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At least 163 records · Page 9

Semiempirical Theories of the Affinities of Negative Atomic Ions

The determination of the electron affinities of negative atomic ions by means of direct experimental investigation is limited. To supplement the meager experimental results, several semiempirical theories have been advanced. One commonly used technique involves extrapolating the electron affinities along the isoelectronic sequences, The most recent of these extrapolations Is studied by extending the method to Include one more member of the isoelectronic sequence, When the results show that this extension does not increase the accuracy of the calculations, several possible explanations for this situation are explored. A different approach to the problem is suggested by the regularities appearing in the electron affinities. Noting that the regular linear pattern that exists for the ionization potentials of the p electrons as a function of Z, repeats itself for different degrees of ionization q, the slopes and intercepts of these curves are extrapolated to the case of the negative Ion. The method is placed on a theoretical basis by calculating the Slater parameters as functions of q and n, the number of equivalent p-electrons. These functions are no more than quadratic in q and n. The electron affinities are calculated by extending the linear relations that exist for the neutral atoms and positive ions to the negative ions. The extrapolated. slopes are apparently correct, but the intercepts must be slightly altered to agree with experiment. For this purpose one or two experimental affinities (depending on the extrapolation method) are used in each of the two short periods. The two extrapolation methods used are: (A) an isoelectronic sequence extrapolation of the linear pattern as such; (B) the same extrapolation of a linearization of this pattern (configuration centers) combined with an extrapolation of the other terms of the ground configurations. The latter method Is preferable, since it requires only experimental point for each period. The results agree within experimental error with all data, except with the most recent value of C, which lies 10% lower.

Edie, John W.

Robust Design Under Uncertainty in Quantum Error Mitigation

Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical postprocessing of quantum computation outcomes is a popular approach for error mitigation, which includes methods, such as zero noise extrapolation, virtual distillation, and learning-based error mitigation. However, these techniques have limitations due to the propagation of uncertainty resulting from the finite shot number of a quantum measurement. In this work, we introduce general and unbiased methods for quantifying the uncertainty and error of error-mitigated observables based on the strategic sampling of error mitigation outcomes. We then extend our approach to demonstrate the optimization of performance and robustness of error mitigation under uncertainty. To illustrate our methods, we apply them to zero noise extrapolation and Clifford date regression in the ground state of the XY model simulated using depolarizing and International Business Machines Corporation (IBM) Toronto noise models, respectively. In particular, we optimize the choice of noise levels and the allocation of shots for zero noise extrapolation and the distribution of the training circuits for Clifford data regression. While our methods are readily applicable to any postprocessing-based error mitigation approach, in practice they must not be prohibitively expensive—even though they perform optimizations of the error mitigation hyperparameters requiring sampling of a statistical distribution of error mitigation outcomes. By leveraging surrogate-based optimization, we show that our methods can efficiently perform optimal design for a zero noise extrapolation implementation. We then further demonstrate the transferability of learned zero noise extrapolation hyperparameters to other similar circuits.

97 MATHEMATICS AND COMPUTING

Genomic instability, bystander effect, cytoplasmic irradiation and other phenomena that may achieve fame without fortune

The possible risk of induced malignancies in astronauts, as a consequence of the radiation environment in space, is a factor of concern for long term missions. Cancer risk estimates for high doses of low LET radiation are available from the epidemiological studies of the A-bomb survivors. Cancer risks at lower doses cannot be detected in epidemiological studies and must be inferred by extrapolation from the high dose risks. The standard setting bodies, such as the ICRP recommend a linear, no-threshold extrapolation of risks from high to low doses, but this is controversial. A study of mechanisms of carcinogenesis may shed some light on the validity of a linear extrapolation. The multi-step nature of carcinogenesis suggests that the role of radiation may be to induce a mutation leading to a mutator phenotype. High energy Fe ions, such as those encountered in space are highly effective in inducing genomic instability. Experiments involving the single particle microbeam have demonstrated a "bystander effect", ie a biological effect in cells not themselves hit, but in close proximity to those that are, as well as the induction of mutations in cells where only the cytoplasm, and not the nucleus, have been traversed by a charged particle. These recent experiments cast doubt on the validity of a simple linear extrapolation, but the data are so far fragmentary and conflicting. More studies are necessary. While mechanistic studies cannot replace epidemiology as a source of quantitative risk estimates, they may shed some light on the shape of the dose response relationship and therefore on the limitations of a linear extrapolation to low doses.

