Experimental Error Research Articles

Implementation of the Projective Quantum Eigensolver on a Quantum Computer.

We study the performance of our previously proposed projective quantum eigensolver (PQE) on IBM's quantum hardware in conjunction with error mitigation techniques. For a single qubit model of H2, we find that we are able to obtain energies within 4 millihartree (2.5 kcal/mol) of the exact energy along the entire potential energy curve, with the accuracy limited by both the stochastic error and the inconsistent performance of the IBM devices. We find that an optimization algorithm using direct inversion of the iterative subspace can converge swiftly, even to excited states, but stochastic noise can prompt large parameter updates. For the 4-site transverse-field Ising model at its critical point, PQE with an appropriate application of qubit tapering can recover 99% of the correlation energy, even after discarding several parameters. The large number of CNOT gates needed for the additional parameters introduces a concomitant error that, on the IBM devices, results in a loss of accuracy despite the increased expressivity of the trial state. Error extrapolation techniques and tapering or postselection are recommended to mitigate errors in PQE hardware experiments.

Measurement the 3D temperature distribution in the combustion zone using acoustic tomography and nolinear wavefont tracing

A non-invasive temperature measurement method in three dimensions is proposed to reconstruct the three-dimensional temperature. It relies on the use of nonlinear acoustic travel-time tomography, which incorporates acoustic path tracing, Gaussian kernel function, and modified Tikhonov regularization. Sound signals can be distorted due to large average temperature gradients and oscillatory release of heat in the combustion region. The effective acoustic signal is extracted based on spectral subtraction to evaluate the sound propagation time under distorted signals. The analysis of experimental errors indicates that the proposed acoustic pyrometry method has an average relative error of less than 15% compared to the time-averaged temperature measured by thermocouples. This result verifies the efficacy of the method when it comes to accurately reconstructing the temperature field in the combustion area. The reduction in error is attributed to the consideration of acoustic ray tracing within the proposed method.

Graph Crypto-Stego System for Securing Graph Data Using Association Schemes

Cryptography has recently become a critical area to research and advance in order to transmit information safely and securely among various entities, especially when the transmitted data is classified as crucial or important. This is due to the increase in the use of the Internet and other novel communication technology. Many businesses now outsource sensitive data to a third party because of the rise of cloud computing and storage. Currently, the key problem is to encrypt the data such that it may be stored on an unreliable server without sacrificing the ability to use it effectively. In this paper, we propose a graph encryption scheme by using cryptography and steganography. Data is encrypted using association schemes over finite abelian groups and then hiding the encrypted data behind randomly chosen cover image. We implemented and evaluated the efficiency of our constructions experimentally. We provide experimental results, statistical analysis, error analysis, and key analysis that demonstrates the appropriateness and efficiency of the proposed technique.

Radiation and heat transport in divergent shock–bubble interactions

Shock–bubble interactions (SBIs) are important across a wide range of physical systems. In inertial confinement fusion, interactions between laser-driven shocks and micro-voids in both ablators and foam targets generate instabilities that are a major obstacle in achieving ignition. Experiments imaging the collapse of such voids at high energy densities (HED) are constrained by spatial and temporal resolution, making simulations a vital tool in understanding these systems. In this study, we benchmark several radiation and thermal transport models in the xRAGE hydrodynamic code against experimental images of a collapsing mesoscale void during the passage of a 300 GPa shock. We also quantitatively examine the role of transport physics in the evolution of the SBI. This allows us to understand the dynamics of the interaction at timescales shorter than experimental imaging framerates. We find that all radiation models examined reproduce empirical shock velocities within experimental error. Radiation transport is found to reduce shock pressures by providing an additional energy pathway in the ablation region, but this effect is small (∼1% of total shock pressure). Employing a flux-limited Spitzer model for heat conduction, we find that flux limiters between 0.03 and 0.10 produce agreement with experimental velocities, suggesting that the system is well-within the Spitzer regime. Higher heat conduction is found to lower temperatures in the ablated plasma and to prevent secondary shocks at the ablation front, resulting in weaker primary shocks. Finally, we confirm that the SBI-driven instabilities observed in the HED regime are baroclinically driven, as in the low energy case.

