Motion Field Research Articles

Influence of Physical Characteristics of Earthquake Input Model on Seismic Response of Hardfill Dam

ABSTRACT To elucidate the influence of physical characteristics of earthquake input models on seismic responses of Hardfill dams, three earthquake input models are selected to perform investigations. First, the theoretical basis of earthquake input models is presented, and the radiation-damping effect and the complex wavefield effect derived from the physical characteristics are clarified. Then, the seismic response of a Hardfill dam under different earthquake input models is investigated, by taking the Oyuk dam as an example. Finally, the influence of the radiation-damping effect and the complex wavefield effect on the seismic response of the Hardfill dam are revealed quantificationally. The results show that only the complex wavefield model can accurately capture characteristics of the wavefield and the motion field. The radiation-damping effect significantly reduces the seismic response, while the complex wavefield effect increases it in most cases.

LARES-2 contribution to global geodetic parameters from the combined LAGEOS-LARES solutions

LARES-2 is a new geodetic satellite designed for high-accuracy satellite laser ranging. The orbit altitude of LARES-2 is similar to that of LAGEOS-1, whereas the inclination angle of 70° complements the LAGEOS-1 inclination of 110°; hence, both satellites form the butterfly configuration for the verification of the Lense–Thirring effect. Although the major objective of LARES-2 is testing general relativity, LARES-2 substantially contributes to geodesy in terms of the realization of terrestrial reference frames, recovery of the geocenter motion, pole coordinates, length-of-day, and low-degree gravity field coefficients. We analyze the first 1.5 years of LARES-2 data and test different empirical orbit models for LARES-2 with and without co-estimating low-degree gravity field coefficients to find the best combination strategy with LAGEOS satellites. We found that LARES-2 orbit determination is more accurate than that of LAGEOS-1/2 due to a different satellite construction consisting of a solid sphere with no inner structure. Neither the correction for D0 nor the empirical once-per-revolution along-track accelerations SC/SS have to be estimated for LARES-2 when co-estimating gravity field coefficients. The only empirical parameter needed for LARES-2 is the constant along-track acceleration S0 to compensate for the Yarkovsky–Schach effect. On the contrary, for LAGEOS-1/2, the non-gravitational perturbations affect C30 and Z geocenter estimates when once-per-revolution parameters are not estimated. LARES-2 does not face this issue. LARES-2 improves the formal errors of the Z geocenter component by up to 59% and C20 by up to 40% compared to the combined LAGEOS-1/2 solutions and provides C30 estimates unaffected by thermal orbit modeling issues.

Prospective motion correction for and susceptibility mapping using spherical navigators.

To perform prospective motion correction (PMC) for improved and susceptibility mapping using a purely navigator-based approach. Spherical navigators (SNAVs) were combined with an additional FID readout for simultaneous measurement of motion and zeroth-order field shifts. The resulting FIDSNAVs were interleaved for PMC of a multi-echo gradient echo sequence with retrospective correction. Experiments were performed on a 3T scanner with a 32-channel head coil. Performance was assessed in five volunteers with motion prompts derived from real unintentional motion trajectories. At short TEs, PMC alone was sufficient to achieve good image quality; at longer TEs, retrospective correction was often just as important for artifact reduction as motion correction. Both PMC and retrospective correction reduced error in and susceptibility maps for all participants. Residual artifacts were observed in the most severe motion case. Combining SNAVs with an additional FID readout enables simultaneous motion and field correction with no additional hardware requirements, improving the fidelity of quantitative mapping in the presence of motion.

Three-Dimensional Phenotyping Pipeline of Potted Plants Based on Neural Radiation Fields and Path Segmentation.

Precise acquisition of potted plant traits has great theoretical significance and practical value for variety selection and guiding scientific cultivation practices. Although phenotypic analysis using two dimensional(2D) digital images is simple and efficient, leaf occlusion reduces the available phenotype information. To address the current challenge of acquiring sufficient non-destructive information from living potted plants, we proposed a three dimensional (3D) phenotyping pipeline that combines neural radiation field reconstruction with path analysis. An indoor collection system was constructed to obtain multi-view image sequences of potted plants. The structure from motion and neural radiance fields (SFM-NeRF) algorithm was then utilized to reconstruct 3D point clouds, which were subsequently denoised and calibrated. Geometric-feature-based path analysis was employed to separate stems from leaves, and density clustering methods were applied to segment the canopy leaves. Phenotypic parameters of potted plant organs were extracted, including height, stem thickness, leaf length, leaf width, and leaf area, and they were manually measured to obtain the true values. The results showed that the coefficient of determination (R2) values, indicating the correlation between the model traits and the true traits, ranged from 0.89 to 0.98, indicating a strong correlation. The reconstruction quality was good. Additionally, 22 potted plants were selected for exploratory experiments. The results indicated that the method was capable of reconstructing plants of various varieties, and the experiments identified key conditions essential for successful reconstruction. In summary, this study developed a low-cost and robust 3D phenotyping pipeline for the phenotype analysis of potted plants. This proposed pipeline not only meets daily production requirements but also advances the field of phenotype calculation for potted plants.

