arXiv subjects

N. Suzuki

Publications and source records attributed to N. Suzuki.

At least 19 recordsLinked to original sources

arXiv2025

DESI Strong Lens Foundry II: DESI Spectroscopy for Strong Lens Candidates

We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lensing Secondary Target Program. This is a spectroscopic follow-up program for strong gravitational lens candidates found in the DESI Legacy Imaging Surveys footprint. Spectroscopic redshifts for the lenses and lensed source are crucial for lens modeling to obtain physical parameters. The spectroscopic catalog in this paper consists of 73 candidate systems from the DESI Early Data Release (EDR). We have confirmed 20 strong lensing systems and determined four to not be lenses. For the remaining systems, more spectroscopic data from ongoing and future observations will be presented in future publications. We discuss the implications of our results for lens searches with neural networks in existing and future imaging surveys as well as for lens modeling. This Strong Lensing Secondary Target Program is part of the DESI Strong Lens Foundry project, and this is Paper II of a series on this project.

astro-ph.CO↗

arXiv2025

DESI Strong Lens Foundry III: Keck Spectroscopy for Strong Lenses Discovered Using Residual Neural Networks

We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legacy Imaging Surveys using Residual Neural Networks (ResNet) and followed up by our Hubble Space Telescope program, with all systems displaying unambiguous lensed arcs. With NIRES, we target eight lensed sources at redshifts difficult to measure in the optical range and determine the source redshifts for six, between $z_s$ = 1.675 and 3.332. DESI observed one of the remaining source redshifts, as well as an additional source redshift within the six systems. The two systems with non-detections by NIRES were observed for a considerably shorter 600s at high airmass. Combining NIRES infrared spectroscopy with optical spectroscopy from our DESI Strong Lensing Secondary Target Program, these results provide the complete lens and source redshifts for six systems, a resource for refining automated strong lens searches in future deep- and wide-field imaging surveys and addressing a range of questions in astrophysics and cosmology.

astro-ph.CO↗

arXiv2025

The unusual spectrum of the X-ray transient source XRISM J174610.8-290021 near the Galactic center

The Galactic center region was observed with the XRISM X-ray observatory during the performance verification phase in 2024 and a point-like X-ray source was detected with the X-ray imager Xtend at a position of (RA, Dec)=(17h46m10.8s, -29{\deg}00'21''), which is thus named XRISM J174610.8-290021. This source was bright in February to March and showed time variations in count rate by more than one order of magnitude in one week. The 2-10 keV X-ray luminosity was ~$10^{35}$ erg/s for the assumed distance of 8 kpc. However, after six months, it was below the detection limit. We found a hint of periodicity of 1537 s from timing analysis. The XRISM/Xtend spectrum has emission lines from helium-like iron (Fe He$\alpha$) at 6.7 keV and hydrogen-like iron (Fe Ly$\alpha$) at 6.97 keV; their intensity ratio is unusual with the latter being four times stronger than the former. If the emission is of thermal origin, the ionization temperature estimated from the iron-line intensity ratio is ~30 keV, which is inconsistent with the electron temperature estimated from the thermal bremsstrahlung, ~7 keV. Spectral models of magnetic cataclysmic variables, which are often seen in the Galactic center in this luminosity range, are found to fail to reproduce the obtained spectrum. By contrast, we found that the spectrum is well reproduced with the models of low-mass X-ray binaries containing a neutron star plus two narrow Gaussian lines. We consider that the source is intrinsically bright reaching $10^{37}$ erg/s, but is blocked from direct view due to a high inclination and only the scattered emission is visible. The photoionized plasma above the accretion disk with an ionization parameter of ~$10^{5}$ may explain the unusual iron line ratio. We further discuss the potential contribution of point sources of the type of XRISM J174610.8-290021 to the diffuse Galactic center X-ray emission.

astro-ph.HE↗

arXiv2025

An Agnostic Approach to Building Empirical Type Ia Supernova Light Curves: Evidence for Intrinsic Chromatic Flux Variation Using Nearby Supernova Factory Data

We present a new empirical Type Ia supernova (SN Ia) model with three chromatic flux variation templates: one phase dependent and two phase independent. No underlying dust extinction model or patterns of intrinsic variability are assumed. Implemented with Stan and trained using spectrally binned Nearby Supernova Factory spectrophotometry, we examine this model's 2D, phase-independent flux variation space using two motivated basis representations. In both, the first phase-independent template captures variation that appears dust-like, while the second captures a combination of effectively intrinsic variability and second-order dust-like effects. We find that approximately 13% of the modeled phase-independent flux variance is not dust-like. Previous empirical SN Ia models either assume an effective dust extinction recipe in their architecture, or only allow for a single mode of phase-independent variation. The presented results demonstrate such an approach may be insufficient, because it could "leak" noticeable intrinsic variation into phase-independent templates.

