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At least 235 records · Page 13

Stochastic Inversion of Gaussian Random Media Using Transverse Coherence Functions for Reflected Waves: Theory and Method

The transverse coherence functions (TCFs) of phase and amplitude fluctuations of a seismic wave are powerful to estimate the spatial distribution, length scales, and strength of random heterogeneities. However, TCFs have been formulated for transmitted waves only, not for reflected waves. In this paper, we derive reflection TCFs for Gaussian random media. Furthermore, we propose to invert for Gaussian random media using the reflection TCFs based on the grid search. We validate the new reflection TCF formulas using 2D finite-difference numerical experiments. The numerical example also illustrates the feasibility and efficiency of the inversion. The stochastic inversion using reflected waves can be used in both exploration and global seismology.

58 GEOSCIENCES↗

Direct Randomized Benchmarking for Multiqubit Devices

Benchmarking methods that can be adapted to multiqubit systems are essential for assessing the overall or “holistic” performance of nascent quantum processors. The current industry standard is Clifford randomized benchmarking (RB), which measures a single error rate that quantifies overall performance. But, scaling Clifford RB to many qubits is surprisingly hard. It has only been performed on one, two, and three qubits as of this writing. This reflects a fundamental inefficiency in Clifford RB: the n-qubit Clifford gates at its core have to be compiled into large circuits over the one- and two-qubit gates native to a device. As n grows, the quality of these Clifford gates quickly degrades, making Clifford RB impractical at relatively low n. In this Letter, we propose a direct RB protocol that mostly avoids compiling. Instead, it uses random circuits over the native gates in a device, which are seeded by an initial layer of Clifford-like randomization. We demonstrate this protocol experimentally on two to five qubits using the publicly available ibmqx5. We believe this to be the greatest number of qubits holistically benchmarked, and this was achieved on a freely available device without any special tuning up. Our protocol retains the simplicity and convenient properties of Clifford RB: it estimates an error rate from an exponential decay. But, it can be extended to processors with more qubits—we present simulations on 10+ qubits—and it reports a more directly informative and flexible error rate than the one reported by Clifford RB. Here, we show how to use this flexibility to measure separate error rates for distinct sets of gates, and we use this method to estimate the average error rate of a set of cnot gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

RanCompute: Computational Security in Embedded Devices via Random Input and Output Encodings

An embedded device in an insecure environment is subject to additional security risk through capture and reverse-engineering by a capable adversary. If this device contains a microchip performing sensitive computations, capture of the chip may leak functionality to an adversary. In this paper we propose a novel method in which we randomly encode the input operands and the outputs of a computation, thus not revealing the arithmetic operations being performed. The operations are sequenced in a graph representing the overall application. Once the initialization values are overwritten and lost, the results of these computations are indecipherable by the device performing the calculations as well as by any adversary. The result is transmitted back to a secure server which has stored the initialization values and so can decode the results which appear random to the adversary.

Embedded computing↗

Effect of dehydroepiandrosterone administration before in vitro fertilization on the live birth rate in poor ovarian responders according to the Bologna criteria: A randomised controlled trial

Abstract Objective To evaluate the effect of dehydroepiandrosterone (DHEA) pre‐treatment before in vitro fertilization and embryo transfer (IVF‐ET) on the live birth rate in infertile women with poor ovarian response (POR) defined according to the Bologna criteria. Design A randomized, double‐blind, placebo‐controlled trial. Setting Nine reproductive medical centers in China. Population A total of 821 participants with POR defined according to the Bologna criteria were enrolled in the study between April 2016 and December 2018. Methods Eligible participants were randomly assigned to receive either DHEA ( n = 410) or placebo ( n = 411) treatments for 4–12 weeks prior to IVF‐ET, in a 1:1 ratio. Main outcome measures Live birth rate after the first embryo transfer. Results Thirty‐six (8.8%) of 410 women in the DHEA group and 37 (9.0%) of 411 women in the placebo group had a live birth, with no significant difference observed between groups (relative risk, 0.98, 95% CI, 0.63–1.51; p = 0.911). There were no significant differences in the number of retrieved oocytes, and the rates of clinical pregnancy, pregnancy loss, and cumulative live births between the two groups. Conclusions DHEA administration prior to IVF‐ET had no beneficial effect on the live birth rate relative to placebo in women with POR defined according to the Bologna criteria. Tweetable Abstract No benefit was found in poor ovarian responders who received DHEA administration prior to IVF.