Computational role of homogeneous–heterogeneous chemical reactions and a mixed convective ternary hybrid nanofluid in a vertical porous microchannel

Abstract This article mainly scrutinizes the heat transfer and flow characteristics of a mixed convection ternary hybrid nanofluid in a porous microchannel considering the catalytic chemical reaction and nonuniform heat absorption/generation. Using appropriate similarity transformations, the modeled equations are converted into reduced ones and then solved via the Runge–Kutta–Fehlberg 4th/5th order method. To strengthen this analysis, the convection mechanism has been deployed. The effect of pertinent physical parameters on the fluid motion and thermal field is displayed, including some important engineering variables like the Nusselt number, Sherwood number, and drag force. The novel outcomes display that the flow reduces with porous permeability and nanoparticle volume fraction. The temperature of the nanofluid improves with nonuniform heat absorption/generation. The concentration decreases in the presence of both homogeneous and heterogeneous reaction intensities. The heat transfer rate enhances for the Eckert number, and a similar influence on the mass transfer rate is noticed for homogeneous reaction parameters. Further, the drag force declines for the Grashof number. The outcomes show that, in all cases, the ternary hybrid nanofluid shows a greater impact than the nanofluid. The attained findings represent applications in the era of cooling and heating systems, thermal engineering, and energy production.

Water-Stable Magnetic Lipiodol Micro-Droplets as a Miniaturized Robotic Tool for Drug Delivery.

Magnetic microrobots, designed to navigate the complex environments of the human body, show promise for minimally invasive diagnosis and treatment. However, their clinical adoption faces hurdles such as biocompatibility, precise control, and intelligent tracking. Here a novel formulation (referred to water-stable magnetic lipiodol micro-droplets, MLMD), integrating clinically approved lipiodol, gelatin, and superparamagnetic iron oxide nanoparticles (SPION) with a fundamental understanding of the structure-property relationships is presented. This formulation demonstrates multiple improved properties including flowability, shape adaptability, efficient drug loading, and compatibility with digital subtraction angiography (DSA) imaging in both in vitro and in vivo experiments. This enables the MLMD as a versatile tool for image-guided therapy, supported by a close-looped magnetic navigation system featuring artificial intelligence (AI)-driven visual feedback for autonomous control. The system effectively performs navigational tasks, including pinpointing specific locations of MLMD, recognizing and avoiding obstacles, mapping and following predetermined paths, and utilizing magnetic fields for precise motion planning to achieve visual drug delivery. The MLMD combines magnetic actuation with an AI-directed close-looped navigation, offering a transformative platform for targeted therapeutic delivery.

Motion and magnetic field inhomogeneity correction techniques for chemical exchange saturation transfer (CEST) MRI: A contemporary review.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful imaging technique sensitive to tissue molecular composition, pH, and metabolic processes in situ. CEST MRI uniquely probes the physical exchange of protons between water and specific molecules within tissues, providing a window into physiological phenomena that remain invisible to standard MRI. However, given the very low concentration (millimolar range) of CEST compounds, the effects measured are generally only on the order of a few percent of the water signal. Consequently, a few critical challenges, including correction of motion artifacts and magnetic field (B0 and B1 +) inhomogeneities, have to be addressed in order to unlock the full potential of CEST MRI. Motion, whether from patient movement or inherent physiological pulsations, can distort the CEST signal, hindering accurate quantification. B0 and B1 + inhomogeneities, arising from scanner hardware imperfections, further complicate data interpretation by introducing spurious variations in the signal intensity. Without proper correction of these confounding factors, reliable analysis and clinical translation of CEST MRI remain challenging. Motion correction methods aim to compensate for patient movement during (prospective) or after (retrospective) image acquisition, reducing artifacts and preserving data quality. Similarly, B0 and B1 + inhomogeneity correction techniques enhance the spatial and spectral accuracy of CEST MRI. This paper aims to provide a comprehensive review of the current landscape of motion and magnetic field inhomogeneity correction methods in CEST MRI. The methods discussed apply to saturation transfer (ST) MRI in general, including semisolid magnetization transfer contrast (MTC) and relayed nuclear Overhauser enhancement (rNOE) studies.

CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network

The optical flow algorithm (OF) is one the main methods for calculating image velocity field and has many applications in space weather. Most OF calculations are applied to the motion of labeled rigid objects and are not suitable for velocity detection of high-energy particles, such as in a coronal mass ejection (CME). Fluctuations in exposure time and the influence of space weather will lead to inconsistent brightness of the same feature point at different times. To address this problem, we propose an unsupervised multiscale optical flow network based on Vision Transformer, named UTFlowNet. The network comprises a multiscale feature extraction module and a coarse-to-fine global optical flow calculation module. The movement of high-energy particles emitted during a CME eruption follows certain physical rules. Therefore, we apply fluid motion–based loss functions to analyze the motion of high-energy particles more effectively, addressing the problem of CME motion field extraction. Our method can be applied to the real-time automatic extraction of a CME’s velocity field and performs well with inconsistent brightness, large-scale motion, and strong CME noise. Additionally, we can estimate subpixel level fine-grained velocity. Our model may be affected by overfitting during cross–data set inference, so we encourage performing a small amount of transfer learning on new data sets to mitigate this issue. In order to verify the accuracy of our method, we conducted experiments and verification on the Solar and Heliospheric Observatory LASCO C2 data and the High Altitude Observatory MLSO data. We constructed a large-scale displacement simulation data set based on LASCO C2 data and tested on it, achieving the best results.

On Hysteresis In A Variable Pitch Fan Transitioning To Reverse Thrust Mode And Back

Abstract A novel hysteresis phenomenon during the transition to and back from the reverse thrust mode in a Variable Pitch Fan (VPF) is identified and characterised in this work. This is done by using a three-dimensional (3D) fully transient Unsteady Reynolds averaged Navier?Stokes (URANS) with the transitioning fan blade aerofoils simulated by an adaptation of the mesh displacement method. The VPF is modelled to be transitioning in a modern 40000 lbf geared high bypass ratio turbofan engine architecture at "Approach Idle" engine power setting in a typical twin-engine airframe with the flaps, slats, and spoilers set for an aircraft touchdown airspeed of 140 knots. The transition to reverse thrust mode involves flow starvation into the engine, formation of recirculation zones in the bypass duct and the establishment of the reverse stream, all of which occurs in the opposing presence of the free stream flow at aircraft touchdown velocity. The transition back to forward flow mode involves the gradual re-establishment of the free stream which is opposed by the presence of the reverse stream within the engine. It is quantified that in the transition to reverse thrust, the blockage develops with a larger time delay than the disappearance of the blockage during the transition back due to the interplay of the temporal dynamics of fan blade motion and flow field response. The hysteresis phenomena described in this work are critical in properly developing control schedules to adapt for potential bi-stable flow field development during the landing run.

Saline based microfluidic soft pressure sensor utilizing a three-dimensional focused electric field for motion and healthcare monitoring

This paper introduces the ‘Spatially Focused Saline-based Pressure Sensor (SF-SaPS)', a novel soft microfluidic pressure sensor featuring a distinctive three-dimensional focusing structure. By critically reducing the cross-sectional area of the microchannel at the focused structure, the SF-SaPS achieves excellent sensitivity to pressure within the sensing region. With the spatially focused region, the SF-SaPS could detect a wide range of pressure from gentle touches to human weight, which is typically unachievable with low-conductivity sensing media such as saline, a medium inherently safe for human use. Beyond its sensitivity, the SF-SaPS exhibits sensing performance and stability comparable with conventional liquid metal-based pressure sensors. Our sensor demonstrated minimal signal drift, a rapid response time of 70 ms under cyclic loading, and 20-day long-term stability tests immersed in water. Additionally, the sensor possesses a transparency advantage unattainable by liquid metal sensors as we utilized transparent polymers and saline. A unique advantage of the SF-SaPS lies in its selective spatial and mechanical sensitivity; as the electrical resistance is highly dependent on changes in the cross-sectional area of the microchannels, the sensor has superior pressure sensitivity compared to bending and strain. Finally, various application examples highlight the SF-SaPS's advantages. By configuring the sensor in a two-axis array, the SF-SaPS facilitates pressure mapping across a plane. Additionally, it proves effective in healthcare monitoring, from radial pulse to finger movements. In conclusion, the SF-SaPS's combination of performance, stability, biocompatibility, and transparency positions this sensor as a versatile tool for applications extending beyond healthcare, as demonstrated in this study.

