Scalable quantum computing can become a reality with error correction, provided that coherent qubits can be constructed in large arrays 1 , 2 . The key premise is that physical errors can remain both small and sufficiently uncorrelated as devices scale, so that logical error rates can be exponentially suppressed. However, impacts from cosmic rays and latent radioactivity violate these assumptions. An impinging particle can ionize the substrate and induce a burst of quasiparticles that destroys qubit coherence throughout the device. High-energy radiation has been identified as a source of error in pilot superconducting quantum devices 3 – 5 , but the effect on large-scale algorithms and error correction remains an open question. Elucidating the physics involved requires operating large numbers of qubits at the same rapid timescales necessary for error correction. Here, we use space- and time-resolved measurements of a large-scale quantum processor to identify bursts of quasiparticles produced by high-energy rays. We track the events from their initial localized impact as they spread, simultaneously and severely limiting the energy coherence of all qubits and causing chip-wide failure. Our results provide direct insights into the impact of these damaging error bursts and highlight the necessity of mitigation to enable quantum computing to scale. Cosmic rays flying through superconducting quantum devices create bursts of excitations that destroy qubit coherence. Rapid, spatially resolved measurements of qubit error rates make it possible to observe the evolution of the bursts across a chip.
Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates, among other functions. However, the morphological characteristics of these micro impact craters are not obvious and they are numerous, resulting in low detection accuracy by deep learning models. Therefore, we proposed a new multi-scale fusion crater detection algorithm (MSF-CDA) based on the YOLO11 to improve the accuracy of lunar impact crater detection, especially for small craters with a diameter of <1 km. Using the images taken by the LROC (Lunar Reconnaissance Orbiter Camera) at the Chang’e-4 (CE-4) landing area, we constructed three separate datasets for craters with diameters of 0–70 m, 70–140 m, and >140 m. We then trained three submodels separately with these three datasets. Additionally, we designed a slicing–amplifying–slicing strategy to enhance the ability to extract features from small craters. To handle redundant predictions, we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels. Finally, our new MSF-CDA method achieved high detection performance, with the Precision, Recall, and F1 score having values of 0.991, 0.987, and 0.989, respectively, perfectly addressing the problems induced by the lesser features and sample imbalance of small craters. Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations. This strategy can also be used to detect other small objects with lesser features and sample imbalance problems. We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area. By statistically analyzing the new data, we updated the distribution function of the number and diameter of impact craters. Finally, we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.
Simon Ghyselincks, Valeriia Okhmak, Stefano Zampini
et al.
Abstract Reconstructing the structural geology and mineral composition of the first few kilometers of the Earth's subsurface from sparse or indirect surface observations remains a long‐standing challenge with critical applications in mineral exploration, geohazard assessment, and geotechnical engineering. This inherently ill‐posed problem is often addressed by classical geophysical inversion methods, which typically yield a single maximum‐likelihood model that fails to capture the full range of plausible geology. The adoption of modern deep learning methods has been limited by the lack of large 3D training data sets. We address this gap with StructuralGeo, a geological simulation engine that mimics eons of tectonic, magmatic, and sedimentary processes to generate a virtually limitless supply of realistic synthetic 3D lithological models. Using this data set, we train both unconditional and conditional generative flow‐matching models with a 3D attention U‐Net architecture. The resulting foundation model can reconstruct multiple plausible 3D scenarios from surface topography and sparse borehole data, depicting structures such as layers, faults, folds, and dikes. By sampling many reconstructions from the same observations, we introduce a probabilistic framework for estimating the size and extent of subsurface features. While the realism of the output is bounded by the fidelity of the training data to true geology, this combination of simulation and generative AI functions offers a flexible prior for probabilistic modeling, regional fine‐tuning, and use as an AI‐based regularizer in traditional geophysical inversion workflows.
Geophysics. Cosmic physics, Information technology
Abstract Talc can strongly influence the rheological properties of the subduction interface. Despite geologic evidence for talc at the interface, and proposed links between its rheology and slow slip events, few experiments have been conducted on talc at relevant conditions. We conducted constant‐load shear deformation experiments on talc aggregates at 1 GPa confining pressure, 420–700°C, and <150 MPa shear stress, and derived a low temperature plasticity flow law at lithospheric conditions. We show that tectonic displacement rates can be accommodated on talc‐rich shear zones with effective viscosities as low as 1013 Pa·s, and that slow slip displacement rates can be accommodated by a meters‐thick talc‐dominated shear zone, with strain rates orders of magnitude greater than antigorite at the same conditions. These observations indicate that talc can significantly weaken the lithosphere, and influence the dynamics of subduction and other tectonic processes when it is present in abundance.
