Systematic Errors Research Articles

Effects of Sample Handling on Visible and Near-Infrared Soil Reflectance

Soil reflectance is a cumulative attribute determined by interactions between light (photons) and the physical, chemical, and biological properties of soil. Soil properties such as organic matter, moisture, mineral oxide contents, soil texture, and surface roughness all influence soil reflectance at unique wavelengths. Many standard sample preparation techniques are designed to alter soil properties, so as to homogenize samples to improve the consistency of reflectance data collected. This study aims to quantify the effects of one standard sample preparation activity, drying, and repeated wetting–drying cycles on visible–near-infrared soil reflectance, by collecting reflectance data from nine samples which were dried then wetted for a total of three times. This study demonstrates the major, permanent effects of a drying and wetting cycle on soil reflectance, and then presents a model which can be used to correct for these effects. These results have direct implications for remote sensing activities, soil libraries, and soil spectral libraries. These results show that without correction, data from soil spectral libraries, spectral data collected from stored samples, and spectral data transferred between studies, have limited utility for characterizing soils as they exist in the field. Soil spectral data collected in the lab requires correction before it may be used to predict soil properties in the field, as standard sample handling procedures change intrinsic soil properties and introduce systematic error into these data.

Lower magnetic field measurement limit of the coupled dark state magnetometer

Abstract The Coupled Dark State Magnetometer (CDSM) is an optically pumped magnetometer. For the Jupiter Icy Moons Explorer (JUICE) mission, the CDSM and two fluxgate magnetometers are combined in the J-MAG instrument to measure the static and low frequency magnetic field in the Jupiter system. During certain calibration manoeuvres, the CDSM has to be able to measure magnetic field strengths down to 100 nT with an accuracy of 0.2 nT (1 σ). At such low magnetic fields, the CDSM’s operational parameters must be carefully selected to obtain narrow resonance structures. Otherwise, the coupled dark state resonances, used for the magnetic field detection in different instrument modes, overlap and result in a systematic error. In this paper we demonstrate that with the found instrument settings the CDSM is able to measure magnetic field strengths below 100 nT with a systematic error less than 0.2 nT resulting from the overlap of the resonances.

Enhancing physically-based flood forecasts through fusion of long short-term memory neural network with unscented Kalman filter

Accurate flood forecasts are vital for reservoir operation and flood prevention. The unscented Kalman filter (UKF) excels in improving physically-based models flood forecasting but depends on precise noise estimation, posing challenges in complex uncertainty quantification. In this study, we propose a novel approach, the deep fusion of a long short-term memory (LSTM) neural network and unscented Kalman filter (LSTM-UKF), to enhance flood forecasts by adaptively updating hydrological model states. The LSTM efficiently learns noise-related information from the estimation of Kalman Gain, obviating the need for intricate uncertainty recognition and approximation. For comparative analysis, the LSTM-UKF and UKF filters are constructed to correct Xinanjiang (XAJ) hydrological model states. Both filters utilize streamflow observations to update the XAJ model states and facilitate its flood forecasting performance. Comprehensive evaluations were conducted using 3-hourly meteor-hydrological sequences from the Jianxi and Tianyi basins in China, focusing on the accuracy, stability, and reliability of multi-step-ahead flood forecasts. Results indicate that the LSTM-UKF performs superior to the UKF, with maximal advancements in Nash-Sutcliffe efficiency coefficient (NSE) by 9.1%, maximal reduction in root mean square error (RMSE) by 18.7%, and maximal decrease in mean absolute error (MAE) by 22.6%. Additionally, the LSTM-UKF exhibits better robustness and stability in non-stationary flood events. The proposed LSTM-UKF mitigates the over-reliance on noise estimates, reducing systematic biases and error accumulation in state estimates and enhancing hydrological model generalizability in operational flood prevention platforms and systems.

