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Kaisey Mandel

Publications and source records attributed to Kaisey Mandel.

16 recordsLinked to original sources

Lightcurve Modelling of 2,205 ZTF DR2 Type~Ia Supernovae: Implications for SN Ia Physics and Cosmology

We fit the multi-band light curves of 2,205 Type Ia supernovae (SNe~Ia) from the Zwicky Transient Facility DR2 with a one-zone radioactive decay model with a phenomenological addition to include Fe recombination physics. We find a strong correlation between inferred nickel mass and SALT2 stretch, which within our simplified modelling is linked to larger ejecta masses providing longer diffusion times, providing a physical basis for the brighter-slower relation. SN~Ia in low-mass hosts ($\log_{10}(M_*/M_\odot) < 10$) produce $12\%$ more $^{56}$Ni than those in high-mass hosts ($\Delta M_{\rm Ni} = 0.13~M_\odot$), linking the host-galaxy mass step to ejecta properties and hinting at metallicity or age-dependent burning efficiencies. This suggests that standardisation based on physical parameters may remove the mass-step. SN~1991T-like events show higher ejecta masses (median $1.64~M_\odot$ vs. $1.38~M_\odot$ for normals) and produce $30\%$ more $^{56}$Ni, with $84\%$ having super-Chandrasekhar masses. Through Hierarchical modelling of $902$ SNe ($z \leq 0.06$), we find thermonuclear supernovae can be well described by a Gaussian distribution in ejecta mass and nickel mass with $\mu_{\rm ej} = 1.26 \pm 0.01~M_\odot$ ($\sigma_{\rm ej} = 0.33 \pm 0.01~M_\odot$) and $\mu_{\rm Ni} = 0.64 \pm 0.06~M_\odot$ ($\sigma_{\rm Ni} = 0.42 \pm 0.02~M_\odot$), respectively. This leads to inferred fractions of $43 \pm 2\%$ sub-$M_{\rm Ch}$ ($<1.2~M_\odot$), $34 \pm 1\%$ near-$M_{\rm Ch}$ ($1.2$--$1.5~M_\odot$), and $24 \pm 2\%$ super-$M_{\rm Ch}$ ($>1.5~M_\odot$) events. This work provides a step towards holistic physical characterization of the local SN~Ia population, reinforcing the physical basis of SN~Ia standardization while quantifying diversity and environmental dependencies critical for understanding progenitor physics and mitigating systematics in precision cosmology.

astro-ph.HE

The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TB of Astronomical Scientific Data

We present the MULTIMODAL UNIVERSE, a large-scale multimodal dataset of scientific astronomical data, compiled specifically to facilitate machine learning research. Overall, the MULTIMODAL UNIVERSE contains hundreds of millions of astronomical observations, constituting 100\,TB of multi-channel and hyper-spectral images, spectra, multivariate time series, as well as a wide variety of associated scientific measurements and "metadata". In addition, we include a range of benchmark tasks representative of standard practices for machine learning methods in astrophysics. This massive dataset will enable the development of large multi-modal models specifically targeted towards scientific applications. All codes used to compile the MULTIMODAL UNIVERSE and a description of how to access the data is available at https://github.com/MultimodalUniverse/MultimodalUniverse

astro-ph.IM

Avoiding methane emission rate underestimates when using the divergence method

Methane is a powerful greenhouse gas, and a primary target for mitigating climate change in the short-term future due to its relatively short atmospheric lifetime and greater ability to trap heat in Earth's atmosphere compared to carbon dioxide. Top-down observations of atmospheric methane are possible via drone and aircraft surveys as well as satellites such as the TROPOspheric Monitoring Instrument (TROPOMI). Recent work has begun to apply the divergence method to produce regional methane emission rate estimates. Here we show that when the divergence method is applied to spatially incomplete observations of methane, it can result in negatively biased time-averaged regional emission rates. We show that this effect can be counteracted by adopting a procedure in which daily advective fluxes of methane are time-averaged before the divergence method is applied. Using such a procedure with TROPOMI methane observations, we calculate yearly Permian emission rates of 3.1, 2.4 and 2.7 million tonnes per year for the years 2019 through 2021. We also show that highly-resolved plumes of methane can have negatively biased estimated emission rates by the divergence method due to the presence of turbulent diffusion in the plume, but this is unlikely to affect regional methane emission budgets constructed from TROPOMI observations of methane. The results from this work are expected to provide useful guidance for future implementations of the divergence method for emission rate estimation from satellite data -- be it for methane or other gaseous species in the atmosphere.

