ShantanuT01/DACTYL-Pretraining huggingface dataset:
For many machine learning algorithms such as $k$-Nearest Neighbor ($k$-NN) classifiers and $ k $-means clustering, often their success heavily depends on the metric used to calculate distances between different data points.   An effective solution for defining such a metric is to learn it from a set of labeled training samples. In this work, we propose a fast and scalable algorithm to learn a Mahalanobis distance metric. By employing the principle of margin maximization to achieve better generalization performances, this algorithm formulates the metric learning as a convex optimization problem and a positive semidefinite (psd) matrix is the unknown variable. a specialized gradient descent method is proposed. our algorithm is much more efficient and has a better performance in scalability compared with existing methods. Experiments on benchmark data sets suggest that, compared with state-of-the-art metric learning algorithms, our algorithm can achieve a comparable classification accuracy with reduced computational complexity.
In this paper a viewpoint that time is an informational and thermal entity is shown. We consider a model for a simple relaxation process for which a relationship among event, time and temperature is mathematically formulated. It is then explicitly illustrated that temperature and time are statistically inferred through measurement of events. The probability distribution of the events thus provides a mutual regulation between temperature and time, which can relevantly be expressed in terms of the Fisher information metric. The two-dimensional differential geometry of temperature and time then leads us to a finding of a simple equation for the scalar curvature, R = -1, in this case of relaxation process. This basic equation, in turn, may be regarded as characterizing the nonequilibrium dynamical process and having a solution given by the Fisher information metric. The time can then be interpreted so as to appear in a thermal way.
Topological error-correcting codes, such as surface codes and color codes, are promising because quantum operations are realized by two-dimensionally (2D) arrayed quantum bits (qubits). However, physical wiring of electrodes to qubits is complicated, and 3D integration for the wiring requires further development of fabrication technologies. Here, we propose a method to reduce the congestion of wiring to qubits by just adding a SWAP gate after each controlled-NOT (CNOT) gate. SWAP gates exchange roles of qubits. Then, the roles of qubits are shared between different qubits. We found that our method transforms the qubit layout and reduces the number of qubits that cannot be accessed two-dimensionally. We show that fully 2D layouts including both qubits and control electrodes can be achieved for surface and color codes of minimum sizes. This method will be beneficial to simplifications of fabrication process of quantum circuits in addition to improvements of reliability of qubit system.
An example is given of a qubit quantum channel which requires four inputs to maximize the Holevo capacity. The example is one of a family of channels which are related to 3-state channels. The capacity of the product channel is studied and numerical evidence presented which strongly suggests additivity. The numerical evidence also supports a conjecture about the concavity of output entropy as a function of entanglement parameters. However, an example is presented which shows that for some channels this conjecture does not hold for all input states. A numerical algorithm for finding the capacity and optimal inputs is presented and its relation to a relative entropy optimization discussed.
We study the algebraic properties of Generalized Laguerre Polynomials for negative integral values of the parameter. For integers $r,n\geq 0$, we conjecture that $L_n^{(-1-n-r)}(x) = \sum_{j=0}^n \binom{n-j+r}{n-j}x^j/j!$ is a $\Q$-irreducible polynomial whose Galois group contains the alternating group on $n$ letters. That this is so for $r=n$ was conjectured in the 50's by Grosswald and proven recently by Filaseta and Trifonov. It follows from recent work of Hajir and Wong that the conjecture is true when $r$ is large with respect to $n\geq 5$. Here we verify it in three situations: i) when $n$ is large with respect to $r$, ii) when $r \leq 8$, and iii) when $n\leq 4$. The main tool is the theory of $p$-adic Newton Polygons.
Camera pose tracking attracts much interest both from academic and industrial communities, of which the methods based on planar markers are easy to be implemented. However, most of the existing methods need to identify multiple points in the marker images for matching to space points. Then, PnP and RANSAC are used to compute the camera pose. If cameras move fast or are far away from markers, matching is easy to generate errors and even RANSAC cannot remove incorrect matching. Then, the result by PnP cannot have good performance. To solve this problem, we design circular markers and represent 6D camera pose analytically and unifiedly as very concise forms from each of the marker by projective invariance. Afterwards, the pose is further optimized by a proposed nonlinear cost function based on a polar-n-direction geometric distance. The method is from imaged circle edges and without PnP/RANSAC, making pose tracking robust and accurate. Experimental results show that the proposed method outperforms the state of the arts in terms of noise, blur, and distance from camera to marker. Simultaneously, it can still run at about 100 FPS on a consumer computer with only CPU.