Abstract In high-intensity mining operations in western China, shallow burial depths and rapid advancement rates induce rapid surface responses, significant deformation, and pronounced crack development. This study comprehensively evaluates these effects through full-process rock movement monitoring at the Jinjie coal mine, focusing on subsidence coefficients, mining coefficients, and inflection point trajectories. Results indicate that weak stability of the overlying strata in the shallow-buried working faces led to substantial surface subsidence, with a subsidence coefficient of 0.87, exceeding typical values (0.6–0.7) for conventional mining. The inflection point at the open-off cut followed a monotonic L-shaped trajectory, migrating laterally up to 4.7 times the mining height (15 m), while the inflection point near the roadway stabilized at 5.6–7.5 times the mining height (18–24 m) after two fluctuations. A significant contrast was observed in the horizontal movement coefficient between the goaf area (0.21–0.47) and the unmined area (1.59–2.38). Surface cracks exhibited an O-shaped ring distribution, synchronizing with periodic weighting intervals of 12–14 m; the pressure coefficient was approximately 1.73. Despite pronounced crack development, self-healing mechanisms reduced environmental risks. Full surface subsidence was achieved after the working face had advanced 320 m, a distance approximately equal to 1.24 times the working face length and 3.5 times the burial depth, with the basin areas occupying 48% of the total. Surface stabilization was achieved within 70 days (less than the ratio of burial depth to 100 m), underscoring the necessity of proactive measures such as crack filling to prevent air leakage and water inrush during rapid advancement (20 m/day).
The Global Navigation Satellite System (GNSS) is vital for monitoring terrestrial water storage (TWS). However, effectively extracting hydrological load deformation from GNSS observations poses a significant challenge. This study proposes a novel strategy; the seasonal hydrological load signals are removed from the raw data, and the remaining signals use principal component analysis (PCA). Simulation results from Yunnan Province demonstrate that the spatial distribution of the root mean square error (RMSE) is improved by approximately 15 % compared with traditional PCA extraction from raw data. From January 2013 to December 2022, TWS was inverted from 24 GNSS stations in Yunnan Province. The spatial distribution and time series of TWS inverted from GNSS align well with those TWS inferred from the Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GFO), and the Global Land Data Assimilation System (GLDAS) land surface model. However, the amplitude of the GNSS-inverted TWS is slightly higher. Since GNSS ground stations are more sensitive to hydrological load signals, they show correlations with precipitation data that are 8.6 % and 6.0 % higher than those of GRACE and GLDAS, respectively. In the power spectral density analysis of GRACE/GFO, GLDAS, and GNSS, the signal strength of GNSS is much higher than that of GRACE/GFO and GLDAS in the June and February cycles. These findings suggest that the new data extraction strategy can capture higher frequency hydrological signals in TWS, and GNSS observations can help address limitations in GRACE/GFO observations. This study demonstrates the potential of GNSS TWS in capturing higher-frequency hydrological signals and climate extremes application.
Jingxuan Li, Lydia Babcock‐Adams, Matthew R. McIlvin
et al.
Abstract Most iron (Fe) dissolved in seawater is complexed to organic ligands of unknown composition. Here we investigate the distribution of siderophores, small organic compounds synthesized by microbes to bind environmental Fe and facilitate its transport into the cell. Siderophores help relieve Fe‐stress and enhance microbial production under Fe‐deficient conditions. Siderophores were found at all stations sampled across a section of the eastern North and Tropical Pacific Oceans visited by the GEOTRACES GP15 expedition. In surface waters of the chronically Fe‐limited North Pacific Subpolar Gyre, Fe‐marinobactin and Fe‐amphibactin siderophore concentrations reached 66 pM and accounted for up to 80% of dissolved Fe. Ferrioxamine/ferrichrome‐like siderophores, including ferricrocin, were abundant near the Alaskan coast. Metal‐free and Al‐siderophores were also abundant across the section indicating rapid and active Fe‐siderophore uptake. Fe‐acquisition via siderophores is a common strategy for microbes inhabiting the upper ocean and likely supplies a large fraction of bioavailable‐Fe in Fe‐deficient regions.
The observed pattern of linear polarization of the cosmic microwave background (CMB) photons is a sensitive probe of physics violating parity symmetry under inversion of spatial coordinates. A new parity-violating interaction might have rotated the plane of linear polarization by an angle $\beta$ as the CMB photons have been traveling for more than 13 billion years. This effect is known as"cosmic birefringence."In this paper, we present new measurements of cosmic birefringence from a joint analysis of polarization data from two space missions, Planck and WMAP. This dataset covers a wide range of frequencies from 23 to 353 GHz. We measure $\beta = 0.342^{\circ\,+0.094^\circ}_{\phantom{\circ\,}-0.091^\circ}$ (68% C.L.) for nearly full-sky data, which excludes $\beta=0$ at 99.987% C.L. This corresponds to the statistical significance of $3.6\sigma$. There is no evidence for frequency dependence of $\beta$. We find a similar result, albeit with a larger uncertainty, when removing the Galactic plane from the analysis.