Evaluation of experimental error in accelerometer monitoring: Variation among individual animals versus variation among devices

Application of sensors is becoming prevalent in research and production settings. With increasing battery power, improved case and component durability, and consistent data connectivity, precision technologies, such as accelerometers, can help identify changes in livestock behavior. The objective of this study is to identify the variation among individual animals and among different accelerometer devices. A repeated 4 × 4 Latin-square design was utilized to identify differences between accelerometer, animal, and week. Twelve ewes separated into three age groups were randomly assigned to 4 different accelerometers deployed as an ear tag weekly over the course of 4 weeks. Manual behavior observations were paired to calculated accelerometer metrics and were used for training and validation dataset to predict animal behavior using random forest machine learning. Movement variation had the greatest importance in predicting behaviors. Across the four week study, differences were found for animal and week through each of the calculated metrics. Differences in accelerometers were detected for 80 % of the calculated metrics. This study shows the importance to account for variation among individual animals and accelerometer devices in experimental designs.

High-Precision Localization of Passive Intermodulation Source in Radio Frequency Transmission Lines Based on Dual-Frequency Signals

With the development of communication technology, the interference from passive intermodulation to the communication system has become increasingly severe. Locating the source of passive intermodulation and then repairing or replacing the device experiencing passive intermodulation is a reliable method. Therefore, this paper proposes a dual-frequency signal localization method based on the principle of phase ranging to accurately locate the passive intermodulation sources in RF cables. This method switches the test signal frequency to obtain the phase of passive intermodulation signals at different frequencies to localize the passive intermodulation source. This paper analyzes the principle of the passive intermodulation localization method based on dual-frequency signals, establishes a localization system for experiments, and finally, analyzes the experimental error to propose an optimization strategy. Through experimental verification, this method can stabilize the positioning error of a passive intermodulation source in a transmission line less than 0.06 m. Meanwhile, this method has high positioning accuracy and the advantages of slight computational complexity, fast positioning speed, and only a small number of requirements on hardware resources. It can work in communication scenarios like satellite and base stations, providing a new technical solution for localizing passive intermodulation interference sources in 5G and 6G communication systems.

Effect of Camera Parallax Angle on the Accuracy of Static Contact Angle Measurements.

Measuring the contact angle at the solid/liquid/vapor triple point in sessile drop experiments is one of the most popular and simple ways to quantify the wettability of surfaces and determine the surface free energy. Despite decades of technical advancements in contact angle measurements, which allowed for improving the precision of sessile drop measurements below ±1°, an often overlooked source of experimental error in these measurements originates from the camera's parallax angle (PA) - the angle between the camera optical axis and the sample stage surface. Here, we quantified the systematic errors in the measurement of contact angles due to the acquisition of drop images at finite PA values by simulating sessile drop experiments in which synthetic drops were created using the Young-Laplace equation. The absolute contact angle error induced by imaging drops at nonzero PAs was found to increase as the true contact angle (TCA) deviates from 90° and resulted in an overestimation (underestimation) of the contact angle for drops having TCAs lower (higher) than 90°. The computed absolute contact angle error reaches values as high as -20° (+12.2°) for drops having a TCA of 175° (5°) when imaged with a PA of 10°, thus indicating the importance of considering the PA when accurately quantifying contact angles in sessile drop experiments. The shape and, by extension, volume of the sessile drop was also found to affect the magnitude of the absolute contact angle error as sessile drops with higher apex curvatures exhibited lower absolute error than those with lower curvatures at any given PA. The outcomes of this work provide guidelines for minimizing systematic errors in sessile drop measurements due to the collection of drop images at nonzero PAs.

