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DOE OSTI2026

CoLoRe-2LPT: Lyman-$α$ mock catalogues for the validation of DESI cosmological analyses

The Lyman-$α$ (Ly$α$) forest has become a crucial probe for studying the large-scale structure of the universe at high redshift ($z > 2$), providing powerful constraints on Baryon Acoustic Oscillations (BAO) and the full-shape (FS) clustering of matter. As a key ingredient for upcoming BAO and FS analyses, we present a new generation of fast cosmological Ly$α$ mocks based on second-order Lagrangian perturbation theory (2LPT). These new mocks significantly improve upon previous log-normal approaches, both at accurately capturing small scale clustering and at recovering the non-linear broadening of the BAO peak. They are able to reproduce Ly$α$ statistics within $10\%$ of the latest DESI measurement; including the Ly$α$ bias and the redshift-space distortion $β$ parameter, mean transmitted flux, and 1D power spectrum. The corresponding quasar (QSO) clustering is also improved with respect to previous approaches, calibrated against high-resolution Abacus simulations, recovering the observational QSO linear bias to less than $5\%$ and improving redshift-space distortions via 2LPT velocities and the addition of Fingers-of-God effects. Furthermore, these mocks incorporate high column density systems and metal lines, allowing us to explore the effects and systematics induced by these astrophysical contaminants. This new set of mocks has been key for enhancing the modeling and validation of the DESI DR2 Ly$α$ full shape cosmological analysis. This work provides a physically motivated and computationally efficient tool for simulating current and next-generation Ly$α$ surveys and validating FS and BAO analysis.

Bernal, M.F. Ruiz-Herrera [Madrid, CIEMAT] (ORCID:↗

DOE OSTI2011

IMPACT OF GRAIN EVOLUTION ON THE CHEMICAL STRUCTURE OF PROTOPLANETARY DISKS

We study the impact of dust evolution in a protoplanetary disk (PPD) around a T Tauri star on the disk's chemical composition. For the first time, we utilize a comprehensive model of dust evolution, which includes growth, fragmentation, and sedimentation. Specific attention is paid to the influence of grain evolution on the penetration of the UV field in the disk. A chemical model that includes a comprehensive set of gas-phase and grain-surface chemical reactions is used to simulate the chemical structure of the disk. The main effect of grain evolution on the disk's chemical composition comes from sedimentation and, to a lesser degree, from reduction of the total grain-surface area. The net effect of grain growth is suppressed by the fragmentation process which maintains a population of small grains, dominating the total grain surface area. We consider three models of dust properties. In model GS, both growth and sedimentation are taken into account. In models A5 and A4, all grains are assumed to be the same size (10{sup -5} cm and 10{sup -4} cm, respectively) with a constant gas-to-dust mass ratio of 100. As in previous studies, the 'three-layer' pattern (cold midplane, warm molecular layer, and hot atmosphere) in the disk-chemical structure is preserved in all models, but shifted closer to the midplane in models with increased grain size (GS and A4). Unlike other similar studies, we find that in models GS and A4, the column densities of most gas-phase species are enhanced by 1-3 orders of magnitude relative to those in a model with pristine dust (A5), while column densities of their surface counterparts are decreased. We show that column densities of certain species, such as C{sub 2}H, HC{sub 2n+1}N (n = 0-3), H{sub 2}O, and some other molecules, as well as the C{sub 2}H{sub 2}/HCN abundance ratio, all of which are accessible with Herschel and ALMA, can be used as observational tracers of early stages of the grain evolution process in PPDs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Process-oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction

Weather forecasting nowadays often requires some estimation of uncertainties associated with the output of meteorological models, in order to better inform decision making, especially in the context of intense weather events. Ensemble prediction systems provide such information through sets of possible scenarios which are designed to represent various uncertainty sources, including model uncertainties. A wide variety of methods have been proposed to estimate model uncertainties, among which perturbation methods targeting uncertain processes are a promising research field. Here, we focus on the representation of small-scale variability by process-oriented perturbation schemes applied to two key physical processes, namely turbulence and shallow convection. The perturbations are applied to a single-column version of the convection-permitting AROME model, in three idealized boundary-layer cases. Large-eddy simulations (LESs) of the same cases serve as a reference for the subgrid variability that has to be represented, and the results are also compared to those given by the Stochastically Perturbed Parametrization Tendencies (SPPT) method, which is a method commonly used by weather forecast centres to represent model uncertainty. The spread produced by our process-oriented perturbations of turbulence and shallow convection does not represent all the small-scale variability implied by the LESs for temperature and humidity. However, it is of a similar order of magnitude for the wind, thanks to perturbations generated by the stochastic turbulence scheme. The dispersion is structurally different from what is obtained with SPPT. It is non-negligible in the lower levels, where SPPT perturbations are usually suppressed because of numerical instabilities, indicating a possible complementarity between the schemes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A new concept for searching for time-reversal symmetry violation using Pa-229 ions trapped in optical crystals

