ShantanuT01/DACTYL-Pretraining huggingface dataset:
We present a multi-frequency study of the intermediate spiral SAB(r)bc type galaxy NGC 6744, using available data from the Chandra X-Ray telescope, radio continuum data from the Australia Telescope Compact Array and Murchison Widefield Array, and Wide-field Infrared Survey Explorer infrared observations. We identify 117 X-ray sources and 280 radio sources. Of these, we find nine sources in common between the X-ray and radio catalogues, one of which is a faint central black hole with a bolometric radio luminosity similar to the Milky Way's central black hole. We classify 5 objects as supernova remnant candidates, 2 objects as likely supernova remnants, 17 as HII regions, 1 source as an AGN; the remaining 255 radio sources are categorised as background objects and one X-ray source is classified as a foreground star. We find the star-formation rate (SFR) of NGC 6744 to be in the range 2.8 - 4.7 $\rm{M_{\odot}~yr^{-1}}$ signifying the galaxy is still actively forming stars. The specific SFR of NGC 6744 is greater than that of late-type spirals such as the Milky Way, but considerably less that that of a typical starburst galaxy.
Recent studies show that the chemical evolution of Sr and Ba in the Galaxy can be explained if different production sites, hosting r- and s-processes, are taken into account. However, the question of unambiguously identifying these sites is still unsolved. Massive stars are shown to play an important role in the production of s-material if rotation is considered. In this work, we study in detail the contribution of rotating massive stars to the production of Sr and Ba, in order to explain their chemical evolution, but also to constrain the rotational behaviour of massive stars. A stochastic chemical evolution model was employed to reproduce the enrichment of the Galactic halo. We developed new methods for model-data comparison which help to objectively compare the stochastic results to the observations. We employed these methods to estimate the value of free parameters which describe the rotation of massive stars, assumed to be dependent on the stellar metallicity. We constrain the parameters using the observations for Sr and Ba. Employing these parameters for rotating massive stars in our stochastic model, we are able to correctly reproduce the chemical evolution of Sr and Ba, but also Y, Zr and La. The data supports a decrease of both the mean rotational velocities and their dispersion with increasing metallicity. Our results show that a metallicity-dependent rotation is a necessary assumption to explain the s-process in massive stars. Our novel methods of model-data comparison represent a promising tool for future galactic chemical evolution studies.
We report the discovery of a substellar-mass co-moving companion to 2MASS J22501512+2325342, an M3 candidate member of the young (130--200 Myr) AB Doradus Moving Group (ABDMG). This L3 beta companion was discovered in a 2MASS search for companions at separations of 3--18" from a list of 2 812 stars suspected to be young (< 500 Myr) in the literature, and was confirmed with follow-up astrometry and spectroscopy. Evolutionary models yield a companion mass of 30 (-4,+11) Mj at the age of ABDMG. The 2MASS J22501512+2325342 AB system appears to be a spatial outlier to the bulk of ABDMG members, similarly to the young 2MASS J22362452+4751425 AB system. Future searches for young objects around these two systems would make it possible to determine whether they are part of a spatial extension of the known ABDMG distribution.
We show that the BRST operator of Neveu-Schwarz-Ramond superstring is closely related to de Rham differential on the moduli space of decorated super-Riemann surfaces P. We develop formalism where superstring amplitudes are computed via integration of some differential forms over a section of P over the super moduli space M. We show that the result of integration does not depend on the choice of section when all the states are BRST physical. Our approach is based on the geometrical theory of integration on supermanifolds of which we give a short review.