Inter-satellite tracking methods and applications: A comprehensive survey

The accurate measurement of inter-satellite distances is fundamental to the successful operation of distributed spacecraft missions, facilitating diverse applications ranging from scientific exploration to navigation and communication. This study comprehensively overviews applications requiring inter-satellite tracking by analyzing 44 multi-spacecraft missions. These missions are divided into seven categories based on their use of inter-satellite distance measurements. Each category necessitates varying levels of accuracy, prompting the utilization of distinct tracking methods. The analysis reveals that missions near Earth typically rely on Global Navigation Satellite Systems measurements, achieving millimeter-level accuracy, while lunar missions opt for radio ranging for centimeter-level accuracy. Inter-satellite Laser Ranging Interferometry emerges as the preferred method for missions demanding exceptionally high accuracy (nanometer to picometer range), such as those dedicated to gravitational wave detection and gravimetry. Notably, the analysis identifies a burgeoning trend towards the adoption of Inter-satellite Laser Transponder Ranging, capable of achieving sub-millimeter accuracy. Furthermore, this work proposes a novel concept: integrating inter-satellite ranging with Laser Communication Terminal (LCTs), either to substitute for existing tracking methods or to enhance measurement accuracy within established frameworks. However, its full potential rests upon the successful adaptation of existing LCTs for ranging functionality without compromising data rates. Future research will play a critical role in quantifying achievable ranging performance by characterizing systematic errors within LCTs.

Improper Background Treatment Underestimates Thermometric Performance of Rare Earth Vanadate and Phosphovanadate Nanocrystals.

Luminescence thermometry is the state-of-the-art technique for remote nanoscale temperature sensing, offering numerous promising cutting-edge applications. Advancing nanothermometry further requires rational design of phosphors and well-defined, comprehensive mathematical treatment of spectral information. However, important questions regarding improper signal processing in ratiometric luminescence thermometry are continuously overlooked in the literature. Here, we demonstrate that systematic errors arising from background/signal superposition impact the calculated thermometric quality parameters of ratiometric thermometers. We designed ultraviolet-excitable (Y,Eu)VO4 and (Y,Eu)(P,V)O4 nanocrystals showing overlapped VO4 3- and Eu3+ emissions to discuss systematically how uncorrected background emissions cause magnified (∼10×) temperature uncertainties and undervalued (∼60%) relative thermal sensitivities. Adequate separation of spectral contributions from the VO4 3- background and the Eu3+ signals via baseline correction is necessary to prevent underestimation of the thermometric performances. The described approach can be potentially extended to other luminescent thermometers to account for signal superposition, thus enabling to circumvent computation of apparent, miscalculated thermometric parameters.

Robust optimization and assessment of dynamic trajectory and mixed-beam arc radiotherapy: a preliminary study

Objective. Dynamic trajectory radiotherapy (DTRT) and dynamic mixed-beam arc therapy (DYMBARC) exploit non-coplanarity and, for DYMBARC, simultaneously optimized photon and electron beams. Margin concepts to account for set-up uncertainties during delivery are ill-defined for electron fields. We develop robust optimization for DTRT&DYMBARC and compare dosimetric plan quality and robustness for both techniques and both optimization strategies for four cases. Approach. Cases for different treatment sites and clinical target volume (CTV) to planning target volume (PTV) margins, m , were investigated. Dynamic gantry-table-collimator photon paths were optimized to minimize PTV/organ-at-risk (OAR) overlap in beam’s-eye-view and minimize potential photon multileaf collimator (MLC) travel. For DYMBARC plans, non-isocentric partial electron arcs or static fields with shortened source-to-surface distance (80 cm) were added. Direct aperture optimization (DAO) was used to simultaneously optimize MLC-based intensity modulation for both photon and electron beams yielding deliverable PTV-based DTRT&DYMBARC plans. Robust-optimized plans used the same paths/arcs/fields. DAO with stochastic programming was used for set-up uncertainties with equal weights in all translational directions and magnitude δ such that m= 0.7δ . Robust analysis considered random errors in all directions with or without an additional systematic error in the worst 3D direction for the adjacent OARs. Main results. Electron contribution was 7%–41% of target dose depending on the case and optimization strategy for DYMBARC. All techniques achieved similar CTV coverage in the nominal (no error) scenario. OAR sparing was overall better in the DYMBARC plans than in the DTRT plans and DYMBARC plans were generally more robust to the considered uncertainties. OAR sparing was better in the PTV-based than in robust-optimized plans for OARs abutting or overlapping with the target volume, but more affected by uncertainties. Significance. Better plan robustness can be achieved with robust optimization than with margins. Combining electron arcs/fields with non-coplanar photon trajectories further improves robustness and OAR sparing.

