Further investigations of random numbers
Random numbers generated by linear recurrence modulo 2 and correlation and distribution functions
CORRELATION FUNCTION↗
SEARCH · Engineering Papers
Results for “correlation functions”
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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Detection of monaural signals as a function of interaural noise correlation and signal frequency.
Interaural correlation effects for masking noise in ear detection of monaural signals
Whitmore, J. K.↗
Fine structure of transient waves in a random medium: The correlation and spectral density functions
This is essentially a progress report on a theoretical investigation of the propagation of transient waves in a random medium. The emphasis in this study is on applications to sonic-boom propagation, particularly as regards the effect of atmospheric turbulence on the sonic-boom waveform. The analysis is general, however, and is applicable to other types of waves besides sonic-boom waves. The phenomenon of primary concern in this investigation is the fine structure of the wave. A figure is used to illustrate what is meant by finestructure.
Wenzel, Alan R.↗
Long-term modulation of galactic cosmic radiation and its model for space exploration
As the human exploration of space has received new attention in the United States, studies find that exposure to space radiation could adversely impact the mission design. Galactic Cosmic Radiation (GCR), with its very wide range of charges and energies, is particularly important for a mission to Mars, because it imposes a stiff mass penalty for spacecraft shielding. Dose equivalent versus shielding thickness calculations, show a rapid initial drop on exposure with thickness, but an asymptotic behavior at a higher shielding thickness. Uncertainties in the radiobiology are largely unknown. For a fixed radiation risk, this leads to large uncertainties in shielding thickness for small uncertainties in estimated dose. In this paper we investigate the application of steady-state, spherically-symmetric diffusion-convection theory of solar modulation to individual measurements of differential energy spectra from 1954 to 1989 in order to estimate the diffusion coefficient, kappa(r,t), as a function of time. We have correlated the diffusion coefficient to the Climax neutron monitor rates and show that, if the diffusion coefficient can be separated into independent functions of space and time: kappa(r,t)=K(t) k(sub 0) beta Pk(sub 1) (r), where beta is the particle velocity and P the rigidity, then (i) The time dependent quantity 1/K(t), which is proportional to the deceleration potential, phi(r,t), is linearly related to the Climax neutron monitor counting rate. (ii) The coefficients obtained from hydrogen or helium intensity measurements are the same. (iii) There are different correlation functions for odd and even solar cycles. (iv) The correlation function for the Climax neutron monitor counting rate for given time, t, can be used to estimate mean deceleration parameter phi(t) to within +/- 15% with 90% confidence. We have shown that k(r,t) determined from hydrogen and/or helium data, can be used to fit the oxygen and iron differential energy spectra with a root mean square error of about +/- 10%, and essentially independent of the particle charge or energy. We have also examined the ion chamber and C-14 measurements which allow the analysis to be extended from the year 1906 to 1990. Using this model we have defined reference GCR spectra at solar minimum and solar maximum. These can be used for space exploration studies and provide a quantitative estimate of the error in dose due to changes in GCR intensities.
Badhwan, G. D.↗
Photon scattering cross sections of H2 and He measured with synchrotron radiation
Total (elastic + inelastic) differential photon scattering cross sections have been measured for H2 gas and He, using an X-ray beam. Absolute measured cross sections agree with theory within the probable errors. Relative cross sections (normalized to theory at large S) agree to better than one percent with theoretical values calculated from wave functions that include the effect of electron-electron Coulomb correlation, but the data deviate significantly from theoretical independent-particle (e.g., Hartree-Fock) results. The ratios of measured absolute He cross sections to those of H2, at any given S, also agree to better than one percent with theoretical He-to-H2 cross-section ratios computed from correlated wave functions. It appears that photon scattering constitutes a very promising tool for probing electron correlation in light atoms and molecules.
