ShantanuT01/DACTYL-Pretraining huggingface dataset:
The discovery of accelerated expansion using supernova surveys has been one of the most surprising discoveries in cosmology in the past ten years. Present and future surveys, among which SNLS, JDEM or LSST, are based on samples of a few hundreds to a million supernovae. The measurement of their spectroscopic redshifts to investigate dark energy properties is already by far the limiting aspect of such surveys. In this paper, I will discuss and illustrate with SNLS data an approach based solely on photometry to both select supernova candidates and determine their redshift.
We present an analysis of the stellar kinematics of the Large Magellanic Cloud based on ~5900 new and existing velocities of massive red supergiants, oxygen-rich and carbon-rich AGB stars, and other giants. After correcting the line-of-sight velocities for the LMC's space motion and accounting for asymmetric drift in the AGB population, we derive a rotation curve that is consistent with all of the tracers used, as well as that of published HI data. The amplitude of the rotation curve is v_0=87+/-5 km s^-1 beyond a radius R_0=2.4+/-0.1 kpc, and has a position angle of the kinematic line of nodes of theta=142 degrees +/-5 degrees. By examining the outliers from our fits, we identify a population of 376 stars, or >~5% of our sample, that have line-of-sight velocities that apparently oppose the sense of rotation of the LMC disk. We find that these kinematically distinct stars are either counter-rotating in a plane closely aligned with the LMC disk, or rotating in the same sense as the LMC disk, but in a plane that is inclined by 54 degrees +/- 2 degrees to the LMC. Their kinematics clearly link them to two known HI arms, which have previously been interpreted as being pulled out from the LMC. We measure metallicities from the Ca triplet lines of ~1000 LMC field stars and 30 stars in the kinematically distinct population. For the LMC field, we find a median [Fe/H]=-0.56 +/- 0.02 with dispersion of 0.5 dex, while for the kinematically distinct stars the median [Fe/H] is -1.25 +/- 0.13 with a dispersion of 0.7 dex. The metallicity differences provide strong evidence that the kinematically distinct population originated in the SMC. This interpretation has the consequence that the HI arms kinematically associated with the stars are likely falling into the LMC, instead of being pulled out.
Accelerated molecular dynamics (MD) simulations are implemented to model the sliding process of AFM experiments at speeds close to those found in experiment. In this study the hyperdynamics method, originally devised to extend MD time scales for non-driven systems, is applied to the frictional sliding system. This technique is combined with a parallel algorithm that simultaneously simulates the system over a range of slider positions. The new methodologies are tested using 2-dimensional and 3-dimensional Lennard-Jones AFM models. Direct comparison with the results from conventional MD shows close agreement validating the methods.
We have analyzed the kinematics of OB2 stars with proper motions and parallaxes selected by Xu et al. from the Gaia EDR3 catalog. The relative parallax errors for all the stars in this sample do not exceed 10\%. Based on a sample of 9750 stars, the group velocity components $(U,V,W)_\odot=(7.21,7.46,8.52)\pm(0.13,0.20,0.10)$~km/s were obtained and the parameters of the angular velocity of rotation of the Galaxy:   $\Omega_0 =29.712\pm0.062$~km/s/kpc, $\Omega^{'}_0=-4.014\pm0.018$~km/s/kpc$^{2}$ and   $\Omega^{''}_0=0.674\pm0.009$~km/s/kpc$^{3}$. The circular velocity of rotation of the solar neighborhood around the center of the Galaxy is $V_0=240.7\pm3.0$~km/s for the assumed distance of the Sun to the galactic center $R_0=8.1\pm0.1$~kpc. It is shown that the influence of the systematic correction to the trigonometric parallaxes of the Gaia EDR3 catalog with the value $\Delta\pi=-0.040$~mas does not exceed the $\sim1\sigma$ level of the errors of the sought-for kinematic parameters of the model. Based on the proper motions of OB stars, the following variances of the residual velocities were found: $(\sigma_1,\sigma_2,\sigma_3)=(11.79,9.66,7.21)\pm(0.06,0.05,0.04)$~km/s. It is shown that the first axis of this ellipsoid slightly deviates from the direction to the center of the Galaxy $L_1=12.4\pm0.1^\circ$, and the third axis is oriented almost exactly to the north pole of the Galaxy, $B_3=87.7\pm0.1^\circ.$
We prove that a smooth, subcanonical surface of P^4 (projective space over an algebraically closed field of characteristic zero) is complete intersection if it is contained in a quartic hypersurface.