Validation of an mHealth System for Monitoring Fundamental Physiological Parameters in the Clinical Setting.

The aim of this work was to validate the measurements of three physiological parameters, namely, body temperature, heart rate, and peripheral oxygen saturation, captured with an out-of-the-lab device using measurements taken with clinically proven devices. The out-of-the-lab specialized device was integrated into a customized mHealth application, e-CoVig, developed within the AIM Health project. To perform the analysis, single consecutive measurements of the three vital parameters obtained with e-CoVig and with the standard devices from patients in an intensive care unit were collected, preprocessed, and then analyzed through classical agreement analysis, where we used Lin's concordance coefficient to assess the agreement correlation and Bland-Altman plots with exact confidence intervals for the limits of agreement to analyze the paired data readings. The existence of possible systematic errors was also addressed, where we found the presence of additive errors, which were corrected, and weak proportional biases. We obtained the mean overall agreement between the measurements taken with the novel e-CoVig device and the reference devices for the measured quantities. Although some limitations in this study were encountered, we present more advanced methods for their further assessment.

Optimal Correction Strategy of Image Guided Radiation Therapy Including the Paraortic Lymph Node Region in Patients With Cervical Cancers

The clinically accepted planning target volume margin for radiation therapy to the paraortic nodal region in cervical cancer patients is 5 mm. However, the comprehensive alignment and variability from the pelvic bone to all lumbar vertebrae are undetermined. This study aims to quantify the residual setup errors between the pelvic bone and lumbar vertebrae and determine the optimal correction strategy for patients with cervical cancer. Fifteen patients underwent pretreatment mega-voltage computed tomography scans (375 total fractions). Residual setup errors and required margins for each lumbar vertebra were calculated based on registrations accounting for pelvic rotation and translation. The systematic residual errors (1 SD) at L1, L2, L3, L4, and L5 using pelvic bone registration were 6.5, 4.9, 3.1, 1.5, and 0.6 mm in the anterior-posterior (AP) direction, 3.1, 2.3, 1.4, 0.6, and 0.3 mm in the right-left direction, and 2.7, 2.2, 1.7, 1.0, and 0.5 mm in the superior-inferior direction, respectively. The residual setup errors were the largest in the AP direction. Registration based on the pelvic bone required margins in the AP direction of 16.0, 12.1, 7.7, 3.6, and 1.3 mm for L1, L2, L3, L4, and L5, respectively, whereas registration based on L3 required margins of 8.8, 4.8, 4.4, 7.1, and 7.7 mm for L1, L2, L4, L5, and pelvic bone, respectively. Considerable local setup variability was found in patients with cervical cancer. After reviewing the corrective strategies, we determined that L3-based registration effectively minimized the required margins.

Maximizing the Accuracy of Equilibrium Dissociation Constants for Affinity Complexes: From Theory to Practical Recommendations.

