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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

MIC-DP: A Scalable Correlation-Aware Differential Privacy Framework for High-Dimensional Data

Conventional differential privacy (DP) assumes record independence, limiting effectiveness on real-world datasets with temporal, spatial, or structural correlations. These dependencies undermine privacy guarantees and degrade utility in domains like healthcare, IoT, and smart city analytics. We propose Maximum Information Correlated Differential Privacy (MIC-DP), a novel framework that dynamically calibrates noise based on statistical dependencies. MIC-DP uses the Maximum Information Coefficient (MIC) to capture both linear and nonlinear correlations without explicit modeling, enabling adaptive sensitivity adjustment and improved privacy–utility trade-offs. Evaluations on healthcare (MIMIC), demographic (ACI), and synthetic datasets show that MIC-DP reduces mean absolute error (MAE) by up to 5.2% under strict privacy budgets (ϵ≤1), with aggregate utility improvements reaching 18% across datasets and evaluation metrics. MIC-DP provides formal (ϵ,δ)-privacy guarantees, scales efficiently with feature count, and supports deployment in moderate-scale, privacy-sensitive applications. Its tunable performance and runtime efficiency make MIC-DP suitable for privacy-sensitive applications where low-latency analytics and strong privacy guarantees must coexist. These results demonstrate MIC-DP’s effectiveness as a correlation-aware solution for practical DP.

Yang, Wenjun [Univ. of Washington, Tacoma, WA (Uni↗
DOE OSTI2018

Generic approach to access barriers in dehydrogenation reactions

The introduction of linear energy correlations, which explicitly relate adsorption energies of reaction intermediates and activation energies in heterogeneous catalysis, has proven to be a key component in the computational search for new and promising catalysts. A simple linear approach to estimate activation energies still requires a significant computational effort. To simplify this process and at the same time incorporate the need for enhanced complexity of reaction intermediates, we generalize a recently proposed approach that evaluates transition state energies based entirely on bond-order conservation arguments. Here, we show that similar variation of the local electronic structure along the reaction coordinate introduces a set of general functions that accurately defines the transition state energy and are transferable to other reactions with similar bonding nature. With such an approach, more complex reaction intermediates can be targeted with an insignificant increase in computational effort and without loss of accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dijet impact factor in DIS at next-to-leading order in the Color Glass Condensate

In this work, we compute the next-to-leading order impact factor for inclusive dijet production in deeply inelastic electron-nucleus scattering at small x Bj . Our computation, performed in the framework of the Color Glass Condensate effective field theory, includes all real and virtual contributions in the gluon shock wave background of all-twist lightlike Wilson line correlators. We demonstrate explicitly that the rapidity evolution of these correlators, to leading logarithmic accuracy, is described by the JIMWLK Hamiltonian. When combined with the next-to-leading order JIMWLK Hamiltonian, our results for the impact factor improve the accuracy of the inclusive dijet cross-section to \( \mathcal{O} \) ( \( {\alpha}_s^2 \) ln( x f /x Bj )), where x f is a rapidity factorization scale. These results are an essential ingredient in assessing the discovery potential of inclusive dijets to uncover the physics of gluon saturation at the Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

ON THE INADEQUACY OF N-POINT CORRELATION FUNCTIONS TO DESCRIBE NONLINEAR COSMOLOGICAL FIELDS: EXPLICIT EXAMPLES AND CONNECTION TO SIMULATIONS

Motivated by recent results on lognormal statistics showing that the moment hierarchy of a lognormal variable completely fails at capturing its information content in the large variance regime, in this work we discuss the inadequacy of the hierarchy of correlation functions to describe a correlated lognormal field, which provides a roughly accurate description of the nonlinear cosmological matter density field. We present families of fields having the same hierarchy of correlation functions than the lognormal field at all orders. This explicitly demonstrates the little studied though known fact that the correlation function hierarchy never provides a complete description of a lognormal field, and that it fails to capture information in the nonlinear regime, where other simple observables are left totally unconstrained. We discuss why perturbative, Edgeworth-like approaches to statistics in the nonlinear regime, common in cosmology, can never reproduce or predict that effect, and why it is, however, generic for tailed fields, hinting at a breakdown of the perturbation theory based on the field fluctuations. We make a rough but successful quantitative connection to N-body simulations results that showed that the spectrum of the log-density field carries more information than the spectrum of the field entering the nonlinear regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control

