ShantanuT01/DACTYL-Pretraining huggingface dataset:
Stellar dynamical modeling is a powerful method to determine the mass of black holes in quiescent galaxies. However, in previous work the presence of a dark matter halo has been ignored in the modeling. Gebhardt & Thomas (2009) showed that accounting for a dark matter halo increased the black hole mass of the massive galaxy M87 by a factor of two. We used a sample of 12 galaxies to investigate the effect of accounting for a dark matter halo in the dynamical modeling in more detail, and also updated the masses using improved modeling. The sample of galaxies possesses Hubble Space Telescope and ground based observations of stellar kinematics. Their black hole masses have been presented before, but without including a dark matter halo in the models. Without a dark halo, we find a mean increase in the estimated mass of 1.5 for the whole sample compared to previous results. We attribute this change to using a more complete orbit library. When we include a dark matter halo, along with the updated models, we find an additional increase in black hole mass by a factor of 1.2 in the mean, much less than for M87. We attribute the smaller discrepancy in black hole mass to using data that better resolves the black hole's sphere of influence. We redetermined the M-sigma and M-L relationships using our updated black hole masses and found a slight increase in both normalization and intrinsic scatter.
We generalize a class of Heisenberg antiferromagnets in one, two and three dimensions, which have been shown to exhibit magnetization plateaus for spin-1/2. In a certain parameter range of the general model, which is formally defined in D dimensions, we obtain the exact ground state(s) in the presence of an external magnetic field for arbitrary values of spin. In this range, the magnetization remains a constant as a function of the external field, except at some special values of the field where there is a jump from one plateau to the next. The plateaus are formed at certain specific fractions of the full magnetization which are determined by the spin and the lattice. Our general spin-S result reproduces the known cases for spin-1/2 in various lattices. Furthermore, we argue that outside the exact regime, the mechanism for the plateau formation is different. This results in first order phase transitions along some of the plateaus as the coupling constant is varied. We rigorously show the existence of such transitions for some particular cases. Finally, we numerically analyze a spin-1 model in one dimension using exact diagonalization to obtain its complete phase diagram. It agrees with our analytic results.
The heavy baryon \Lambda_{Q} (Q=b or c) can be regarded as composed of a heavy quark and a scalar light diquark which has good spin and isospin quantum numbers. In this picture we establish the Bethe-Salpeter (BS) equation for \Lambda_{Q} to second order in the 1/m_{Q} expansion. With the kernel containing both the scalar confinement and the one-gluon-exchange terms we solve the BS equation numerically. The value of the spin-dependant form factor for the matrix element <\Lambda_{b}{(v,s)}|\bar{b}\gamma^{\lambda}\gamma_{5}b|\Lambda_{b}(v,s)>, \epsilon_{b}, which is non-zero at order 1/m^{2}_{b}, is obtained numerically from our model.
We study the thermodynamical properties of compressed baryonic matter with strangeness within non-relativistic energy density functional models with a particular emphasis on possible phase transitions found earlier for a simple $n,p,e,\Lambda$-mixture. The aim of the paper is twofold: I) examining the phase structure of the complete system, including the full baryonic octet and II) testing the sensitivity of the results to the model parameters. We find that, associated to the onset of the different hyperonic families, up to three separate strangeness-driven phase transitions may occur. Consequently, a large fraction of the baryonic density domain is covered by phase coexistence with potential relevance for (proto)-neutron star evolution. It is shown that the presence of a phase transition is compatible both with the observational constraint on the maximal neutron star mass, and with the present experimental information on hypernuclei. In particular we show that two solar mass neutron stars are compatible with important hyperon content. Still, the parameter space is too large to give a definitive conclusion of the possible occurrence of a strangeness driven phase transition, and further constraints from multiple-hyperon nuclei and/or hyperon diffusion data are needed.
