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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Noise and Spreading of a Subsonic Coannular Jet - Comparison with Single Equivalent Jet

The issue of scaling of noise as well as spreading of subsonic coannular jets is revisited. Far-field noise and centerline Pitot-static pressure surveys are conducted with concentric, circular nozzles having an outer-to-inner diameter ratio of 1.42. Both the inner nozzle and the outer annular passage are convergent. Outer-to-inner Mach number ratio (R) is varied over a large range from 0 to approximately 10. Results are examined on the basis of single equivalent jet parameters calculated by satisfying continuity, momentum and energy equations. The results confirm that coannular jets with normal velocity profiles are noisier than the single equivalent jet. Jets with "inverted" velocity profiles are also found to be noisier except in a narrow R-range of 1-1.5. In the latter range, contrasting the inference in previous studies of IVP jets, the present data do not exhibit a clear noise reduction. When normalized with equivalent jet parameters the asymptotic Mach number decay rate, as well as potential core length, are found to be comparable to those of a single jet. However, an abrupt shift in the virtual origin is noted across R=1.

Zaman, K. B. M. Q.↗
NASA NTRS2005

Abundance and Speciation of Water and Sulfate at Gusev Crater and Meridiani Planum

A major science goal of the Mars Exploration Rover (MER) mission is to search for evidence of water activity, and direct mineralogical evidence for aqueous activity has been reported for Meridiani Planum in the form of the iron sulfate hydroxide mineral jarosite and at Gusev crater in the form of goethite. The Spirit and Opportunity rovers have each collected 110+ Moessbauer (MB) and 75+ Alpha Particle X-Ray Spectrometer (APXS) spectra from Gusev crater and Meridiani Planum [1 - 4]. In this abstract, we use mineralogical and elemental data, primarily from the Moessbauer and APXS instruments, to infer the speciation and estimate the abundance of sulfate and water (as either the H2O molecule or the hydroxyl anion) at Gusev crater and Meridiani Planum. Throughout the abstract, we adopt a format for mineral formulas that shows water explicitly rather than the usual practice of structure-based formulas (e.g., for goethite we write Fe2O3xH2O instead of FeOOH).

Ming, D. W.↗
NASA NTRS2007

Variations in Upper-Tropospheric Humidity and Convective Processes as Seen from SSM/T-2

Water vapor feedback, particularly involving water vapor in the upper troposphere (UTH), is widely regarded as the process with the most potential to amplify anthropogenic greenhouse forcing. Yet, our ability to quantify observationally water vapor variations in the current climate and the relationships to convective processes remains rather crude. Remote sensing from polar orbiting instruments has played a major role in documenting UTH variability, supplementing highly undersampled and poorly calibrated rawinsonde measurements. Most of our observational understanding of UTH has come from the 6.7 micrometer channel measurements which are subject to cloud contamination uncertainties. In this work we examine UTH variations present in the Special Sensor Microwave Temperature Sounder 2 (SSM/T-2) sensors flying aboard Defense Military Satellite Program (DMSP) polar orbiting satellites during the period 1993 through 2001. We employ data from the the 183.3 +/- 1 GHz channel which is far less sensitive to cirrus than IR methods. Our primary focus is on obtaining more reliable statistics of interannual behavior; i.e. How close to constant RH are interannual variations in T2 UTH over the tropics? How do temperature and moisture variations contribute regionally? The 1997/1998 strong ENS0 warming event and adjacent cool periods provide a strong signal to study, albeit a perturbation of natural climate variability. Modeling the 183.3 GHz channel using reanalysis temperature data, but with climatological water vapor, allows us to infer the separate contribution by water vapor in the observations. In addition, frozen hydrometeors produced by deep convection are also captured in the 150 GHz oxygen channel, providing an opportUnity to relate the incidence of deep convection to water vapor variability. Our results indicate a much larger variation of 183.3 GHz brightness temperatures would be observed were it not for water vapor variations positively correlated with tropical SSTs. Comparisons are made with previous studies using both IR and microwave observations to characterize UTH response to tropical SSTs.

Robertson, Franklin R.↗
NASA NTRS2008

The Mock LISA Data Challenge Round 3: New and Improved Sources

The Mock LISA Data Challenges are a program to demonstrate and encourage the development of data-analysis capabilities for LISA. Each round of challenges consists of several data sets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants are asked to analyze the data sets and report the maximum information they can infer about the source parameters. The challenges are being released in rounds of increasing complexity and realism. Challenge 3. currently in progress, brings new source classes, now including cosmic-string cusps and primordial stochastic backgrounds, and more realistic signal models for supermassive black-hole inspirals and galactic double white dwarf binaries.

