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At least 397 records · Page 22

The Dark Energy Survey Year 3 high-redshift sample: selection, characterization, and analysis of galaxy clustering

ABSTRACT The fiducial cosmological analyses of imaging surveys like DES typically probe the Universe at redshifts z < 1. We present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around z ∼ 0.9, 1.2, and 1.5, which extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal to noise S/N ∼ 70 after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe Ωm and the Hubble parameter h, $\Omega _m h = 0.195^{+0.023}_{-0.018}$, and 2–3 per cent measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, bσ8. A companion paper (in preparation) will present the cross-correlations of these high-z samples with cosmic microwave background lensing from Planck and South Pole Telescope, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Gradient-based surface nuclear magnetic resonance for groundwater investigation

In medical magnetic resonance imaging, spatial localization (imaging) is based upon the application of controlled magnetic field gradients on top of the main magnetic field to spatially modulate the frequency and/or phase of the nuclear magnetic resonance (NMR) signal across the volume of investigation. In this work, we have applied similar physical principles to produce controlled magnetic field gradients during surface NMR-based groundwater investigations. In this approach, a gradient pulse of variable amplitude or duration is applied immediately after the excitation pulse to cause predictable phase encoding of the NMR signal as a function of depth. This approach is also applicable to emerging surface NMR detection methods that use a prepolarization field with fast nonadiabatic turn-off to generate detectable NMR signals from the shallow subsurface. In this case, the gradient pulse is applied after terminating the prepolarization field and provides a heretofore unavailable means of localizing the NMR response as a function of depth. The application of gradients can also be combined with tip-angle-based modulation to yield higher imaging resolution than can be achieved through either gradient- or tip-angle-based imaging alone. We implemented this new gradient-based capability into a surface NMR gradient generation accessory that is compatible with the GMR-Flex instrument and developed surface NMR-specific forward modeling and linear inverse models. We validated the accuracy of this novel gradient-based sNMR technology using computer simulations, experiments using a small pool filled with a discrete layer of bulk water, and field experiments at well-characterized groundwater test sites along Ebey Island, WA, and Larned, KS. The gradient-based sNMR imaging observations were compared with high-resolution direct push NMR results observed at these sites. The results of computer simulations and field experiments indicate improvements in both the detection (signal-to-noise ratio) and spatial resolution of shallow subsurface water content using gradient-based surface NMR, compared with traditional surface NMR imaging methods.

Geochemistry & Geophysics↗

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

58 GEOSCIENCES↗

Data Compression in the NEXT-100 Data Acquisition System

NEXT collaboration detectors are based on energy measured by an array of photomultipliers (PMT) and topological event filtering based on an array of silicon photomultipliers (SiPMs). The readout of the PMT sensors for low-frequency noise effects and detector safety issues requires a grounded cathode connection that makes the readout AC-couple with variations in the signal baseline. Strict detector requirements of energy resolution better than 1% FWHM require a precise baseline reconstruction that is performed offline for data analysis and detector performance characterization. Baseline variations make it inefficient to apply traditional lossy data compression techniques, such as zero-suppression, that help to minimize data throughput and, therefore, the dead time of the system. However, for the readout of the SiPM sensors with less demanding requirements in terms of accuracy, a traditional zero-suppression is currently applied with a configuration that allows for a compression ratio of around 71%. The third stage in the NEXT detectors program, the NEXT-100 detector, is a 100 kg detector that instruments approximately five times more PMT sensors and twice the number of SiPM sensors than its predecessor, the NEXT-White detector, putting more pressure in the DAQ throughput, expected to be over 900 MB/s with the current configuration, which will worsen the dead time of the acquisition data system. This paper describes the data compression techniques applied to the sensor data in the NEXT-100 detector, which reduces data throughput and minimizes dead time while maintaining the event rate to the level of its predecessor, around 50 Hz.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BACCHUS Analysis of Weak Lines in APOGEE Spectra (BAWLAS)

