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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CO 2 Storage prospeCtive Resource Estimation Excel aNalysis (CO 2 -SCREEN) User’s Manual: Python_V4.1

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO 2 Storage prospeCtive Resource Estimation Excel aNalysis (CO 2 -SCREEN) tool, which was developed to aid users in screening geologic formations for prospective CO 2 storage resources. This manual is specific to the CO 2 -SCREEN 4.1 version which is based in Python. The 4.1 version of CO 2 -SCREEN adds in newly updated storage efficiency factors for saline formations. CO 2 -SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO 2 storage resources for saline formations, shale formations, and residual oil zones (ROZ). CO 2 -SCREEN was developed to be substantive and user-friendly and provide a consistent method for calculating prospective CO 2 storage resources. CO 2 -SCREEN uses a Java- based graphical user interface (GUI) for data inputs and uses Python to calculate prospective CO 2 storage resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Identification of surface urban heat versus cool islands for arid cities depends on the choice of urban and rural definitions

The urban heat island (UHI) effect in arid cities can be small or even negative, the latter known as the urban cool island (UCI) effect. Differences in defining urban and rural areas can introduce uncertainties in detecting UHI or UCI, especially when the UHI signal is small. Here, we compared the surface UHI intensity (SUHII) estimated by a dozen different methods (with multiple urban and/or rural definitions) across 104 arid cities globally, providing a comprehensive evaluation of the uncertainty in SUHII estimates. Results show that the absolute difference in annual average SUHII (ΔSUHII) among methods exceeded 1°C in about half of the arid cities during both daytime and nighttime. Further, the overall annual mean ΔSUHII for all arid cities was 1.35°C during daytime and 1.03 °C at night. The uncertainty arising from simultaneous variations in urban and rural definitions was generally higher than that resulting from their individual changes. It was observed that, with varying definitions of urban and rural areas, nearly 50% of arid cities experienced a sign reversal in daytime SUHII estimates, while approximately 15% exhibited a sign reversal in nighttime SUHII. Variations in urban-rural differences in surface properties, such as vegetation index and albedo, due to differing urban and rural definitions, contributed strongly to the observed SUHII uncertainties. Overall, our results offer new insights into the ongoing debate on heat and cold islands in arid cities, emphasizing a critical need to standardize SUHII estimation frameworks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Nonparametric estimators for incomplete surveys

Nonparametric estimators, such as the 1/V{sub max} estimator and the C{sup −} estimator, have been applied extensively to estimate luminosity functions (LFs) of astronomical sources from complete, truncated survey data sets. Application of such estimators to incomplete data sets typically requires further truncation of data, separation into subsets of constant completeness, and/or correction for incompleteness-induced bias. In this paper, we derive generalizations of the above estimators designed for use with incomplete, truncated data sets. We compare these generalized nonparametric estimators, investigate some of their simple statistical properties, and validate them using Monte Carlo simulation methods. We apply a nonparametric estimator to data obtained from the extended Baryon Oscillation Spectroscopic Survey to estimate the QSO LF for redshifts 0.68<z<4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Regional differences in tobacco smoking and lung cancer in Portugal in 2018: a population-based analysis using nationwide incidence and mortality data

Objectives: This study aims to estimate the proportion of lung cancer cases and deaths attributable to tobacco smoking in Portugal in 2018, complemented by trends in incidence and mortality, by sex and region. Design: Cancer cases for 1998–2011 and cancer deaths for 1991–2018 were obtained from population-based registries and Statistics Portugal, respectively. We projected cases for 2018 and used reported deaths for the same year to estimate, using Peto’s method, the number and proportion of lung cancer cases and deaths caused by tobacco smoking in 2018. We calculated the age-adjusted incidence and mortality rates in each year of diagnosis and death. We fitted a joinpoint regression to the observed data to estimate the annual percentage change (APC) in the rates. Setting: Portugal. Results: In 2018, an estimated 3859 cases and 3192 deaths from lung cancer were attributable to tobacco smoking in Portugal, with men presenting a population attributable fraction (PAF) of 82.6% (n=3064) for incidence and 84.1% (n=2749) for mortality, while in women those values were 51.0% (n=795) and 42.7% (n=443), respectively. In both sexes and metrics, the Azores were the region with the highest PAF and the Centre with the lowest. During 1998–2011, the APC for incidence ranged from 0.6% to 3.0% in men and 3.6% to 7.9% in women, depending on region, with mortality presenting a similar pattern between sexes. Conclusion: Exposure to tobacco smoking has accounted for most of the lung cancer cases and deaths estimated in Portugal in 2018. Differential patterns of tobacco consumption across the country, varying implementation of primary prevention programmes and differences in personal cancer awareness may have contributed to the disparities observed. Primary prevention of lung cancer remains a public health priority, particularly among women.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗
DOE OSTI2025

