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At least 631 records · Page 35

Demonstration of Algorithmic Quantum Speedup for an Abelian Hidden Subgroup Problem

Simon’s problem is to find a hidden period (a bitstring) encoded into an unknown 2-to-1 function. It is one of the earliest problems for which an exponential quantum speedup was proven for ideal, noiseless quantum computers, albeit in the oracle model. Here, using two different 127-qubit IBM Quantum superconducting processors, we demonstrate an algorithmic quantum speedup for a variant of Simon’s problem where the hidden period has a restricted Hamming weight 𝑤. For sufficiently small values of 𝑤 and for circuits involving up to 58 qubits, we demonstrate an exponential speedup, albeit of a lower quality than the speedup predicted for the noiseless algorithm. The speedup exponent and the range of 𝑤 values for which an exponential speedup exists are significantly enhanced when the computation is protected by dynamical decoupling. Further enhancement is achieved with measurement error mitigation. This case constitutes a demonstration of a bona fide quantum advantage for an Abelian hidden subgroup problem.

computation↗

3D-printed sheet jet for stable megahertz liquid sample delivery at X-ray free-electron lasers

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Low-Power and In Situ Annealing Mitigation Technique for Fast Neutrons Irradiation of Integrated Temperature Sensing Diodes

High doses of fast neutrons is detrimental to the performance of most common solid-state devices such as diodes and transistors. The ionizing effect is observed in particular for diodes used as simple integrated temperature sensors, or thermo-diodes, when their junction voltage is measured at constant current bias. In this work, we present a low-power and in situ mitigation technique based on Silicon-on-Insulator (SOI) micro-hot-plates to recover thermo-diodes. The basic operating principle consists in annealing the temperature-sensitive diodes integrated on the membrane during or after their irradiation in order to restore similar sensing characteristics over time. We measured thermo-diodes integrated to micro-hot-plates during their irradiation by fast neutrons (23 MeV peak) with total doses about 2.97±0.08 kGy. The membrane annealing is taking place at 450 deg. C using 40 mW of electrical power. Thanks to the annealing, the diode keeps a total measurement error below 0.5 deg. C. In this harsh radiation environment and beside the good tolerance of the thermo-diodes and the membrane materials to the total ionizing dose, the thermo-diode located on the heating membrane keeps a constant sensitivity. The demonstrated resistance of micro-hot-plates and the integrated thermo-diodes to fast neutron radiations can extend their use in nuclear plants and for radiation detectors. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Determining Series Resistance for Equivalent Circuit Models of a PV Module

Literature describes various methods for determining a series resistance for a photovoltaic device from measured IV curves. We investigate use of these techniques to estimate the series resistance parameter for a single diode equivalent circuit model. With simulated IV curves we demonstrate that the series resistance values obtained by these techniques differ systematically from the known series resistance parameter values used to generate the curves, indicating that these methods are not suitable for determining the series resistance parameter for the single diode model equation. Furthermore, we present an alternative method to determine the series resistance parameter jointly with the other parameters for the single diode model equation, and demonstrate the accuracy and reliability of this technique in the presence of measurement errors.

42 ENGINEERING↗

Short-Term Distribution System State Forecast Based on Optimal Synchrophasor Sensor Placement and Extreme Learning Machine

This paper proposes an approach for distribution system state forecasting, which aims to provide an accurate and high speed state forecasting with an optimal synchrophasor sensor placement (OSSP) based state estimator and an extreme learning machine (ELM) based forecaster. Specifically, considering the sensor installation cost and measurement error, an OSSP algorithm is proposed to reduce the number of synchrophasor sensor and keep the whole distribution system numerically and topologically observable. Then, the weighted least square (WLS) based system state estimator is used to produce the training data for the proposed forecaster. Traditionally, the artificial neural network (ANN) and support vector regression (SVR) are widely used in forecasting due to their nonlinear modeling capabilities. However, the ANN contains heavy computation load and the best parameters for SVR are difficult to obtain. In this paper, the ELM, which overcomes these drawbacks, is used to forecast the future system states with the historical system states. The proposed approach is effective and accurate based on the testing results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep Convolutional Neural Networks for Distribution System Fault Classification

Faults happen very frequently in distribution systems. Identifying fault types and phases are of critical importance for outage management, fault location, and service restoration. However, this task becomes very challenging due to measurement scarcity in distribution systems. This paper is among the first few that applies deep learning techniques in distribution system fault classification. Specifically, a sequential Convolutional Neural Network(CNN)-based classifier is developed to identify fault buses and phases. The input to the CNN is the steady-state voltage and current data measured at substations. The fault identification is modeled as a multi-label classification problem. Training data under various fault scenarios are obtained in OpenDSS and Gaussian noises are added to mimic measurement errors. A case study in IEEE 13-feeder test system is conducted with single and multiple bus faults scenarios. Numerical results demonstrate the high accuracy and fast computation of the proposed deep CNN-based fault classification.

