Exploring Photometric Redshifts as an Optimization Problem: An Ensemble MCMC and Simulated Annealing-Driven Template-Fitting Approach

Using a grid of $\sim 2$ million elements ($\Delta z = 0.005$) adapted from COSMOS photometric redshift (photo-z) searches, we investigate the general properties of template-based photo-z likelihood surfaces. We find these surfaces are filled with numerous local minima and large degeneracies that generally confound rapid but "greedy" optimization schemes, even with additional stochastic sampling methods. In order to robustly and efficiently explore these surfaces, we develop BAD-Z [Brisk Annealing-Driven Redshifts (Z)], which combines ensemble Markov Chain Monte Carlo (MCMC) sampling with simulated annealing to sample arbitrarily large, pre-generated grids in approximately constant time. Using a mock catalog of 384,662 objects, we show BAD-Z samples $\sim 40$ times more efficiently compared to a brute-force counterpart while maintaining similar levels of accuracy. Our results represent first steps toward designing template-fitting photo-z approaches limited mainly by memory constraints rather than computation time.Comment: 14 pages, 8 figures; submitted to MNRAS; comments welcom

Hierarchical Bayesian Inference of Globular Cluster Properties

We present a hierarchical Bayesian inference approach to estimating the structural properties and the phase space center of a globular cluster (GC) given the spatial and kinematic information of its stars based on lowered isothermal cluster models. As a first step towards more realistic modelling of GCs, we built a differentiable, accurate emulator of the lowered isothermal distribution function using interpolation. The reliable gradient information provided by the emulator allows the use of Hamiltonian Monte Carlo methods to sample large Bayesian models with hundreds of parameters, thereby enabling inference on hierarchical models. We explore the use of hierarchical Bayesian modelling to address several issues encountered in observations of GC including an unknown GC center, incomplete data, and measurement errors. Our approach not only avoids the common technique of radial binning but also incorporates the aforementioned uncertainties in a robust and statistically consistent way. Through demonstrating the reliability of our hierarchical Bayesian model on simulations, our work lays out the foundation for more realistic and complex modelling of real GC data.Comment: 16 pages, 12 figures, and 2 table

Improving Power Spectral Estimation using Multitapering: Precise asteroseismic modeling of stars, exoplanets, 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 interiors physics. Such analyses usually occur in the Fourier domain by computing the Lomb-Scargle (LS) periodogram, an estimator of the \textit{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. In addition, it is designed to detect strictly periodic signals but is unsuitable for non-sinusoidal periodic or quasi-periodic signals. Here, we develop a multitaper spectral estimation method that tackles the inconsistency and bias problems of the LS periodogram. We combine this multitaper method with the Non-Uniform Fast Fourier Transform (\texttt{mtNUFFT}) to more precisely estimate the frequencies of asteroseismic signals that are non-sinusoidal periodic (e.g., exoplanet transits) or quasi-periodic (e.g., pressure modes). We illustrate this using a simulated and the Kepler-91 red giant light curve. Particularly, we detect the Kepler-91b exoplanet and precisely estimate its period, $6.246 \pm 0.002$ days, in the frequency domain using the multitaper F-test alone. We also integrate \texttt{mtNUFFT} into the \texttt{PBjam} package to obtain a Kepler-91 age estimate of $3.96 \pm 0.48$ Gyr. This $36$\% improvement in age precision relative to the $4.27 \pm 0.75$ Gyr APOKASC-2 (uncorrected) estimate illustrates that \texttt{mtNUFFT} has promising implications for Galactic archaeology, in addition to stellar interiors and exoplanet studies. Our frequency analysis method generally applies to time-domain astronomy and is implemented in the public Python package \texttt{tapify}, available at \url{https://github.com/aaryapatil/tapify}.Comment: 32 pages (3 pages in the Appendix), 14 figures, 2 tables, Submitted to A

Searching for the extra-tidal stars of globular clusters using high-dimensional analysis and a core particle spray code