Coalescing binary black holes experience a ``kick'' due to anisotropic emission of gravitational waves with an amplitude as great as 200$ km/s. We examine the orbital evolution of black holes that have been kicked from the centers of triaxial galaxies. Time scales for orbital decay are generally longer in triaxial galaxies than in equivalent spherical galaxies, since a kicked black hole does not return directly through the dense center where the dynamical friction force is highest. We evaluate this effect by constructing self-consistent triaxial models and integrating the trajectories of massive particles after they are ejected from the center; the dynamical friction force is computed directly from the velocity dispersion tensor of the self-consistent model. We find return times that are several times longer than in a spherical galaxy with the same radial density profile, particularly in galaxy models with dense centers, implying a substantially grea
We study the growth of the Tate-Shafarevich and p-infinity Selmer groups for isogenous abelian varieties in towers of number fields, with an emphasis on elliptic curves. The growth types are usually exponential, as in the setting of `positive mu-invariant' in Iwasawa theory of elliptic curves. The towers we consider are p-adic and l-adic Lie extensions for l<>p, in particular cyclotomic and other Z_l-extensions.
Ozawa et. al [1] presented numerical results for the configurational entropy density, $s_c$, of a model glass-forming liquid in the presence of random pinning. The location of a "phase boundary" in the pin density ($c$) - temperature ($T$) plane, that separates an "ideal glass" phase from the supercooled liquid phase, is obtained by finding the points at which $s_c(T,c) \to 0$. According to the theoretical arguments by Cammarota et. al. [2], an ideal glass transition at which the $\alpha$-relaxation time $\tau_\alpha$ diverges takes place when $s_c$ goes to zero. We have studied the dynamics of the same system using molecular dynamics simulations. We have calculated the time-dependence of the self intermediate scattering function, $F_s(k,t)$ at three state points in the $(c-T)$ plane where $s_c(T,c) \simeq 0$ according to Ref. [1]. It is clear from the plots that the relaxation time is finite [$\tau_\alpha \sim \mathcal{O}(10^6)]$ at these state points. Similar conclusions have been obtained in Ref.[3] where an overlap function was used to calculate $\tau_\alpha$ at these state points.
In multi-person 2D pose estimation, the bottom-up methods simultaneously predict poses for all persons, and unlike the top-down methods, do not rely on human detection. However, the SOTA bottom-up methods' accuracy is still inferior compared to the existing top-down methods. This is due to the predicted human poses being regressed based on the inconsistent human bounding box center and the lack of human-scale normalization, leading to the predicted human poses being inaccurate and small-scale persons being missed. To push the envelope of the bottom-up pose estimation, we firstly propose multi-scale training to enhance the network to handle scale variation with single-scale testing, particularly for small-scale persons. Secondly, we introduce dual anatomical centers (i.e., head and body), where we can predict the human poses more accurately and reliably, especially for small-scale persons. Moreover, existing bottom-up methods use multi-scale testing to boost the accuracy of pose estimation at the price of multiple additional forward passes, which weakens the efficiency of bottom-up methods, the core strength compared to top-down methods. By contrast, our multi-scale training enables the model to predict high-quality poses in a single forward pass (i.e., single-scale testing). Our method achieves 38.4\% improvement on bounding box precision and 39.1\% improvement on bounding box recall over the state of the art (SOTA) on the challenging small-scale persons subset of COCO. For the human pose AP evaluation, we achieve a new SOTA (71.0 AP) on the COCO test-dev set with the single-scale testing. We also achieve the top performance (40.3 AP) on OCHuman dataset in cross-dataset evaluation.