Certain pear-shaped nuclei are expected to have enhanced sensitivity to time-reversal and parity-violating interactions originating within the nuclear medium. In particular, Protactinium-229 is thought to be about 100,000 times more sensitive than Mercury-199 which currently sets some of the most stringent limits for these types of interactions. Several challenges would first have to be addressed in order to take advantage of this discovery potential. First, there is not currently a significant source of Pa-229 (1.5 day half-life); however, there are plans to harvest Pa-229 at the Facility for Rare Isotope Beams at Michigan State University. Second, the spin-5/2 nucleus of Pa-229 limits its coherence time while also making it sensitive to systematic effects related to local electric field gradients. On the other hand, this also give Pa-229 an additional source of signal in the form of a magnetic quadrupole moment (MQM) which violates the same symmetries as an EDM but is not observable in spin-1/2 systems. Third, in order to compensate for the small atom numbers and short coherence times, the Pa-229 atoms would have to be probed with exceptionally large electric and magnetic fields that may be possible if Pa-229 ions are embedded inside an optical crystal. We will describe some aspects of this concept using the stable Praseodymium-141 isotope as a surrogate which has the same nuclear spin and similar atomic structure of Pa-229.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Super-swelled lyotropic single crystals

Lipids self-assemble into diverse supramolecular structures that exhibit thermotropic and/or lyotropic behavior. Lyotropic mesophases, where membranes conform to periodic minimal surfaces dividing two nonpenetrating aqueous subspaces, are arguably one of the most intriguing phases of lipid materials. Traditional 3D bicontinuous cubic lipid materials appear as a polycrystal of varying degrees of order. When exposed to water, the properties of the molecular building blocks of the membrane determine specific swelling limits setting the lattice dimensions at about 15 nm. This limited swelling severely impairs their application as delivery vehicles of large drugs or as matrices for guiding protein crystallization. We report the discovery of self-assembly strategies leading to the emergence of lipid bicontinuous single crystals with unprecedented swelling capacity. Here, the conventional strategy to increase unit cell size is tweaking membrane composition to include charged building blocks, a process to achieve electrostatic-driven swelling. In this paper, we demonstrate that controlling self-assembly external conditions when coupled to membrane composition yields 3D bicontinuous cubic phases that swell up to lattice dimensions of 68 nm. Importantly, and contrary to what is perceived for soft lyotropic materials in general, the self-assembly methodology enables the development of large super-swelled monocrystals. Utilizing small-angle X-ray scattering and cryoelectron microscopy, we underpin three crucial factors dictating the stabilization of super-swelled lipid bicontinuous cubic single crystals: (i) organic solvent drying speed, (ii) membrane charge density, and (iii) polyethylene glycol-conjugated lipids amount.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗

DOE OSTI2017

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Exploring the feasibility of crack detection in plate weldments through an interposed layer of viscoelastic material.

