The Great Pyramid, or Khufu’s Pyramid, was built on the Giza plateau in Egypt during the fourth dynasty by the pharaoh Khufu (Cheops), who reigned from 2509 bc to 2483 bc. Despite being one of the oldest and largest monuments on Earth, there is no consensus about how it was built. To understand its internal structure better, we imaged the pyramid using muons, which are by-products of cosmic rays that are only partially absorbed by stone. The resulting cosmic-ray muon radiography allows us to visualize the known and any unknown voids in the pyramid in a non-invasive way. Here we report the discovery of a large void (with a cross-section similar to that of the Grand Gallery and a minimum length of 30 metres) situated above the Grand Gallery. This constitutes the first major inner structure found in the Great Pyramid since the nineteenth century. The void, named ScanPyramids’ Big Void, was first observed with nuclear emulsion films installed in the Queen’s chamber, then confirmed with scintillator hodoscopes set up in the same chamber and finally re-confirmed with gas detectors outside the pyramid. This large void has therefore been detected with high confidence by three different muon detection technologies and three independent analyses. These results constitute a breakthrough for the understanding of the internal structure of Khufu’s Pyramid. Although there is currently no information about the intended purpose of this void, these findings show how modern particle physics can shed new light on the world’s archaeological heritage.
Muhammad Ahmad, Francesco Mauro, Rana Aamir Raza
et al.
Hyperspectral image (HSI) classification presents inherent challenges due to high spectral dimensionality, significant domain shifts, and limited availability of labeled data. To address these issues, we propose a novel Active Transfer Learning (ATL) framework built upon a spatial-spectral transformer (SST) backbone. The framework integrates multistage transfer learning with an uncertainty-diversity-driven active learning mechanism that strategically selects highly informative and diverse samples for annotation, thereby significantly reducing labeling costs and mitigating sample redundancy. A dynamic layer freezing strategy is introduced to enhance transferability and computational efficiency, enabling selective adaptation of model layers based on domain shift characteristics. Furthermore, we incorporate a self-calibrated attention mechanism that dynamically refines spatial and spectral weights during adaptation, guided by uncertainty-aware feedback. A diversity-promoting sampling strategy ensures broad spectral coverage among selected samples, preventing overfitting to specific classes. Extensive experiments on benchmark cross-domain HSI datasets demonstrate that the proposed SST–ATL framework achieves superior classification performance compared to conventional approaches.
Tropical cyclones (TCs) are highly destructive weather phenomena that cause extensive human and economic losses in affected regions. Accurate prediction of tropical cyclone intensity (TCI) is crucial for disaster preparedness and mitigation. Traditional TCI forecasting methods fail to extract nonlinear features and suffer from high computation costs. In recent years, deep learning methods have been increasingly used to address this challenge. However, current approaches often underutilize meteorological variables and satellite cloud imagery, and fail to capture correlations between multimodal data. In this article, we propose TCIque, a sequence-to-sequence model specifically designed for TCI forecasting. TCIque is designed to integrate multimodal data and retrieve correlational features between them based on the Wide and Deep concept. The “Wide” component leverages domain knowledge to extract statistical features, while the “Deep” component captures nonlinear correlations and spatio-temporal dynamics based on self-attention mechanisms. This unique combination allows the model to fully utilize diverse data sources, such as meteorological variables, satellite imagery, and expert-driven features, ensuring robust feature fusion. Furthermore, a predictive encoder–decoder architecture associated with the self-attention mechanism is employed to address the challenge of long-term dependency decay. Experimental results demonstrate that the TCIque model outperforms existing methods, achieving more accurate performance in TCI prediction by 60.9%, 51.6%, 39.2%, and 1.8% compared to the best performance of baselines, which includes ConvLSTM, PredRNN, TC-Pred, SCSTque, SAF-Net, TCI-Net, Tint, and Pred_3d at 6h, 12h, 18h, and 24h forecast, respectively.
