Search Results (45)

A core–corona decomposition of compact (neutron) star models was compared with the current mass–radius data of the outlier XTE J1814-338. The corona (which may also be dubbed the envelope, halo or outer crust) is assumed to be of Standard Model matter, with an equation of state that is supposed to be faithfully known and accommodates nearly all other neutron star data. The core, solely parameterized by its mass, radius and transition pressure, presents a challenge regarding its composition. We derived a range of core parameters needed to describe the current data of XTE J1814-338. Full article

In this study, we utilized Gaia-DR3 astrometric data combined with the density-based spatial clustering of applications with noise (DBSCAN) algorithm to thoroughly investigate the dynamics and extra-tidal members of the open cluster NGC 6705. We determined more than 1900 cluster members within ∽12 pc of the cluster. We estimated the core and tidal radii to be 3.11 ± 0.21 arcmin (∽2 pc) and 20.02 ± 0.71 arcmin (∽13 pc), respectively, based on the cluster members. A Gaussian mixture model (GMM) was used to segregate the core and halo components of the cluster. The major and minor axes of the core and halo were determined through principal component analysis (PCA). The semi-major axis lengths of the core and halo were estimated to be $7^{\prime }$ (∽4.5 pc) and ${21}^{\prime }$ (∽13.6 pc), respectively. Additionally, the axis ratios of the core and halo were found to be e∽0.89 and e∽0.80, respectively, suggesting that the halo was significantly affected by the external tidal field. We detected a clear mass segregation effect within the cluster. Furthermore, we also detected some extra-tidal members around the cluster, implying that these stars are being lost from the cluster because of gravitational interactions with the Milky Way. This work provided a comprehensive characterization of NGC 6705, revealing its tighter structure, ongoing mass segregation, and potential star loss. Full article

Characterizing alteration and its geochemical signature provides critical information relevant to ore-deposit genesis and its related footprint; for porphyry-type deposits, zoned potassic-phyllic-propylitic alteration and metal enrichment are critical features. Here we integrate earlier lithological and mineralogical studies of the (10+ Moz Au) Archean Côté Gold porphyry-type Au(-Cu) deposit (Ontario, Canada) with identified alteration types to provide exploration vectors. The ca. 2740 tonalite-quartz diorite-diorite intrusive complex and co-temporal Au(-Cu) mineralization as disseminations, breccias and veins are co-spatial with ore-related alteration types (amphibole, biotite, muscovite). An early, locally developed amphibole event coring the deposit is followed by emplacement of a Au(-Cu) mineralized biotite-rich magmatic-hydrothermal breccia body and broad halo of disseminated biotite and quartz veining. These rocks record gains via mass balance calculations of K, Fe, Mg, LILE, and LREE with Au, Cu, Mo, Ag, Se and Bi. Later muscovite alteration is enriched in K, Rb, Cs, Ba, CO₂, and LOI with varied Au, Cu, Mo, Te, As, and Bi values. A strong albite overprint records extreme Na gains with the loss of most other elements, including ore metals (i.e., Au, Cu). Together these data define an Au-Cu-Mo-Ag-Te-Bi-Se core co-spatial with biotite breccia versus a peripheral stockwork and sheeted vein zone with a Te-Se-Zn-Pb-As association. These features further support the posited porphyry-type model for the Côté Gold Au(-Cu) deposit. Full article

We employ the simba-c cosmological simulation to study the impact of its upgraded chemical enrichment model (Chem5) on the distribution of metals in the intragroup medium (IGrM). We investigate the projected X-ray emission-weighted abundance profiles of key elements over two decades in halo mass (${10}^{13}\le M_{500}/{\mathrm{M}}_{\odot }\le {10}^{15}$). Typically, simba-c generates lower-amplitude abundance profiles than simba with flatter cores, in better agreement with observations. For low-mass groups, both simulations over-enrich the IGrM with Si, S, Ca, and Fe compared to observations, a trend likely related to inadequate modeling of metal dispersal and mixing. We analyze the 3D mass-weighted abundance profiles, concluding that the lower simba-c IGrM abundances are primarily a consequence of fewer metals in the IGrM, driven by reduced metal yields in Chem5, and the removal of the instantaneous recycling of metals approximation employed by simba. Additionally, an increased IGrM mass in low-mass simba-c groups is likely triggered by changes to the AGN and stellar feedback models. Our study suggests that a more realistic chemical enrichment model broadly improves agreement with observations, but physically motivated sub-grid models for other key processes, like AGN and stellar feedback and turbulent diffusion, are required to realistically reproduce observed group environments. Full article

