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At least 343 records · Page 19

Nuclear-electronic orbital reduced explicitly correlated Hartree-Fock approach: Restricted basis sets and open-shell systems

The nuclear electronic orbital (NEO) reduced explicitly correlated Hartree-Fock (RXCHF) approach couples select electronic orbitals to the nuclear orbital via Gaussian-type geminal functions. This approach is extended to enable the use of a restricted basis set for the explicitly correlated electronic orbitals and an open-shell treatment for the other electronic orbitals. The working equations are derived and the implementation is discussed for both extensions. The RXCHF method with a restricted basis set is applied to HCN and FHF{sup −} and is shown to agree quantitatively with results from RXCHF calculations with a full basis set. The number of many-particle integrals that must be calculated for these two molecules is reduced by over an order of magnitude with essentially no loss in accuracy, and the reduction factor will increase substantially for larger systems. Typically, the computational cost of RXCHF calculations with restricted basis sets will scale in terms of the number of basis functions centered on the quantum nucleus and the covalently bonded neighbor(s). In addition, the RXCHF method with an odd number of electrons that are not explicitly correlated to the nuclear orbital is implemented using a restricted open-shell formalism for these electrons. This method is applied to HCN{sup +}, and the nuclear densities are in qualitative agreement with grid-based calculations. Future work will focus on the significance of nonadiabatic effects in molecular systems and the further enhancement of the NEO-RXCHF approach to accurately describe such effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying finite-time coherent sets from limited quantities of Lagrangian data

A data-driven procedure for identifying the dominant transport barriers in a time-varying flow from limited quantities of Lagrangian data is presented. Our approach partitions state space into coherent pairs, which are sets of initial conditions chosen to minimize the number of trajectories that “leak” from one set to the other under the influence of a stochastic flow field during a pre-specified interval in time. In practice, this partition is computed by solving an optimization problem to obtain a pair of functions whose signs determine set membership. From prior experience with synthetic, “data rich” test problems, and conceptually related methods based on approximations of the Perron-Frobenius operator, we observe that the functions of interest typically appear to be smooth. We exploit this property by using the basis sets associated with spectral or “mesh-free” methods, and as a result, our approach has the potential to more accurately approximate these functions given a fixed amount of data. In practice, this could enable better approximations of the coherent pairs in problems with relatively limited quantities of Lagrangian data, which is usually the case with experimental geophysical data. We apply this method to three examples of increasing complexity: The first is the double gyre, the second is the Bickley Jet, and the third is data from numerically simulated drifters in the Sulu Sea.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An approach to develop chemical intuition for atomistic electron transport calculations using basis set rotations

Single molecule conductance measurements are often interpreted through computational modeling, but the complexity of these calculations makes it difficult to directly link them to simpler concepts and models. Previous work has attempted to make this connection using maximally localized Wannier functions and symmetry adapted basis sets, but their use can be ambiguous and non-trivial. Starting from a Hamiltonian and overlap matrix written in a hydrogen-like basis set, we demonstrate a simple approach to obtain a new basis set that is chemically more intuitive and allows interpretation in terms of simple concepts and models. By diagonalizing the Hamiltonians corresponding to each atom in the molecule, we obtain a basis set that can be partitioned into pseudo-σ and −π and allows partitioning of the Landuaer-Büttiker transmission as well as create simple Hückel models that reproduce the key features of the full calculation. This method provides a link between complex calculations and simple concepts and models to provide intuition or extract parameters for more complex model systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Second-order asymptotics for quantum hypothesis testing in settings beyond i.i.d.—quantum lattice systems and more

Quantum Stein’s lemma is a cornerstone of quantum statistics and concerns the problem of correctly identifying a quantum state, given the knowledge that it is one of two specific states (ρ or σ). It was originally derived in the asymptotic i.i.d. setting, in which arbitrarily many (say, n) identical copies of the state (ρ{sup ⊗n} or σ{sup ⊗n}) are considered to be available. In this setting, the lemma states that, for any given upper bound on the probability α{sub n} of erroneously inferring the state to be σ, the probability β{sub n} of erroneously inferring the state to be ρ decays exponentially in n, with the rate of decay converging to the relative entropy of the two states. The second order asymptotics for quantum hypothesis testing, which establishes the speed of convergence of this rate of decay to its limiting value, was derived in the i.i.d. setting independently by Tomamichel and Hayashi, and Li. We extend this result to settings beyond i.i.d. Examples of these include Gibbs states of quantum spin systems (with finite-range, translation-invariant interactions) at high temperatures, and quasi-free states of fermionic lattice gases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic level-set variational implicit-solvent approach to solute-solvent interfacial fluctuations

Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. We also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the “normal velocity” that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the inclusion of fluctuations into the VISM and understanding the impact of interfacial fluctuations on biomolecular solvation with an implicit-solvent approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Studying excited-state-specific perturbation theory on the Thiel set

Here, we explore the performance of a recently introduced N 5 -scaling excited-state-specific second order perturbation theory (ESMP2) on the singlet excitations of the Thiel benchmarking set. We find that, without regularization, ESMP2 is quite sensitive to π system size, performing well in molecules with small π systems but poorly in those with larger π systems. With regularization, ESMP2 is far less sensitive to π system size and shows a higher overall accuracy on the Thiel set than CC2, equation of motion-coupled cluster with singles and doubles, CC3, and a wide variety of time-dependent density functional approaches. Unsurprisingly, even regularized ESMP2 is less accurate than multi-reference perturbation theory on this test set, which can, in part, be explained by the set’s inclusion of some doubly excited states but none of the strong charge transfer states that often pose challenges for state-averaging. Beyond energetics, we find that the ESMP2 doubles norm offers a relatively low-cost way to test for doubly excited character without the need to define an active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved learning from data competitions through strategic design of training and test data sets

Leveraging the depth and breadth of solutions generated through crowdsourcing can be a powerful accelerator to method development for high consequence problems. While data science competitions have become quite popular and prevalent, particularly in supervised learning formats, their implementations by the host are highly variable. Without careful planning, a supervised learning competition is vulnerable to overfitting, where the winning solutions are so closely tuned to the particular set of provided data that they cannot generalize to the general underlying problem of interest to the host. This paper outlines important considerations for strategically designing relevant and informative data sets to maximize the learning outcome from hosting a competition. These include: precisely defining the scope of the problem, encouraging participation by competitors from diverse technical backgrounds, specifying the most interesting solution space in order to encourage improvement and distinguish between competitors, strategically generating data sets that enable testing for interpolation and extrapolation to new scenarios of interest, leveraging design of experiment principles for strategic data design while preventing unintentional artifacts in the competition data set that an algorithm could exploit without addressing the real problem of interest, and carefully designing the leaderboard scoring metric to select top solutions that exactly match the overall competition goals. The methods are illustrated with a recently completed competition in the context of urban radiological search to evaluate algorithms capable of detecting, identifying, and locating radioactive materials. Simulated data were used in the urban search competition. Ideas for using measured real data in competitions are also suggested

97 MATHEMATICS AND COMPUTING↗

A NOVEL, FULLY AUTOMATED PIPELINE FOR PERIOD ESTIMATION IN THE EROS 2 DATA SET

We present a new method to discriminate periodic from nonperiodic irregularly sampled light curves. We introduce a periodic kernel and maximize a similarity measure derived from information theory to estimate the periods and a discriminator factor. We tested the method on a data set containing 100,000 synthetic periodic and nonperiodic light curves with various periods, amplitudes, and shapes generated using a multivariate generative model. We correctly identified periodic and nonperiodic light curves with a completeness of ∼90% and a precision of ∼95%, for light curves with a signal-to-noise ratio (S/N) larger than 0.5. We characterize the efficiency and reliability of the model using these synthetic light curves and apply the method on the EROS-2 data set. A crucial consideration is the speed at which the method can be executed. Using a hierarchical search and some simplification on the parameter search, we were able to analyze 32.8 million light curves in ∼18 hr on a cluster of GPGPUs. Using the sensitivity analysis on the synthetic data set, we infer that 0.42% of the sources in the LMC and 0.61% of the sources in the SMC show periodic behavior. The training set, catalogs, and source code are all available at http://timemachine.iic.harvard.edu.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models

Abstract We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation invariant functions on sets. More generally, this work provides a step towards building large foundation models for HEP that can be generically pre-trained with self-supervised learning and later fine-tuned for a variety of down-stream tasks. In MPM, particles in a set are masked and the training objective is to recover their identity, as defined by a discretized token representation of a pre-trained vector quantized variational autoencoder. We study the efficacy of the method in samples of high energy jets at collider physics experiments, including studies on the impact of discretization, permutation invariance, and ordering. We also study the fine-tuning capability of the model, showing that it can be adapted to tasks such as supervised and weakly supervised jet classification, and that the model can transfer efficiently with small fine-tuning data sets to new classes and new data domains.