Implementation of the D1S Methodology for Shutdown Dose Rate Calculations in the OpenMC Monte Carlo Particle Transport Code

We present an implementation of the direct one-step (D1S) methodology for shutdown dose rate (SDR) calculations in the OpenMC Monte Carlo particle transport code. In addition to being the first fully open-source D1S implementation, it is also the first to require no ad hoc source code or nuclear data library modifications. The code can seamlessly switch between production of prompt and decay photons based on a user input parameter, and the decay data needed for decay photon generation are made available through a depletion chain file, which is already used for OpenMC’s built-in depletion/activation solver. A set of Python functions significantly eases the burden of computing and applying time correction factors needed to properly account for the time dependence of radionuclide activity. To assess the accuracy of the D1S implementation, SDR calculations have been carried out for three problems: a prism of iron irradiated by 14-MeV neutrons, the ITER port plug computational benchmark, and the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For each of these problems, comparisons were made to calculations using the rigorous two-step (R2S) method. The results on the iron prism problem illustrate how the D1S method achieves superior spatial resolution compared to the R2S method without the need for spatial discretization of the activation regions. The D1S and R2S results for the ITER port plug benchmark agree well with previously reported results in the literature. While the D1S results are 10% to 15% lower than the R2S results, this may be due to stochastic uncertainty and/or spatial discretization in the R2S calculations. On the FNG dose rate benchmark problem, the D1S method produces dose rate estimates that are within 4% of the dose rates predicted using a cell-based R2S workflow. The D1S estimates of the SDR are also in reasonable agreement with the experimental measurements and show the same basic trends that have been observed in previous works. A qualitative analysis of the execution time and uncertainty for the R2S and D1S workflows suggests that the D1S method would attain a higher figure of merit.

D1S method↗
DOE OSTI2024

Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant

Abstract We study stars in the J-regions of the asymptotic giant branch (JAGB) of near-infrared color–magnitude diagrams in the maser host NGC 4258 and four hosts of six Type Ia supernovae (SNe Ia): NGC 1448, NGC 1559, NGC 5584, and NGC 5643. These clumps of stars are readily apparent near 1.0 < F150W − F277W < 1.5 andm F150W = 22–25 mag with James Webb Space Telescope NIRCam photometry. Various methods have been proposed to assign an apparent reference magnitude to this recently proposed standard candle, including the mode, median, sigma-clipped mean, or a modeled luminosity function parameter. We test the consistency of these by measuring intrahost variations, finding differences of up to ∼0.2 mag that significantly exceed statistical uncertainties. Brightness differences appear intrinsic, and are further amplified by the nonuniform shape of the JAGB luminosity function, also apparent in the LMC and SMC. We follow a “many methods” approach to measure consistently JAGB magnitudes and distance moduli to the SN Ia host sample calibrated by NGC 4258. We find broad agreement with distance moduli measured from Cepheids, tip of the red giant branch, and Miras. However, the SN host mean distance modulus estimated via the JAGB method necessary to estimateH 0 differs by ∼0.19 mag among the above definitions, the result of different levels of luminosity function asymmetry. The methods yield a full range of 71−78 km s −1 Mpc −1 , i.e., a fiducial result ofH 0 = 74.7 ± 2.1(stat) ± 2.3(sys, ±3.1 if combined in quadrature) km s −1 Mpc −1 , with systematic errors limited by the differences in methods. Future work may seek to standardize and refine this promising tool further, making it more competitive with established distance indicators.