The equilibrium dissociation constant (Kd) is a major characteristic of affinity complexes and one of the most frequently determined physicochemical parameters. Despite its significance, the values of Kd obtained for the same complex under similar conditions often exhibit considerable discrepancies and sometimes vary by orders of magnitude. These inconsistencies highlight the susceptibility of Kd determination to large systematic errors, even when random errors are small. It is imperative to both minimize and quantitatively assess the systematic errors inherent in Kd determination. Traditionally, Kd values are determined through nonlinear regression of binding isotherms. This analysis utilizes three variables: concentrations of two reactants and a fraction R of unbound limiting reactant. The systematic errors in Kd arise directly from systematic errors in these variables. Therefore, to maximize the accuracy of Kd, this study thoroughly analyzes the sources of systematic errors within the three variables, including (i) non-additive signals to calculate R, (ii) mis-calibrated experimental instruments, (iii) inaccurate calibration parameters, (iv) insufficient incubation time, (v) unsaturated binding isotherm, (vi) impurities in the reactants, and (vii) solute adsorption onto surfaces. Through this analysis, we illustrate how each source contributes to inaccuracies in the determination of Kd and propose strategies to minimize these contributions. Additionally, we introduce a method for quantitatively assessing the confidence intervals of systematic errors in concentrations, a crucial step toward quantitatively evaluating the accuracy of Kd. While presenting original findings, this paper also reiterates the fundamentals of Kd determination, hence guiding researchers across all proficiency levels. By shedding light on the sources of systematic errors and offering strategies for their mitigation, our work will help researchers enhance the accuracy of Kd determination, thereby making binding studies more reliable and the conclusions drawn from such studies more robust.

Compositional Analysis of Pt1-XCox Thin Film with Single Deposition, Combinatorial Co-Sputter Technique

Applications of thin-film magnetic materials often have narrow windows that the magnetic characteristics (i.e., remnant magnetization and coercive field) must meet – for instance magneto-optical devices [1] with latching operations [2] or amplitude- [3] or phase-control [4] of superconducting-ferromagnetic hybrid systems for next-generation computing memory. As systems become more complex, manipulating magnetic layers without affecting the rest of the device becomes increasingly challenging. Alloys of magnetic materials can alleviate this but determining viability – whether an alloy has any composition that can meet design needs – requires fabricating and analyzing samples that span the compositional space.Despite the community utilizing high-throughput methods for decades, including for thin-film materials [5], most exploratory research is still conducted by creating one composition per run, varying relative power or time during a deposition, for example. Obtaining a library of samples that vary in subtle but non-trivial ways becomes time-intensive, often prohibitive, and the resulting data set is prone to systematic errors that result from run-to-run variations. High-throughput methods, especially those that can produce a breadth of variation in a single fabrication or synthesis run, can expedite the discovery phase and reduce errors that complicate comparative analysis.One method that can provide, in a single run, a broad range of compositions for a material system is combinatorial fabrication using oblique angle co-deposition [6]. Using this method, we co-sputtered samples using targets of elemental Pt and Co to obtain PtCo thin film (Figure 1a). During deposition, the wafer is not rotated, relying instead on the target and sample geometry in the chamber to provide compositional variation across the wafer. After unloading and dicing our test wafer into 4mm-by-4mm samples, we ran XRD of multiple samples to determine thickness and composition of the thin film alloys as a function of position (Figure 1b).Across an 8” wafer, this technique yielded Pt1-xCox thin film between 5% and 83% atomic composition Co. A subset of samples (68 nm < t < 117 nm, where t is the PtCo thickness) were measured with VSM up to 1 T applied field to obtain B-H curves (Figure 1c), from which the remnant magnetization and coercive field characteristics relative to composition were extracted (Figure 1d). We find that remnant magnetization varies from 0 T to about 0.6 T, mostly increasing as %Co increases. Coercivities vary between 0 Oe and 1800 Oe, maximized at about 50% Co. Because the samples were fabricated in the same run, all samples are free from run-to-run variations and differences in processing, and thus they can be compared directly. Utilizing this technique, we were able to determine the viability window of Pt1-xCox films for nearly all compositions (5%-83% Co) in a single run.Figure 1 a) Sputtering system running combinatorial Co-Pt growth. b) Thickness and atomic%-composition of Co relative to sample location. c) J-H curve for 66at% Co. d) Remnant magnetization (JR) and coercive field (H0) for Pt1-xCox , 0.05 < x < 0.83. Acknowledgement: This work was performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science. This work is supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This written work is authored by an employee of NTESS. The employee, not NTESS, owns the right, title and interest in and to the written work and is responsible for its contents. Any subjective views or opinions that might be expressed in the written work do not necessarily represent the views of the U.S. Government. The publisher acknowledges that the U.S. Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this written work or allow others to do so, for U.S. Government purposes. The DOE will provide public access to results of federally sponsored research in accordance with the DOE Public Access Plan. Figure 1

Investigations into the Geometric Calibration and Systematic Effects of a Micro-CT System.