Wang, Ze↗

Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses

Here, this work proposes a framework for large-scale stochastic derivative-free optimization (DFO) by introducing STARS, a trust-region method based on iterative minimization in random subspaces. This framework is both an algorithmic and theoretical extension of a random subspace derivative-free optimization (RSDFO) framework, and an algorithm for stochastic optimization with random models (STORM). Moreover, like RSDFO, STARS achieves scalability by minimizing interpolation models that approximate the objective in low-dimensional affine subspaces, thus significantly reducing per-iteration costs in terms of function evaluations and yielding strong performance on largescale stochastic DFO problems. The user-determined dimension of these subspaces, when the latter are defined, for example, by the columns of so-called Johnson-Lindenstrauss transforms, turns out to be independent of the dimension of the problem. For convergence purposes, inspired by the analyses of RSDFO and STORM, both a particular quality of the subspace and the accuracies of random function estimates and models are required to hold with sufficiently high, but fixed, probabilities. Using martingale theory under the latter assumptions, an almost sure global convergence of STARS to a first-order stationary point is shown, and the expected number of iterations required to reach a desired first-order accuracy is proved to be similar to that of STORM and other stochastic DFO algorithms, up to constants.

97 MATHEMATICS AND COMPUTING↗

The Half Monte Carlo Method: Combining Total Monte Carlo with Nuclear Data Sensitivity Profiles

Both Total Monte Carlo (TMC) and Generalized Linear Least Squares (GLLS) algorithms have been used extensively to perform nuclear uncertainty propagation. Both methods have strengths and weaknesses, for example, the time required to perform TMC limits its attractiveness, while GLLS cannot generate higher order moments of output distributions and also has trouble dealing with nonlinear distributions. This work uses a new method that overcomes many of the aforementioned limitations of TMC and GLLS, while at the same time reasonably reproduces the TMC result. The concept is a simple combination of the two methods i.e., generate the random nuclear data files using the TMC approach, and then propagate the effect on the integral parameters like k{sub eff} using sensitivity coefficients, as opposed to cumbersome neutron transport calculations. Agreement is demonstrated for the Jezebel sphere ICSBEP benchmark. Since the method is part TMC part GLLS, the term Half Monte Method (HMM) will be used.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Masking of a High-Reflectivity Sphere by a Layer with a Random Quasi-Zero Refractive Index

The method of masking of a large-radius sphere made of an arbitrary material by a masking coating with a random quasi-zero refractive index is substantiated theoretically and experimentally. In this method of masking, the sphere is first coated with a mirror layer (e.g., high-reflectivity silver) and then with a masking layer with a thickness much smaller than the radius of the sphere. The fraction of the external radiation intensity bending around the sphere at the points of observation near the surface of the sphere and the extinction cross section of the sphere with the masking coating for points of observation far away from the sphere are calculated. It is shown that extinction cross section Q of the sphere with a masking coating is much smaller than 2D, where D is the geometrical cross section of the sphere; this corresponds to the masking effect for the sphere in the wavelength range of at least 450–1200 nm in the transparency region of the masking coating.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Comparing Methods for Assessing Reliability Uncertainty Based on Pass/Fail Data Collected Over Time

In this paper, we compare statistical methods for analyzing pass/fail data collected over time; some methods are traditional and one (the RADAR or Rationale for Assessing Degradation Arriving at Random) was recently developed. These methods are used to provide uncertainty bounds on reliability. We make observations about the methods' assumptions and properties. Finally, we illustrate the differences between two traditional methods, logistic regression and Weibull failure time analysis, and the RADAR method using a numerical example.