Baker, John↗
NASA NTRS2010

Aero-Heating of Shallow Cavities in Hypersonic Freestream Flow

The purpose of these experiments and analysis was to augment the heating database and tools used for assessment of impact-induced shallow-cavity damage to the thermal protection system of the Space Shuttle Orbiter. The effect of length and depth on the local heating disturbance of rectangular cavities tested at hypersonic freestream conditions has been globally assessed using the two-color phosphor thermography method. These rapid-response experiments were conducted in the Langley 31-Inch Mach 10 Tunnel and were initiated immediately prior to the launch of STS-114, the initial flight in the Space Shuttle Return-To-Flight Program, and continued during the first week of the mission. Previously-designed and numerically-characterized blunted-nose baseline flat plates were used as the test surfaces. Three-dimensional computational predictions of the entire model geometry were used as a check on the design process and the two-dimensional flow assumptions used for the data analysis. The experimental boundary layer state conditions were inferred using the measured heating distributions on a no-cavity test article. Two test plates were developed, each containing 4 equally-spaced spanwise-distributed cavities. The first test plate contained cavities with a constant length-to-depth ratio of 8 with design point depth-to-boundary-layer-thickness ratios of 0.1, 0.2, 0.35, and 0.5. The second test plate contained cavities with a constant design point depth-to-boundary-layer-thickness ratio of 0.35 with length-to-depth ratios of 8, 12, 16, and 20. Cavity design parameters and the test condition matrix were established using the computational predictions. Preliminary results indicate that the floor-averaged Bump Factor (local heating rate nondimensionalized by upstream reference) at the tested conditions is approximately 0.3 with a standard deviation of 0.04 for laminar-in/laminar-out conditions when the cavity length-to-boundary-layer thickness is between 2.5 and 10 and for cavities in the depth-to-boundary-layer-thickness range of 0.3 to 0.8. Over this same range of conditions and parameters, preliminary results also indicate that the maximum Bump Factor on the cavity centerline falls between 2.0 and 2.75, as long as the cavity-exit conditions remain laminar. Cavities with length-to-boundary-layer-thickness ratio less than 2.5 can not be easily classified with this approach and require further analysis.

Everhart, Joel L.↗
NASA NTRS2002

Maximizing TDRS Command Load Lifetime

The GNC software onboard ISS utilizes TORS command loads, and a simplistic model of TORS orbital motion to generate onboard TORS state vectors. Each TORS command load contains five "invariant" orbital elements which serve as inputs to the onboard propagation algorithm. These elements include semi-major axis, inclination, time of last ascending node crossing, right ascension of ascending node, and mean motion. Running parallel to the onboard software is the TORS Command Builder Tool application, located in the JSC Mission Control Center. The TORS Command Builder Tool is responsible for building the TORS command loads using a ground TORS state vector, mirroring the onboard propagation algorithm, and assessing the fidelity of current TORS command loads onboard ISS. The tool works by extracting a ground state vector at a given time from a current TORS ephemeris, and then calculating the corresponding "onboard" TORS state vector at the same time using the current onboard TORS command load. The tool then performs a comparison between these two vectors and displays the relative differences in the command builder tool GUI. If the RSS position difference between these two vectors exceeds the tolerable lim its, a new command load is built using the ground state vector and uplinked to ISS. A command load's lifetime is therefore defined as the time from when a command load is built to the time the RSS position difference exceeds the tolerable limit. From the outset of TORS command load operations (STS-98), command load lifetime was limited to approximately one week due to the simplicity of both the onboard propagation algorithm, and the algorithm used by the command builder tool to generate the invariant orbital elements. It was soon desired to extend command load lifetime in order to minimize potential risk due to frequent ISS commanding. Initial studies indicated that command load lifetime was most sensitive to changes in mean motion. Finding a suitable value for mean motion was therefore the key to achieving this goal. This goal was eventually realized through development of an Excel spreadsheet tool called EMMIE (Excel Mean Motion Interactive Estimation). EMMIE utilizes ground ephemeris nodal data to perform a least-squares fit to inferred mean anomaly as a function of time, thus generating an initial estimate for mean motion. This mean motion in turn drives a plot of estimated downtrack position difference versus time. The user can then manually iterate the mean motion, and determine an optimal value that will maximize command load lifetime. Once this optimal value is determined, the mean motion initially calculated by the command builder tool is overwritten with the new optimal value, and the command load is built for uplink to ISS. EMMIE also provides the capability for command load lifetime to be tracked through multiple TORS ephemeris updates. Using EMMIE, TORS command load lifetimes of approximately 30 days have been achieved.

