High-fidelity Measurements Research Articles

Dispersive heterodyne cavity ring-down spectroscopy exploiting eigenmode frequencies for high-fidelity measurements.

Measuring low light absorption with combined uncertainty <1 per mil (‰) is crucial for many applications. Popular cavity ring-down spectroscopy can provide ultrahigh precision, below 0.01‰, but its accuracy is often worse than 5‰ due to inaccuracies in light intensity measurements. To eliminate this problem, we exploit optical frequency information carried by the ring-down cavity electromagnetic field. Instead of measuring only the decaying light intensity, we perform heterodyne detection of ring-downs followed by Fourier analysis to provide exact frequencies of optical cavity modes and a high-fidelity dispersive spectrum of a gas sample from them. We demonstrate the sub-per-mil accuracy of our method, confirmed by the best ab initio results for CO line intensity and for HD line shape, and the long-term repeatability of our dispersion measurements at 10-4 level. We see potential for our approach in atmospheric remote sensing, isotope ratio metrology, thermometry, and establishment of primary gas standards.

Photometrically optimized event-based stereo 3D measurements.

Event cameras only report changes in brightness when thresholds in individual pixels relative to previous levels are crossed. They output sparse streams of events that quantify these changes spatially and temporally. We have developed a measurement system using two event cameras in a stereo configuration with a specialized projector for 3D measurements of static objects. We show that optimal contrast in the structured illumination yields high-fidelity measurements, reaching 3D root-mean-square deviations of 0.6 mm (≈0.3% of the measurement volume's diagonal). This work opens up the possibility of precise event-based, highly dynamic 4D measurements in the near future.

Fast and high-fidelity dispersive readout of a spin qubit with squeezed microwave and resonator nonlinearity

Fast and high-fidelity qubit measurement is essential for quantum error correction in universal quantum computing. This study examines dispersive measurement of a spin in a semiconductor double quantum dot using a nonlinear microwave resonator. By employing displaced squeezed vacuum states, we achieve rapid, high-fidelity readout for silicon spin qubits. Our results show that modest squeezing and mild nonlinearity significantly enhance the signal-to-noise ratio (SNR) and the fidelity of qubit-state readout. By optimally adjusting the phases of squeezing and nonlinearity, we reduce readout time to sub-microsecond ranges. With current technology parameters (κ ≈ 2χs, χs/(2π) ≈ 0.15 MHz), utilizing a displaced squeezed vacuum state with 30 photons and a modest squeezing parameter r ≈ 0.6, along with a nonlinear microwave resonator charactered by a strength of λ ≈ − 1.2χs, a readout fidelity of 98% can be attained within a readout time of around 0.6 μs.

Pulmonary Impedance and Wave Reflections in Adults with Mitral Stenosis: Immediate and Follow-Up Effects of Balloon Valvuloplasty

Abstract Purpose We compared adults with mitral stenosis (MS) to 8 controls (CONT) to see how pulmonary impedance and wave reflections differ at baseline and after balloon valvuloplasty. Methods We separated the MS patients into groups according to mean pulmonary artery pressure: moderate (MOD; ≤ 26 mmHg, n = 21) and high (HIGH; &gt; 26 mmHg, n = 33). We made baseline high-fidelity measurements in all patients, in the MS groups after vasodilation with nitroprusside, immediately and 4 months after balloon valvuloplasty. Results Comparing MOD vs CONT, using the Kruskal-Wallis test with Bonferroni correction, reveals evidence for higher baseline input resistance (R) (489 vs 205 dyne-sec/cm5, P = 0.07); first harmonic of impedance modulus (Z1) (97.3 vs 27.6 dyne-sec/cm5, P = 0.01); first zero crossing of impedance phase angle (F0) (4.49° vs 2.19°, P = 0.02) but no difference in wave reflection index (Pb/Pf). Baseline HIGH vs CONT comparisons reveal stronger evidence and larger differences than MOD for R (995 vs 205, P &lt; 0.001); Z1 (151 vs 27.6, P &lt; 0.001); F0 (5.25 vs 2.19, P &lt; 0.001); as well as Pb/Pf (0.69 vs 0.42, P &lt; 0.001). Responses to nitroprusside and valvuloplasty are also greater in the HIGH than MOD, but the HIGH parameters still differ from the CONT. Four months after valvuloplasty there is evidence for reverse remodeling in both groups. Further analyses reveal that sinus rhythm and younger age are potentially important factors for remodeling. Conclusion MS causes alterations in pulmonary hemodynamics that differ according to pressure levels. These changes are only partially reversed immediately after valvuloplasty. There is evidence for reverse remodeling 4 months afterwards.

