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We have measured the cross section of the $^{83}$Rb(p,$\gamma)^{84}$Sr radiative capture reaction in inverse kinematics using a radioactive beam of $^{83}$Rb at incident energies of 2.4 and $2.7 A$ MeV. Prior to the radioactive beam measurement, the $^{84}$Kr(p,$\gamma)^{85}$Rb radiative capture reaction was measured in inverse kinematics using a stable beam of $^{84}$Kr at an incident energy of $2.7 A$ MeV. The effective relative kinetic energies of these measurements lie within the relevant energy window for the $\gamma$ process in supernovae. The central values of the measured partial cross sections of both reactions were found to be $0.17-0.42$ times the predictions of statistical model calculations. Assuming the predicted cross section at other energies is reduced by the same factor leads to a slightly higher calculated abundance of the $p$ nucleus $^{84}$Sr, caused by the reduced rate of the $^{84}$Sr($\gamma$,p)$^{83}$Rb reaction derived from the present measurement., Comment: 11 pages, 11 figures. arXiv admin note: text overlap with arXiv:2109.06775

Magnetic Resonance Fingerprinting (MRF) is an efficient quantitative MRI technique that can extract important tissue and system parameters such as T1, T2, B0, and B1 from a single scan. This property also makes it attractive for retrospectively synthesizing contrast-weighted images. In general, contrast-weighted images like T1-weighted, T2-weighted, etc., can be synthesized directly from parameter maps through spin-dynamics simulation (i.e., Bloch or Extended Phase Graph models). However, these approaches often exhibit artifacts due to imperfections in the mapping, the sequence modeling, and the data acquisition. Here we propose a supervised learning-based method that directly synthesizes contrast-weighted images from the MRF data without going through the quantitative mapping and spin-dynamics simulation. To implement our direct contrast synthesis (DCS) method, we deploy a conditional Generative Adversarial Network (GAN) framework and propose a multi-branch U-Net as the generator. The input MRF data are used to directly synthesize T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) images through supervised training on paired MRF and target spin echo-based contrast-weighted scans. In-vivo experiments demonstrate excellent image quality compared to simulation-based contrast synthesis and previous DCS methods, both visually as well as by quantitative metrics. We also demonstrate cases where our trained model is able to mitigate in-flow and spiral off-resonance artifacts that are typically seen in MRF reconstructions and thus more faithfully represent conventional spin echo-based contrast-weighted images., Comment: 19 pages, 8 figures

A High Rigidity Spectrometer (HRS) has been designed for experiments at the Facility for Rare-Isotope Beams (FRIB) at Michigan State University (MSU). The HRS will allow experiments to be performed with the most exotic neutron-rich isotopes at high beam energies ($\gtrsim$100MeV/u). The HRS consists of an analysis beamline called the High-Transmission Beamline (HTBL) and the spectrometer proper called the Spectrometer Section. The maximum magnetic rigidity of the HRS is 8Tm, which corresponds to the rigidities at which rare-isotope beams are optimally produced at FRIB. The resolving power, angular acceptance, and momentum acceptance are set to match the anticipated scientific program. An ion-optical design developed for the HRS is described in detail, along with the specifications of the associated magnet and detector systems., Comment: 24 pages, 26 figures, 6 tables

We have performed the first direct measurement of the 83Rb(p,g) radiative capture reaction cross section in inverse kinematics using a radioactive beam of 83Rb at incident energies of 2.4 and 2.7 A MeV. The measured cross section at an effective relative kinetic energy of Ecm = 2.393 MeV, which lies within the relevant energy window for core collapse supernovae, is smaller than the prediction of statistical model calculations. This leads to the abundance of 84Sr produced in the astrophysical p process being higher than previously calculated. Moreover, the discrepancy of the present data with theoretical predictions indicates that further experimental investigation of p-process reactions involving unstable projectiles is clearly warranted., Comment: 6 pages, 4 figures, published in Physical Review Letters

We introduce blueprint separable convolutions (BSConv) as highly efficient building blocks for CNNs. They are motivated by quantitative analyses of kernel properties from trained models, which show the dominance of correlations along the depth axis. Based on our findings, we formulate a theoretical foundation from which we derive efficient implementations using only standard layers. Moreover, our approach provides a thorough theoretical derivation, interpretation, and justification for the application of depthwise separable convolutions (DSCs) in general, which have become the basis of many modern network architectures. Ultimately, we reveal that DSC-based architectures such as MobileNets implicitly rely on cross-kernel correlations, while our BSConv formulation is based on intra-kernel correlations and thus allows for a more efficient separation of regular convolutions. Extensive experiments on large-scale and fine-grained classification datasets show that BSConvs clearly and consistently improve MobileNets and other DSC-based architectures without introducing any further complexity. For fine-grained datasets, we achieve an improvement of up to 13.7 percentage points. In addition, if used as drop-in replacement for standard architectures such as ResNets, BSConv variants also outperform their vanilla counterparts by up to 9.5 percentage points on ImageNet. Code and models are available under https://github.com/zeiss-microscopy/BSConv., Comment: Published at CVPR 2020. Code and models are available under https://github.com/zeiss-microscopy/BSConv

