ShantanuT01/DACTYL-Pretraining huggingface dataset:
Mergers of galaxies have been suspected to be a major trigger of AGN activity for many years. However, when compared to carefully matched control samples, AGN host galaxies often show no enhanced signs of interaction. A common explanation for this lack of observed association between AGN and mergers has often been that while mergers are of importance for triggering AGN, they only dominate at the very high luminosity end of the AGN population. In this study, we compare the morphologies of AGN hosts to a carefully matched control sample and particularly study the role of AGN luminosity. We find no enhanced merger rates in AGN hosts and also find no trend for stronger signs of disturbance at higher AGN luminosities. While this study does not cover very high luminosity AGN, we can exclude a strong connection between AGN and mergers over a wide range of AGN luminosities and therefore for a large part of the AGN population.
For any odd $n$, we describe a smooth minimal (i.e. obtained by adding an irreducible hypersurface) compactification $\tilde S_n$ of the quasi-projective homogeneous variety $S_{n}=PGL(n+1)/SL(2)$ that parameterizes the rational normal curves in $P^n$. We show that $\tilde S_{n}$ is isomorphic to a component of the Maruyama scheme of the semi-stable sheaves on $P^n$ of rank $n$ and Chern polynomial $(1+t)^{n+2}$ and we compute its Betti numbers.   In particular $\tilde S_{3}$ is isomorphic to the variety of nets of quadrics defining twisted cubics, studied by G. Ellinsgrud, R. Piene and S. Str{\o}mme (Space curves, Proc. Conf., LNM 1266).
We study the palindrome complexity of infinite sequences on finite alphabets, i.e., the number of palindromic factors (blocks) of given length occurring in a given sequence. We survey the known results and obtain new results for some sequences, in particular for Rote sequences and for fixed points of primitive morphisms of constant length belonging to the class P substitutions of Hof-Knill-Simon. We also give an upper bound for the palindrome complexity of a sequence in terms of its (block-)complexity.
Let a and b be positive integers with a \leq b. An (a,b)-triple is a set {x,ax+d,bx+ 2d}, where x,d \geq 1. Define T(a,b;r) to be the least positive integer n such that any r-coloring of {1,2...,n} contains a monochromatic (a,b)-triple. Earlier results gave an upper bound on T(a,b;2) that is a fourth degree polynomial in b and a, and a quadratic lower bound. A new upper bound for T(a,b;2) is given that is a quadratic. Additionally, lower bounds are given for the case in which a = b, updated tables are provided, and open questions are presented.
Thin film YIG (Y$_3$Fe$_5$O$_{12}$) is a prototypical material for experiments on thermally generated pure spin currents and the spin Seebeck effect. The 3-omega method is an established technique to measure the cross-plane thermal conductance of thin films, but can not be used in YIG/GGG (Ga$_3$Gd$_5$O$_{12}$) systems in its standard form. We use two-dimensional modeling of heat transport and introduce a technique based on Bayesian statistics to evaluate measurement data taken from the 3-omega method. Our analysis method allows us to study materials systems that have not been accessible with the conventionally used 3-omega analysis. Temperature dependent thermal conductance data of thin film YIG are of major importance for experiments in the field of spin-caloritronics. Here we show data between room temperature and 10 K for films covering a wide thickness range as well as the magnetic field effect on the thermal conductance between 10 K and 50 K.
The purpose of this article is to present closed forms for various types of infinite series involving Fibonacci (Lucas) numbers and the Riemann zeta function at integer arguments.
We present a unified theoretical framework for computing spin-independent direct detection rates via various channels relevant for sub-GeV dark matter -- nuclear recoils, electron transitions and single phonon excitations. Despite the very different physics involved, in each case the rate factorizes into the particle-level matrix element squared, and an integral over a target material- and channel-specific dynamic structure factor. We show how the dynamic structure factor can be derived in all three cases following the same procedure, and extend previous results in the literature in several aspects. For electron transitions, we incorporate directional dependence and point out potential daily modulation signals in anisotropic target materials. For single phonon excitations, we present a new derivation of the rate formula from first principles for generic spin-independent couplings, and include the first calculation of phonon excitation through electron couplings. We also discuss the interplay between single phonon excitations and nuclear recoils, and clarify the role of Umklapp processes, which can dominate the single phonon production rate for dark matter heavier than an MeV. Our results highlight the complementarity between various search channels in probing different kinematic regimes of dark matter scattering, and provide a common reference to connect dark matter theories with ongoing and future direct detection experiments.