Multi-physics coupling simulation and design of magnetic field-driven soft microrobots in liquid environments

Magnetic field-driven soft microrobots have widespread applications in biomedical science, microfluidic chips, nanoengineering, and various other domains. However, the existing methods for designing such magnetic-driven flexible robots largely rely on experimental trial and error or steady-state numerical simulated results, which fall short of meeting the intricate requirements for magnetic field editing and magnetic domain distribution. Addressing this issue, a multi-physics coupling numerical analysis method encompassing Magnetic-Fluid-Solid mechanics was developed. A complete process for transient numerical simulation resolution has been achieved. Utilizing this analysis method, the motion patterns of two typical prototypes of magnetic-driven miniature soft bionic robots, a bionic midge larvae robot, and a bionic jellyfish robot, have been analyzed. The central role of the magnetic field in driving these robotic designs—causing deformation in microrobots by designing magnetic domains and spinning the microrobots by controlling the magnetic field—has been revealed. We developed a theoretical model of a bionic fish tail fin robot driven solely by a rotating magnetic field and conducted comparative studies on the swimming efficiency, flexibility, stability, and relative advantages of the three types of robots. The impact of different magnetic domain distribution rules and different magnetic field driving methods on a robot's performance is analyzed, validating that higher swimming efficiency can be achieved by designing a robot's magnetic domains so that they undergo magnetic displacement under magnetic torque resulting in deformation. This innovative analysis method holds potential to provide valuable references for designing motion patterns of magnetically driven microrobots within liquid environments, thereby deepening our understanding toward various complex gait mechanisms involved in biological swimming.

A 19-Bit Small Absolute Matrix Encoder.

With the application of encoders in artificial intelligence and aerospace, the demand for the miniaturization and high measurement accuracy of encoders is increasing. To solve this problem, a new absolute matrix encoder is proposed in this paper, which can realize 19-bit matrix coding by engraving two circles of matrix code, and has the advantages of fewer circles of code disk engraving and higher measurement accuracy. This article mainly focuses on the design of a new matrix code disk, encoding and decoding methods, decoding circuit design, Matlab simulation analysis, and experimental error analysis. The experimental results show that the encoder designed in this paper achieves ultra-small volume Φ30 mm × 20 mm, and the angle measurement accuracy is 2.57".

On semiconductor–metal transition in FeSi induced by ultrahigh magnetic field

At low temperatures, iron monosilicide is a strongly correlated narrow-gap semiconductor. A first order transition to metal state induced by magnetic field was observed for the first time at 355 T in Ref. [Yu. B. Kudasov et al., JETP Lett. 68 (1998) 350]. However, recently a smooth transition from 230 T to 270 T was found under similar conditions in Ref. [D. Nakamura et al., Phys. Rev. Lett. 127 (2021) 156601]. This discrepancy goes far beyond experimental errors and deserves a careful study. A methodological analysis of inductive and RF techniques of conductivity measurements shows that the difference of these critical magnetic field estimations stems from a divergence in dynamic ranges of the techniques. In fact, the above mentioned methods supplement each other. The semiconductor-metal transition under magnetic field in FeSi is a complex phenomenon which occurs at the wide range of magnetic fields.

Experimental Investigation of Uncertainty Relations for Non-Hermitian Operators.

Uncertainty relations for Hermitian operators have been confirmed through many experiments. However, previous experiments have only tested the special case of non-Hermitian operators, i.e., uncertainty relations for unitary operators. In this study, we explore uncertainty relations for general non-Hermitian operators, which include Hermitian and unitary operators as special cases. We perform experiments with both real and complex non-Hermitian operators for qubit states, and confirm the validity of the uncertainty relations within the experimental error. Our results provide experimental evidence of uncertainty relations for non-Hermitian operators. Furthermore, our methods for realizing and measuring non-Hermitian operators are valuable in characterizing open-system dynamics and enhancing parameter estimation.

Amplifying Sensing Capabilities: Combining Plasmonic Resonances and Fresnel Reflections through Multivariate Analysis.