Development of new approaches in the nondestructive evaluation of welded steel plates for large naval structures continues to be an area of interest for the DoD and the military complex. In this report we will evaluate an elastic-microwave based detection and imaging method using both numerical finite element (3D FEM) and experimental methods. The evaluation was performed on two test articles that were designed to represent critical structural components with flaws of interest. Details of the materials and the mechanical drawings were provided with the test articles. Flaws, cracks and weld defects have been included in the test articles to determine detection sensitivity and accuracy of the proposed method. Our approach uses a microwave interferometer (MI) to record the scattered response of flaws in the steel plated as it is driven by an incident elastic field. The MI can “see” (penetrate) through the viscoelastic coating to the upper surface of the plate. Out-of-plane displacement amplitudes of 10nm in the frequency range (1kHz to 25kHz) are readily observable, with the key feature being, that the surface bond between the coating and the steel plate are undisturbed. The non-contact aspect of the interferometer allows for large surface regions to be accurately and efficiently scanned in space and time. Spatiotemporal data sets of this kind and specialized wavefield processing provide powerful detection and imaging modalities. From these wavefield data sets, a plate thickness mapping capability has been demonstrated that can detect thickness changes on the order of 0.79 mm (1/32”) with spatial resolution on the order of the spatial sampling rate, 15mm (~5/8”). We have also shown that a topological energy analysis of the wavefield data can detect and locate small flaws, on the order of 5-10 mm (0.025-0.40”) in the welded joint of a 1.5” thick T-plate. As before, these results are obtained through a 2” thick viscoelastic coating without altering the integrity of coating or the coating bond. These results show that we are detecting and locating damage (flaws) in the plate that are much smaller than the wavelength of the propagating guided modes. Classical scattering theory places a (λ/2) resolution limit on the detectability of flaws in terms of the incident field [22], however, since the spatial resolution of the scanned region is much smaller, (Δx=Δy=15mm) and the inherent natural focusing of the time reversal operation, we are able to detect smaller flaws on the order of (λ/10). It is important to realize that we are not imaging the flaw but detecting and localizing a difference between a reference (pristine) sample and the measured (damaged) sample, relative to a spatial grid on the surface. The current scan resolution is 15mm x 15mm. At present we cannot expect to resolve individual flaws within a grid space only their cumulative effect. Even with the current limitations, this imaging approach appears to be a promising alternative to current methods where the coating layer is removed.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Visualizing Size-Dependent Dynamics of CeO 2-δ {100}-Supported CoO x Nanoparticles Under CO 2 Hydrogenation Conditions

Carbon dioxide is a major greenhouse gas. In order to optimize processes focused on its chemical valorization, one needs detailed information about the effects of CO 2 and/or CO 2 /H 2 mixtures on the structure and morphology of metal/oxide catalysts. Here, in this study, the evolution of a catalyst with cobalt supported on CeO 2 -cube nanostructures under CO 2 hydrogenation conditions was investigated by using a set of in situ characterization techniques (X-ray absorption fine structure, X-ray diffraction, diffuse reflectance infrared Fourier transform spectroscopy, and environmental transmission electron microscopy (TEM)). The {100} facets of the ceria support displayed an unexpectedly high stability due to strong interactions with the aggregates of cobalt oxide. A significant influence of interfacial bonding between CoO x and CeO 2-δ {100} is evident through a clear preference in the orientation of CoO x nanoparticles (NPs) with respect to the substrate. For initially reduced Co/CeO 2 -cube nanostructures, a kinetically controlled oxidation of cobalt upon the introduction of CO 2 was observed during the early stages of CO 2 hydrogenation. Environmental TEM revealed the size-dependent morphological behavior of cobalt oxide NPs due to strong interactions with the CeO 2 {100} surface. When the environment was switched from H 2 to a mixture of H 2 and CO 2 at 250 °C, small CoO x NPs (in the largest dimension < 2.5 nm) rapidly transformed from a pyramidal three-dimensional (3D) form to a planar, monatomic layer attached to the concurrently oxidized CeO 2-δ {100} surface. This maximizes the number of sites available for the binding of CO 2 or reaction intermediates. The shape transformation reflected the oxophilic character of cobalt and strong metal–support interactions. The removal of CO 2 from the gas phase led to a reduction of the cobalt oxide NPs by hydrogen and a reversible two-dimensional → 3D transformation. In contrast, no significant morphological changes, apart from further oxidation, were observed for big CoO x NPs (in the largest dimension > 3 nm). These trends are not seen for nanoparticles of noble metals. The observed morphological and structural changes in the small CoO x NPs affected the stability of reaction intermediates and modified the selectivity of the CoO x /CeO 2 catalyst system for methane production.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Intermediate-Scale Experimental Study to Improve Fundamental Understanding of Attenuation Capacity for Leaking CO 2 in Heterogeneous Shallow Aquifers

