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DOE OSTI2026

NuLattice: Ab initio computations of atomic nuclei on lattices

Here, we introduce NuLattice, a Python software package for ab initio computations of atomic nuclei on lattices. The computational tools consist of Hartree Fock, the coupled cluster method, the in-medium similarity renormalization group, and full configuration interaction. At present, the employed interactions are from pion-less effective field theory at leading order and consist of two-body and three-body contacts. We present results for light nuclei 2 H, 3,4 He, 8 Be, 12 C, and 16 O. NuLattice algorithms exploit the sparsity and locality of lattice interactions, and as a result computations can be run on laptops.

Rothman, Maxwell [Univ. of Tennessee, Knoxville, T↗

DOE OSTI2022

Insights on sources and formation mechanisms of liquid-bearing clouds over MOSAiC examined from a Lagrangian framework

Understanding Arctic stratiform liquid-bearing cloud life cycles and properly representing these life cycles in models is crucial for evaluations of cloud feedbacks as well as the faithfulness of climate projections for this rapidly warming region. Examination of cloud life cycles typically requires analyses of cloud evolution and origins on short time scales, on the order of hours to several days. Measurements from the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide a unique view of the current state of the central Arctic over an annual cycle. Here, we use the MOSAiC radiosonde measurements to detect liquid-bearing cloud layers over full atmospheric columns and to examine the cloud-generating air masses’ properties. We perform 5-day (120 h) back-trajectory calculations for every detected cloud and cluster them using a unique set of variables extracted from these trajectories informed by ERA5 reanalysis data. This clustering method enables us to separate between the air mass source regions such as ice-covered Arctic and midlatitude open water. We find that moisture intrusions into the central Arctic typically result in multilayer liquid-bearing cloud structures and that more than half of multilayer profiles include overlying liquid-bearing clouds originating in different types of air masses. Finally, we conclude that Arctic cloud formation via prolonged radiative cooling of elevated stable subsaturated air masses circulating over the Arctic can occur frequently (up to 20% of detected clouds in the sounding data set) and may lead to a significant impact of ensuing clouds on the surface energy budget, including net surface warming in some cases.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Evaluation of Seismic Artificial Intelligence with Uncertainty

Artificial intelligence has transformed the seismic community with deep learning models (DLMs) that are trained to complete specific tasks within workflows. However, there is still a lack of robust evaluation frameworks for evaluating and comparing DLMs. Here, we address this gap by designing an evaluation framework that jointly incorporates two crucial aspects: performance uncertainty and learning efficiency. To target these aspects, we meticulously construct the training, validation, and test splits using a clustering method tailored to seismic data and enact an expansive training design to segregate performance uncertainty arising from stochastic training processes and random data sampling. The framework’s ability to guard against misleading declarations of model superiority is demonstrated through the evaluation of PhaseNet (Zhu and Beroza, 2018), a popular seismic phase picking DLM, under three training approaches. Our framework helps practitioners choose the best model for their problem and set performance expectations by explicitly analyzing model performance with uncertainty at varying budgets of training data.

58 GEOSCIENCES↗

DOE OSTI2020

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

LBNL CRADA (FP00009949) with the American Public Power Association: Electricity Reliability Metrics, Analysis, and Planning (Final Technical Report)

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Electricity Reliability Metrics, Analysis, and Planning (CRADA Final Report)

LBNL and APPA (the team) jointly examined the extent to which differences in distribution feeder characteristics are correlated with differences in their reliability performance when exposed to three different types of natural hazards (wildlife, weather, and vegetation). The team employed data-driven approaches to quantify the relationships between various measures of feeder reliability and a suite of feeder characteristics individually and jointly via a statistically-based clustering method. The team developed suggestions on how comparisons across groupings of feeders and review of the relative contributions of the constituents of SAIFI and SAIDI could be used to help prioritize utility actions to improve reliability. However, they also caution that their suggestions require further evaluation because they are based on only one year of information from a modest number of small utilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1974

Nineteen hundred seventy three significant accomplishments

Data collected by the Skylab remote sensing satellites was used to develop applications techniques and to combine automatic data classification with statistical clustering methods. Continuing research was concentrated in the correlation and registration of data products and in the definition of the atmospheric effects on remote sensing. The causes of errors encountered in the automated classification of agricultural data are identified. Other applications in forestry, geography, environmental geology, and land use are discussed.