Elements with weak and blended spectral features in stellar spectra are challenging to measure and require specialized analysis methods to precisely measure their chemical abundances. In this work, we have created a catalog of approximately 120,000 giants with high signal-to-noise Apache Point Observatory Galactic Evolution Experiment (APOGEE) Data Release 17 (DR17) spectra, for which we explore weak and blended species to measure Na, P, S, V, Cu, Ce, and Nd abundances and 12 C/ 13 C isotopic ratios. We employ an updated version of the Brussels Automatic Code for Characterizing High-accuracy Spectra (BACCHUS) code to derive these abundances using the stellar parameters measured by APOGEE's DR17 Stellar Parameters and Chemical Abundances Pipeline, quality flagging to identify suspect spectral lines, and a prescription for upper limits. Combined, these allow us to provide our BACCHUS Analysis of Weak Lines in APOGEE Spectra catalog of precise chemical abundances for these weak and blended species, which agrees well with the literature and improves upon APOGEE abundances for these elements, some of which are unable to be measured with APOGEE's current, grid-based approach without computationally expensive expansions. This new catalog can be used alongside APOGEE and provides measurements for many scientific applications ranging from nuclear physics to Galactic chemical evolution and Milky Way population studies. To illustrate this we show some examples of uses for this catalog, such as showing that we observe stars with enhanced s-process abundances or that we can use the 12 C/ 13 C ratios to explore extra mixing along the red giant branch.

79 ASTRONOMY AND ASTROPHYSICS↗

Charge collection efficiency in back-illuminated Charge-Coupled Devices

Low noise CCDs fully-depleted up to 675 micrometers have been identified as a unique tool for Dark Matter searches and low energy neutrino physics. The charge collection efficiency (CCE) for these detectors is a critical parameter for the performance of future experiments. We present here a new technique to characterize CCE in back-illuminated CCDs based on soft X-rays. This technique is used to characterize two different detector designs. The results demonstrate the importance of the backside processing for detection near threshold, showing that a recombination layer of a few microns significantly distorts the low energy spectrum. The studies demonstrate that the region of partial charge collection can be reduced to less than 1 micrometer thickness with adequate backside processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A 1.2-V 6-GHz Dual-Path Charge-Pump PLL Frequency Synthesizer for Quantum Control and Readout in CMOS 65-nm Process

This paper presents a low jitter dual-path chargepump phase locked loop (PLL) synthesizer in a CMOS 65-nm process for quantum readout applications. The PLL incorporates a programmable dual chargepump and a loop filter with both proportional and integral paths that can be driven independently providing flexible control of the loop bandwidth to achieve low jitter performance. The design is implemented at 300 K and critical blocks like voltage-controlled oscillator (VCO) and chargepump (CP) are analyzed at 77 K based on the characterized results. The LC-VCO is realized with the class-C NMOS only architecture with 5-bit coarse control and quadrature signals are generated with poly phase filter. The VCO is designed with the tuning range of 1 GHz around the center frequency of 6 GHz with Phase Noise of -123 dBc/Hz and -132 dBc/Hz at 1MHz offset at 300 K and 77 K temperature. The simulated PLL rms jitter is 125 fs at 6 GHz with a power consumption of 8 mW at the 1.2 V power supply.

47 OTHER INSTRUMENTATION↗

Realization of a gas puff imaging system on the Wendelstein 7-X stellarator

A system for studying the spatiotemporal dynamics of fluctuations in the boundary of the W7-X plasma using the “Gas-Puff Imaging” (GPI) technique has been designed, constructed, installed, and operated. This GPI system addresses a number of challenges specific to long-pulse superconducting devices, such as W7-X, including the long distance between the plasma and the vacuum vessel wall, the long distance between the plasma and diagnostic ports, the range of last closed flux surface (LCFS) locations for different magnetic configurations in W7-X, and management of heat loads on the system’s plasma-facing components. The system features a pair of “converging–diverging” nozzles for partially collimating the gas puffed locally ≈135 mm radially outboard of the plasma boundary, a pop-up turning mirror for viewing the gas puff emission from the side (which also acts as a shutter for the re-entrant vacuum window), and a high-throughput optical system that collects visible emission resulting from the interaction between the puffed gas and the plasma and directs it along a water-cooled re-entrant tube directly onto the 8 × 16 pixel detector array of the fast camera. The DEGAS 2 neutral code was used to simulate the Hα (656 nm) and HeI (587 nm) line emission expected from well-characterized gas-puffs of H2 and He and excited within typical edge plasma profiles in W7-X, thereby predicting line brightnesses used to reduce the risks associated with system sensitivity and placement of the field of view. Operation of GPI on W7-X shows excellent signal-to-noise ratios (>100 at 2 Mframes/s) over the field of view for minimally perturbing gas puffs. The GPI system provides detailed measurements of the two-dimensional (radial and poloidal) dynamics of plasma fluctuations in the W7-X edge and scrape-off layer and in and around the magnetic islands outside the LCFS that make up the island divertor configuration employed on W7-X.

