Conventional methods for bathymetry inversion based on gravity field data usually adopt gravity anomaly and vertical gravity gradient. Indeed, a gravity gradient tensor (GGT) has six components. Besides the commonly used vertical gravity gradient, the other five components can also contribute to bathymetry inversion, which is investigated in this article. The formulas for the inversion are derived based on the Parker’s formula. In order to provide GGT data for the inversion, vertical deflections and gravity anomalies of Scripps Institution of Oceanography, including north_SWOT_02 (1’), east_SWOT_02 (1’) and grav_SWOT_02 (1’) are firstly used to derive GGT in the study region, i.e., Bay of Bengal. And then, six bathymetric grid models are derived using the six components of the gravity gradients, respectively. The results show that within the study area, the <inline-formula><tex-math notation="LaTeX">${{{\bm{T}}}_{{\bm{yz}}}}$</tex-math></inline-formula> component exhibits the best performance among the bathymetric inversion results derived from the single components of GGT. Combining the inversion results of the six GGT components yields a new bathymetric model—one with higher accuracy than that derived from the single <inline-formula><tex-math notation="LaTeX">${{{\bm{T}}}_{{\bm{yz}}}}$</tex-math></inline-formula> component. Evaluations using ship-borne depth data indicate that, at the test points, the root mean square error of the combined model is 5.24 meters less than that of the <inline-formula><tex-math notation="LaTeX">${{{\bm{T}}}_{{\bm{yz}}}}$</tex-math></inline-formula>-derived model. When GEBCO_2024 depths are treated as the reference (true values), the RMS error of the combined bathymetric model is 14.31 meters less than that of the <inline-formula><tex-math notation="LaTeX">${{{\bm{T}}}_{{\bm{yz}}}}$</tex-math></inline-formula>-derived model.
The infrared scanner (IRS) onboard the HJ-2B satellite is a high-resolution, dual-channel thermal infrared sensor suitable for applications such as land-surface temperature retrieval and smoke detection. Radiometric calibration is a fundamental prerequisite for ensuring the quality and reliability of IRS observation data and is typically performed via two-point (high- and low-temperature) calibration using the instrument’s onboard blackbody. However, the effectiveness of this procedure can be constrained by performance degradation of the calibration hardware and by its frequency of usage. In response to these limitations, this article proposes a refined radiometric cross-calibration method for the HJ-2B/IRS sensor over plateau lakes, which adopts the double-difference method as the technical basis and uses the high-accuracy Terra/MODIS as the reference sensor. Implemented through rigorous screening of calibration sites and sampling points, the method explicitly accounts for viewing geometry, as well as contemporaneous surface and atmospheric conditions. First, calibration points between IRS and MODIS are screened by setting a CV threshold and using the RANSAC algorithm. Next, given the surface and atmospheric conditions at the satellite overpass time, radiances at calibration points with large viewing zenith angles were corrected to their nadir-equivalent values, and a temperature-dependent simulated brightness temperature difference function is constructed, from which the fitted calibration coefficients (FCCs) are derived using the double-difference method. Finally, validation with Landsat-8/TIRS indicates that IRS brightness temperatures calculated by the FCCs deviate less from the TIRS observations than those computed with the official calibration coefficients (OCCs) issued by the China Centre for Resources Satellite Data and Application. Furthermore, when compared with the top-of-atmosphere brightness temperatures derived from forward modeling of in situ measurement data, the IRS at-aperture brightness temperature computed using the FCCs shows mean deviations of −1.04 K and −0.92 K for Band 8 and Band 9, respectively. These values are superior to the corresponding deviations of −1.32 K and −2.43 K obtained using the OCCs. Following a quantitative analysis of various factors influencing the FCCs, the total uncertainty for IRS Band 8 and Band 9 was determined to be below 0.937% and 1.257%, respectively.
The micro-Doppler (μD) characteristics of ballistic targets are crucial for estimating motion and structural parameters, as well as for target recognition. However, existing time-frequency (TF) analysis methods are predominantly nonparametric and suffer from limited resolution, making it challenging to accurately extract μD TF curves. This limitation hampers further applications in this domain. Therefore, under narrowband radar observation conditions, this article proposes a method for μD TF characteristics extraction and scatterer type identification, specifically for smooth-surfaced cone-shaped precession targets. The method first utilizes sliding-window Root-MUSIC to extract the instantaneous μD frequencies of the target. Then, the inverse Radon transform (IRT) and You Only Look Once version 5 algorithm are applied to locate and identify the peaks of cone vertex and cone base after IRT. Based on the peaks, the μD TF trend curves can be reconstructed using the Radon transform (RT). The extracted instantaneous μD frequencies are then associated according to the trend curves, enabling the reconstruction of the μD frequencies for the cone vertex and cone base. Experiments validate the effectiveness and noise robustness of the proposed method. The results demonstrate that the estimation accuracy of the proposed method is independent of the sampling interval and significantly outperforms traditional nonparametric methods.
