Extrapolation technique pitfalls in asymmetry measurements at colliders
Not Available
Colletti, Katrina↗
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Ground-state properties of 4He and 16O extrapolated from lattice QCD with pionless EFT
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Uncertainty in stretch extrapolation of laminar flame speed from expanding spherical flames
Not Available
Wu, Fujia (ORCID:0000000227733410)↗
Single-Point Extrapolation to the Complete Basis Set Limit through Deep Learning
Machine learning (ML) offers an attractive method for making predictions about molecular systems while circumventing the need to run expensive electronic structure calculations. Once trained on ab initio data, the promise of ML is to deliver accurate predictions of molecular properties that were previously computationally infeasible. In this work, we develop and train a graph neural network model to correct the basis set incompleteness error (BSIE) between a small and large basis set at the RHF and B3LYP levels of theory. Our results show that, when compared to fitting to the total potential, an ML model fitted to correct the BSIE is better at generalizing to systems not seen during training. We test this ability by training on single molecules while evaluating on molecular complexes. We also show that ensemble models yield better behaved potentials in situations where the training data is insufficient. However, even when only fitting to the BSIE, acceptable performance is only achieved when the training data sufficiently resemble the systems one wants to make predictions on. As a result, the test error of the final model trained to predict the difference between the cc-pVDZ and cc-pV5Z potential is 0.184 kcal/mol for the B3LYP density functional, and the ensemble model accurately reproduces the large basis set interaction energy curves on the S66x8 dataset.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Reducing the Cost of CCSD Basis Set Extrapolation in Ab Initio Computational Thermochemistry
Here, a series of approximations to CCSD contributions in computational model chemistries is presented in the context of kcal mol –1 , kJ mol –1 , and 20 cm –1 theoretical predictions of total atomization energies, benchmarked within the HEAT+CH 4 test suite. A specific set of circumstances where MP2, without empirical scaling, may be used as an effective intermediate in the first two of these accuracy ranges was determined. However, SDQ-MP4, a method long used in pursuit of kcal mol –1 accuracy but relatively unstudied in the subchemical accuracy community, offers significant improvement over the quality of MP2 as a basis-set intermediate at significantly reduced cost compared to CCSD. Given this, we argue for SDQ-MP4 as the de facto CCSD basis-set intermediate in sub-chemical accuracy calculations when CCSD in a desired basis set becomes unaffordable. We additionally report on a “CBS-like” scheme, where MP2 and SDQ-MP4 are used in conjunction to create a “cheap” three-part approximation of large CCSD basis set limits. The data for the CCSD approximation schemes are organized in such a way that model chemistry developers can locate an analog of their current approach for the CCSD basis set limit and explore alternative intermediates that either decrease computational cost or increase computational accuracy. We also show, for a handful of molecules, that SDQ-MP4 shows promise as an effective basis-set intermediate for harmonic and fundamental frequency computations, allowing for zero-point corrections of nearly CCSD(T)/ANO1 quality using simple composite methods that only require CCSD(T)/ANO0.
Thorpe, James H. [Argonne National Laboratory (ANL↗
Comparative Computational Study of Electronic Excitations of Neutral and Charged Small Oligothiophenes and Their Extrapolations Based on Simple Models
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Extrapolating dynamic leidenfrost principles to metallic nanodroplets on asymmetrically textured surfaces
In an effort to enhance our knowledge on how to control the movement of metallic nanodroplets, here we have used classical molecular dynamics simulations to investigate whether Cu nanostructures deposited on nanopillared substrates can be made to jump at desired angles. We find that such control is possible, especially for Cu nanostructures that are symmetric; for asymmetric nanostructures, however, control is more uncertain. The work presented here borrows ideas from two seemingly different fields, metallic droplets and water droplets in the dynamic Leidenfrost regime. Despite the differences in the respective systems, we find common ground in their behavior on nanostructured surfaces. As a result, we suggest that the ongoing research in Leidenfrost droplets is a fertile area for scientists working on metallic nanodroplets.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery
Traditional machine learning (ML) metrics overestimate model performance for materials discovery.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant
In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles’ velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Impact of ELM control techniques on tungsten sputtering in the DIII-D divertor and extrapolations to ITER
