Mass Density Distribution Research Articles

Molecular dynamics study on the enhancement of high‐temperature friction and mechanical properties of perfluoroelastomers by carbon nanomaterials

AbstractThe mechanical and frictional properties of pure perfluoroelastomer, graphene (GN)/perfluoroelastomer, and carbon nanotube (CNT)/perfluoroelastomer composite systems were investigated using molecular dynamics simulations. The influence of carbon nanomaterials on the glass transition temperature, mechanical properties, and frictional behavior of perfluoroelastomers at various temperatures was evaluated. The simulation results demonstrated that the addition of GN and CNTs increased the glass transition temperature of perfluoroelastomers to varying extents. CNTs enhanced the mechanical properties of perfluoroelastomers more effectively than GN, whereas GN provided superior improvement in frictional properties compared to CNTs. Analysis of stress–strain distribution, atomic motion trajectory, interaction energy, mass density, and temperature distribution, bond orientation parameters, radial distribution function (RDF), mean square displacement (MSD), and diffusion coefficients revealed the mechanisms and differences by which GN and CNTs enhance the mechanical and frictional properties of perfluoroelastomers.Highlights Carbon nanomaterials enhance perfluoroelastomer's high‐temperature performance. CNTs provide higher mechanical strength but lower wear resistance. GN nanosheets outperform CNTs in reducing friction and wear. Molecular dynamics simulations reveal distinct enhancement mechanisms.

On gravity implication in the wavefunction collapse

Abstract Inspired by an ontic view of the wavefunction in quantum mechanics and motivated
by the universal e¤ect of gravity, we discuss a possible gravity implication in the reduc-
tion scenario of the quantum state. Concretely, we investigate the stability of the spatial
superposition of a massive quantum state under the gravity e¤ect. In this context, we
argue that the stability of the spatially superposed state jYi =
nå
i=1
ai jyii, ai 2 C, depends
on its gravitational self-energy UG
Y originating from the effective mass density distribution
r m (x) through the spatially localized eigenstates jyii. We reveal that the gravitational
self-interaction between the di¤erent spacetime curvatures jGii created by the eigenstate
e¤ective masses m y leads to the reduction of the superposed state to one of the possible
localized states jyki jGki. Among others, we discuss such a gravity-driven state reduc-
tion. Then, we approach the corresponding collapse time t Collapse Y and the induced effective electric current I Y in the case of a charged state, as well as the possible detection aspects.

Origin of Ca II emission around polluted white dwarfs

Dozens of white dwarfs with anomalous metal polluted atmospheres are currently known to host dust and gas discs. The line profiles of the Ca II triplet emitted by the gas discs show a significant asymmetry. In recent decades, researchers have also discovered several minor planets orbiting such white dwarf stars. The most challenging burden of modelling gas discs around metal polluted white dwarfs is to simultaneously explain the asymmetry and metal pollution of the star's atmosphere over a certain period of time. Furthermore, models should also be consistent with other aspects of the observations, such as the morphology of the emission lines. This paper aims to construct a self-consistent model to explain the simultaneous white dwarf pollution and Ca II line asymmetry over at least three years. In our model, an asteroid disintegrates in an eccentric orbit, periodically entering below the star's Roche limit. The debris resulting from the disintegration sublimates at a temperature of 1500 K, producing gas that viscously spreads to form a disc. The evolution of the disc is studied over a period of 1.2 years (over 21000 orbits) using two-dimensional hydrodynamic simulations. Synthetic Ca II line profiles are calculated using the surface mass density and velocity distributions provided by the simulations, taking into account for the first time the asymmetric velocity distribution in the disc. An asteroid disintegrating on an eccentric orbit gives rise to the formation of an asymmetric disc and asymmetric Ca II triplet emission. Our model can explain the periodic reversal of the redshifted and blueshifted peak of the Ca II lines caused by the precession of the disc on timescales of 10.6 to 177.4 days. Our work suggests that the persistence of Ca II asymmetry over decades and its periodic change in the peaks can be explained by asteroids on eccentric orbits in two scenarios. In the first case, the asteroid disrupts on a short timescale (a couple of orbits), and the gas has a low viscosity range ($0.001< to maintain the Ca II signal for decades. In the other scenario, the asteroid disrupts on a timescale of a year, and the viscosity of the gas is required to be high, $

Deep Learning-driven Automatic Nuclei Segmentation of Label-free Live Cell Chromatin-sensitive Partial Wave Spectroscopic Microscopy Imaging.

