The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for viable ultraviolet completions in fundamental physics. It provides us with a natural framework to study theoretical models where degrees of freedom are correlated over long distances and that may exhibit very distinct behavior on different energy scales. The nonperturbative functional renormalization-group (FRG) approach is a modern implementation of Wilson's RG, which allows one to set up nonperturbative approximation schemes that go beyond the standard perturbative RG approaches. The FRG is based on an exact functional flow equation of a coarse-grained effective action (or Gibbs free energy in the language of statistical mechanics). We review the main approximation schemes that are commonly used to solve this flow equation and discuss applications in equilibrium and out-of-equilibrium statistical physics, quantum many-particle systems, high-energy physics and quantum gravity.
The past decades have witnessed an explosion of interest in topological materials, and a lot of mathematical concepts have been introduced in condensed matter physics. Among them, the bulk-boundary correspondence is the central topic in topological physics, which has inspired researchers to focus on boundary physics. Recently, the concepts of topological phases have been extended to non-Hermitian Hamiltonians, whose eigenvalues can be complex. Besides the topology, non-Hermiticity can also cause a boundary phenomenon called the non-Hermitian skin effect, which is an extreme sensitivity of the spectrum to the boundary condition. In this article, we review developments in non-Hermitian topological physics by focusing mainly on the boundary problem. As well as the competition between non-Hermitian and topological boundary phenomena, we discuss the topological nature inherent in non-Hermiticity itself. Expected final online publication date for the Annual Review of Condensed Matter Physics, Volume 14 is March 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Upcoming and planned experiments combining increasingly intense lasers and energetic particle beams will access new regimes of nonlinear, relativistic, quantum effects. This improved experimental capability has driven substantial progress in QED in intense background fields. We review here the advances made during the last decade, with a focus on theory and phenomenology. As ever higher intensities are reached, it becomes necessary to consider processes at higher orders in both the number of scattered particles and the number of loops, and to account for non-perturbative physics (e.g. the Schwinger effect), with extreme intensities requiring resummation of the loop expansion. In addition to increased intensity, experiments will reach higher accuracy, and these improvements are being matched by developments in theory such as in approximation frameworks, the description of finite-size effects, and the range of physical phenomena analysed. Topics on which there has been substantial progress include: radiation reaction, spin and polarisation, nonlinear quantum vacuum effects and connections to other fields including physics beyond the Standard Model.
Abstract Smilei is a collaborative, open-source, object-oriented (C++) particle-in-cell code. To benefit from the latest advances in high-performance computing (HPC), Smilei is co-developed by both physicists and HPC experts. The code’s structures, capabilities, parallelization strategy and performances are discussed. Additional modules (e.g. to treat ionization or collisions), benchmarks and physics highlights are also presented. Multi-purpose and evolutive, Smilei is applied today to a wide range of physics studies, from relativistic laser–plasma interaction to astrophysical plasmas. Program summary Program title: Smilei (version 3.2) Program Files doi: http://dx.doi.org/10.17632/gsn4x6mbrg.1 Licensing provisions: This version of the code is distributed under the GNU General Public License v3 Programming language: C++11, Python 2.7 Nature of the problem: The kinetic simulation of plasmas is at the center of various physics studies, from laser–plasma interaction to astrophysics. To address today’s challenges, a versatile simulation tool requires high-performance computing on massively parallel super-computers. Solution method: The Vlasov–Maxwell system describing the self-consistent evolution of a collisionless plasma is solved using the Particle-In-Cell (PIC) method. Additional physics modules allow to account for additional effects such as collisions and/or ionization. A hybrid MPI-OpenMP strategy, based on a patch-based super-decomposition, allows for efficient cache-use, dynamic load balancing and high-performance on massively parallel super-computers. Additional comments: Repository https://github.com/SmileiPIC/Smilei References: http://www.maisondelasimulation.fr/smilei