Enhancing Dispersive Readout of Superconducting Qubits through Dynamic Control of the Dispersive Shift: Experiment and Theory

The performance of a wide range of quantum computing algorithms and protocols depends critically on the fidelity and speed of the employed qubit readout. Examples include gate sequences benefiting from midcircuit real-time measurement-based feedback, such as qubit initialization, entanglement generation, teleportation, and, perhaps most importantly, quantum error correction. A prominent and widely used readout approach is based on the dispersive interaction of a superconducting qubit strongly coupled to a large-bandwidth readout resonator, frequently combined with a dedicated or shared Purcell filter protecting qubits from decay. By dynamically reducing the qubit-resonator detuning and thus increasing the dispersive shift, we demonstrate a beyond-state-of-the-art two-state-readout error of only 0.25% in 100-ns integration time. Maintaining low-readout-drive strength, we nearly quadruple the signal-to-noise ratio of the readout by doubling the readout-mode line width, which we quantify by considering the hybridization of the readout resonator and its dedicated Purcell filter. We find excellent agreement between our experimental data and our theoretical model. The presented results are expected to further boost the performance of new and existing algorithms and protocols critically depending on high-fidelity fast midcircuit measurements. Published by the American Physical Society 2024

Modeling detector response curves for a high-fidelity uranium measurement for use in simulations

Enrichment measurements using identiFinder2 (‘HM5’) detector are performed on two Material Testing Reactor (MTR) fuel assemblies - one with low-enriched uranium plates (LEU) and another with high-enriched uranium plates (HEU). The effectiveness of International Atomic Energy Agency (IAEA) inspection plans for verifying nuclear material strata, in the form of defect detection probability (DP), is evaluated using statistical models. These models use defect identification probability (IP) curves, which represent the probability that a measured item is identified as a defective item. This paper describes a new modeling procedure that converts the experimental measurements into IP curves and employing such experimentally derived IP curves within DP simulations will better represent the experimental conditions like material type, material distribution, and plate configuration. A comparison of experimental performance curves to a simple statistical model (Gaussian, 15% relative standard deviation RSD) shows that the DP results from the modeled response of HM5 measurements better captures the experimental conditions. This result highlights a need for further research into experimental error variables test model development as use of a simple model does not adequately capture true performance in either the LEU or HEU cases.

Measuring Black Hole Light Echoes with Very Long Baseline Interferometry

Light passing near a black hole can follow multiple paths from an emission source to an observer due to strong gravitational lensing. Photons following different paths take different amounts of time to reach the observer, which produces an echo signature in the image. The characteristic echo delay is determined primarily by the mass of the black hole, but it is also influenced by the black hole spin and inclination to the observer. In the Kerr geometry, echo images are demagnified, rotated, and sheared copies of the direct image and lie within a restricted region of the image. Echo images have exponentially suppressed flux, and temporal correlations within the flow make it challenging to directly detect light echoes from the total light curve. In this Letter, we propose a novel method to search for light echoes by correlating the total light curve with the interferometric signal at high spatial frequencies, which is a proxy for indirect emission. We explore the viability of our method using numerical general relativistic magnetohydrodynamic simulations of a near-face-on accretion system scaled to M87-like parameters. We demonstrate that our method can be used to directly infer the echo delay period in simulated data. An echo detection would be clear evidence that we have captured photons that have circled the black hole, and a high-fidelity echo measurement would provide an independent measure of fundamental black hole parameters. Our results suggest that detecting echoes may be achievable through interferometric observations with a modest space-based very long baseline interferometry mission.

ETHOS: An automated framework to generate multi-fidelity constitutive data tables and propagate uncertainties to hydrodynamic simulations

Accurate constitutive data, such as equations of state and plasma transport coefficients, are necessary for reliable hydrodynamic simulations of plasma systems such as fusion targets, planets, and stars. Here, we develop a framework for automatically generating transport-coefficient tables using a parameterized model that incorporates data from both high-fidelity sources (e.g., density functional theory calculations and reference experiments) and lower-fidelity sources (e.g., average-atom and analytic models). The framework incorporates uncertainties from these multi-fidelity sources, generating ensembles of optimally diverse tables that are suitable for uncertainty quantification of hydrodynamic simulations. We illustrate the utility of the framework with magnetohydrodynamic simulations of magnetically launched flyer plates, which are used to measure material properties in pulsed-power experiments. We explore how changes in the uncertainties assigned to the multi-fidelity data sources propagate to changes in simulation outputs and find that our simulations are most sensitive to uncertainties near the melting transition. The presented framework enables computationally efficient uncertainty quantification that readily incorporates new high-fidelity measurements or calculations and identifies plasma regimes where additional data will have high impact.