physics.ao-ph

Constraints on the Hubble constant from Supernova Refsdal's reappearance

The gravitationally lensed Supernova Refsdal appeared in multiple images, produced through gravitational lensing by a massive foreground galaxy cluster. After the supernova appeared in 2014, lens models of the galaxy cluster predicted an additional image of the supernova would appear in 2015, which was subsequently observed. We use the time delays between the images to perform a blinded measurement of the expansion rate of the Universe, quantified by the Hubble constant (H0). Using eight cluster lens models, we infer H0 = 64.8 +4.4-4.3 km / s / Mpc, where Mpc is the megaparsec. Using the two models most consistent with the observations, we find H0 = 66.6 +4.1-3.3 km / s / Mpc. The observations are best reproduced by models that assign dark-matter halos to individual galaxies and the overall cluster.

astro-ph.CO

Roman CCS White Paper: Measuring Type Ia Supernovae Discovered in the Roman High Latitude Time Domain Survey

We motivate the cosmological science case of measuring Type Ia supernovae with the Nancy Grace Roman Space Telescope as part of the High Latitude Time Domain Survey. We discuss previously stated requirements for the science, and a baseline survey strategy. We discuss the various areas that must still be optimized and point to the other white papers that consider these topics in detail. Overall, the baseline case should enable an exquisite measurement of dark energy using SNe Ia from z=0.1 to z>2, and further optimization should only strengthen this once-in-a-generation experiment.

astro-ph.IM

The Magnificent Five Images of Supernova Refsdal: Time Delay and Magnification Measurements

In late 2014, four images of Supernova (SN) "Refsdal," the first known example of a strongly lensed SN with multiple resolved images, were detected in the MACS J1149 galaxy-cluster field. Following the images' discovery, the SN was predicted to reappear within hundreds of days at a new position ~8 arcseconds away in the field. The observed reappearance in late 2015 makes it possible to carry out Refsdal's (1964) original proposal to use a multiply imaged SN to measure the Hubble constant H0, since the time delay between appearances should vary inversely with H0. Moreover, the position, brightness, and timing of the reappearance enable a novel test of the blind predictions of galaxy-cluster models, which are typically constrained only by the positions of multiply imaged galaxies. We have developed a new photometry pipeline that uses DOLPHOT to measure the fluxes of the five images of SN Refsdal from difference images. We apply four separate techniques to perform a blind measurement of the relative time delays and magnification ratios (mu_i/mu_1) between the last image SX and the earlier images S1-S4. We measure the relative time delay of SX-S1 to be 376.0+5.6-5.5 days and the relative magnification to be 0.30+0.05-0.03. This corresponds to a 1.5% precision on the time delay and 17% precision for the magnification ratios, and includes uncertainties due to millilensing and microlensing. In an accompanying paper, we place initial and blind constraints on the value of the Hubble constant.

astro-ph.CO

Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference

Methane is a strong greenhouse gas, with a higher radiative forcing per unit mass and shorter atmospheric lifetime than carbon dioxide. The remote sensing of methane in regions of industrial activity is a key step toward the accurate monitoring of emissions that drive climate change. Whilst the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinal-5P satellite is capable of providing daily global measurement of methane columns, data are often compromised by cloud cover. Here, we develop a statistical model which uses nitrogen dioxide concentration data from TROPOMI to efficiently predict values of methane columns, expanding the average daily spatial coverage of observations of the Permian basin from 16% to 88% in the year 2019. The addition of predicted methane abundances at locations where direct observations are not available will support inversion methods for estimating methane emission rates at shorter timescales than is currently possible.

physics.ao-ph

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

The Wide Field Infrared Survey Telescope: 100 Hubbles for the 2020s

The Wide Field Infrared Survey Telescope (WFIRST) is a 2.4m space telescope with a 0.281 deg^2 field of view for near-IR imaging and slitless spectroscopy and a coronagraph designed for > 10^8 starlight suppresion. As background information for Astro2020 white papers, this article summarizes the current design and anticipated performance of WFIRST. While WFIRST does not have the UV imaging/spectroscopic capabilities of the Hubble Space Telescope, for wide field near-IR surveys WFIRST is hundreds of times more efficient. Some of the most ambitious multi-cycle HST Treasury programs could be executed as routine General Observer (GO) programs on WFIRST. The large area and time-domain surveys planned for the cosmology and exoplanet microlensing programs will produce extraordinarily rich data sets that enable an enormous range of Archival Research (AR) investigations. Requirements for the coronagraph are defined based on its status as a technology demonstration, but its expected performance will enable unprecedented observations of nearby giant exoplanets and circumstellar disks. WFIRST is currently in the Preliminary Design and Technology Completion phase (Phase B), on schedule for launch in 2025, with several of its critical components already in production.

astro-ph.IM

Estimating the Mass of the Milky Way Using the Ensemble of Classical Satellite Galaxies

