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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Interannual and Seasonal Variability of Biomass Burning Emissions Constrained by Satellite Observations

We present a methodology for estimating the seasonal and interannual variation of biomass burning designed for use in global chemical transport models. The average seasonal variation is estimated from 4 years of fire-count data from the Along Track Scanning Radiometer (ATSR) and 1-2 years of similar data from the Advanced Very High Resolution Radiometer (AVHRR) World Fire Atlases. We use the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) data product as a surrogate to estimate interannual variability in biomass burning for six regions: Southeast Asia, Indonesia and Malaysia, Brazil, Central America and Mexico, Canada and Alaska, and Asiatic Russia. The AI data set is available from 1979 to the present with an interruption in satellite observations from mid-1993 to mid-1996; this data gap is filled where possible with estimates of area burned from the literature for different regions. Between August 1996 and July 2000, the ATSR fire-counts are used to provide specific locations of emissions and a record of interannual variability throughout the world. We use our methodology to estimate mean seasonal and interannual variations for emissions of carbon monoxide from biomass burning, and we find that no trend is apparent in these emissions over the last two decades, but that there is significant interannual variability.

Duncan, Bryan N.↗
NASA NTRS1977

Relative crater production rates on planets

The relative numbers of impacts on different planets, estimated from the dynamical histories of planetesimals in specified orbits (Wetherill, 1975), are converted by a described procedure to crater production rates. Conversions are dependent on impact velocity and surface gravity. Crater retention ages can then be derived from the ratio of the crater density to the crater production rate. The data indicate that the terrestrial planets have crater production rates within a factor ten of each other. As an example, for the case of Mars, least-squares fits to crater-count data suggest an average age of 0.3 to 3 billion years for two types of channels. The age of Olympus Mons is discussed, and the effect of Tharsis volcanism on channel formation is considered.

Hartmann, W. K.↗
DOE OSTI2026

Low energy neutron light output characterization of EJ301D and deuterated stilbene with a comparison of light output characterization methods

The neutron-induced light yield of a 2.54 cm diameter by 2.54 cm long right circular cylinder of EJ301D and a (5.08 cm)3 custom made cube of deuterated trans-stilbene-d12 (d-stilbene) were measured over incident neutron energies from 300 keV to 2.2 MeV and 200 keV to 2.4 MeV, respectively. The measurements were performed using a time-of-flight experiment with a Cf-252 source and an approximately 1.5 m flight path. We compare three light output spectrum full energy deposition edge estimation methods: (1) simulating the neutron energy spectrum edge and fitting it to the light output spectrum, (2) using the inflection point of the light output spectrum edge (derivative method, a.k.a. Kornilov’s method), and (3) using an empirical model fit to the edge of the light output spectrum. Both the derivative and equation fit methods do not account for physical processes such as multiple neutron scattering in the detectors. They instead rely on assumptions about the linear shape continuum shape of the light output spectrum and the direct correlation between the location of the spectrum’s inflection point and maximum energy deposition. These assumptions were found to introduce bias into those methods when tested against simulated spectra with known edge locations. When tested against measured spectra the derivative method was found to differ from the simulation fit by greater than 30% at low energies with large discontinuities for adjacent data points above 800 keV incident neutron energy. The empirical equation fitting method was found to also exhibit bias of a similar magnitude, but with significantly more continuous behavior, especially with the lower count data of the smaller volumed EJ301D scintillator. Experimental light output yield for this neutron energy range is reported using the simulated spectrum fitting method because it includes physics neglected by the other methods, and did not exhibit the bias observed in the other methods

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2011

Dawn Maps the Surface Composition of Vesta

By 7-October-2011, the Dawn mission will have completed Survey orbit and commenced high altitude mapping of 4-Vesta. We present a preliminary analysis of data acquired by Dawn's Framing Camera (FC) and the Visual and InfraRed Spectrometer (VIR) to map mineralogy and surface temperature, and to detect and quantify surficial OH. The radiometric calibration of VIR and FC is described. Background counting data acquired by GRaND are used to determine elemental detection limits from measurements at low altitude, which will commence in November. Geochemical models used in the interpretation of the data are described. Thermal properties, mineral-, and geochemical-data are combined to provide constraints on Vesta s formation and thermal evolution, the delivery of exogenic materials, space weathering processes, and the origin of the howardite, eucrite, and diogenite (HED) meteorites.