It has long been known that the observed mass surface density of cored dark matter (DM) halos is approximately constant, independently of the galaxy mass (i.e., ${\rho }_c{r}_c\simeq \mathrm{constant}$, with ${\rho }_c$ and $r_c$ being the central volume density and the radius of the core, respectively). Here, we review the evidence supporting this empirical fact as well as its theoretical interpretation. It seems to be an emergent law resulting from the concentration–halo mass relation predicted by the current cosmological model, where the DM is made of collisionless cold DM particles (CDM). We argue that the prediction ${\rho }_c{r}_c\simeq \mathrm{constant}$ is not specific to this particular model of DM but holds for any other DM model (e.g., self-interacting) or process (e.g., stellar or AGN feedback) that redistributes the DM within halos conserving its CDM mass. In addition, the fact that ${\rho }_c{r}_c\simeq \mathrm{constant}$ is shown to allow the estimate of the core DM mass and baryon fraction from stellar photometry alone is particularly useful when the observationally expensive conventional spectroscopic techniques are unfeasible. Full article

Over the past two decades, significant deposit discoveries were made in Northeastern China, including the super-large Chalukou, Daheishan, and Luming porphyry Mo deposits. The discovery of the Luming deposit was accomplished through verification of stream sediment anomalies, with mineralization closely associated with early Jurassic monzogranite and granite porphyry. Previous studies primarily focused on the mineralization mechanisms of these deposits without adequately addressing the exploration methods and prospecting criteria. This study involved a comprehensive re-evaluation of geological observations, analysis of rock primary halo, gravity and magnetic surveys, and induced polarization surveys conducted during exploration campaigns at the Luming porphyry Mo deposit. The results suggest that hydrothermal breccias play a critical role in controlling the mineralization by forming a central low-grade core within the deposit while the Mo mineralization and hydrothermal alteration exhibit a donut-shaped distribution around it. The primary halo shows a distinct metal zonation moving from a central W-Bi-Mo-(Sb) to a peripheral Cu-Co-Ni and a distal Pb-Zn-Ag-In. The mineralization zone exhibits a low Bouguer gravity anomaly, negative magnetic anomaly, medium to low resistivity, and moderate to high chargeability, indicating the effectiveness of geophysical methods in defining the extent of the ore body. The Luming porphyry Mo deposit and distal skarn-epithermal Pb-Zn mineralization are parts of a porphyry-related magmatic-hydrothermal system. The results of this study offer valuable insights into the genesis of porphyry Mo deposits and their implications for prospecting in the forested region of Northeastern China. Full article

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of the non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi-equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but, unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously emitted thermal fluctuations and the background turbulence leads to the formation of a non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment. Full article