Domain adaptation is of huge interest as labeling is an expensive and error-prone task, especially when labels are needed on pixel-level like in semantic segmentation. Therefore, one would like to be able to train neural networks on synthetic domains, where data is abundant and labels are precise. However, these models often perform poorly on out-of-domain images. To mitigate the shift in the input, image-to-image approaches can be used. Nevertheless, standard image-to-image approaches that bridge the domain of deployment with the synthetic training domain do not focus on the downstream task but only on the visual inspection level. We therefore propose a "task aware" version of a GAN in an image-to-image domain adaptation approach. With the help of a small amount of labeled ground truth data, we guide the image-to-image translation to a more suitable input image for a semantic segmentation network trained on synthetic data (synthetic-domain expert). The main contributions of this work are 1) a modular semi-supervised domain adaptation method for semantic segmentation by training a downstream task aware CycleGAN while refraining from adapting the synthetic semantic segmentation expert 2) the demonstration that the method is applicable to complex domain adaptation tasks and 3) a less biased domain gap analysis by using from scratch networks. We evaluate our method on a classification task as well as on semantic segmentation. Our experiments demonstrate that our method outperforms CycleGAN - a standard image-to-image approach - by 7 percent points in accuracy in a classification task using only 70 (10%) ground truth images. For semantic segmentation we can show an improvement of about 4 to 7 percent points in mean Intersection over union on the Cityscapes evaluation dataset with only 14 ground truth images during training.
The most stringent local measurement of the Hubble-Lema\^itre constant from Cepheid-calibrated Type Ia supernovae (SNe~Ia) differs from the value inferred via the cosmic microwave background radiation ({\it Planck}$+\Lambda$CDM) by $\sim 5\sigma$. This so-called "Hubble tension" has been confirmed by other independent methods, and thus does not appear to be a possible consequence of systematic errors. Here, we continue upon our prior work of using Type II supernovae to provide another, largely-independent method to measure the Hubble-Lema\^itre constant. From 13 SNe~II with geometric, Cepheid, or tip of the red giant branch (TRGB) host-galaxy distance measurements, we derive H$_0= 75.4^{+3.8}_{-3.7}$\,km\,s$^{-1}$\,Mpc$^{-1}$ (statistical errors only), consistent with the local measurement but in disagreement by $\sim 2.0\sigma$ with the {\it Planck}$+\Lambda$CDM value. Using only Cepheids ($N=7$), we find H$_0 = 77.6^{+5.2}_{-4.8}$\,km\,s$^{-1}$\,Mpc$^{-1}$, while using only TRGB ($N=5$), we derive H$_0 = 73.1^{+5.7}_{-5.3}$\,km\,s$^{-1}$\,Mpc$^{-1}$. Via 13 variants of our dataset, we derive a systematic uncertainty estimate of 1.5\,km\,s$^{-1}$\,Mpc$^{-1}$. The median value derived from these variants differs by just 0.3\,km\,s$^{-1}$\,Mpc$^{-1}$ from that produced by our fiducial model. Because we only replace SNe~Ia with SNe~II -- and we do not find statistically significant difference between the Cepheid and TRGB H$_0$ measurements -- our work reveals no indication that SNe~Ia or Cepheids could be the sources of the "H$_0$ tension." We caution, however, that our conclusions rest upon a modest calibrator sample; as this sample grows in the future, our results should be verified.
Black hole (BH) spectroscopy has emerged as a powerful approach to extract spacetime information from gravitational wave (GW) observed signals. Yet, quasinormal mode (QNM) spectral instability under high wave-number perturbations has been recently shown to be a common classical general relativistic phenomenon [1]. This requires to assess its impact on the BH QNM spectrum, in particular on BH QNM overtone frequencies. We conclude: i) perturbed BH QNM overtones are indeed potentially observable in the GW waveform, providing information on small-scale environment BH physics, and ii) their detection poses a challenging data analysis problem of singular interest for LISA astrophysics. We adopt a two-fold approach, combining theoretical results from scattering theory with a fine-tuned data analysis on a highly-accurate numerical GW ringdown signal. The former introduces a set of effective parameters (partially lying on a BH Weyl law) to characterise QNM instability physics. The latter provides a proof-of-principle demonstrating that the QNM spectral instability is indeed accessible in the time-domain GW waveform, though certainly requiring large signal-to-noise ratios. Particular attention is devoted to discuss the patterns of isospectrality loss under QNM instability, since the disentanglement between axial and polar GW parities may already occur within the near-future detection range.