We report on the calculation of Gamow-Teller and double-beta decay properties for nuclei around 132Sn within the framework of the realistic shell model. The effective shell-model Hamiltonian and Gamow-Teller transition operator are derived by way of many-body perturbation theory, without resorting to empirical effective quenching factor for the Gamow-Teller operator. The results are then compared with the available experimental data, in order to establish the reliability of our approach. This is a mandatory step, before we apply the same methodology, in forthcoming studies, to the calculation of the neutrinoless double-beta decay nuclear matrix element for nuclei that are currently considered among the best candidates for the detection of this process.
The effect of magnetic domain boundaries displacement induced by electric field is observed in epitaxial ferrite garnet films (on substrates with the (210) crystallographic orientation). The effect is odd with respect to the electric field (the direction of wall displacement changes with the polarity of the voltage) and even with respect to the magnetization in domains. The inhomogeneous magnetoelectric interaction as a possible mechanism of the effect is proposed.
Quantitative morphologies, such as asymmetry and concentration, have long been used as an effective way to assess the distribution of galaxy starlight in large samples. Application of such quantitative indicators to other data products could provide a tool capable of capturing the 2-dimensional distribution of a range of galactic properties, such as stellar mass or star-formation rate maps. In this work, we utilize galaxies from the Illustris and IllustrisTNG simulations to assess the applicability of concentration and asymmetry indicators to the stellar mass distribution in galaxies. Specifically, we test whether the intrinsic values of concentration and asymmetry (measured directly from the simulation stellar mass particle maps) are recovered after the application of measurement uncertainty and a point spread function (PSF). We find that random noise has a non-negligible systematic effect on asymmetry that scales inversely with signal-to-noise, particularly at signal-to-noise less than 100. We evaluate different methods to correct for the noise contribution to asymmetry at very low signal-to-noise, where previous studies have been unable to explore due to systematics. We present algebraic corrections for noise and resolution to recover the intrinsic morphology parameters. Using Illustris as a comparison dataset, we evaluate the robustness of these fits in the presence of a different physics model, and confirm these correction methods can be applied to other datasets. Lastly, we provide estimations for the uncertainty on different correction methods at varying signal-to-noise and resolution regimes.
Intestinal enteroendocrine cells secrete hormones that are vital for the regulation of glucose metabolism but their differentiation from intestinal stem cells is not fully understood. Asymmetric stem cell divisions have been linked to intestinal stem cell homeostasis and secretory fate commitment. We monitored cell divisions using 4D live cell imaging of cultured intestinal crypts to characterize division modes by means of measurable features such as orientation or shape. A statistical analysis of these measurements requires annotation of mitosis events, which is currently a tedious and time-consuming task that has to be performed manually. To assist data processing, we developed a learning based method to automatically detect mitosis events. The method contains a dual-phase framework for joint detection of dividing cells (mothers) and their progeny (daughters). In the first phase we detect mother and daughters independently using Hough Forest whilst in the second phase we associate mother and daughters by modelling their joint probability as Conditional Random Field (CRF). The method has been evaluated on 32 movies and has achieved an AUC of 72%, which can be used in conjunction with manual correction and dramatically speed up the processing pipeline.
In this article we consider the discretely self-similar singular solutions of the Euler equations, and the possible velocity profiles concerned not only have decaying spatial asymptotics, but also have unconventional non-decaying asymptotics. By relying on the local energy inequality of the velocity profiles and the bootstrapping method, we prove some nonexistence results and show the energy behavior of the possible nontrivial velocity profiles. For the case with non-decaying asymptotics, the needed representation formula of the pressure profile in terms of velocity profiles is also given and justified.
Here, we report on the experimental discovery of biskyrmion magnetic nanodomains at RT and the observation of a biskyrmion-derived topological Hall effect (THE) in the centrosymmetric hexagonal MnNiGa magnet. Using a phase reconstruction technique based on a transport-of-intensity equation (TIE), we established the texture of the biskyrmion spin. Results from Lorentz transmission electron microscopy (TEM) and the topological Hall effect revealed that the biskyrmion phase is stable over a much wider temperature range (100 K to ~340K) and a larger magnetic field range in our material than in skyrmion-hosting bulk crystals reported previously[1-3,6]. The super-wide operating temperature and the broad range of material options indicate important progress toward the realization of skyrmion-based spintronic devices.
This manuscript introduces a new analytical approach for studying the time evolution of disease spread on a finite size network. Our methodology can accommodate any disease with a general infectivity profile. This new approach is able to incorporate the impact of a general intervention - at the population level - in a number of different ways. Below, we discuss the details of the equations involved and compare the outcomes of analytical calculation against simulation results. We conclude with a discussion of possible extensions of this methodology.