astro-ph.HE↗

arXiv2025

DESI Strong Lens Foundry I: HST Observations and Modeling with GIGA-Lens

We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lens Foundry. We discovered $\sim 3500$ new strong gravitational lens candidates in the DESI Legacy Imaging Surveys using residual neural networks (ResNet). We observed a subset (51) of our candidates using the Hubble Space Telescope (HST). All of them were confirmed to be strong lenses. We also briefly describe spectroscopic follow-up observations by DESI and Keck NIRES programs. From this very rich dataset, a number of studies will be carried out, including evaluating the quality of the ResNet search candidates and lens modeling. In this paper, we present our initial effort in these directions. In particular, as a demonstration, we present the lens model for DESI-165.4754-06.0423, with imaging data from HST, and lens and source redshifts from DESI and Keck NIRES, respectively. In this effort, we have applied a \emph{fully} forward-modeling Bayesian approach (GIGA-Lens), using \emph{multiple} GPUs, for the first time in both regards, to a strong lens with HST data, or any high resolution imaging.

astro-ph.CO↗

arXiv2024

Euclid preparation. The Cosmic Dawn Survey (DAWN) of the Euclid Deep and Auxiliary Fields

Euclid will provide deep NIR imaging to $\sim$26.5 AB magnitude over $\sim$59 deg$^2$ in its deep and auxiliary fields. The Cosmic DAWN survey complements the deep Euclid data with matched depth multiwavelength imaging and spectroscopy in the UV--IR to provide consistently processed Euclid selected photometric catalogs, accurate photometric redshifts, and measurements of galaxy properties to a redshift of $z\sim 10$. In this paper, we present an overview of the survey, including the footprints of the survey fields, the existing and planned observations, and the primary science goals for the combined data set.

astro-ph.GA↗

arXiv2024

Euclid Preparation. Cosmic Dawn Survey: Data release 1 multiwavelength catalogues for Euclid Deep Field North and Euclid Deep Field Fornax

The Cosmic Dawn Survey (DAWN survey) provides multiwavelength (UV/optical to mid-IR) data across the combined 59 deg$^{2}$ of the Euclid Deep and Auxiliary fields (EDFs and EAFs). Here, the first public data release (DR1) from the DAWN survey is presented. DR1 catalogues are made available for a subset of the full DAWN survey that consists of two Euclid Deep fields: Euclid Deep Field North (EDF-N) and Euclid Deep Field Fornax (EDF-F). The DAWN survey DR1 catalogues do not include $Euclid$ data as they are not yet public for these fields. Nonetheless, each field has been covered by the ongoing Hawaii Twenty Square Degree Survey (H20), which includes imaging from CFHT MegaCam in the new $u$ filter and from Subaru Hyper Suprime-Cam (HSC) in the $griz$ filters. Each field is further covered by $Spitzer$/IRAC 3.6-4.5$\mu$m imaging spanning 10 deg$^{2}$ and reaching $\sim$25 mag AB (5$\sigma$). All present H20 imaging and all publicly available imaging from the aforementioned facilities are combined with the deep $Spitzer$/IRAC data to create source catalogues spanning a total area of 16.87 deg$^{2}$ in EDF-N and 2.85 deg$^{2}$ in EDF-F for this first release. Photometry is measured using The Farmer, a well-validated model-based photometry code. Photometric redshifts and stellar masses are computed using two independent codes for modeling spectral energy distributions: EAZY and LePhare. Photometric redshifts show good agreement with spectroscopic redshifts ($\sigma_{\rm NMAD} \sim 0.5, \eta < 8\%$ at $i < 25$). Number counts, photometric redshifts, and stellar masses are further validated in comparison to the COSMOS2020 catalogue. The DAWN survey DR1 catalogues are designed to be of immediate use in these two EDFs and will be continuously updated. Future data releases will provide catalogues of all EDFs and EAFs and include $Euclid$ data.

