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DOE OSTI2014

Accelerated evolution of the Lyα luminosity function at z ≳ 7 revealed by the Subaru ultra-deep survey for Lyα emitters at z = 7.3

We present the ultra-deep Subaru narrowband imaging survey for Lyα emitters (LAEs) at z = 7.3 in the Subaru/XMM-Newton Deep Survey (SXDS) and Cosmic Evolution Survey (COSMOS) fields (∼0.5 deg{sup 2}) with a total integration time of 106 hr. Exploiting our new sharp bandwidth filter, NB101, installed on the Suprime-Cam, we have reached L(Lyα) = 2.4 × 10{sup 42} erg s{sup –1} (5σ) for z = 7.3 LAEs, about four times deeper than previous Subaru z ≳ 7 studies, which allows us to reliably investigate the evolution of the Lyα luminosity function (LF) for the first time down to the luminosity limit same as those of Subaru z = 3.1-6.6 LAE samples. Surprisingly, we only find three and four LAEs in the SXDS and COSMOS fields, respectively, while one expects a total of ∼65 LAEs by our survey in the case of no Lyα LF evolution from z = 6.6 to 7.3. We identify a decrease of the Lyα LF from z = 6.6 to 7.3 at the >90% confidence level from our z = 7.3 Lyα LF with the best-fit Schechter parameters of L{sub Lyα}{sup ∗}=2.7{sub −1.2}{sup +8.0}×10{sup 42} erg s{sup −1} and ϕ{sup ∗}=3.7{sub −3.3}{sup +17.6}×10{sup −4} Mpc{sup −3} for a fixed α = –1.5. Moreover, the evolution of the Lyα LF is clearly accelerated at z > 6.6 beyond the measurement uncertainties including cosmic variance. Because no such accelerated evolution of the UV-continuum LF or the cosmic star formation rate (SFR) is found at z ∼ 7, but suggested only at z > 8, this accelerated Lyα LF evolution is explained by physical mechanisms different from a pure SFR decrease but related to the Lyα production and escape in the process of cosmic reionization. Because a simple accelerating increase of intergalactic medium neutral hydrogen absorbing Lyα cannot be reconciled with Thomson scattering of optical depth measurements from WMAP and Planck, our findings may support new physical pictures suggested by recent theoretical studies, such as the existence of HI clumpy clouds within cosmic ionized bubbles that are selectively absorbing Lyα and the large ionizing photon escape fraction of galaxies causing weak Lyα emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g {sub P1}, r {sub P1}, i {sub P1}, and z {sub P1}. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A deep Hubble Space Telescope and KECK search for definitive identification of Lyman continuum emitters at cic>∼3.1

Narrowband imaging of the rest-frame Lyman continuum (LyC) of galaxies at z∼3.1 has produced a large number of candidate LyC-emitting galaxies. These samples are contaminated by galaxies at lower redshift. To better understand LyC escape, we need an uncontaminated sample of galaxies that emit strongly in the LyC. Here we present deep Hubble Space Telescope imaging of five bright galaxies at z∼3.1 that had previously been identified as candidate LyC emitters with ground-based images. The WFC3 F336W images probe the LyC of galaxies at z>3.06 and provide an order-of-magnitude increase in spatial resolution over ground-based imaging. The non-ionizing UV images often show multiple galaxies (or components) within ∼1{sup ′′} of the candidate LyC emission seen from the ground. In each case, only one of the components is emitting light in the F336W filter, which would indicate LyC escape if that component is at z>3.06. We use Keck/NIRSPEC near-IR spectroscopy to measure redshifts of these components to distinguish LyC emitters from foreground contamination. We find that two candidates are low-redshift contaminants, one candidate had a previously misidentified redshift, and the other two cannot be confirmed as LyC emitters. The level of contamination is consistent with previous estimates. For the galaxies with z>3.06, we derive strong 1σ limits on the relative escape fraction between 0.07 and 0.09. We still do not have a sample of definitive LyC emitters, and a much larger study of low-luminosity galaxies is required. The combination of high-resolution imaging and deep spectroscopy is critical for distinguishing LyC emitters from foreground contaminants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A DEEP NARROWBAND IMAGING SEARCH FOR C iv AND He ii EMISSION FROM Lyα BLOBS

