Estimating Spectra from Photometry

Kalmbach, J. Bryce; Connolly, Andrew J.

doi:10.3847/1538-3881/aa9933

Cited by 9 publications

(7 citation statements)

References 24 publications

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“…Some background knowledge of PCA and neural networks is assumed in this section; see e.g., Bishop (2006) for a comprehensive and pedagogical review. For previous work on representing spectra as interpolations over PCA bases, see Han & Han (2014), Czekala et al (2015), and Kalmbach & Connolly (2017).…”

Section: Speculator: Emulating Spsmentioning

confidence: 99%

SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry

Alsing

Peiris

Leja

et al. 2020

ApJS

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We present SPECULATOR-a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry. For emulating spectra, we use a principal component analysis to construct a set of basis functions and neural networks to learn the basis coefficients as a function of the SPS model parameters. For photometry, we parameterize the magnitudes (for the filters of interest) as a function of SPS parameters by a neural network. The resulting emulators are able to predict spectra and photometry under both simple and complicated SPS model parameterizations to percent-level accuracy, giving a factor of 10 3-10 4 speedup over direct SPS computation. They have readily computable derivatives, making them amenable to gradient-based inference and optimization methods. The emulators are also straightforward to call from a GPU, giving an additional order of magnitude speedup. Rapid SPS computations delivered by emulation offers a massive reduction in the computational resources required to infer the physical properties of galaxies from observed spectra or photometry and simulate galaxy populations under SPS models, while maintaining the accuracy required for a range of applications.

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Section: Speculator: Emulating Spsmentioning

confidence: 99%

SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry

Alsing

Peiris

Leja

et al. 2020

ApJS

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“…To construct a template set we begin with the empirical SED catalog of Brown et al (2014). We then use the ESP software package (Kalmbach & Connolly 2017), which constructs a principal component basis set from the empirical SEDs and uses photometric training data to construct the final SED template via Gaussian Processes. The final training set used by BPZ consists of the 129 empirical templates and 100 additional templates output from ESP.…”

Section: Template Fitting Redshiftsmentioning

confidence: 99%

A Composite Likelihood Approach for Inference under Photometric Redshift Uncertainty

Rau,

Morrison,

Schmidt

et al. 2021

Preprint

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Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We combine the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the Cos-moDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1 + 𝑧), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.

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“…PCA has been widely used in the literature in closely related contexts, such as spectral classification of galaxies (Connolly et al 1995) and quasars (Yip et al 2004), stellar mass estimation (Chen et al 2012), K-corrections (Blanton & Roweis 2007), and inferring spectra from optical imaging (Kalmbach & Connolly 2017). In this work, the application of PCA to galaxy colours is motivated by the obvious correlation between broad-band colours shown in Fig.…”

Section: Influence Of Sfh On Broad-band Coloursmentioning

confidence: 99%

“…We then carry out a Principal Component Analysis (PCA) of these colours to study how physically motivated SFH variations, as well as changes in other galaxy properties, manifest in observations of broad-band optical and near-infrared colours. PCA has been widely used in the literature in closely related contexts, such as spectral classification of galaxies (Connolly et al 1995) and quasars (Yip et al 2004), stellar mass estimation (Chen et al 2012), K-corrections (Blanton & Roweis 2007), and inferring spectra from optical imaging (Kalmbach & Connolly 2017). Finally, we seek to determine the galaxy properties with the strongest influence on galaxy colours by carrying out a PCA on the colours of a volume-limited sample of galaxies from the Sloan Digital Sky Survey (SDSS, York et al 2000;Dawson et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Surrogate modelling the Baryonic Universe I: The colour of star formation

Chaves-Montero,

Hearin

2019

Preprint

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The spectral energy distribution of a galaxy emerges from the complex interplay of many physical ingredients, including its star formation history (SFH), metallicity evolution, and dust properties. Using galaxpy, a new stellar population synthesis model, and SFHs predicted by the empirical model universemachine and the cosmological hydrodynamical simulation IllustrisTNG, we isolate the influence of SFH on broadband colours at z = 0. By carrying out a principal component analysis, we show that physically-motivated SFH variations modify broad-band colours along a single direction in colour space: the SFH-direction. We find that the projection of a galaxy's present-day colours onto the SFH-direction is almost completely regulated by the fraction of stellar mass that the galaxy formed over the last billion years. Together with cosmic downsizing, this results in galaxies becoming redder as their host halo mass increases. We additionally study the change in galaxy colours due to variations in metallicity, dust attenuation, and nebular emission lines, finding that these properties vary broad-band colours along distinct directions in colour space relative to the SFH-direction. Finally, we show that the colours of low-redshift SDSS galaxies span an ellipsoid with significant extent along two independent dimensions, and that the SFHdirection is well-aligned with the major axis of this ellipsoid. Our analysis supports the conclusion that variations in star formation history are the dominant influence on present-day galaxy colours, and that the nature of this influence is strikingly simple.

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Estimating Spectra from Photometry

Cited by 9 publications

References 24 publications

SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry

SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry

A Composite Likelihood Approach for Inference under Photometric Redshift Uncertainty

Surrogate modelling the Baryonic Universe I: The colour of star formation

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