We report an analysis of the archival Rossi X-ray Timing Explorer (RXTE) data from the December 2004 hyperflare from SGR 1806-20. In addition to the 90 Hz QPO first discovered by Israel et al., we report the detection of higher frequency oscillations at 150, 625, and 1,840 Hz. In addition, we also find indications of oscillations at 720, and 2,384 Hz, but with lower significances. The 150 Hz QPO has a width (FWHM) of about 17 Hz, an average amplitude (rms) of 6.8 %, and is detected in average power spectra centered on the rotational phase of the strongest peak in the pulse profile. This is approximately half a cycle from the phase at which the 90 Hz QPO is detected. The 625 Hz oscillation was detected in an average power spectrum from nine successive cycles beginning approximately 180 s after the initial hard spike. It has a width (FWHM) of 2 Hz and an average amplitude (rms) during this interval of 8.5 %. We find a strong detection of the 625 Hz oscillation in a pair of successive rotation cycles begining about 230 s after the start of the flare. In these cycles we also detect the 1,840 Hz QPO. When the 625 Hz QPO is detected we also confirm the simultaneous presence of 30 and 92 Hz QPOs. The centroid frequency of the 625 Hz QPO detected with RXTE is within 1 Hz of the 626 Hz oscillation recently found in RHESSI data from this hyperflare by Watts & Strohmayer. We argue that these new findings provide further evidence for a connection of these oscillations with global oscillation modes of neutron stars, in particular, the high frequency signals may represent toroidal modes with at least one radial node in the crust. We discuss their implications in the context of this model, in particular for the depth of neutron star crusts
It is known that humans display "shape bias" when classifying new items, i.e., they prefer to categorize objects based on their shape rather than color. Convolutional Neural Networks (CNNs) are also designed to take into account the spatial structure of image data. In fact, experiments on image datasets, consisting of triples of a probe image, a shape-match and a color-match, have shown that one-shot learning models display shape bias as well.   In this paper, we examine the shape bias property of CNNs. In order to conduct large scale experiments, we propose using the model accuracy on images with reversed brightness as a metric to evaluate the shape bias property. Such images, called negative images, contain objects that have the same shape as original images, but with different colors. Through extensive systematic experiments, we investigate the role of different factors, such as training data, model architecture, initialization and regularization techniques, on the shape bias property of CNNs. We show that it is possible to design different CNNs that achieve similar accuracy on original images, but perform significantly different on negative images, suggesting that CNNs do not intrinsically display shape bias. We then show that CNNs are able to learn and generalize the structures, when the model is properly initialized or data is properly augmented, and if batch normalization is used.
The results of the investigation of electromagnetic field effects on the process of beta decay are used for analyzing experimental data on direct neutrino mass search.
We investigate the capability of ongoing radio telescopes for probing Faraday rotation measure (RM) due to the intergalactic magnetic field (IGMF) in the large-scale structure of the universe which is expected to be of order $O(1) {\rm rad/m^2}$. We consider polarization observations of a compact radio source such as quasars behind a diffuse source such as the Galaxy, and calculate Stokes parameters $Q$ and $U$ assuming a simple model of the Faraday dispersion functions with Gaussian shape. Then, we perform the Fisher analysis to estimate the expected errors in the model parameters from QU-fitting of polarization intensity, accounting for sensitivities and frequency bands of Australian Square Kilometer Array Pathfinder, Low Frequency Array, and the Giant Meterwave Radio Telescope. Finally, we examine the condition on the source intensities which are required to detect the IGMF. Our analysis indicates that the QU-fitting is promising for forthcoming wideband polarimetry to explore RM due to the IGMF in filaments of galaxies.
On a bounded smooth domain we study solutions of a semilinear elliptic equation with an exponential nonlinearity and a Hardy potential depending on the distance to the boundary of the domain. We derive global a priori bounds of the Keller-Osserman type. Using a Phragmen-Lindelof alternative for generalized sub and super-harmonic functions we discuss existence, nonexistence and uniqueness of so-called large solutions, i.e., solutions which tend to infinity at the boundary. The approach develops the one used by the same authors for a problem with a power nonlinearity instead of the exponential nonlinearity.
We study the impact of lensing magnification on the observed three-dimensional galaxy clustering in redshift space. We used the RayGal suite of N-body simulations, from which we extracted samples of dark matter particles and haloes in the redshift regime of interest for future large redshift surveys. Several magnitude-limited samples were built that reproduce various levels of magnification bias ranging from s = 0 to s = 1.2, where s is the logarithmic slope of the cumulative magnitude number counts, in three redshift intervals within 1 < z < 1.95. We studied the two-point correlation function multipole moments in the different cases in the same way as would be applied to real data, and investigated how well the growth rate of structure parameter could be recovered. In the analysis, we used an hybrid model that combines non-linear redshift-space distortions and linear curved-sky lensing magnification. We find that the growth rate is underestimated when magnification bias is not accounted for in the modelling. This bias becomes non-negligible for z > 1.3 and can reach 10% at z = 1.8, depending on the properties of the target sample. In our data, adding the lensing linear correction allowed us to recover an unbiased estimate of the growth rate in most cases when the correction was small, even when the fiducial cosmology was different from that of the data. For larger corrections (high redshifts, low bias, and high s value), we find that the weak-lensing limit has to be treated with caution as it may no longer be a good approximation . Our results also show the importance of knowing s in advance instead of letting this parameter free with flat priors because in this case, the error bars increase significantly.