NASA Discipline Radiation Health

Deriving Three Dimensional Reservoir Bathymetry from Multi-Satellite Datasets

We evaluate different techniques that rebuild reservoir bathymetry by combining multi-satellite imagery of surface water elevation and extent. Digital elevation models (DEMs) are processed in two distinct ways in order to determine 3-D reservoir bathymetry. They are defined as (a) linear extrapolation and (b) linear interpolation. The first one linearly extrapolates the land slope, defining the bottom as the intersection of all extrapolated lines. The second linearly interpolates the uppermost and lowermost pixels of the reservoir's main river, repeating the process for all other tributaries. A visible bathymetry, resulting from the combination of radar altimetry and water extent masks, can be coupled with the DEM, improving the accuracy of techniques (a) and (b). Envisat-and Altika-based altimetric time series is combined to a Landsat-based water extent database over the2002-2016 period in order to generate the visible bathymetry, and topography is derived from the 3-arcsecHydroSHEDS DEM. Fourteen 3-D bathymetries derived from the combination of these techniques and datasets, plus the inclusion of upstream and downstream riverbed elevations, are evaluated over Lake Mead. Accuracy is measured using ground observations, and show that metrics improve as a function of added data requirement and processing. Best bathymetry estimates are obtained when the visible bathymetry, linear extrapolation technique and riverbed elevation are combined. Water storage variability is also evaluated and shows that best results are derived from the aforementioned combination. This study contributes to our understanding and representation of reservoir water impoundment impacts on the hydrological cycle.

HydroSHEDS

Sonic boom predictions for three generic models using a solution-adaptive full-potential code

The TranAir full-potential code, which utilizes a solution-adaptive, unstructured Cartesian grid, was used to compute near-field pressure signatures of three generic supersonic configurations: a cone-cylinder, a low aspect ratio rectangular wing, and a delta-wing/body. TranAir pressure signatures are extrapolated to near- and mid-field distances using a quasi-linear extrapolation technique. Results are compared with existing wind tunnel data and, where possible, with extrapolated experimental data and quasi-linear Whitham-method results. In general, the extrapolated TranAir data is in good agreement with experimental and Whitham-method pressure signatures, but peak pressures are slightly under-predicted. It is thought that computed data obtained too near to the model was the main reason for the discrepancies. Flow-field grid structure was also found to be important in obtaining accurate offbody data.

Madson, Michael D.

Sonic boom predictions using a solution-adaptive full-potential code

The TranAir full-potential code, which utilizes a solution-adaptive, unstructured Cartesian grid, was used to compute near-field pressure signatures of three generic geometries: (1) a cone-cylinder; (2) a low aspect ratio rectangular wing; and (3) a delta-wing/body. Pressure signatures computed by TranAir are extrapolated to near- and midfield distances using a quasilinear extrapolation technique. Results are compared with wind-tunnel data and, where possible, with extrapolated wind-tunnel data and Whitham-method results. In general, extrapolated TranAir data is in good agreement with experimental and Whitham-method pressure signatures, but peak pressures are slightly underpredicted. It is felt that data computed too close to the model caused some of the discrepancies. The flowfield grid structure was also found to be an important issue in obtaining accurate off-body data. Results were encouraging enough to proceed with the application of TranAir to conceptual configurations in support of the NASA high speed research program (HSRP).

Madson, Michael D.

Sonic Boom Propagation Codes Validated by Flight Test

The sonic boom propagation codes reviewed in this study, SHOCKN and ZEPHYRUS, implement current theory on air absorption using different computational concepts. Review of the codes with a realistic atmosphere model confirm the agreement of propagation results reported by others for idealized propagation conditions. ZEPHYRUS offers greater flexibility in propagation conditions and is thus preferred for practical aircraft analysis. The ZEPHYRUS code was used to propagate sonic boom waveforms measured approximately 1000 feet away from an SR-71 aircraft flying at Mach 1.25 to 5000 feet away. These extrapolated signatures were compared to measurements at 5000 feet. Pressure values of the significant shocks (bow, canopy, inlet and tail) in the waveforms are consistent between extrapolation and measurement. Of particular interest is that four (independent) measurements taken under the aircraft centerline converge to the same extrapolated result despite differences in measurement conditions. Agreement between extrapolated and measured signature duration is prevented by measured duration of the 5000 foot signatures either much longer or shorter than would be expected. The duration anomalies may be due to signature probing not sufficiently parallel to the aircraft flight direction.