P. Diego-Palazuelos, J. R. Eskilt, Y. Minami
et al.
We search for the signature of parity-violating physics in the cosmic microwave background, called cosmic birefringence, using the Planck data release 4. We initially find a birefringence angle of β=0.30°±0.11° (68% C.L.) for nearly full-sky data. The values of β decrease as we enlarge the Galactic mask, which can be interpreted as the effect of polarized foreground emission. Two independent ways to model this effect are used to mitigate the systematic impact on β for different sky fractions. We choose not to assign cosmological significance to the measured value of β until we improve our knowledge of the foreground polarization.
The present white paper is submitted as part of the"Snowmass"process to help inform the long-term plans of the United States Department of Energy and the National Science Foundation for high-energy physics. It summarizes the science questions driving the Ultra-High-Energy Cosmic-Ray (UHECR) community and provides recommendations on the strategy to answer them in the next two decades.
For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of their free parameters. In this study, we review and compare a wide range of Markov Chain Monte Carlo (MCMC) and nested sampling techniques to determine their relative efficacy on functions that resemble those encountered most frequently in the particle astrophysics literature. Our first series of tests explores a series of high-dimensional analytic test functions that exemplify particular challenges, for example highly multimodal posteriors or posteriors with curving degeneracies. We then investigate two real physics examples, the first being a global fit of the $\Lambda$CDM model using cosmic microwave background data from the Planck experiment, and the second being a global fit of the Minimal Supersymmetric Standard Model using a wide variety of collider and astrophysics data. We show that several examples widely thought to be most easily solved using nested sampling approaches can in fact be more efficiently solved using modern MCMC algorithms, but the details of the implementation matter. Furthermore, we also provide a series of useful insights for practitioners of particle astrophysics and cosmology.
Silk damping is well known in the study of cosmic microwave background (CMB) and accounts for suppression of the angular power spectrum of CMB on large angular multipoles. In this article, we study the effect of Silk damping on the scalar-induced gravitational waves (SIGWs). Resulting from the dissipation of cosmic fluid, the Silk damping notably suppresses the energy-density spectrum of SIGWs on scales comparable to a diffusion scale at the decoupling time of weakly-interacting particles. The effect offers a novel observable for probing the underlying particle interaction, especially for those mediated by heavy gauge bosons beyond the standard model of particles. We anticipate that pulsar timing arrays are sensitive to gauge bosons with mass ∼ 103–104 GeV, while space- and ground-based interferometers to those with mass ∼ 107–1012 GeV, leading to essential complements to on-going and future experiments of high-energy physics.
Neutrinos traveling over cosmic distances are ideal probes of new physics. We leverage on the approaching detection of the diffuse supernova neutrino background (DSNB) to explore whether, if the DSNB showed departures from theoretical predictions, we could attribute such modifications to new physics unequivocally. In order to do so, we focus on visible neutrino decay. Many of the signatures from neutrino decay are degenerate with astrophysical unknowns entering the DSNB modeling. Next generation neutrino observatories, such as Hyper-Kamiokande, JUNO, as well as DUNE, will set stringent limits on a neutrino lifetime over mass ratio τ/m ∼ 109–1010 s eV-1 at 90% C.L., if astrophysical uncertainties and detector backgrounds were to be fully under control. However, if the lightest neutrino is almost massless and the neutrino mass ordering is normal, constraining visible decay will not be realistically possible in the coming few decades. We also assess the challenges of distinguishing among different new physics scenarios (such as visible decay, invisible decay, and quasi-Dirac neutrinos), all leading up to similar signatures in the DSNB. This work shows that the DSNB potential for probing new physics strongly depends on an improved understanding of the experimental backgrounds at next generation neutrino observatories as well as progress in the DSNB modeling.
In this work, I investigate the impact of Dark Energy Spectroscopic Instrument (DESI) Baryonic Acoustic Oscillations (BAO) data on cosmological parameters, focusing on the inflationary spectral index $n_s$, the amplitude of scalar perturbations $A_s$, and the matter density parameter $\omega_m$. By examining different models of late-time new physics, the inflationary parameters were revealed to be stable when compared with the baseline dataset that used the earlier BAO data from the SDSS collaboration. When combined with Cosmic Microwave Background (CMB) and type Ia supernovae (SNeIa), DESI BAO data leads to a slight reduction in $\omega_m$ (less than 2\%) and modest changes in $A_s$ and $n_s$, if compared with the same combination but using SDSS BAO data instead, suggesting a subtle shift in matter clustering. These effects may be attributed to a higher expansion rate from dynamical dark energy, changes in the recombination period, or modifications to the matter-radiation equality time. Further analyses of models with dynamical dark energy and free curvature show a consistent trend of reduced $\omega_m$, accompanied by slight increases in both $n_s$ and $H_0$. The results emphasize the importance of the DESI BAO data in refining cosmological parameter estimates and highlight the stability of inflationary parameters across different late-time cosmological models.