Optimal Design of a Sensor Network for Guided Wave-Based Structural Health Monitoring Using Acoustically Coupled Optical Fibers.

Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantages but their use has been limited for the GW sensing due to its limited sensitivity. FBG sensors in the edge-filtering configuration have overcome this issue with sensitivity and there is a renewed interest in their use. Unfortunately, the FBG sensors and the equipment needed for interrogation is quite expensive, and hence their number is restricted. In the previous work by the authors, the number and location of the actuators was optimized for developing a SHM system with a single sensor and multiple actuators. But through the use of the phenomenon of acoustic coupling, multiple locations on the structure may be interrogated with a single FBG sensor. As a result, a sensor network with multiple sensing locations and a few actuators is feasible and cost effective. This paper develops a two-step methodology for the optimization of an actuator-sensor network harnessing the acoustic coupling ability of FBG sensors. In the first stage, the actuator-sensor network is optimized based on the application demands (coverage with at least three actuator-sensor pairs) and the cost of the instrumentation. In the second stage, an acoustic coupler network is designed to ensure high-fidelity measurements with minimal interference from other bond locations (overlap of measurements) as well as interference from features in the acoustically coupled circuit (fiber end, coupler, etc.). The non-sorting genetic algorithm (NSGA-II) is implemented for finding the optimal solution for both problems. The analytical implementation of the cost function is validated experimentally. The results show that the optimization does indeed have the potential to improve the quality of SHM while reducing the instrumentation costs significantly.

Increased atom-cavity coupling through cooling-induced atomic reorganization

The strong coupling of atoms to optical cavities can improve optical lattice clocks as the cavity enables metrologically useful collective atomic entanglement and high-fidelity measurement. To this end, it is necessary to cool the ensemble to suppress motional broadening, and advantageous to maximize and homogenize the atom-cavity coupling. We demonstrate resolved Raman sideband cooling via the cavity as a method that can simultaneously achieve both goals. In 200 ms of Raman sideband cooling, we cool Yb171 atoms to an average vibration number 〈nx〉=0.23(7) in the tightly binding direction, resulting in 93% optical π-pulse fidelity on the clock transition S01→P03. During cooling, the atoms self-organize into locations with maximal atom-cavity coupling, which will improve quantum metrology applications. Published by the American Physical Society 2024

Near-Unity Indistinguishability of Single Photons Emitted from Dissimilar and Independent Atomic Quantum Nodes

Generating indistinguishable photons from independent nodes is an important challenge for the development of quantum networks. In this work, we demonstrate the generation of highly indistinguishable single photons from two dissimilar atomic quantum nodes. One node is based on a fully blockaded cold Rydberg ensemble and generates on-demand single photons. The other node is a quantum repeater node based on a Duan-Lukin-Cirac-Zoller quantum memory and emits heralded single photons after a controllable memory time that is used to synchronize the two sources. We demonstrate an indistinguishability of 94.6±5.2% for a temporal window including 90% of the photons. This advancement opens new possibilities for interconnecting quantum repeater and processing nodes with high-fidelity Bell state measurement without sacrificing its efficiency. Published by the American Physical Society 2024

Accelerating Formulation Design via Machine Learning: Generating a High-throughput Shampoo Formulations Dataset

Liquid formulations are ubiquitous yet have lengthy product development cycles owing to the complex physical interactions between ingredients making it difficult to tune formulations to customer-defined property targets. Interpolative ML models can accelerate liquid formulations design but are typically trained on limited sets of ingredients and without any structural information, which limits their out-of-training predictive capacity. To address this challenge, we selected eighteen formulation ingredients covering a diverse chemical space to prepare an open experimental dataset for training ML models for rinse-off formulations development. The resulting design space has an over 50-fold increase in dimensionality compared to our previous work. Here, we present a dataset of 812 formulations, including 294 stable samples, which cover the entire design space, with phase stability, turbidity, and high-fidelity rheology measurements generated on our semi-automated, ML-driven liquid formulations workflow. Our dataset has the unique attribute of sample-specific uncertainty measurements to train predictive surrogate models.