Ice, G. E.↗
Photon-scattering cross sections of H2 and He measured with synchrotron radiation
Total (elastic + inelastic) differential photon-scattering cross sections have been measured for H2 gas and for He, using an X-ray beam. Absolute measured cross sections agree with theory within the probable errors. Relative cross sections (normalized to theory at large S) agree to better than 1% with theoretical values calculated from wave functions that include the effect of electron-electron Coulomb correlation, but the data deviate significantly from theoretical independent-particle (e.g., Hartree-Fock) results. The ratios of measured absolute He cross sections to those of H2, at any given S, also agree to better than 1% with theoretical He-to-H2 cross-section ratios computed from correlated wave functions. It appears that photon scattering constitutes a very promising tool for probing electron correlation in light atoms and molecules. The degree of polarization of the synchrotron radiation beam has been measured by rotating the scattering plane about the beam axis; results are compared with theory.
Ice, G. E.↗
First-order wavefunctions, orbital correlation energies, and electron affinities of first-row atoms
First order wave functions orbital correlation energies and electron affinities of first row atoms for low lying electronic states of B, C, N, O, F and Ne
Harris, F. E.↗
Algorithms For Detection Of Correlation Spots
Three algorithms provide for improved postprocessing of outputs of optical correlators based on binary phase-only filters. Detect correlation spots. Function in presence of noise and executed rapidly. First algorithm starts processing correlation-image data while data fed out of video camera and digitized for subsequent analysis. Second involves convolution of correlation image with small-window two-dimensional impulse-response function followed by threshold operation in which negative values of convolution integral set to zero. Third affects generation as well as postprocessing of correlation image.
Scholl, Marija S.↗
Techniques and errors in measuring cross- correlation and cross-spectral density functions
Instrument errors and data reduction techniques for dynamic pressure cross correlation and cross spectral density function measurements
DATA REDUCTION↗
Temporal Error Correlations in a Terrestrial Carbon Cycle Model Derived by Comparison to Carbon Dioxide Eddy Covariance Flux Tower Measurements
Abstract Atmospheric CO 2 flux inversions require as input an estimate of spatial and temporal correlations of errors in their estimate of the prior mean. Some previous studies have used the differences in CO 2 daily average flux estimates produced by terrestrial carbon cycle models and eddy covariance measurements to constrain the flux error correlations. Since inversions are starting to resolve the daily cycle, we set out to examine the correlations at sub‐daily time scales, as well as the correlations across years. To this end, we examine the autocorrelations in the difference between net ecosystem‐atmosphere exchange measurements from 75 AmeriFlux towers and temporally downscaled high‐spatial‐resolution flux estimates from the Carnegie‐Ames‐Stanford Approach (CASA) terrestrial carbon cycle model. We find that the daily cycle is prominent in these hourly autocorrelations and that these autocorrelations persist across years. We propose a family of functions to model these temporal correlations in atmospheric inversions, and use cross validation to determine which of the correlation functions best fits autocorrelation data from towers not in the training set. Correlation functions with a component that attempts to model the daily cycle in the differences match correlations from other towers better than those without. Those models that reproduce the same correlation structures at 1‐year intervals while modulating the amplitudes of the correlations between those intervals improve the fit still further.
54 ENVIRONMENTAL SCIENCES↗
GPU acceleration of local and semilocal density functional calculations in the SPARC electronic structure code
We present a Graphics Processing Unit (GPU)-accelerated version of the real-space SPARC electronic structure code for performing Kohn–Sham density functional theory calculations within the local density and generalized gradient approximations. In particular, we develop a modular math-kernel based implementation for NVIDIA architectures wherein the computationally expensive operations are carried out on the GPUs, with the remainder of the workload retained on the central processing units (CPUs). Here, using representative bulk and slab examples, we show that relative to CPU-only execution, GPUs enable speedups of up to 6× and 60× in node and core hours, respectively, bringing time to solution down to less than 30 s for a metallic system with over 14 000 electrons and enabling significant reductions in computational resources required for a given wall time.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Modeling of pressure-induced far-infrared absorption spectra Molecular hydrogen pairs
Meyer et al. (1985) have calculated the accurate induced dipole moment function of H2-H2 from first principles, using highly correlated wave functions for the first time in such work. The present paper is concerned with the collision-induced translational-rotational absorption coefficient for molecular hydrogen pairs, taking into account computations on the basis of the fundamental theory considered by Meyer et al. Data have been obtained for temperatures in the range from 40 to 300 K. Criteria are developed for choosing among various model line shapes. It is found that certain models are capable of approximating the quantum profiles closely, with rms errors of only a few percent.