Influence of scalar field in massive particle motion in JNW spacetime

In this paper, we investigated the motion of massive particles in the presence of scalar and gravitational fields, particularly focusing on the Janis-Newman-Winicour (JNW) naked singularity solution. It is shown that the innermost stable circular orbit radius strongly depends on scalar coupling parameter. Additionally, we explored the radiation reaction effects on particle dynamics, incorporating a reaction term into the motion equations. Numerical simulations indicated minimal impact on particle trajectories from radiation reaction. We also examined the oscillatory motion of particles around compact objects in the JNW spacetime, focusing on radial and vertical oscillations. Our analysis indicated that the scalar field’s coupling parameter and the spacetime deformation parameter n significantly alter the fundamental frequencies of these oscillations. Furthermore, we studied quasiperiodic oscillations (QPOs) in x-ray binaries, using the relativistic precession model to analyze upper- and lower-frequency relationships. Our results indicated that increasing parameters (n and gs) shifts the frequency ratio of 3∶2 QPOs closer to the naked singularity, with n decreasing and gs increasing both frequencies. Finally, we analyzed QPO data from four selected x-ray binary systems using Markov chain Monte Carlo analysis to constrain JNW parameters. Our findings provided insights into the mass, coupling, and deformation parameter for each system, enhancing our understanding of compact object dynamics in strong gravitational fields. Published by the American Physical Society 2024

Magnetohydrodynamic Motions of Oldroyd-B Fluids in Infinite Circular Cylinder That Applies Longitudinal Shear Stresses to the Fluid or Rotates Around Its Axis

Two classes of magnetohydrodynamic (MHD) motions of the incompressible Oldroyd-B fluids through an infinite cylinder are analytically investigated. General expressions are firstly established for shear stress and velocity fields corresponding to the motion induced by longitudinal shear stress on the boundary. For validation, the expression of the shear stress is determined by two different methods. Using an important remark regarding the governing equations for shear stress and fluid velocity corresponding to the two different motions, this expression is then used to provide the dimensionless velocity field of the MHD motion of the same fluids generated by a cylinder that rotates around its symmetry axis. Obtained results can generate exact solutions for any motion of this kind of Oldroyd-B fluids. Consequently, both types of motions are completely solved. For illustration, some case studies are considered, and adequate velocity fields are provided. The steady-state components of these velocities are presented in different forms whose equivalence is graphically proved. The influence of the magnetic field on the fluid behavior is graphically investigated. It was found that the fluid flows slower, and a steady state is earlier reached in the presence of a magnetic field. The fluid behavior when shear stress is given on the boundary is also investigated.

An Optimization Design of Piezoelectric Hair Sensor for Oscillatory Flow Detection

Abstract Biological hair is widely found in nature, and they are responsible for sensing and responding to environmental stimuli in living organisms. By simulating biological hair characteristics, they develop hair flow sensor to achieve high sensitivity detection of environmental factors such as small motion and fluid flow field. Output signal is the key indicator of hair flow sensor, and the improvement of output signal is important to the design of hair flow sensor. The existing hair flow sensor sensing structure is generally straight hair, and the output signal is limited by the structure, and the response is small. Using the direct piezoelectric fiber as the initial configuration, we form a new piezoelectric curved fiber by modeling the secondary spline curve and control point. We propose an optimization model for piezoelectric functional hair design using axial strain as a target function. At 100Hz and 500Hz, the output voltage of the optimized model is much higher than that of straight, 10 times and 7 times that of straight, respectively; An optimized curved hair configuration is obtained in a specific frequency band from 1 Hz to 500 Hz, whose average voltage magnitude of 3.1×10−3 V is 4 times greater than that of the straight hair of 7.8×10−4 V with the same size. The curved hair flow sensor breaks the output limitation of traditional straight hair configuration.