V-mode polarization of the cosmic microwave background is expected to be vanishingly small in the ΛCDM model and, hence, usually ignored. Nonetheless, several astrophysical effects, as well as beyond standard model physics could produce it at a detectable level. A realistic half-wave plate — an optical element commonly used in CMB experiments to modulate the polarized signal — can provide sensitivity to V modes without significantly spoiling that to linear polarization. We assess this sensitivity for some new-generation CMB experiments, such as the LiteBIRD satellite, the ground-based Simons Observatory and a CMB-S4-like experiment. We forecast the efficiency of these experiments to constrain the phenomenology of certain classes of BSM models inducing mixing of linear polarization states and generation of V modes in the CMB. We find that new-generation experiments can improve current limits by 1-to-3 orders of magnitude, depending on the data combination. The inclusion of V-mode information dramatically boosts the sensitivity to these BSM models.
Abdolvahab Afroogh, Jaber Shoghi, Mohammad Seraj
et al.
Understanding the governing factors that influence structural style and fault-related folding mechanisms is crucial in the Dezful Embayment, an area of ∼ 60,000 km2 which accounts for most of oil production from Iran. Such studies enable the subsurface kinematic modeling of structures and structural geological analysis of hydrocarbon traps. In this study, variations in geometry and folding mechanism along the strike of the Mansourabad anticline are studied through field data, 2D and 3D seismic lines interpretation and well data. The displacement-distance profile of the forelimb thrust fault indicates that the anticline is a fault propagation fold in its central and NW parts. In the SE part of the anticline, there is a north-verging detachment fold, which is opposite to the southward vergence at the NW part. Due to structural variations, the amount of slip along the NW-SE trending Behbahan Fault varies. This variation in structural style results from changes in slip along the Behbahan Fault's forelimb. This blind thrust, which trends NW-SE, extends along the entire length of the Mansourabad anticline. The variable thickness of the syn-folding sediments controlled the structural style of the anticline, which interacted with the migration of the Gachsaran Formation and the deformation of the competent rocks.
Abstract Forecasting landslide inundation upon catastrophic failure is crucial for reducing casualties, yet it remains a long‐standing challenge owing to the complex nature of landslides. Recent global studies indicate that catastrophic hillslope failures are commonly preceded by a period of precursory creep, motivating a novel scheme to foresee their hazard. Here, we showcase an approach to hindcast landslide inundation by linking satellite‐captured precursory displacements to modeling of consequent granular‐fluid flows. We present its application to the 2021 Chunchi, Ecuador landslide, which failed catastrophically and evolved into a mobile debris flow after four months of precursory creep, destroying 68 homes along its lengthy flow path. Underpinned by uncertainty quantification and in situ validations, we highlight the feasibility and potential of forecasting landslide inundation damage using observable precursors. This forecast approach is broadly applicable for flow hazards initiated from geomaterial failures.
Isabela S. Matos, M. Quartin, Luca Amendola
et al.
Cosmological distances are fundamental observables in cosmology. The luminosity (D L), angular diameter (D A) and gravitational wave (D GW) distances are all trivially related in General Relativity assuming no significant absorption of photons in the extragalactic medium, also known as cosmic opacity. Supernovae have long been the main cosmological standard candle, but bright standard sirens are now a proven alternative, with the advantage of not requiring calibration with other astrophysical sources. Moreover, they can also measure deviations from modified gravity through discrepancies between D L and D GW. However, both gravitational and cosmological parameters are degenerate in the Hubble diagram, making it hard to properly detect beyond standard model physics. Finally, recently a model-independent method named FreePower was proposed to infer angular diameter distances from large-scale structure which is independent of the knowledge of both early universe and dark energy physics. In this paper we propose a tripartite test of the ratios of these three distances with minimal amount of assumptions regarding cosmology, the early universe, cosmic opacity and modified gravity. We proceed to forecast this test with a combination of LSST and Roman supernovae, Einstein Telescope bright sirens and a joint DESI-like + Euclid-like galaxy survey. We find that even in this very model-independent approach we will be able to detect, in each of many redshift bins, percent-level deviations in these ratios of distances, allowing for very precise consistency checks of ΛCDM and standard physics. It can also result in sub-percent measurements of H 0.