Triplet loss, one of the deep metric learning (DML) methods, is to learn the embeddings where examples from the same class are closer than examples from different classes. Motivated by DML, we propose an effective BP-Triplet Loss for unsupervised domain adaption (UDA) from the perspective of Bayesian learning and we name the model as BP-Triplet Net. In previous metric learning based methods for UDA, sample pairs across domains are treated equally, which is not appropriate due to the domain bias. In our work, considering the different importance of pair-wise samples for both feature learning and domain alignment, we deduce our BP-Triplet loss for effective UDA from the perspective of Bayesian learning. Our BP-Triplet loss adjusts the weights of pair-wise samples in intra domain and inter domain. Especially, it can self attend to the hard pairs (including hard positive pair and hard negative pair). Together with the commonly used adversarial loss for domain alignment, the quality of target pseudo labels is progressively improved. Our method achieved low joint error of the ideal source and target hypothesis. The expected target error can then be upper bounded following Ben-David s theorem. Comprehensive evaluations on five benchmark datasets, handwritten digits, Office31, ImageCLEF-DA, Office-Home and VisDA-2017 demonstrate the effectiveness of the proposed approach for UDA.
Group activity recognition aims to understand the activity performed by a group of people. In order to solve it, modeling complex spatio-temporal interactions is the key. Previous methods are limited in reasoning on a predefined graph, which ignores the inherent person-specific interaction context. Moreover, they adopt inference schemes that are computationally expensive and easily result in the over-smoothing problem. In this paper, we manage to achieve spatio-temporal person-specific inferences by proposing Dynamic Inference Network (DIN), which composes of Dynamic Relation (DR) module and Dynamic Walk (DW) module. We firstly propose to initialize interaction fields on a primary spatio-temporal graph. Within each interaction field, we apply DR to predict the relation matrix and DW to predict the dynamic walk offsets in a joint-processing manner, thus forming a person-specific interaction graph. By updating features on the specific graph, a person can possess a global-level interaction field with a local initialization. Experiments indicate both modules' effectiveness. Moreover, DIN achieves significant improvement compared to previous state-of-the-art methods on two popular datasets under the same setting, while costing much less computation overhead of the reasoning module.
The solution to the Schwinger-Dyson equation that describes the summation over Pomeron loop diagrams is derived. The solution is a closed expression which splits into two parts. The first leads directly to the renormalization of the BFKL Pomeron, and the second contribution is equivalent to non interacting Pomerons with renormalized vertices. Thus a closed expression is derived for the sum over Pomeron loop diagrams in the perturbative QCD approach, which preserves unitarity.
Consider an abelian variety $A$ defined over a global field $K$ and let $L/K$ be a $\Z_p^d$-extension, unramified outside a finite set of places of $K$, with $\Gal(L/K)=\Gamma$. Let $\Lambda(\Gamma):=\Z_p[[\Gamma]]$ denote the Iwasawa algebra. In this paper, we study how the characteristic ideal of the $\Lambda(\Gamma)$-module $X_L$, the dual $p$-primary Selmer group, varies when $L/K$ is replaced by a intermediate $\Z_p^e$-extension.
We study the collective behavior of an Ising system on a small-world network with the interaction $J(r) \propto r^{-\alpha}$, where $r$ represents the Euclidean distance between two nodes. In the case of $\alpha = 0$ corresponding to the uniform interaction, the system is known to possess a phase transition of the mean-field nature, while the system with the short-range interaction $(\alpha\to\infty)$ does not exhibit long-range order at any finite temperature. Monte Carlo simulations are performed at various values of $\alpha$, and the critical value $\alpha_c$ beyond which the long-range order does not emerge is estimated to be zero. Thus concluded is the absence of a phase transition in the system with the algebraically decaying interaction $r^{-\alpha}$ for any nonzero positive value of $\alpha$.
In this thesis we present detailed analyses on various running vacuum models (RVM's), in which the vacuum energy density "runs" with the cosmic expansion. The RVM's are motivated from the renormalization group formalism of Quantum Field Theory in curved spacetime. In this theoretical framework, the vacuum energy density depends explicitly on the Hubble function and its time derivative and thus does not remain constant, in contradistinction to the standard $\Lambda$CDM picture. Upon studying how these models fit the data, we can determine whether this dynamical behavior is favored by observations or not. Is the vacuum energy density (or more generically, the DE density) dynamical? One of the main conclusions of this dissertation is that we have indeed strong evidences in favor of the variability of the DE density throughout the cosmic history. It is shown that this variation can also be traced through other (purely phenomenological) dynamical vacuum models, together with different parametrizations of the DE (as the XCDM and CPL), and scalar field models as the Peebles-Ratra one. The statistical confidence level of these evidences reaches in some cases the 3-4$\sigma$ c.l., something that is unprecedented in the literature. An exhaustive explanation of the reasons why large collaborations as BOSS, Planck and DES have not been able to detect such signal in favor of the DE dynamics is provided in this thesis too.