This paper describes a new practical numerical model for the calculation of lateral electromagnetic (EM) loads in tokamaks during asymmetric vertical displacement events (AVDEs). The model combines key features of two recently reported trial models while avoiding their drawbacks. Their common basic feature is the superposition of two patterns of halo current: one perfectly symmetric and another perfectly anti-symmetric. This model combines the following features that have not been combined before (a) a helically distorted halo layer wrapping around core plasma, and (b) halo-to-wall interception belts slipping along plasma-facing walls. This combination almost doubles the lateral net forces. An AVDE creates significant lateral net moments. Being relatively modest at VDEs, the lateral moments become a dominant component of EM loads at AVDEs. The model carefully tracks the balance of net EM loads (zero total for the tokamak), as a necessary condition for the consequent numerical simulation of the tokamak’s dynamic response. This balance is needed as well for the development of tokamak monitoring algorithms and simulators. In order to decouple from the current uncertainties in the interpretation and simulation of AVDE physics, the model does not simulate AVDE evolution but uses it as an input assumption based on the existing interpretation and simulation of AVDE physics. This means the model is to be used in a manner of parametric study, at widely varied input assumptions on AVDE evolution and severity. Parametric results will fill a library of ready-for-use waveforms of asymmetric EM loads (distributed and total) at tokamak structures and coils, so that the physics community may point to specific variants for subsequent engineering analysis. This article presents the first practical contribution to this AVDE library. Full article

The presence of dark matter (DM) within neutron stars (NSs) can be introduced by different accumulation scenarios in which DM and baryonic matter (BM) may interact only through the gravitational force. In this work, we consider asymmetric self-interacting bosonic DM, which can reside as a dense core inside the NS or form an extended halo around it. It is seen that depending on the boson mass ($m_{\chi }$), self-coupling constant ($\lambda$) and DM fraction ($F_{\chi }$), the maximum mass, radius and tidal deformability of NSs with DM admixture will be altered significantly. The impact of DM causes some modifications in the observable features induced solely by the BM component. Here, we focus on the widely used nuclear matter equation of state (EoS) called DD2 for describing NS matter. We show that by involving DM in NSs, the corresponding observational parameters will be changed to be consistent with the latest multi-messenger observations of NSs. It is seen that for $m_{\chi }\gtrsim 200$ MeV and $\lambda \lesssim 2\pi$, DM-admixed NSs with $4\%\lesssim F_{\chi }\lesssim 20\%$ are consistent with the maximum mass and tidal deformability constraints. Full article

We present a Monte Carlo approach that allows us to easily implement Lynden-Bell (LB) entropy maximization for an arbitrary initial particle distribution. The direct maximization of LB entropy for an arbitrary initial distribution requires an infinite number of Lagrange multipliers to account for the Casimir invariants. This has restricted studies of Lynden-Bell’s violent relaxation theory to only a very small class of initial conditions of a very simple waterbag form, for which the entropy maximization can be performed numerically. In the present approach, an arbitrary initial distribution is discretized into density levels which are then evolved using an efficient Monte Carlo algorithm towards the final equilibrium state. A comparison is also made between the LB equilibrium and explicit Molecular Dynamics simulations. We find that for most initial distributions, relaxation is incomplete and the system is not able to reach the state of maximum LB entropy. In particular, we see that the tail of the stationary particle distribution is very different from the one predicted by the theory of violent relaxation, with a hard cutoff instead of an algebraic decay predicted by LB’s theory. Full article

Prebaked carbon anodes are a critical consumable in the aluminum electrolysis industry. Prebaked carbon anode paste is the intermediate product of the prebaked carbon anode, and its quality significantly impacts the prebaked carbon anode. Therefore, inspecting the quality of the prebaked carbon anode paste is essential. Currently, the quality inspection of the paste still relies on laboratory analysis or manual experience. A laboratory inspection cannot obtain results in real time, while manual inspection poses potential risks. To address these issues, an online intelligent inspection method for prebaked carbon anode paste based on an anomaly detection algorithm was proposed. Firstly, we acquired the temperature of the paste and the power of the kneading motor. Secondly, we transformed these time-series data into images using the Gramian Angular Field (GAF) technique and joined them to create the paste anomaly detection dataset. Thirdly, we trained a matched anomaly detection model based on the PatchCore algorithm. Finally, we compared two advanced models: HaloAE and TSRD. PatchCore performs best on our dataset with an AUC-ROC score of 0.9943, followed by HaloAE (0.9906) and TSRD (0.9811). Our proposed method enables on-time intelligent inspection of prebaked carbon anode paste quality. This eliminates the need for manual inspection, reduces labor requirements, and ensures worker safety. Full article

