Hasil untuk "Physics"

Guancong Ma, M. Xiao, C. T. Chan

D. Kennes, M. Claassen, L. Xian et al.

H. Stapelfeldt, T. Seideman

A. Millis, P. Littlewood, B. Shraiman

The ${\mathrm{La}}_{1\ensuremath{-}x}{\mathrm{Sr}}_{x}{\mathrm{MnO}}_{3}$ system with $0.2\ensuremath{\lesssim}x\ensuremath{\lesssim}0.4$ has traditionally been modeled with a ``double-exchange'' Hamiltonian in which it is assumed that the only relevant physics is the tendency of carrier hopping to line up neighboring spins. We present a solution of the double-exchange model, show it is incompatible with many aspects of the data, and propose that in addition to double-exchange physics a strong electron-phonon interaction arising from the Jahn-Teller splitting of the outer Mn $d$ level plays a crucial role.

P. Dirac

The steady progress of physics requires for its theoretical formulation a mathematics that gets continually more advanced. This is only natural and to be expected. What, however, was not expected by the scientific workers of the last century was the particular form that the line of advancement of the mathematics would take, namely, it was expected that the mathematics would get more and more complicated, but would rest on a permanent basis of axioms and definitions, while actually the modern physical developments have required a mathematics that continually shifts its foundations and gets more abstract. Non-euclidean geometry and non-commutative algebra, which were at one time considered to be purely fictions of the mind and pastimes for logical thinkers, have now been found to be very necessary for the description of general facts of the physical world. It seems likely that this process of increasing abstraction will continue in the future and that advance in physics is to be associated with a continual modification and generalisation of the axioms at the base of the mathematics rather than with a logical development of any one mathematical scheme on a fixed foundation. There are at present fundamental problems in theoretical physics awaiting solution, e.g. , the relativistic formulation of quantum mechanics and the nature of atomic nuclei (to be followed by more difficult ones such as the problem of life), the solution of which problems will presumably require a more drastic revision of our fundamental concepts than any that have gone before. Quite likely these changes will be so great that it will be beyond the power of human intelligence to get the necessary new ideas by direct attempts to formulate the experimental data in mathematical terms. The theoretical worker in the future will therefore have to proceed in a more indirect way. The most powerful method of advance that can be suggested at present is to employ all the resources of pure mathematics in attempts to perfect and generalise the mathematical formalism that forms the existing basis of theoretical physics, and after each success in this direction, to try to interpret the new mathematical features in terms of physical entities (by a process like Eddington’s Principle of Identification).

G. Barton

Henry W. Lin, Max Tegmark

We show how the success of deep learning could depend not only on mathematics but also on physics: although well-known mathematical theorems guarantee that neural networks can approximate arbitrary functions well, the class of functions of practical interest can frequently be approximated through “cheap learning” with exponentially fewer parameters than generic ones. We explore how properties frequently encountered in physics such as symmetry, locality, compositionality, and polynomial log-probability translate into exceptionally simple neural networks. We further argue that when the statistical process generating the data is of a certain hierarchical form prevalent in physics and machine learning, a deep neural network can be more efficient than a shallow one. We formalize these claims using information theory and discuss the relation to the renormalization group. We prove various “no-flattening theorems” showing when efficient linear deep networks cannot be accurately approximated by shallow ones without efficiency loss; for example, we show that n variables cannot be multiplied using fewer than 2n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2^n$$\end{document} neurons in a single hidden layer.

F. Melia

During a dramatic development of the field over the last decade, German groups and institutions have played central, often decisive, roles in high-energy astrophysics. Both spatially resolved and temporal studies of gamma-ray sources are conducted with unprecedented sensitivity, deciphering the physical processes in Galactic and extragalactic sources of high-energy emission, and providing new insights into fundamental physics. Radio observations of compact objects, especially black holes and neutron stars, permit exploring physics under extreme conditions and testing for fundamental properties such as the existence of event horizons around black holes. Observations of ultra-high energy cosmic rays provide information on particle acceleration at the highest energy. The first detection in 2013 of cosmic high-energy neutrinos was named the Physics World breakthrough of the year.