The variability in multi-pulse gamma-ray bursts (GRBs) may help to reveal the mechanism of underlying processes from the central engine. To investigate whether the self-organized criticality (SOC) phenomena exist in the prompt phase of GRBs, we statistically study the properties of GRBs with more than 3 pulses in each burst by fitting the distributions of several observed physical variables with a Markov Chain Monte Carlo approach, including the isotropic energy $E_{\rm iso}$, the duration time $T$ and the peak count rate $P$ of each pulse. Our sample consists of 454 pulses in 93 GRBs observed by the CGRO/BATSE satellite. The best-fitting values and uncertainties for these power-law indices of the differential frequency distributions are: $\alpha^d_{E}=1.54 \pm 0.09$, $\alpha^d_{T}=1.82_{-0.15}^{+0.14}$ and $\alpha^d_{P}=2.09_{-0.19}^{+0.18}$, while the power-law indices in the cumulative frequency distributions are: $\alpha^c_{E}=1.44_{-0.10}^{+0.08}$, $\alpha^c_{T}=1.75_{-0.13}^{+0.11}$ and $\alpha^c_{P}=1.99_{-0.19}^{+0.16}$. We find that these distributions are roughly consistent with the physical framework of a Fractal-Diffusive, Self-Organized Criticality (FD-SOC) system with the spatial dimension $S=3$ and the classical diffusion $\beta$=1. Our results support that the jet responsible for the GRBs should be magnetically dominated and magnetic instabilities (e.g., kink model, or tearing-model instability) lead the GRB emission region into the SOC state.
Saliency detection based on the complementary information from RGB images and depth maps has recently gained great popularity. In this paper, we propose Complementary Attention and Adaptive Integration Network (CAAI-Net), a novel RGB-D saliency detection model that integrates complementary attention based feature concentration and adaptive cross-modal feature fusion into a unified framework for accurate saliency detection. Specifically, we propose a context-aware complementary attention (CCA) module, which consists of a feature interaction component, a complementary attention component, and a global-context component. The CCA module first utilizes the feature interaction component to extract rich local context features. The resulting features are then fed into the complementary attention component, which employs the complementary attention generated from adjacent levels to guide the attention at the current layer so that the mutual background disturbances are suppressed and the network focuses more on the areas with salient objects. Finally, we utilize a specially-designed adaptive feature integration (AFI) module, which sufficiently considers the low-quality issue of depth maps, to aggregate the RGB and depth features in an adaptive manner. Extensive experiments on six challenging benchmark datasets demonstrate that CAAI-Net is an effective saliency detection model and outperforms nine state-of-the-art models in terms of four widely-used metrics. In addition, extensive ablation studies confirm the effectiveness of the proposed CCA and AFI modules.
We present a microscopic calculation of multi-nucleon transfer reactions employing the time-dependent Hartree-Fock (TDHF) theory. In our previous publication [Phys. Rev. C 88, 014614 (2013)], we reported our analysis for the multi-nucleon transfer processes for several systems. Here we discuss effects of particle evaporation processes on the production cross sections. Since particle evaporation processes may not be described adequately by the TDHF calculations, we evaluate them using a statistical model. As an input of the statistical model, excitation energies of the final fragments are necessary. We evaluate them from the TDHF wave function after collisions, extending the particle number projection technique. From the calculation, the particle evaporation effects are found to improve descriptions of the production cross sections. However, the production cross sections are still underestimated for processes where a number of protons are transferred. Possible origins of the discrepancy are discussed.
