arXiv subjects

David Rubin

Publications and source records attributed to David Rubin.

At least 55 records · Page 3Linked to original sources

arXiv2020

Evaluating K bands for Nancy Grace Roman Space Telescope Rest-Frame NIR SN Ia Distances

Recently, the Nancy Grace Roman Space Telescope (Roman) Project raised the possibility of adding another filter to Roman. Based on the Filter Working Group's recommendations, this filter may be a K-band filter, extending significantly redder than the current-reddest F184. Among other scientific possibilities, this K filter raises the possibility of measuring SNe Ia in the rest-frame NIR out to higher redshifts than is possible with the current filter complement. I perform a simple survey optimization for NIR SN Ia distances with Roman, simultaneously optimizing both filter cutoffs and survey strategy. I find that the roughly optimal K band extends from 19,000A--23,000A (giving exposure times roughly half that of a 20,000A--23,000A Ks filter). Moving the K much redder than this range dramatically increases the thermal background, while moving the K band much bluer limits the redshift reach. Thus I find any large modification reduces or eliminates the gain over the current F184. I consider both rest-frame Y band and rest-frame J band surveys. Although the proposed K band is too expensive for a large rest-frame Y band survey, it increases the rest-frame J Figure of Merit by 59%.

astro-ph.CO↗

arXiv2020

Evaluating the Calibration of SN Ia Anchor Datasets with a Bayesian Hierarchical Model

Inter-survey calibration remains an important systematic uncertainty in cosmological studies using type Ia supernova (SNe Ia). Ideally, each survey would measure its system throughputs, for instance with bandpass measurements combined with observations of well-characterized spectrophotometric standard stars; however, many important nearby-SN surveys have not done this. We recalibrate these surveys by tying their tertiary survey stars to Pan-STARRS1 g, r, and i, and SDSS/CSP u. This improves upon previous recalibration efforts by taking the spatially variable zeropoints of each telescope/camera into account, and applying improved color transformations in the surveys' natural instrumental photometric systems. Our analysis uses a global hierarchical model of the data which produces a covariance matrix of magnitude offsets and bandpass shifts, quantifying and reducing the systematic uncertainties in the calibration. We call our method CROSS-CALIBration with a Uniform Reanalysis (X-CALIBUR). This approach gains not only from a sophisticated analysis, but also from simply tying our calibration to more color calibrators, rather than just the one color calibrator (BD+17 4708) as many previous efforts have done. The results presented here have the potential to help understand and improve calibration uncertainties upcoming SN Ia cosmological analyses.

astro-ph.SR↗

arXiv2020

SN2019dge: a Helium-rich Ultra-Stripped Envelope Supernova

We present observations of ZTF18abfcmjw (SN2019dge), a helium-rich supernova with a fast-evolving light curve indicating an extremely low ejecta mass ($\approx 0.3\,M_\odot$) and low kinetic energy ($\approx 1.2\times 10^{50}\,{\rm erg}$). Early-time (<4 d after explosion) photometry reveal evidence of shock cooling from an extended helium-rich envelope of $\sim0.1\,M_\odot$ located at $\sim 3\times 10^{12}\,{\rm cm}$ from the progenitor. Early-time He II line emission and subsequent spectra show signatures of interaction with helium-rich circumstellar material, which extends from $\gtrsim 5\times 10^{13}\,{\rm cm}$ to $\gtrsim 2\times 10^{16}\,{\rm cm}$. We interpret SN2019dge as a helium-rich supernova from an ultra-stripped progenitor, which originates from a close binary system consisting of a mass-losing helium star and a low-mass main sequence star or a compact object (i.e., a white dwarf, a neutron star, or a black hole). We infer that the local volumetric birth rate of 19dge-like ultra-stripped SNe is in the range of 1400--8200$\,{\rm Gpc^{-3}\, yr^{-1}}$ (i.e., 2--12% of core-collapse supernova rate). This can be compared to the observed coalescence rate of compact neutron star binaries that are not formed by dynamical capture.

astro-ph.HE↗

arXiv2020

Is the expansion of the universe accelerating? All signs still point to yes a local dipole anisotropy cannot explain dark energy