Micro-Computed Tomography (µCT) systems are used for examining the internal structures of various objects, such as material samples, manufactured parts, and natural objects. Resolving fine details or performing accurate geometric measurements in the voxel data critically depends on the precise calibration of the µCT systems geometry. This paper presents a calibration method for µCT systems using projections of a calibration phantom, where the coordinates of the phantom are initially unknown. The approach involves detecting and tracking steel ball bearings and adjusting the unknown system geometry parameters using non-linear least squares optimization. Multiple geometric models are tested to verify their suitability for a self-calibration approach. The implementation is tested using a calibration phantom captured at different magnifications. The results demonstrate the system's capability to determine the geometry model parameters with a remaining error on the detector between 0.27 px and 0.18 px. Systematic errors that remain after calibration, as well as changing parameters due to system instabilities, are investigated. The source code of this work is published to enable further research.

Linear-Structured-Light Measurement System Based on Scheimpflug Camera Thick-Lens Imaging.

A thick-lens, structured-light measurement model is introduced to overcome the oversights in traditional models, which often disregard the impact of lens thickness. This oversight can lead to inaccuracies in Scheimpflug camera calculations, causing systematic errors and diminished measurement precision. By geometrical optics, the model treats the camera as a thick lens, factoring in the locations of its principal points and the spatial shifts due to image plane tilting. The model deduces the positional relationship of the thick lens with a tilted optical axis and establishes a linear-structured-light measurement model. Simulations confirm that the model can precisely calculate the 3D coordinates of subjects from image light strip data, markedly reducing systematic errors across the measurement spectrum. Moreover, experimental results suggest that the refined sensor model offers enhanced accuracy and lower standard deviation.

Systematic improvement of x -dependent unpolarized nucleon generalized parton distributions in lattice-QCD calculation

We present a first study of the effects of renormalization-group resummation (RGR) and leading-renormalon resummation (LRR) on the systematic errors of the unpolarized isovector nucleon generalized parton distribution in the framework of large-momentum effective theory. This work is done using lattice gauge ensembles generated by the MILC Collaboration, consisting of 2+1+1 flavors of highly improved staggered quarks with a physical pion mass at lattice spacing a≈0.09 fm and a box width L≈5.76 fm. We present results for the nucleon H and E generalized parton distributions (GPDs) with average boost momentum Pz≈2 GeV at momentum transfers Q2=[0,0.97] GeV2 at skewness ξ=0 as well as Q2∈0.23 GeV2 at ξ=0.1, renormalized in the modified minimal subtraction (MS¯) scheme at scale μ=2.0 GeV, with two- and one-loop matching, respectively. We demonstrate that the simultaneous application of RGR and LRR significantly reduces the systematic errors in renormalized matrix elements and distributions for both the zero and nonzero skewness GPDs, and that it is necessary to include both RGR and LRR at higher orders in the matching and renormalization processes. Published by the American Physical Society 2024

A Bi-Temporal Airborne Lidar Shrub-to-Tree Aboveground Biomass Model for the Taiga of Western Canada

Monitoring aboveground biomass (AGB) is critical for carbon reporting and quantifying ecosystem change. AGB from field data can be scaled to the region using airborne lidar. However, lidar-based AGB products emphasize upland forests, which may not represent the conditions in rapidly changing peatland complexes in the southern Taiga of western Canada. In addition, to ensure that modeled AGB changes do not incorporate systematic error due to differences between older and newer lidar technologies, model transfer tests are required. The aim of this study was to develop one bi-temporal lidar-based AGB model applicable to (1) vegetation structures at varying vertical and horizontal continuity in this region and to (2) data collected with an earlier generation lidar system for which Canada-wide aerial coverage is available. Goodness-of-fit metrics show that AGB can be modeled with moderate (R2 = 48%–58% Taiga Shield, peatlands) to high accuracies (R2 = 83%–89% Taiga Plains, upland/permafrost plateau forests including ecotones) by using the point clouds average height and 90th height percentile within a weighted approach as function of modeled AGB and calibrating the earlier lidar data. These results are important for quantifying climate change effects on forest to peatland ecotones.