TEDR: A spatiotemporal attention radar extrapolation network constrained by optical flow and distribution correction

In recent years, deep learning has been widely applied to meteorological radar extrapolation due to the shortcomings of traditional optical flow methods in predicting the genesis and dissipation of radar echoes. However, it still faces challenges in addressing issues of clarity and overall intensity attenuation caused by uncertainty. This study implemented a dual-path spatiotemporal attention network that integrates optical flow techniques by employing intra-frame static attention and inter-frame dynamic attention, which could simulate motion fields and the overall intensity distribution of radar echoes separately. Our approach effectively resolve the issues of systematic intensity attenuation and clarity degradation introduced by deep learning methods. Through the comparisons of key metrics such as MSE, SSIM, CSI20, CSI30, and CSI40, the results demonstrated significant improvements over traditional approaches, particularly in CSI30 and CSI40, where the metrics improved by more than 35 %.

A unified feature-motion consistency framework for robust image matching

Establishing reliable feature matches between a pair of images in various scenarios is a long-standing open problem in photogrammetry. Attention-based detector-free matching with coarse-to-fine architecture has been a typical pipeline to build matches, but the cross-attention module with global receptive field may compromise the structural local consistency by introducing irrelevant regions (outliers). Motion field can maintain structural local consistency under the assumption that matches for adjacent features should be spatially proximate. However, motion field can only estimate local displacements between consecutive images and struggle with long-range displacements estimation in large-scale variation scenarios without spatial correlation priors. Moreover, large-scale variations may also disrupt the geometric consistency with the application of mutual nearest neighbor criterion in patch-level matching, making it difficult to recover accurate matches. In this paper, we propose a unified feature-motion consistency framework for robust image matching (MOMA), to maintain structural consistency at both global and local granularity in scale-discrepancy scenarios. MOMA devises a motion consistency-guided dependency range strategy (MDR) in cross attention, aggregating highly relevant regions within the motion consensus-restricted neighborhood to favor true matchable regions. Meanwhile, a unified framework with hierarchical attention structure is established to couple local motion field with global feature correspondence. The motion field provides local consistency constraints in feature aggregation, while feature correspondence provides spatial context prior to improve motion field estimation. To alleviate geometric inconsistency caused by hard nearest neighbor criterion, we propose an adaptive neighbor search (soft) strategy to address scale discrepancy. Extensive experiments on three datasets demonstrate that our method outperforms solid baselines, with AUC improvements of 4.73/4.02/3.34 in two-view pose estimation task at thresholds of 5°/10°/20° on Megadepth test, and 5.94% increase of accuracy at threshold of 1px in homography task on HPatches datasets. Furthermore, in the downstream tasks such as 3D mapping, the 3D models reconstructed using our method on the self-collected SYSU UAV datasets exhibit significant improvement in structural completeness and detail richness, manifesting its high applicability in wide downstream tasks. The code is publicly available at https://github.com/BunnyanChou/MOMA.

Shallow Convective Heating in Weak Temperature Gradient Balance Explains Mesoscale Vertical Motions in the Trades

AbstractEarth's climate sensitivity depends on how shallow clouds in the trades respond to changes in the large‐scale tropical circulation with warming. In canonical theory for this cloud‐circulation coupling, it is assumed that the clouds are controlled by the field of vertical motion on horizontal scales larger than the convection's depth ( 1 km). This assumption has been challenged both by recent in situ observations, and idealized large‐eddy simulations (LESs). Here, we therefore bring together the recent observations, new analysis from satellite data, and a 40‐day, large‐domain ( km2) LES of the North Atlantic from the 2020 EUREC4A field campaign, to study the interaction between shallow convection and vertical motions on scales between 10 and 1,000 km (mesoscales), in settings that are as realistic as possible. Across all data sets, the shallow mesoscale vertical motions are consistently represented, ubiquitous, frequently organized into circulations, and formed without imprinting themselves on the mesoscale buoyancy field. Therefore, we use the weak‐temperature gradient approximation to show that between at least 12.5–400 km scales, the vertical motion balances heating fluctuations in groups of precipitating shallow cumuli. That is, across the mesoscales, shallow convection controls the vertical motion in the trades, and does not simply adjust to it. In turn, the mesoscale convective heating patterns appear to consistently grow through moisture‐convection feedback. Therefore, to represent and understand the cloud‐circulation coupling of trade cumuli, the full range of scales between the synoptics and the hectometer must be included in our conceptual and numerical models.