In-situ two-dimensional temperature measurements using x-ray fluorescence spectroscopy in laminar flames with high silica particle concentrations

X-ray fluorescence spectroscopy (XRF) was used to measure temperatures and study mixing, for the first time in silica particle synthesis flames. Hexamethyldisiloxane (HMDSO) and trimethylsilanol (TMSO) were the particle precursors. A multi-element diffusion burner was used to produce a flat methane flame, and the precursors, dilute in inert gas, were injected via a central jet. Krypton was the fluorescent medium at 3.2 % concentration by volume. Scans with Kr in the central flow and not in the main flow were made to assess the mixing effects between the central and main gas flows. When HMDSO or TMSO were added, a secondary diffusion flame formed between the jet and the main methane flame. The results revealed a dramatic change in the centerline temperature profile of the jet gases when HMDSO or TMSO were added. The main methane flame stoichiometry also affected the temperature profiles. The results show HMDSO and TMSO reactions are initiated in a low-temperature and low-oxygen concentration region of the jet where thermal decomposition is not expected to be significant. Reaction of the particle precursors is therefore attributed to radical transport from the main methane flame. In the current work, particle number densities of up to 270 g/m3 locally are estimated. Thus, the study also demonstrates the capability of the XRF technique for high spatial fidelity measurements in flames with high concentrations of condensed-phase particles, leveraging the attribute that the XRF signal is generally not impacted by condensed-phase interferences. The observations and data obtained in this study inform likely reaction pathways for this important class of siloxane compounds.

Copper permalloys for fluxgate magnetometer sensors

Abstract. Fluxgate magnetometers are commonly used to provide high-fidelity vector magnetic field measurements. The magnetic noise of the measurement is typically dominated by that intrinsic to a ferromagnetic core used to modulate (gate) the local field as part of the fluxgate sensing mechanism. A polycrystalline molybdenum–nickel–iron alloy (6.0–81.3 Mo permalloy) has been used in fluxgates since the 1970s for its low magnetic noise. Guided by previous investigations of high-permeability copper–nickel–iron alloys, we investigate alternative materials for fluxgate sensing by examining the magnetic properties and fluxgate performance of that permalloy regime in the range 28 %–45 % Cu by weight. Optimizing the alloy constituents within this regime enables us to create fluxgate cores with both lower noise and lower power consumption than equivalent cores based on the traditional molybdenum alloy. Racetrack geometry cores using six layers of ∼30 mm long foil washers consistently yield magnetic noise around 4–5 pT/Hz at 1 Hz and 6–7 pT/Hz at 0.1 Hz, meeting the 2012 1 s INTERMAGNET standard of less than 10 pT/Hz noise at 0.1 Hz.

A simple RANS closure for wind-farms under neutral atmospheric conditions: Preliminary findings

Accurately predicting wind turbine wake effects is essential for optimizing wind-farm performance and minimizing maintenance costs. This study explores the applicability of the Sparse Regression of Turbulent Stress Anisotropy (SpaRTA) framework to develop a simple yet robust Reynolds-averaged Navier-Stokes (RANS) model for wake prediction in wind energy contexts. The framework introduces two correction terms into two-equation models, with k − ε model being utilized in the current study. One correction term resembles the residual of the Turbulent Kinetic Energy (TKE) equation, and the other corrects the deviatoric part of the Reynolds Stress Tensor (RST). The terms are calculated from high-fidelity measurement or simulation data, and symbolic regression is used to determine the model for these terms.In this study, Large Eddy Simulation (LES) data from a single turbine is used as the training dataset, and a sample pre-selection process is employed to discover a correction model efficiently. The derived model incorporates two terms based on Pope’s basis tensors and their invariants. The expression of the obtained model shows that it functions as a modification to the constant Cµ in the k − ε model. The model is evaluated by comparing its predicted velocity and TKE fields with the LES data used for the training. The model showed satisfactory performance in predicting both fields. Additionally, its generalizability is evaluated by testing it against a more complex six-turbine unseen case. The results indicate that the model effectively captures the velocity field and power output, but it tends to overpredict TKE, especially in the wake region.

A parametric study on pulse duplicator design and valve hemodynamics.