In the last decade, two revolutionary concepts in nano magnetism emerged from research for storage technologies and advanced information processing. The first suggests the use of magnetic domain walls (DWs) in ferromagnetic nanowires to permanently store information in DW racetrack memories. The second proposes a hardware realisation of neuromorphic computing in nanomagnets using nonlinear magnetic oscillations in the GHz range. Both ideas originate from the transfer of angular momentum from conduction electrons to localised spins in ferromagnets, either to push data encoded in DWs along nanowires or to sustain magnetic oscillations in artificial neurones. Even though both concepts share a common ground, they live on very different time scales which rendered them incompatible so far. Here, we bridge both ideas by demonstrating the excitation of magnetic auto-oscillations inside nano-scale DWs using pure spin currents.
In this paper, we propose to disentangle and interpret contextual effects that are encoded in a pre-trained deep neural network. We use our method to explain the gaming strategy of the alphaGo Zero model. Unlike previous studies that visualized image appearances corresponding to the network output or a neural activation only from a global perspective, our research aims to clarify how a certain input unit (dimension) collaborates with other units (dimensions) to constitute inference patterns of the neural network and thus contribute to the network output. The analysis of local contextual effects w.r.t. certain input units is of special values in real applications. Explaining the logic of the alphaGo Zero model is a typical application. In experiments, our method successfully disentangled the rationale of each move during the Go game.
We present the observation of the Tycho supernova remnant obtained with the EPIC and RGS instruments onboard the XMM-Newton satellite. We compare images and azimuthally averaged radial profiles in emission lines from different elements (silicon and iron) and different transition lines of iron (Fe L and Fe K). While the Fe XVII L line and Si XIII K line images are globally spatially coincident, the Fe K emission clearly peaks at a smaller radius, indicating a higher temperature toward the reverse shock. This is qualitatively the profile expected when the reverse shock, after travelling through the outer power-law density profile, has entered the central plateau of the ejecta. The high energy continuum map has an overall smooth distribution, with a similar extent to the radio emission. Its radial profile peaks further out than the lines emission. Brighter and harder continuum regions are observed with a rough bipolar symmetry in the eastern and western edges. The spectral analysis of the southeastern knots supports spatial variations of the relative abundance of silicon and iron, which implies an incomplete mixing of the silicon and iron layers.
Colossal magneto-resistance manganites are characterised by a complex interplay of charge, spin, orbital and lattice degrees of freedom. Formulating microscopic models for these compounds aims at meeting to conflicting objectives: sufficient simplification without excessive restrictions on the phase space. We give a detailed introduction to the electronic structure of manganites and derive a microscopic model for their low energy physics. Focussing on short range electron-lattice and spin-orbital correlations we supplement the modelling with numerical simulations.
We perform an analysis of the line-of-sight (LOS) observables of the SDO/HMI for models of the solar atmosphere heated by precipitating high-energy electrons during solar flares. The radiative hydrodynamic (RADYN) flare models are obtained from the F-CHROMA database. The Stokes profiles for the Fe 6173 A line observed by SDO/HMI are calculated using the radiative transfer code RH1.5D assuming statistical equilibrium for atomic level populations and imposing uniform background vertical magnetic field of various strength. The SDO/HMI observing sequence and LOS data processing pipeline algorithm are applied to derive the observables (continuum intensity, line depth, Doppler velocity, LOS magnetic field). Our results reveal that the strongest deviations of the observables from the actual spectroscopic line parameters are found for the model with a total energy deposited of $E_{total}=1.0\times{}10^{12}$ erg cm$^{-2}$, injected with power-law spectral index of $\delta=3$ above a low-energy cutoff of $E_{c}=25$ keV. The magnitudes of the velocity and magnetic field deviations depend on the imposed magnetic field, and can reach 0.35 km/s for LOS velocities, 90 G for LOS magnetic field, and 3\% for continuum enhancement for the 1000 G imposed LOS magnetic field setup. For $E_{total}\geq{}3.0\times{}10^{11}$ erg cm$^{-2}$ models, the velocity and magnetic field deviations are most strongly correlated with the energy flux carried by $\sim$50 keV electrons, and the continuum enhancement is correlated with the synthesized $\sim$55-60 keV hard X-ray photon flux. The relatively low magnitudes of perturbations of the observables and absence of magnetic field sign reversals suggest that the considered radiative hydrodynamic beam heating models augmented with the uniform vertical magnetic field setups cannot explain strong transient changes found in the SDO/HMI observations.