Chromatin-sensitive Partial Wave Spectroscopic (csPWS) microscopy offers a non-invasive glimpse into the mass density distribution of cellular structures at the nanoscale, leveraging the spectroscopic information. Such capability allows us to analyze the chromatin structure and organization and the global transcriptional state of the cell nuclei for the study of its role in carcinogenesis. Accurate segmentation of the nuclei in csPWS microscopy images is an essential step in isolating them for further analysis. However, manual segmentation is error-prone, biased, time-consuming, and laborious, resulting in disrupted nuclear boundaries with partial or over-segmentation. Here, we present an innovative deep-learning-driven approach to automate the accurate nuclei segmentation of label-free live cell csPWS microscopy imaging data. Our approach, csPWS-seg, harnesses the Convolutional Neural Networks-based U-Net model with an attention mechanism to automate the accurate cell nuclei segmentation of csPWS microscopy images. We leveraged the structural, physical, and biological differences between the cytoplasm, nucleus, and nuclear periphery to construct three distinct csPWS feature images for nucleus segmentation. Using these images of HCT116 cells, csPWS-seg achieved superior performance with a median Intersection over Union (IoU) of 0.80 and a Dice Similarity Coefficient (DSC) score of 0.88. The csPWS-seg overcame the segmentation performance over the baseline U-Net model and another attention-based model, SE-U-Net, marking a significant improvement in segmentation accuracy. Further, we analyzed the performance of our proposed model with four loss functions: binary cross-entropy loss, focal loss, dice loss, and Jaccard loss. The csPWS-seg with focal loss provided the best results compared to other loss functions. The automatic and accurate nuclei segmentation offered by the csPWS-seg not only automates, accelerates, and streamlines csPWS data analysis but also enhances the reliability of subsequent chromatin analysis research, paving the way for more accurate diagnostics, treatment, and understanding of cellular mechanisms for carcinogenesis.

Molecular interaction mechanism and process analysis of separation of cyclohexane/ethyl acetate by extractive distillation

The selection of efficient and environmentally friendly extractants is crucial for extractive distillation (ED), and the microscopic mechanism of extractants in ED is still unclear. For the benefit of interpreting the microstructure distribution and phase behavior of the mixed system, this paper studied it by quantum chemical (QC) calculation and molecular dynamics (MD) simulation. Firstly, 1,3-dimethylimidazolium hexafluorophosphate [Mmim][PF6], 1-ethyl-3-methylimidazolium hexafluorophosphate [Emim][PF6] and organic solvent DMSO were screened based on COSMO-RS model and relative volatility. The bond length, bond energy, total electron density and deformation charge density of [Mmim][PF6], [Emim][PF6], DMSO extractant and ethyl acetate were analyzed by QC, the intrinsic properties of the chosen extractant and azeotropic system, as well as the interactions among the three extractants and ethyl acetate, were investigated. Then, the effect of extractant on the separation performance of cyclohexane ethyl acetate azeotrope in solvent environment was further studied by MD simulation. The two-dimensional mass density distributions (ANDDs) visualized the mixing behavior and structural distribution of the three extractants with the azeotropic system in the ternary system respectively, and the hydrogen bonding statistics indicated a high number of hydrogen bonds between [Mmim][PF6] and ethyl acetate. The radial distribution function (RDF) indicated that the extraction effect of [Mmim][PF6] was better and [PF6-] played a dominant role in the separation of azeotropic system. The strong interaction between [Mmim][PF6] extractant [PF6-] and ethyl acetate was further verified by the spatial distribution function (SDF). Ultimately, through Aspen Plus software simulation, it was found that the [Mmim][PF6] extractive distillation process was superior to the traditional solvent DMSO process, TAC was reduced by 8 %, and gas emissions were reduced by 5 %. Through the combination of QC, MD, and process simulation offer theoretical guidance for the efficient separation of the cyclohexane-ethyl acetate system and provide a specific reference value for the selection of the optimal extractant.