Instruments & Instrumentation↗

Nuclear Quadrupole Resonance for Substance Detection

This review paper provides a comprehensive overview of recent advances in nuclear quadrupole resonance (NQR) spectroscopy for substance detection, highlighting its principles, methodologies, and applications. The paper elucidates the fundamental physics underlying NQR spectroscopy, emphasizing the interaction between nuclear quadrupole moments and electric field gradients. It explores the various experimental techniques and instrumentation developments that have enabled the sensitive detection and precise characterization of substances containing quadrupolar nuclei. A significant portion of the survey is dedicated to discussing the diverse applications of NQR spectroscopy, including the detection of explosives, drug pharmaceuticals, and material authentication. Furthermore, the survey examines the challenges and limitations associated with NQR spectroscopy, including issues related to signal-to-noise ratio (SNR), temperature dependency, and substance restrictions. Strategies to overcome these challenges are discussed, offering insights into the future directions of NQR spectroscopy research that includes artificial intelligence (AI), internet of things (IoT) integration, incorporating a cloud database for NQR parameter storage, and multi-modal analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Single photon emitters in van der Waals solids for quantum photonics: materials, theory and molecular-scale characterization probes

Strong light–matter interactions in two-dimensional layered materials (2D materials) have attracted the interest of researchers from interdisciplinary fields for more than a decade now. A unique phenomenon in some 2D materials is their large exciton binding energies (BEs), increasing the likelihood of exciton survival at room temperature. It is this large BE that mediates the intense light–matter interactions of many of the 2D materials, particularly in their monolayer limit, where the interplay of excitonic phenomena poses a wealth of opportunities for high-performance optoelectronics and quantum photonics. Within quantum photonics, quantum information science (QIS) is growing rapidly, where photons are a promising platform for information processing due to their low-noise properties, excellent modal control, and long-distance propagation. A central element for QIS applications is a single photon emitter (SPE) source, where an ideal on-demand SPE emits exactly one photon at a time into a given spatiotemporal mode. Recently, 2D materials have shown practical appeal for QIS which is directly driven from their unique layered crystalline structure. This structural attribute of 2D materials facilitates their integration with optical elements more easily than the SPEs in conventional three-dimensional solid state materials, such as diamond and SiC. In this review article, we will discuss recent advances made with 2D materials towards their use as quantum emitters, where the SPE emission properties maybe modulated deterministically. Here, the use of unique scanning tunneling microscopy tools for the in-situ generation and characterization of defects is presented, along with theoretical first-principles frameworks and machine learning approaches to model the structure-property relationship of exciton–defect interactions within the lattice towards SPEs. Given the rapid progress made in this area, the SPEs in 2D materials are emerging as promising sources of nonclassical light emitters, well-poised to advance quantum photonics in the future.

2D layered materials↗

Prospects for Characterizing the Haziest Sub-Neptune Exoplanets with High-resolution Spectroscopy

Observations to characterize planets larger than Earth but smaller than Neptune have led to largely inconclusive interpretations at low spectral resolution due to hazes or clouds that obscure molecular features in their spectra. However, here we show that high-resolution spectroscopy (R ∼ 25,000–100,000) enables one to probe the regions in these atmospheres above the clouds where the cores of the strongest spectral lines are formed. We present models of transmission spectra for a suite of GJ 1214b–like planets with thick photochemical hazes covering 1–5 μm at a range of resolutions relevant to current and future ground-based spectrographs. Furthermore, we compare the utility of the cross-correlation function that is typically used with a more formal likelihood-based approach, finding that only the likelihood-based method is sensitive to the presence of haze opacity. We calculate the signal-to-noise ratio (S/N) of these spectra, including telluric contamination, Required to robustly detect a host of molecules such as CO, CO{sub 2}, H{sub 2}O, and CH{sub 4} and photochemical products like HCN as a function of wavelength range and spectral resolution. Spectra in the M band require the lowest S/N{sub res} to detect multiple molecules simultaneously. CH{sub 4} is only observable for the coolest models (T {sub eff} = 412 K) and only in the L band. We quantitatively assess how these requirements compare to what is achievable with current and future instruments, demonstrating that characterization of small cool worlds with ground-based high-resolution spectroscopy is well within reach.

