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Elucidating the Atomic Structures of the Gel Layer Formed during Aluminoborosilicate Glass Dissolution: An Integrated Experimental and Simulation Study

The altered glasses produced during aqueous dissolution of silicate and borosilicate glasses are among the most complex structures to understand at the atomic level due to their amorphous nature, random porosity and various levels of hydration. In this study, we gained insights of the complex atomic structures of altered aluminoborosilicate glasses by combining a range of experimental and computational approaches. The altered glasses were prepared by dissolution of three glasses with varying level of alumina in acid for 7 days. A comprehensive set of experimental [elemental analysis, high-energy X-ray diffraction, 29 Si and 27 Al solid-state nuclear magnetic resonance (NMR), and O 1s X-ray photoelectron spectroscopy (XPS)] and modeling (molecular dynamics (MD) simulations using non-reactive and reactive force fields) were used to study the atomic structures of these altered glasses. Elemental analysis showed that most of the B in the pristine glasses was leached into the solution and was not contained in the altered glass. The 29 Si and 27 Al solid-state NMR spectra revealed that the altered glasses have more polymerized silicate network as compared to those in the pristine glasses due to the reformation of linkages among Si and Al oxygen polyhedral in the altered glasses. The bridging and non-bridging (or hydroxyl O) atoms in the altered glasses were also quantified from their O 1s XPS spectra. Atomic structure models of the altered glasses were constructed by using MD simulations using the reactive force field based on the compositional information obtained from experiments. Various pore structures were generated using the charge-scaling (CS) method by using different initial densities and CS temperatures; the best CS parameters of each alternated glass were then determined by comparing with the experimental structure factors obtained from high energy X-ray diffraction. Pore and the atomic structures and vibrational properties around these pore surfaces were analyzed. Furthermore, these results from this comprehensive study thus provides a realistic insight into the pore morphology, atomic structure, and vibrational properties of altered glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Optical Constants for Liquids in the Near-Infrared: Improved Methods for Obtaining the n and k Constants from 1 to 4 Microns

Other than open bodies of water, bulk liquids are rarely encountered in the environment. Rather, liquids are typically found as aerosols, liquid droplets, or liquid layers on sundry substrates: glass, concrete, metals, etc. The layers can be of varying thicknesses, from micron-level to millimeter thick deposits. The infrared (IR) reflectance spectra of such deposits vary greatly, approximating the bulk reflectance for thicker deposits and for thinner layers on reflective surfaces, producing “transflectance” spectra that more closely replicate simple transmission of the IR light twice traversing the absorptive medium. Rather than recording large numbers of such spectra to serve as endmembers of a spectral reflectance library, we have recognized that the spectra can be modeled so long as the complex optical constants n(?) and k(?) are known as a function of frequency, ?. Here n is the real (dispersion) part and k is the imaginary (absorption) component of the complex index of refraction. However, in many cases the bands in the longwave IR (7 to 13 µm) can become saturated, and better signal-to-noise and specificity can be realized at shorter wavelengths. In earlier studies, we obtained the n/k values from 1.28 to 25 µm for a series of liquids, but are now expanding those measurements to include additional liquid species and extending the spectral range to lower wavelengths. In this paper we describe the methodologies for compiling and fusing the two data sets collected to provide better and more complete spectral coverage from 1 to 25 µm (10,000 to 400 cm-1). The broad spectral range means that one needs to account for both strong and weak spectral features, all of which can be useful for detection, depending on the scenario. To account for the large dynamic range, both long and short path length transmission cells are required for accurate measurements.