Measurement System for the Calibration of Accelerometer Arrays

This paper addresses accelerometer array calibration, focusing on determining the errors between multiple sensors. Micro-electromechanical system (MEMS) based triaxial accelerometers, key components of Inertial Measurement Units (IMUs), are used in localization, robotics, and navigation systems. The requirements of these applications necessitate low-cost sensors, which makes MEMS IMUs a reasonable choice. However, these low-cost IMUs are significantly affected by systematic (i.e., bias, misalignment, scale-factor) and random errors. Achieving reliable sensor output depends on the precision of the executed calibration method. While traditional laboratory-based sensor calibration using specialized equipment (i.e., three-axis turntable) is accurate, it is time-consuming and costly. In contrast, in-field calibration techniques, which can be performed using a mechatronic actuator or a robotic arm, have gained popularity. These techniques involve comparing sensor measurements to established reference values. The MEMS sensors are increasingly being used in multi-sensor applications, which demands not only individual sensor error calibration but also important to determine the axis misalignment between the used sensors. During calibration process, various optimization algorithms (e.g., GA, PSO) can also be used to find the error parameters. The proposed measurement system allows for individual calibration of misalignment, bias, and scale factor of the sensor array, and eliminates between-sensor misalignment errors.

Re-Evaluating the Appropriateness of the "Don't Know" Response Option: Guessing Rate as a Source of Systematic Error on Autism Knowledge Assessments.

Several autism knowledge assessments include "don't know" as a response option. The inclusion of this response option may lead to systematic error, such that participants' guessing rate affects the measurement of their autism knowledge. This study examines both predictors of guessing rate for autism knowledge and predictors of autism knowledge, including guessing rate. School-based professionals (n = 396) completed the Autism Spectrum Knowledge Scale Professional Version-Revised (ASKSP-R; McClain et al, Journal of Autism and Developmental Disorders 50(3):998-1006, 2020). and the Autism Stigma and Knowledge Questionnaire (ASK-Q; Harrison et al, Journal of Autism and Developmental Disorders 47(10):3281-3295, 2017). Both assessments include "don't know" as a response option. Guessing rate was the strongest predictor of autism knowledge across both the ASKSP-R and the ASK-Q assessments. For the ASKSP-R, participants who were school psychologists, practicing for more years, had more autism-related clinical experiences, and who personally knew an autistic person had a higher guessing rate. School psychologists and participants who worked with more autistic students scored higher in autism knowledge. For the ASK-Q, participants with greater self-perceived autism knowledge had a higher guessing rate. Participants with a doctorate degree, who personally knew an autistic person, and who worked with more autistic students scored higher in autism knowledge. Guessing rate can be a source of systematic error on autism knowledge assessments. Potential solutions to correct for guessing rate are examined and recommended for future use.

Fast and direct calibration for high numerical aperture quadriwave lateral shearing interferometry using geometry model with higher-order Taylor expansion

The current research on quadriwave lateral shearing interferometry (LSI) is primarily focused on the measurements of plane wave or quasiplane wave. When directly measuring spherical waves with high numerical apertures (NA&gt;0.35), it will generate additional systematic errors, which affect measurement accuracy. To make the quadriwave LSI applicable to the measurements of a high-NA spherical wave, this paper proposes a fast and direct calibration method by establishing the geometry model of the quadriwave LSI with high-NA spherical wave incidence. The expression for the optical path difference represented systematic errors introduced by high-NA spherical waves in the shearing wavefronts are derived, which utilize a ninth-order Taylor expansion and Zernike polynomials fitting to achieve the high accuracy required by the high-NA spherical wave incidence. Then, the systematic errors are directly calibrated in the shearing wavefronts of four directions. This paper presents the theoretical analysis and verifies the feasibility and reliability of the proposed method through simulations and experiments, achieving a good measurement accuracy.