Poling, Hugh W.

Accurate Evaluation of Quantum Integrals

Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schr\"{o}dinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.

Galant, David C.

Accurate Evaluation of Quantum Integrals

Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.

Galant, D. C.

Wind Tunnel Measurements of Shuttle Orbiter Global Heating with Comparisons to Flight

An aerothermodynamic database of global heating images was acquired of the Shuttle Orbiter in the NASA Langley Research Center 20-Inch Mach 6 Air Tunnel. These results were obtained for comparison to the global infrared images of the Orbiter in flight from the infrared sensing aeroheating flight experiment (ISAFE). The most recent ISAFE results from STS-103, consisted of port side images, at hypersonic conditions, of the surface features that result from the strake vortex scrubbing along the side of the vehicle. The wind tunnel results were obtained with the phosphor thermography system, which also provides global information and thus is ideally suited for comparison to the global flight results. The aerothermodynamic database includes both windward and port side heating images of the Orbiter for a range of angles of attack (20 to 40 deg), freestream unit Reynolds number (1 x 10(exp 6))/ft to 8 x 10(exp 6)/ft, body flap deflections (0, 5, and 10 deg), speed brake deflections (0 and 45 deg), as well as with boundary layer trips for forced transition to turbulence heating results. Sample global wind tunnel heat transfer images were extrapolated to flight conditions for comparison to Orbiter flight data. A windward laminar case for an angle of attack of 40 deg was extrapolated to Mach 11.6 flight conditions for comparison to STS-2 flight thermocouple results. A portside wind tunnel image for an angle of attack of 25 deg was extrapolated for Mach 5 flight conditions for comparison to STS-103 global surface temperatures. The comparisons showed excellent qualitative agreement, however the extrapolated wind tunnel results over-predicted the flight surface temperatures on the order of 5% on the windward surface and slightly higher on the portside.

Berry, Scott A.

Loss tolerant speech decoder for telecommunications

A method and device for extrapolating past signal-history data for insertion into missing data segments in order to conceal digital speech frame errors. The extrapolation method uses past-signal history that is stored in a buffer. The method is implemented with a device that utilizes a finite-impulse response (FIR) multi-layer feed-forward artificial neural network that is trained by back-propagation for one-step extrapolation of speech compression algorithm (SCA) parameters. Once a speech connection has been established, the speech compression algorithm device begins sending encoded speech frames. As the speech frames are received, they are decoded and converted back into speech signal voltages. During the normal decoding process, pre-processing of the required SCA parameters will occur and the results stored in the past-history buffer. If a speech frame is detected to be lost or in error, then extrapolation modules are executed and replacement SCA parameters are generated and sent as the parameters required by the SCA. In this way, the information transfer to the SCA is transparent, and the SCA processing continues as usual. The listener will not normally notice that a speech frame has been lost because of the smooth transition between the last-received, lost, and next-received speech frames.

Prieto, Jr., Jaime L.

Bounding Species Distribution Models

Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].

Stohlgren, Thomas J.

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics

Plasma performance and operational space with an RMP-ELM suppressed edge

Abstract The operational space and global performance of plasmas with edge-localized modes (ELMs) suppressed by resonant magnetic perturbations (RMPs) are surveyed by comparing AUG, DIII-D, EAST, and KSTAR stationary operating points. RMP-ELM suppression is achieved over a range of plasma currents, toroidal fields, and RMP toroidal mode numbers. Consistent operational windows in edge safety factor are found across devices, while windows in plasma shaping parameters are distinct. Accessed pedestal parameters reveal a quantitatively similar pedestal-top density limit for RMP-ELM suppression in all devices of just over 3 × 10 19 m −3 . This is surprising given the wide variance of many engineering parameters and edge collisionalities, and poses a challenge to extrapolation of the regime. Wide ranges in input power, confinement time, and stored energy are observed, with the achieved triple product found to scale like the product of current, field, and radius. Observed energy confinement scaling with engineering parameters for RMP-ELM suppressed plasmas are presented and compared with expectations from established H and L-mode scalings, including treatment of uncertainty analysis. Different scaling exponents for individual engineering parameters are found as compared to the established scalings. However, extrapolation to next-step tokamaks ITER and SPARC find overall consistency within uncertainties with the established scalings, finding no obvious performance penalty when extrapolating from the assembled multi-device RMP-ELM suppressed database. Overall this work identifies common physics for RMP-ELM suppression and highlights the need to pursue this no-ELM regime at higher magnetic field and different plasma physical size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Exponentially Reduced Circuit Depths Using Trotter Error Mitigation