NASA is supporting the development of Electrified Aircraft Propulsion (EAP) technology due to its potential to reduce aircraft fuel burn, emissions, and noise as well as improving safety and performance. One focus of this research is the electrification of conventional turbomachinery propulsion systems, which offers ways to improve the performance and operability of turbine-engine powered aircraft through the addition of electro-mechanical systems. These hybrid-electric turbine engines provide additional actuation and energy management control opportunities for improving stability and transient response behavior. This paper summarizes the results of a Hardware-in-the-Loop (HIL) test performed at the NASA Electric Aircraft Testbed (NEAT) during the summer of 2022. The test demonstrates the feasibility and performance of an advanced energy management control strategy by integrating a simulated turbofan engine with scaled electro-mechanical hardware. A full-scale real-time reference model of a geared turbofan was run alongside a scaled electro-mechanical system representing the electrified turbofan components operating at a megawatt-scale power level. The model was interfaced with the hardware through a novel closed-loop control and scaling algorithm that emulated the dynamic speed and torque response of the turbofan shafts. The control strategy was implemented on the electrical machines connected to the emulated turbomachinery shafts. The results from the testbed are compared against simulations that predict the testbed and geared turbofan model operation. The energy management control strategy successfully changed the operating point of the engine model and improved its stability during throttle transients. These results also demonstrate the success of the novel closed loop control and scaling approach for emulating turbomachinery and elevate the Technology Readiness Level (TRL) of the energy management control strategy.

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

In support of aviation fuel burn and emission reduction goals, NASA is pursuing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP). Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes addressing challenges related to propulsion controls, which will be vital for ensuring efficient coordinated operation of EAP subsystems. This paper presents results from real-time hardware-in-theloop (HIL) testing of a control design for a single aisle partially-turboelectric aircraft propulsion concept conducted at the NASA Electric Aircraft Testbed (NEAT) facility. The control system under test is designed for a propulsion concept consisting of two wing-mounted turbofan engines that produce thrust and generate electrical power to drive a boundary layer ingesting tailfan propulsor via an electrical motor. An integrated control strategy is applied to ensure coordinated operation of the turbofan and tailfan subsystems during steady-state and transient operation throughout the flight envelope. The NEAT test of this integrated control design consists of a partially HIL, partially simulated configuration. A subscale representation of the electrical system design is implemented in hardware and mechanically coupled to electric machines that emulate turbomachinery and propulsor shaft dynamics. The hardware configuration is then operated under the control of a real-time computer application that runs a simulation of the propulsion system and the developed control logic. The NEAT facility test campaign includes a series of experiments that subject the control design to throttle transients conducted throughout the flight envelope and full-flight mission profiles. Testing under simulated performance degradation is also conducted to evaluate control design robustness. This includes constant and abrupt changes in degradation levels. Results from the HIL test are presented and shown to be in good agreement with pretest simulation predictions demonstrating the efficacy of the integrated control design approach.

We show that, by monitoring the free carrier reservoir in a GaAs-based quantum well microcavity under nonresonant pulsed optical pumping, lasing supported by a fermionic reservoir (photon lasing) can be distinguished from lasing supported by a reservoir of bosons (polariton lasing). Carrier densities are probed by measuring the photocurrent between lateral contacts deposited directly on the quantum wells of a microcavity that are partially exposed by wet chemical etching. We identify two clear thresholds in the input-output characteristic of the photoluminescence signal which can be attributed to polariton and photon lasing, respectively. The power dependence of the probed photocurrent shows a distinct kink at the threshold power for photon lasing due to an increased radiative recombination of free carriers as stimulated emission into the cavity mode sets in. At the polariton lasing threshold, on the other hand, the nonlinear increase of the luminescence is caused by stimulated scattering of exciton polaritons to the ground state which do not contribute directly to the photocurrent., Comment: Copyright 2016 American Physical Society DOI: https://doi.org/10.1103/PhysRevLett.117.127401

Security-critical system requirements are increasingly enforced through mandatory access control systems. These systems are controlled by security policies, highly sensitive system components, which emphasizes the paramount importance of formally verified security properties regarding policy correctness. For the class of safety-properties, addressing potential dynamic right proliferation, a number of known and tested formal analysis methods and tools already exist. Unfortunately, these methods need to be redesigned from scratch for each particular policy from a broad range of different application domains. In this paper, we seek to mitigate this problem by proposing a uniform formal framework, tailorable to a safety analysis algorithm for a specific application domain. We present a practical workflow, guided by model-based knowledge, that is capable of producing a meaningful formal safety definition along with an algorithm to heuristically analyze that safety. Our method is demonstrated based on security policies for the SELinux operating system. Keywords: Security engineering, security policies, access control systems, access control models, safety, heuristic analysis, SELinux.