97 MATHEMATICS AND COMPUTING↗

Conservative Estimation of Tail Probabilities from Limited Sample Data

Several sparse-sample uncertainty quantification (UQ) methods are compared for conservative but not overly conservative estimation of small tail probabilities involving responses that lay beyond specified thresholds in the tails of probability distributions. Sixteen very differently shaped distributions (or probability density functions, PDFs) and tail probability magnitudes ranging from 10 -5 to 10 -1 are considered in order for the study to be relevant to a wide range of risk analysis and quantification of margins and uncertainty (QMU) problems. The emphasis of the study is on limited data regimes ranging from N = 2 to 20 samples, reflective of most experimental and some expensive computational situations. Relatively simple sparse-sample UQ methods tested for this regime involve statistical tolerance interval "Equivalent Normal and related "Ensemble of Normals" and "Superdistribution (SD) approaches. (The independently derived SD is effectively equivalent to the Bayesian posterior predictive distribution given the assumptions of the derivation.) The performance of the methods was generally improved for N ≥ 5 samples with a generalized Jackknife resampling technique, which determines a tail probability estimate by averaging estimates from smaller sub-samples. Several quantitative metrics for method conservatism and accuracy of tail probability estimation are used to assess and rank the methods' performance over many random trials for each test PDF and probability magnitude. A variant of Bootstrap resampling was also tried, but did not significantly improve tail probability estimates in most cases. Detailed results are presented from over 100-million tests over the above factors that provide useful granular information on which methods or combination of methods perform best in various areas of the factor space.

97 MATHEMATICS AND COMPUTING↗

Simple effective conservative treatment of uncertainty from sparse samples of random functions

This paper examines the variability of predicted responses when multiple stress-strain curves (reflecting variability from replicate material tests) are propagated through a finite element model of a ductile steel can being slowly crushed. Over 140 response quantities of interest (including displacements, stresses, strains, and calculated measures of material damage) are tracked in the simulations. Each response quantity’s behavior varies according to the particular stress-strain curves used for the materials in the model. We desire to estimate response variability when only a few stress-strain curve samples are available from material testing. Propagation of just a few samples will usually result in significantly underestimated response uncertainty relative to propagation of a much larger population that adequately samples the presiding random-function source. A simple classical statistical method, Tolerance Intervals, is tested for effectively treating sparse stress-strain curve data. The method is found to perform well on the highly nonlinear input-to-output response mappings and non-standard response distributions in the can-crush problem. The results and discussion in this paper support a proposition that the method will apply similarly well for other sparsely sampled random variable or function data, whether from experiments or models. Finally, the simple Tolerance Interval method is also demonstrated to be very economical.

36 MATERIALS SCIENCE↗

Upscaling of Regional Scale Transport Under Transient Conditions: Evaluation of the Multirate Mass Transfer Model

Abstract Regional scale transport models are needed to support the long‐term evaluation of groundwater quality and to develop management strategies aiming to prevent serious groundwater degradation. The purpose of this study is to evaluate the capacity of a previously developed upscaling approach to adequately describe the main solute transport processes, including the capture of late‐time tails under changing boundary conditions. Potential factors that impact the performance of upscaling methods, including temporal variations in mass transfer rates and mass distributions, were investigated. Advective‐dispersive contaminant transport in a 3‐D heterogeneous domain was simulated and used as a reference solution. The equivalent transport under homogeneous flow conditions was then evaluated by applying the multirate mass transfer (MRMT) model. The random walk particle tracking method was used to solve the solute transport for heterogeneous and homogeneous MRMT scenarios under steady state and transient conditions. The results indicate that the MRMT model can capture the tails satisfactorily for plumes transported with ambient steady state flow fields at all studied scales using the same parameters. However, when the boundary conditions change in either local, plume, or regional scale, the mass transfer model calibrated for transport under steady state conditions cannot accurately reproduce the tailings observed for the heterogeneous scenario. The deteriorating impacts of transient boundary conditions on the upscaled model are more significant for regions where the flow fields are dramatically affected, which highlights the poor applicability of the MRMT approach for complex field settings. This finding also has implications for the suitability of other potential upscaling approaches.

Guo, Zhilin↗

Continued Discussion of Failure Mode Modeling and Overall Component Reliability: Is the Data Missing or Censored?

This paper is a continuation of a paper presented at the 13th Probabilistic Safety Assessment and Management Conference, in which a discussion of modeling failure modes of complex components was presented; see Paulos and Smith (2016). The paper demonstrated how the typical method of treating failure modes as being exponential in nature may yield optimistic predictions when estimating how improvements to components will perform in the real world. Instead of relying on textbook methods, it is more accurate to model the failure modes as a race in time; unfortunately, this does not give a closed-form solution. This work uses a simulation to solve for the model of the world, and is compared to the standard methodology of treating the failure modes as exponential random failures. The standard method is shown to have optimistic predictions, which will lead to prediction errors when failure modes were removed or “fixed.” The failure mode methodology presented in the first paper treated the data as being censored when the test stopped. In this paper, we will compare the results from treating the data as both censored and missing, and comparisons will be shown showing which method is more accurate and under what conditions.