optical constants, refractive index, liquids, mid ↗

Planck 2015 results: XIX. Constraints on primordial magnetic fields

In this paper, we compute and investigate four types of imprint of a stochastic background of primordial magnetic fields (PMFs) on the cosmic microwave background (CMB) anisotropies: the impact of PMFs on the CMB temperature and polarization spectra, which is related to their contribution to cosmological perturbations; the effect on CMB polarization induced by Faraday rotation; the impact of PMFs on the ionization history; magnetically-induced non-Gaussianities and related non-zero bispectra; and the magnetically-induced breaking of statistical isotropy. We present constraints on the amplitude of PMFs that are derived from different Planck data products, depending on the specific effect that is being analysed. Overall, Planck data constrain the amplitude of PMFs to less than a few nanoGauss, with different bounds that depend on the considered model. In particular, individual limits coming from the analysis of the CMB angular power spectra, using the Planck likelihood, are B 1 Mpc < 4.4 nG (where B 1 Mpc is the comoving field amplitude at a scale of 1 Mpc) at 95% confidence level, assuming zero helicity. By considering the Planck likelihood, based only on parity-even angular power spectra, we obtain B 1 Mpc < 5.6 nG for a maximally helical field. For nearly scale-invariant PMFs we obtain B 1 Mpc < 2.0 nG and B 1 Mpc < 0.9 nG if the impact of PMFs on the ionization history of the Universe is included in the analysis. From the analysis of magnetically-induced non-Gaussianity, we obtain three different values, corresponding to three applied methods, all below 5 nG. The constraint from the magnetically-induced passive-tensor bispectrum is B 1 Mpc < 2.8 nG. Additionally, a search for preferred directions in the magnetically-induced passive bispectrum yields B 1 Mpc < 4.5 nG, whereas the compensated-scalar bispectrum gives B 1 Mpc < 3 nG. The analysis of the Faraday rotation of CMB polarization by PMFs uses the Planck power spectra in EE and BB at 70 GHz and gives B 1 Mpc < 1380 nG. In our final analysis, we consider the harmonic-space correlations produced by Alfvén waves, finding no significant evidence for the presence of these waves. Together, these results comprise a comprehensive set of constraints on possible PMFs with Planck data.

79 ASTRONOMY AND ASTROPHYSICS↗

Material Identification From Radiographs Without Energy Resolution

We propose a method for performing material identification from radiographs without energy-resolved measurements. Material identification has a wide variety of applications, including in biomedical imaging, nondestructive testing, and security. While existing techniques for radiographic material identification make use of dual energy sources, energy-resolving detectors, or additional (e.g., neutron) measurements, such setups are not always practical— requiring additional hardware and complicating imaging. We tackle material identification without energy resolution, allowing standard X-ray systems to provide material identification information without requiring additional hardware. Assuming a setting where the geometry of each object in the scene is known and the materials come from a known set of possible materials, we pose the problem as a combinatorial optimization with a loss function that accounts for the presence of scatter and an unknown gain and propose a branch and bound algorithm to efficiently solve it. We present experiments on both synthetic data and real, experimental data with relevance to security applications— thick, dense objects imaged with MeV X-rays. We show that material identification can be efficient and accurate, for example, in a scene with three shells (two copper, one aluminum), our algorithm ran in six minutes on a consumer-level laptop and identified the correct materials as being among the top 10 best matches out of 8,000 possibilities.

36 MATERIALS SCIENCE↗

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗

Lensing without borders – I. A blind comparison of the amplitude of galaxy–galaxy lensing between independent imaging surveys

ABSTRACT Lensing without borders is a cross-survey collaboration created to assess the consistency of galaxy–galaxy lensing signals (ΔΣ) across different data sets and to carry out end-to-end tests of systematic errors. We perform a blind comparison of the amplitude of ΔΣ using lens samples from BOSS and six independent lensing surveys. We find good agreement between empirically estimated and reported systematic errors which agree to better than 2.3σ in four lens bins and three radial ranges. For lenses with zL > 0.43 and considering statistical errors, we detect a 3–4σ correlation between lensing amplitude and survey depth. This correlation could arise from the increasing impact at higher redshift of unrecognized galaxy blends on shear calibration and imperfections in photometric redshift calibration. At zL > 0.54, amplitudes may additionally correlate with foreground stellar density. The amplitude of these trends is within survey-defined systematic error budgets that are designed to include known shear and redshift calibration uncertainty. Using a fully empirical and conservative method, we do not find evidence for large unknown systematics. Systematic errors greater than 15 per cent (25 per cent) ruled out in three lens bins at 68 per cent (95 per cent) confidence at z < 0.54. Differences with respect to predictions based on clustering are observed to be at the 20–30 per cent level. Our results therefore suggest that lensing systematics alone are unlikely to fully explain the ‘lensing is low’ effect at z < 0.54. This analysis demonstrates the power of cross-survey comparisons and provides a promising path for identifying and reducing systematics in future lensing analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