We demonstrate high yield fabrication of field effect transistors (FET) using chemically reduced graphene oxide (RGO) sheets suspended in water assembled via dielectrophoresis. The two terminal resistances of the devices were improved by an order of magnitude upon mild annealing at 200 0C in Ar/H2 environment for 1 hour. With the application of a backgate voltage, all of the devices showed FET behavior with maximum hole and electron mobilities of 4.0 and 1.5 cm2/Vs respectively. This study shows promise for scaled up fabrication of graphene based nanoelectronic devices.
The surface detector of the Pierre Auger Observatory is a 1600 water Cherenkov tank array on a triangular 1.5 km grid. The signals from each tank are read out using three 9'' photomultipliers and processed at a sampling frequency of 40 MHz, from which a local digital trigger efficiently selects shower candidates. GPS signals are used for time synchronization and a wireless communication system connects all tanks to the central data acquisition system. Power is provided by a stand-alone solar panel system. With large ambient temperature variations, that can reach over 20 degrees in 24 hours, high salinity, dusty air, high humidity inside the tank, and remoteness of access, the performance and reliability of the array is a challenge. Several key parameters are constantly monitored to ensure consistent operation. The Surface Array has currently over 750 detectors and has been in reliable operation since January 2004. Good uniformity in the response of different detectors and good long term stability is observed.
Pseudospin symmetry in nuclei is investigated by solving the Dirac equation with Woods-Saxon scalar and vector radial potentials, and studying the correlation of the energy splittings of pseudospin partners with the nuclear potential parameters. The pseudospin interaction is related to a pseudospin-orbit term that arises in a Schroedinger-like equation for the lower component of the Dirac spinor. We show that the contribution from this term to the energy splittings of pseudospin partners is large. The near pseudospin degeneracy results from a significant cancelation among the different terms in that equation, manifesting the dynamical character of this symmetry in the nucleus. We analyze the isospin dependence of the pseudospin symmetry and find that its dynamical character is behind the different pseudospin splittings observed in neutron and proton spectra of nuclei.
This is the second of two papers in which we study real and virtual photon-proton scattering in a nonperturbative framework. In the first paper we have identified the leading contributions to this process at high energies and have derived expressions for them which take into account the renormalisation of the photon-quark-antiquark vertex. In the present paper we investigate the approximations and assumptions that are necessary to obtain the dipole model of high energy scattering from the results derived in the first paper. We discuss the gauge invariance of different contributions to the scattering amplitude and point out some subtleties related to gauge invariance in the correct definition of a perturbative photon wave function. As a phenomenological consequence of the dipole picture we derive a bound on the ratio of the cross sections for longitudinally and transversely polarised photons. This bound is independent of any particular model for the dipole-proton cross section and allows one to test the validity of the assumptions leading to the dipole picture in particular at low photon virtualities. We conclude that the naive dipole model formula should be supplemented by two additional terms which can potentially become large at small photon virtualities.
The Ising double chain has been overlooked for more than 80 years, since one was mostly interested in phase transitions. We consider two types of degeneracy, spin occupation degeneracy and "bond" occupation degeneracy. We show that bond occupation on "open nets" is of particular importance for the understanding of melting. The number of open nets on a double chain is determined analytically. If only one bond site of a net is occupied, this already produces a definite number of bonds on sites, bonds that do not belong to the net. All nets on a given chain of length $n$ then yield a total number $i^{(n)}_{\rm tot}$ of bonds, allowing to calculate a characteristic energy $u^{(n)}_{ch}$, an approximation of the critical energy $u_c$ of the infinite double chain. We finally present an explanation for the critical energy $u^{\rm KG}_c$ of the kagom\'e lattice in terms of the critical energies $u^{\rm TR}_c$ and $u^{\rm HC}_c$ of the triangular and honeycomb lattices.