We present a systematic approach to optimise distributed acoustic sensing (DAS) fibre-optic cable layouts using global optimisation techniques. Our method represents cable geometries using splines, enabling efficient exploration of layouts while respecting physical deployment constraints. The use of evolutionary algorithms enables single and multi-objective optimisation, taking into account complex design constraints such as terrain, accesibility, exclusion zones and cable length, while allowing efficient parallelisation of the optimisation process. We demonstrate the approach on a real-world case study, optimising the layout of a DAS cable for monitoring slope stability in the Cuolm da Vi area of Switzerland. We adapt design criteria for seismic source location problems, and for ambient noise surface wave tomography, to account for the unique characteristics of DAS, such as directional sensitivity patterns. The results show significant potential for improvements in source location accuracy and surface wave tomographic resolution by optimising cable layouts, highlighting the potential of this approach for optimising DAS deployments in various geophysical applications.
Jolan Lavoisier, Xishui Tian, Kumiko Kotera
et al.
GRANDProto300 (GP300) is a prototype array of the GRAND experiment, designed to validate the technique of autonomous radio-detection of astroparticles by detecting cosmic rays with energies between 10$^{17}$-10$^{18.5}$ eV. This observation will further enable the study of the Galactic-to-extragalactic source transition region. Between November 2024 u to May 2025, 46 out of 300 antennas have been operational and collecting data stably. We present here our cosmic-ray search pipeline, which involves several filtering steps: (1) coincidence search for signals triggering multiple antennas within a time window, (2) directional reconstruction of events, (3) exclusion of clustered (in time and space) noise events, (4) polarization cut, (5) selection based on the size of the footprint, and (6) other less mature cuts in this preliminary stage, including visual cuts. The efficiency of the pipeline is evaluated and applied to the first batch of data, yielding a set of cosmic-ray candidate events, which we present.
Recent studies, supported by updated hadronic interaction models, suggest that the mass composition of ultra-high-energy cosmic rays may be heavier than previously assumed. This has significant implications for source identification, as the deflections of the Galactic magnetic field (GMF) are larger for heavy primaries than for lighter ones at the same energy. In this work, we assume that cosmic rays above 40 EeV consist of iron nuclei only and investigate their possible sources through simulations of cosmic ray propagation, including interactions with ambient photon fields and deflections in the GMF using multiple models. We consider two types of sources as potential origins of these cosmic rays, active galactic nuclei and starburst galaxies. We compare the predicted distributions of arrival directions from sources within 250 Mpc with the measured arrival directions of cosmic rays above 40 EeV. Our results indicate that stronger correlation is found for the active galactic nuclei scenario compared to starburst galaxies. However, we find that within our heavy mass composition model, the GMF leads to significant deflections, making source identification challenging with current knowledge and tools, even at the highest energies.
Recent studies have utilized deep learning (DL) techniques to automatically extract features from synthetic aperture radar (SAR) images, which shows great promise for enhancing the performance of SAR automatic target recognition (ATR). However, our research reveals a previously overlooked issue: SAR images to be recognized include not only the foreground (i.e., the target), but also a certain size of the background area. When a DL-model is trained exclusively on foreground data, its recognition performance is significantly superior to a model trained on original data that includes both foreground and background. This suggests that the presence of background impedes the ability of the DL-model to learn additional semantic information about the target. To address this issue, we construct a structural causal model (SCM) that incorporates the background as a confounder. Based on the constructed SCM, we propose a causal intervention-based regularization method to eliminate the negative impact of background on feature semantic learning and achieve background debiased SAR-ATR. The proposed causal interventional regularizer can be integrated into any existing DL-based SAR-ATR models, mitigating the impact of background interference on the feature extraction and recognition accuracy without affecting the testing speed of these models. Experimental results on the moving and stationary target acquisition and recognition and SAR-AIRcraft-1.0 datasets indicate that the proposed method can enhance the efficiency of existing DL-based methods in a plug-and-play manner.