Type Ia supernovae (SNe Ia) provided the first strong evidence that the expansion of the universe is accelerating. With SN samples now more than ten times larger than those used for the original discovery and joined by other cosmological probes, this discovery is on even firmer ground. Two recent, related studies (Nielsen et al. 2016 and Colin et al. 2019, hereafter N16 and C19, respectively) have claimed to undermine the statistical significance of the SN Ia constraints. Rubin & Hayden (2016) (hereafter RH16) showed N16 made an incorrect assumption about the distributions of SN Ia light-curve parameters, while C19 also fails to remove the impact of the motion of the solar system from the SN redshifts, interpreting the resulting errors as evidence of a dipole in the deceleration parameter. Building on RH16, we outline the errors C19 makes in their treatment of the data and inference on cosmological parameters. Reproducing the C19 analysis with our proposed fixes, we find that the dipole parameters have little effect on the inferred cosmological parameters. We thus affirm the conclusion of RH16: the evidence for acceleration is secure.

astro-ph.CO↗

arXiv2020

Accelerated Bayesian Optimization throughWeight-Prior Tuning

Bayesian optimization (BO) is a widely-used method for optimizing expensive (to evaluate) problems. At the core of most BO methods is the modeling of the objective function using a Gaussian Process (GP) whose covariance is selected from a set of standard covariance functions. From a weight-space view, this models the objective as a linear function in a feature space implied by the given covariance K, with an arbitrary Gaussian weight prior ${\bf w} \sim \mathcal{N} ({\bf 0}, {\bf I})$. In many practical applications there is data available that has a similar (covariance) structure to the objective, but which, having different form, cannot be used directly in standard transfer learning. In this paper we show how such auxiliary data may be used to construct a GP covariance corresponding to a more appropriate weight prior for the objective function. Building on this, we show that we may accelerate BO by modeling the objective function using this (learned) weight prior, which we demonstrate on both test functions and a practical application to short-polymer fibre manufacture.

stat.ML↗

arXiv2020

Does Gravity Fall Down? Evidence for Gravitational Wave Deflection Along the Line of Sight to GW 170817

We present a novel test of general relativity (GR): measuring the geometric component of the time delay due to gravitational lensing. GR predicts that photons and gravitational waves follow the same geodesic paths and thus experience the same geometric time delay. We show that for typical systems, the time delays are tens of seconds, and thus can dominate over astrophysical delays in the timing of photon emission. For the case of GW 170817, we use a multi-plane lensing code to evaluate the time delay due to four massive halos along the line of sight. From literature mass and distance measurements of these halos, we establish at high confidence (significantly greater than 5 sigma) that the gravitational waves of GW 170817 underwent gravitational deflection to arrive within 1.7 seconds of the photons.

astro-ph.CO↗

arXiv2019

Precise Mass Determination of SPT-CL J2106-5844, the Most Massive Cluster at z>1

We present a detailed high-resolution weak-lensing (WL) study of SPT-CL J2106-5844 at z=1.132, claimed to be the most massive system discovered at z > 1 in the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey. Based on the deep imaging data from the Advanced Camera for Surveys and Wide Field Camera 3 on-board the Hubble Space Telescope, we find that the cluster mass distribution is asymmetric, composed of a main clump and a subclump ~640 kpc west thereof. The central clump is further resolved into two smaller northwestern and southeastern substructures separated by ~150 kpc. We show that this rather complex mass distribution is more consistent with the cluster galaxy distribution than a unimodal distribution as previously presented. The northwestern substructure coincides with the BCG and X-ray peak while the southeastern one agrees with the location of the number density peak. These morphological features and the comparison with the X-ray emission suggest that the cluster might be a merging system. We estimate the virial mass of the cluster to be $M_{200c} = (10.4^{+3.3}_{-3.0}\pm1.0)~\times~10^{14}~M_{\odot}$, where the second error bar is the systematic uncertainty. Our result confirms that the cluster SPT-CL J2106-5844 is indeed the most massive cluster at z>1 known to date. We demonstrate the robustness of this mass estimate by performing a number of tests with different assumptions on the centroids, mass-concentration relations, and sample variance.