Abstract Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate linear unmixing methods generally explore similarities in the energy dimension, but ignore correlations in the spatial domain. At the same time, Gaussian process (GP) explicitly incorporate spatial correlations in the form of kernel functions but is computationally intensive. Here, we implement a GP method operating on the full spatial domain and reduced representations in the energy domain. In this multivariate GP, the information between the components is shared via a common spatial kernel structure, while allowing for variability in the relative noise magnitude or image morphology. We explore the role of kernel constraints on the quality of the reconstruction, and suggest an approach for estimating them from the experimental data. We further show that spatial information contained in higher-order components can be reconstructed and spatially localized.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Extended Brueckner-Hartree-Fock theory with pionic correlation in finite nuclei

Highlights: > We formulate a many-body theory with explicit treatment of tensor correlations. > The Hartree-Fock (HF) model space is extended to include 2-particle 2-hole states. > This extended HF equation has a structure of the Brueckner theory. > Single-particle states are obtained under the influence of the tensor correlation. > This framework is interpreted by the Feshbach projection method. - Abstract: We formulate a nuclear many-body theory with explicit treatment of the strong tensor correlation caused by the pion-exchange interaction. To do this, we have to extend the Hartree-Fock variational model space to include 2-particle 2-hole (2p-2h) states, which are able to handle the tensor correlation and to contain high momentum components originating from its pseudo-scalar nature of the pion. We take the variational principle of the total energy, and obtain equations of motion for the variational parameters as the Hartree-Fock single particle states and 2p-2h states. As for the short range repulsion, we use the unitary correlation operator method (UCOM) to express the short range correlation in the ground state wave function. We then arrive at an extended Hartree-Fock equation with the inclusion of the effect of the pion exchange and short range repulsive interactions. We find this extended Hartree-Fock equation has a structure of the Brueckner theory. Thus, we name the present theoretical framework as an extended Brueckner-Hartree-Fock (EBHF) theory. We compare the EBHF theory with the Feshbach projection method and the Brueckner-Hartree-Fock theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Effect of electron correlation on the electronic structure and spin-lattice coupling of high- T c cuprates: Quantum Monte Carlo calculations

Electron correlation effects are particularly strong in high-temperature superconducting materials. Devising an accurate description of these materials has long been a challenge, with these strong correlation effects historically being considered impossible or impractical to simulate computationally. Using quantum Monte Carlo techniques, we have explicitly simulated electron correlations in several cuprate materials from first principles. These simulations accurately reproduce many important physical quantities of these materials, including the interaction-induced gap and superexchange coupling between copper spins, with no additional parameters beyond fundamental constants. We further investigate the dimensionless spin-lattice coupling parameter in the parent materials, showing that it varies dramatically, between 0.1 and 1.0, depending on the interlayer. Furthermore, this result indicates that the lattice and magnetic degrees of freedom are not independent in these systems, which may have ramifications for the origin of superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

On the measurability of quantum correlation functions

The concept of correlation function is widely used in classical statistical mechanics to characterize how two or more variables depend on each other. In quantum mechanics, on the other hand, there are observables that cannot be measured at the same time; the so-called incompatible observables. This prospect imposes a limitation on the definition of a quantum analog for the correlation function in terms of a sequence of measurements. Here, based on the notion of sequential weak measurements, we circumvent this limitation by introducing a framework to measure general quantum correlation functions, in principle, independently of the state of the system and the operators involved. To illustrate, we propose an experimental configuration to obtain explicitly the quantum correlation function between two Pauli operators, in which the input state is an arbitrary mixed qubit state encoded on the polarization of photons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Cyber–Physical Correlation Effects in Defense Games for Large Discrete Infrastructures