Recognizing an event in an image can be enhanced by detecting relevant objects in two ways: 1) indirectly utilizing object detection information within the unified architecture or 2) directly making use of the object detection output results. We introduce a novel approach, referred to as Doubly-injected Object Detection CNN (DOD-CNN), exploiting the object information in both ways for the task of event recognition. The structure of this network is inspired by the Integrated Object Detection CNN (IOD-CNN) where object information is indirectly exploited by the event recognition module through the shared portion of the network. In the DOD-CNN architecture, the intermediate object detection outputs are directly injected into the event recognition network while keeping the indirect sharing structure inherited from the IOD-CNN, thus being `doubly-injected'. We also introduce a batch pooling layer which constructs one representative feature map from multiple object hypotheses. We have demonstrated the effectiveness of injecting the object detection information in two different ways in the task of malicious event recognition.
Any medium can be represented as an isometric subgraph of the hypercube, with each token of the medium represented by a particular equivalence class of arcs of the subgraph. Such a representation, although useful, is not especially revealing of the structure of a particular medium. We propose an axiomatic definition of the concept of a `mediatic graph'. We prove that the graph of any medium is a mediatic graph. We also show that, for any non-necessarily finite set S, there exists a bijection from the collection M of all the media on a given set S (of states) onto the collection G of all the mediatic graphs on S.
We prove It{\^o}'s formula for the flow of measures associated with an It{\^o} process having a bounded drift and a uniformly elliptic and bounded diffusion matrix, and for functions in an appropriate Sobolev-type space. This formula is the almost analogue, in the measure-dependent case, of the It{\^o}-Krylov formula for functions in a Sobolev space on $\mathbf{R}^+ \times \mathbf{R}^d $.
We consider first order transition amplitudes in external fields in QED in the expanding de Sitter space and point out that they are gauge dependent quantities. We examine the gauge variations of the amplitudes assuming a decoupling of the interaction at large times, which allows to conclude that the source of the problem lies in the fact that the frequencies of the modes in the infinite future become independent of the comoving momenta. We show that a possibility to assure the gauge invariance of the external field amplitudes is to restrict to potentials which vanish sufficiently fast at infinite times, and briefly discuss a number of options in the face of the possible gauge invariance violation in the full interacting theory.
Topological spin textures have attracted much attention both for fundamental physics and spintronics applications. Among them, antiskyrmions possess a unique spin configuration with Bloch-type and N\'eel-type domain walls due to anisotropic Dzyaloshinskii-Moriya interaction (DMI) in the noncentrosymmetric crystal structure. However, antiskyrmions have thus far only been observed in a few Heusler compounds with $D_{2\mathrm{d}}$ symmetry. Here, we report a new material Fe$_{1.9}$Ni$_{0.9}$Pd$_{0.2}$P in a different symmetry class ($S_4$ symmetry), where antiskyrmions exist over a wide temperature region including room temperature, and transform to skyrmions upon changing magnetic field and lamella thickness. The periodicity of magnetic textures greatly depends on crystal thickness, and domains with anisotropic sawtooth fractals are observed at the surface of thick crystals, which are attributed to the interplay between dipolar interaction and DMI as governed by crystal symmetry. Our findings provide a new arena to study antiskyrmions, and should stimulate further research on topological spin textures and their applications.
Pb2V3O9 was found to have antiferromagnetic alternating chains of S=1/2 and show the antiferromagnetic long range ordered (AFLRO) state under the magnetic field between 4 and 38 T. We succeeded in growing single crystals of Pb2V3O9 by floating zone method and determined the asymmetric H-T phase diagram of Pb2V3O9 from measurements of the magnetization and the heat capacity. Previous reports focused on the AFLRO state in the low magnetic field region and that in high magnetic field region was not discussed so much. In this paper, we examined the AFLRO state in terms of the mean field theory and the picture of Bose-Einstein condensation of magnons to discuss the whole phase diagram. Consequently, the asymmetry of the phase boundary in Pb2V3O9 is explained by the mixing contribution of excited states and by interchain interactions.