AMICO galaxy clusters in KiDS-DR3: Measuring the splashback radius from weak gravitational lensing

Context. Weak gravitational lensing offers a powerful method to investigate the projected matter density distribution within galaxy clusters, granting crucial insights into the broader landscape of dark matter on cluster scales. Aims. In this study, we make use of the large photometric galaxy cluster data set derived from the publicly available Third Data Release of the Kilo-Degree Survey, along with the associated shear signal. Our primary objective is to model the peculiar sharp transition in the cluster profile slope, that is what is commonly referred to as the splashback radius. The data set under scrutiny includes 6962 galaxy clusters, selected by AMICO (an optimised detection algorithm of galaxy clusters) on the KiDS-DR3 data, in the redshift range of 0.1 ≤ z ≤ 0.6, all observed at a signal-to-noise ratio greater than 3.5. Methods. Employing a comprehensive Bayesian analysis, we model the stacked excess surface mass density distribution of the clusters. We adopt a model from recent results on numerical simulations that capture the dynamics of both orbiting and infalling materials, separated by the region where the density profile slope undergoes a pronounced deepening. Results. We find that the adopted profile successfully characterizes the cluster masses, consistent with previous works, and models the deepening of the slope of the density profiles measured with weak-lensing data up to the outskirts. Moreover, we measure the splashback radius of galaxy clusters and show that its value is close to the radius within which the enclosed overdensity is 200 times the mean matter density of the Universe, while theoretical models predict a larger value consistent with a low accretion rate. This points to a potential bias of optically selected clusters preferentially characterized by a high density at small scales compared to a pure mass-selected cluster sample.

The impact of stellar bars on star-formation quenching: Insights from a spatially resolved analysis in the local Universe

Stellar bars are common morphological structures in the local Universe; according to optical and NIR surveys, they are present in about two-thirds of disc galaxies. These elongated structures are also believed to play a crucial role in secular evolutionary processes, because they are able to efficiently redistribute gas, stars, and angular momentum within their hosts, although it remains unclear as to whether they enhance or suppress star formation. A useful tool to investigate this ambiguity is the main sequence (MS) relation, which tightly links stellar mass ($M_ star $) and star formation rate (SFR). The main goal of this work is to explore star-formation processes in barred galaxies in order to assess the relevance of bars in star-formation quenching and whether or not they affect the typical log-linear trend of the resolved MS. To this purpose, we carried out a spatially resolved analysis on subkiloparsec (subkpc) scales for a sample of six nearby barred galaxies. We collected multi-wavelength photometric data from far-ultraviolet (FUV) to far-infrared (FIR) from the DustPedia database and applied a panchromatic spectral energy distribution (SED) fitting procedure on square apertures of fixed angular size ( arcsec times arcsec ) using the magphys code. For each galaxy, we obtain the distributions of stellar mass and SFR surface density and relate them in the $ star SFR $ plane, deriving the spatially resolved MS relation. Although significant galaxy-to-galaxy variations are in place, we infer the presence of a common anti-correlation track in correspondence with the bar-hosting region, which shows systematically lower SFRs. This central quiescent signature can be interpreted as the result of a bar-driven depletion of gas reservoirs and a consequent halting of star formation. Our findings appear to support an inside-out quenching scenario.

The excess of diffuse radio emission in galaxy clusters A4038 and A1664

In this study, we investigate the potential connection between Dark matter (DM) particles and synchrotron emission in galaxy clusters, with a focus on radio relics. We explore three models beyond the standard model of particle physics and calculate emissions from DM particle candidates, comparing the results to radio observations. Our analysis centres on galaxy clusters A4038 and A1664, considering their radio properties and magnetic field characteristics. We employ the Navarro, Frenk, and White (NFW) profile to represent mass density distributions and in situ acceleration models for cosmic ray contributions. We estimate upper limits on DM cross-section annihilation 〈σv〉 for various DM particle candidates for two decay channels (bb̄ and μ+μ− decay channels). Our findings suggest that the DM is not likely the source of the excess emission, but we acknowledge the potential impact of DM on total radio emissions in galaxy clusters. Further studies are needed to refine excess emissions and assess DM’s influence on the total radio emissions. In summary, this research delves into the intricate relationship between DM particles and radio emissions in galaxy clusters, emphasizing the need for precise modelling and observation to unveil the mysteries of DM.