Multivariate analysis applied in biosensing greatly improves analytical performance by extracting relevant information or bypassing confounding factors such as nonlinear responses or experimental errors and noise. Plasmonic sensors based on various light coupling mechanisms have shown impressive performance in biosensing by detecting dielectric changes with high sensitivity. In this study, gold nanodiscs are used as metasurface in a Kretschmann setup, and a variety of features from the reflectance curve are used by machine learning to improve sensing performance. The nanostructures of the metasurface generate new plasmonic features, apart from the typical resonance that occurs in the classical Kretschmann mode of a gold thin film, related to the evanescent field beyond total internal reflection. When the engineered metasurface is integrated into a microfluidic chamber, the device provides additional spectral features generated by Fresnel reflections at all dielectric interfaces. The increased number of features results in greatly improved detection. Here, multivariate analysis enhances analytical sensitivity and sensor resolution by 200% and more than 20%, respectively, and reduces prediction errors by almost 40% compared to a standard plasmonic sensor. The combination of plasmonic metasurfaces and Fresnel reflections thus offers the possibility of improving sensing capabilities even in commonly available setups.

Fourier-transform spectroscopy and global deperturbation treatment of the A1Σu+ and b3Πu states of K2 in the entire bound energy range.

Rotationally resolved Fourier-transform spectra of laser-induced fluorescence A1Σu+∼b3Πu→X1Σg+ of K2 molecules were recorded and analyzed, yielding 4053 term values of the spin-orbit (SO) coupled A ∼ b complex of the 39K2 isotopologue with ∼0.01 cm-1 accuracy. Their compilation with 1739 term values from previously published sources allowed them to cover the energy range [9955, 17 436] cm-1 from the bottom of the lower-lying b3Πu state up to the vicinity of the atomic asymptote 4s2S12 + 4p2P12, with a rotational quantum number J ∈ [0, 149]. The experimental data were processed by a direct 6 × 6 coupled-channel (CC) deperturbation treatment, which accounted explicitly for both SO and electronic-rotational interactions between all six e-symmetry states: A1Σu+(0u+), b3Πu(0u+,1u,2u), c3Σu(1u), and B1Πu(1u). The initial parameters of the global deperturbation model have been estimated in the framework of abinitio electronic structure calculations applying multi-reference configuration-interaction and coupled-clusters methods. The interatomic potentials analytically defined for A and b states, as well as SO-splitting of the triplet b state and A ∼ b SO-coupling functions, have been particularly refined to fit the 5792 term values of the 39K2 isotopologue, whereas the rest parameters were fixed on their abinitio values. The resulting mass-invariant parameters of the 6 × 6 CC model reproduced the overall rovibronic term energies of the A ∼ b complex of 39K2 with accuracy, which is well within the experimental errors. The quality of the deperturbation analysis was independently confirmed by comparison with the present obtained 705 and 14 term values of respective 39K41K and 41K2 isotopologues, as well as by agreement between measured and predicted relative intensity distributions in long A ∼ b → X(vX) band progressions. This deperturbation analysis provided the refined dissociation energy Tdis = 17 474.569(5) cm-1 and the long-range coefficient C3Σ = 5.501(4) × 105 cm-1 Å3 relevant to the non-relativistic atomic limit 4s + 4p. The derived Tdis yielded the accurate well depth De = 4450.910(5) cm-1 for the ground X1Σg+ state, whereas the new C3Σ value yielded the improved estimates for atomic K(4p2P12;32) radiative lifetimes, τ12 = 26.67(3) and τ32 = 26.32(3) ns.