The levels of amylose and amylopectin in foxtail millet are important factors that influence grain quality. The application of organic fertilizers can affect the ratio of amylose and amylopectin components. These components are typically determined using chemical analysis methods, which are difficult to apply on a large scale for nutrient deficiency diagnosis and do not meet the original intention of precise agricultural development. This study set up five different gradient treatments for organic fertilizer (sheep manure) application. Hyperspectral imaging combined with chemometrics was employed to achieve rapid and non-destructive detection of the content of amylose and amylopectin in foxtail millet flour. The aim of this study was to determine the optimal dosage of organic fertilizers for application. Spectral data preprocessing used multiplicative scatter correction (MSC), and the combined algorithm of competitive adaptive reweighted sampling (CARS), random frog (RF), and iterated retaining informative variables (IRIVs) was employed for key band extraction. Partial least squares regression (PLSR) was then used to establish the prediction model and regression equation, which was used to visualize the two components. Results demonstrated that the key band extraction combined algorithm effectively reduced data dimension without compromising the accuracy of the prediction model. The prediction model for amylose using MSC–RF–IRIV–PLSR exhibited good performance, with the correlation coefficient (R) and root mean square error (RMSE) predicted to be 0.73 and 1.23 g/(100 g), respectively. Similarly, the prediction model for amylopectin using MSC–CARS–IRIV–PLSR also demonstrated good performance, with the R and RMSE values predicted to be 0.59 and 7.34 g/(100 g), respectively. The results of visualization and physicochemical determination showed that the amount of amylopectin accumulation was highest, and the amount of amylose was lowest, under the application of 22.5 t/ha of organic fertilizer. The experimental results offer valuable insights for the rapid detection of nutritional components in foxtail millet, serving as a basis for further research.
Jason Aebischer, Atakan Tugberk Akmete, Riccardo Aliberti
et al.
The kaon physics programme, long heralded as a cutting-edge frontier by the European Strategy for Particle Physics, continues to stand at the intersection of discovery and innovation in high-energy physics (HEP). With its unparalleled capacity to explore new physics at the multi-TeV scale, kaon research is poised to unveil phenomena that could reshape our understanding of the Universe. This document highlights the compelling physics case, with emphasis on exciting new opportunities for advancing kaon physics not only in Europe but also on a global stage. As an important player in the future of HEP, the kaon programme promises to drive transformative breakthroughs, inviting exploration at the forefront of scientific discovery.
Recently, tracking with unmanned aerial vehicle (UAVs) platforms has played significant roles in Earth observation tasks. However, target occlusion remains a challenging factor during the continuous tracking procedure. In particular, incomplete local appearance features can mislead the tracking network to produce inaccurate size and position estimations when the target is occluded. Furthermore, the tracking network lacks sufficient occlusion supervision information, which may lead to template degradation during template updating. To address these challenges, in this article, we design an occlusion-aware tracker with local-global features modeling, which contains two key components, namely the feature intrinsic association module (FIAM) and the feature verification module (FVM). Specifically, the FIAM divides the local features into blocks and utilizes the transformer network to explore the relative relationships among each subblock, which supplements the damaged local target features and assists the modeling for global target features. In addition, the FVM establishes a correlation measurement network between the target and the template. To precisely evaluate the occlusion status, masked samples with occlusion exceeding 50% are selected as negative samples for independent training, which ensures the purity of the target template. Qualitative and quantitative experiments are conducted on publicly available datasets, including UAV20 L, UAV123, and LaSOT. Qualitative and quantitative experiments have demonstrated the effectiveness of the proposed tracking algorithm over the other state-of-the-art trackers in occlusion scenarios.
One of the most abundant Al-containing molecules detected in the interstellar medium (ISM) is AlOH. Over the past several years, there have been various pathways proposed for the formation of AlOH in the ISM, including reactions between AlO and H2 or H2O. However, these pathways include an energetic barrier from a transition state that likely prevents the reaction from progressing efficiently in the low temperature/low pressure environment of the ISM. Recently, a barrierless pathway for formation of AlOH from AlO and AlH has been proposed for the formation of AlOH. Even so, only one of these species really needs to contain an aluminum atom. To account for this, alternative but related pathways reacting the known interstellar molecule AlO with XH and AlH with XO (X = Mg, Si, P, or S) to form AlOH are explored with high accuracy quantum chemical calculations via CCSD(T)-F12b/cc-pVTZ-F12. Each third row element has at least one pair of reactants that lead to exothermic formation of AlOH. These reactions can go on to form other aluminum oxides and aluminum oxide clusters that may, in part, lead to the formation of interstellar dust grains.