79 ASTRONOMY AND ASTROPHYSICS↗

Generation and representation of synthetic smart meter data

Advanced energy algorithms running at big-data scale will be necessary to identify, realize, and verify energy savings to meet government and utility goals of building energy efficiency. Any algorithm must be well characterized and validated before it is trusted to run at these scales. Smart meter data from real buildings will ultimately be required for the development, testing, and validation of these energy algorithms and processes. However, for initial development and testing, smart meter data are difficult to work with due to privacy restrictions, noise from unknown sources, data accessibility, and other concerns which can complicate algorithm development and validation. This paper describes a new methodology to generate synthetic smart meter data of electricity use in buildings using detailed building energy modeling, which aims to capture the variability and stochastics of real energy use in buildings. The methodology can create datasets tailored to represent specific scenarios with known truth and controllable amounts of synthetic noise. Knowledge of ground truth also allows the development and validation of enhanced processes which leverage building metadata, such as building type or size (floor area), in addition to smart meter data. The methodology described in this paper includes the key influencing factors of real-world building energy use including weather data, occupant-driven loads, building operation and maintenance practices, and special events. Data formats to support workflows leveraging both synthetic meter data and associated metadata are proposed and discussed. Finally, example use cases of the synthetic meter data are described to illustrate potential applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Langevin dynamics of generalized spins as SU( N ) coherent states

Classical models of spin systems traditionally retain only the dipole moments, but a quantum spin state will frequently have additional structure. Spins of magnitude S have N = 2⁢S + 1 levels. Alternatively, the spin state is fully characterized by a set of N 2 - 1 local physical observables, which we interpret as generalized spin components. For example, a spin with S = 1 has three dipole components and five quadrupole components. Further, these components evolve under a generalization of the classical Landau-Lifshitz dynamics, which can be extended with noise and damping terms. In this paper, we reformulate the dynamical equations of motion as a Langevin dynamics of SU(N) coherent states in the Schrödinger picture. This viewpoint is especially useful as the basis for an efficient numerical method to sample spin configurations in thermal equilibrium and to simulate the relaxation and driven motion of topological solitons. To illustrate the approach, we simulate a nonequilibrium relaxation process that creates CP 2 skyrmions, which are topological defects with both dipole and quadrupole character.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantitative approaches for multiscale structural analysis with atomic resolution electron microscopy

Atomic-resolution imaging with scanning transmission electron microscopy is a powerful tool for characterizing the nanoscale structure of materials, in particular features such as defects, local strains, and symmetry-breaking distortions. In addition to advanced instrumentation, the effectiveness of the technique depends on computational image analysis to extract meaningful features from complex datasets recorded in experiments, which can be complicated by the presence of noise and artifacts, small or overlapping features, and the need to scale analysis over large representative areas. Here, we present image analysis approaches which synergize real and reciprocal space information to efficiently and reliably obtain meaningful structural information with picometer scale precision across hundreds of nanometers of material from atomic-resolution electron microscope images. Damping superstructure peaks in reciprocal space allows symmetry-breaking structural distortions to be disentangled from other sources of inhomogeneity and measured with high precision. Real-space fitting of the wavelike signals resulting from Fourier filtering enables absolute quantification of lattice parameter variations and strain, as well as the uncertainty associated with these measurements. Implementations of these algorithms are made available as an open source python package.

36 MATERIALS SCIENCE↗

NucD-23 Nuclear Diagnostics Development: The future of neutron imaging and gamma reaction history

The Neutron Imaging team has deployed novel, active detection systems along two lines of sight at NIF. Studies aimed to characterize NIS sensitivity to implosion shape will be carried out to further extend reconstruction capabilities. Additionally, an improved camera timing system that will reduce uncertainties stemming from bang time jitter will also be fielded. The NIF GRH data recording system is more then 10 years old needs to be updated. Bandwidth and noise are a key limiting factor for improving data quality. New high bandwidth and low noise components will be tested at OMEGA in advance before fielding the components at NIF.