A. Einstein, L. Infeld

Ilya Mandel, Om Sharan Salafia, Andrew Levan et al.

We analytically derive, and illustrate with a population synthesis model, the maximum offset of binary neutron star mergers ejected from their host galaxies. This approximate maximum offset is 300 kpc $\times \,{({v}_{{\rm{esc}}}/500\,{\rm{km}}\,{{\rm{s}}}^{-1})}^{-7}$ , where v _esc is the escape velocity from the host galaxy. Massive hosts with high escape velocities are unlikely to yield very large offsets. This maximum offset should inform the host associations of mergers that are not coincident with galaxies. We also discuss potential correlations between offsets and system masses, and possibly the duration of the gamma-ray burst accompanying the merger.

Markus Seidel

In these proceedings we review the physics objects used by the CMS experiment during LHC Run 3 at 13.6 TeV, including charged leptons, photons, jets, and missing transverse momentum. Their performance and calibration is critical for physics analysis. In particular, the algorithms need to be resilient against the high pileup conditions in Run 3 collisions. Furthermore, transformer-based algorithms are deployed for the identification of heavy-flavor jets and boosted resonances.

E. Segre, H. Bethe, N. Ramsey et al.

Duschanova Sanat K., Boyjanov Islom R., Kholmuratov Kholilla S. et al.

This study presents a comprehensive analysis of the mineralogical composition of marl samples from the Meshkli mine using modern analytical methods. By employing combined X-ray diffraction and thermogravimetric analysis (TGA), complemented by high-resolution differential scanning calorimetry (DSC), we identified four distinct periods within the TG and DSC curves. Each of these periods is characterized by specific thermal effects, providing critical insights into the presence of hygroscopic water, combustion of organic compounds, oxidation of iron compounds, and thermal decomposition of calcite. Additionally, X-ray analyses reveal a variety of minerals, including calcite, quartz, montmorillonite, kaolinite, and hematite. These findings significantly enhance our understanding of the mineralogical aspects of the Meshkli mine marls. The purpose of this work is to investigate the physicochemical characteristics of Meshkli mine marl, which is novel for the silicate industry, and to assess its suitability for use in cement compositions. Macroscopically, the marl samples from the Meshkli mine exhibit a green color with yellow and brown spots. They consist of dense rock composed of finely dispersed calcite, clay minerals, and siltstone quartz grains. Chemical analysis indicates that Meshkli mine marl has a homogeneous chemical composition.

P. D. Marinos, T. A. Porter, G. P. Rowell et al.

We use the GALPROP cosmic ray (CR) framework to model the Galactic CR distributions and associated nonthermal diffuse emissions up to PeV energies. We consider ensembles of discrete, finite lifetime CR sources, e.g., supernova remnants, for a range of creation rates and lifetimes. We find that the global properties of the CR sources are likely not directly recoverable from the current “snapshot” of the historic injection and propagation of CRs within the Galaxy that are provided by the data. We show that models for the diffuse γ rays based on the discrete/time-dependent scenarios we consider are able to explain the LHAASO very-/ultra-high-energy (VHE/UHE) γ -ray data with up to 50% contribution by unresolved leptonic sources at the highest energies. Over the models that we consider, variations in the diffuse VHE emissions can be ∼25%, which is comparable to those for the steady-state models that we investigated in an earlier work. Such variations due to the discrete/finite nature of the CR sources are an important factor that are necessary to construct accurate physical models of the diffuse emissions from the Galaxy at VHE/UHEs.

Zaki Ahmed, Ali Al-Kifaie Abbas M.