Heinrich, Lukas (ORCID:0000000240487584)↗

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

59 BASIC BIOLOGICAL SCIENCES↗

On data set tensions and signatures of new cosmological physics

ABSTRACT Can new cosmic physics be uncovered through tensions amongst data sets? Tensions in parameter determinations amongst different types of cosmological observation, especially the ‘Hubble tension’ between probes of the expansion rate, have been invoked as possible indicators of new physics, requiring extension of the ΛCDM paradigm to resolve. Within a fully Bayesian framework, we show that the standard tension metric gives only part of the updating of model probabilities, supplying a data co-dependence term that must be combined with the Bayes factors of individual data sets. This shows that, on its own, a reduction of data set tension under an extension to ΛCDM is insufficient to demonstrate that the extended model is favoured. Any analysis that claims evidence for new physics solely on the basis of alleviating data set tensions should be considered incomplete and suspect. We describe the implications of our results for the interpretation of the Hubble tension.

Cortês, Marina (ORCID:0000000304853767)↗

Multisliced gausslet basis sets for electronic structure

We introduce highly local basis sets for electronic structure which are very efficient for correlation calculations near the complete basis set limit. Our approach is based on gausslets, recently introduced waveletlike smooth orthogonal functions. We adapt the gausslets to particular systems using one-dimensional (1D) coordinate transformations, putting more basis functions near the nuclei, while maintaining orthogonality. Furthermore, three-dimensional basis functions are composed out of products of the 1D functions in an efficient way called multislicing. We demonstrate these bases with both Hartree-Fock and density matrix renormalization group calculations on hydrogen chain systems. With both methods, we can go to higher accuracy in the complete basis set limit than is practical for conventional Gaussian basis sets, with errors near 0.1 mH per atom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automating the Solar Interconnection Technical Evaluation Process: PREconfiguring and Controlling Inverter SEt-Points (PRECISE)

Utilities are receiving an increasing number of interconnection requests for distributed solar photovoltaic (PV) systems from their customers, requiring a solution to quickly and intelligently perform technical assessments of these requests and to manage these new renewable energy assets. In this paper, we present a stand-alone interconnection tool, PREconfiguring and Controlling Inverter SEt-points (PRECISETM), and how it overcomes the challenges of accelerating technical evaluations and leverages smart inverter functionality to provide local voltage support on an as-needed basis. The paper details the purpose and architecture of PRECISE, including tools, data source requirements, the model-based interconnection evaluation process, and technical results. PRECISE is an integrated software tool that customizes PV inverter settings for utilities by modeling and assessing impacts on local voltages and the need for advanced inverter functions (AIFs) (e.g., volt-VAR and volt-watt). PRECISE maximizes the use of readily available utility data sets to make fast online assessments of incoming PV interconnection requests and makes accept/reject recommendations along with custom settings for AIFs.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

A Comprehensive Set of Impact Data for Common Aerospace Metals

Our results for the two sets of impact experiments are reported here. In order to assist with model development using the impact data reported, the materials are mechanically characterized using a series of standard experiments. The first set of impact data comes from a series of coefficient of restitution experiments, in which a 2 meter long pendulum is used to study "in context" measurements of the coefficient of restitution for eight different materials (6061-T6 Aluminum, Phosphor Bronze alloy 510, Hiperco, Nitronic 60A, Stainless Steel 304, Titanium, Copper, and Annealed Copper). The coefficient of restitution is measured via two different techniques: digital image correlation and laser Doppler vibrometry. Due to the strong agreement of the two different methods, only results from the digital image correlation are reported. The coefficient of restitution experiments are "in context" as the scales of the geometry and impact velocities are representative of common features in the motivating application for this research. Finally, a series of compliance measurements are detailed for the same set of materials. Furthermore, the compliance measurements are conducted using both nano-indentation and micro-indentation machines, providing sub-nm displacement resolution and uN force resolution. Good agreement is seen for load levels spanned by both machines. As the transition from elastic to plastic behavior occurs at contact displacements on the order of 30 nm, this data set provides a unique insight into the transitionary region.