TU-FG-201-06: Remote Dosimetric Auditing for Clinical Trials Using EPID Dosimetry: A Pilot Study

Purpose: To perform a pilot study for remote dosimetric credentialing of intensity modulated radiation therapy (IMRT) based clinical trials. The study introduces a novel, time efficient and inexpensive dosimetry audit method for multi-center credentialing. The method employs electronic portal imaging device (EPID) to reconstruct delivered dose inside a virtual flat/cylindrical water phantom. Methods: Five centers, including different accelerator types and treatment planning systems (TPS), were asked to download two CT data sets of a Head and Neck (H&N) and Postprostatectomy (P-P) patients to produce benchmark plans. These were then transferred to virtual flat and cylindrical phantom data sets that were also provided. In-air EPID images of the plans were then acquired, and the data sent to the central site for analysis. At the central site, these were converted to DICOM format, all images were used to reconstruct 2D and 3D dose distributions inside respectively the flat and cylindrical phantoms using inhouse EPID to dose conversion software. 2D dose was calculated for individual fields and 3D dose for the combined fields. The results were compared to corresponding TPS doses. Three gamma criteria were used, 3%3mm-3%/2mm–2%/2mm with a 10% dose threshold, to compare the calculated and prescribed dose. Results: All centers had a high pass rate for the criteria of 3%/3 mm. For 2D dose, the average of centers mean pass rate was 99.6% (SD: 0.3%) and 99.8% (SD: 0.3%) for respectively H&N and PP patients. For 3D dose, 3D gamma was used to compare the model dose with TPS combined dose. The mean pass rate was 97.7% (SD: 2.8%) and 98.3% (SD: 1.6%). Conclusion: Successful performance of the method for the pilot centers establishes the method for dosimetric multi-center credentialing. The results are promising and show a high level of gamma agreement and, the procedure is efficient, consistent and inexpensive. Funding has been provided from Department of Radiation Oncology, TROG Cancer Research and the University of Newcastle. Narges Miri is a recipient of a University of Newcastle postgraduate scholarship.

60 APPLIED LIFE SCIENCES↗

Influence of Welding Strength Matching Coefficient and Cold Stretching on Welding Residual Stress in Austenitic Stainless Steel

Austenitic stainless steel is widely used in pressure vessels for the storage and transportation of liquid gases such as liquid nitrogen, liquid oxygen, and liquid hydrogen. Cryogenic pressure vessel manufacturing uses cold stretching technology, which relies heavily on welding joint performance, to construct lightweight and thin-walled vessels. Residual stress from welding is a primary factor in cases of austenitic stainless steel pressure vessel failure. In this paper, on the basis of Visual Environment 10.0 finite element simulation technology, the residual stress resulting from different welding strength matching coefficients (0.8, 1, 1.2, 1.4) for two S30408 plates welded with three-pass butt welds is calculated according to thermal elastoplastic theory. In addition, the stress field was calculated under a loading as high as 410 MPa and after the load was released. Path 1 was set to analyze stress along the welding line, and path 2 was set to analyze stress normal to the welding line. The welding strength matching coefficient strongly affected both the longitudinal residual stress (center of path 1) and the transverse residual stress (both ends of path 1) after the welding was completed. However, the coefficient had little effect on the longitudinal and transverse residual stress of path 2. Under the loading of 410 MPa, the longitudinal and transverse stress decreased and the stress distribution, with different welding strength matching coefficients, was less diverse. After the load was released, longitudinal and transverse stress distribution for both path 1 and path 2 decreased to a low level. Cold stretching could reduce the effect of residual stress to various degrees. Transverse strain along the stretching direction was also taken into consideration. The experimental results validated the reliability of the partial simulation.

36 MATERIALS SCIENCE↗

Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity

Life cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle-based systems level analysis at the earliest stages of technology development. While early assessments provide the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes.