Prettyman, T.↗
NASA NTRS2003

The Distribution and Abundance of Bird Species: Towards a Satellite, Data Driven Avian Energetics and Species Richness Model

This paper addresses the fundamental question of why birds occur where and when they do, i.e., what are the causative factors that determine the spatio-temporal distributions, abundance, or richness of bird species? In this paper we outline the first steps toward building a satellite, data-driven model of avian energetics and species richness based on individual bird physiology, morphology, and interaction with the spatio-temporal habitat. To evaluate our model, we will use the North American Breeding Bird Survey and Christmas Bird Count data for species richness, wintering and breeding range. Long term and current satellite data series include AVHRR, Landsat, and MODIS.

Smith, James A.↗
NASA NTRS2011

Geochemical Mapping of 4 Vesta Begins

By December, the NASA Dawn spacecraft will have descended to a low altitude mapping orbit (LAMO), where the Gamma Ray and Neutron Detector (GRaND) will acquire global mapping data for up to four months. Measurements by GRaND will help answer elusive questions about how Vesta differentiated and the nature of processes that shaped Vesta s surface. The data will be analyzed to determine the abundances of Mg, Si, Fe, K, Th, and H at a spatial resolution of roughly 300 km full-width-at-half-maximum from a 465 km radius orbit. Thermal and fast neutron counting data will be analyzed to determine the neutron macroscopic absorption cross section and average atomic mass, providing constraints on additional elements, such as Ca and Al. GRaND will quantify the elemental composition of coarse spatial units identified by Dawn s Framing Camera (FC) and the Visible & Infrared Spectrometer (VIR). In addition, GRaND will map the mixing ratio of compositional end members selected from the howardite, eucrite and diogenite (HED) meteorites, determine the relative proportions of plagioclase and mafic minerals, and search for compositions that are absent or under-represented in the meteorite collection. While it is generally thought that Vesta s crust on a regional scale should be well-represented by linear mixing of HED whole-rock compositions, there are hints that Vesta may be more diverse than implied by this model. For example, the discovery of K-rich impact glasses in howardites suggests that K-rich rocks may be present on a portion of Vesta s surface, and the analysis of diogenites indicates considerable variability in the magmatic processes that formed them. The chemical composition of materials within Vesta s south polar structure may provide further clues to how it formed. An impact might have exposed mantle and lower crustal materials, which should have a distinctive compositional signature. We present the analysis of data acquired by GRaND from cruise through the descent to LAMO, including GRaND s sensitivity to different elements and geochemical processes.

Prettyman, Thomas H.↗
NASA NTRS2003

Mid-Latitude Composition of Mars from Thermal and Epithermal Neutrons

Epithermal neutron data acquired by Mars Odyssey have been analyzed to determine global maps of water-equivalent hydrogen abundance. By assuming that hydrogen was distributed uniformly with depth within the surface, a map of minimum water abundance was obtained. The addition of thermal neutrons to this analysis could provide information needed to determine water stratigraphy. For example, thermal and epithermal neutrons have been used together to determine the depth and abundance of water-equivalent hydrogen of a buried layer in the south polar region. Because the emission of thermal neutrons from the Martian surface is sensitive to absorption by elements other than hydrogen, analysis of stratigraphy requires that the abundance of these elements be known. For example, recently published studies of the south polar region assumed that the Mars Pathfinder mean soil composition is representative of the regional soil composition. This assumption is partially motivated by the fact that Mars appears to have a well-mixed global dust cover and that the Pathfinder soil composition is representative of the mean composition of the Martian surface. In this study, we have analyzed thermal and epithermal neutron data measured by the neutron spectrometer subsystem of the gamma ray spectrometer to determine the spatial distribution of the composition of elements other than hydrogen. We have restricted our analysis to mid-latitude regions for which we have corrected the neutron counting data for variations in atmospheric thickness.

T H Prettyman↗
DOE OSTI2025

Real-time neutron multiplicity and source localization for criticality safety during fuel debris removal

Advancing neutron detection and analysis techniques for complex radiation environments is an ongoing focus in nuclear instrumentation and monitoring. This proposal presents research and development of a generalized real-time neutron monitoring and analysis system, applicable to any detector capable of producing time-tagged neutron count data. While the work is demonstrated using the Neutron Multiplication Analysis Detector (NoMAD), a modular 15-tube helium-3 (He-3) array, due to its availability, spatial resolution, and flexible deployment, the methods developed are extensible to other systems, including organic scintillators and fast digital detectors. This research investigates two complementary analytical techniques for real-time characterization of neutron emitting sources: neutron multiplicity estimation based on the Hage-Cifarelli formalism and spatial localization using supervised machine learning applied to spatial count rate patterns. These methods are designed to operate under dynamic, evolving conditions such as fuel debris retrieval or reactor startup, where neutron-emitting material geometries may be partially unknown or changing over time. By integrating statistical neutron emission data with spatial localization, this research aims to develop and evaluate methods for real time neutron monitoring, source characterization, and material verification. Key contributions include implementation of a low-latency data pipeline for continuous neutron multiplicity analysis, development and validation of machine learning models for spatial inference, and experimental evaluation of system performance under variable measurement conditions. The outcomes are intended to support applications in nuclear safeguards, verification, emergency response, and reactor startup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Shot-noise-induced lower temperature limit of the nonneutral plasma parallel temperature diagnostic