Universal behavior is a typical emergent feature of critical systems. A paramount model of the non-equilibrium critical behavior is the directed bond percolation process that exhibits an active- to-absorbing state phase transition in the vicinity of a percolation threshold. Fluctuations of the ambient environment might affect or destroy the universality properties completely. In this work we assume that the random environment can be described by means of compressible velocity fluctu- ations. Using field-theoretic models and renormalization group methods we investigate large-scale and long-time behavior. Altogether eleven universality classes are found, out of which four are stable in the infrared limit and thus macroscopically accessible. In contrast to the model without veloc- ity fluctuations a possible candidate for a realistic three-dimensional case, a regime with relevant short-range noise, is identified. Depending on the dimensionality of space and the structure of the turbulent flow we calculate critical exponents of the directed percolation process. In the limit of the purely transversal velocity field random force critical exponents comply with the incompressible results obtained by previous authors. We have found intriguing non-universal behavior related to the mutual effect of compressibility and advection.
In this paper we consider the problem of calculating the higher-order Weierstrass weight of the branch points of a superelliptic curve $C$. For any $q>1$, we give an exact formula for the $q$-weight of an affine branch point. We also find a formula for the $q$-weight of a point at infinity in the case where $n$ and $d$ are relatively prime. With these formulas, for any fixed $n$, we obtain an asymptotic formula for the ratio of the $q$-weight of the branch points, denoted $BW_q$, to the total $q$-weight of points on the curve: \[ \liminf_{d\to\infty}\frac{BW_q}{g(g-1)^2(2q-1)^2}\geq \frac{n+1}{3(n-1)^2(2q-1)^2},\] with equality when the limit is taken such that $\gcd(n,d)=1$.
Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.   In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy.
Automatic affect recognition has applications in many areas such as education, gaming, software development, automotives, medical care, etc. but it is non trivial task to achieve appreciable performance on in-the-wild data sets. In-the-wild data sets though represent real-world scenarios better than synthetic data sets, the former ones suffer from the problem of incomplete labels. Inspired by semi-supervised learning, in this paper, we introduce our submission to the Multi-Task-Learning Challenge at the 4th Affective Behavior Analysis in-the-wild (ABAW) 2022 Competition. The three tasks that are considered in this challenge are valence-arousal(VA) estimation, classification of expressions into 6 basic (anger, disgust, fear, happiness, sadness, surprise), neutral, and the 'other' category and 12 action units(AU) numbered AU-{1,2,4,6,7,10,12,15,23,24,25,26}. Our method Semi-supervised Multi-task Facial Affect Recognition titled SS-MFAR uses a deep residual network with task specific classifiers for each of the tasks along with adaptive thresholds for each expression class and semi-supervised learning for the incomplete labels. Source code is available at https://github.com/1980x/ABAW2022DMACS.
Advances in face rotation, along with other face-based generative tasks, are more frequent as we advance further in topics of deep learning. Even as impressive milestones are achieved in synthesizing faces, the importance of preserving identity is needed in practice and should not be overlooked. Also, the difficulty should not be more for data with obscured faces, heavier poses, and lower quality. Existing methods tend to focus on samples with variation in pose, but with the assumption data is high in quality. We propose a generative adversarial network (GAN) -based model to generate high-quality, identity preserving frontal faces from one or multiple low-resolution (LR) faces with extreme poses. Specifically, we propose SuperFront-GAN (SF-GAN) to synthesize a high-resolution (HR), frontal face from one-to-many LR faces with various poses and with the identity-preserved. We integrate a super-resolution (SR) side-view module into SF-GAN to preserve identity information and fine details of the side-views in HR space, which helps model reconstruct high-frequency information of faces (i.e., periocular, nose, and mouth regions). Moreover, SF-GAN accepts multiple LR faces as input, and improves each added sample. We squeeze additional gain in performance with an orthogonal constraint in the generator to penalize redundant latent representations and, hence, diversify the learned features space. Quantitative and qualitative results demonstrate the superiority of SF-GAN over others.