The free-streaming plus recycling model (FSRM) has recently been developed to understand and predict tungsten gross erosion rates from the divertor during edge localized modes (ELMs). In this work, the FSRM was tested against the experimental measurements of W sputtering during ELMs, conducted via fast neutral tungsten (WI) spectroscopy. Good agreement is observed using a variety of controlling techniques, including gas puffing, neutral beam heating, and plasma shaping to modify the pedestal stability boundary and, thus, the ELM behavior. ELM mitigation by pellet pacing was observed to strongly reduce W sputtering by flushing C impurities from the pedestal and reducing the divertor target electron temperature. No reduction of W sputtering was observed during the application of resonant magnetic perturbations (RMPs), in contrast to the prediction of the FSRM. Potential sources of this discrepancy are discussed. Lastly, the framework of the FSRM is utilized to predict intra-ELM W sputtering rates in ITER. It is concluded that W erosion during ELMs in ITER will be caused mainly by free-streaming fuel ions, but free-streaming seeded impurities (N or Ne) may increase the erosion rate significantly if present in the pedestal at even the 1% level. Impurity recycling is not expected to cause critical W erosion in ITER due to the very low target electron temperature.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Use of reconstructed 3D equilibria to determine onset conditions of helical cores in tokamaks for extrapolation to ITER
The threshold for spontaneous symmetry breaking, which results in growth of m/n = 1/1 helical cores, in tokamaks is determined using VMEC. This model is based on a DIII-D hybrid discharge with helical core, and it predicts ITER (15MA scenario) to operate far in the helical core formation regime. Helical cores can only exist in tokamak discharges with monotonic but low, or reversed q-shear and qmin 1 in the core. The helical core is a saturated internal kink mode; its onset threshold is proportional to (dp/d)/B 2 t around q = 1. Below the threshold, applied 3-D fields can drive a helical core to finite size, as in DIIID. Above it, a random 3-D kick causes a bifurcation from axisymmetry and excites a spontaneous helical core. Helical cores occur frequently in C-Mod due to impurities; modeling shows the axisymmetric equilibrium becomes unstable at the end of the current ramp up due to the slow current penetration and a resultant reversed shear q-profile, which lowers the threshold. Lastly, a comparison of the helical core onset threshold for discharges from DIII-D, C-Mod and ITER confirms that while DIII-D is marginally stable, C-Mod and especially ITER are highly susceptible to helical core formation.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Dynamic mode decomposition for extrapolating nonequilibrium Green's-function dynamics
The Hartree-Fock generalized Kadanoff-Baym ansatz (HF-GKBA) offers an approximate numerical procedure for propagating the two-time nonequilibrium Green's function (NEGF). Here, using the GW self-energy, we compare the HF-GKBA to exact results for a variety of systems with long- and short-range interactions, different two-body interaction strengths, and various nonequilibrium preparations. We find excellent agreement between the HF-GKBA and exact time evolution in models when more realistic long-range exponentially decaying interactions are considered. Furthermore, this agreement persists for long times and for intermediate to strong interaction strengths. In large systems, HF-GKBA becomes prohibitively expensive for long-time evolutions. For this reason, we look at the use of dynamical mode decomposition (DMD) to reconstruct long-time NEGF trajectories from a sample of the initial trajectory. Using no more than 16% of the total time evolution, we reconstruct the total trajectory with high fidelity. Our results show the potential for DMD to be used in conjunction with HF-GKBA to calculate long-time trajectories in large-scale systems.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Validation and extrapolation of atomic masses with a physics-informed fully connected neural network
Not Available
Huang, Yiming (ORCID:0009000111354387)↗
Extrapolation of scattering data to the negative-energy region. II. Applicability of effective range functions within an exactly solvable model
A problem of analytical continuation of scattering data to the negative-energy region to obtain information about bound states is discussed within an exactly solvable potential model. This work is continuation of the previous one by the same authors [L. D. Blokhintsev et al., Phys. Rev. C 95, 044618 (2017)]. The goal of this paper is to determine the most effective way of analytic continuation for different systems. The d + α and α + 12 C systems are considered and, for comparison, an effective-range function approach and a recently suggested Δ method [O. L. Ramírez Suárez and J.-M. Sparenberg, Phys. Rev. C 96, 034601 (2017).] are applied. We conclude that the method is more effective for heavier systems with large values of the Coulomb parameter, whereas for light systems with small values of the Coulomb parameter the effective-range function method might be preferable.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