A new OSL dose model to account for post-depositional mixing of sediments

In applications of optically stimulated luminescence (OSL) dating to unconsolidated sediments, the burial age of a sample of grains is estimated using statistical models of the distribution of the experimentally determined equivalent doses of the grains, together with estimates of the environmental dose rate. For grains that have been vertically mixed after deposition (e.g., due to bioturbation), existing dose models may fail to appropriately account for the complexity of the mixing process, thus producing inaccurate age estimates of the original time of deposition of the ‘native’ grains in any particular sample (usually the quantity of most interest). Here we introduce a new dose model, the asymmetric Laplacian mixture model (ALMM), developed for vertically mixed samples with single-grain dose distributions. The approach is based on a continuous statistical mixture that models the displacement of grains in both upward and downward directions. The central dose of the native grains in each sediment sample is estimated by the ALMM, as well as the parameters associated with overdispersion of single-grain dose distributions and the (modelled) mixing process. Using Bayesian methodology, we apply the model to two series of vertically contiguous samples collected at the site of Nawarla Gabarnmang in northern Australia. Independent age estimates obtained from radiocarbon dating of charcoal fragments support the OSL ages for the native grains estimated by the ALMM. Moreover, our study includes sensitivity analyses that show the model is robust to variation in the experimental error of the OSL data, as well as a simulation study that demonstrates the model’s good ability to recover the simulated central dose and its excellent coverage properties. The ALMM is introduced in the context of compound Gaussian distributions, a broadly encompassing statistical framework that includes many of the most commonly used dose models. This unifying and accessible perspective on the statistical modelling of dose distributions will support practitioners in selecting an appropriate model for samples affected by post-depositional mixing, and hopefully stimulate further theoretical developments. A new R package rstanosl is provided that fits the ALMM and other commonly used dose models using Hamiltonian Monte Carlo methods via the Stan programming language.

Fourier-transform-only method for random phase shifting interferometry

An accurate and computationally simple phase shifting interferometry (PSI) method is developed to reconstruct phase maps without a priori knowledge of the phase shift. Previous methods developed for random PSI either do not address general sources of error or require complex iterative processes and increased computational time. Here we demonstrate a novel method that is able to extract the phase using only Fourier transform (FT). With spatial FT analysis, randomly phase-shifted data is reordered to allow performing temporal FT on the intensity, which is a function of the phase shift. Since the entire process, including order analysis and phase calculation, is based only on Fourier analysis, it is rapid, easy to implement, and addresses general sources of error. The method exhibits high performance in experiments containing random phase shifts. Moreover, simulations incorporating common experimental error sources such as random intensity noise, intensity harmonics, and phase shift errors demonstrate that the proposed method performs as good as or better than the state-of-the-art phase reconstruction techniques in terms of accuracy and time.

Comparison and discussion of behavior and pathology of four kinds of cerebral palsy disease models.

Explore the differences in behavioral and pathological manifestations of rat models of cerebral palsy made by different methods and discuss what types of studies these models are suitable for. Behavioral evaluation and pathological section observation were used to observe and evaluate the model. Conclusion: except for the absence of data of bilateral common carotid artery ligation rats, the other three methods could all achieve a successful cerebral palsy disease model for both behavioral and pathological. For researchers, the selection of intraperitoneal infection model in pregnant rats or unilateral ischemia and hypoxia model in infant rats is sufficient to meet the experimental needs, whereas the selection of the combined method for modeling does not show enough advantages, which not only causes the waste of financial and human resources but also increases the possibility of experimental error made by intervention factors.

Selection and Validation of Reference Genes in Sudan Grass (Sorghum sudanense (Piper) Stapf) under Various Abiotic Stresses by qRT-PCR.

Quantitative reverse transcription PCR (qRT-PCR) can screen applicable reference genes of species, and reference genes can be used to reduce experimental errors. Sudan grass (Sorghum sudanense (Piper) Stapf) is a high-yield, abiotic-tolerant annual high-quality forage with a wide range of uses. However, no studies have reported reference genes suitable for Sudan grass. Therefore, we found eight candidate reference genes, including UBQ10, HIS3, UBQ9, Isoform0012931, PP2A, ACP2, eIF4α, and Actin, under salt stress (NaCl), drought stress (DR), acid aluminum stress (AlCl3), and methyl jasmonate treatment (MeJA). By using geNorm, NormFinder, BestKeeper, and RefFinder, we ranked eight reference genes on the basis of their expression stabilities. The results indicated that the best reference gene was PP2A under all treatments. eIF4α can be used in CK, MeJA, NaCl, and DR. HIS3 can serve as the best reference gene in AlCl3. Two target genes (Isoform0007606 and Isoform0002387) belong to drought-stress-response genes, and they are highly expressed in Sudan grass according to transcriptome data. They were used to verify eight candidate reference genes under drought stress. The expression trends of the two most stable reference genes were similar, but the trend in expression for Actin showed a significant difference. The reference genes we screened provided valuable guidance for future research on Sudan grass.