Structural pattern recognition describes and classifies data based on the relationships of features and parts. Topological invariants, like the Euler number, characterize the structure of objects of any dimension. Cohomology can provide more refined algebraic invariants to a topological space than does homology. It assigns `quantities' to the chains used in homology to characterize holes of any dimension. Graph pyramids can be used to describe subdivisions of the same object at multiple levels of detail. This paper presents cohomology in the context of structural pattern recognition and introduces an algorithm to efficiently compute representative cocycles (the basic elements of cohomology) in 2D using a graph pyramid. An extension to obtain scanning and rotation invariant cocycles is given.
Cellular automata have turned out to be important tools for the simulation of traffic flow. They are designed for an efficient impletmentation on the computer, but hard to treat analytically. Here we discuss several approaches for an analytical description of the Nagel-Schreckenberg (NaSch) model and its variants. These methods yield the exact solution for the special case $\vm=1$ of the NaSch model and are good approximations for higher values of the velocity ($\vm > 1$). We discuss the validity of these approximations and the conclusions for the underlying physics that can be drawn from the success or failure of the approximation.
The lowest excitation energies of the given multipole J^pi state (the J^pi yrast energies) are given for even-even nuclei throughout the entire periodic table. The yrast energies were calculated using the recently proposed empirical formula that depends only on the mass number A, and the valence nucleon numbers Np and Nn. We provide a complete tabulation and plots of the yrast energies calculated using the empirical formula together with the ones measured for the natural parity states up to 10+ and for the unnatural parity states up to 10^+ with the hope of encouraging active study on the possible origin of the relationship between the yrast energies, as revealed by the empirical formula.
A new multichannel spectrometer, Phoenix-3, is in operation having capabilities to observe solar flare radio emissions in the 0.1 - 5 GHz range at an unprecedented spectral resolution of 61.0 kHz with high sensitivity. The present setup for routine observations allows measuring circular polarization, but requires a data compression to 4096 frequency channels in the 1 - 5 GHz range and to a temporal resolution of 200 ms. First results are presented by means of a well observed event that included narrowband spikes at 350 - 850 MHz. Spike bandwidths are found to have a power-law distribution, dropping off below a value of 2 MHz for full width at half maximum (FWHM). The narrowest spikes have a FWHM bandwidth less than 0.3 MHz or 0.04% of the central frequency. The smallest half-power increase occurs within 0.104 MHz at 443.5 MHz, which is close to the predicted natural width of maser emission. The spectrum of spikes is found to be asymmetric, having an enhanced low-frequency tail. The distribution of the total spike flux is approximately an exponential.
Broad-lined type Ic supernovae (SNe Ic-BL) are peculiar stellar explosions that distinguish themselves from ordinary SNe. Some SNe Ic-BL are associated with long-duration (\gtrsim 2 s) gamma-ray bursts (GRBs). Black holes and magnetars are two types of compact objects that are hypothesized to be central engines of GRBs. In spite of decades of investigations, no direct evidence for the formation of black holes or magnetars has been found for GRBs so far. Here we report the finding that the early peak (t \lesssim 50 days) and late-time (t \gtrsim 300 days) slow decay displayed in the light curves of both SNe 1998bw (associated with GRB 980425) and 2002ap (not GRB-associated) can be attributed to magnetar spin-down with initial rotation period P0 \sim 20 ms, while the intermediate-time (50 \lesssim t \lesssim 300 days) linear decline is caused by radioactive decay of 56Ni. The connection between the early peak and late-time slow decline in the light curves is unexpected in alternative models. We thus suggest that GRB 980425 and SN 2002ap were powered by magnetars.