Kaon mixing beyond the standard model with physical masses

We present nonperturbative results for beyond the standard model kaon mixing matrix elements in the isospin symmetric limit (mu=md) of QCD, including a complete estimate of all dominant sources of systematic error. Our results are obtained from numerical simulations of lattice QCD with Nf=2+1 flavors of dynamical domain wall fermions. For the first time, these quantities are simulated directly at the physical pion mass mπ∼139 MeV for two different lattice spacings. We include data at three lattice spacings in the range a=0.11–0.07 fm and with pion masses ranging from the physical value up to 450 MeV. Compared to our earlier work, we have added both direct calculations at physical quark masses and a third lattice spacing making the removal of discretization effects significantly more precise and eliminating the need for any significant mass extrapolation beyond the range of simulated data. We renormalize the lattice operators nonperturbatively using RI-SMOM off-shell schemes. These schemes eliminate the need to model and subtract nonperturbative pion poles that arises in the RI-MOM scheme and, since the calculations are performed with domain wall fermions, the unphysical mixing between chirality sectors is suppressed. Our results for the bag parameters in the MS¯ scheme at 3 GeV are BK≡B1=0.5240(17)(54), B2=0.4794(25)(35), B3=0.746(13)(17), B4=0.897(02)(10) and B5=0.6882(78)(94), where the first error is from lattice uncertainties and the second is the uncertainty due to the perturbative matching to MS¯. Published by the American Physical Society 2024

Quantum advantage and stability to errors in analogue quantum simulators

Several quantum hardware platforms, while being unable to perform fully fault-tolerant quantum computation, can still be operated as analogue quantum simulators for addressing many-body problems. However, due to the presence of errors, it is not clear to what extent those devices can provide us with an advantage with respect to classical computers. In this work, we make progress on this problem for noisy analogue quantum simulators computing physically relevant properties of many-body systems both in equilibrium and undergoing dynamics. We first formulate a system-size independent notion of stability against extensive errors, which we prove for Gaussian fermion models, as well as for a restricted class of spin systems. Remarkably, for the Gaussian fermion models, our analysis shows the stability of critical models which have long-range correlations. Furthermore, we analyze how this stability may lead to a quantum advantage, for the problem of computing the thermodynamic limit of many-body models, in the presence of a constant error rate and without any explicit error correction.

Reliability of cervicocephalic sense of force

Cervicocephalic proprioception (CCP) is an important assessment item for people with a range of clinical conditions, where reduced CCP is associated with neck pain and imbalance. Reliability has been established for a range of positional and movements tests, but there is limited data regarding sense of force, particularly across three planes of movement. The current test–retest study assessed reliability when evaluating sense of force in healthy adults (8 males, 6 females, mean age 31.50 years [SD 10.14]) over two sessions, 4–7 days apart. A force matching protocol was used to evaluate reliability of absolute error (AE), constant error (CE), and variable error (VE) for 10 % and 25 % maximal voluntary contraction (MVC) target forces for flexion, extension, lateral flexion, and rotation. Participants were strapped to a chair to limit trunk movement and data was captured using a compressive force transducer fixed to an adjustable wall mount. Six trials were performed for each contraction-type, totaling 72 submaximal MVCs per session. ICC estimates for AE (0.15–0.77), CE (0.01–0.85), and VE (0.00–0.83) were varied and confidence intervals were mostly wide. Considering lower limits of confidence intervals, CE had best reliability values generally, but more specifically the most reliable contraction type and movement was 25 % MVC flexion (ICC 0.85, confidence interval 0.54–0.95). This study found that reliability for sense of force testing was dependent upon contraction, type of error, and target force utilized. Further reliability analysis should be performed when applying this test to measure validity outcomes in clinical populations.