Abstract Ultra-thick soft-hard (UTSH) composite coal seams, composed of alternating layers of soft and hard coal, frequently experience severe rockburst accidents during roadway excavation under shallow burial depths (< 500 m). However, research on the mechanisms underlying such rockbursts remains limited. This study simulates the failure process of surrounding rock in roadways excavated through UTSH composite coal seams under shallow depth conditions using true triaxial low axial pressure unloading tests. Through a comprehensive analysis of failure characteristics, mechanical properties, and acoustic emission (AE) parameters of soft coal, hard coal, and multi-layered soft-hard coal composite specimens (2–4 alternating layers), the mechanism of rockburst induced by excavation unloading in shallow depths UTSH composite coal seams is revealed. Results demonstrate that under low axial pressure unloading conditions, composite specimens exhibit higher crack quantities and lengths compared to the hard coal specimen, with energy accumulation ranging from 70.2 to 120.7 kJ/m3, significantly exceeding the 66.6 kJ/m3 observed in the hard coal specimen. AE parameters further confirm that composite specimens undergo more severe damage than the hard coal specimen. A three-stage failure mechanism is proposed: (1) low-stress shear failure in soft coal layers, (2) interface shear failure induced by concentrated stress, and (3) shear failure in hard coal layers caused by stress transfer. This sequential process explains rockburst occurrences in shallow depths of composite coal seams, and a mechanical criterion is established accordingly. The findings provide theoretical foundations for monitoring, early warning, and prevention of rockburst hazards in roadways excavated through UTSH composite coal seams.
Implementation of high-dimensional (HD) quantum gates shows very promising perspectives for HD quantum computation. A bipartite quantum system with arbitrary dimensions n and m is termed a quNit–quMit. Here we propose a synthesis scheme to construct the quantum circuit for general quNit–quMit gates with controlled increment (CINC) gates and local gates. This shows that CINC gates combined with local gates form a universal gate set for HD quantum computation. An upper bound of $O(n^2)$ CINC gates is achieved for arbitrary quNit–quMit gate implementation in the proposed scheme, which is the best known result. Especially for the controlled quNit–quMit gates, our scheme requires only 2 CINC gates, whereas the previous scheme required 2 n .
In this proceedings we explore the physics potential of the ESSnuSBplus setup to study beam and non-beam based physics scenarios in both standard and new physics cases. The ESSnuSBplus setup consists of three neutrino sources: the main ESS linac, a low energy monitored neutrino beam and a low energy nuSTORM facility and three detectors: the main far detector and two near detectors. The goal of this facility is to measure the leptonic CP phase with extremely high precision and the neutrino nucleus cross-section in the few hundred MeV region.
In recent years, gaze estimation has received a lot of interest in areas including human–computer interface, virtual reality, and user engagement analysis. Despite significant advances in convolutional neural network (CNN) techniques, directly and effectively predicting the point of gaze (PoG) in unconstrained situations remains a difficult task. This study proposes a gaze point estimation network (L1fcs-Net) that combines facial features with positional features derived from a two-dimensional array obtained by projecting the face relative to the screen. Our approach incorporates a Face-grid branch to enhance the network’s ability to extract features such as the relative position and distance of the face to the screen. Additionally, independent fully connected layers regress x and y coordinates separately, enabling the model to better capture gaze movement characteristics in both horizontal and vertical directions. Furthermore, we employ a multi-loss approach, balancing classification and regression losses to reduce gaze point prediction errors and improve overall gaze performance. To evaluate our model, we conducted experiments on the MPIIFaceGaz dataset, which was collected under unconstrained settings. The proposed model achieves state-of-the-art performance on this dataset with a gaze point prediction error of 2.05 cm, demonstrating its superior capability in gaze estimation.
Oishi Jyoti, Md. Samiul Habib, Nguyen Hoang Hai
et al.