Image inpainting has achieved remarkable progress and inspired abundant methods, where the critical bottleneck is identified as how to fulfill the high-frequency structure and low-frequency texture information on the masked regions with semantics. To this end, deep models exhibit powerful superiority to capture them, yet constrained on the local spatial regions. In this paper, we delve globally into texture and structure information to well capture the semantics for image inpainting. As opposed to the existing arts trapped on the independent local patches, the texture information of each patch is reconstructed from all other patches across the whole image, to match the coarsely filled information, specially the structure information over the masked regions. Unlike the current decoder-only transformer within the pixel level for image inpainting, our model adopts the transformer pipeline paired with both encoder and decoder. On one hand, the encoder captures the texture semantic correlations of all patches across image via self-attention module. On the other hand, an adaptive patch vocabulary is dynamically established in the decoder for the filled patches over the masked regions. Building on this, a structure-texture matching attention module anchored on the known regions comes up to marry the best of these two worlds for progressive inpainting via a probabilistic diffusion process. Our model is orthogonal to the fashionable arts, such as Convolutional Neural Networks (CNNs), Attention and Transformer model, from the perspective of texture and structure information for image inpainting. The extensive experiments over the benchmarks validate its superiority. Our code is available at https://github.com/htyjers/DGTS-Inpainting.
We generalize to the Kerr spacetime existing self-force results on tidal invariants for particles moving along circular orbits around a Schwarzschild black hole. We obtain linear-in-mass-ratio corrections to the quadratic and cubic electric-type invariants and the quadratic magnetic-type invariant in series of the rotation parameter up to the fourth order. We then construct the eigenvalues of both electric and magnetic tidal tensors and analytically compute them through high post-Newtonian orders.
Predictions of nuclear properties far from measured data are inherently imprecise because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when input variables such as proton or neutron number are extrapolated, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We show that feature selection can systematically improve theoretical predictions without increasing uncertainties.
We study the survival probability of an immobile target in presence of N independent diffusing walkers. We address the problem of the Mean Target Lifetime and its dependence on the number and initial distribution of the walkers when the trapping is perfect or imperfect. We consider the diffusion on lattices and in the continuous space and we address the bulk limit corresponding to a density of diffusing particles and only one isolated trap. Also, we use intermittent motion for optimization of search strategies.
Aims: We characterise the properties of stars, dust, and gas and their spatial distribution in the central region of the Seyfert 2 galaxy NGC1068. Method: Our study is based on near-infrared (YJH, 0.95-1.650 um, R=350) long-slit spectroscopy observations of the central region of NGC 1068 with a 0.4" spatial resolution. We decomposed the observed continuum emission into three components: hot dust, stars, and scattered light from the central engine. We measured their contributions at various distances from the nucleus. We also measured fluxes and Doppler shifts for the emission lines in our spectrum to probe the physical conditions of the narrow line region. Results: Dust and stars are the main sources of continuum emission, but scattered light from the central engine has also been detected in the very central region. Together, these three components reproduce the observed continuum well. The dust emission is compatible with a 830~K blackbody. It has only been detected in the very central region and is not spatially resolved. The stellar content is ubiquitous. It harbours a 250 pc cusp centred around the nucleus, over-imposed on a young stellar background. The spectrum of the cusp is consistent with a 120 Myr old single stellar population. Finally, the emission lines exhibit a significant Doppler shift that is consistent with a radial outflow from the nucleus in a biconical structure. The $\left[Fe\ II\right]$ behaviour strongly differs from other lines, indicating that it arises from a different structure.
We have studied quantized transport in HgTe wells with inverted band structure corresponding to the two-dimensional topological insulator phase (2D TI) with locally-controlled density allowing n-p-n and n-2D TI-n junctions. The resistance reveals the fractional plateau $2h/e^{2}$ in n-p-n regime in the presence of the strong perpendicular magnetic field. We found that in n-2D TI-n regime the plateaux in resistance in not universal and results from the edge state equilibration at the interface between chiral and helical edge modes. We provided the simple model describing the resistance quantization in n-2D TI-n regime.