Product formulas are a popular class of digital quantum simulation algorithms due to their conceptual simplicity, low overhead, and performance, which often exceeds theoretical expectations. Recently, Richardson extrapolation and polynomial interpolation have been proposed to mitigate the Trotter error incurred by the use of these formulas. This work provides a rigorous, general analysis of these techniques for computing time-evolved observables, simplifying the interpolation algorithm in the process, and shows that extrapolation generically improves the performance of product formulas for this task. We demonstrate that, to achieve error 𝜖 in a simulation of time 𝑇 using a 𝑝 ⁢th-order product formula with extrapolation, circuit depths of 𝑂⁡(𝑇 1+1/𝑝 ⁢polylog (1/𝜖)) are sufficient—an exponential improvement in the precision over product formulas alone. Furthermore, we prove that these algorithms achieve commutator scaling, and improve the 𝑇 complexity for the interpolation algorithm. By relaxing the requirement of performing exact Chebyshev interpolation, our simplified algorithm eliminates the need for fractional implementations of Trotter steps, reducing computational overhead. Finally, we show these techniques can be combined with the classical shadows method to estimate many time-evolved local observables. Taken together, our findings provide the strongest evidence yet for the utility of Trotter error-mitigation techniques in algorithmic applications.

quantum algorithms & computation

16 O ⁡(𝑒,𝑒′⁢𝛼)⁢ 12 C measurements and the 12 C ⁡(𝛼,𝛾)⁢ 16 O astrophysical reaction rate

The 12 C ⁡(𝛼,𝛾)⁢ 16 O reaction, an important component of stellar helium burning, has a key role in nuclear astrophysics. It has significant impact on the evolution and final state of heavy to low mass stars, maximum mass of stellar formed black holes and also shapes the elemental abundances resulting from nucleosynthesis in such stars. Providing a reliable estimate for the energy dependence of this reaction at stellar helium burning temperatures has been a longstanding and important goal. In this work, we study the role of potential new 𝐸⁢1 and 𝐸⁢2 measurements of the 16 O ⁡(𝑒,𝑒′⁢𝛼)⁢ 12 C reaction in reducing the overall uncertainty in the astrophysical 𝑆 factor for the 12 C ⁡(𝛼,𝛾)⁢ 16 O 𝐸⁢1 and 𝐸⁢2 ground state capture extrapolated to a stellar energy of 300 keV. A multilevel 𝑅-matrix analysis is used to make extrapolations of the 𝑆 𝐸⁢1 (300 keV) and 𝑆 𝐸⁢2 (300 keV) factors for the 12 C ⁡(𝛼,𝛾)⁢ 16 O reaction from existing ground state capture data. Bayesian analysis is used to quantify the uncertainties in the extrapolations for both the existing data alone and also when possible new experimental data are included. In particular, we consider a new experiment that would make use of a high-intensity low-energy electron beam that impinges on a windowless oxygen gas target as a means to determine the total 𝐸⁢1 and 𝐸⁢2 ground state cross sections for this reaction. Here we find that the new data could significantly reduce the 𝑆⁡(300) uncertainties. Splitting the new data into high and low energy regions shows that both low and high energy data are effective in reducing the uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Crime prediction modeling

A study of techniques for the prediction of crime in the City of Los Angeles was conducted. Alternative approaches to crime prediction (causal, quasicausal, associative, extrapolative, and pattern-recognition models) are discussed, as is the environment within which predictions were desired for the immediate application. The decision was made to use time series (extrapolative) models to produce the desired predictions. The characteristics of the data and the procedure used to choose equations for the extrapolations are discussed. The usefulness of different functional forms (constant, quadratic, and exponential forms) and of different parameter estimation techniques (multiple regression and multiple exponential smoothing) are compared, and the quality of the resultant predictions is assessed.

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