Generation and evaluation of anatomy-preserving virtual CT for online adaptive proton therapy.

Daily CTs generated by CBCT correction are required for daily replanning in online-adaptive proton therapy (APT) to effectively deal with inter-fractional changes. Out of the currently available methods, the suitability of a daily CT generation method for proton dose calculation also depends on the anatomical site. We propose an anatomy-preserving virtual CT (APvCT) method as a hybrid method of CBCT correction, which is especially suitable for large anatomy deformations. The accuracy of the hybrid method was assessed by comparison with the corrected CBCT (cCBCT) and virtual CT (vCT) methods in the context of online APT. Seventy-one daily CBCTs of four prostate cancer patients treated with intensity modulated proton therapy (IMPT) were converted to daily CTs using cCBCT, vCT, and the newly proposed APvCT method. In APvCT, planning CT (pCT) were mapped to CBCT geometry using deformable image registration with boundary conditions on controlling regions of interest (ROIs) created with deep learning segmentation on cCBCT. The relative frequency distribution (RFD) of HU, mass density and stopping power ratio (SPR) values were assessed and compared with the pCT. The ROIs in the APvCT and vCT were compared with cCBCT in terms of Dice similarity coefficient (DSC) and mean distance-to-agreement (mDTA). For each patient, a robustly optimized IMPT plan was created on the pCT and subsequent daily adaptive plans on daily CTs. For dose distribution comparison on the same anatomy, the daily adaptive plans on cCBCT and vCT were recalculated on the corresponding APvCT. The dose distributions were compared in terms of isodose volumes and 3D global gamma-index passing rate (GPR) at γ(2%, 2mm) criterion. For all patients, no noticeable difference in RFDs was observed amongst APvCT, vCT, and pCT except in cCBCT, which showed a noticeable difference. The minimum DSC value was 0.96 and 0.39 for contours in APvCT and vCT respectively. The average value of mDTA for APvCT was 0.01cm for clinical target volume and ≤0.01cm for organs at risk, which increased to 0.18cm and ≤0.52cm for vCT. The mean GPR value was 90.9%, 64.5%, and 67.0% for APvCT versus cCBCT, vCT versus cCBCT, and APvCT versus vCT, respectively. When recalculated on APvCT, the adaptive cCBCT and vCT plans resulted in mean GPRs of 89.5±5.1% and 65.9±19.1%, respectively. The mean DSC values for 80.0%, 90.0%, 95.0%, 98.0%, and 100.0% isodose volumes were 0.97, 0.97, 0.97, 0.95, and 0.91 for recalculated cCBCT plans, and 0.89, 0.88, 0.87, 0.85, and 0.81 for recalculated vCT plans. Hausdorff distance for the 100.0% isodose volume in some cases of recalculated cCBCT plans on APvCT exceeded 1.00cm. APvCT contours showed good agreement with reference contours of cCBCT which indicates anatomy preservation in APvCT. A vCT with erroneous anatomy can result in an incorrect adaptive plan. Further, slightly lower values of GPR between the APvCT and cCBCT-based adaptive plans can be explained by the difference in the cCBCT's SPR RFD from the pCT.

Effect of surface structure on fluid flow and heat transfer in cold and hot wall nanochannels

Nanochannels consisting of hot and cold walls with periodic rectangular and triangular nanostructures were simulated by molecular dynamics in this paper, the periodic size dimensionless parameters φ was defined to describe the dimension of nanostructures on the wall. The results show that the addition of nanostructures leads to the variation of mass density distribution of fluid near the wall. A hot wall with nanostructures can promote the appearance of a fluid high-potential area near it. The discrepant attraction for fluid from the wall caused by the different wall conditions leads to different flow characteristics in nanochannels. Fluid velocity growth rate near the hot wall is 10.5% higher than that near the cold wall. Average velocity of the fluid near the hot wall is 5.1% higher than that of fluid near the cold wall. A wall with rectangular nanostructures at φ = 0.28 shows minimum flow resistance among rough hot walls, while a wall with triangular nanostructures at φ = 0.14 has minimum flow resistance among rough cold walls. Heat is transferred from the hot wall to the cold wall through fluid flow. Wall conditions impact the heat transfer situation of fluid in flow boundary by changing the fluid mass density contribution. The addition of nanostructures and decrease of nanostructures size is beneficial for heat transfer while unfavorable for fluid flow, convective heat transfer was influenced by their combination. For a wall with 300 K, the addition of rectangular nanostructures at φ = 0.07 has the best convective heat transfer performance. For a wall with 200 K temperature, increasing triangular nanostructures at φ = 0.14 on the wall can reach the best convective heat transfer capacity. This paper can provide a theoretical foundation for the optimization of nanochannels to achieve best convective heat transfer ability.