42 ENGINEERING↗

SU-E-T-63: A Preliminary Study of Gold Nanoparticles Enhanced Cone Beam Computed Tomography

Purpose: Gold nanoparticles (GNPs) have potential of being used as a new-generation contrast agent to enhance CT imaging of cancer. This feasibility study is to determine the GNP concentration required to provide sufficient image contrast in small animal cone beam CT (CBCT) imaging. Methods: The GNPs used are nanorods with 10nm diameter and 44nm length. A 50µl GNP colloid with an original GNP concentration of 3.6mg/ml was diluted to five different concentrations at 2.4, 2.1, 2.0, 1.9 and 1.8mg/ml, respectively. The GNP colloid was enclosed in a 150µl vial, and the GNP colloid vial was submerged in a water bottle for CBCT. CBCTs were acquired with x-ray energy of 65kVp and tube current of 1.5mA. In addition, to evaluate the optimal x-ray energy for GNP detection in CBCT, the GNP colloid of 1.8mg/ml was also imaged at x-ray energy of 45kVp and 85kVp. Regions of interest were placed in axial CBCT slices contouring the GNP colloid volume and a same volume in the surrounding water to calculate the signal and contrast. Results: For the GNP colloid at concentrations of 3.6, 2.4, 2.1, 2.0, 1.9 and 1.8mg/ml, the image contrasts between GNP colloid and water were 68±4, 33±4, 23±3, 20±3, 13±4, and 10±3 HU, respectively. At 1.8mg/ml concentration level, the image contrasts were 16±3 and 7±4 HU, respectively, when the x-ray energy was set at 45kVp and 85kVp. Conclusion: The minimal GNP concentration required on our small animal CBCT was estimated to be around 1.8mg/ml due to the fact that the minimum image contrast for adequate differentiation in CT is about 8 HU. CBCT at lower x-ray energy, i.e. 45kVp, can provide better image contrast than at higher energies, i.e., 65kVp and 85kVp. A study of GNP enhanced CBCT for in vivo small animal imaging is ongoing efforts in our group.

60 APPLIED LIFE SCIENCES↗

The Cosmological Bootstrap: Spinning correlators from symmetries and factorization

We extend the cosmological bootstrap to correlators involving massless spinning particles, focusing on spin-1 and spin-2. In de Sitter space, these correlators are constrained both by symmetries and by locality. In particular, the de Sitter isometries become conformal symmetries on the future boundary of the spacetime, which are reflected in a set of Ward identities that the boundary correlators must satisfy. We solve these Ward identities by acting with weight-shifting operators on scalar seed solutions. Using this weight-shifting approach, we derive three- and four-point correlators of massless spin-1 and spin-2 fields with conformally coupled scalars. Four-point functions arising from tree-level exchange are singular in particular kinematic configurations, and the coefficients of these singularities satisfy certain factorization properties. We show that in many cases these factorization limits fix the structure of the correlators uniquely, without having to solve the conformal Ward identities. The additional constraint of locality for massless spinning particles manifests itself as current conservation on the boundary. We find that the four-point functions only satisfy current conservation if the s, t, and u-channels are related to each other, leading to nontrivial constraints on the couplings between the conserved currents and other operators in the theory. For spin-1 currents this implies charge conservation, while for spin-2 currents we recover the equivalence principle from a purely boundary perspective. For multiple spin-1 fields, we recover the structure of Yang--Mills theory. Finally, we apply our methods to slow-roll inflation and derive a few phenomenologically relevant scalar-tensor three-point functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extended calculations with spectroscopic accuracy: Energy levels and transition properties for the fluorine-like isoelectronic sequence with Z = 24–30

We have performed extensive multiconfiguration Dirac–Hartree–Fock calculations and second-order many-body perturbation calculations for F-like ions with Z = 24–30. Energy levels and transition rates for electric dipole (E1), electric-quadrupole (E2), electric-octupole (E3), magnetic dipole (M1), and magnetic-quadrupole (M2) transitions, as well as radiative lifetimes, are provided for the lowest 200 levels belonging to the 1s{sup 2}2s{sup 2}2p{sup 5}, 1s{sup 2}2s2p{sup 6}, 1s{sup 2}2s{sup 2}2p{sup 4}3l, 1s{sup 2}2s2p{sup 5}3l, 1s{sup 2}2p{sup 6}3l, and 1s{sup 2}2s{sup 2}2p{sup 4}4l configurations of each ion. The results from the two sets of calculations are in excellent agreement. Extensive comparisons are also made with other theoretical results and observed data from the CHIANTI and NIST databases. The present energies and wavelengths are believed to be accurate enough to aid line identifications involving the n = 3 and n = 4 configurations, for which observations are largely missing. The calculated wavelengths and transition data will be useful in the modeling and diagnostics of astrophysical and fusion plasmas.