High precision proper motion (PM) measurements are available for approximately 20% of all known dwarf satellite galaxies of the Milky Way (MW). Here we extend the Bayesian framework of Patel et al. (2017b) to include all MW satellites with measured 6D phase space information and apply it with the Illustris-Dark simulation to constrain the MW's mass. Using the properties of each MW satellite individually, we find that the scatter among mass estimates is reduced when the magnitude of specific orbital angular momentum (j) is adopted rather than their combined instantaneous positions and velocities. We also find that high j satellites (i.e. Leo II) constrain the upper limits for the MW's mass and low j satellites rather than the highest speed satellites (i.e. Leo I and LMC), set the lower mass limits. When j of all classical satellites is used to simultaneously estimate the MW's mass, we conclude the halo mass is $0.85^{+0.23}_{-0.26}\times 10^{12} \rm \, M_{\odot}$ (including Sagittarius dSph) and $0.96^{+0.29}_{-0.28} \times 10^{12} \rm \, M_{\odot}$ (excluding Sagittarius dSph), cautioning that low j satellites on decaying orbits like Sagittarius dSph may bias the distribution. These estimates markedly reduce the current factor of two spread in the mass range of the MW. We also find a well-defined relationship between host halo mass and satellite j distribution, which yields the prediction that upcoming PMs for ultra-faint dwarfs should reveal j within $ 5\times10^3 - 10^4$ kpc km s$^{-1}$. This is a promising method to significantly constrain the cosmologically expected mass range for the MW and eventually M31 as more satellite PMs become available.

astro-ph.GA

Orbits of massive satellite galaxies: II. Bayesian Estimates of the Milky Way and Andromeda masses using high precision astrometry and cosmological simulations

Space observatories like the Hubble Space Telescope and Gaia are providing unprecedented 6D phase space information of satellite galaxies. Such measurements can shed light on the structure and assembly history of the Local Group, but improved statistical methods are needed to use them efficiently. Here we illustrate such a method using analogs of the Local Group's two most massive satellite galaxies, the Large Magellanic Cloud (LMC) and Triangulum (M33), from the Illustris dark-matter-only cosmological simulation. We use a Bayesian inference scheme combining measurements of positions, velocities, and specific orbital angular momenta ( j ) of the LMC/M33 with importance sampling of their simulated analogs to compute posterior estimates of the Milky Way (MW) and Andromeda's (M31) halo masses. We conclude the resulting host halo mass is more susceptible to bias when using measurements of the current position and velocity of satellites, especially when satellites are at short-lived phases of their orbits (i.e. at pericentre). Instead, the j value of a satellite is well-conserved over time and provides a more reliable constraint on host mass. The inferred virial mass of the MW (M31) using j of the LMC (M33) is $\rm M_{vir, MW}=1.02^{+0.77}_{-0.55}\times10^{12}\; M_{\odot}$ ($\rm M_{vir, M31}=1.37^{+1.39}_{-0.75}\times10^{12}\; M_{\odot}$). Choosing simulated analogs whose j values are consistent with the conventional picture of a previous (< 3 Gyr ago), close encounter (< 100 kpc) of M33 about M31 results in a very low virial mass for M31 ($\rm\sim\!10^{12}\; M_{\odot}$). This supports the new scenario put forth in Patel et al. (2017), wherein M33 is on its first passage about M31 or on a long period orbit. We conclude that this Bayesian inference scheme, utilising satellite j, is a promising method to reduce the current factor of two spread in the mass range of the MW and M31 moving forward.

astro-ph.GA

Bayesian Estimates of Astronomical Time Delays between Gravitationally Lensed Stochastic Light Curves

The gravitational field of a galaxy can act as a lens and deflect the light emitted by a more distant object such as a quasar. Strong gravitational lensing causes multiple images of the same quasar to appear in the sky. Since the light in each gravitationally lensed image traverses a different path length from the quasar to the Earth, fluctuations in the source brightness are observed in the several images at different times. The time delay between these fluctuations can be used to constrain cosmological parameters and can be inferred from the time series of brightness data or light curves of each image. To estimate the time delay, we construct a model based on a state-space representation for irregularly observed time series generated by a latent continuous-time Ornstein-Uhlenbeck process. We account for microlensing, an additional source of independent long-term extrinsic variability, via a polynomial regression. Our Bayesian strategy adopts a Metropolis-Hastings within Gibbs sampler. We improve the sampler by using an ancillarity-sufficiency interweaving strategy and adaptive Markov chain Monte Carlo. We introduce a profile likelihood of the time delay as an approximation of its marginal posterior distribution. The Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian method is more principled but the profile likelihood is simpler to implement. We demonstrate our estimation strategy using simulated data of doubly- and quadruply-lensed quasars, and observed data from quasars Q0957+561 and J1029+2623.

