky Transient Facility. Examples of M-dwarfs with hot companions are spectroscopically observed, along with regular system variability. While the kinematics of our candidates are consistent with their host clusters, some systems have spatial positions offset relative to their hosts, potentially indicative of natal kicks. Ultimately, this catalogue is a first step to obtaining a set of observational benchmarks to better link post-CE systems to their pre-CE progenitors.

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Birth of the Galactic Disk Revealed by the H3 Survey

We use chemistry ([alpha/Fe] and [Fe/H]), main sequence turnoff ages, and kinematics determined from H3 Survey spectroscopy and Gaia astrometry to identify the birth of the Galactic disk. We separate in-situ and accreted stars on the basis of angular momenta and eccentricities. The sequence of high-alpha in-situ stars persists down to at least [Fe/H]=-2.5 and shows unexpected non-monotonic behavior: with increasing metallicity the population first declines in [alpha/Fe], then increases over the range -1.3<[Fe/H]<-0.7, and then declines again at higher metallicities. The number of stars in the in-situ population rapidly increases above [Fe/H]=-1. The average kinematics of these stars are hot and independent of metallicity at [Fe/H]<-1 and then become increasingly cold and disk-like at higher metallicities. The ages of the in-situ, high-alpha stars are uniformly very old (13 Gyr) at [Fe/H]<-1.3, and span a wider range (8-12 Gyr) at higher metallicities. Interpreting the chemistry with a simple chemical evolution model suggests that the non-monotonic behavior is due to a significant increase in star formation efficiency, which began 13 Gyr ago. These results support a picture in which the first 1 Gyr of the Galaxy was characterized by a "simmering phase" in which the star formation efficiency was low and the kinematics had substantial disorder with some net rotation. The disk then underwent a dramatic transformation to a "boiling phase", in which the star formation efficiency increased substantially, the kinematics became disk-like, and the number of stars formed increased tenfold. We interpret this transformation as the birth of the Galactic disk at z~4. The physical origin of this transformation is unclear and does not seem to be reproduced in current galaxy formation models.

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Estimating Probability Densities with Transformer and Denoising Diffusion

Transformers are often the go-to architecture to build foundation models that ingest a large amount of training data. But these models do not estimate the probability density distribution when trained on regression problems, yet obtaining full probabilistic outputs is crucial to many fields of science, where the probability distribution of the answer can be non-Gaussian and multimodal. In this work, we demonstrate that training a probabilistic model using a denoising diffusion head on top of the Transformer provides reasonable probability density estimation even for high-dimensional inputs. The combined Transformer+Denoising Diffusion model allows conditioning the output probability density on arbitrary combinations of inputs and it is thus a highly flexible density function emulator of all possible input/output combinations. We illustrate our Transformer+Denoising Diffusion model by training it on a large dataset of astronomical observations and measured labels of stars within our Galaxy and we apply it to a variety of inference tasks to show that the model can infer labels accurately with reasonable distributions.

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Should zeros count? Modeling the galaxy-globular cluster scaling relation with(out) zero-inflated count models

The scaling relation between the size of a galaxy's globular cluster (GC) population ($N_{GC}$) and the galaxy's stellar mass ($M_*$) is usually described with a continuous, linear model, but in reality it is a count relationship that should be modeled as such. For massive galaxies, a negative binomial (NB) model has been shown to describe the data well, but it is unclear how the scaling relation behaves at low galaxy masses where a substantial portion of galaxies have $N_{GC}=0$. In this work, we test the utility of Poisson and NB models for describing the low-mass end of the $N_{GC}-M_*$ scaling relation. We introduce the use of zero-inflated versions of these models, which allow for larger zero populations (e.g. galaxies without GCs) than would otherwise be predicted. We evaluate our models with a variety of predictive model comparison methods, including predictive intervals, leave-one-out cross-validation criterion, and posterior predictive comparisons. We find that the NB model is consistent with our data, but the naive Poisson is not. Moreover, we find that zero inflation of the models is not necessary to describe the population of low-mass galaxies that lack GCs, suggesting that a single formation and evolutionary process acts over all galaxy masses. Under the NB model, there does not appear to be anything unique about the lack of GCs in many low-mass galaxies; they are simply the low-mass extension of the larger $N_{GC}-M_*$ scaling relation.