We conduct a deep narrowband imaging survey of 13 Lyα blobs (LABs) located in the SSA22 proto-cluster at z ∼ 3.1 in the C iv and He ii emission lines in an effort to constrain the physical process powering the Lyα emission in LABs. Our observations probe down to unprecedented surface brightness (SB) limits of (2.1–3.4) × 10{sup −18} erg s{sup −1} cm{sup −2} arcsec{sup −2} per 1 arcsec{sup 2} aperture (5σ) for the He ii λ1640 and C iv λ1549 lines, respectively. We do not detect extended He ii and C iv emission in any of the LABs, placing strong upper limits on the He ii/Lyα and C iv/Lyα line ratios, of 0.11 and 0.16, for the brightest two LABs in the field. We conduct detailed photoionization modeling of the expected line ratios and find that, although our data constitute the deepest ever observations of these lines, they are still not deep enough to rule out a scenario where the Lyα emission is powered by the ionizing radiation from an obscured active galactic nucleus. Our models can accommodate He ii/Lyα and C iv/Lyα ratios as low as ≃0.05 and ≃0.07, respectively, implying that one needs to reach SB as low as (1–1.5) × 10{sup −18} erg s{sup −1} cm{sup −2} arcsec{sup −2} (at 5σ) in order to rule out a photoionization scenario. These depths will be achievable with the new generation of image-slicing integral field units such as the Multi Unit Spectroscopic Explorer (MUSE) on VLT and the Keck Cosmic Web Imager (KCWI). We also model the expected He ii/Lyα and C iv/Lyα in a different scenario, where Lyα emission is powered by shocks generated in a large-scale superwind, but find that our observational constraints can only be met for shock velocities v{sub s} ≳ 250 km s{sup −1}, which appear to be in conflict with recent observations of quiescent kinematics in LABs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE MINIMUM OF SOLAR CYCLE 23: AS DEEP AS IT COULD BE?

In this work we introduce a new way of binning sunspot group data with the purpose of better understanding the impact of the solar cycle on sunspot properties and how this defined the characteristics of the extended minimum of cycle 23. Our approach assumes that the statistical properties of sunspots are completely determined by the strength of the underlying large-scale field and have no additional time dependencies. We use the amplitude of the cycle at any given moment (something we refer to as activity level) as a proxy for the strength of this deep-seated magnetic field. We find that the sunspot size distribution is composed of two populations: one population of groups and active regions and a second population of pores and ephemeral regions. When fits are performed at periods of different activity level, only the statistical properties of the former population, the active regions, are found to vary. Finally, we study the relative contribution of each component (small-scale versus large-scale) to solar magnetism. We find that when hemispheres are treated separately, almost every one of the past 12 solar minima reaches a point where the main contribution to magnetism comes from the small-scale component. However, due to asymmetries in cycle phase, this state is very rarely reached by both hemispheres at the same time. From this we infer that even though each hemisphere did reach the magnetic baseline, from a heliospheric point of view the minimum of cycle 23 was not as deep as it could have been.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE EVOLUTION OF THE FAR-UV LUMINOSITY FUNCTION AND STAR FORMATION RATE DENSITY OF THE CHANDRA DEEP FIELD SOUTH FROM z = 0.2 TO 1.2 WITH SWIFT/UVOT

We use deep Swift UV/Optical Telescope (UVOT) near-ultraviolet (1600–4000 Å) imaging of the Chandra Deep Field South to measure the rest-frame far-UV (FUV; 1500 Å) luminosity function (LF) in four redshift bins between z = 0.2 and 1.2. Our sample includes 730 galaxies with u < 24.1 mag. We use two methods to construct and fit the LFs: the traditional V{sub max} method with bootstrap errors, and a maximum likelihood estimator. We observe luminosity evolution such that M* fades by ∼2 mag from z ∼ 1 to z ∼ 0.3, implying that star formation activity was substantially higher at z ∼ 1 than today. We integrate our LFs to determine the FUV luminosity densities and star formation rate densities (SFRDs) from z = 0.2 to 1.2. We find evolution consistent with an increase proportional to (1 + z){sup 1.9} out to z ∼ 1. Our luminosity densities and star formation rates are consistent with those found in the literature but are, on average, a factor of ∼2 higher than previous FUV measurements. In addition, we combine our UVOT data with the MUSYC survey to model the galaxies’ ultraviolet-to-infrared spectral energy distributions and estimate the rest-frame FUV attenuation. We find that accounting for the attenuation increases the SFRDs by ∼1 dex across all four redshift bins.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE VERY LARGE ARRAY 1.4 GHz SURVEY OF THE EXTENDED CHANDRA DEEP FIELD SOUTH: SECOND DATA RELEASE