Astronomy & Astrophysics↗
DOE OSTI2025

Welch Method and Bootstrapping Applied to Subcritical Gamma Noise

We measured the prompt neutron decay constant 𝛼 of the CROCUS zero-power reactor at the Swiss Federal Institute of Technology Lausanne using cross-power spectral density (CPSD) analysis of gamma-gamma correlations from two trans-stilbene organic scintillators positioned near the reactor core. We measured critical and subcritical states, with water levels ranging from 960 mm (critical) to 800 mm (𝜌=−1.4 $ subcritical). Our analysis used the Welch method, dividing signal segments for fast Fourier transform (FFT) frequency analysis and applying bootstrapping uncertainty quantification that uses Welch-defined segments. Results demonstrated a clear increase in the measured 𝛼 as reactor reactivity decreased, distinguishing critical from subcritical conditions. At the 960-mm critical level, 𝛼 was estimated at 155.9 ± 0.7 s −1 , and for the 800-mm subcritical level, 𝛼 increased significantly to 367.3 ± 6.9 s –1 . A linear regression of subcritical states yielded a critical estimate of 154.0 ± 3.1 s –1 , aligning with the static 𝛼 estimate at critical. The bootstrapping method produced normally distributed 𝛼 estimates, confirming data consistency. The gamma CPSD 𝛼 estimates clearly distinguish reactor states and improve monitoring of zero-power reactors. The future deployment of modular and microreactors as potential candidates for noise analysis is demonstrated in CROCUS, particularly zero-power mock-ups of new designs. The improvement of noise analysis in the subcritical domain from this work will support experimental data for reactor deployment and procedure.

CROCUS↗
DOE OSTI2024

Single-ancilla ground state preparation via Lindbladians

We design a quantum algorithm for ground state preparation in the early fault tolerant regime. As a Monte Carlo style quantum algorithm, our method features a Lindbladian where the target state is stationary. The construction of this Lindbladian is algorithmic and should not be seen as a specific approximation to some weakly coupled system-bath dynamics in nature. Our algorithm can be implemented using just one ancilla qubit and efficiently simulated on a quantum computer. It can prepare the ground state even when the initial state has zero overlap with the ground state, bypassing the most significant limitation of methods like quantum phase estimation. As a variant, we also propose a discrete-time algorithm, demonstrating even better efficiency and providing a near-optimal simulation cost depending on the desired evolution time and precision. Numerical simulations using Ising and Hubbard models demonstrate the efficacy and applicability of our method. Published by the American Physical Society 2024

Ding, Zhiyan (ORCID:000000018863403X)↗
DOE OSTI2018

A kriging and entropy-based approach to raingauge network design

Highlights: • A kriging and entropy theory-based approach is developed for gauge network design. • The method considers both minimum estimating error andoptimum rainfall information. • The best combination is verified to be effectiveto achieve final goals. Hydrological data, such as precipitation, is fundamental for planning, designing, developing, and managing water resource projects as well as for hydrologic research. An optimal raingauge network leads to more accurate estimates of mean or point precipitation at any site over the watershed. Some studies in the past have suggested increasing gauge network density for reducing the estimation error. However, more stations mean more cost of installation and monitoring. This study proposes an approach on the basis of kriging and entropy theory to determine an optimal network design in the city of Shanghai, China. Unlike the past studies using kriging interpolation and entropy theory for network design, the approach developed in the current study not only used the kriging method as an interpolator to determine rainfall data at ungauged locations but also incorporated the minimum kriging standard error (KSE) and maximum net information (NI) content. The approach would thus lead to an optimal network and would enable the reduction of kriging standard error of precipitation estimates throughout the watershed and achieve an optimum rainfall information. This study also proposed an NI-KSE-based criterion which is dependent on a single-objective optimization. To evaluate the final optimal gauge network, areal average rainfall was estimated and its accuracy was compared with that obtained with the existing rain gauge network.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A stable high-order perturbation of surfaces method for numerical simulation of diffraction problems in triply layered media

The accurate numerical simulation of linear waves interacting with periodic layered media is a crucial capability in engineering applications. In this contribution we study the stable and high-order accurate numerical simulation of the interaction of linear, time-harmonic waves with a periodic, triply layered medium with irregular interfaces. In contrast with volumetric approaches, High-Order Perturbation of Surfaces (HOPS) algorithms are inexpensive interfacial methods which rapidly and recursively estimate scattering returns by perturbation of the interface shape. In comparison with Boundary Integral/Element Methods, the stable HOPS algorithm we describe here does not require specialized quadrature rules, periodization strategies, or the solution of dense non-symmetric positive definite linear systems. In addition, the algorithm is provably stable as opposed to other classical HOPS approaches. With numerical experiments we show the remarkable efficiency, fidelity, and accuracy one can achieve with an implementation of this algorithm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Systematic Assessment of Retrieval Methods for Canopy Far-Red Solar-Induced Chlorophyll Fluorescence Using High-Frequency Automated Field Spectroscopy