Deep learning (DL) techniques have been widely used in prestack three-parameter inversion to address its ill-posed problems. Among these DL techniques, Multi-task learning (MTL) methods can simultaneously train multiple tasks, thereby enhancing model generalization and predictive performance. However, existing MTL methods typically adopt heuristic or non-heuristic approaches to jointly update the gradient of each task, leading to gradient conflicts between different tasks and reducing inversion accuracy. To address this issue, we propose a semi-supervised temporal convolutional network (STCN) based on Nash equilibrium (Nash-MTL-STCN). Firstly, temporal convolutional networks (TCN) with non-causal convolution and convolutional neural networks (CNNs) are used as multi-task layers to extract the shared features from partial angle stack seismic data, with CNNs serving as the single-task layer. Subsequently, the feature mechanism is utilized to extract shared features in the multi-task layer through hierarchical processing, and the gradient combination of these shared features is treated as a Nash game for strategy optimization and joint updates. Ultimately, the overall utility of the three-parameter is maximized, and gradient conflicts are alleviated. In addition, to enhance the network's generalization and stability, we have incorporated geophysical forward modeling and low-frequency models into the network. Experimental results demonstrate that the proposed method overcomes the gradient conflict issue of the conventional MTL methods with constant weights (CW) and achieves higher precision than four widely used non-heuristic MTL methods. Further field data experiments also validate the method's effectiveness.
The paper aims to demonstrate how the measurements of different species of cosmic ray flux can lead to a meaningful physical inference. We want to show when and how it is possible to path the way from measurement to physical inference and how we can prove that measurements are not artifacts or equipment failures but manifestations of a new physical phenomenon.
ABSTRACT Our world is wonderful because of the normal but negligibly small baryonic part (i.e. atoms) although unknown dark matter and dark energy dominate the Universe. A stable atomic nucleus could be simply termed as ‘strong matter’ since its nature is dominated by the fundamental strong interaction. Is there any other form of strong matter? Although nuclei are composed of 2-flavoured (i.e. up and down flavours of valence quarks) nucleons, it is conjectured that bulk strong matter could be 3-flavoured (with additional strange quarks) if the baryon number exceeds the critical value, Ac in which case quarks could be either free (so-called strange quark matter) or localized (in strangeons, coined by combining ‘strange nucleon’). Bulk strong matter could be manifested in the form of compact stars, cosmic rays, and even dark matter. This trinity will be explained in this brief review that may impact dramatically on today’s physics, particularly in the era of multi-messenger astronomy after the discovery of gravitational wave. GRAPHICAL abstract
The standard cosmological model ($\Lambda CDM$) assumes that everything started in a singular Big Bang out of Cosmic Inflation, a mysterious form of modern Aether (the inflaton). Here we look for direct observational evidence for such beginning in two recent measurements: 1) cosmic acceleration, something $\Lambda CDM$ attributes to Dark Energy (DE), 2) discordant measurements for $H_0$ and anomalies in the CMB. We find here that observed variations in $H_0$ correspond to large metric perturbations that are not consistent with the simplest models of Inflation or DE in the $\Lambda CDM$ paradigm. Together, these observations indicate instead that cosmic expansion could originate from a simple gravitational collapse and bounce. We conjecture that such bounce is trigger by neutron degeneracy at GeV energies. This new paradigm explains the heavens above using only the known laws of Physics, without any new Aether, DE or Inflation.
The cooling storage ring (CSR) external-target experiment (CEE) is a spectrometer running at the Heavy Ion Research Facility (HIRFL) at Lanzhou. The CEE is the first large-scale nuclear physics experimental device by China to operate in the fixed-target mode with an energy of 1 GeV. The purpose of the CEE is to study the properties of dense nuclear matter. CEE uses a multi-gap resistive plate chamber (MRPC) as its internal time-of-flight (iTOF) detector for the identification of final-state particles. An iTOF-MRPC prototype with 24 gaps was designed to meet the requirements of CEE, and the readout electronics of the prototype use the FPGA-based time digitization technology. Using cosmic ray tests, the time resolution of the iTOF prototype was found to be approximately 30 ps. In order to further understand how to improve the time resolution of MRPC, ANSYS HFSS was used to simulate the signal transmission process in MRPC. The main factors affecting the timing performance of the MRPC and, accordingly, the optimization scheme are presented.