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Photometric Completeness Modelled With Neural Networks

In almost any study involving optical/NIR photometry, understanding the completeness of detection and recovery is an essential part of the work. The recovery fraction is, in general, a function of several variables including magnitude, color, background sky noise, and crowding. We explore how completeness can be modelled, {with the use of artificial-star tests,} in a way that includes all of these parameters \emph{simultaneously} within a neural network (NN) framework. The method is able to manage common issues including asymmetric completeness functions and the bilinear dependence of the detection limit on color index. We test the method with two sample HST (Hubble Space Telescope) datasets: the first involves photometry of the star cluster population around the giant Perseus galaxy NGC 1275, and the second involves the halo-star population in the nearby elliptical galaxy NGC 3377. The NN-based method achieves a classification accuracy of $>$\,94\%, and produces results entirely consistent with more traditional techniques for determining completeness. Additional advantages of the method are that none of the issues arising from binning of the data are present, and that a recovery probability can be assigned to every individual star in the real photometry. Our data, models, and code (called COINTOSS) can be found online on Zenodo at the following link: https://doi.org/10.5281/zenodo.8306488.

astro-ph.IM↗

Improving Power Spectrum Estimation using Multitapering: Efficient asteroseismic analyses for understanding stars, the Milky Way, and beyond

Asteroseismic time-series data have imprints of stellar oscillation modes, whose detection and characterization through time-series analysis allows us to probe stellar interior physics. Such analyses usually occur in the Fourier domain by computing the Lomb-Scargle (LS) periodogram, an estimator of the power spectrum underlying unevenly-sampled time-series data. However, the LS periodogram suffers from the statistical problems of (1) inconsistency (or noise) and (2) bias due to high spectral leakage. Here, we develop a multitaper power spectrum estimator using the Non-Uniform Fast Fourier Transform (mtNUFFT) to tackle the inconsistency and bias problems of the LS periodogram. Using a simulated light curve, we show that the mtNUFFT power spectrum estimate of solar-like oscillations has lower variance and bias than the LS estimate. We also apply our method to the Kepler-91 red giant, and combine it with PBjam peakbagging to obtain mode parameters and a derived age estimate of $3.97 \pm 0.52$ Gyr. PBjam allows the improvement of age precision relative to the $4.27 \pm 0.75$ Gyr APOKASC-2 (uncorrected) estimate, whereas partnering mtNUFFT with PBjam speeds up peakbagging thrice as much as LS. This increase in efficiency has promising implications for Galactic archaeology, in addition to stellar structure and evolution studies. Our new method generally applies to time-domain astronomy and is implemented in the public Python package tapify, available at https://github.com/aaryapatil/tapify.

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Improving Harmonic Analysis using Multitapering: Precise frequency estimation of stellar oscillations using the harmonic F-test

In Patil et. al 2024a, we developed a multitaper power spectrum estimation method, mtNUFFT, for analyzing time-series with quasi-regular spacing, and showed that it not only improves upon the statistical issues of the Lomb-Scargle periodogram, but also provides a factor of three speed up in some applications. In this paper, we combine mtNUFFT with the harmonic F-test to test the hypothesis that a strictly periodic signal or its harmonic (as opposed to e.g. a quasi-periodic signal) is present at a given frequency. This mtNUFFT/F-test combination shows that multitapering allows detection of periodic signals and precise estimation of their frequencies, thereby improving both power spectrum estimation and harmonic analysis. Using asteroseismic time-series data for the Kepler-91 red giant, we show that the F-test automatically picks up the harmonics of its transiting exoplanet as well as certain dipole ($l=1$) mixed modes. We use this example to highlight that we can distinguish between different types of stellar oscillations, e.g., transient (damped, stochastically-excited) and strictly periodic (undamped, heat-driven). We also illustrate the technique of dividing a time-series into chunks to further examine the transient versus periodic nature of stellar oscillations. The harmonic F-test combined with mtNUFFT is implemented in the public Python package tapify (https://github.com/aaryapatil/tapify), which opens opportunities to perform detailed investigations of periodic signals in time-domain astronomy.