Borysow, J.↗
ν-point energy correletors with F AST EEC: Small-x physics from LHC jets
In recent years, energy correlators have emerged as a powerful tool for studying jet substructure, with promising applications such as probing the hadronization transition, analyzing the quark-gluon plasma, and improving the precision of top quark mass measurements. The projected N-point correlator measures correlations between N final-state particles by tracking the largest separation between them, showing a scaling behavior related to DGLAP splitting functions. These correlators can be analytically continued in N, commonly referred to as ν-correlators, allowing access to non-integer moments of the splitting functions. Of particular interest is the ν → 0 limit, where the small momentum fraction behavior of the splitting functions requires resummation. Originally, the computational complexity of evaluating ν-correlators for M particles scaled as 2 2M , making it impractical for real-world analyses. However, by using recursion, we reduce this to M 2M , and through the FastEEC method of dynamically resolving subjets, M is replaced by the number of subjets. This breakthrough enables, for the first time, the computation of ν-correlators for LHC data. In practice, limiting the number of subjets to 16 is sufficient to achieve percent-level precision, which we validate using known integer-ν results and convergence tests for non-integer ν. We have implemented this in an update to FastEEC and conducted an initial study of power-law scaling in the perturbative regime as a function of ν, using CMS Open Data on jets. The results agree with DGLAP evolution, except at small ν, where the anomalous dimension saturates to a value that matches the BFKL anomalous dimension.
Energy correlators↗
The Ground State Electronic Energy of Benzene
We report here on the findings of a blind challenge devoted to determining the frozen-core, full configuration interaction (FCI) ground-state energy of the benzene molecule in a standard correlation-consistent basis set of double-ζ quality. As a broad international endeavor, our suite of wave function-based correlation methods collectively represents a diverse view of the high-accuracy repertoire offered by modern electronic structure theory. In our assessment, the evaluated high-level methods are all found to qualitatively agree on a final correlation energy, with most methods yielding an estimate of the FCI value around -863 mE H . However, we find the root-mean-square deviation of the energies from the studied methods to be considerable (1.3 mE H ), which in light of the acclaimed performance of each of the methods for smaller molecular systems clearly displays the challenges faced in extending reliable, near-exact correlation methods to larger systems. While the discrepancies exposed by our study thus emphasize the fact that the current state-of-the-art approaches leave room for improvement, we still expect the present assessment to provide a valuable community resource for benchmark and calibration purposes going forward.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learning for accuracy in density functional approximations
Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Effect of XC functionals and dispersion corrections on the DFT‐computed structural and vibrational properties of SrCl 2 –NaCl and ZrF 4 –LiF
Density functional theory (DFT) calculations were performed to examine the impact of exchange–correlation (XC) functionals and van der Waals corrections (specifically the D3 method) on the structural and vibrational properties of the SrCl 2 –NaCl and ZrF 4 –LiF salt systems. Multiple XC functionals, including the local density approximation (LDA), the generalized gradient approximation using the Perdew–Burke–Ernzerhof (PBE) model, and its modified form suitable for solids (PBEsol), the dispersion-corrected PBE-D3 and PBEsol-D3, were considered. Of these functionals, LDA was found to exhibit the highest degree of error, while PBEsol and PBE-D3 displayed the least error. Underestimated lattice parameters compared with experimental values were observed to result in higher force constants, leading to an overprediction of vibrational frequencies. Conversely, an overestimation of lattice parameters was associated with lower vibrational frequencies. The methodology presented in this study yielded results that are in good agreement with experiment, irrespective of the method (finite differences vs. density functional perturbation theory) employed for calculating infrared and Raman spectra. It was further demonstrated that for alkali halides with weak Raman scattering, utilizing a supercell constructed from primitive cells better predicts Raman features than does the use of conventional cells.
Raman↗
DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models
We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