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Statistical Homogenization of Elastic and Fracture Properties of a Sample Selective Laser Melting Material

Selective laser melting (SLM) is an additive manufacturing technique commonly used in the rapid prototyping of components. The complexity of the SLM microstructure poses a unique challenge to deriving effective mechanical properties at different length scales. Representative volume elements (RVEs) are often used to homogenize the material properties of composites. Instead of RVEs, we use statistical volume elements (SVEs) to homogenize the elastic and fracture properties of the material. This relates the inherent variation of a material’s microstructure to the variation in its mechanical properties at different observation scales. The convergence to the RVE limit is examined from two perspectives: the stability of the mean value as the SVE size increases for the mean-based approach, and the tendency of the normalized variation in homogenized properties to zero as the SVE size increases for the variation-based approach. Fracture properties tend to make the RVE limit slower than do elastic properties from both perspectives. There are also differences between vertical (normal to printing plane) and horizontal (in-plane) properties. While the elastic properties tend to make the RVE limit faster for the horizontal direction, i.e., having a smaller variation and more stable mean value, the fracture properties exhibit the opposite effect. We attributed these differences to the geometry of the melt pools.

36 MATERIALS SCIENCE↗

Thermochemistry of the smallest QOOH radical from the roaming fragmentation of energy selected methyl hydroperoxide ions

Here, the dissociative photoionization processes of methyl hydroperoxide (CH 3 OOH) have been studied by imaging Photoelectron Photoion Coincidence (iPEPICO) spectroscopy experiments as well as quantum-chemical and statistical rate calculations. Energy selected CH 3 OOH + ions dissociate into CH 2 OOH + , HCO + , CH 3 + , and H 3 O + ions in the 11.4–14.0 eV photon energy range. The lowest-energy dissociation channel is the formation of the cation of the smallest “QOOH” radical, CH 2 OOH + . An extended RRKM model fitted to the experimental data yields a 0 K appearance energy of 11.647 ± 0.005 eV for the CH 2 OOH + ion, and a 74.2 ± 2.6 kJ mol -1 mixed experimental-theoretical 0 K heat of formation for the CH 2 OOH radical. The proton affinity of the Criegee intermediate, CH 2 OO, was also obtained from the heat of formation of CH 2 OOH + (792.8 ± 0.9 kJ mol -1 ) to be 847.7 ± 1.1 kJ mol - 1, reducing the uncertainty of the previously available computational value by a factor of 4. RRKM modeling of the complex web of possible rearrangement-dissociation processes was used to model the higher-energy fragmentation. Supported by Born–Oppenheimer molecular dynamics simulations, we found that the HCO + fragment ion is produced through a roaming transition state followed by a low barrier. Lastly, H 3 O + is formed in a consecutive process from the CH 2 OOH + fragment ion, while direct C–O fission of the molecular ion leads to the methyl cation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum statistical plasmonic metacrystals

Engineering materials that control quantum many-body dynamics remains challenging, as multiparticle interactions typically produce complex emergent behaviour that is difficult to predict. Here we introduce quantum statistical plasmonic metacrystals, structures in which the multiparticle dynamics mediated by optical near fields produce forbidden quantum statistical bands that enable selective transmission of different types of light. This functionality arises from a plasmonic structure composed of nanoantennas acting as meta-atoms. Multiphoton fields with statistics within the allowed bands propagate without distortion, whereas fields in forbidden bands are suppressed or driven towards the nearest accessible statistical state. We show that these bands are determined by the geometry and collective arrangement of the meta-atoms, providing a deterministic route to engineering quantum statistical transport. This platform establishes a room-temperature quantum material intrinsically sensitive to the quantum coherence of many-body photonic systems, enabling their robust manipulation and transport. Our results have implications for coherence-sensitive photonic materials for energy harvesting and scalable many-body quantum technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Statistical searches for microlensing events in large, non-uniformly sampled time-domain surveys: A test using palomar transient factory data

Many photometric time-domain surveys are driven by specific goals, such as searches for supernovae or transiting exoplanets, which set the cadence with which fields are re-imaged. In the case of the Palomar Transient Factory (PTF), several sub-surveys are conducted in parallel, leading to non-uniform sampling over its ∼20,000 deg{sup 2} footprint. While the median 7.26 deg{sup 2} PTF field has been imaged ∼40 times in the R band, ∼2300 deg{sup 2} have been observed >100 times. We use PTF data to study the trade off between searching for microlensing events in a survey whose footprint is much larger than that of typical microlensing searches, but with far-from-optimal time sampling. To examine the probability that microlensing events can be recovered in these data, we test statistics used on uniformly sampled data to identify variables and transients. We find that the von Neumann ratio performs best for identifying simulated microlensing events in our data. We develop a selection method using this statistic and apply it to data from fields with >10 R-band observations, 1.1 × 10{sup 9} light curves, uncovering three candidate microlensing events. We lack simultaneous, multi-color photometry to confirm these as microlensing events. However, their number is consistent with predictions for the event rate in the PTF footprint over the survey's three years of operations, as estimated from near-field microlensing models. This work can help constrain all-sky event rate predictions and tests microlensing signal recovery in large data sets, which will be useful to future time-domain surveys, such as that planned with the Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation Free Energies