In order to assess the risks of Geologic Carbon Sequestration (GCS), it is crucial to understand the fundamental physicochemical processes that may occur if and when stored CO 2 leaks upward from a deep storage reservoir into the shallow subsurface. Intermediate-scale experiments allow for improved understanding of the multiphase evolution processes that control CO 2 migration behaviour in the subsurface, because the boundary conditions, initial conditions, and porous media parameters can be better controlled and monitored in the laboratory than in field settings. For this study, a large experimental test bed was designed to mimic a cross-section of a shallow aquifer with layered geologic heterogeneity. As water with aqueous CO 2 was injected into the system to mimic a CO 2 -charged water leakage scenario, the spatiotemporal evolution of the multiphase CO 2 plume was monitored. Similar experiments were performed with two different sand combinations to assess the relative effects of different types of geologic facies transitions on the CO 2 evolution processes. Significant CO 2 attenuation was observed in both scenarios, but by fundamentally different mechanisms. When the porous media layers had very different permeabilities, attenuation was caused by local accumulation (structural trapping) and slow re-dissolution of gas phase CO 2 . When the permeability difference between the layers was relatively small, on the other hand, gas phase continually evolved over widespread areas near the leading edge of the aqueous plume, which also attenuated CO 2 migration. In conclusion, this improved process understanding will aid in the development of models that could be used for effective risk assessment and monitoring programs for GCS projects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Joint high temperature observation of a small C6.5 solar flare with IRIS/EIS/AIA

We present the observation of a C6.5 class flare on 2014 February 3, obtained with the Interface Region Imaging Spectrograph (IRIS) and the EUV Imaging Spectrometer (EIS) on board HINODE. We follow the details of the impulsive phase with IRIS and the gradual decay phase with both IRIS and EIS. The IRIS Slit-Jaw Imager and Atmospheric Imaging Assembly (AIA) are used to precisely co-align the two sets of spectroscopic observations. Of particular interest is the Fe xxi 1354.08 Å spectral line, which is the highest temperature emission (∼10 MK) observed in the IRIS wavelength range. We show the evolution of the Fe xxi profiles during the impulsive phase of the flare at the same ribbon location with a 75 s temporal cadence. Totally blueshifted (∼82 km s{sup −1}) profiles are found at the very early phase of the flare and gradually decrease in about 6 minutes. This result is consistent with 1D model predictions during chromospheric evaporation in flares. The blueshifted components also exhibit large non-thermal broadening, which decreases simultaneously with the blueshifted velocity. After the evaporation first occurs, the Fe xxi intensity progressively moves from the footpoints to the top of the hot flare loops seen in the AIA 131 Å images, where the emission is observed to be at rest and thermal. Emission measure estimates from IRIS/EIS/AIA observations during the gradual phase show isothermal loop top structures cooling from about 13.5 to 12 MK with electron densities of the order of ∼5−6×10{sup 10} cm{sup −3}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Modelling nearest neighbour distributions of biased tracers using hybrid effective field theory

ABSTRACT We investigate the application of hybrid effective field theory (HEFT) – which combines a Lagrangian bias expansion with subsequent particle dynamics from N-body simulations – to the modelling of k-nearest neighbour cumulative distribution functions (kNN-CDFs) of biased tracers of the cosmological matter field. The kNN-CDFs are sensitive to all higher order connected N-point functions in the data, but are computationally cheap to compute. We develop the formalism to predict the kNN-CDFs of discrete tracers of a continuous field from the statistics of the continuous field itself. Using this formalism, we demonstrate how kNN-CDF statistics of a set of biased tracers, such as haloes or galaxies, of the cosmological matter field can be modelled given a set of low-redshift HEFT component fields and bias parameter values. These are the same ingredients needed to predict the two-point clustering. For a specific sample of haloes, we show that both the two-point clustering and the kNN-CDFs can be well-fit on quasi-linear scales (≳ 20h−1Mpc) by the second-order HEFT formalism with the same values of the bias parameters, implying that joint modelling of the two is possible. Finally, using a Fisher matrix analysis, we show that including kNN-CDF measurements over the range of allowed scales in the HEFT framework can improve the constraints on σ8 by roughly a factor of 3, compared to the case where only two-point measurements are considered. Combining the statistical power of kNN measurements with the modelling power of HEFT, therefore, represents an exciting prospect for extracting greater information from small-scale cosmological clustering.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Lastly, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Diagrammatic theories of anharmonic molecular vibrations