GALAXY CLUSTER MERGERS: THE USE OF THE COMPUTER MODELING

We show the possibilities of the methods of computer modeling of the galaxy cluster merger process with different initial parameters for the investigation of the features of the clusters after colliding. We considered the galaxy clusters as evolving objects including through collisions. Computer modeling of galaxy cluster mergers and comparing its results with observational data makes it possible to determine the evolutionary status of real clusters with complex internal structures. Within the study, we analyzed in detail a series of models of the galaxy clusters’ merger consequences by ZuHone under different initial conditions like mass ratio, initial collision parameter, or plasma coefficient β. The considered time intervals were from 0 to 4.8 billion years, from 0 to 6 billion years, and from 0 to 10 billion years, depending on the initial conditions. Based on the images of the simulated galaxy clusters, maps of the distribution of the total mass density and X-ray radiation were created and compared with observations. We showed a good perspective to use this catalog for studying galaxy clusters having compound inner structure.

Multi-scale topology optimization of structures with multi-material microstructures using stiffness and mass design criteria

Nowadays, there is a great interest on the part of the automotive and aerospace industry to design environmentally-friendly structures. To that purpose, stiffness-oriented designs are proposed here by extending previous work on multi-scale topology optimization to the multi-material setting reformulating the problem to include appropriately mass constraints and discussing different design domain parametrizations and algorithmic strategies.On the macroscale, the problem of minimizing the compliance subject to a global mass constraint is addressed. On the microstructure scale, the multi-material design is carried out by solving the problem of minimizing the local complementary strain energy density with mass density constraint. As a result, very efficient structures composed of spatially varying porous and multi-material microstructures are obtained. The optimal design of the multi-material microstructure can be done either in a pointwise manner or in larger subdomains, to promote design uniformity. These parametrizations are here compared and discussed. Moreover, two different algorithmic strategies to solve the multi-scale problem are proposed, and their pros and cons discussed. They differ in the way the macro and micro design variables are related and updated. The macro design variables consider the mass density distribution along the structure, while the micro variables define the microstructure's topology using a multi-material SIMP interpolation scheme.The results show very efficient structures with locally optimized multi-material microstructures, which can outperform their single-material counterparts with regards to stiffness while maintaining the same mass. Additionally, the maximum stress verified on multi-material structures tends to be lower than the one obtained in the single-material counterparts.

Fractal dynamics and computational analysis of local fractional Poisson equations arising in electrostatics

In this paper, the local fractional natural decomposition method (LFNDM) is used for solving a local fractional Poisson equation. The local fractional Poisson equation plays a significant role in the study of a potential field due to a fixed electric charge or mass density distribution. Numerical examples with computer simulations are presented in this paper. The obtained results show that LFNDM is effective and convenient for application.

The surface mass density of the Milky Way: does the traditional KZ approach work in the context of new surveys?

ABSTRACT We revisit the classical KZ problem – determination of the vertical force and implied total mass density distribution of the Milky Way disc – for a wide range of Galactocentric radius and vertical height using chemically selected thin and thick disc samples based on Apache Point Observatory Galactic Evolution Experiment spectroscopy combined with the Gaia astrometry. We derived the velocity dispersion profiles in Galactic cylindrical coordinates, and solved the Jeans equation for the two samples separately. The result is surprising that the total surface mass density as a function of vertical height as derived for these two chemically distinguished populations is different. The discrepancies are larger in the inner compared to the outer Galaxy, with the density calculated from thick disc being larger, independent of the Galactic radius. Furthermore, while there is an overall good agreement between the total mass density derived for the thick disc population and the standard halo model for vertical heights larger than 1 kpc, close to the mid-plane the mass density observed using the thick disc population is larger than that predicted from the standard halo model. We explore various implications of these discrepancies, and speculate their sources, including problems associated with the assumed density laws, velocity dispersion profiles, and the Galactic rotation curve, potential non-equilibrium of the Galactic disc, or a failure of the Navarro-Frenk-White (NFW) dark matter halo profile for the Milky Way. We conclude that the growing detail in hand on the chemodynamical distributions of Milky Way stars challenges traditional analytical treatments of the KZ problem.