Brown, Aaron J.↗
NASA NTRS2006

NASA Tech Briefs, December 2006

Topic include: Inferring Gear Damage from Oil-Debris and Vibration Data; Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs; User Interactive Software for Analysis of Human Physiological Data; Representation of Serendipitous Scientific Data; Automatic Locking of Laser Frequency to an Absorption Peak; Self-Passivating Lithium/Solid Electrolyte/Iodine Cells; Four-Quadrant Analog Multipliers Using G4-FETs; Noise Source for Calibrating a Microwave Polarimeter; Hybrid Deployable Foam Antennas and Reflectors; Coating MCPs with AlN and GaN; Domed, 40-cm-Diameter Ion Optics for an Ion Thruster; Gesture-Controlled Interfaces for Self-Service Machines; Dynamically Alterable Arrays of Polymorphic Data Types; Identifying Trends in Deep Space Network Monitor Data; Predicting Lifetime of a Thermomechanically Loaded Component; Partial Automation of Requirements Tracing; Automated Synthesis of Architecture of Avionic Systems; SSRL Emergency Response Shore Tool; Wholly Aromatic Ether-Imides as n-Type Semiconductors; Carbon-Nanotube-Carpet Heat-Transfer Pads; Pulse-Flow Microencapsulation System; Automated Low-Gravitation Facility Would Make Optical Fibers; Alignment Cube with One Diffractive Face; Graphite Composite Booms with Integral Hinges; Tool for Sampling Permafrost on a Remote Planet; and Special Semaphore Scheme for UHF Spacecraft Communications.

Source record↗
NASA NTRS2011

Emission Lines from the Gas Disk Around TW Hydra and the Origin of the Inner Hole

We compare line emission calculated from theoretical disk models with optical to submillimeter wavelength observational data of the gas disk surrounding TW Hya and infer the spatial distribution of mass in the gas disk. The model disk that best matches observations has a gas mass ranging from approx.10(exp −4) to 10(exp −5) M for 0.06AU < r < 3.5 AU and approx. 0.06M for 3.5AU < r < 200 AU. We find that the inner dust hole (r < 3.5 AU) in the disk must be depleted of gas by approx. 1-2 orders of magnitude compared with the extrapolated surface density distribution of the outer disk. Grain growth alone is therefore not a viable explanation for the dust hole. CO vibrational emission arises within r approx. 0.5 AU from thermal excitation of gas. [O i] 6300Å and 5577Å forbidden lines and OH mid-infrared emission are mainly due to prompt emission following UV photodissociation of OH and water at r < or approx. 0.1 AU and at r approx. 4 AU. [Ne ii] emission is consistent with an origin in X-ray heated neutral gas at r < or approx. 10 AU, and may not require the presence of a significant extreme-ultraviolet (hν > 13.6 eV) flux from TW Hya. H2 pure rotational line emission comes primarily from r approx. 1 to 30 AU. [Oi] 63microns, HCO+, and CO pure rotational lines all arise from the outer disk at r approx. 30-120 AU. We discuss planet formation and photoevaporation as causes for the decrease in surface density of gas and dust inside 4 AU. If a planet is present, our results suggest a planet mass approx. 4-7MJ situated at ∼3 AU. Using our photoevaporation models and the best surface density profile match to observations, we estimate a current photoevaporative mass loss rate of 4x10(exp −9M)/yr and a remaining disk lifetime of approx.5 million years.

Planet-Disk interactions↗
NASA NTRS2016

Spaceborne Remote Sensing of Aerosol Type: Global Distribution, Model Evaluation and Translation into Chemical Speciation