We consider the following generalization of the seminal Erd\H{o}s-Ko-Rado theorem, due to Frankl. For k>= 2, let F be a k-wise intersecting family of r-subsets of an n element set X, i.e. any k sets in F have a nonempty intersection. If r<= (k-1/k)n, then |F|<={n-1 \choose r-1}. We extend Frankl's theorem in a graph-theoretic direction. For a graph G, and r>=1, let P^r(G) be the family of all r-subsets of the vertex set of G such that every r-subset is either an independent set or contains a maximum independent set. We will consider k-wise intersecting subfamilies of this family for the graph M_n, where M_n is the perfect matching on 2n vertices, and prove an analog of Frankl's theorem. This result can also be considered as an extension of a theorem of Bollob\'as and Leader for intersecting families of independent vertex sets in M_n.
We argue that global F-theory compactifications to four dimensions generally exhibit higher rank Yukawa matrices from multiple geometric contributions known as Yukawa points. The holomorphic couplings furthermore have large hierarchies for generic complex structure moduli. Unlike local considerations, the compact setup realizes these features all through geometry, and requires no instanton corrections. As an example, we consider a concrete toy model with $SU(5) \times U(1)$ gauge symmetry. From the geometry, we find two Yukawa points for the ${\bf 10}_{-2} \, \bar{\bf 5}_6 \, \bar{\bf 5}_{-4}$ coupling, producing a rank two Yukawa matrix. Our methods allow us to track all complex structure dependencies of the holomorphic couplings and study the ratio numerically. This reveals hierarchies of ${\cal O}(10^5)$ and larger on a full-dimensional subspace of the moduli space.
We study the temperature-magnetic field T-B phase diagrams of heavy fermion (HF) metals, and show that at sufficiently high temperatures outside the ordered phase the crossover temperature T*(B), regarded as the energy scale, follows a linear B-dependence, crossing the origin of the T-B phase diagram. This behavior of T*(B) constitutes the general property, and is formed by the presence of fermion condensation quantum phase transition hidden within the ordered phase. Our result is in good agreement with the experimental T-B phase diagram of the HF metals YbRh2Si2, Yb(Rh{0.93}Co{0.07})2Si2, and Yb(Rh{0.94}Ir{0.06})2Si2. To support our observations, we analyze the isothermal magnetization M, and demonstrate that dM/dT exhibits a universal temperature behavior over magnetic field scaling. The obtained results are in good agreement with the corresponding data collected on YbRh2Si2 as a function of magnetic field at different temperatures under hydrostatic pressure.
We report quantitative experimental measurements of the nonlinear response of a radiofrequency mechanical resonator, with very high quality factor, driven by a large swept-frequency force. We directly measure the noise-free transition dynamics between the two basins of attraction that appear in the nonlinear regime, and find good agreement with those predicted by the one-dimensional Duffing equation of motion. We then measure the response of the transition rates to controlled levels of white noise, and extract the activation energy from each basin. The measurements of the noise-induced transitions allow us to obtain precise values for the critical frequencies, the natural resonance frequency, and the cubic nonlinear parameter in the Duffing oscillator, with direct applications to high sensitivity parametric sensors based on these resonators.
In this note we extend some of the results of a previous paper \url{arXiv:math/0511593} to algebraically closed fields of finite characteristic. In particular, we show that there is an explicit expression in $n$ and $d$ which is divisible by the prime to $p$ part of the order of the the automorphism group of a smooth degree $d$ hypersurface $\subset \mathbb{P}^n_k$ for $k$ an algebraically closed field of characteristic $p$.
In a recent article a breakthrough was made in quantum computer science which established the existence of a phenomenon commonly known as $\mathsf{MIP}^\ast = \mathsf{RE}$. We show that the existence of this phenomenon implies that the supremum of the real parts of the zeroes of the Riemann zeta function is less than one. Our main tool is an assertion about the representation theory of the rank two free group that we refer to as the charged mean ergodic theorem. Our method also involves the construction of novel modular functions we refer to as complete electromagnetic functions.