Iron oxide (Fe₂O₃) nanoparticles demonstrate significant antibacterial properties combined with facile synthesis potential. This study examines the concentration-dependent antimicrobial effects against Escherichia coli and Staphylococcus aureus. Field emission scanning electron microscopy (FESEM) characterization reveals agglomerated, irregularly shaped nanoparticles with crystalline sizes ranging from 35.73 to 71.49 nm, exhibiting semi-spherical morphology. X-ray diffraction (XRD) analysis confirms polycrystalline structure with rectangular tetrahedral geometry. Antibacterial assessment shows pronounced inhibition zones, with E. coli exhibiting maximum sensitivity at 0.08 g nanoparticle concentration. The crystalline structure and morphological characteristics correlate with observed antimicrobial efficacy, suggesting structure-dependent biological activity. These findings highlight the potential of Fe₂O₃ nanoparticles as effective antimicrobial agents, with implications for biomedical and industrial applications.

Yu Zhipeng, Li Yang, Jiang Haoran

Using the multiellipse-based discrete element method (DEM), we numerically study the biaxial shearing behavior of granular materials composed of star-shaped particles. These particle shapes are generated by overlapping two or three identical ellipses with a common center of mass, while varying the aspect ratio from 1 to 5. Our results reveal that the macroscopic shear strength of the system increases monotonically with particle non-convexity. In contrast, the packing fraction exhibits a non-monotonic dependence on non-convexity, initially increasing and then decreasing as non-convexity further grows. This behavior reflects variations in the local pore size due to the competition between short-range ordering and excluded volume effects. Furthermore, microscopic analysis indicates that the increase in shear strength is linked to higher contact numbers and reduced contact and inter-grain distances, corresponding to stronger interlocking at higher non-convexity.

Rongchao Xu, Liang Gao, Yiding Jin et al.

Abstract The crack initiation stress (σ ci) and crack damage stress (σ cd) are two important stress thresholds for describing the progressive failure process of rocks. Accurately obtaining these two stress thresholds is crucial for analyzing the anisotropic characteristics of shale under the influence of bedding planes. The stress thresholds of rocks can be effectively obtained based on the response law of axial and circumferential strains during rock failure. Therefore, strain measurement methods have a significant impact on the stress threshold of rocks. Currently, there are mainly two methods to measure the axial strain of rock by displacement sensors, namely, axial extensometer and linear variable differential transformer (LVDT). To investigate the influence of strain measurement methods on σ ci and σ cd of shale, the stress thresholds and corresponding strain thresholds obtained by the extensometer and LVDT axial strain measurement methods were calculated based on the triaxial compression test results of Longmaxi shale under seven different bedding plane angles, and the differences in the calculation results based on the two methods were analysed. The discrete element method (DEM) was used to carry out numerical analysis, and the influence of the two measurement methods on the mechanical properties of rock was further studied. The research shows that the influence of strain measurement methods on the mechanical properties of shale is mainly reflected in deformation parameters, stress and strain thresholds and the post‒peak shape of the stress‒strain curve. For σ cd and its corresponding strain threshold, the calculation result of the extensometer is obviously smaller than that of the LVDT. In terms of σ cd, shale shows significant anisotropic characteristics.

F. Archilli, Sw. Banerjee, E. Ben-Haim et al.

Heavy-flavour physics is an essential component of the particle-physics programme, offering critical tests of the Standard Model and far-reaching sensitivity to physics beyond it. Experiments such as LHCb, Belle II, and BESIII drive progress in the field, along with contributions from ATLAS and CMS. The LHCb Upgrade II and upgraded Belle II experiments will provide unique and highly sensitive measurements for decades, playing a key role in the searches for new physics. Future facilities with significant heavy-flavour capabilities will further expand these opportunities. We advocate for a European Strategy that fully supports Upgrade II of LHCb and an upgrade of Belle II, along with their subsequent exploitation. Additionally, we support a long-term plan that fully integrates flavour physics in an $e^+e^-$ collider to run as a $Z$ factory.

Anisa Khatun

The ALICE experiment has undergone a major detector upgrade for Run 3, expanding its detection capabilities for a wide variety of studies. The new continuous readout has significantly enhanced the physics potential for ultra-peripheral collision analyses. In this talk, we discussed some of the physics analyses that can be carried out in ultra-peripheral collisions using the Run 3 data and presented some of the first physics performance plots in both proton-proton and heavy-ion collisions.

J. Sneed, R. Good