It is essential to evaluate and refine aerosol classification methods applied to passive satellite remote sensing. We have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground-based passive remote sensing instruments [1]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrialdeveloped economy, urban-industrialdeveloping economy, dark biomass smoke, light biomass smoke and pure marine. We apply the SCMC method to inversions from the ground-based AErosol RObotic NETwork (AERONET [2]) and retrievals from the space-borne Polarization and Directionality of Earths Reflectances instrument (POLDER, [3]). The POLDER retrievals that we use differ from the standard POLDER retrievals [4] as they make full use of multi-angle, multispectral polarimetric data [5]. We analyze agreement in the aerosol types inferred from both AERONET and POLDER and evaluate GEOS-Chem [6] simulations over the globe. Finally, we use in-situ observations from the SEAC4RS airborne field experiment to bridge the gap between remote sensing-inferred qualitative SCMC aerosol types and their corresponding quantitative chemical speciation. We apply the SCMC method to airborne in-situ observations from the NASA Langley Aerosol Research Group Experiment (LARGE, [7]) and the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP, [8]) instruments; we then relate each coarsely defined SCMC type to a sum of percentage of individual aerosol species, using in-situ observations from the Particle Analysis by Laser Mass Spectrometry (PALMS, [9]), the Soluble Acidic Gases and Aerosol (SAGA, [10]), and the High - Resolution Time - of - Flight Aerosol Mass Spectrometer (HR ToF AMS, [11]).

airborne↗
NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗
DOE OSTI2023

Risk-Informed Condition Evaluation of Solar-centered Energy Generation and Distribution Networks through Bayesian Learning and Inference

We develop a methodology based on Bayesian inference over Probabilistic Graphical Models (PGMs) to understand and quantify risk in solar-centered grids using targeted measurements and learned system behavior. Being non-prescriptive but, rather, able to infer system behavior and, ultimately, address risk queries from data, our machine learning-type paradigm is tailored for diverse topologies and threat scenarios often associated with distributed energy generation and photovoltaic distributed energy resources (PV-DERs) in particular. We describe algorithmic processes for: (i) learning the structure of PGMs that result from attack-prone PV-DER-proliferated distribution systems, (ii) quantifying cause-effect relationships, and (iii) evaluating risk queries based on diverse evidence. The contributions are illustrated on a residential grid subject to output impairment attacks on its PV-DER infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Dynamical Dark Energy Imprints in the Lyman-Alpha Forest

The nature of dark energy (DE) remains elusive, even though it constitutes the dominant energy-density component of the Universe and drives the late-time acceleration of cosmic expansion. By combining measurements of the expansion history from baryon acoustic oscillations, supernova surveys, and cosmic microwave background data, the Dark Energy Spectroscopic Instrument (DESI) Collaboration has inferred that the DE equation of state may evolve over time. The profound implications of a time-variable, ``dynamical" DE (DDE) that departs from a cosmological constant motivate the need for independent observational tests. In this work, we use cosmological hydrodynamical simulations of structure formation to investigate how DDE affects the properties of the Lyman-Alpha ``forest'' of absorption features produced by neutral hydrogen in the cosmic web. We find that DDE models consistent with the DESI constraints induce a spectral tilt in the forest transmitted flux power spectrum, imprinting a scale- and redshift-dependent signature relative to standard Lambda-CDM cosmologies. These models also yield higher intergalactic medium temperatures and reduced Lyman-Alpha opacity compared to Lambda-CDM. We discuss the observational implications of these trends as potential avenues for independent confirmation of DDE.

Garza, Diego [UC, Santa Cruz, Inst. Part. Phys.] (↗
DOE OSTI2026

Strong Lensing Cosmology with Population-level Calibrated Neural Ratio Estimation

Strong gravitational lensing contains key information about cosmic acceleration. Modern and next-generation galaxy imaging surveys are expected to provide high-quality data on $\mathcal{O}(10^5)$ galaxy-galaxy lensing systems. The plethora and complexity of the data are likely to present computational challenges for parameter inference methods for fitting high-dimensional likelihoods, which are often analytically intractable. Neural Ratio Estimation (NRE) efficiently computes individual likelihood ratios that can be combined into population-level posteriors. We use simulations to study the capacity of NRE to jointly predict the dark energy equation-of-state parameter $w$ and the total matter density $Ω_{m}$ from lensing images and companion spectroscopic information. We also introduce a post hoc posterior coverage calibration procedure that mitigates the model overconfidence that is typically found in neural density estimation applications. Our experiments show that the errors on both parameters decrease with increasing inference population sizes. In particular, for 100 lenses in a standard $Λ$CDM Universe, our calibrated NRE model achieves median fractional uncertainty of $22.8\%$ in $w$ and $2.9\%$ in $Ω_{m}$. This proof of concept demonstrates a potentially scalable approach for efficient cosmological parameter inference with large populations of galaxy-scale lenses observed in future surveys.