36 MATERIALS SCIENCE↗

Characteristics of flattening filter free beams at low monitor unit settings

Purpose: Newer linear accelerators (linacs) have been equipped to deliver flattening filter free (FFF) beams. When FFF beams are used for step-and-shoot intensity-modulated radiotherapy (IMRT), the stability of delivery of small numbers of monitor units (MU) is important. The authors developed automatic measurement techniques to evaluate the stability of the dose profile, dose linearity, and consistency. Here, the authors report the performance of the Artiste™ accelerator (Siemens, Erlangen, Germany) in delivering low-MU FFF beams.Methods: A 6 MV flattened beam (6X) with 300 MU/min dose rate and FFF beams of 7 (7XU) and 11 MV (11XU), each with a 500 MU/min dose rate, were measured at 1, 2, 3, 5, 8, 10, and 20 MU settings. For the 2000 MU/min dose rate, the 7 (7XUH) and 11 MV (11XUH) beams were set at 10, 15, 20, 25, and 30 MU because of the limits of the minimum MU settings. Beams with 20 × 20 and 10 × 10 cm{sup 2} field sizes were alternately measured ten times in intensity modulated (IM) mode, with which Siemens linacs regulate beam delivery for step-and-shoot IMRT. The in- and crossplane beam profiles were measured using a Profiler™ Model 1170 (Sun Nuclear Corporation, Melbourne, FL) in multiframe mode. The frames of 20 × 20 cm{sup 2} beams were identified at the off-axis profile. The 6X beam profile was normalized at the central axis. The 7 and 11 MV FFF beam profiles were rescaled to set the dose at the central axis at 145% and 170%, respectively. Point doses were also measured using a Farmer-type ionization chamber and water-equivalent solid phantom to evaluate the linearity and consistency of low-MU beam delivery. The values displayed on the electrometer were recognized with a USB-type camera and read with open-source optical character recognition software.Results: The symmetry measurements of the 6X, 7XU, and 11XU beam profiles were better than 2% for beams ≥2 MU and improved with increasing MU. The variations in flatness of FFF beams ≥2 MU were ±5%. The standard deviation of the symmetry and flatness also decreased with increasing MU. The linearity of the 6X beam was ±1% and ±2% for the beams of ≥5 and ≥3 MU, respectively. The 7XU and 11XU beams of ≥2 MU showed linearity with ±2% except the 7XU beam of 8 MU (+2.9%). The profiles of the FFF beams with 2000 and 500 MU/min dose rate were similar.Conclusions: The characteristics of low-MU beams delivered in IM mode were evaluated using an automatic measurement system developed in this study. The authors demonstrated that the profiles of FFF beams of the Artiste™ linac were highly stable, even at low MU. The linearity of dose output was also stable for beams ≥2 MU.

61 RADIATION PROTECTION AND DOSIMETRY↗

Development of a golden beam data set for the commissioning of a proton double-scattering system in a pencil-beam dose calculation algorithm

Purpose: The purpose of this investigation is to determine if a single set of beam data, described by a minimal set of equations and fitting variables, can be used to commission different installations of a proton double-scattering system in a commercial pencil-beam dose calculation algorithm. Methods: The beam model parameters required to commission the pencil-beam dose calculation algorithm (virtual and effective SAD, effective source size, and pristine-peak energy spread) are determined for a commercial double-scattering system. These parameters are measured in a first room and parameterized as function of proton energy and nozzle settings by fitting four analytical equations to the measured data. The combination of these equations and fitting values constitutes the golden beam data (GBD). To determine the variation in dose delivery between installations, the same dosimetric properties are measured in two additional rooms at the same facility, as well as in a single room at another facility. The difference between the room-specific measurements and the GBD is evaluated against tolerances that guarantee the 3D dose distribution in each of the rooms matches the GBD-based dose distribution within clinically reasonable limits. The pencil-beam treatment-planning algorithm is commissioned with the GBD. The three-dimensional dose distribution in water is evaluated in the four treatment rooms and compared to the treatment-planning calculated dose distribution. Results: The virtual and effective SAD measurements fall between 226 and 257 cm. The effective source size varies between 2.4 and 6.2 cm for the large-field options, and 1.0 and 2.0 cm for the small-field options. The pristine-peak energy spread decreases from 1.05% at the lowest range to 0.6% at the highest. The virtual SAD as well as the effective source size can be accurately described by a linear relationship as function of the inverse of the residual energy. An additional linear correction term as function of RM-step thickness is required for accurate parameterization of the effective SAD. The GBD energy spread is given by a linear function of the exponential of the beam energy. Except for a few outliers, the measured parameters match the GBD within the specified tolerances in all of the four rooms investigated. For a SOBP field with a range of 15 g/cm{sup 2} and an air gap of 25 cm, the maximum difference in the 80%–20% lateral penumbra between the GBD-commissioned treatment-planning system and measurements in any of the four rooms is 0.5 mm. Conclusions: The beam model parameters of the double-scattering system can be parameterized with a limited set of equations and parameters. This GBD closely matches the measured dosimetric properties in four different rooms.