Remote sensing of solar-induced chlorophyll fluorescence (SIF) offers potential to infer photosynthesis across scales and biomes. Many retrieval methods have been developed to estimate top-of-canopy SIF using ground-based spectroscopy. However, inconsistencies among methods may confound interpretation of SIF dynamics, eco-physiological/environmental drivers, and its relationship with photosynthesis. Using high temporal- and spectral resolution ground-based spectroscopy, we aimed to (1) evaluate performance of SIF retrieval methods under diverse sky conditions using continuous field measurements; (2) assess method sensitivity to fluctuating light, reflectance, and fluorescence emission spectra; and (3) inform users for optimal ground-based SIF retrieval. Analysis included field measurements from bi-hemispherical and hemispherical-conical systems and synthetic upwelling radiance constructed from measured downwelling radiance, simulated reflectance, and simulated fluorescence for benchmarking. Fraunhofer-based differential optical absorption spectroscopy (DOAS) and singular vector decomposition (SVD) retrievals exhibit convergent SIF-PAR relationships and diurnal consistency across different sky conditions, while O2A-based spectral fitting method (SFM), SVD, and modified Fraunhofer line discrimination (3FLD) exhibit divergent SIF-PAR relationships across sky conditions. We find that such behavior holds across system configurations, though hemispherical-conical systems diverge less across sky conditions. O 2 A retrieval accuracy, influenced by atmospheric distortion, improves with a narrower fitting window and when training SVD with temporally local spectra. This may impact SIF-photosynthesis relationships interpreted by previous studies using O 2 A-based retrievals with standard (759–767.76 nm) fitting windows. Fraunhofer-based retrievals resist atmospheric impacts but are noisier and more sensitive to assumed SIF spectral shape than O 2 A-based retrievals. We recommend SVD or SFM using reduced fitting window (759.5–761.5 nm) for robust far-red SIF retrievals across sky conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗
DOE OSTI2020

Excavation Volume Growth Factors at Environmental Remediation Sites - 20318

The U.S. Army Corps of Engineers (USACE) manages numerous environmental remediation projects in accordance with the Comprehensive Environmental Response, Compensation, and Liability Act, otherwise known as CERCLA. These include projects for the Formerly Utilized Sites Remedial Action Program (FUSRAP). Utilizing the CERCLA framework to address these projects requires detailed cost estimates and a significant portion of costs are associated with the volume of material to be excavated and that material's final disposition. Accordingly, understanding the expected volumes and uncertainty associated with those volumes is vital to project cost estimating. These estimates are completed at various stages of the CERCLA process, thus the project team has varying degrees of information available from which to develop these estimates depending on how far along the project is. Understanding the factors contributing to volume growth (increase in volume of material from that originally estimated) is a crucial element to determining volume and cost uncertainty. This paper presents a case study of a FUSRAP site which involves excavation and offsite disposal of contaminated soils from complex commercial, industrial, and residential properties. Original volume estimates were compared to post excavation volumes on a property by property basis. Reasons for differences are determined along with magnitude of impacts to cost estimating. For both residential and commercial property types, volume estimating factors, uncertainty considerations, and methods to account for each are discussed with emphasis on volume growth considerations. Cost estimating model input considerations are discussed with specific emphasis on accounting for volume uncertainty at the Feasibility Study (FS) phase of CERCLA. Underestimating or overestimating costs at the FS phase has repercussions under CERCLA that may impact project close out or completion schedule. Discussions presented will be helpful to both reviewers and preparers of cost estimates involving excavations. Additionally, project planners may be able to use the information to plan for volume growth contingencies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Constitutive Modeling of the Flow Stress of GCr15 Continuous Casting Bloom in the Heavy Reduction Process