In this review, we summarise recent developments in our laboratory in the field of many-body quantum-mechanical calculations of the anharmonic vibrational structure of molecules. Our size-extensive vibrational self-consistent field (XVSCF) and size-extensive second-order many-body perturbation (XVMP2) methods are, unlike their parent methods (VSCF and VMP2), defined in diagram- matic formulations of the energies and Dyson self-energies, leading to manifestly size-consistent expressions for zero-point energies and anharmonic vibrational frequencies calculable with much greater efficiency. The effective one-mode potentials of XVSCF are quadratic and hence the Schrödinger equation for each mode can be solved analytically, unlike VSCF, where a basis-set expansion of wave functions on more complex one-mode potentials need to be performed; VSCF potentials and their minima (anharmonic geometry) are shown to reduce to the quadratic potentials and their minima (also given analytically) of XVSCF in the thermodynamic limit. By self-consistently solving the Dyson equation with frequency-dependent self-energies, XVMP2 has the ability to calculate anharmonic frequencies of fundamentals as well as combinations and overtones in the presence of strong anharmonic resonance without a multireference or quasi-degenerate formulation, which tends to be non-size-consistent. To eliminate the computational bottleneck of XVSCF and XVMP2, which is the high-rank force-constant evaluation, we have developed alternative algorithms in which the diagrammatic equations are recast as a small number of high-dimensional integrals and then evaluated stochastically using a Metropolis Monte Carlo (MC) method. These MC-XVSCF and MC-XVMP2 methods not only remove the need for force-constant evaluation or storage, but also take into account force constants of up to infinite order according to their importance. Furthermore, they are a new branch of quantum Monte Carlo which can calculate frequencies (excitation energies) directly without fixed-node errors.

Dyson equation↗

DOE OSTI2025

Production of alternate realizations of DESI fiber assignment for unbiased clustering measurement in data and simulations

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi & Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

SU-E-T-03: 3 Year Clinical Experience with the IBA Proton Eyeline

Purpose: Over the past 3 years, more than 50 patients with ocular disease have been treated with a prototype commercial eyeline developed by Ion Beam Applications (IBA). It is particularly crucial for the dosimetry of the machine to be accurate, precise, and reproducible because of the small treatment volumes and several surrounding critical structures. A quality assurance (QA) program has been developed in order to regularly check and record the machine’s dosimetry over time. In this study we have summarized and evaluated three years of patient and system QA data for the eyeline prototype. Methods: In order to accurately deliver the prescribed dose to the patient’s treatment site, an output model was created based on several machine parameters. This output model, along with the requested system parameters, are regularly checked and recorded by a QA program. 10 standard proton fields have been created which have regular QA performed monthly with a water tank and parallel-plate chamber, and recorded in a database. QA has additionally been performed for each patient-specific treatment field. This is to verify and evaluate the patient output model as well as the system parameters for range&modulation combinations different than the standard QA fields. Results: 140 beam measurements have been analyzed for range, modulation, and output. The range is typically within tolerance, although there are about 6 cases where the system did not perform as expected. The modulation appears to be very stable, always being within tolerance. Output for the standard QA fields are typically within 2.5% from the baseline value. The patient output measurements agree within 2.5% from the model. Conclusion: Overall the eyeline performs well within the tolerances set, and the patient output measurements agree within 2% of the model.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Influence of pseudopotentials on excitation energies from selected configuration interaction and diffusion Monte Carlo

Due to their diverse nature, the faithful description of excited states within electronic structure theory methods remains one of the grand challenges of modern theoretical chemistry. Quantum Monte Carlo (QMC) methods have been applied very successfully to ground state properties but still remain generally less effective than other non-stochastic methods for electronically excited states. Nonetheless, we have recently reported accurate excitation energies for small organic molecules at the fixed-node diffusion Monte Carlo (FN-DMC) within a Jastrow-free QMC protocol relying on a deterministic and systematic construction of nodal surfaces using the selected configuration interaction (sCI) algorithm known as CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively). Albeit highly accurate, these all-electron calculations are computationally expensive due to the presence of core electrons. One very popular approach to remove these chemically-inert electrons from the QMC simulation is to introduce pseudopotentials (also known as effective core potentials). Taking the water molecule as an example, we investigate the influence of Burkatzki-Filippi-Dolg (BFD) pseudopotentials and their associated basis sets on vertical excitation energies obtained with sCI and FN-DMC methods. Although these pseudopotentials are known to be relatively safe for ground state properties, we evidence that special care may be required if one strives for highly accurate vertical transition energies. Indeed, comparing all-electron and valence-only calculations, we show that using pseudopotentials with the associated basis sets can induce differences of the order of 0.05 eV on the excitation energies. Fortunately, a reasonable estimate of this shift can be estimated at the sCI level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