Basics of modern modeling and expansion of the relativity theory of time in the field of classical physics

Throughout history, many scientists considered time as the result of changing the world and believed that time is not true. Among those who say that time is not true, Einstein is the only one who was able to mathematically explain the relativity of time in the field of geometry (space time) and present his equations in relativistic physics. Although Einstein, like other scientists, did not provide a clear definition of time, he presented the relativity of time well. He showed that time is not independent of space and bends along with space. Also, Einstein used the speed of light to convert mass into energy to introduce the law of mass–energy equivalence. Currently, basic laws such as conservation of mass, conservation of energy and equivalence of mass and energy have been presented. Recently, due to the importance of time in the development of science, especially in the field of water and chemistry, “timemass equivalence law” has also been presented (by the author). In this research, with the aim of expanding the relativity of time in the flows of mass and energy (not the field of motion and geometry), while presenting new definitions of “phenomenon”, “time” and “specific speed of transformation”, in addition to the theory of “mass equivalence law” “Time” was completed, the general equations of equivalence of energy time—and timemass were introduced. Then, to check the results more accurately, the general masstime equation (in this study, absorption kinetics) by performing surface absorption experiments of heavy metals (Fe + 2, Pb + 2, Zn + 2, Ni + 2, Cd + 2, Cu + 2)) was investigated by the adsorbents of green walnut shell (GWH) and its biochar (GWHB), and the results are tested in different ways.

Asymmetrical Solar Wind Deflection in the Martian Magnetosheath

AbstractAs incident solar wind encounters the martian upper atmosphere, it undergoes deflection particularly in the magnetosheath. However, the plasma flow exhibits asymmetrical distribution features within this transition region, which is investigated by employing a three‐dimensional Hall magnetohydrodynamic (MHD) model from an energy transfer perspective in this study. Simulation results reveal that solar wind protons transfer momentum to ionospheric heavy ions through motional electric field in the hemisphere where the motional electric field points outward from the planet. In the opposite hemisphere, solar wind flow tends to be effectively accelerated by ambipolar and Hall electric fields. The distinct dynamics of solar wind protons in both hemispheres result in the asymmetrical deflection. Furthermore, the extent of asymmetry grows as the cross‐flow component of the upstream interplanetary magnetic field increases, but diminishes as the density of the solar wind proton increases, contingent upon the energy effectively acquired from ambipolar and Hall electric fields.

Space-time Fourier ptychography for in vivo quantitative phase imaging

Quantitative phase imaging of living biological specimens is challenging due to their continuous movement and complex behavior. Here, we introduce space-time Fourier ptychography (ST-FP), which combines a fast Fourier ptychography (FP) model based on compressive sensing with space-time motion priors for joint reconstruction of quantitative phase, intensity, and motion fields across consecutive frames. Using the same input data as compressive sensing FP, ST-FP increases the space-bandwidth-time product of the reconstructed complex image sequence while leveraging redundant temporal information to achieve robust reconstruction performance. The efficacy of this approach is demonstrated across various applications, particularly in observing living microorganisms undergoing rapid morphological changes and reconstructing amplitude and phase targets in motion. The improved phase retrieval capability of ST-FP enables digital refocusing, facilitating comprehensive three-dimensional analysis of microorganisms. This advancement paves the way for enhanced visualization of cellular processes, developmental biology studies, and investigations into life mechanics at the microscopic level.

Two‐Spacecraft Observations of Asymmetric Martian Bow Shock: Conjunctions of Tianwen‐1 and MAVEN

AbstractThe Martian bow shock has been extensively studied through magnetic field and plasma instrument observations from various Mars space missions. However, prior investigations primarily involve statistical analyses based on single spacecraft crossings, leaving the asymmetry of the Martian bow shock unstudied through simultaneous two‐spacecraft observations. In this study, utilizing simultaneous observations from Tianwen‐1 and MAVEN, we examine the instantaneous asymmetry of the Martian bow shock. We present the asymmetry of the Martian bow shock in the Mars‐Solar‐Electric and Mars‐Solar‐Orbital reference frames, possibly influenced by the solar wind motional electric field and Martian crustal magnetic field, respectively. Moreover, we suggest that the bow shock exhibits increased asymmetry under stronger solar wind motional electric field conditions. This study highlights how a two‐point observation approach offers valuable insights into the dynamic behavior of the Martian induced magnetosphere.