43 PARTICLE ACCELERATORS↗

SU-C-204-06: Surface Imaging for the Set-Up of Proton Post-Mastectomy Chestwall Irradiation: Gated Images Vs Non Gated Images

Purpose: Historically, the set-up for proton post-mastectomy chestwall irradiation at our institution started with positioning the patient using tattoos and lasers. One or more rounds of orthogonal X-rays at gantry 0° and beamline X-ray at treatment gantry angle were then taken to finalize the set-up position. As chestwall targets are shallow and superficial, surface imaging is a promising tool for set-up and needs to be investigated Methods: The orthogonal imaging was entirely replaced by AlignRT™ (ART) images. The beamline X-Ray image is kept as a confirmation, based primarily on three opaque markers placed on skin surface instead of bony anatomy. In the first phase of the process, ART gated images were used to set-up the patient and the same specific point of the breathing curve was used every day. The moves (translations and rotations) computed for each point of the breathing curve during the first five fractions were analyzed for ten patients. During a second phase of the study, ART gated images were replaced by ART non-gated images combined with real-time monitoring. In both cases, ART images were acquired just before treatment to access the patient position compare to the non-gated CT. Results: The average difference between the maximum move and the minimum move depending on the chosen breathing curve point was less than 1.7 mm for all translations and less than 0.7° for all rotations. The average position discrepancy over the course of treatment obtained by ART non gated images combined to real-time monitoring taken before treatment to the planning CT were smaller than the average position discrepancy obtained using ART gated images. The X-Ray validation images show similar results with both ART imaging process. Conclusion: The use of ART non gated images combined with real time imaging allows positioning post-mastectomy chestwall patients in less than 3 mm / 1°.

60 APPLIED LIFE SCIENCES↗

MO-F-CAMPUS-T-05: Correct Or Not to Correct for Rotational Patient Set-Up Errors in Stereotactic Radiosurgery

Purpose: To quantify the effect of patient rotation in stereotactic radiation therapy and establish a threshold where rotational patient set-up errors have a significant impact on target coverage. Methods: To simulate rotational patient set-up errors, a Matlab code was created to rotate the patient dose distribution around the treatment isocentre, located centrally in the lesion, while keeping the structure contours in the original locations on the CT and MRI. Rotations of 1°, 3°, and 5° for each of the pitch, roll, and yaw, as well as simultaneous rotations of 1°, 3°, and 5° around all three axes were applied to two types of brain lesions: brain metastasis and acoustic neuroma. In order to analyze multiple tumour shapes, these plans included small spherical (metastasis), elliptical (acoustic neuroma), and large irregular (metastasis) tumour structures. Dose-volume histograms and planning target volumes were compared between the planned patient positions and those with simulated rotational set-up errors. The RTOG conformity index for patient rotation was also investigated. Results: Examining the tumour volumes that received 80% of the prescription dose in the planned and rotated patient positions showed decreases in prescription dose coverage of up to 2.3%. Conformity indices for treatments with simulated rotational errors showed decreases of up to 3% compared to the original plan. For irregular lesions, degradation of 1% of the target coverage can be seen for rotations as low as 3°. Conclusions: This data shows that for elliptical or spherical targets, rotational patient set-up errors less than 3° around any or all axes do not have a significant impact on the dose delivered to the target volume or the conformity index of the plan. However the same rotational errors would have an impact on plans for irregular tumours.

60 APPLIED LIFE SCIENCES↗