In certain critical infrastructures, correlations between cyber and physical components can be exploited to launch strategic attacks, so that disruptions to one component may affect others and possibly the entire infrastructure. Such correlations must be explicitly taken into account in ensuring the survival of the infrastructure. For large discrete infrastructures characterized by the number of cyber and physical components, we characterize the cyber–physical interactions at two levels: (i) the cyber–physical failure correlation function specifies the conditional survival probability of the cyber sub-infrastructure given that of the physical sub-infrastructure (both specified by their marginal probabilities), and (ii) individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions expressed in terms of their multiplier functions. We formulate an abstract problem of ensuring the survival probability of a cyber–physical infrastructure with discrete components as a game between the provider and attacker, whose utility functions are composed of infrastructure survival probability terms and cost terms, both expressed in terms of the number of components attacked and reinforced. We derive Nash equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure survival probability on cost terms, correlation functions, multiplier functions, and sub-infrastructure survival probabilities. We apply these analytical results to characterize the defense postures of simplified models of metro systems, cloud computing infrastructures, and smart power grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integrate them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

On path-dependence of the QCD correlation functions

Gauge-invariant hadronic and vacuum correlation functions in QCD contain the systems of Wilson lines and loops having complicated geometrical structure. Path-dependence propagates, therefore, into such important properties of the quantum correlators as the renormalization-group behaviour, light-cone peculiarities, evolution, etc. In the present paper, I briefly overview several instructive examples of the manifestations of the structure of paths in the hadronic and vacuum correlation functions with explicit transverse momentum/distance dependence. In particular, the transverse-momentum dependent (TMD) parton densities and the skewed jet quenching parameter in Euclidean and Minkowski space-time are addressed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Correlation of isocurvature perturbation and non-Gaussianity

We explore the correlations between primordial non-Gaussianity and isocurvature perturbation. We sketch the generic relation between the bispectrum of the curvature perturbation and the cross-correlation power spectrum in the presence of explicit couplings between the inflaton and another light field which gives rise to isocurvature perturbation. Using a concrete model of a Peccei-Quinn type field with generic gravitational couplings, we illustrate explicitly how the primordial bispectrum correlates with the cross-correlation power spectrum. Assuming the resulting f{sub NL} ∼ O(1), we find that the form of the correlation depends mostly upon the inflation model but only weakly on the axion parameters, even though f{sub NL} itself does depend heavily on the axion parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A redefinition of the halo boundary leads to a simple yet accurate halo model of large-scale structure

ABSTRACT We present a model for the halo–mass correlation function that explicitly incorporates halo exclusion and allows for a redefinition of the halo boundary in a flexible way. We assume that haloes trace mass in a way that can be described using a single scale-independent bias parameter. However, our model exhibits scale-dependent biasing due to the impact of halo-exclusion, the use of a ‘soft’ (i.e. not infinitely sharp) halo boundary, and differences in the one halo term contributions to ξhm and ξmm. These features naturally lead us to a redefinition of the halo boundary that lies at the ‘by eye’ transition radius from the one-halo to the two-halo term in the halo–mass correlation function. When adopting our proposed definition, our model succeeds in describing the halo–mass correlation function with $\approx 2{{\ \rm per\ cent}}$ residuals over the radial range 0.1 h−1 Mpc < r < 80 h−1 Mpc, and for halo masses in the range 1013 h−1 M⊙ < M < 1015 h−1 M⊙. Our proposed halo boundary is related to the splashback radius by a roughly constant multiplicative factor. Taking the 87 percentile as reference we find rt/Rsp ≈ 1.3. Surprisingly, our proposed definition results in halo abundances that are well described by the Press–Schechter mass function with δsc = 1.449 ± 0.004. The clustering bias parameter is offset from the standard background-split prediction by $\approx 10{{\ \rm per\ cent}}\!-\!15{{\ \rm per\ cent}}$. This level of agreement is comparable to that achieved with more standard halo definitions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Rapid Population Assessment Method for Wild Pigs Using Baited Cameras at 3 Study Sites