Source record↗

NASA NTRS1976

Digital processing of satellite imagery application to jungle areas of Peru

The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

Pomalaza, J. C.↗

NASA NTRS1978

The CLASSY clustering algorithm: Description, evaluation, and comparison with the iterative self-organizing clustering system (ISOCLS)

A clustering method, CLASSY, was developed, which alternates maximum likelihood iteration with a procedure for splitting, combining, and eliminating the resulting statistics. The method maximizes the fit of a mixture of normal distributions to the observed first through fourth central moments of the data and produces an estimate of the proportions, means, and covariances in this mixture. The mathematical model which is the basic for CLASSY and the actual operation of the algorithm is described. Data comparing the performances of CLASSY and ISOCLS on simulated and actual LACIE data are presented.

Lennington, R. K.↗

NASA NTRS1980

ICAP: An Interactive Cluster Analysis Procedure for analyzing remotely sensed data

An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. The algorithm interfaces the rapid numerical processing capacity of a computer with the human ability to integrate qualitative information. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters and the analyst, who evaluate and elect to modify the cluster structure. Clusters can be deleted or lumped pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The ICAP was implemented in APL (A Programming Language), an interactive computer language. The flexibility of the algorithm was evaluated using data from different LANDSAT scenes to simulate two situations: one in which the analyst is assumed to have no prior knowledge about the data and wishes to have the clusters formed more or less automatically; and the other in which the analyst is assumed to have some knowledge about the data structure and wishes to use that information to closely supervise the clustering process. For comparison, an existing clustering method was also applied to the two data sets.

Wharton, S. W.↗

NASA NTRS1989

Decision net, directed graph, and neural net processing of imaging spectrometer data

A decision-net solution involving a novel hierarchical classifier and a set of multiple directed graphs, as well as a neural-net solution, are respectively presented for large-class problem and mixture problem treatments of imaging spectrometer data. The clustering method for hierarchical classifier design, when used with multiple directed graphs, yields an efficient decision net. New directed-graph rules for reducing local maxima as well as the number of perturbations required, and the new starting-node rules for extending the reachability and reducing the search time of the graphs, are noted to yield superior results, as indicated by an illustrative 500-class imaging spectrometer problem.

Casasent, David↗

NASA NTRS1991

Analytic gradients for coupled-cluster energies that include noniterative connected triple excitations - Application to cis- and trans-HONO

An efficient formulation of the analytic energy gradient for the single and double excitation coupled-cluster method that includes a perturbational estimate of the effects of connected triple excitations is presented. The formulation has a small computational cost, and the algebraic manipulations may be applied generally to the analytic gradient of Moller-Plesset perturbation theory energies. The new formulation has been implemented in an efficient set of programs that utilize highly vectorized algorithms and has been used to investigate the equilibrium structures, harmonic vibrational frequencies, IR intensities, and energy separation of cis- and trans-HONO.

Lee, Timothy J.↗

NASA NTRS1992

On the performance of large Gaussian basis sets for the computation of total atomization energies

The total atomization energies of a number of molecules have been computed using an augmented coupled-cluster method and (5s4p3d2f1g) and 4s3p2d1f) atomic natural orbital (ANO) basis sets, as well as the correlation consistent valence triple zeta plus polarization (cc-pVTZ) correlation consistent valence quadrupole zeta plus polarization (cc-pVQZ) basis sets. The performance of ANO and correlation consistent basis sets is comparable throughout, although the latter can result in significant CPU time savings. Whereas the inclusion of g functions has significant effects on the computed Sigma D(e) values, chemical accuracy is still not reached for molecules involving multiple bonds. A Gaussian-1 (G) type correction lowers the error, but not much beyond the accuracy of the G1 model itself. Using separate corrections for sigma bonds, pi bonds, and valence pairs brings down the mean absolute error to less than 1 kcal/mol for the spdf basis sets, and about 0.5 kcal/mol for the spdfg basis sets. Some conclusions on the success of the Gaussian-1 and Gaussian-2 models are drawn.