Three-body interactions can eject stars from the core of a globular cluster, causing them to enter the Galactic halo as extra-tidal stars. While finding extra-tidal stars is imperative for understanding cluster evolution, connecting isolated extra-tidal field stars back to their birth cluster is extremely difficult. In this work, we present a new methodology consisting of high-dimensional data analysis and a particle spray code to identify extra-tidal stars of any Galactic globular cluster using M3 as a case study. Using the t-Stochastic Neighbour Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) machine learning dimensionality reduction algorithms, we first identify a set of 103 extra-tidal candidates in the APOGEE DR17 data catalogue with chemical abundances similar to M3 stars. To confirm each candidate's extra-tidal nature, we introduce Corespray; a new Python-based three-body particle spray code that simulates extra-tidal stars for any Galactic globular cluster. Using Gaia EDR3 proper motions and APOGEE DR17 radial velocities, we apply multivariate Gaussian modelling and an extreme deconvolution to identify the extra-tidal candidates that are more likely to be associated with a distribution of Corespray-simulated M3 extra-tidal stars than the field. Through these methods, we identify 13 new high-probability extra-tidal stars of M3. Future applications of Corespray will yield better understandings of core dynamics, star formation histories and binary fractions in globular clusters.Comment: 15 pages, 8 figures, 2 tables. Submitted to Monthly Notices of the Royal Astronomical Societ

Source Selection for Cluster Weak Lensing Measurements in the Hyper Suprime-Cam Survey

We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP survey will uncover thousands of galaxy clusters to $z\lesssim1.5$. In deriving cluster masses via WL, a critical source of systematics is contamination and dilution of the lensing signal by cluster {members, and by foreground galaxies whose photometric redshifts are biased}. Using the first-year CAMIRA catalog of $\sim$900 clusters with richness larger than 20 found in $\sim$140 deg$^2$ of HSC-SSP data, we devise and compare several source selection methods, including selection in color-color space (CC-cut), and selection of robust photometric redshifts by applying constraints on their cumulative probability distribution function (PDF; P-cut). We examine the dependence of the contamination on the chosen limits adopted for each method. Using the proper limits, these methods give mass profiles with minimal dilution in agreement with one another. We find that not adopting either the CC-cut or P-cut methods results in an underestimation of the total cluster mass ($13\pm4\%$) and the concentration of the profile ($24\pm11\%$). The level of cluster contamination can reach as high as $\sim10\%$ at $R\approx 0.24$ Mpc/$h$ for low-z clusters without cuts, while employing either the P-cut or CC-cut results in cluster contamination consistent with zero to within the 0.5% uncertainties. Our robust methods yield a $\sim60\sigma$ detection of the stacked CAMIRA surface mass density profile, with a mean mass of $M_\mathrm{200c} = (1.67\pm0.05({\rm {stat}}))\times 10^{14}\,M_\odot/h$.Comment: 19 pages, 4 tables, 12 figures, accepted to PASJ special issu

Star Formation at 4<z<64 < z < 6 From the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH)

Using the first 50% of data collected for the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH) observations on the 1.8 deg$^2$ Cosmological Evolution Survey (COSMOS) we estimate the masses and star formation rates of 3398 $M_*>10^{10}M_\odot$ star-forming galaxies at $4 < z < 6$ with a substantial population up to $M_* \gtrsim 10^{11.5} M_\odot$. We find that the strong correlation between stellar mass and star formation rate seen at lower redshift (the "main sequence" of star-forming galaxies) extends to $z\sim6$. The observed relation and scatter is consistent with a continued increase in star formation rate at fixed mass in line with extrapolations from lower-redshift observations. It is difficult to explain this continued correlation, especially for the most massive systems, unless the most massive galaxies are forming stars near their Eddington-limited rate from their first collapse. Furthermore, we find no evidence for moderate quenching at higher masses, indicating quenching either has not occurred prior to $z \sim 6$ or else occurs rapidly, so that few galaxies are visible in transition between star-forming and quenched.Comment: ApJL, accepte