Performance of a combined electrotrophic and electrogenic biofilm operated under long-term, continuous cycling.

Evaluate electrochemically active biofilms as high energy density rechargeable microbial batteries toward providing persistent power in applications where traditional battery technology is limiting (, remote monitoring applications). Here we demonstrated that an electrochemically active biofilm was able to store and release electrical charge for alternating charge/discharge cycles of up to 24h periodicity (50% duty cycle) with no significant decrease in average current density (0.16 ± 0.04 A/m2) for over 600days. However, operation at 24h periodicity for > 50days resulted in a sharp decrease in the current to nearly zero. This current crash was recoverable by decreasing the periodicity. Overall, the coulombic efficiency remained near unity within experimental error (102 ± 3%) for all of the tested cycling periods. Electrochemical characterization here suggests that electron transfer occurs through multiple routes, likely a mixture of direct and mediated mechanisms. These results indicate that bidirectional electrogenic/electrotrophic biofilms are capable of efficient charge storage/release over a wide range of cycling frequency and may eventually enable development of sustainable, high energy density rechargeable batteries.

An Improved Self-Adaptive Flower Pollination-Backpropagation Neural Network for the State of Charge Estimation of Lithium-Ion Batteries with Output Sliding Average Window Strategy

With the rapid development of electric vehicles and green energy sources, the use of backpropagation neural network (BPNN) to precisely estimate the state of charge (SOC) in lithium-ion batteries has become a popular research topic. However, traditionally BPNN has low prediction accuracy and large output fluctuations. To address the shortcomings of BPNN, self-adaptive flower pollination algorithm (SFPA) was proposed to optimize the initial weights and thresholds of BPNN, and an output sliding average window (OSAW) strategy is proposed to smooth SOC outputs in this research, which SOC estimation method is named SFPA-BP-OSAW. In addition, the performance of the newly proposed method is compared with other common related algorithms under different working conditions to verify the effectiveness of SFPA-BP-OSAW. The experimental results show that the mean absolute error of SFPA-BP-OSAW is 0.771% and 0.897%, and the root mean square error is 0.236% and 0.37%, respectively, under HPPC and BBDST working conditions. Experimental data and error analysis show that the method proposed in this paper has fast convergence, high prediction accuracy, and curve smoothness.

An Innovative Experimental Methodology for Testing Anisotropic Permeabilities of Formation Rocks

Abstract The permeability of reservoir rocks is a typical anisotropic property. Accurate testing and characterization of reservoir in situ anisotropic permeability is crucial for geo-energy applications including geothermal energy extraction, hydrocarbon reservoir development, coalbed methane production, and carbon dioxide geological sequestration. In this work, a novel experimental apparatus was designed to more precisely determine the permeability tensor of reservoir rocks. The device can independently apply stresses in different directions to simulate in situ reservoir stress conditions and reservoir temperatures. The experiment can accurately measure the principal components of the permeability tensor in three directions for rock samples while effectively avoiding experimental errors caused by internal structure damage during disassembly. Using the self-developed apparatus, anisotropic permeability tests were conducted on sandstone, shale, and coal samples. The results show that the three-dimensional permeability of rock samples under in situ reservoir stress conditions is lower than under isotropic stress conditions. However, the variation magnitude of the three-dimensional permeability differs between the three rock types because of lithological differences. This confirms the difference in data between the proposed anisotropic permeability test method and other traditional methods. We also observed that for rocks without distinct oriented internal structures like sandstone, anisotropic permeability is more sensitive to (normal) stress changes. In contrast, for rocks with oriented pore structures such as shale and coal, the degree of anisotropic permeability is less sensitive to (normal) stress changes. The proposed novel anisotropic permeability test method obtains more accurate and realistic data under simulated in situ stress conditions compared with existing methods. It can evaluate rock properties and optimize geothermal or hydrocarbon production well designs to improve production efficiency.