We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) without the need for complex multi-layer stacks or hybrid-patterned alternatives. Full-wave simulations demonstrate that VO2’s insulator-to-metal transition dynamically enhances absorption, while structural parameters—ring width, ellipticity ratio, and dielectric thickness—precisely control bandwidth and spectral response, as explained by impedance matching theory and electric field distributions. Furthermore, we explore the impact of varying the angle of incidence, highlighting the angular sensitivity of the structure. Beyond conventional parametric sweeps, we implement a targeted machine learning (ML) strategy for inverse design. Our models, trained on augmented data, show that Random Forest Regressor excels in predicting multiple geometric parameters simultaneously, while CatBoost is optimal for single-target prediction. The predicted geometric parameters are validated through simulation; this ML-guided approach, tailored to different design goals, combines physics-based modeling with data-driven optimization, offering a robust and efficient framework for designing next-generation broadband THz absorbers.
This article is aimed at studying the effects of the dimensional crossover (DC) on physical properties of condensed systems near phase transition and critical points. Here we consider the following problems: (1) the theoretical provisions that allow to study the effect of spatial confinement on DC near phase transition and critical points; (2) the study of DC in condensed systems with the Ginzburg number Gi < 1, where fluctuation effects are described in different ways at the fluctuation, regular and intermediate (crossover) regions; (3) two types of DC were investigated: (a) a decrease in the linear dimensions L to the values of the correlation length of the order parameter fluctuations leads to the conversion of the dependence on thermodynamic variable into a dependence on linear sizes of 3D systems, as well as (b) a further decrease in linear sizes L the 3D–2D or 3D1D DC happens depending on slitlike or cylindrical geometry, which is determined by the value of the lower crossover dimensionality dLCD; (4) it is proposed to extend the known equalities for critical exponents by using the Mandelbrot formula for fractal dimension Df as a critical exponent; (5) the influence of 3D–2D DC on the characteristics of the fine structure of the molecular light scattering (MLS) spectrum is studied.
The International Axion Observatory (IAXO) is a next-generation axion helioscope designed to search for solar axions with unprecedented sensitivity. IAXO holds a unique position in the global landscape of axion searches, as it will probe a region of the axion parameter space inaccessible to any other experiment. In particular, it will explore QCD axion models in the mass range from meV to eV, covering scenarios motivated by astrophysical observations and potentially extending to axion dark matter models. Several studies in recent years have demonstrated that IAXO has the potential to probe a wide range of new physics beyond solar axions, including dark photons, chameleons, gravitational waves, and axions from nearby supernovae. IAXO will build upon the two-decade experience gained with CAST, the detailed studies for BabyIAXO, which is currently under construction, as well as new technologies. If, in contrast to expectations, solar axion searches with IAXO ``only'' result in limits on new physics in presently uncharted parameter territory, these exclusions would be very robust and provide significant constraints on models, as they would not depend on untestable cosmological assumptions.
Semantic segmentation of rural roads presents unique challenges due to the unstructured nature of these environments, including irregular road boundaries, mixed surfaces, and diverse obstacles. In this study, we propose an enhanced PP-LiteSeg model specifically designed for rural road segmentation, incorporating a novel Strip Pooling Simple Pyramid Module (SP-SPPM) and a Bottleneck Unified Attention Fusion Module (B-UAFM). These modules improve the model’s ability to capture both global and local features, addressing the complexity of rural roads. To validate the effectiveness of our model, we constructed the Rural Roads Dataset (RRD), which includes a diverse set of rural scenes from different regions and environmental conditions. Experimental results demonstrate that our model significantly outperforms baseline models such as UNet, BiSeNetv1, and BiSeNetv2, achieving higher accuracy in terms of mean intersection over union (MIoU), Kappa coefficient, and Dice coefficient. Our approach enhances segmentation performance in complex rural road environments, providing practical applications for autonomous navigation, infrastructure maintenance, and smart agriculture.