Abstract To further raise the gas extraction efficiency of the tight sandstone, the liquid nitrogen (LN2) freezing-thawing cycles method can be employed to improve the permeability of the low-permeability reservoirs. Permeability is generally regarded as a macroscopic description of the pore structure and usually has functional relationship to pore structure properties. The permeability of the rock is closely related to the change of microscopic pore structure. The permeability of rock depends on how the subzero temperatures changed the microscopic pore structure of rock, but it has not yet been confirmed obviously. In this study, the nuclear magnetic resonance (NMR) technique was adopted to investigate the pore structure evolution law and permeability of the tight sandstone with different LN2 freezing-thawing cycles. The results demonstrate that the LN2 freezing-thawing cycles promotes pore development and micro-fracture connection, and enhances the pore connectivity. The proportion of meso-pores, macro-pores and micro-fractures in the sandstone samples increases significantly, which provides a channel for the sandstone gas flow and extraction. Total porosity and effective porosity of the samples present a trend of rapid increase as the number of LN2 freezing-thawing cycles increasing, while the residual porosity decreases as the number of LN2 freezing-thawing cycles increasing. Coates model, SDR model (mean T2 model) and PP model were used to calculate and evaluate the permeability of the samples subjected to different LN2 freezing-thawing cycles. Furthermore, PP model can provide a better permeability estimate than the classical Coates and SDR model.
Romy Schlögel, Romy Schlögel, Romy Schlögel
et al.
Introduction: This study aims to differentiate local and regional ground uplift, as well as sub-regional subsidence induced by groundwater level drawdown, which are possibly enhanced across fault structures, as monitored by various synthetic aperture radar interferometry (InSAR) processing methods. A buoyant mantle plume under the Eifel may be responsible for the regional ground uplift, including the Weser–Geul (BE) and South Limburg regions (NL), which could negatively affect the area proposed for the future Einstein Telescope.Methods: Different InSAR processing techniques are compared to evaluate their limits in tracking fault structures on a time series of Copernicus Sentinel-1 images while detecting and measuring ground motion based on their phase signature. The results present an overall stable ground for the Euregio Meuse–Rhine region, especially at the Belgian–Dutch border, while tectonic activity is observed along the German side of the Rhine Graben.Results: As the current neotectonic activity in the target area was not well known, we performed a spatiotemporal analysis of ground deformation associated with the presence of NW–SE-trending normal faults where karst also develops, as well as along the Variscan NE–SW-trending thrust faults. This work demonstrates that the identification of deformation hazards using satellite remote sensing (and connected seismological) techniques is challenging mainly due to (very) small regional scale deformation, terrain conditions, and SAR properties.Discussion: Thus, the results mostly indicate ground stability over the area; however, also some agricultural activities were observed, as was deformation along some infrastructure such as railways. Displacements of millimetric order measured along the faults located near the Geul valley (BE) are probably related to old mining activities.
Soumik Saha, Biswajit Bera, Sumana Bhattacharjee
et al.
In this study, we have investigated four glaciers, namely Zemu, Talung, Alukthang and Rathong within Kanchenjunga national park. This study evaluates physical and morphometric parameters (area, length, perimeter, area of accumulation zone, ablation zone length, snout position, thickness and specific mass balance) of multiple glaciers and to ascertain the poorly understood glaciers of western Sikkim region under Kanchenjunga national park. The principal objective of this research is to find out the changes of glacial mass and other physical parameters of the selected glaciers using multi sources digital elevation model data.Various techniques of statistics, including Mann-Kendall and Sen’s slope tests have been applied at different confidence interval. We have identified that climate change is responsible for the alterations of the physical characteristics of the glaciers. Result shows that during the study period, Zemu glacier has faced highest amount of deglaciation in terms of area (20.79 sq.km) along with maximum 30 m elevation reduction, 24 m increase of snout elevation and 200 m retreat of terminus. Furthermore, it is observed that terminus of the each selected glaciers retreated during the study period. Rathong experienced maximum retreat rate, approximately 550 m, and is accompanied by a notable 163% increase in the ablation zone. Alukthang and Talung reduced their areas 0.56 and 4.06 sq.km respectively, along with 2.75 m and 9.10 m thickness respectively. Maximum 36.39 m/y-1 flow rate has been observed over Zemu glacier. The flow rate of Talung, Rathong and Alukthang glacier is 26.4 m/y-1, 34.1 m/y-1, and 23.7 m/y-1 respectively.