According to the calculation results of a 3D thermomechanical-coupled finite-element (FE) model of GCr15 bearing steel bloom during a heavy reduction (HR) process, the variation ranges in the strain rate and strain under HR were described. In addition, the hot deformation behavior of the GCr15 bearing steel was studied over the temperature range from 1023 K to 1573 K (750 °C to 1300 °C) with strain rates of 0.001, 0.01, and 0.1 s{sup −1} in single-pass thermosimulation compression experiments. To ensure the accuracy of the constitutive model, the temperature range was divided into two temperature intervals according to the fully austenitic temperature of GCr15 steel [1173 K (900 °C)]. Two sets of material parameters for the constitutive model were derived based on the true stress–strain curves of the two temperature intervals. A flow stress constitutive model was established using a revised Arrhenius-type constitutive equation, which considers the relationships among the material parameters and true strain. This equation describes dynamic softening during hot compression processes. Considering the effect of glide and climb on the deformation mechanism, the Arrhenius-type constitutive equation was modified by a physically based approach. This model is the most accurate over the temperatures ranging from 1173 K to 1573 K (900 °C to 1300 °C) under HR deformation conditions (ignoring the range from 1273 K to 1573 K (1000 °C to 1300 °C) with a strain rate of 0.1 s{sup −1}). To ensure the convergence of the FE calculation, an approximated method was used to estimate the flow stress at temperatures greater than 1573 K (1300 °C).

36 MATERIALS SCIENCE↗
DOE OSTI2015

Light output measurements and computational models of microcolumnar CsI scintillators for x-ray imaging

Purpose: The authors report on measurements of light output and spatial resolution of microcolumnar CsI:Tl scintillator detectors for x-ray imaging. In addition, the authors discuss the results of simulations aimed at analyzing the results of synchrotron and sealed-source exposures with respect to the contributions of light transport to the total light output. Methods: The authors measured light output from a 490-μm CsI:Tl scintillator screen using two setups. First, the authors used a photomultiplier tube (PMT) to measure the response of the scintillator to sealed-source exposures. Second, the authors performed imaging experiments with a 27-keV monoenergetic synchrotron beam and a slit to calculate the total signal generated in terms of optical photons per keV. The results of both methods are compared to simulations obtained with hybridMANTIS, a coupled x-ray, electron, and optical photon Monte Carlo transport package. The authors report line response (LR) and light output for a range of linear absorption coefficients and describe a model that fits at the same time the light output and the blur measurements. Comparing the experimental results with the simulations, the authors obtained an estimate of the absorption coefficient for the model that provides good agreement with the experimentally measured LR. Finally, the authors report light output simulation results and their dependence on scintillator thickness and reflectivity of the backing surface. Results: The slit images from the synchrotron were analyzed to obtain a total light output of 48 keV{sup −1} while measurements using the fast PMT instrument setup and sealed-sources reported a light output of 28 keV{sup −1}. The authors attribute the difference in light output estimates between the two methods to the difference in time constants between the camera and PMT measurements. Simulation structures were designed to match the light output measured with the camera while providing good agreement with the measured LR resulting in a bulk absorption coefficient of 5 × 10{sup −5} μm{sup −1}. Conclusions: The combination of experimental measurements for microcolumnar CsI:Tl scintillators using sealed-sources and synchrotron exposures with results obtained via simulation suggests that the time course of the emission might play a role in experimental estimates. The procedure yielded an experimentally derived linear absorption coefficient for microcolumnar Cs:Tl of 5 × 10{sup −5} μm{sup −1}. To the author’s knowledge, this is the first time this parameter has been validated against experimental observations. The measurements also offer insight into the relative role of optical transport on the effective optical yield of the scintillator with microcolumnar structure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Compound Poisson Generator Approach to Point-source Inference in Astrophysics

Abstract The identification and description of point sources is one of the oldest problems in astronomy, yet even today the correct statistical treatment for point sources remains one of the field’s hardest problems. For dim or crowded sources, likelihood-based inference methods are required to estimate the uncertainty on the characteristics of the source population. In this work, a new parametric likelihood is constructed for this problem using compound Poisson generator (CPG) functionals that incorporate instrumental effects from first principles. We demonstrate that the CPG approach exhibits a number of advantages over non-Poissonian template fitting (NPTF)—an existing method—in a series of test scenarios in the context of X-ray astronomy. These demonstrations show that the effect of the point-spread function, effective area, and choice of point-source spatial distribution cannot, generally, be factorized as they are in NPTF, while the new CPG construction is validated in these scenarios. Separately, an examination of the diffuse-flux emission limit is used to show that most simple choices of priors on the standard parameterization of the population model can result in unexpected biases: when a model comprising both a point-source population and diffuse component is applied to this limit, nearly all observed flux will be assigned to either the population or to the diffuse component. A new parameterization is presented for these priors that properly estimates the uncertainties in this limit. In this choice of priors, CPG correctly identifies that the fraction of flux assigned to the population model cannot be constrained by the data.

79 ASTRONOMY AND ASTROPHYSICS↗