Tian, Guanyu↗

Self-Reference Procedure to Reduce Uncertainty in Module Calibration

This paper presents a composite measurement approach that capitalizes on complimentary strengths of 3 different test beds to significantly reduce uncertainty in I-V parameters for secondary module calibration. This approach addresses PV manufacturers' need for reduced uncertainty in the calibration modules that provide the basis for their module power ratings. This new method enables NREL to reduce uncertainty for secondary module calibration in commercial c-Si modules from +/-3.2% to +/-0.7% for I SC and from +/-3.3% to +/-1.1% for P MAX . This new module self-reference, or MSR procedure is based on the sensitivity of module voltage to temperature plus the uniformity of outdoor sunlight. By calibrating module V OC in thermal equilibrium on a flash simulator we provide an accurate gauge of junction temperature for subsequent measurements. By calibrating I SC outdoors in natural sunlight we enable the module to serve as its own reference device in setting the intensity of a continuous simulator, effectively eliminating the impact of spatial non-uniformity and spectral mismatch on the I-V measurement. These procedures significantly reduce measurement errors due to temperature uncertainty, spatial non-uniformity, and spectral mismatch.

14 SOLAR ENERGY↗

Mitigating Communication Delays in Remotely Connected Hardware-in-the-loop Experiments

Here, this paper introduces a potential approach for mitigating the effects of communication delays between multiple, closed-loop hardware-in-the-loop experiments which are virtually connected, yet physically separated. The method consists of an analytical method for the compensation of communication delays, along with the supporting computational and communication infrastructure. The control design leverages tools for the design of observers for the compensation of measurement errors in systems with time-varying delays. The proposed methodology is validated through computer simulation and hardware experimentation connecting hardware-in-the-loop experiments conducted between laboratories separated by a distance of over 100 km.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Time-Domain Protection Approach for AC Transmission Systems With Grid-Forming Resources

Ac transmission protection must reliably detect, classify, and locate short-circuit faults from voltage and current measurements. At present, these functionalities, which have been classically engineered using phasors approaches, are being challenged by the dynamic behavior and fault-current limits of converter-based generation. This paper tackles these challenges by engineering a time-domain protection approach that leverages the classical Bergeron model in a new manner. Low- and high-impedance faults are detected and classified by ascertaining how well line voltage and current measurements match the Bergeron equations. Faults are located by posing a novel one-variable optimization problem, whereas voltage and current waveforms at the fault location are estimated by unveiling rigorous relationships. The proposed elements are secure against external faults, measurement errors, and variation of line parameters and sampling time. Furthermore, these advances are tested via electromagnetic transient simulations and are significant to satisfy IEEE and North American Electric Reliability Corporation requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Effect of 1–10-MeV Neutrons on the JESD89 Test Standard

Here, the JESD89 test standard defines how terrestrial neutron testing is conducted [1] . The test standard covers a number of different types of radiation used for testing, including protons, neutrons, and alphas, and different types of testing, including life testing and accelerated testing. Broad-spectrum neutron testing is the most common type of accelerated radiation testing for the terrestrial radiation environment. Unlike most test standards, the JESD89 defines the minimum energy for determining the cumulative fluence for the deployed and test environment. Currently, the minimum energy is set at 10 MeV. As the test standard is currently being rewritten, changing the minimum energy to 1 MeV is being explored, because it is believed that the onset to neutron-induced single-event effects (SEEs) is less than 10 MeV. There are three separate problems with lowering the minimum energy: determining whether electronics have a sensitivity to neutron-induced SEEs below 10 MeV, determining whether the test spectra match the terrestrial environment in the 1–10-MeV range, and the measurement error caused by not including the fluence from 1 to 10 MeV. In this paper, we present information on these factors and whether the minimum energy should be lowered to 1 MeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Co-Pyrolysis of Chicken and Cow Manure