Planetesimal formation at the gas pressure bump following a migrating planet

Context. Planetesimal formation is still mysterious. One of the ways to form planetesimals is to invoke a gas pressure bump in a protoplanetary disc. In our previous paper, we proposed a new scenario in which the piled-up dust at a gas pressure bump created by a migrating planet forms planetesimals by streaming instability in a wide region of the disc as the planet migrates inwards. Aims. In the present work, we consider the global time evolution of dust and investigate the detailed conditions and results of the planetesimal formation in our scenario. Methods. We used a 1D grid single-sized dust evolution model, which can follow the growth of the particles in terms of their mutual collision and their radial drift and diffusion. We calculated the time-evolution of the radial distribution of the peak mass and surface density of the dust in a gas disc perturbed by an embedded migrating planet and investigated whether or not the dust satisfies the condition for planetesimal formation. Results. We find that planetesimals form in a belt-like region between the snowline and the position where the planet reaches its pebble-isolation mass when the strength of turbulence is 10−4 ≤ α ≤ 10−3, which is broadly consistent with the observed value of α. Whether the mechanism of the formation is streaming instability or mutual collision depends on the timescale of the streaming instability. The total mass of planetesimals formed in this scenario also depends on α; it is about 30–100 ME if the planetary core already exists at the beginning of the simulation and grows by gas accretion, but decreases as the timing of the formation of the planetary core gets later. We also provide simple approximate expressions for the surface density and total mass of the planetesimals and find that the total planetesimal mass strongly depends on the dust mass. Conclusions. We show that planetesimals form in a belt-like region by a combination of dust pile-up at the gas pressure bump formed by a planet and its inward migration.

Much ado about no offset – characterizing the anomalous multiple-image configuration and the model-driven displacement between light and mass in the multiplane strong lens Abell 3827

ABSTRACT Abell 3827 is a unique galaxy cluster with a dry merger in its core causing a highly resolved multiple-image configuration of a blue spiral galaxy at zs = 1.24. The surface brightness profiles of four merging galaxies around zd = 0.099 complicate a clear identification of the number of images and finding corresponding small-scale features across them. The entailed controversies about offsets between luminous and dark matter have never been settled and dark matter characteristics in tension with bounds from complementary probes and simulations seemed necessary to explain this multiple-image configuration. We resolve these issues with a systematic study of possible feature matchings across all images and their impact on the reconstructed mass density distribution. From the local lens properties directly constrained by these feature matchings without imposing any global lens model, we conclude that none of them are consistent with expected local characteristics from standard single-lens-plane lensing, nor can they be motivated by the light distribution in the cluster. Inspecting complementary spectroscopic data, we show that all these results originate from an insufficient constraining power of the data and seem to hint at a thick lens and not at exotic forms of dark matter or modified gravity. If the thick-lens hypothesis can be corroborated with follow-up multiplane lens modelling, A3827 suffers from a full three-dimensional degeneracy in the distribution of dark matter because combinations of shearings and scalings in a single lens plane can also be represented by an effective shearing and a rotation caused by multiple lens planes.