42 ENGINEERING↗

Seismoacoustic Data Fusion for Ground Coupled Airwaves: a FACT Case Study for Calibration and Array Processing

This report covers an inquiry into seismoacoustic array processing using infrasound arrivals combined with resulting Ground Coupled Airwaves (GCA) that are present on collocated seismic sensors. In preparation, data calibration and denoising is completed for a seismoacoustic sensor array that was deployed at the Facility for Acceptance, Calibration, and Testing on Kirtland Airforce Base from August through September of 2021. The events of interest for this study are small, local explosive sources that lead to short duration, impulsive signals on the instruments. The goal is to determine if combining infrasound signals with the corresponding GCAs on collocated seismic sensors can be used to improve the results returned by automated signal detection and characterization (e.g., back azimuth estimates). Preparation for seismic and infrasound data involves removing the instrument response so that sensors have flat power spectra over the frequency range 0.1-10 Hz, where signal from events of interest may be detected. After instrument response removal, deployment conditions specific to this array require a retrospective noise analysis to determine station emplacement characteristics. Once all data is calibrated, a manual search is performed for possible GCA arrivals across the seismoacoustic network. These arrivals are then processed through beamforming and subsequent event identification, resulting in a catalogue of seismoacoustic GCA arrivals with corresponding back azimuth and trace velocity estimations.

47 OTHER INSTRUMENTATION↗

Scaling Subspace-Driven Approaches Using Information Fusion

In this work, we seek to exploit the deep structure of multi-modal data to robustly exploit the group subspace distribution of the information using the Convolutional Neural Networks (CNNs) formalism. Upon unfolding the set of subspaces constituting each data modality, and learning their corresponding encoders, an optimized integration of the generated inherent information is carried out to yield a characterization of various classes. Referred to as deep Multimodal Robust Group Subspace Clustering (DRoGSuRe), this approach is compared against the independently developed state-of-the-art approach named Deep Multimodal Subspace Clustering (DMSC). Experiments on different multimodal datasets show that our approach is competitive and more robust in the presence of noise.

Ghanem, Sally↗

Characterization and Optimization of Skipper CCDs for the SOAR Integral Field Spectrograph

We present results from the characterization and optimization of Skipper charge-coupled devices (CCDs) for use in a focal plane prototype for the Southern Astrophysical Research Integral Field Spectrograph (SIFS). We tested eight Skipper CCDs and selected six for SIFS based on performance results. The Skipper CCDs are 6k × 1k, 15 μm pixels, thick, fully depleted, p-channel devices that have been thinned to ~250 μm, backside processed, and treated with an anti-reflective coating. We demonstrate a single-sample readout noise of <4.3 e - rms pixel -1 in all amplifiers. We optimize the readout sequence timing to achieve a readout noise of 0.5 e - rms pixel -1 after 74 non-destructive measurements, which can be accomplished in a region covering 5% of the detector area in a readout time of <4 minutes. We demonstrate single-photon-counting in all 24 amplifiers (four amplifiers per detector) with a readnoise of σ N ~ 0.18 e - rms pixel -1 after N samp = 400 samples, and we constrain the degree of nonlinearity to be ≲1% at low signal levels (0 e - to 50 e - ). Clock-induced charge (CIC) remains an important issue when the Skipper CCD is configured to provide a large full-well capacity. We achieve a CIC rate of <1.45 × 10 -3 e - pixel -1 frame -1 for a full-well capacity of ~900 e - , which increases to a CIC rate of ~3 e - pixel -1 frame -1 for full-well capacities ~40,000-65,000 e - . We also perform conventional CCD characterization measurements such as charge transfer inefficiency (3.44 × 10 -7 on average), dark current (~2 × 10 -4 e - pixel -1 s -1 ), photon transfer curves, cosmetic defects (<0.45% “bad” pixels), and charge diffusion (point-spread function < 7.5 μm) to verify that these properties are consistent with expectations from conventional p-channel CCDs used for astronomy. Furthermore, we provide the first measurements of the brighter-fatter effect and absolute quantum efficiency (≳80% between 450 and 980 nm; ≳90% between 600 and 900 nm) using Skipper CCDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