Abstract We develop a new algorithm to estimate the temperature of a nonneutral plasma in a Penning-Malmberg trap. The algorithm analyzes data obtained by slowly lowering a voltage that confines one end of the plasma and collecting escaping charges, and is a maximum likelihood estimator based on a physically-motivated model of the escape protocol presented in (Beck in Measurement of the magnetic and temperature dependence of the electron-electron anisotropic temperature relaxation rate. PhD thesis, 1990). Significantly, our algorithm may be used on single-count data, allowing for improved fits with low numbers of escaping electrons. This is important for low-temperature plasmas such as those used in antihydrogen trapping. We perform a Monte Carlo simulation of our algorithm, and assess its robustness to intrinsic shot noise and external noise. The assumptions in this paper allow for a lower bound for measurable plasma temperatures of approximately $3\,\mathrm{K}$ 3 K for plasmas of length $1\,\mathrm{cm}$ 1 cm , with approximately 100 particle counts needed for an accuracy of $\pm 10 \%$ ± 10 % .

Zhong, Adrianne (ORCID:0000000162618736)↗
NASA NTRS1981

The number-intensity distribution for extragalactic X-ray sources

It is shown that a self-consistent assessment of source count data can be made, if many of the deep survey sources are QSOs which are known to be evolving strongly at fluxes comparable to the survey limits. The QSO contribution would in this case become significant at X-ray fluxes below 10 to the -12th erg/sq cm per sec, and dominates at fluxes below 10 to the -13th erg/sq cm per sec. The X-ray background intensity places a limit on total source counts and requires a turnover in the evolution of X-ray emitting sources. Sources detected in the Einstein survey account for over 35% of the 1-3 keV background flux, suggesting that most of the background is due to discrete sources.

Murray, S. S.↗
DOE OSTI2025

eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework

Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. While occupancy modelling software has dominated the analytical landscape for eDNA data analysis of single species, this type of model may not always be the most appropriate. The rate of eDNA detection often corresponds to species density, rather than just occupancy, and researchers often have access to observations from non‐genetic sampling methods at the same sites. To provide users access to a modelling framework designed to maximize the use of all available data, we developed an R package, eDNAjoint . The package provides an easy‐to‐use interface for fitting a ‘joint’ model that integrates data from paired or semi‐paired eDNA and traditional surveys in a Bayesian framework. The model can be used to estimate parameters like the probability of a false positive eDNA detection and mean catch rate at a site, and the package allows access to multiple model variations and Bayesian prior customization. Additional functionality can be used for model selection, summarising posteriors and comparing the relative sensitivities of the two survey methods. We demonstrate the use of eDNAjoint by fitting a variation of the model with site‐level covariates that scale the sensitivity of eDNA sampling relative to traditional sampling. The example workflow uses binary eDNA and seine count data for the endangered tidewater goby ( Eucyclogobius newberryi ) from a study by Schmelzle and Kinziger (2016). This use case includes a prior sensitivity analysis and an evaluation of the relationship between detection rates and environmental variables. eDNAjoint has the potential to greatly increase the range of users who will be able to rigorously analyse eDNA and traditional survey data in a Bayesian framework, understand if and how eDNA can improve monitoring practices, and gain confidence in the interpretability of eDNA data.