ABSTRACT Reliable and efficient population estimates are a critical need for effective management of invasive wild pigs ( Sus scrofa ). We evaluated the use of 10‐day camera grids for rapid population assessment (RPA) of wild pigs at 3 study sites that varied in vegetation communities and wild pig densities. Study areas included Buck Island Ranch, Florida; Tejon Ranch, California; and the Savannah River Site, South Carolina, USA, during 2016–2018. Rapid population assessments grids were composed of baited camera traps spaced approximately 500 or 750 m apart. Two RPA grids were deployed per study site and each grid was deployed twice (4–6 months apart) to assess changes in response to season or population control efforts. We assessed the ability of RPA grids to track population trends, how camera number influenced estimate precision, and how relative abundance indices related to density estimates. We detected changes in occupancy probability, detection probability, and N‐mixture estimates following removal operations and between seasons, but the ability of RPA grids to track population trends was dependent on the statistical method used and number of cameras traps. Increasing the number of cameras traps used in RPA grids increased precision, and these results can be used in determining survey design and estimate choice. We found that estimates of occupancy probability, detection probability, and N‐mixture estimates were positively correlated with spatially explicit capture–recapture density estimates. Thus, these less labor‐intensive estimates from RPA grids showed potential to index the relative abundance of wild pigs in some systems. Our evaluation of RPAs indicates that using study‐specific combinations of statistical method and number of cameras can provide a useful tool for monitoring wild pig presence, tracking population trends, and evaluating the effectiveness of management actions. © 2020 The Wildlife Society.

Schlichting, Peter E.↗
DOE OSTI2025

Intrinsic Layer-Dependent Surface Energy and Exfoliation Energy of van der Waals Materials

Stacking and twisting 2D van der Waals (vdW) layers have become versatile platforms to tune the electron correlation. These platforms rely on exfoliating vdW materials down to a single vdW layer and a few vdW layers. We calculate the intrinsic layer-dependent surface and exfoliation energies of typical vdW materials such as graphite, h-BN, black P, MX 2 (M = Mo or W; X = S, Se, or Te), MX (M = Ga or In; X = S, Se, or Te), Bi 2 Te 3 , and MnBi 2 Te 4 using density functional theory. For exchange-correlation functionals with explicit vdW interaction, a single vdW layer always has the smallest surface energy, giving a surface energy reduction when compared to that of thicker vdW layers. Furthermore, the magnitude of this surface energy reduction quickly decreases with an increase in the number of atomic layers inside the single vdW layer for different vdW materials. Such atomic-layer dependence in surface energy reduction helps explain the different effectiveness of exfoliation for different vdW materials down to a single vdW layer.

Anode materials↗
DOE OSTI2024

Climate change-resilient snowpack estimation in the Western United States

Abstract In the 21st century, warmer temperatures and changing atmospheric circulation will likely produce unprecedented changes in Western United States snowfall 1–3 , with impacts on the timing, amount, and spatial patterns of snowpack 4–7 . The ~900 snow pillow stations are indispensable to water resource management by measuring snow-water equivalent (SWE) 8,9 in strategic but fixed locations 10,11 . However, this network may not be impacted by climate change in the same way as the surrounding area 12 and thus fail to accurately represent unmeasured locations; climate change thereby threatens our ability to measure the effects of climate change on snow. In this work, we show that maintaining the current peak SWE estimation skill is nonetheless possible. We find that explicitly including spatial correlations—either from gridded observations or learned by the model—improves skill at predicting distributed snowpack from sparse observations by 184%. Existing artificial intelligence methods can be useful tools to harness the many available sources of snowpack information to estimate snowpack in a nonstationary climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Assessing electronic structure approaches for gas-ligand interactions in metal-organic frameworks: The CO{sub 2}-benzene complex

Adsorption of gas molecules in metal-organic frameworks is governed by many factors, the most dominant of which are the interaction of the gas with open metal sites, and the interaction of the gas with the ligands. Herein, we examine the latter class of interaction in the context of CO{sub 2} binding to benzene. We begin by clarifying the geometry of the CO{sub 2}–benzene complex. We then generate a benchmark binding curve using a coupled-cluster approach with single, double, and perturbative triple excitations [CCSD(T)] at the complete basis set (CBS) limit. Against this ΔCCSD(T)/CBS standard, we evaluate a plethora of electronic structure approximations: Hartree-Fock, second-order Møller-Plesset perturbation theory (MP2) with the resolution-of-the-identity approximation, attenuated MP2, and a number of density functionals with and without different empirical and nonempirical van der Waals corrections. We find that finite-basis MP2 significantly overbinds the complex. On the other hand, even the simplest empirical correction to standard density functionals is sufficient to bring the binding energies to well within 1 kJ/mol of the benchmark, corresponding to an error of less than 10%; PBE-D in particular performs well. Methods that explicitly include nonlocal correlation kernels, such as VV10, vdW-DF2, and ωB97X-V, perform with similar accuracy for this system, as do ωB97X and M06-L.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