97 MATHEMATICS AND COMPUTING↗

Propagation of partially spatially coherent laser beams in instantaneous Kerr media

The propagation of intense, partially spatially coherent laser beams in a medium with instantaneous third-order susceptibility is studied analytically and numerically. For sufficiently high power relative to that required for nonlinear self-focusing, the propagation initially proceeds in two stages. In the first stage, spatial coherence builds up, and in the second stage, the number of speckles reduces. Once the degree of coherence is sufficiently high, whole-beam self-focusing occurs. The beam power is mostly confined within the initial spot radius. Two analytical approaches for describing the evolution of the beam are presented. The method of moments leads to an analytical solution for the rms spot radius that is in excellent agreement with simulations. This method does not require any knowledge of the field statistics beyond the initial conditions and provides no information about the evolution of the individual speckles. The other approach employs a self-similar solution for the second-order coherence function of the field and assumes that the fourth-order coherence function is factorizable and obeys complex circular Gaussian random statistics. The latter method also leads to an analytical expression for the spot radius, but its predictions for the qualitative evolution of the speckles disagree with wave-optics simulations.

lasers↗

Two-Year Mortality After Angioplasty of the Femoro-Popliteal Artery with Uncoated Balloons and Paclitaxel-Coated Balloons—A Pooled Analysis of Four Randomized Controlled Multicenter Trials

Purpose: In view of a recent meta-analysis reporting increased mortality following angioplasty with paclitaxel-coated devices in peripheral arteries, we performed a patient-level 2-year mortality analysis based on pooled original data of four randomized controlled trials (THUNDER, FEMPAC, PACIFIER and CONSEQUENT). Methods and Results: Clinical data of four randomized controlled trial were pooled to assess 2-year mortality following paclitaxel-coated balloon (PCB) angioplasty compared to angioplasty without paclitaxel (control group). A logistic regression model was applied to identify potential predictors of mortality. At two years, 13 of 185 (7.0%) patients had died in the control group and 16/184 (8.7%) in the PBC group, p = 0.55. Kaplan–Meier analysis revealed no significant difference from all-cause death at 2 years (log rank p = 0.54). Causes of death were well balanced between the groups with no pattern or trend in favour of any specific causes in the PBC group. Logistic regression revealed that treatment groups (controls or PBC) were not a predictor of 2-year mortality. The only predictor for mortality was patient age ≥ 75 years. The delivered paclitaxel doses per patient were not significantly different in patients that died and those who did not die during the 24-month follow-up (5.300 ± 4.224 μg vs. 6.248 ± 4.629 μg, p = 0.433). Conclusions: Based on original patient-level data of four pooled randomized controlled trials, we found no increase in 2-year mortality in patients treated with PCB compared to control patients treated with uncoated balloons. Causes of death were well balanced between PCB and control patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

W$^+$W$^-$ boson pair production in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A measurement of the W+W- boson pair production cross section in proton-proton collisions at s=13 TeV is presented. The data used in this study are collected with the CMS detector at the CERN LHC and correspond to an integrated luminosity of 35.9 fb-1. The W+W- candidate events are selected by requiring two oppositely charged leptons (electrons or muons). Two methods for reducing background contributions are employed. In the first one, a sequence of requirements on kinematic quantities is applied allowing a measurement of the total production cross section, 117.6±6.8 pb, which agrees well with the theoretical prediction. Fiducial cross sections are also reported for events with zero or one jet, and the change in the zero-jet fiducial cross section with the jet transverse momentum threshold is measured. Normalized differential cross sections are reported within the fiducial region. A second method for suppressing background contributions employs two random forest classifiers. The analysis based on this method includes a measurement of the total production cross section and also a measurement of the normalized jet multiplicity distribution in W+W- events. Finally, a dilepton invariant mass distribution is used to probe for physics beyond the standard model in the context of an effective field theory, and constraints on the presence of dimension-6 operators are derived.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