astro-ph.IM

SN~2012cg: Evidence for Interaction Between a Normal Type Ia Supernova and a Non-Degenerate Binary Companion

We report evidence for excess blue light from the Type Ia supernova SN 2012cg at fifteen and sixteen days before maximum B-band brightness. The emission is consistent with predictions for the impact of the supernova on a non-degenerate binary companion. This is the first evidence for emission from a companion to a SN Ia. Sixteen days before maximum light, the B-V color of SN 2012cg is 0.2 mag bluer than for other normal SN~Ia. At later times, this supernova has a typical SN Ia light curve, with extinction-corrected M_B = -19.62 +/- 0.02 mag and Delta m_{15}(B) = 0.86 +/- 0.02. Our data set is extensive, with photometry in 7 filters from 5 independent sources. Early spectra also show the effects of blue light, and high-velocity features are observed at early times. Near maximum, the spectra are normal with a silicon velocity v_{Si} = -10,500$ km s^{-1}. Comparing the early data with models by Kasen (2010) favors a main-sequence companion of about 6 solar masses. It is possible that many other SN Ia have main-sequence companions that have eluded detection because the emission from the impact is fleeting and faint.

astro-ph.SR

Strong Lens Time Delay Challenge: II. Results of TDC1

We present the results of the first strong lens time delay challenge. The motivation, experimental design, and entry level challenge are described in a companion paper. This paper presents the main challenge, TDC1, which consisted of analyzing thousands of simulated light curves blindly. The observational properties of the light curves cover the range in quality obtained for current targeted efforts (e.g.,~COSMOGRAIL) and expected from future synoptic surveys (e.g.,~LSST), and include simulated systematic errors. \nteamsA\ teams participated in TDC1, submitting results from \nmethods\ different method variants. After a describing each method, we compute and analyze basic statistics measuring accuracy (or bias) $A$, goodness of fit $χ^2$, precision $P$, and success rate $f$. For some methods we identify outliers as an important issue. Other methods show that outliers can be controlled via visual inspection or conservative quality control. Several methods are competitive, i.e., give $|A|<0.03$, $P<0.03$, and $χ^2<1.5$, with some of the methods already reaching sub-percent accuracy. The fraction of light curves yielding a time delay measurement is typically in the range $f = $20--40\%. It depends strongly on the quality of the data: COSMOGRAIL-quality cadence and light curve lengths yield significantly higher $f$ than does sparser sampling. Taking the results of TDC1 at face value, we estimate that LSST should provide around 400 robust time-delay measurements, each with $P<0.03$ and $|A|<0.01$, comparable to current lens modeling uncertainties. In terms of observing strategies, we find that $A$ and $f$ depend mostly on season length, while P depends mostly on cadence and campaign duration.

astro-ph.IM

Classifying Supernovae Using Only Galaxy Data

We present a new method for probabilistically classifying supernovae (SNe) without using SN spectral or photometric data. Unlike all previous studies to classify SNe without spectra, this technique does not use any SN photometry. Instead, the method relies on host-galaxy data. We build upon the well-known correlations between SN classes and host-galaxy properties, specifically that core-collapse SNe rarely occur in red, luminous, or early-type galaxies. Using the nearly spectroscopically complete Lick Observatory Supernova Search sample of SNe, we determine SN fractions as a function of host-galaxy properties. Using these data as inputs, we construct a Bayesian method for determining the probability that a SN is of a particular class. This method improves a common classification figure of merit by a factor of >2, comparable to the best light-curve classification techniques. Of the galaxy properties examined, morphology provides the most discriminating information. We further validate this method using SN samples from the Sloan Digital Sky Survey and the Palomar Transient Factory. We demonstrate that this method has wide-ranging applications, including separating different subclasses of SNe and determining the probability that a SN is of a particular class before photometry or even spectra can. Since this method uses completely independent data from light-curve techniques, there is potential to further improve the overall purity and completeness of SN samples and to test systematic biases of the light-curve techniques. Further enhancements to the host-galaxy method, including additional host-galaxy properties, combination with light-curve methods, and hybrid methods should further improve the quality of SN samples from past, current, and future transient surveys.

astro-ph.CO

Analytic Lightcurves for Planetary Transit Searches

We present exact analytic formulae for the eclipse of a star described by quadratic or nonlinear limb darkening. In the limit that the planet radius is less than a tenth of the stellar radius, we show that the exact lightcurve can be well approximated by assuming the region of the star blocked by the planet has constant surface brightness. We apply these results to the HST observations of HD 209458, showing that the ratio of the planetary to stellar radii is 0.1207+-0.0003. These formulae give a fast and accurate means of computing lightcurves using limb-darkening coefficients from model atmospheres which should aid in the detection, simulation, and parameter fitting of planetary transits.

astro-ph