Jarugula, Sreevani [Fermilab] (ORCID:0000000253867↗
DOE OSTI2026

Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses

Smokescreen is an open-source Python library for data-vector concealment (blinding) in cosmological analyses. Data-vector blinding works by applying cosmology-dependent shifts to the observed data vector, moving it away from the true cosmological signal without affecting its statistical properties, so that analysts cannot infer the true result until the analysis is frozen and the blinding is lifted. The package computes these shifts using Firecrown likelihoods applied to data vectors stored in the SACC format, ensuring that the theoretical model used for blinding is identical to that used for inference whilst remaining agnostic to the specific observable being blinded. To prevent accidental unblinding, the original SACC file, containing the true cosmology, is encrypted. Although developed for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Smokescreen is applicable to any experiment using Firecrown likelihoods and the SACC data format.

Loureiro, Arthur [Stockholm U., OKC; Imperial Coll↗
NASA NTRS2005

Probing the Reverse Shock in an Oxygen-Rich Supernovae Remnant

The purpose of this investigation is to examine the O VI emission from the X-ray bright ring of the supernova remnant 1 E0102.2-729 in the small Magellanic cloud. Three pointings were positioned tangent to the ring, north (N), northeast (NE), and southeast (SE), to examine a range of X-ray emitting regions overlapping a range of optical [O III] nebulosity and to examine the velocity structure. One background pointing was also obtained, but it was contaminated by a star. The background levels in the pointings on the remnant were low enough that the background pointing was not required for the remaining analysis. The SE pointing was reobserved in August, 2004, in order to bring the total exposure up to the originally requested 15 ks. The archive notified us of the data's availability in mid September. Significant broad O VI 1032 and O VI 1038 emission was found, brightest in the NE and SE pointings. In the NE and SE pointings, the FWHM of the broad O VI component is approx.800-1000 km/s, while in the N pointing, the line is approx.1500 km/s wide. The O VI is redshifted in the N (approx.380 km/s) and NE (approx.60 km/s) but is blueshifted in the SE (approx. -160 km/s). These FUSE O VI velocity dispersions can be compared to the X-ray gas velocities inferred from Doppler distortions in the Chandra X-ray data as reported by Flanagan et al. 2004 (ApJ 605, 230). The bulk velocities in the X-ray bright ring of order +/- 1000 km/s, comparable to the velocity dispersion seen in the FUSE data. However, the X-ray data indicates a redshift of approx.1000 km/s in the SE, while the FUSE data show a blueshift of approx.160 km/s, underscoring the complex velocity structure in this remnant. The O VI fluxes estimated from the fits to the FUSE data were combined with X-ray (XMM- Newton) O VI1 and O VIII fluxes and compared with predictions from a plasma nonequilibrium ionization model in a "line-based" analysis. We found that the plasma departs significantly from collisional ionization equilibrium, particularly in the SE, and that the plasma excitation conditions vary among the pointings: the O plasma sees different conditions than the Ne and Mg plasmas.

Gaetz, Terrance↗
NASA NTRS2000

A Language for Probabilistic Modeling of Scientific Data

We describe a portable container which allows specification of the probabilistic relations between several variables. The applications motivating this work are mainly scientific inference problems.

probabilistic modeling scientific data↗
DOE OSTI2022

Inference for Nonparanormal Partial Correlation via Regularized Rank-Based Nodewise Regression

Abstract Partial correlation is a common tool in studying conditional dependence for Gaussian distributed data. However, partial correlation being zero may not be equivalent to conditional independence under non-Gaussian distributions. In this paper, we propose a statistical inference procedure for partial correlations under the high-dimensional nonparanormal (NPN) model where the observed data are normally distributed after certain monotone transformations. The NPN partial correlation is the partial correlation of the normal transformed data under the NPN model, which is a more general measure of conditional dependence. We estimate the NPN partial correlations by regularized nodewise regression based on the empirical ranks of the original data. A multiple testing procedure is proposed to identify the nonzero NPN partial correlations. The proposed method can be carried out by a simple coordinate descent algorithm for lasso optimization. It is easy-to-implement and computationally more efficient compared to the existing methods for estimating NPN graphical models. Theoretical results are developed to show the asymptotic normality of the proposed estimator and to justify the proposed multiple testing procedure. Numerical simulations and a case study on brain imaging data demonstrate the utility of the proposed procedure and evaluate its performance compared to the existing methods. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

97 MATHEMATICS AND COMPUTING↗