Atom interferometers measure quantum interference patterns in the wave functions of cold atoms that follow superpositions of different space-time trajectories. These can be sensitive to phase shifts induced by fundamental physics processes such as interactions with ultralight dark matter or the passage of gravitational waves. The capabilities of large-scale atom interferometers are illustrated by their estimated sensitivities to the possible interactions of ultralight dark matter with electrons and photons, and to gravitational waves in the frequency range around 1 Hz, intermediate between the peak sensitivities of the LIGO and LISA experiments. Atom interferometers can probe ultralight scalar couplings with much greater sensitivity than is currently available from probes of the Equivalence Principle. Their sensitivity to mid-frequency gravitational waves may open a window on mergers of masses intermediate between those discovered by the LIGO and Virgo experiments and the supermassive black holes present in the cores of galaxies, as well as fundamental physics processes in the early Universe such as first-order phase transitions and the evolution of networks of cosmic strings.
Kathryn Scholz, Meredith Townsend, Christian Huber
et al.
Abstract Magmatic volatiles drive pressure, temperature, and compositional changes in upper crustal magma chambers and alter the physical properties of stored magmas. Previous studies suggest that magmatic H2O content influences the growth and longevity of silicic chambers through regulating the size and frequency of eruptions and impacting the crystallinity‐temperature curve. However, there has been comparatively little exploration of how CO2 impacts the evolution of magma chambers despite the strong influence of CO2 on H2O solubility and the high concentrations of CO2 often present in mafic systems. In this study, we integrate the thermodynamic effects of dissolved and exsolved H2O and CO2 with the mechanics of open‐system magma chambers that interact thermally and mechanically with the crust. We applied this model to investigate how intrinsic variations in magmatic H2O‐CO2 content influence the growth and longevity of silicic and mafic magma chambers. Our findings indicate that even with a tenfold increase in CO2 content (up to 10,000 ppm), CO2 plays a minimal role in long‐term chamber growth and longevity. While CO2 content affects the magma compressibility, the resulting changes in eruption mass are balanced out by a commensurate change in eruption frequency so that the time‐averaged eruptive flux and long‐term chamber behavior remain similar. In contrast, H2O content strongly influences chamber growth and longevity. In silicic systems, high H2O contents hinder magma chamber growth by increasing the total eruptive flux and steepening the slope of the crystallinity‐temperature curve. In mafic systems, high H2O contents promote magma chamber growth by flattening the slope of the crystallinity‐temperature curve.
Abstract: This article shows that the existence of a universal frame of reference, in which light propagates, is still an unresolved problem of physics. The analyzed articles show that the rejection of the idea of ether due to Michelson-Morley’s and Kennedy-Thorndike’s experiments was too hasty. The zero results of these experiments can be explained by the theory with a universal frame of reference, in which light propagates. The fact that one-way speed of light has never been accurately measured and that there is a well-documented effect showing the anisotropy of space from the perspective of our frame of reference, which is the dipolar anisotropy of cosmic microwave background radiation, further substantiates theories with a universal frame of reference. The article shows that the null result of the Michelson-Morley and Kennedy-Thorndike experiments does not determine the Lorentz symmetry. Keywords: Lorentz transformation, Coordinate and time transformation, Universal frame of reference, Anisotropy of cosmic microwave background radiation, One-way speed of light.
Diffusive TeV gamma-ray emissions have been recently discovered extending beyond the pulsar wind nebulae of a few middle-aged pulsars, implying that energetic electron/positron pairs are escaping from the pulsar wind nebulae and radiating in the ambient interstellar medium. It has been suggested that these extended emissions constitute a distinct class of nonthermal sources, termed"pulsar halos". In this article, I will review the research progress on pulsar halos and discuss our current understanding on their physics, including the multiwavelength observations, different theoretical models, as well as implications for the origin of cosmic-ray positron excess and Galactic diffuse gamma-ray emission.