Keller, Abigail G. [Department of Environment Scie↗
NASA NTRS2018

Neutrophil to Lymphocyte Ratio: A Prognostic Indicator for Astronaut Health

Short-term and long-term spaceflight missions can cause immune system dysfunction in astronauts. Recent studies indicate elevated white blood cells (WBC) and polymorphonuclear neutrophils (PMN) in astronaut blood, along with unchanged or reduced lymphocyte counts, and reduced T cell function, during short-(days) and long-(months) term spaceflight. A high PMN to lymphocyte ratio (NLR) can acts as a strong predictor of poor prognosis in cancer, and as a biomarker for subclinical inflammation in humans and chronic stress in mouse models, however, the NLR has not yet been identified as a predictor of astronaut health during spaceflight. For this, complete blood cell count data collected from astronauts and rodents that have flown for short- and long-term missions on board the International Space Station (ISS) was repurposed to determine the NLR pre-, in-, and post-flight. The results displayed that the NLR progressively increased during spaceflight in both human and mice, while a spike in the NLR was observed at post-flight landing, suggesting stress-induced factors may be involved. In addition, the ground-based chronic microgravity analog, hindlimb unloading in mice, indicated an increased NLR, along with induced myeloperoxidase expression, as measured by quantitative (q)PCR. The mechanism for increased NLR was further assessed in vitro using the NASA-developed rotating wall vessel (RWV) cell culture suspension system with human WBCs. The results indicated that simulated microgravity led to increased mature PMN counts, NLR profiles, and production of reactive oxygen species (ROS). Collectively, these studies show that an increased NLR is observed in spaceflight missions, and in chronic microgravity-analog simulation in mice, and that this effect may be potentiated by the oxidative stress response in blood cells under microgravity conditions. Furthermore, these results suggest that a disrupted NLR profile in spaceflight may further disrupt immune homeostasis, potentially causing chronic immune-mediated inflammatory diseases. Thus, we propose that the health status of astronauts during short- and long-term space missions can be monitored by their NLR profile, in addition to utilizing this measurement as a tool for interventions and countermeasure development to restore homeostatic immunity.

biomarker↗
NASA NTRS2001

Large Aperture Scanning Lidar Based on Holographic Optical Elements

Lidar remote sensing instruments can make a significant contribution to satisfying many of the required measurements of atmospheric and surface parameters for future spaceborne platforms, including topographic altimeters, atmospheric profiles of, wind, humidity, temperature, trace molecules, aerosols, and clouds. It is highly desirable to have wide measurement swaths for rapid coverage rather than just the narrow ribbon of data that is obtained with a nadir only observation. For most applications global coverage is required, and for wind measurements scanning or pointing is required in order to retrieve the full 3-D wind vector from multiple line-of-sight Doppler measurements. Conventional lidar receivers make up a substantial portion of the instrument's size and weight. Wide angle scanning typically requires a large scanning mirror in front of the receiver telescope, or pointing the entire telescope and aft optics assembly, Either of these methods entails the use of large bearings, motors, gearing and their associated electronics. Spaceborne instruments also need reaction wheels to counter the torque applied to the spacecraft by these motions. NASA has developed simplified conical scanning telescopes using Holographic Optical Elements (HOEs) to reduce the size, mass, angular momentum, and cost of scanning lidar systems. NASA has developed two operating lidar systems based on 40 cm diameter HOEs. The first such system, named Prototype Holographic Atmospheric Scanner for Environmental Remote Sensing (PHASERS) was a joint development between NASA Goddard Space Flight Center (GSFC) and the University of Maryland College Park. PHASERS is based on a reflection HOE for use at the doubled Nd:YAG laser wavelength of 532 nm and has recently undergone a number of design changes in a collaborative effort between GSFC and Saint Anselm College in New Hampshire. The next step was to develop IR transmission HOEs for use with the Nd:YAG fundamental in the Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE). The HOE spins like a compact disk in a large ring ball bearing. In an aircraft the HOE faces down, looking out through a window at an angle of 45 degrees off-nadir. The HOE diffracts 85% of the incident 532 nm light into a 160 micron spot at a focal length of 1 meter. HARLIE is a field deployable lidar measuring aerosol, cloud, and boundary layer backscatter for atmospheric research. It has flown several times and is also used from a ground-based trailer in an upward-looking mode. The HOE generates a 45 degree conical scan pattern by rotating at speeds up to 30 rpm. Like PHASERS, the HOE in HARLIE serves both as the laser collimating lens as well as the receiver telescope primary optic. The telescope is coupled to the receiver package via fiber optic. The transmitter is a diode pumped Nd:YAG laser operating at 1064 nm, delivering 1 mJ pulses at a 5 KHz rep-rate. The receiver has a 200 microradian field-of-view and a 0.5 nm optical bandpass. The photon counting data system utilizes a single Geiger-mode silicon avalanche photodiode detector, This new technology has also presented us with new data visualization challenges as well as new measurement techniques. The backscatter data obtained from a stationary (i.e. ground-based) scanning HOE lidar is on the surface of a cone, which when viewed over many consecutive scans can reveal atmospheric motions on this surface over time as the atmosphere advects over the site. In a moving platform such as an airplane or satellite, the data from consecutive scans cover different areas under the flight path, revealing atmospheric structure in 3-dimensions. An example of a visualization of HARLIE ground-based data is presented, showing aerosol backscatter on a 90 degree conical surface generated from one 360 degree scan of the lidar during the HOLO-1 field campaign on the afternoon of 10 March 1999. Higher backscatter levels are rendered as lighter signal against a dark background. Breaking Kelvin-Helmholtz waves are evident on the north side of the scan at an altitude of 10-11 km. Time series of successive scans made at regular intervals render unique views of atmospheric motions, from which vertical profiles of atmospheric wind vectors can be obtained using a unique data analysis approach. Wind vectors obtained from the lidar were compared with co-located radiosonde wind profiles during an intensive operating period in September-October 2000 at the Atmospheric Radiation Measurement Program's Southern Great Plains Central Facility.