Microcavity exciton polaritons are promising candidates to build a new generation of highly nonlinear and integrated optoelectronic devices. Such devices range from novel coherent light emitters to reconfigurable potential landscapes for electro-optical polariton-lattice based quantum simulators as well as building blocks of optical logic architectures. Especially for the latter, the strongly interacting nature of the light-matter hybrid particles has been used to facilitate fast and efficient switching of light by light, something which is very hard to achieve with weakly interacting photons. We demonstrate here that polariton transistor switches can be fully integrated in electro-optical schemes by implementing a one-dimensional polariton channel which is operated by an electrical gate rather than by a control laser beam. The operation of the device, which is the polariton equivalent to a field-effect transistor, relies on combining electro-optical potential landscape engineering with local exciton ionization to control the scattering dynamics underneath the gate. We furthermore demonstrate that our device has a region of negative differential resistance and features a completely new way to create bistable behavior., Comment: 15 Pages, 8 Figures

When the coupling between light and matter becomes comparable to the energy gap between different excited states they hybridize, leading to the appearance of a rich and complex phenomenology which attracted remarkable interest in recent years. While the mixing between states with different number of excitations, so-called ultrastrong coupling regime, has been observed in various implementations, the effect of the hybridization between different single excitation states, referred to as very strong coupling regime, has remained elusive. In semiconductor quantum wells such a regime is predicted to manifest as a photon-mediated electron-hole coupling leading to different excitonic wavefunctions for the two polaritonic branches when the ratio of the coupling strength to exciton binding energy approaches unity. Here, we verify experimentally the existence of this regime in magneto-optical measurements on a microcavity with 28 GaAs quantum wells, showing that the average electron-hole separation of the upper polariton is significantly increased compared to the bare quantum well exciton Bohr radius. This manifests in a diamagnetic shift around zero detuning that exceeds the shift of the lower polariton by one order of magnitude and the bare quantum well exciton diamagnetic shift by a factor of two. The lower polariton exhibits a diamagnetic shift smaller than expected from the coupling of a rigid exciton to the cavity mode which suggests more tightly bound electron-hole pairs than in the bare quantum well.

The systematic study of fission fragment yields under different initial conditions provides a valuable experimental benchmark for fission models that aim to understand this complex decay channel and to predict reaction product yields. Inverse kinematics coupled to the use of a high-resolution spectrometer is shown to be a powerful tool to identify and measure the inclusive isotopic yields of fission fragments. In-flight fusion fission was used to produce secondary beams of neutron-rich isotopes in the collision of a 238U beam at 24 MeV/u with 9Be and 12C targets at GANIL using the LISE3 fragment-separator. Unique A,Z,q identification of fission products was attained with the dE-TKE-Brho-ToF measurement technique. Mass, and atomic number distributions are reported for the two reactions that show the importance of different reaction mechanisms for these two targets., Comment: 14 pages, 10 figures, 4 tables

We propose Impatient Deep Neural Networks (DNNs) which deal with dynamic time budgets during application. They allow for individual budgets given a priori for each test example and for anytime prediction, i.e., a possible interruption at multiple stages during inference while still providing output estimates. Our approach can therefore tackle the computational costs and energy demands of DNNs in an adaptive manner, a property essential for real-time applications. Our Impatient DNNs are based on a new general framework of learning dynamic budget predictors using risk minimization, which can be applied to current DNN architectures by adding early prediction and additional loss layers. A key aspect of our method is that all of the intermediate predictors are learned jointly. In experiments, we evaluate our approach for different budget distributions, architectures, and datasets. Our results show a significant gain in expected accuracy compared to common baselines., Comment: British Machine Vision Conference (BMVC) 2016

X-ray bursts are thermonuclear flashes on the surface of accreting neutron stars and reliable burst models are needed to interpret observations in terms of properties of the neutron star and the binary system. We investigate the dependence of X-ray burst models on uncertainties in (p,$\gamma$), ($\alpha$,$\gamma$), and ($\alpha$,p) nuclear reaction rates using fully self-consistent burst models that account for the feedbacks between changes in nuclear energy generation and changes in astrophysical conditions. A two-step approach first identified sensitive nuclear reaction rates in a single-zone model with ignition conditions chosen to match calculations with a state-of-the-art 1D multi-zone model based on the {\Kepler} stellar evolution code. All relevant reaction rates on neutron deficient isotopes up to mass 106 were individually varied by a factor of 100 up and down. Calculations of the 84 highest impact reaction rate changes were then repeated in the 1D multi-zone model. We find a number of uncertain reaction rates that affect predictions of light curves and burst ashes significantly. The results provide insights into the nuclear processes that shape X-ray burst observables and guidance for future nuclear physics work to reduce nuclear uncertainties in X-ray burst models., Comment: 24 pages, 13 figures, 4 tables, submitted

We study the influence of spatial confinement on the second-order temporal coherence of the emission from a semiconductor microcavity in the strong coupling regime. The confinement, provided by etched micropillars, has a favorable impact on the temporal coherence of solid state quasi-condensates that evolve in our device above threshold. By fitting the experimental data with a microscopic quantum theory based on a quantum jump approach, we scrutinize the influence of pump power and confinement and find that phonon-mediated transitions are enhanced in the case of a confined structure, in which the modes split into a discrete set. By increasing the pump power beyond the condensation threshold, temporal coherence significantly improves in devices with increased spatial confinement, as revealed in the transition from thermal to coherent statistics of the emitted light.