astro-ph.CO↗

arXiv2019

Measurement and modeling of electron-cloud-induced betatron tune shifts at the Cornell Electron-positron Storage Ring test accelerator

We report on extensive measurements at the Cornell Electron-positron Storage Ring of electron-cloud-induced betatron tune shifts for trains of positron bunches at 2.1 and 5.3 GeV with bunch populations ranging between 0.64x10^10 and 9.6x10^10. Measurements using a witness bunch with variable distance from the end of the train and variable bunch population provide information on cloud decay and cloud pinching during the bunch passage. We employ Monte Carlo simulations of the reflection and absorption of synchrotron radiation photons to determine the pattern of absorption sites around the circumference of the storage ring. The Geant4 simulation toolkit is used to model the interactions of the photons with the beampipe wall and determine the production energy and location distributions of the photoelectrons which seed the electron cloud. An electron cloud buildup model based on fitted ring-averaged secondary-yield properties of the vacuum chamber predicts tune shifts in good agreement with the measurements.

physics.acc-ph↗

arXiv2019

Discovery of an intermediate-luminosity red transient in M51 and its likely dust-obscured, infrared-variable progenitor

We present the discovery of an optical transient (OT) in Messier 51, designated M51 OT2019-1 (also ZTF19aadyppr, AT 2019abn, ATLAS19bzl), by the Zwicky Transient Facility (ZTF). The OT rose over 15 days to an observed luminosity of $M_r=-13$ ($νL_ν=9\times10^6~L_{\odot}$), in the luminosity gap between novae and typical supernovae (SNe). Spectra during the outburst show a red continuum, Balmer emission with a velocity width of $\approx400$ km s$^{-1}$, Ca II and [Ca II] emission, and absorption features characteristic of an F-type supergiant. The spectra and multiband light curves are similar to the so-called "SN impostors" and intermediate-luminosity red transients (ILRTs). We directly identify the likely progenitor in archival Spitzer Space Telescope imaging with a $4.5~μ$m luminosity of $M_{[4.5]}\approx-12.2$ and a $[3.6]-[4.5]$ color redder than 0.74 mag, similar to those of the prototype ILRTs SN 2008S and NGC 300 OT2008-1. Intensive monitoring of M51 with Spitzer further reveals evidence for variability of the progenitor candidate at [4.5] in the years before the OT. The progenitor is not detected in pre-outburst Hubble Space Telescope optical and near-IR images. The optical colors during outburst combined with spectroscopic temperature constraints imply a higher reddening of $E(B-V)\approx0.7$ mag and higher intrinsic luminosity of $M_r\approx-14.9$ ($νL_ν=5.3\times10^7~L_{\odot}$) near peak than seen in previous ILRT candidates. Moreover, the extinction estimate is higher on the rise than on the plateau, suggestive of an extended phase of circumstellar dust destruction. These results, enabled by the early discovery of M51 OT2019-1 and extensive pre-outburst archival coverage, offer new clues about the debated origins of ILRTs and may challenge the hypothesis that they arise from the electron-capture induced collapse of extreme asymptotic giant branch stars.

astro-ph.SR↗

arXiv2019

Accelerating Experimental Design by Incorporating Experimenter Hunches

Experimental design is a process of obtaining a product with target property via experimentation. Bayesian optimization offers a sample-efficient tool for experimental design when experiments are expensive. Often, expert experimenters have 'hunches' about the behavior of the experimental system, offering potentials to further improve the efficiency. In this paper, we consider per-variable monotonic trend in the underlying property that results in a unimodal trend in those variables for a target value optimization. For example, sweetness of a candy is monotonic to the sugar content. However, to obtain a target sweetness, the utility of the sugar content becomes a unimodal function, which peaks at the value giving the target sweetness and falls off both ways. In this paper, we propose a novel method to solve such problems that achieves two main objectives: a) the monotonicity information is used to the fullest extent possible, whilst ensuring that b) the convergence guarantee remains intact. This is achieved by a two-stage Gaussian process modeling, where the first stage uses the monotonicity trend to model the underlying property, and the second stage uses `virtual' samples, sampled from the first, to model the target value optimization function. The process is made theoretically consistent by adding appropriate adjustment factor in the posterior computation, necessitated because of using the `virtual' samples. The proposed method is evaluated through both simulations and real world experimental design problems of a) new short polymer fiber with the target length, and b) designing of a new three dimensional porous scaffolding with a target porosity. In all scenarios our method demonstrates faster convergence than the basic Bayesian optimization approach not using such `hunches'.