Owing to the rapid urbanization combined with global climate change, dramatic land-use change in coastal watersheds is occurred, which, in turn, cause the evolution of landscape patterns and threaten the valuable but fragile ecosystem. The coastal zone is characterized by severe cloud cover, frequent changes in land type, and fragmented landscape, so it is challenging to carry out the accurate landscape patterns analysis. To address this problem, this study employed the Google Earth engine cloud platform, Landsat time series, and landscape metrics in the Fragstats model to develop a comprehensive framework that integrates landscape pattern metrics and spatial analysis methods, considering both type level and landscape level. The Hangzhou Bay region was selected for conducting land-use classification and landscape patterns analysis. The results indicate that, during nearly four decades, with the continuous expansion of the urban, the urbanization process has accelerated, and the construction land has expanded by 6.93 times. By analyzing the evolution of landscape patterns, Hangzhou Bay heightened landscape fragmentation and patch shapes became more irregular caused by a trend toward intensified urbanization. The Shannon's diversity index continuously increased from 1.14 to 1.51, while the contagion index consistently decreased from 59.83% to 42.21%, suggesting an increase in land-use diversity, reduced aggregation, and extension tendencies between land patches, along with a decrease in the proportion of highly connected patches within the landscape. This study is anticipated to provide robust evidence for the rational planning of future development directions and the deployment of landscape ecological spatial services.
Abstract Knowledge regarding the abundance and distribution of solar wind (SW)‐sourced water (OH/H2O) on the Moon in the shallow subsurface remains limited. Here, we report the NanoSIMS measurements of H abundances and D/H ratios on soil grains from three deepest sections of the Chang'E‐5 drill core sampled at depths of 0.45–0.8 m. High water contents of 0.13–1.3 wt.% are present on approximately half of the grain surfaces (topmost ∼100 nm), comparable to the values of Chang'E‐5 scooped soils. The extremely low δD values (as low as −995‰) and negative correlations between δD and water contents indicate that SW implantation is an important source of water beneath the lunar surface. The results are indicative of homogeneous distribution of SW‐derived water in the vertical direction, providing compelling evidence for the well‐mixed nature of the lunar regolith. Moreover, the findings demonstrate that the shallow subsurface regolith of the Moon contains a considerable amount of water.
For green hydrogen energy systems driven by renewables, despite the complexities in design and operations, uncertainties related to availability of infrastructures or seasonality of resources are significant as well as the uncertainties in technical side such as adoption of technologies for energy generation, conversion, and storage. Such uncertainties put the economy and sustainability of these systems under shadows. Consequently, it has been attempted to balance and offset the impacts of uncertainties by means of providing the side products such as hydrogen. An enviro-economic optimization considering reliability, availability, and maintenance of a biomass-gasification-driven combined heating, hydrogen, and electricity system is considered in this study. The emission penalty cost as well as the electricity and hydrogen generation revenues are also pinpointed as part of the objective function which is the total cost. Such costs incorporate capital cost for purchase and installation of all modules, primary fuel (High Heat Value Woods) purchase, and transportation costs. Probabilistic approach using Weibull function is used for modeling reliability for the whole system. The most optimal values for total cost, hydrogen and electrical modules incomes, rated capacities, utilization times, reliability and maintainability indicators such as mean time to failure and maintenance intervals for modules are derived and compared. The sensitivity to performance parameters and sizing characteristics of those three modules are also investigated. The results support this notion that if there are opportunities to sell hydrogen, it is advantageous to integrate hydrogen module to the heating and power co-generation. The results show that minimum cost is obtained by devoting less rated capacities and utilization times to electricity modules in favor of increasing the hydrogen module utilization times and flow rates.
Alan Kostelecky, Ralf Lehnert, Marco Schreck
et al.
The physical intepretation of effective field theories of fundamental interactions incorporating large Lorentz violation is a long-standing challenge, known as the concordance problem. In condensed-matter physics, certain Weyl semimetals with emergent Lorentz invariance exhibit large Lorentz violation, thereby offering prospective laboratory analogues for exploration of this issue. We take advantage of the mathematical equivalence between the descriptions of large Lorentz violation in fundamental and condensed-matter physics to investigate the primary aspects of the concordance problem, which arise when the coefficients for Lorentz violation are large or the observer frame is highly boosted. Using thermodynamic arguments, we present a physical solution to the concordance problem and explore some implications.