The Correlations of Stellar Tidal Disruption Rates with Properties of Massive Black Holes and Their Host Galaxies

Stars can be either disrupted as tidal disruption events (TDEs) or swallowed whole by massive black holes (MBHs) at galactic centers when they approach sufficiently close to these MBHs. In this work, we investigate the correlations of such stellar consumption rates with both the MBH mass M BH and the inner slope of the host-galaxy mass density distribution α. We introduce a simplified analytical power-law model with a power-law stellar-mass density distribution surrounding MBHs and separate the contributions of two-body relaxation and stellar orbital precession for the stellar orbital angular momentum evolution in nonspherical galaxy potentials. The stellar consumption rates derived from this simplified model can be well consistent with the numerical results obtained with a more realistic treatment of stellar distributions and dynamics around MBHs, providing an efficient way to estimate TDE rates. The origin of the correlations of stellar consumption rates with M BH and α is explained by the dependence of this analytical model on those MBH/host-galaxy properties and by the separation of the stellar angular momentum evolution mechanisms. We propose that the strong positive correlation between the rates of stellar consumption due to two-body relaxation and α provides one interpretation for the overrepresentation of TDEs found in some rare E+A/poststarburst galaxies. We find high TDE rates for giant stars, up to those for solar-type stars. Understanding the origin of the correlations of the stellar consumption rates will be necessary for obtaining the demographics of MBHs and their host galaxies via TDEs.

A simulation study of in-beam visualization system for proton therapy by monitoring scattered protons.

Recently, in-beam positron emission tomography (PET) has been actively researched for reducing biological washout effects and dose monitoring during irradiation. However, the positron distribution does not precisely reflect the dose distribution since positron production and ionization are completely different physical processes. Thus, a novel in-beam system was proposed to determine proton dose range by measuring scattered protons with dozens of scintillation detectors surrounding the body surface. While previous studies conducted a preliminary experiment with a simple phantom, we simulated more complex situations in this paper. Especially, we conducted three stepwise simulation studies to demonstrate the feasibility of the proposed method. First, a simple rectangular phantom was reproduced on simulation and irradiated with protons for obtaining current values and Monte Carlo (MC) dose. Next, we trained a deep learning model to estimate 2-dimensional-dose range (2D-DL dose) from measured current values for simulation (A). We simulated plastic scintillators as detectors to measure the scattered protons. Second, a rectangular phantom with an air layer was used, and 3D-DL dose was estimated in simulation (B). Finally, a cylindrical phantom that mimics the human body was used for confirming the estimation quality of the simulation (C). Consequently, the position of the Bragg peak was estimated with an error of 1.0 mm in simulation (A). In addition, the position of the air layer, as well as the verifying peak position with an error of 2.1 mm, was successfully estimated in simulation (B). Although the estimation error of the peak position was 12.6 mm in simulation (C), the quality was successfully further improved to 9.3 mm by incorporating the mass density distribution obtained from the computed tomography (CT). These simulation results demonstrated the potential of the as-proposed verification system. Additionally, the effectiveness of CT utilization for estimating the DL dose was also indicated.

Quantum Effects in General Relativity: Investigating Repulsive Gravity of Black Holes at Large Distances

This paper proposes a theoretical study that investigates quantum effects on the gravity of black holes. This study utilizes a gravitational model that incorporates quantum mechanics derived from the classical-like quantum hydrodynamic representation. This research calculates the mass density distribution of quantum black holes, specifically in the case of central symmetry. The gravity of a quantum black hole shows contributions coming from quantum potential energy, which is also sensitive to the presence of a background of gravitational noise. The additional energy, stored in quantum potential fluctuations and constituting a form of dark energy, leads to a repulsive gravity in the weak gravity limit. This repulsive gravity overcomes the attractive classical Newtonian force at large distances of order of the intergalactic length.

Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems Using Recurrent Inference Machines

Modeling strong gravitational lenses in order to quantify distortions in the images of background sources and to reconstruct the mass density in foreground lenses has been a difficult computational challenge. As the quality of gravitational lens images increases, the task of fully exploiting the information they contain becomes computationally and algorithmically more difficult. In this work, we use a neural network based on the recurrent inference machine to reconstruct simultaneously an undistorted image of the background source and the lens mass density distribution as pixelated maps. The method iteratively reconstructs the model parameters (the image of the source and a pixelated density map) by learning the process of optimizing the likelihood given the data using the physical model (a ray-tracing simulation), regularized by a prior implicitly learned by the neural network through its training data. When compared to more traditional parametric models, the proposed method is significantly more expressive and can reconstruct complex mass distributions, which we demonstrate by using realistic lensing galaxies taken from the IllustrisTNG cosmological hydrodynamic simulation.