Deep radio observations at 1.4 GHz for the Extended Chandra Deep Field South were performed in 2007 June through September and presented in a first data release. The survey was made using six separate pointings of the Very Large Array with over 40 hr of observation per pointing. In the current paper, we improve on the data reduction to produce a second data release (DR2) mosaic image. This DR2 image covers an area of about a third of a square degree, reaches a best rms sensitivity of 6 {mu}Jy, and has a typical sensitivity of 7.4 {mu}Jy per 2.''8 by 1.''6 beam. We also present a more comprehensive catalog, including sources down to peak flux densities of five or more times the local rms noise along with information on source sizes and relevant pointing data. We discuss in some detail the consideration of whether sources are resolved under the complication of a radio image created as a mosaic of separate pointings each suffering some degree of bandwidth smearing, and the accurate evaluation of the flux densities of such sources. Finally, the radio morphologies and optical/near-IR counterpart identifications are used to identify 17 likely multiple-component sources and arrive at a catalog of 883 radio sources, which is roughly double the number of sources contained in the first data release.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

PHOTOMETRIC REDSHIFTS IN THE HAWAII-HUBBLE DEEP FIELD-NORTH (H-HDF-N)

We derive photometric redshifts (z {sub phot}) for sources in the entire (∼0.4 deg{sup 2}) Hawaii-Hubble Deep Field-North (H-HDF-N) field with the EAzY code, based on point-spread-function-matched photometry of 15 broad bands from the ultraviolet (U band) to mid-infrared (IRAC 4.5 μm). Our catalog consists of a total of 131,678 sources. We evaluate the z {sub phot} quality by comparing z {sub phot} with spectroscopic redshifts (z {sub spec}) when available, and find a value of normalized median absolute deviation σ{sub NMAD} = 0.029 and an outlier fraction of 5.5% (outliers are defined as sources having |z{sub phot} – z{sub spec} |/(1 + z{sub spec} ) > 0.15) for non-X-ray sources. More specifically, we obtain σ{sub NMAD} = 0.024 with 2.7% outliers for sources brighter than R = 23 mag, σ{sub NMAD} = 0.035 with 7.4% outliers for sources fainter than R = 23 mag, σ{sub NMAD} = 0.026 with 3.9% outliers for sources having z < 1, and σ{sub NMAD} = 0.034 with 9.0% outliers for sources having z > 1. Our z {sub phot} quality shows an overall improvement over an earlier z {sub phot} work that focused only on the central H-HDF-N area. We also classify each object as a star or galaxy through template spectral energy distribution fitting and complementary morphological parameterization, resulting in 4959 stars and 126,719 galaxies. Furthermore, we match our catalog with the 2 Ms Chandra Deep Field-North main X-ray catalog. For the 462 matched non-stellar X-ray sources (281 having z {sub spec}), we improve their z {sub phot} quality by adding three additional active galactic nucleus templates, achieving σ{sub NMAD} = 0.035 and an outlier fraction of 12.5%. We make our catalog publicly available presenting both photometry and z {sub phot}, and provide guidance on how to make use of our catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

Abstract Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model’s ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Engineering↗
DOE OSTI2022

Automatic Detection and Classification of Radio Galaxy Images by Deep Learning

Abstract Surveys conducted by radio astronomy observatories, such as SKA, MeerKAT, Very Large Array, and ASKAP, have generated massive astronomical images containing radio galaxies (RGs). This generation of massive RG images has imposed strict requirements on the detection and classification of RGs and makes manual classification and detection increasingly difficult, even impossible. Rapid classification and detection of images of different types of RGs help astronomers make full use of the observed astronomical image data for further processing and analysis. The classification of FRI and FRII is relatively easy, and there are more studies and literature on them at present, but FR0 and FRI are similar, so it is difficult to distinguish them. It poses a greater challenge to image processing. At present, deep learning has made breakthrough progress in the field of image analysis and processing and has preliminary applications in astronomical data processing. Compared with classification algorithms that can only classify galaxies, object detection algorithms that can locate and classify RGs simultaneously are preferred. In target detection algorithms, YOLOv5 has outstanding advantages in the classification and positioning of small targets. Therefore, we propose a deep-learning method based on an improved YOLOv5 object detection model that makes full use of multisource data, combining FIRST radio with SDSS optical image data, and realizes the automatic detection of FR0, FRI, and FRII RGs. The innovation of our work is that on the basis of the original YOLOv5 object detection model, we introduce the SE Net attention mechanism, increase the number of preset anchors, adjust the network structure of the feature pyramid, and modify the network structure, thereby allowing our model to demonstrate galaxy classification and position detection effects. Our improved model produces satisfactory results, as evidenced by experiments. Overall, the mean average precision (mAP@0.5) of our improved model on the test set reaches 89.4%, which can determine the position (R.A. and decl.) and automatically detect and classify FR0s, FRIs, and FRIIs. Our work contributes to astronomy because it allows astronomers to locate FR0, FRI, and FRII galaxies in a relatively short time and can be further combined with other astronomically generated data to study the properties of these galaxies. The target detection model can also help astronomers find FR0s, FRIs, and FRIIs in future surveys and build a large-scale star RG catalog. Moreover, our work is also useful for the detection of other types of galaxies.