In vitro assessment is mandatory for artificial heart valve development. This study aims to investigate the effects of pulse duplicator features on valve responsiveness, conduct a sensitivity analysis across valve prosthesis types, and contribute on the development of versatile pulse duplicator systems able to perform reliable prosthetic aortic valve assessment under physiologic hemodynamic conditions. A reference pulse duplicator was established based on literature. Further optimization process led to new designs that underwent a parametric study, also involving different aortic valve prostheses. These designs were evaluated on criteria such as mean pressure differential and pulse pressure (assessed from high-fidelity pressure measurements), valve opening and closing behavior, flow, and regurgitation. Finally, the resulting optimized setup was tested under five different hemodynamic settings simulating a range of physiologic and pathologic conditions. The results show that both, pulse duplicator design and valve type significantly influence aortic and ventricular pressure, flow, and valve kinematic response. The optimal design comprised key features such as a compliance chamber and restrictor for diastolic pressure maintenance and narrow pulse pressure. Additionally, an atrial reservoir was included to prevent atrial-aortic interference, and a bioprosthetic valve was used in mitral positionto avoid delayed valve closing effects. This study showed that individual pulse duplicator features can have a significant effect on valve's responsiveness. The optimized versatile pulse duplicator replicated physiologic and pathologic aortic valve hemodynamic conditions, serving as a reliable characterization tool for assessing and optimizing aortic valve performance.

Development of compact-modulated absorption/emission technique towards micro-gravity sooting flame measurements

To meet the experimental physical limitations on Chinese Space Station (CSS), three compact-modulated absorption/emission (CMAE) implementations are miniaturized progressively from original MAE layout, which are investigated as potential options for simultaneous soot temperature and volume fraction measurements in the axis-symmetric flames. Contrasted with the original MAE technique, a white LED point light source (diameter of ϕ = 8 mm) and a white LED planar light source (rectangle of 200 × 120 mm2) in turns replaces the laser source, by which the light beam homogeneous implementation is significantly simplified. Moreover, a 3-CMOS prism-based camera enables simultaneously recording flame two color radiations that reduces the detecting complexity. It is found that backlight beam intensity should be more than 2.5 times the flame radiation intensity to avoid abnormal extinction coefficient on the flame edge in this configuration. Moreover, the robustness and consistency of the three CMAEs measurements are validated with a standard Santoro’s flame, and low average standard deviation ranges of ±0.04∼±0.06 ppm and ±65.0∼± 96.3 K for soot volume fraction and temperature respectively is evaluated from error propagation assessment. As such, the proposed CMAE-2 and CMAE-3 layouts are promising candidates for high-fidelity flame soot parameters measurements under limited space, weight and power supply on CSS.

A Mini-Review of Recent Developments in Plenoptic Background-Oriented Schlieren Technology for Flow Dynamics Measurement

To uncover the underlying fluid mechanisms, it is crucial to explore imaging techniques for high-resolution and large-scale three-dimensional (3D) measurements of the flow field. Plenoptic background-oriented schlieren (Plenoptic BOS), an emerging volumetric method in recent years, has demonstrated being able to resolve volumetric flow dynamics with a single plenoptic camera. The focus-stack-based plenoptic BOS system can qualitatively infer the position of the density gradient in 3D space based on the relative sharpness of the refocused BOS image. Plenoptic BOS systems based on tomography or specular enhancement techniques are realized for use in high-fidelity 3D flow measurements due to the increased number of acquisition views. Here, we first review the fundamentals of plenoptic BOS, and then discuss the system configuration and typical application of single-view and multi-view plenoptic BOS. We also discuss the related challenges and outlook on the potential development of plenoptic BOS in the future.

(188) - Right Ventriculo-Arterial Coupling Assessment by High-Fidelity Hemodynamic Measurements in Patients Undergoing Left Ventricular Assist Device Implantation

(188) - Right Ventriculo-Arterial Coupling Assessment by High-Fidelity Hemodynamic Measurements in Patients Undergoing Left Ventricular Assist Device Implantation

Multi-level and Metrics Evaluation Approach for Data-Driven Based Sensor Models

Nowadays, with increased sensor perception performance for Advanced Driver Assistance Systems (ADAS), scenario-based simulation is becoming more frequent to manage the complexity of reality in terms of cost and time. The perception system provides the basis for the vehicle guidance algorithms calculation, but the simulation of ADAS sensors is a challenging task in virtual testing. Literature reports the magnitude of relevant modelling approaches and data-driven models becoming increasingly important. A basic method is to fit the sensor output in the virtual environment with high-fidelity measurements of real-world scenarios, thus a direct relation can be established between real and synthetic sensor data. To prove the suitability of a method, it is necessary to quantify the gap between simulation and reality to determine the performance of different models. In this work, authors address this problem and visualize the gap by introducing a multi-level evaluation approach that combines Model Generalization Ability Evaluation and Case Implicit Performance Evaluation. The former directly evaluates the model’s overall performance, while the latter is used for specific cases in simulation. The study shows that this combined evaluation approach provides an in-depth framework for evaluating sensor models to make the differences apparent.