74 ATOMIC AND MOLECULAR PHYSICS↗

Advanced Methods for Modeling Water-Levels and Estimating Drawdowns with SeriesSEE, an Excel Add-In

Water-level modeling is used for multiple-well aquifer tests to reliably differentiate pumping responses from natural water-level changes in wells, or environmental fluctuations. Synthetic water levels are created during water-level modeling and represent the summation of multiple component fluctuations, including those caused by environmental forcing and pumping. Pumping signals are modeled by transforming step-wise pumping records into water-level changes by using superimposed Theis functions. Water-levels can be modeled robustly with this Theis-transform approach because environmental fluctuations and pumping signals are simulated simultaneously. Water-level modeling with Theis transforms has been implemented in the program SeriesSEE, which is a Microsoft® Excel add-in. Moving average, Theis, pneumatic-lag, and gamma functions transform time series of measured values into water-level model components in SeriesSEE. Earth tides and step transforms are additional computed water-level model components. Water-level models are calibrated by minimizing a sum-of-squares objective function where singular value decomposition and Tikhonov regularization stabilize results. Drawdown estimates from a water-level model are the summation of all Theis transforms minus residual differences between synthetic and measured water levels. The accuracy of drawdown estimates is limited primarily by noise in the data sets, not the Theis-transform approach. Drawdowns much smaller than environmental fluctuations have been detected across major fault structures, at distances of more than 1 mile from the pumping well, and with limited pre-pumping and recovery data at sites across the United States. In addition to water-level modeling, utilities exist in SeriesSEE for viewing, cleaning, manipulating, and analyzing time-series data.

58 GEOSCIENCES↗

Close to Home: Employment Outcomes for Recent Radiation Oncology Graduates

Purpose: To characterize the practice type and location of radiation oncology (RO) residents graduating in 2013. Methods and Materials: Graduates completing RO residency in 2013 were identified, and for each, postgraduate practice setting (academic vs private practice) and location were identified. Characteristics of the graduates, including details regarding their institutions of medical school and residency education, were collected and analyzed. Results: Data were obtained from 146 of the 154 RO graduates from the class of 2013. Employment data were available for 142 graduates. Approximately one-third of graduates were employed in the same state as residency (36.6%), approximately two-thirds (62.0%) in the same region as residency, and nearly three-fourths (73.9%) in the same region as medical school or residency completion. Of the 66 graduates (46.5%) working in academics, 40.9% were at the same institution where they completed residency. Most trainees (82.4%) attended medical schools with RO residency programs. Conclusions: Although personal factors may attract students to train in a particular area, the location of medical school and residency experiences may influence RO graduate practice location choice. Trends in the geographic distribution of graduating radiation oncologists can help identify and better understand disparities in access to RO care. Steps to improve access to RO care may include interventions at the medical student or resident level, such as targeting students at medical schools without associated residency programs and greater resident exposure to underserved areas.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-F-T-201: Acceleration of Dose Optimization Process Using Dual-Loop Optimization Technique for Spot Scanning Proton Therapy