Schwemmer, Geary K.↗
DOE OSTI2025

Quantifying health benefits of sustainable aviation fuels: Modeling decreased ultrafine particle emissions and associated impacts on communities near the Seattle-Tacoma International Airport

Exposure to ultrafine particles (UFP, ≤100 nm) is an emerging health concern linked to premature mortality, with jet fuel combustion identified as a significant source of UFPs near airports. Sustainable aviation fuel (SAF) adoption has the potential to reduce aviation-related UFPs and may particularly benefit populations who reside nearby. However, assessing aviation-specific impacts on health remains challenging due to the lack of tools capable of addressing: fine-scale exposure evaluation, novel ambient pollutants, and groups with increased exposure or susceptibility. We develop and apply a method to estimate reductions in mortality associated with aviation-related UFP reductions at the Seattle-Tacoma (SEA-TAC) International Airport under SAF adoption scenarios, with a focus on near-airport communities. Using UFP exposure surfaces generated from AERMOD modeling, flight count data, and UFP measurements, we evaluated UFP reductions under various control scenarios. We estimated mortality reductions by combining this with population data, baseline mortality, and a hazard ratio of 1.012 (95 % confidence interval: 1.010, 1.015) per interquartile range increment of 2723 particles/cm 3 . Our analysis included 412 census tracts representing almost 1.5 million adults. Baseline aviation-related UFP exposures averaged 1145 (SD: 277) particles/cm 3 . The highest baseline concentrations and subsequent reductions under SAF scenarios were near SEA-TAC. Mortality case reductions averaged between 3.1 (95 % range: 2.5–3.7) for a 5 % UFP reduction to 31.0 (24.6–37.4) for a 50 % reduction, with corresponding mortality rate reductions of 0.2 (0.2–0.3) to 2.1 (1.7–2.5) cases per 100,000 people per year. Mortality rate reductions were larger among populations residing closer to SEA-TAC, including those that were Hispanic or Latino, below-poverty, and did not identify as White. Reducing aviation-related UFPs through SAF adoption could lead to lower mortality, particularly in near-airport communities. This reproducible approach can be adapted to other settings to evaluate health benefits from aviation-related UFP reductions.

Aviation-related air pollution↗
DOE OSTI2025

Generalized fiducial inference on differentiable manifolds

We introduce a novel approach to inference on parameters that take values in a Riemannian manifold embedded in a Euclidean space. Parameter spaces of this form are ubiquitous across many fields, including chemistry, physics, computer graphics, and geology. Here, this new approach uses generalized fiducial inference (GFI) to obtain a posterior-like distribution on the manifold, without needing to know local parameterizations that map to the constrained space from an unconstrained Euclidean space. Using mathematical tools from Riemannian geometry, we construct a constrained generalized fiducial distribution (CGFD). A Bernstein-von Mises-type result for the CGFD, which provides intuition for how the desirable asymptotic qualities of the unconstrained generalized fiducial distribution are inherited by the CGFD, is provided. To illustrate the practical use of the CGFD, we provide a proof-of-concept example in the context of a linear logspline density estimation problem, and demonstrate that CGFD-based confidence sets exhibit desirable coverage properties via simulation. As an application, we fit a CGFD to COVID-19 case count data from North Carolina, USA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Prime VI

SAND2025-03757O Prime VI is a distribution-of-disease outbreak model calibration code based on variational inference. It accompanies a publication for submission to Statistics in Medicine journal, and the code will be maintained for open-source use on Sandia's GitLab. The software provides methods for calibrating an epidemiological model to measured case-count data for a multitude of correlated spatial regions. The code solves a Bayesian inverse problem for model calibration where the posterior over-model parameters are approximated through a custom implementation of variational inference. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Safta, Cosmin↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2025

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