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We present a new empirical framework modeling the metallicity and star formation history (SFH) dependence of X-ray luminous ( L ≳ 10 ^36 erg s ^−1 ) point-source population X-ray luminosity functions (XLFs) in normal galaxies. We expect that the X-ray point-source populations are dominated by X-ray binaries (XRBs), with contributions from supernova remnants near the low luminosity end of our observations. Our framework is calibrated using the collective statistical power of 3731 X-ray detected point sources within 88 Chandra-observed galaxies at D ≲ 40 Mpc that span broad ranges of metallicity ( Z ≈ 0.03–2 Z _⊙ ), SFH, and morphology (dwarf irregulars, late types, and early types). Our best-fitting models indicate that the XLF normalization per unit stellar mass declines by ≈2–3 dex from 10 Myr to 10 Gyr, with a slower age decline for low-metallicity populations. The shape of the XLF for luminous X-ray sources ( L ≳ 10 ^38 erg s ^−1 ) significantly steepens with increasing age and metallicity, while the lower-luminosity XLF appears to flatten with increasing age. Integration of our models provides predictions for X-ray scaling relations that agree very well with past results presented in the literature, including, e.g., the L _X –SFR– Z relation for high-mass XRBs in young stellar populations as well as the L _X / M _⋆ ratio observed in early-type galaxies that harbor old populations of low-mass XRBs. The model framework and data sets presented in this paper further provide unique benchmarks that can be used for calibrating binary population synthesis models.

We present an updated version of Lightning , a galaxy spectral energy distribution (SED) fitting code that can model X-ray to submillimeter observations. The models in Lightning include the options to contain contributions from stellar populations, dust attenuation and emission, and active galactic nuclei (AGNs). X-ray emission, when utilized, can be modeled as originating from stellar compact binary populations with the option to include emission from AGNs. We have also included a variety of algorithms to fit the models to observations and sample parameter posteriors; these include adaptive Markov Chain Monte Carlo (MCMC), affine-invariant MCMC, and Levenberg–Marquardt gradient-descent ( MPFIT ) algorithms. To demonstrate some of the capabilities of Lightning , we present several examples using a variety of observational data. These examples include (1) deriving the spatially resolved stellar properties of the nearby galaxy M81, (2) demonstrating how X-ray emission can provide constraints on the properties of the supermassive black hole of a distant AGN, (3) exploring how to rectify the attenuation effects of inclination on the derived the star formation rate of the edge-on galaxy NGC 4631, (4) comparing the performance of Lightning to similar Bayesian SED-fitting codes when deriving physical properties of the star-forming galaxy NGC 628, and (5) comparing the derived X-ray and UV-to-IR AGN properties from Lightning and CIGALE for a distant AGN. Lightning is an open-source application developed in IDL and is available at https://github.com/rafaeleufrasio/lightning .

We analyze the physical properties of eight X-ray-selected active galactic nuclei (AGNs) and one candidate protoquasar system (ADF22A1) in the z = 3.09 SSA22 protocluster by fitting their X-ray-to-IR spectral energy distributions (SEDs) using our SED-fitting code, Lightning ( https://www.github.com/rafaeleufrasio/lightning ). We recover star formation histories (SFHs) for seven of these systems which are well fit by composite stellar population plus AGN models. We find indications that four out of nine of the SSA22 AGN systems we study have host galaxies below the main sequence, with SFR/SFR _MS ≤ −0.4. The remaining SSA22 systems, including ADF22A1, are consistent with obscured supermassive black hole (SMBH) growth in star-forming galaxies. We estimate the SMBH accretion rates and masses, and compare the properties and SFHs of the nine protocluster AGN systems with X-ray-detected AGN candidates in the Chandra Deep Fields (CDF), finding that the distributions of SMBH growth rates, star formation rates (SFRs), SMBH masses, and stellar masses for the protocluster AGNs are consistent with field AGNs. We constrain the ratio between the sample-averaged SSA22 SMBH mass and CDF SMBH mass to