Most domain adaptation methods consider the problem of transferring knowledge to the target domain from a single source dataset. However, in practical applications, we typically have access to multiple sources. In this paper we propose the first approach for Multi-Source Domain Adaptation (MSDA) based on Generative Adversarial Networks. Our method is inspired by the observation that the appearance of a given image depends on three factors: the domain, the style (characterized in terms of low-level features variations) and the content. For this reason we propose to project the image features onto a space where only the dependence from the content is kept, and then re-project this invariant representation onto the pixel space using the target domain and style. In this way, new labeled images can be generated which are used to train a final target classifier. We test our approach using common MSDA benchmarks, showing that it outperforms state-of-the-art methods.
Spatial-Temporal Video Super-Resolution (ST-VSR) aims to generate super-resolved videos with higher resolution(HR) and higher frame rate (HFR). Quite intuitively, pioneering two-stage based methods complete ST-VSR by directly combining two sub-tasks: Spatial Video Super-Resolution (S-VSR) and Temporal Video Super-Resolution(T-VSR) but ignore the reciprocal relations among them. Specifically, 1) T-VSR to S-VSR: temporal correlations help accurate spatial detail representation with more clues; 2) S-VSR to T-VSR: abundant spatial information contributes to the refinement of temporal prediction. To this end, we propose a one-stage based Cycle-projected Mutual learning network (CycMu-Net) for ST-VSR, which makes full use of spatial-temporal correlations via the mutual learning between S-VSR and T-VSR. Specifically, we propose to exploit the mutual information among them via iterative up-and-down projections, where the spatial and temporal features are fully fused and distilled, helping the high-quality video reconstruction. Besides extensive experiments on benchmark datasets, we also compare our proposed CycMu-Net with S-VSR and T-VSR tasks, demonstrating that our method significantly outperforms state-of-the-art methods.
The surface magnetic field strength of white dwarfs is observed to vary from very little to around 10^9 G. Here we examine the proposal that the strongest fields are generated by dynamo action during the common envelope phase of strongly interacting stars that leads to binary systems containing at least one white dwarf. The resulting magnetic field depends strongly on the electrical conductivity of the white dwarf, the lifetime of the convective envelope and the variability of the magnetic dynamo. We assess the various energy sources available and estimate necessary lifetimes of the common envelope. In the case of a dynamo that leads a randomly oriented magnetic field we find that the induced field is confined to a thin boundary layer at the surface of the white dwarf. This then decays away rapidly upon dispersal of the common envelope. The residual field is typically less than 10^-8 times the strength of the external field. Only in the case where there is some preferential direction to the dynamo-generated field can an induced field, that avoids rapid decay, be produced. We show that a surface field of magnitude a few per cent of the external field may be produced after a few Myr. In this case the residual field strength is roughly proportional to the lifetime of the dynamo activity.
We present an on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry. Using a combination of vision and odometry that are tightly integrated we can increase the overall performance of object based tracking for semantic mapping. We present a framework for integration of the two data-sources into a coherent framework through information based fusion/arbitration. We demonstrate the framework in the context of OmniMapper[1] and present results on 6 challenging sequences over multiple objects compared to data obtained from a motion capture systems. We are able to achieve a mean error of 0.23m for per frame tracking showing 9% relative error less than state of the art tracker.
The present status of our understanding of low mass dilepton production in relativistic heavy ion collisions is discussed. The focus of the discussion will be the sensitivity of dilepton measurements to in medium changes of hadrons and the restoration of chiral symmetry. We will finally discuss how the presence of strong long wavelength pion modes, i.e. disoriented chiral condensates can be seen in the dilepton spectrum.