Purpose: The purpose was to demonstrate a developed acceleration technique of dose optimization and to investigate its applicability to the optimization process in a treatment planning system (TPS) for proton therapy. Methods: In the developed technique, the dose matrix is divided into two parts, main and halo, based on beam sizes. The boundary of the two parts is varied depending on the beam energy and water equivalent depth by utilizing the beam size as a singular threshold parameter. The optimization is executed with two levels of iterations. In the inner loop, doses from the main part are updated, whereas doses from the halo part remain constant. In the outer loop, the doses from the halo part are recalculated. We implemented this technique to the optimization process in the TPS and investigated the dependence on the target volume of the speedup effect and applicability to the worst-case optimization (WCO) in benchmarks. Results: We created irradiation plans for various cubic targets and measured the optimization time varying the target volume. The speedup effect was improved as the target volume increased, and the calculation speed increased by a factor of six for a 1000 cm3 target. An IMPT plan for the RTOG benchmark phantom was created in consideration of ±3.5% range uncertainties using the WCO. Beams were irradiated at 0, 45, and 315 degrees. The target’s prescribed dose and OAR’s Dmax were set to 3 Gy and 1.5 Gy, respectively. Using the developed technique, the calculation speed increased by a factor of 1.5. Meanwhile, no significant difference in the calculated DVHs was found before and after incorporating the technique into the WCO. Conclusion: The developed technique could be adapted to the TPS’s optimization. The technique was effective particularly for large target cases.

60 APPLIED LIFE SCIENCES↗

Beyond CCSD(T) Accuracy at Lower Scaling with Auxiliary Field Quantum Monte Carlo

We introduce a black-box auxiliary field quantum Monte Carlo (AFQMC) approach to perform highly accurate electronic structure calculations using configuration interaction singles and doubles (CISD) trial states. This method consistently provides more accurate energy estimates than coupled cluster singles and doubles with perturbative triples (CCSD(T)), often regarded as the gold standard in quantum chemistry. This level of precision is achieved at a lower asymptotic computational cost, scaling as O(N 6 ) compared to the O(N 7 ) scaling of CCSD(T). Furthermore, we provide numerical evidence supporting these findings through results for challenging main group and transition metal-containing molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The halo light-cone catalogues of ABACUSSUMMIT

We describe a method for generating halo catalogues on the light-cone using the AbacusSummit suite of N-body simulations. The main application of these catalogues is the construction of realistic mock galaxy catalogues and weak lensing maps on the sky. Our algorithm associates the haloes from a set of coarsely spaced snapshots with their positions at the time of light-cone crossing by matching halo particles to on-the-fly light-cone particles. It then records the halo and particle information into an easily accessible product, which we call the AbacusSummit halo light-cone catalogues. Our recommended use of this product is in the halo mass regime of M halo > 2.1 x 10 11 M ⊙ h -1 for the base resolution simulations, i.e. haloes containing at least 100 particles, where the interpolated halo properties are most reliable. To test the validity of the obtained catalogues, we perform various visual inspections and consistency checks. In particular, we construct galaxy mock catalogues of emission-line galaxies (ELGs) at z ~ 1 by adopting a modified version of the AbacusHOD script, which builds on the standard halo occupation distribution (HOD) method by including various extensions. We find that the multipoles of the autocorrelation function are consistent with the predictions from the full-box snapshot, implicitly validating our algorithm. In addition, we compute and output CMB convergence maps and find that the auto- and cross-power spectrum agrees with the theoretical prediction at the sub-per-cent level.

79 ASTRONOMY AND ASTROPHYSICS↗

Kinetic Deep Learning v0.1

Here, we present a method that uses protein levels to predict times series of metabolite concentrations. Understanding this type of pathway dynamics is important in order to predict the behavior of the pathway and, more pragmatically, to be able to design biological systems (such as strains bioengineered to produce chemical products) reliably. Typically, for this purpose, kinetic models consisting of differential equations based on the Michaelis-Menten dynamics have been used in the past. However, these methods can rarely produce good fits to measured data time series. Possibly, this happens because the kinetic constants are unknown or are different from the ones measured in vivo, or perhaps because Michaelis-Menten dynamics is not a satisfactory description. In order to improve the predictive nature of these kinetic models we have eliminated the Michaelis-Menten description of pathway dynamics and we have substituted it by algorithms that automatically learn these dynamics from previously obtained metabolomics and proteomics data using machine learning approaches. Specifically, kinetic deep learning uses deep learning to map proteomics time series to metabolite concentration time series, instead of learning the first metabolite derivative and integrating in (as in the first version of kinetic learning). This approach is shown to provide good to excellent results with a data set specifically collected for this purpose.

Garcia Martin, Hector [Joint BioEnergy Institute (↗