This paper applies the Bayesian Model Averaging (BMA) statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range methods for predicting solvation free energies, ranging from empirical statistical models to {\it ab initio} quantum mechanical approaches. Each of these methods are based on a set of conceptual assumptions that can affect a method's predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the SAMPL4 blind prediction study to form a single, aggregated solvation energy estimate. The ensemble design process evaluates the statistical information in each individual method as well as the performance of the aggregate estimate obtained from the ensemble as a whole. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal/mol accuracy. We also compare our iterative refinement approach to other statistical ensemble approaches and demonstrate that this iterative process reduces estimate errors by as much as 61%. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with predictive accuracy.

solvation, Bayesian model averaging, Electrostatic↗

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as imaging systematics. In this paper, we present the imaging systematics mitigation applied to the DESI Data Release 1 (DR1) large-scale structure catalogs used in the DESI 2024 cosmological analyses. We also explore extensions of the fiducial treatment. This includes a combined approach, through forward image simulations (Obiwan) in conjunction with neural network-based regression, to obtain an angular selection function that mitigates the imaging systematics observed in the DESI DR1 ELGs target density. We further derive a line of sight selection function from the forward model that removes the strong redshift dependence between imaging systematics and low redshift ELGs. Combining both angular and redshift-dependent systematics, we construct a three-dimensional selection function and assess the impact of all selection functions on clustering statistics. We quantify differences between these extended treatments and the fiducial treatment in terms of the measured 2-point statistics. We find that the results are generally consistent with the fiducial treatment and conclude that the differences are far less than the imaging systematics uncertainty included in DESI 2024 full-shape measurements. We extend our investigation to the ELGs at 0.6 < z < 0.8, i.e., beyond the redshift range (0.8 < z < 1.6) adopted for the DESI clustering catalog, and demonstrate that determining the full three-dimensional selection function is necessary in this redshift range. Our tests showed that all changes are consistent with statistical noise for BAO analyses indicating they are robust to even severe imaging systematics. Specific tests for the full-shape analysis will be presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

Predicting Catalytic Pyrolysis Aromatic Selectivity from Pyrolysis Vapor Composition Using Mass Spectra Coupled with Statistical Analysis

The behavior of fast pyrolysis (FP) and catalytic FP (CFP) of 20 renewable feedstocks was studied in a microscale reactor with molecular beam mass spectral analysis of products generated. A partial least-squares (PLS) model was constructed based on the FP vapor spectra that predicts the aromatic selectivity when upgrading over a ZSM-5 catalyst. Additionally, principal component analysis of both FP and CFP spectra was performed for comprehensive spectral analysis. This work highlighted the value of vapor-phase mass spectral screening to predict the subsequent feedstock performance and demonstrated that the quantity of coke deposited on the catalyst is not a reliable measure of catalyst deactivation when the feedstock type is varied.

09 BIOMASS FUELS↗

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same is for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project.

60 APPLIED LIFE SCIENCES↗

Grain growth competition during thin-sample directional solidification of dendritic microstructures: A phase-field study

Here we present the results of a comprehensive phase-field study of columnar grain growth competition in bi-crystalline samples in two dimensions (2D) and in three dimensions (3D) for small sample thicknesses allowing a single row of dendrites to form. We focus on the selection of grain boundary (GB) orientation during directional solidification in the steady-state dendritic regime, and study its dependence upon the orientation of two competing grains. In 2D, we map the entire orientation range for both grains, performing several simulations for each configuration to account for the stochasticity of GB orientation selection and to assess the average GB behavior. We find that GB orientation selection depends strongly on whether the primary dendrite growth directions have lateral components (i.e. components perpendicular to the axis of the temperature gradient) that point in the same or opposite directions in the two grains. Here, we identify a range of grain orientations in which grain selection follows the classical description of Walton and Chalmers. We also identify conditions that favor unusual overgrowth of favorably-oriented dendrites at a converging GB. We propose a simple analytical description that reproduces the average GB orientation selection from 2D simulations within statistical fluctuations of a few degrees. In 3D, we find a similar GB orientation selection as in 2D when secondary branches grow in planes parallel and perpendicular to the sample walls. Remarkably, quasi-2D behavior is also observed even when those perpendicular sidebranching planes are rotated by a finite azimuthal angle about the primary dendrite growth axis as long as the absolute values of those azimuthal angles are equal in both grains. In contrast, when the absolute values of those azimuthal angles differ markedly, we find that unusual overgrowth events at a converging GB are promoted by a high azimuthal angle in the least-favorably-oriented grain. We also find that diverging GBs can be strongly affected by those azimuthal angles, while converging GBs exhibit a weak dependence on those angles. Finally, for diverging GBs, GB orientation is also strongly affected by the relative signs of the lateral components of the primary dendrite growth directions in both grains.