stat.ML↗

arXiv2019

The Hyper Suprime-Cam SSP Transient Survey in COSMOS: Overview

We present an overview of a deep transient survey of the COSMOS field with the Subaru Hyper Suprime-Cam (HSC). The survey was performed for the 1.77 deg$^2$ ultra-deep layer and 5.78 deg$^2$ deep layer in the Subaru Strategic Program over 6- and 4-month periods from 2016 to 2017, respectively. The ultra-deep layer shows a median depth per epoch of 26.4, 26.3, 26.0, 25.6, and 24.6 mag in $g$, $r$, $i$, $z$, and $y$ bands, respectively; the deep layer is $\sim0.6$ mag shallower. In total, 1,824 supernova candidates were identified. Based on light curve fitting and derived light curve shape parameter, we classified 433 objects as Type Ia supernovae (SNe); among these candidates, 129 objects have spectroscopic or COSMOS2015 photometric redshifts and 58 objects are located at $z > 1$. Our unique dataset doubles the number of Type Ia SNe at $z > 1$ and enables various time-domain analyses of Type II SNe, high redshift superluminous SNe, variable stars, and active galactic nuclei.

astro-ph.GA↗

arXiv2019

Constraining the Dimensionality of SN Ia Spectral Variation with Twins

SNe Ia continue to play a key role in cosmological measurements. Their interpretation over a range in redshift requires a rest-frame spectral energy distribution model. For practicality, these models are parameterized with a limited number of parameters and are trained using linear or nonlinear dimensionality reduction. This work focuses on the related problem of estimating the number of parameters underlying SN Ia spectral variation (the dimensionality). I present a technique for using the properties of high-dimensional space and the counting statistics of "twin" SNe Ia to estimate this dimensionality. Applying this method to the supernova pairings from Fakhouri et al. (2015) shows that a modest number of parameters (three to five, not including extinction) explain those data well. The analysis also finds that the intrinsic parameters are approximately Gaussian-distributed. The limited number of parameters hints that improved SED models are possible that may enable substantial reductions in SN cosmological uncertainties with current and near-term datasets.

astro-ph.CO↗

arXiv2019

The Next Generation of Cosmological Measurements with Type Ia Supernovae

While Type Ia Supernovae (SNe Ia) are one of the most mature cosmological probes, the next era promises to be extremely exciting in the number of different ways SNe Ia are used to measure various cosmological parameters. Here we review the experiments in the 2020s that will yield orders of magnitudes more SNe Ia, and the new understandings and capabilities to constrain systematic uncertainties at a level to match these statistics. We then discuss five different cosmological probes with SNe Ia: the conventional Hubble diagram for measuring dark energy properties, the distance ladder for measuring the Hubble constant, peculiar velocities and weak lensing for measuring sigma8 and strong-lens measurements of H0 and other cosmological parameters. For each of these probes, we discuss the experiments that will provide the best measurements and also the SN Ia-related systematics that affect each one.

astro-ph.CO↗

arXiv2019

SN Ia Standardization on the Rise: Evidence for the Cosmological Importance of Pre-Maximum Measurements

We present SALT2X, an extension of the SALT2 model for SN Ia supernova light curves. SALT2X separates the light-curve-shape parameter x1 into an x1r and x1f for the rise and fall portions of the light curve. Using the Joint Lightcurve Analysis (JLA) SN sample, we assess the importance of the rising and falling portions of the light curve for cosmological standardization using a modified version of the Unified Nonlinear Inference for Type Ia cosmologY (UNITY) framework. We find strong evidence that x1r has a stronger correlation with peak magnitude than x1f. We see evidence that standardizing on the rise affects the color standardization relation, and reduces the size of the host-galaxy standardization and the unexplained ("intrinsic") luminosity dispersion. Since SNe Ia generally rise more quickly than they decline, a faster observing cadence in future surveys will be necessary to maximize the gain from this work, and to continue to explore the impacts of decoupling the rising and falling portions of SN Ia light curves.