Astronomy & Astrophysics↗
DOE OSTI2017

Background rejection in NEXT using deep neural networks

Here, we investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Volume I. Introduction to DUNE

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE's physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Volume III. DUNE far detector technical coordination

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Electromagnetic shower reconstruction and energy validation with Michel electrons and π 0 samples for the deep-learning-based analyses in MicroBooNE

This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two v μ -sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Finally, the absolute shower energy scale is shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Methane emission hotspots in a boreal forest-fen mosaic potentially linked to deep taliks

Permafrost thaw is transforming boreal forests into mosaics of wetlands and drier uplands. Topographic controls on hydrological and ecological conditions impact methane (CH 4 ) fluxes, contributing to uncertainty in local and regional CH 4 budgets and underlying drivers. The objective of this study was to explore CH 4 fluxes and their drivers in a transitioning boreal forest-fen ecosystem (Goldstream Valley, Alaska, USA). This landscape is characterized by thawing discontinuous permafrost and heterogeneous mosaics of fens, collapse-scar channels, and small mounds of permafrost soils. From a survey in July 2021, observed chamber CH4 fluxes included fen areas with intermediate to very high emissions (29.8–635.3 mg CH 4 m −2 d −1 ), clustered locations with CH 4 uptake (−2.11 to −0.7 mg CH 4 m −2 d −1 ), and three anomalous emission hotspots (342.4–772.4 mg CH 4 m −2 d −1 ) that were located near samples with lower emissions. Some surface and near-surface variables partially explained the spatial variation in CH 4 flux. Log-transformed CH 4 flux had a positive linear relationship with soil moisture at 20 cm depth ( R 2 = 0.31, p -value < 1e-5) and negative linear relationships with microtopography ( R 2 = 0.13, p -value < 0.006) and slope ( R 2 = 0.28, p -value < 2e-5). Methane emissions generally occurred in flat, wet, graminoid-dominated fens, whereas CH 4 uptake occurred on permafrost mounds dominated by feather mosses and woody vegetation. However, the CH 4 hotspots occurred on drier, slightly sloped locations with low or undetectable near-surface methanogen abundance, suggesting that CH 4 was produced in deeper soils. When the hotspot samples were omitted, log-transformed CH 4 flux had a positive linear relationship with near-surface methanogen abundance ( R 2 = 0.29, p -value = 0.0023), and stronger linear relationships with soil moisture, slope, and soil macronutrient concentrations. Our findings suggest that some CH 4 emission hotspots could arise from CH 4 in deep taliks. The inference that methanogenesis occurs in deep taliks was strengthened by the identification of intrapermafrost taliks across the study area using low-frequency geophysical induction. This study assesses surface spatial heterogeneity in the context of subsurface permafrost conditions and highlights the complexity of CH 4 flux patterns in transitioning forest-wetland ecosystems. To better inform regional CH 4 budgets, further research is needed to understand the spatial distribution of terrestrial CH 4 hotspots and to resolve their surface, near-surface, and subsurface drivers.

boreal↗
DOE OSTI2013

DEEP LBT/LUCI SPECTROSCOPY OF AN Ly{alpha} EMITTER CANDIDATE AT z {approx_equal} 7.7