astro-ph.GA↗

arXiv2023

Bump Morphology of the CMAGIC Diagram

We apply the color-magnitude intercept calibration method (CMAGIC) to the Nearby Supernova Factory SNe Ia spectrophotometric dataset. The currently existing CMAGIC parameters are the slope and intercept of a straight line fit to the first linear region in the color-magnitude diagram, which occurs over a span of approximately 30 days after maximum brightness. We define a new parameter, $ω_{XY}$, the size of the ``bump'' feature near maximum brightness for arbitrary filters $X$ and $Y$. We find a significant correlation between the slope of the first linear region, $β_{XY, 1}$, in the CMAGIC diagram and $ω_{XY}$. These results may be used to our advantage, as they are less affected by extinction than parameters defined as a function of time. Additionally, $ω_{XY}$ is computed independently of templates. We find that current empirical templates are successful at reproducing the features described in this work, particularly SALT3, which correctly exhibits the negative correlation between slope and bump size seen in our data. In 1-D simulations, we show that the correlation between the size of the bump feature and $β_{XY, 1}$ can be understood as a result of chemical mixing due to large-scale Rayleigh-Taylor instabilities.

astro-ph.SR↗

arXiv2022

A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series

We construct a physically-parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an Auto-Encoder (AE) which is interpreted probabilistically after training using a Normalizing Flow (NF). We demonstrate that the PAE learns a low-dimensional latent space that captures the nonlinear range of features that exists within the population, and can accurately model the spectral evolution of SNe Ia across the full range of wavelength and observation times directly from the data. By introducing a correlation penalty term and multi-stage training setup alongside our physically-parameterized network we show that intrinsic and extrinsic modes of variability can be separated during training, removing the need for the additional models to perform magnitude standardization. We then use our PAE in a number of downstream tasks on SNe Ia for increasingly precise cosmological analyses, including automatic detection of SN outliers, the generation of samples consistent with the data distribution, and solving the inverse problem in the presence of noisy and incomplete data to constrain cosmological distance measurements. We find that the optimal number of intrinsic model parameters appears to be three, in line with previous studies, and show that we can standardize our test sample of SNe Ia with an RMS of $0.091 \pm 0.010$ mag, which corresponds to $0.074 \pm 0.010$ mag if peculiar velocity contributions are removed. Trained models and codes are released at \href{https://github.com/georgestein/suPAErnova}{github.com/georgestein/suPAErnova}

astro-ph.CO↗

arXiv2022

Uniform Recalibration of Common Spectrophotometry Standard Stars onto the CALSPEC System using the SuperNova Integral Field Spectrograph

We calibrate spectrophotometric optical spectra of 32 stars commonly used as standard stars, referenced to 14 stars already on the HST-based CALSPEC flux system. Observations of CALSPEC and non-CALSPEC stars were obtained with the SuperNova Integral Field Spectrograph over the wavelength range 3300 A to 9400 A as calibration for the Nearby Supernova Factory cosmology experiment. In total, this analysis used 4289 standard-star spectra taken on photometric nights. As a modern cosmology analysis, all pre-submission methodological decisions were made with the flux scale and external comparison results blinded. The large number of spectra per star allows us to treat the wavelength-by-wavelength calibration for all nights simultaneously with a Bayesian hierarchical model, thereby enabling a consistent treatment of the Type Ia supernova cosmology analysis and the calibration on which it critically relies. We determine the typical per-observation repeatability (median 14 mmag for exposures >~ 5 s), the Maunakea atmospheric transmission distribution (median dispersion of 7 mmag with uncertainty 1 mmag), and the scatter internal to our CALSPEC reference stars (median of 8 mmag). We also check our standards against literature filter photometry, finding generally good agreement over the full 12-magnitude range. Overall, the mean of our system is calibrated to the mean of CALSPEC at the level of ~ 3 mmag. With our large number of observations, careful crosschecks, and 14 reference stars, our results are the best calibration yet achieved with an integral-field spectrograph, and among the best calibrated surveys.

astro-ph.IM↗

arXiv2021

A Reference Survey for Supernova Cosmology with the Nancy Grace Roman Space Telescope