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The FENIKS Survey: Spectroscopic Confirmation of Massive Quiescent Galaxies at z ~ 3-5

The measured ages of massive, quiescent galaxies at $z\sim 3-4$ imply that massive galaxies quench as early as $z\sim 6$. While the number of spectroscopic confirmations of quiescent galaxies at $z < 3$ has increased over the years, there are only a handful at $z > 3.5$. We report spectroscopic redshifts of one secure ($z=3.757$) and two tentative ($z = 3.336$, $z=4.673$) massive ($\log(M_\ast/M_\odot) > 10.3$) quiescent galaxies with 11 hours of Keck/MOSFIRE $K$-band observations. Our candidates were selected from the FENIKS survey, which uses deep Gemini/Flamingos-2 $K_b$ $K_r$ imaging optimized for increased sensitivity to the characteristic red colors of galaxies at $z > 3$ with strong Balmer/4000 Å breaks. The rest-frame $UVJ$ and $(ugi)_s$ colors of 3/4 quiescent candidates are consistent with $1-2$ Gyr old stellar populations. This places these galaxies as the oldest objects at these redshifts, and challenges the notion that quiescent galaxies at $z > 3$ are all recently-quenched, "post-starburst" galaxies. Our spectroscopy shows that the other quiescent-galaxy candidate is a broad-line AGN ($z = 3.594$) with strong, redshifted $Hβ$+[O III] emission with a velocity offset $>1000$ km/s, indicative of a powerful outflow. The star-formation history of our highest redshift candidate suggests that its progenitor was already in place by $z \sim 7-11$, reaching $\sim$ 10$^{11} M_{\odot}$ by $z \simeq 8$. These observations reveal the limit of what is possible with deep near-infrared photometry and targeted spectroscopy from the ground and demonstrate that secure spectroscopic confirmation of quiescent galaxies at $z > 4$ is only feasible with JWST.

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Stochastic prior for non-parametric star-formation histories

The amount of power contained in the variations in galaxy star-formation histories (SFHs) across a range of timescales encodes key information about the physical processes which modulate star formation. Modelling the SFHs of galaxies as stochastic processes allows the relative importance of different timescales to be quantified via the power spectral density (PSD). In this paper, we build upon the PSD framework and develop a physically-motivated, "stochastic" prior for non-parametric SFHs in the spectral energy distribution (SED)-modelling code Prospector. We test this prior in two different regimes: 1) massive, $z = 0.7$ galaxies with both photometry and spectra, analogous to those observed with the LEGA-C survey, and 2) $z = 8$ galaxies with photometry only, analogous to those observed with NIRCam on JWST. We find that it is able to recover key galaxy parameters (e.g. stellar mass, stellar metallicity) to the same level of fidelity as the commonly-used continuity prior. Furthermore, the realistic variability information incorporated by the stochastic SFH model allows it to fit the SFHs of galaxies more accurately and precisely than traditional non-parametric models. In fact, the stochastic prior is $\gtrsim 2\times$ more accurate than the continuity prior in measuring the recent star-formation rates (log SFR$_{100}$ and log SFR$_{10}$) of both the $z = 0.7$ and $z = 8$ mock systems. While the PSD parameters of individual galaxies are difficult to constrain, the stochastic prior implementation presented in this work allows for the development hierarchical models in the future, i.e. simultaneous SED-modelling of an ensemble of galaxies to measure their underlying PSD.

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