36 MATERIALS SCIENCE↗

Mechanism of Hydrocarbon Functionalization by an Iodate/Chloride System: The Role of Ester Protection

Mixtures of chloride and iodate salts for light alkane oxidation achieve > 20% yield of methyl trifluoroacetate (TFA) from methane with > 85% selectivity (J. Am. Chem. Soc. 2014, 136, 8393-8401). The mechanism of this C–H oxygenation has been probed by examining adamantane as a model substrate. These recent results lend support to the involvement of free radicals. Comparative studies between radical chlorination and iodate/chloride functionalization of adamantane afford statistically identical 3°:2° selectivities (~5.2:1) and kinetic isotope effects for C–H/C–D functionalization {kH/kD = 1.52(3) and 1.6(3)}. Alkane functionalization by iodate/chloride in HTFA is proposed to occur through H-atom abstraction by free radical species including Cl· to give alkyl radicals. Iodine, which forms by in situ reduction of iodate, traps the alkyl radicals as alkyl radicals that are subsequently converted to alkyl esters in HTFA solvent. Importantly, the alkyl ester products (RTFA) are quite stable to further oxidation under the oxidizing conditions due to the protecting nature of the ester moiety.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective deuteration illuminates the importance of tunneling in the unimolecular decay of Criegee intermediates to hydroxyl radical products

Significance Ozonolysis of volatile biogenic and anthropogenic alkenes is a significant source of hydroxyl radicals, a key oxidant in the troposphere. A critical step in the generation of hydroxyl radicals is a hydrogen-atom transfer reaction involving a carbonyl oxide species, known as the Criegee intermediate. In this study, experiment and statistical theory reveal that selective deuteration of a Criegee intermediate results in deuterium atom transfer and slows the release of hydroxyl- d radicals. A large kinetic isotope effect is found at energies near the classical barrier to reaction and under thermal conditions relevant to the atmosphere. This demonstrates that quantum mechanical tunneling significantly enhances the rate of production of hydroxyl radicals in alkene ozonolysis reactions under atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rainfall erosivity in Slovenia: Sensitivity estimation and trend detection

Highlights: • Rainfall erosivity for 10 rainfall stations located in Slovenia was evaluated. • Rainfall erosivity trends are mostly positive while mostly statistically insignificant. • The maximum rainfall erosivity is obtained under Alpine climate. • Monthly rainfall erosivity was computed. • Sensitivity analyses were carried out. Slovenia is one of the EU countries with the largest values and largest amounts of variability in rainfall erosivity, with maximum annual values exceeding 10,000 MJ mm ha{sup -1} h{sup -1} yr{sup -1}. Five-minute rainfall data was analysed from 10 Slovenian rainfall stations with data-length availability longer than 25 years with a maximum data length of 69 years and a total data-station length equal to 443 years. Trends in the rainfall erosivity R-factor were detected for four different sub-samples using monthly, half-year, and annual rainfall erosivity values. The results indicate that rainfall erosivity trends for the selected Slovenian stations are mostly statistically insignificant, with the selected significance level of 0.05. However, a larger share of identified trends are positive than negative. The maximum annual rainfall erosivity values were obtained for one specific mountain station. Furthermore, a sensitivity analysis regarding the rainfall erosivity factor R calculation showed that the rainfall threshold parameter (12.7 mm) that is used to remove the small-magnitude rainfall events in order to reduce the computational burden can attribute up to 10% of the average annual R-values in cases where this threshold is not used. Other parameters have, on average, a smaller impact on the calculated rainfall erosivity. Furthermore, the application of local kinetic energy equations resulted in, on average, about 20% higher annual rainfall erosivity values compared to the equation that is proposed by the Revised Universal Soil Loss Equation (RUSLE) manual and was not developed specifically for this region.

54 ENVIRONMENTAL SCIENCES↗

SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended under simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.