astro-ph.CO↗

arXiv2018

Characterization of Unstable Pixels Using a Mixture Model: Application to HST WFC3 IR

Many IR datasets are taken with two dithers per filter, complicating the automated recognition of pixels with unstable response. Much data from the HST cameras NICMOS and WFC3 IR fall into this category, and future JWST and WFIRST data are likely to as well. It is thus important to have an updated list of unstable pixels built from many datasets. We demonstrate a simple Bayesian method that directly estimates the fraction of the time the output of each pixel is unstable. The last major update for WFC3 IR was a 2012 instrument science report (ISR WFC3 2012-10, Hilbert 2012), so we compute a new list. Rather than reproduce the old analysis on newer data, we use our new method. By visual inspection, our method identifies unstable pixels with better purity and completeness.

astro-ph.IM↗

arXiv2018

The Discovery of a Gravitationally Lensed Supernova Ia at Redshift 2.22

We present the discovery and measurements of a gravitationally lensed supernova (SN) behind the galaxy cluster MOO J1014+0038. Based on multi-band Hubble Space Telescope and Very Large Telescope (VLT) photometry of the supernova, and VLT spectroscopy of the host galaxy, we find a 97.5% probability that this SN is a SN Ia, and a 2.5% chance of a CC SN. Our typing algorithm combines the shape and color of the light curve with the expected rates of each SN type in the host galaxy. With a redshift of 2.2216, this is the highest redshift SN Ia discovered with a spectroscopic host-galaxy redshift. A further distinguishing feature is that the lensing cluster, at redshift 1.23, is the most distant to date to have an amplified SN. The SN lies in the middle of the color and light-curve shape distributions found at lower redshift, disfavoring strong evolution to z = 2.22. We estimate an amplification due to gravitational lensing of 2.8+0.6-0.5 (1.10 +- 0.23 mag)---compatible with the value estimated from the weak-lensing-derived mass and the mass-concentration relation from LambdaCDM simulations---making it the most amplified SN Ia discovered behind a galaxy cluster.

astro-ph.GA↗

arXiv2018

Covariance Function Pre-Training with m-Kernels for Accelerated Bayesian Optimisation

The paper presents a novel approach to direct covariance function learning for Bayesian optimisation, with particular emphasis on experimental design problems where an existing corpus of condensed knowledge is present. The method presented borrows techniques from reproducing kernel Banach space theory (specifically m-kernels) and leverages them to convert (or re-weight) existing covariance functions into new, problem-specific covariance functions. The key advantage of this approach is that rather than relying on the user to manually select (with some hyperparameter tuning and experimentation) an appropriate covariance function it constructs the covariance function to specifically match the problem at hand. The technique is demonstrated on two real-world problems - specifically alloy design and short-polymer fibre manufacturing - as well as a selected test function.

stat.ML↗

arXiv2017

Science-Driven Optimization of the LSST Observing Strategy

The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation. However, exactly how the LSST observations will be taken (the observing strategy or "cadence") is not yet finalized. In this dynamically-evolving community white paper, we explore how the detailed performance of the anticipated science investigations is expected to depend on small changes to the LSST observing strategy. Using realistic simulations of the LSST schedule and observation properties, we design and compute diagnostic metrics and Figures of Merit that provide quantitative evaluations of different observing strategies, analyzing their impact on a wide range of proposed science projects. This is work in progress: we are using this white paper to communicate to each other the relative merits of the observing strategy choices that could be made, in an effort to maximize the scientific value of the survey. The investigation of some science cases leads to suggestions for new strategies that could be simulated and potentially adopted. Notably, we find motivation for exploring departures from a spatially uniform annual tiling of the sky: focusing instead on different parts of the survey area in different years in a "rolling cadence" is likely to have significant benefits for a number of time domain and moving object astronomy projects. The communal assembly of a suite of quantified and homogeneously coded metrics is the vital first step towards an automated, systematic, science-based assessment of any given cadence simulation, that will enable the scheduling of the LSST to be as well-informed as possible.

astro-ph.IM↗