Martin, J. M. L.↗

NASA NTRS1992

An accurate ab initio quartic force field for ammonia

The quartic force field of ammonia is computed using basis sets of spdf/spd and spdfg/spdf quality and an augmented coupled cluster method. After correcting for Fermi resonance, the computed fundamentals and nu 4 overtones agree on average to better than 3/cm with the experimental ones except for nu 2. The discrepancy for nu 2 is principally due to higher-order anharmonicity effects. The computed omega 1, omega 3, and omega 4 confirm the recent experimental determination by Lehmann and Coy (1988) but are associated with smaller error bars. The discrepancy between the computed and experimental omega 2 is far outside the expected error range, which is also attributed to higher-order anharmonicity effects not accounted for in the experimental determination. Spectroscopic constants are predicted for a number of symmetric and asymmetric top isotopomers of NH3.

Martin, J. M. L.↗

NASA NTRS1993

Accurate ab initio quartic force fields for the ions HCO(+) and HOC(+)

The quartic force fields of HCO(+) and HOC(+) have been computed using augmented coupled cluster methods and basis sets of spdf and spdfg quality. Calculations on HCN, CO, and N2 have been performed to assist in calibrating the computed results. Going from an spdf to an spdfg basis shortens triple bonds by about 0.004 A, and increases the corresponding harmonic frequency by 10-20/cm, leaving bond distances about 0.003 A too long and triple bond stretching frequencies about 5/cm too low. Accurate estimates for the bond distances, fundamental frequencies, and thermochemical quantities are given. HOC(+) lies 37.8 +/- 0.5 kcal/mol (0 K) above HCO(+); the classical barrier height for proton exchange is 76.7 +/- 1.0 kcal/mol.

Martin, J. M. L.↗

NASA NTRS1992

A global ab initio potential for HCN/HNC, exact vibrational energies, and comparison to experiment

An ab initio (i.e., from first principles) calculation of vibrational energies of HCN and HNC is reported. The vibrational calculations were done with a new potential derived from a fit to 1124 ab initio electronic energies which were calculated using the highly accurate CCSD(T) coupled-cluster method in conjunction with a large atomic natural orbital basis set. The properties of this potential are presented, and the vibrational calculations are compared to experiment for 54 vibrational transitions, 39 of which are for zero total angular momentum, J = 0, and 15 of which are for J = 1. The level of agreement with experiment is unprecedented for a triatomic with two nonhydrogen atoms, and demonstrates the capability of the latest computational methods to give reliable predictions on a strongly bound triatomic molecule at very high levels of vibrational excitation.

Bentley, Joseph A.↗

NASA NTRS1994

An Accurate Quartic Force Field and Vibrational Frequencies for HNO and DNO

An accurate ab initio quartic force field for HNO has been determined using the singles and doubles coupled-cluster method that includes a perturbational estimate of the effects of connected triple excitations, CCSD(T), in conjunction with the correlation consistent polarized valence triple zeta (cc-pVTZ) basis set. Improved harmonic frequencies were determined with the cc-pVQZ basis set. Fundamental vibrational frequencies were determined using a second-order perturbation theory analysis and also using variational calculations. The N-0 stretch and bending fundamentals are determined well from both vibrational analyses. The H-N stretch, however, is shown to have an unusually large anharmonic correction, and is not well determined using second-order perturbation theory. The H-N fundamental is well determined from the variational calculations, demonstrating the quality of the ab initio quartic force field. The zero-point energy of HNO that should be used in isodesmic reactions is also discussed.

Dateo, Christopher E.↗

NASA NTRS1995

A Correlated Ab Initio Study of Linear Carbon-Chain Radicals C(sub n)H (n=2-7)

Linear carbon-chain radicals C(sub n) H for n = 2-7 have been studied with correlation consistent valence and core-valence basis sets and the coupled cluster method RCCSD(T). Equilibrium structures, rotational constants, and dipole moments are reported and compared with available experimental data. The ground state of the even-n series changes from 2Sigma(+) to 2Pi as the chain is extended. For C4H, the 2Sigma(+) state was found to lie only 72 cm(exp -1) below the 2Pi state in the estimated complete basis set limit for valence correlation. The C2H(-) and C3H(-) anions have also been characterized.

Woon, David E.↗