Some self-supervised cross-modal learning approaches have recently demonstrated the potential of image signals for enhancing point cloud representation. However, it remains a question on how to directly model cross-modal local and global correspondences in a self-supervised fashion. To solve it, we proposed PointCMC, a novel cross-modal method to model multi-scale correspondences across modalities for self-supervised point cloud representation learning. In particular, PointCMC is composed of: (1) a local-to-local (L2L) module that learns local correspondences through optimized cross-modal local geometric features, (2) a local-to-global (L2G) module that aims to learn the correspondences between local and global features across modalities via local-global discrimination, and (3) a global-to-global (G2G) module, which leverages auxiliary global contrastive loss between the point cloud and image to learn high-level semantic correspondences. Extensive experiment results show that our approach outperforms existing state-of-the-art methods in various downstream tasks such as 3D object classification and segmentation. Code will be made publicly available upon acceptance.
Stubbed plates, i.e., thin elastic sheets endowed with pillar-like resonators, display subwavelength, locally-resonant bandgaps that are primarily controlled by the intrinsic resonance properties of the pillars. In this work, we experimentally study the bandgap response of a tunable heterogeneous plate endowed with reconfigurable families of pillars. We demonstrate that, under certain circumstances, both the spectrum of resonant frequencies of the pillars and their spatial arrangement influence the filtering characteristics of the system. Specifically, both spatially graded and disordered arrangements result in bandgap widening. Moreover, the spectral range over which attenuation is achieved with random arrangements is on average wider than the one observed with graded configurations.
Seeking for next-generation energy sources that are economic, sustainable (renewable), clean (environment-friendly), and abundant in earth is crucial when facing the challenges of energy crisis. There have been numerous studies exploring the possibility of carbon based materials to be utilized in future energy applications. In this paper, we introduce T-carbon, which is a theoretically predicted but recently experimentally synthesized carbon allotrope, as a promising material for next-generation energy applications. It is shown that T-carbon can be potentially used in thermoelectrics, hydrogen storage, lithium ion batteries, \emph{etc}. The challenges, opportunities, and possible directions for future studies of energy applications of T-carbon are also addressed. With the development of more environment-friendly technologies, the promising applications of T-carbon in energy fields would not only produce scientifically significant impact in related fields but also lead to a number of industrial and technical applications.
The composition of ultra-high energy (UHE) cosmic rays E>10^17 eV is still unknown. The observation of UHE photons would extend the observed electromagnetic spectrum to highest energy and open a new channel for multimessenger observations in the universe. Current limits on the photon flux already constrain ``exotic'' scenarios where a large number of photons is expected by the decay products of supermassive X-particles. Motivated by the growing exposure of UHE cosmic ray experiments - like the Pierre Auger Observatory - the observation of conventionally produced GZK photons may be in reach in the near future. We investigate UHE particle propagation using the Monte Carlo code CRPropa. Particularly, the expected photon fluxes normalized to current experiments as well as prospects for future experiments are illustrated. Varying source and propagation scenarios are analyzed and the impact on secondary GZK photons is shown. For the specific case of Centaurus A, we study which source parameters can be tested by searching for the expected GZK photons.
We obtain lower tail estimates for the smallest singular value of random matrices with independent but non-identically distributed entries. Specifically, we consider $n\times n$ matrices with complex entries of the form \[ M = A\circ X + B = (a_{ij}\xi_{ij} + b_{ij}) \] where $X=(\xi_{ij})$ has iid centered entries of unit variance and $A$ and $B$ are fixed matrices. In our main result we obtain polynomial bounds on the smallest singular value of $M$ for the case that $A$ has bounded (possibly zero) entries, and $B= Z\sqrt{n}$ where $Z$ is a diagonal matrix with entries bounded away from zero. As a byproduct of our methods we can also handle general perturbations $B$ under additional hypotheses on $A$, which translate to connectivity hypotheses on an associated graph. In particular, we extend a result of Rudelson and Zeitouni for Gaussian matrices to allow for general entry distributions satisfying some moment hypotheses. Our proofs make use of tools which (to our knowledge) were previously unexploited in random matrix theory, in particular Szemer\'edi's Regularity Lemma, and a version of the Restricted Invertibility Theorem due to Spielman and Srivastava.