This note presents an initial survey design for the Nancy Grace Roman High-latitude Time Domain Survey. This is not meant to be a final or exhaustive list of all the survey strategy choices, but instead presents a viable path towards achieving the desired precision and accuracy of dark energy measurements using Type Ia supernovae (SNe Ia). We describe a survey strategy that use six filters (RZYJH and F) and the prism on the Roman Wide Field Instrument. This survey has two tiers, one "wide" which targets SNe Ia at redshifts up to 1 and one "deep" targeting redshifts up to 1.7; for each, four filters are used (with Y and J used in both tiers). We propose one field each in the north and south continuous viewing zones, and expect to obtain high-quality distances of $\sim$12,000 SNe Ia with $\sim$5,000 at z > 1. We propose a wide-tier area of $\sim$19 deg$^2$ and a deep tier of $\sim$5 deg$^2$. Exposure times range from 100 s to 900 s for imaging and 900 s to 3600 s for the prism. These exposure times would reach $\sim$25.5 mag and $\sim$26.5 mag for the wide and deep tiers respectively, with deep co-add stacks reaching $\sim$28 mag and $\sim$29 mag. The total survey spans two years, with a total allocation time of six months, and a cadence of $\sim$5 days.

astro-ph.CO↗

arXiv2021

The Twins Embedding of Type Ia Supernovae II: Improving Cosmological Distance Estimates

We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the "Twins Embedding". In this article, we discuss how the Twins Embedding can be used to improve the standardization of SNe Ia. With a single spectrophotometrically-calibrated spectrum near maximum light, we can standardize our sample of SNe Ia with an RMS of $0.101 \pm 0.007$ mag, which corresponds to $0.084 \pm 0.009$ mag if peculiar velocity contributions are removed and $0.073 \pm 0.008$ mag if a larger reference sample were obtained. Our techniques can standardize the full range of SNe Ia, including those typically labeled as peculiar and often rejected from other analyses. We find that traditional light curve width + color standardization such as SALT2 is not sufficient. The Twins Embedding identifies a subset of SNe Ia including but not limited to 91T-like SNe Ia whose SALT2 distance estimates are biased by $0.229 \pm 0.045$ mag. Standardization using the Twins Embedding also significantly decreases host-galaxy correlations. We recover a host mass step of $0.040 \pm 0.020$ mag compared to $0.092 \pm 0.024$ mag for SALT2 standardization on the same sample of SNe Ia. These biases in traditional standardization methods could significantly impact future cosmology analyses if not properly taken into account.

astro-ph.CO↗

arXiv2021

The Twins Embedding of Type Ia Supernovae I: The Diversity of Spectra at Maximum Light

We study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin" SNe Ia. We call this parameterization the "Twins Embedding". Our methodology naturally handles highly nonlinear variability in spectra, such as changes in the photosphere expansion velocity, and uses the full spectrum rather than being limited to specific spectral line strengths, ratios or velocities. We find that the time evolution of SNe Ia near maximum light is remarkably similar, with 84.6% of the variance in common to all SNe Ia. After correcting for brightness and color, the intrinsic variability of SNe Ia is mostly restricted to specific spectral lines, and we find intrinsic dispersions as low as ~0.02 mag between 6600 and 7200 A. With a nonlinear three-dimensional model plus one dimension for color, we can explain 89.2% of the intrinsic diversity in our sample of SNe Ia, which includes several different kinds of "peculiar" SNe Ia. A linear model requires seven dimensions to explain a comparable fraction of the intrinsic diversity. We show how a wide range of previously-established indicators of diversity in SNe Ia can be recovered from the Twins Embedding. In a companion article, we discuss how these results an be applied to standardization of SNe Ia for cosmology.

astro-ph.CO↗

arXiv2020

Strong Dependence of Type Ia Supernova Standardization on the Local Specific Star Formation Rate

As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization of Type Ia supernovae (SNIa) for cosmology, we have statistically classified a large sample of nearby SNeIa into those located in predominantly younger or older environments. This classification is based on the specific star formation rate measured within a projected distance of 1kpc from each SN location (LsSFR). This is an important refinement compared to using the local star formation rate directly as it provides a normalization for relative numbers of available SN progenitors and is more robust against extinction by dust. We find that the SNeIa in predominantly younger environments are DY=0.163\pm0.029 mag (5.7 sigma) fainter than those in predominantly older environments after conventional light-curve standardization. This is the strongest standardized SN Ia brightness systematic connected to host-galaxy environment measured to date. The well-established step in standardized brightnesses between SNeIa in hosts with lower or higher total stellar masses is smaller at DM=0.119\pm0.032 mag (4.5 sigma), for the same set of SNeIa. When fit simultaneously, the environment age offset remains very significant, with DY=0.129\pm0.032 mag (4.0 sigma), while the global stellar mass step is reduced to DM=0.064\pm0.029 mag (2.2 sigma). Thus, approximately 70% of the variance from the stellar mass step is due to an underlying dependence on environment-based progenitor age. Standardization using only the SNeIa in younger environments reduces the total dispersion from 0.142\pm0.008 mag to 0.120\pm0.010 mag. We show that as environment ages evolve with redshift a strong bias on measurement of the dark energy equation of state parameters can develop. Fortunately, data to measure and correct for this effect is likely to be available for many next-generation experiments. [abstract shorten]