Conventional pyrolysis is a relatively simple way for biochar production; however, a single biomass feedstock approach is not promising for the development of multiple properties of biochar used in various applications. Here, this study provides a detailed comparison in terms of pyrolysis kinetics between the cow manure and chicken manure, in addition to the co-pyrolysis by mixing the two livestock at different ratios. Eight different heating rates were tested, 5–40 °C/min with 5 °C/min step, on both livestock using the nitrogen as a gas agent with a flowrate of 50 ml/min. The initial results show that for the slow heating rates, 5 °C/min, the thermal degradation of the cow manure is different compared to that obtained from chicken manure. For the cow manure, the first peak, associated with hemicellulose decomposition, is higher than the second peak, associated with cellulose decomposition, which is the other way around for chicken manure. At 5 °C /min, the hemicellulose decomposition took place at 250 °C and 300 °C for the chicken manure and cow manure, respectively. The cellulose decomposition was started at 300 °C for chicken manure and 470 °C for cow manure. The lowest heat rate was selected for the co-pyrolysis case study to allow a quasi-equilibrium state to avoid measurement errors and heat transfer limitation in terms of thermal lag. Co-pyrolysis is studied with different blend ratios between the chicken and cow manure, where the 40% cow manure shows a positive result in terms of keeping an exothermic reaction over the co-pyrolysis process.

09 BIOMASS FUELS↗

Iterative image-domain decomposition for dual-energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

TU-F-18A-02: Iterative Image-Domain Decomposition for Dual-Energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

WE-A-17A-09: Exploiting Electromagnetic Technologies for Real-Time Seed Drop Position Validation in Permanent Implant Brachytherapy

Purpose: To report on preliminary results validating the performance of a specially designed LDR brachytherapy needle prototype possessing both electromagnetic (EM) tracking and seed drop detection abilities. Methods: An EM hollow needle prototype has been designed and constructed in collaboration with research partner Philips Healthcare. The needle possesses conventional 3D tracking capabilities, along with a novel seed drop detection mechanism exploiting local changes of electromagnetic properties generated by the passage of seeds in the needle's embedded sensor coils. These two capabilities are exploited by proprietary engineering and signal processing techniques to generate seed drop position estimates in real-time treatment delivery. The electromagnetic tracking system (EMTS) used for the experiment is the NDI Aurora Planar Field Generator. The experiment consisted of dropping a total of 35 seeds in a prismatic agarose phantom, and comparing the 3D seed drop positions of the EMTS to those obtained by an image analysis of subsequent micro-CT scans. Drop position error computations and statistical analysis were performed after a 3D registration of the two seed distributions. Results: Of the 35 seeds dropped in the phantom, 32 were properly detected by the needle prototype. Absolute drop position errors among the detected seeds ranged from 0.5 to 4.8 mm with mean and standard deviation values of 1.6 and 0.9 mm, respectively. Error measurements also include undesirable and uncontrollable effects such as seed motion upon deposition. The true accuracy performance of the needle prototype is therefore underestimated. Conclusion: This preliminary study demonstrates the potential benefits of EM technologies in detecting the passage of seeds in a hollow needle as a means of generating drop position estimates in real-time treatment delivery. Such tools could therefore represent a potentially interesting addition to existing brachytherapy protocols for rapid dosimetry validation. Equipments and fundings for this project were provided by Philips Medical.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Neutron lifetime measurement on setups with gravitational trap

Currently, the best accuracy of neutron lifetime measurements has been attained in the experiment with a gravitational trap for ultracold neutrons (UCNs), performed at the Petersburg Nuclear Physics Institute (PNPI); the measured lifetime was 878.5 ± 0.8 s. A new setup with a big gravitational trap has been designed to continue the methods and approaches used in the previous experiment. It is planned to reduce the measurement error to 0.2 s, i.e., improve the existing accuracy by a factor of 4. The spectrometer was designed at PNPI and installed on the PF2/MAM beam at the Institute Laue–Langevin. Test experiments have been performed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Thermodynamic Functions and Electrical Resistivity of Fluid Lead in the Metal–Nonmetal Transition Range

A dynamic method is used to measure the thermodynamic functions and the electrical resistivity of fluid lead for a wide range of specific volume and pressure. The measurements errors have been reduced to a level comparable to those of stationary methods. It is found that the transition of the fluid from the metallic state to a nonmetallic state occurs when its specific volume increases 2.7 times relative to the normal value. In each individual experiment the transition occurred at almost a constant pressure, and was detected by the change in sign of the isochoric temperature coefficient of resistance determined for the entire series of the experiments. In the pressure range of 0.6–5 GPa, the specific volume at which the metal–nonmetal transition occurs is found to be independent of pressure, and therefore, the transition line is close to an isochore. For the whole range of states of fluid lead investigated here, the speed of sound and the Grüneisen coefficient have been determined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