Clustering is used to analyze the intrinsic structure of a dataset based on the similarity of datapoints. Its widespread use, from image segmentation to object recognition and information retrieval, requires great robustness in the clustering process. In this paper, a novel clustering method based on adjacent grid searching (CAGS) is proposed. The CAGS consists of two steps: a strategy based on adaptive grid-space construction and a clustering strategy based on adjacent grid searching. In the first step, a multidimensional grid space is constructed to provide a quantization structure of the input dataset. The noise and cluster halo are automatically distinguished according to grid density. Moreover, the adaptive grid generating process solves the common problem of grid clustering, in which the number of cells increases sharply with the dimension. In the second step, a two-stage traversal process is conducted to accomplish the cluster recognition. The cluster cores with arbitrary shapes can be found by concealing the halo points. As a result, the number of clusters will be easily identified by CAGS. Therefore, CAGS has the potential to be widely used for clustering datasets with different characteristics. We test the clustering performance of CAGS through six different types of datasets: dataset with noise, large-scale dataset, high-dimensional dataset, dataset with arbitrary shapes, dataset with large differences in density between classes, and dataset with high overlap between classes. Experimental results show that CAGS, which performed best on 10 out of 11 tests, outperforms the state-of-the-art clustering methods in all the above datasets. Full article

Based on the expected population of core collapse supernova remnants and the huge number of detected pulsars in the Galaxy, still representing only a fraction of the real population, pulsar wind nebulae are likely to constitute one of the largest classes of extended Galactic sources in many energy bands. For simple evolutionary reasons, the majority of the population is made of evolved systems, whose detection and identification are complicated by their reduced luminosity, the possible lack of X-ray emission (that fades progressively away with the age of the pulsar), and by their modified morphology with respect to young systems. Nevertheless they have gained renewed attention in recent years, following the detection of misaligned X-ray tails protruding from an increasing number of nebulae created by fast moving pulsars, and of extended TeV halos surrounding aged systems. Both these features are clear signs of an efficient escape of particles, with energy close to the maximum acceleration limit of the pulsar. Here we discuss the properties of those evolved systems and what we have understood about the process of particle escape, and the formation of observed features. Full article

Galaxy rotation curve (RC) fitting is an important technique which allows the placement of constraints on different kinds of dark matter (DM) halo models. In the case of non-phenomenological DM profiles with no analytic expressions, the art of finding RC best-fits including the full baryonic + DM free parameters can be difficult and time-consuming. In the present work, we use a gradient descent method used in the backpropagation process of training a neural network, to fit the so-called Grand Rotation Curve of the Milky Way (MW) ranging from ∼1 pc all the way to ∼${10}^5$ pc. We model the mass distribution of our Galaxy including a bulge (inner + main), a disk, and a fermionic dark matter (DM) halo known as the Ruffini-Argüelles-Rueda (RAR) model. This is a semi-analytical model built from first-principle physics such as (quantum) statistical mechanics and thermodynamics, whose more general density profile has a dense core–diluted halo morphology with no analytic expression. As shown recently and further verified here, the dark and compact fermion-core can work as an alternative to the central black hole in SgrA* when including data at milliparsec scales from the S-cluster stars. Thus, we show the ability of this state-of-the-art machine learning tool in providing the best-fit parameters to the overall MW RC in the ${10}^{-2}$–${10}^5$ pc range, in a few hours of CPU time. Full article

The PHENIX experiment measured two-particle Bose–Einstein quantum-statistical correlations of charged kaons in Au+Au collisions at $\sqrt{s_{\mathrm{NN}}}$ = 200 GeV. The correlation functions are parametrized assuming that the source emitting the particles has a Lévy shape, characterized by the Lévy exponent $\alpha$ and the Lévy scale R. By introducing the intercept parameter $\lambda$, we account for the core–halo fraction. The parameters are investigated as a function of transverse mass. The comparison of the parameters measured for kaon–kaon with those measured from pion–pion correlation may clarify the connection of Lévy parameters to physical processes. Full article