Flexural elastic waves and sound in solids are of great interest in wide-ranging contexts such as ultrasound in plates, geophysics, ocean engineering, aerospace and automotive structures, and musical acoustics. Despite bending waves being the most important elastic waves for such surface structures, their propagation in the presence of the inevitable non-uniformity is poorly understood. Here we show the branching and focusing behaviour of highly dispersive flexural waves travelling in elastic plates of non-uniform thickness. The thickness profile has isotropically correlated spatial randomness. The correlation length is much larger than the wavelength. The location of wave focusing shows a scaling relationship with randomness, which is consistent with those previously reported in other random media. We show this analytically and numerically. This suggests a universality in the scaling between the location of wave focusing with randomness and the correlation length, regardless of the physics of the waves in question. Despite the relevance of flexural elastic waves to many diverse physical systems, modelling their propagation is non-trivial. Here, branching and focusing of highly dispersive flexural waves in heterogeneous elastic plates is described numerically and analytically.
Muography is a novel imaging technology based on particle physics instrumentation to reveal density structure of hill-sized objects. The cosmic muon flux is attenuated while penetrating into the ground, thus the differential local flux correlates with the overburden density-length. Underground muography exploits the close-to-zenith flux, while main challenges became portability, low power consumption, and robustness against the out-of-the-laboratory environment. Various fields could benefit from this non-invasive imaging, eg. speleology, mining, archeology, or industry. Portable gaseous tracking detector systems have been designed, built, and successfully used in several underground locations. This paper presents the designed portable muography systems, the main requirements, and measurement campaigns for calibration, natural caves, and cultural heritage.
Construction of future Muon Collier (or dedicated [Formula: see text]-ring) tangential to the energy frontier [Formula: see text] colliders will give opportunity to realize [Formula: see text] and [Formula: see text] collisions at multi-TeV center-of-mass energies with sufficiently high luminosities. Obviously, such colliders will essentially enlarge the physics search potential of corresponding muon and hadron colliders for both the SM (especially for clarifying QCD basics and confinement hypothesis) and BSM phenomena. In addition, they will provide parton distribution functions for adequate interpretation of energy frontier [Formula: see text] colliders’ and cosmic ray experiments data. This paper is devoted to review of main parameters of [Formula: see text] colliders proposed until now.
Cosmological Collider Physics gives us the opportunity to probe high-energy physics from observing the spacetime fluctuations generated during inflation imprinted on the cosmic microwave background. In other words, it is a method to investigate physics on energy scales that cannot be reached by terrestrial accelerators by means of precise observations of the universe. In this paper, we focus on the case where the GUT scale is close to the energy scale of inflation, and calculate three point function of inflaton by exchanging the Higgs boson in GUT at tree level. The results are found to be consistent with the current observed restrictions on non-Gaussianity without a drastic fine tuning of parameters, and it might be possible to detect the signature of the Higgs boson in GUT by 21cm spectrum, future LSS and future CMB depending on our model parameters.
New neutrino interactions beyond the Standard Model (BSM) have been of much interest in not only particle physics but also cosmology and astroparticle physics. We numerically investigate the time delay distribution of astrophysical neutrinos that interact with the cosmic neutrino background. Using the Monte Carlo method, we develop a framework that enables us to simulate the time-dependent energy spectra of high-energy neutrinos that experience even multiple scatterings en route and to handle the sharp increase in the cross section at the resonance energy. As an example, we focus on the case of secret neutrino interactions with a scalar mediator. While we find the excellent agreement between analytical and simulation results for small optical depths, our simulations enable us to study optically thick cases that are not described by the simplest analytic estimates. Our simulations are used to understand effects of cosmological redshifts, neutrino spectra and flavors. The developments will be useful for probing BSM neutrino interactions with not only current neutrino detectors such as IceCube and Super-Kamiokande but also future neutrino detectors such as IceCube-Gen2 and Hyper-Kamiokande.
Over the last two decades, the possibility of using RPCs in outdoors systems has increased considerably. Our group has participated in this effort having installed several systems and continues to work on their optimization, while simultaneously studying and developing new approaches that can to use of RPCs in outdoor applications. In particular, some detectors were deployed in the field at the Pierre Auger Observatory in 2019 remained inactive, awaiting the commissioning of support systems. During the pandemic the detectors were left without gas flow for more than two years, but were recently reactivated with no major problems. The LouMu project combines particle physics and geophysics in order to map large geologic structures, using Muon Tomography. The development of the RPC system used and the data from the last two years will be presented. Finally, recent advances in a large area (1 m2) double gap-sealed RPC will be presented.