astro-ph.CO↗

arXiv2020

Multiplicity distribution in pseudo-rapidity windows and charge conservation

Charged multiplicity distribution in a pseudo-rapidity window is formulated under the assumption that the charge conservation is satisfied in the full phase space. At first, we analyze measured charged particle multiplicity distributions in pseudo-rapidity windows in LHC by CMS and ALICE collaborations with the two probability distributions. One is the convolution of negative binomial and Poisson distributions, and the other is the Glauber-Lachs formula. Each distribution is considered as an analogy of the quantum optics. Next, we analyze the data with the double GL formulae for $|η|<2.4$ at 7 TeV by the CMS collaboration and for $|η|<1.5$ at 8 TeV by the ALICE collaboration to describe the global structure of measured distributions.

hep-ph↗

arXiv2020

The SNEMO and SUGAR Companion Datasets

The Nearby Supernova Factory has made spectrophotometric observations of Type Ia supernovae since $2004$. This work presents an interim version of the data produced, including $210$ supernovae observed between $2004$ and $2013$.

astro-ph.CO↗

arXiv2019

SUGAR: An improved empirical model of Type Ia Supernovae based on spectral features

Type Ia Supernovae (SNe Ia) are widely used to measure the expansion of the Universe. Improving distance measurements of SNe Ia is one technique to better constrain the acceleration of expansion and determine its physical nature. This document develops a new SNe Ia spectral energy distribution (SED) model, called the SUpernova Generator And Reconstructor (SUGAR), which improves the spectral description of SNe Ia, and consequently could improve the distance measurements. This model is constructed from SNe Ia spectral properties and spectrophotometric data from The Nearby Supernova Factory collaboration. In a first step, a PCA-like method is used on spectral features measured at maximum light, which allows us to extract the intrinsic properties of SNe Ia. Next, the intrinsic properties are used to extract the average extinction curve. Third, an interpolation using Gaussian Processes facilitates using data taken at different epochs during the lifetime of a SN Ia and then projecting the data on a fixed time grid. Finally, the three steps are combined to build the SED model as a function of time and wavelength. This is the SUGAR model. The main advancement in SUGAR is the addition of two additional parameters to characterize SNe Ia variability. The first is tied to the properties of SNe Ia ejecta velocity, the second is correlated with their calcium lines. The addition of these parameters, as well as the high quality the Nearby Supernova Factory data, makes SUGAR an accurate and efficient model for describing the spectra of normal SNe Ia as they brighten and fade. The performance of this model makes it an excellent SED model for experiments like ZTF, LSST or WFIRST.

astro-ph.CO↗

arXiv2018

SNEMO: Improved Empirical Models for Type Ia Supernovae

Type Ia supernova cosmology depends on the ability to fit and standardize observations of supernova magnitudes with an empirical model. We present here a series of new models of Type Ia Supernova spectral time series that capture a greater amount of supernova diversity than possible with the models that are currently customary. These are entitled SuperNova Empirical MOdels (\textsc{SNEMO}\footnote{https://snfactory.lbl.gov/snemo}). The models are constructed using spectrophotometric time series from $172$ individual supernovae from the Nearby Supernova Factory, comprising more than $2000$ spectra. Using the available observations, Gaussian Processes are used to predict a full spectral time series for each supernova. A matrix is constructed from the spectral time series of all the supernovae, and Expectation Maximization Factor Analysis is used to calculate the principal components of the data. K-fold cross-validation then determines the selection of model parameters and accounts for color variation in the data. Based on this process, the final models are trained on supernovae that have been dereddened using the Fitzpatrick and Massa extinction relation. Three final models are presented here: \textsc{SNEMO2}, a two-component model for comparison with current Type~Ia models; \textsc{SNEMO7}, a seven component model chosen for standardizing supernova magnitudes which results in a total dispersion of $0.100$~mag for a validation set of supernovae, of which $0.087$~mag is unexplained (a total dispersion of $0.113$~mag with unexplained dispersion of $0.097$~mag is found for the total set of training and validation supernovae); and \textsc{SNEMO15}, a comprehensive $15$ component model that maximizes the amount of spectral time series behavior captured.

astro-ph.CO↗