We present deep spectroscopic observations of an Ly{alpha} emitter (LAE) candidate at z {approx_equal} 7.7 using the infrared spectrograph LUCI on the 2 Multiplication-Sign 8.4 m Large Binocular Telescope (LBT). The candidate is the brightest among the four z {approx_equal} 7.7 LAE candidates found in a narrowband imaging survey by Krug et al. Our spectroscopic data include a total of 7.5 hr of integration with LBT/LUCI and are deep enough to significantly (3.2{sigma}-4.9{sigma}) detect the Ly{alpha} emission line of this candidate based on its Ly{alpha} flux 1.2 Multiplication-Sign 10{sup -17} erg s{sup -1} cm{sup -2} estimated from the narrowband photometry. However, we do not find any convincing signal at the expected position of its Ly{alpha} emission line, suggesting that this source is not an LAE at z {approx_equal} 7.7. The non-detection in this work, together with the previous studies of z {approx_equal} 7.7 LAEs, puts a strong constraint on the bright-end Ly{alpha} luminosity function (LF) at z {approx_equal} 7.7. We find a rapid evolution of the Ly{alpha} LF from z {approx_equal} 6.5 to 7.7: the upper limit of the z {approx_equal} 7.7 LF is more than five times lower than the z {approx_equal} 6.5 LF at the bright end (f{>=} 1.0 Multiplication-Sign 10{sup -17} erg s{sup -1} cm{sup -2} or L{>=} 6.9 Multiplication-Sign 10{sup 42} erg s{sup -1}). This is likely caused by an increasing neutral fraction in the intergalactic medium that substantially attenuates Ly{alpha} emission at z {approx_equal} 7.7.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE SPECTRAL ENERGY DISTRIBUTIONS OF z ∼ 8 GALAXIES FROM THE IRAC ULTRA DEEP FIELDS: EMISSION LINES, STELLAR MASSES, AND SPECIFIC STAR FORMATION RATES AT 650 MYR

Using new ultradeep Spitzer/InfraRed Array Camera (IRAC) photometry from the IRAC Ultra Deep Field program, we investigate the stellar populations of a sample of 63 Y-dropout galaxy candidates at z ∼ 8, only 650 Myr after the big bang. The sources are selected from HST/ACS+WFC3/IR data over the Hubble Ultra Deep Field (HUDF), two HUDF parallel fields, and wide area data over the CANDELS/GOODS-South. The new Spitzer/IRAC data increase the coverage in [3.6] and [4.5] to ∼120h over the HUDF reaching depths of ∼28 (AB,1σ). The improved depth and inclusion of brighter candidates result in direct ≥3σ InfraRed Array Camera (IRAC) detections of 20/63 sources, of which 11/63 are detected at ≥5σ. The average [3.6]-[4.5] colors of IRAC detected galaxies at z ∼ 8 are markedly redder than those at z ∼ 7, observed only 130 Myr later. The simplest explanation is that we witness strong rest-frame optical emission lines (in particular [O III] λλ4959, 5007 + Hβ) moving through the IRAC bandpasses with redshift. Assuming that the average rest-frame spectrum is the same at both z ∼ 7 and z ∼ 8 we estimate a rest-frame equivalent width of contributing 0.56{sup +0.16}{sub -0.11} mag to the [4.5] filter at z ∼ 8. The corresponding W{sub Hα}=430{sup +160}{sub -110} Å implies an average specific star formation rate of sSFR=11{sub -5}{sup +11} Gyr{sup –1} and a stellar population age of 100{sub -50}{sup +100} Myr. Correcting the spectral energy distribution for the contribution of emission lines lowers the average best-fit stellar masses and mass-to-light ratios by ∼3 ×, decreasing the integrated stellar mass density to ρ{sup *}(z=8,M{sub UV}<-18)=0.6{sup +0.4}{sub -0.3}×10{sup 6} M{sub sun} Mpc{sup –3}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The deep-acceptor nature of the chalcogen vacancies in 2D transition-metal dichalcogenides

Abstract Chalcogen vacancies in the semiconducting monolayer transition-metal dichalcogenides (TMDs) have frequently been invoked to explain a wide range of phenomena, including both unintentional p-type and n-type conductivity, as well as sub-band gap defect levels measured via tunneling or optical spectroscopy. These conflicting interpretations of the deep versus shallow nature of the chalcogen vacancies are due in part to shortcomings in prior first-principles calculations of defects in the semiconducting two-dimensional TMDs that have been used to explain experimental observations. Here we report results of hybrid density functional calculations for the chalcogen vacancy in a series of monolayer TMDs, correctly referencing the thermodynamic charge transition levels to the fundamental band gap (as opposed to the optical band gap). We find that the chalcogen vacancies are deep acceptors and cannot lead to n-type or p-type conductivity. Both the (0/−1) and (−1/−2) transition levels occur in the gap, leading to paramagnetic charge states S = 1 / 2 and S = 1, respectively, in a collinear-spin representation. We discuss trends in terms of the band alignments between the TMDs, which can serve as a guide to future experimental studies of vacancy behavior.

36 MATERIALS SCIENCE↗