60 APPLIED LIFE SCIENCES↗

SU-E-T-448: Heightened Apical Positivity of 2-Year Post-Radiotherapy Biopsies Is Not Related to Suboptimal Dosimetry

Purpose: Previous research has demonstrated that following radiation therapy for prostate cancer, there is a relative increase in positive biopsies in the apex versus the rest of the prostate. The increase could be due to: 1) Inter-fraction apex motion or deformation, 2) Intra-fraction apex motion or deformation, 3) Suboptimal dose coverage in the apex, 4) Tissue composition in the apex and/or 5) Prostate size. In this initial study, the potential for suboptimal dose coverage in the apex was assessed by splitting the prostate planning target volume into the apex (inferior third) and remainder. Methods: 69 patients were selected from 303 patients treated on a clinical radiotherapy trial for prostate cancer. These patients were selected as they had both a localized (sextant template) 2-year post-treatment biopsy and 3D dose information. Of these patients, 10 had positive biopsies in the apex, 8 in the remainder and 11 in both locations. For all patients, the following dosimetric data was acquired from the apex dose volume histogram: Dmean, Dmax, Dmin, D95% and V100%. Unpaired, one-tailed t-tests were used to test for statistical significance (p < 0.05) between all dosimetric parameters for patients with positive versus negative apical biopsies. Additionally, D95% for the apex was plotted against D95% of the remainder. Results: There was no statistical difference for the selected apical dosimetric parameters for patients with positive versus negative biopsies (p-values > 0.05). No correlation was found between D95% (normalized to the prescription dose) for the apex and remainder (R{sup 2} = 0.0116). Conclusion: No correlation was found between positive apical biopsy and suboptimal dosimetric coverage. Current research is looking into inter-fraction apex motion and deformation as a potential source of the increased apical failure using daily CBCT images.

60 APPLIED LIFE SCIENCES↗

Comparative genomics of the Liberibacter genus reveals widespread diversity in genomic content and positive selection history

‘Candidatus Liberibacter’ is a group of bacterial species that are obligate intracellular plant pathogens and cause Huanglongbing disease of citrus trees and Zebra Chip in potatoes. Here, we examined the extent of intra- and interspecific genetic diversity across the genus using comparative genomics. Our approach examined a wide set of Liberibacter genome sequences including five pathogenic species and one species not known to cause disease. By performing comparative genomics analyses, we sought to understand the evolutionary history of this genus and to identify genes or genome regions that may affect pathogenicity. With a set of 52 genomes, we performed comparative genomics, measured genome rearrangement, and completed statistical tests of positive selection. We explored markers of genetic diversity across the genus, such as average nucleotide identity across the whole genome. These analyses revealed the highest intraspecific diversity amongst the ‘Ca. Liberibacter solanacearum’ species, which also has the largest plant host range. We identified sets of core and accessory genes across the genus and within each species and measured the ratio of nonsynonymous to synonymous mutations (dN/dS) across genes. We identified ten genes with evidence of a history of positive selection in the Liberibacter genus, including genes in the Tad complex, which have been previously implicated as being highly divergent in the ‘Ca. L. capsica’ species based on high values of dN.

59 BASIC BIOLOGICAL SCIENCES↗

Distortion of the luminosity function of high-redshift galaxies by gravitational lensing

The observed properties of high-redshift galaxies depend on the underlying foreground distribution of large-scale structure, which distorts their intrinsic properties via gravitational lensing. We focus on the regime where the dominant contribution originates from a single lens and examine the statistics of gravitational lensing by a population of virialized and non-virialized structures using sub-millimeter galaxies at z∼2.6 and Lyman-break galaxies (LBGs) at redshifts z∼6−15 as the background sources. We quantify the effect of lensing on the luminosity function of the high-redshift sources, focusing on the intermediate and small magnifications, μ≲2, which affect the majority of the background galaxies, and comparing to the case of strong lensing. We show that, depending on the intrinsic properties of the background galaxies, gravitational lensing can significantly affect the observed luminosity function even when no obvious strong lenses are present. Finally, we find that in the case of the LBGs it is important to account for the surface brightness profiles of both the foreground and the background galaxies when computing the lensing statistics, which introduces a selection criterion for the background galaxies that can actually be observed. Not taking this criterion into account leads to an overestimation of the number densities of very bright galaxies by nearly two orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗

Parsimonious Potential Energy Surface Expansions Using Dictionary Learning with Multipass Greedy Selection

Potential energy surfaces fit with basis set expansions have been shown to provide accurate representations of electronic energies and have enabled a variety of high-accuracy dynamics, kinetics, and spectroscopy applications. The number of terms in these expansions scales poorly with system size, a drawback that challenges their use for systems with more than similar to 10 atoms. A solution is presented here using dictionary learning. Subsets of the full set of conventional basis functions are optimized using a newly developed multipass greedy regression method inspired by forward and backward selection methods from the statistics, signal processing, and machine learning literatures. Here, the optimized representations have accuracies comparable to the full set but are 1 or more orders of magnitude smaller, and notably, the number of terms in the optimized multipass greedy expansions scales approximately linearly with the number of atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