Context. he study of prestellar cores is essential to understanding the initial stages of star formation. With $Herschel$ more cold clumps have been detected than ever before. For this study we have selected 21 cold clumps from 20 $Herschel$ fields observed as a follow-up on original $Planck$ detections. We have observed these clumps in $^{13}$CO (1-0), C$^{18}$O (1-0), and N$_2$H$^+$ (1-0) lines. Aims. Our aim is to find out if these cold clumps are prestellar. We have examined to what extent independent analysis of the dust and the molecular lines lead to similar conclusions about the masses of these objects. Methods. We calculate the clump masses and densities from the dust continuum and molecular line observations and compare these to each other and to the virial and Bonnor-Ebert masses calculated for each clump. Finally we examine two of the fields with radiative transfer models to estimate CO abundances. Results. When excitation temperatures could be estimated, the column densities derived from molecular line observations were comparable to those from dust continuum data. The median column density estimates are 4.2$\times 10^{21}$cm$^{-2}$ and 5.5$\times 10^{21}$cm$^{-2}$ for the line and dust emission data, respectively. The calculated abundances, column densities, volume densities, and masses all have large uncertainties and one must be careful when drawing conclusions. Abundance of $^{13}$CO was found in modeling the two clumps in the field G131.65$+$9.75 to be close to the usual value of 10$^{-6}$. The abundance ratio of $^{13}$CO and C$^{18}$O was $\sim$10. Molecular abundances could only be estimated with modeling, relying on dust column density data. Conclusions. The results indicate that most cold clumps, even those with dust color temperatures close to 11 K, are not necessarily prestellar.
Convolutional neural networks (CNNs) are extensively beneficial for medical image processing. Medical images are plentiful, but there is a lack of annotated data. Transfer learning is used to solve the problem of lack of labeled data and grants CNNs better training capability. Transfer learning can be used in many different medical applications; however, the model under transfer should have the same size as the original network. Knowledge distillation is recently proposed to transfer the knowledge of a model to another one and can be useful to cover the shortcomings of transfer learning. But some parts of the knowledge may not be distilled by knowledge distillation. In this paper, a novel knowledge distillation using transfer learning is proposed to transfer the whole knowledge of a model to another one. The proposed method can be beneficial and practical for medical image analysis in which a small number of labeled data are available. The proposed process is tested for diabetic retinopathy classification. Simulation results demonstrate that using the proposed method, knowledge of an extensive network can be transferred to a smaller model.
We report on three numerical experiments on the implementation of Time-Delay Interferometry (TDI) for LISA, performed with Synthetic LISA, a C++/Python package that we developed to simulate the LISA science process at the level of scientific and technical requirements. Specifically, we study the laser-noise residuals left by first-generation TDI when the LISA armlengths have a realistic time dependence; we characterize the armlength-measurements accuracies that are needed to have effective laser-noise cancellation in both first- and second-generation TDI; and we estimate the quantization and telemetry bitdepth needed for the phase measurements. Synthetic LISA generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables; it also provides a streamlined module to compute the TDI responses to gravitational waves according to a full model of TDI, including the motion of the LISA array and the temporal and directional dependence of the armlengths. We discuss the theoretical model that underlies the simulation, its implementation, and its use in future investigations on system characterization and data-analysis prototyping for LISA.
We analyze the $X(3872)$ production in the processes $ \bar{D} D \rightarrow \pi X $, $\bar{D}^* D \rightarrow \pi X $ and $\bar{D}^* D^* \rightarrow \pi X $, making use of the Heavy-Meson Effective Theory, with an effective Lagrangian built based on chiral $SU(3)_{L} \times SU(3)_{R}$ and heavy quark symmetries. In this scenario, we consider $X$ as a bound state of $D^{*} \bar{D} + c.c.$, including neutral and charged components, and obtain the cross sections the mentioned reactions as function of collision energy.
We propose general topological order parameters for interacting insulators in terms of the Green's function at zero frequency. They provide an unified description of various interacting topological insulators including the quantum anomalous Hall insulators and the time reversal invariant insulators in four, three and two dimensions. Since only Green's function at zero frequency is used, these topological order parameters can be evaluated efficiently by most numerical and analytical algorithms for strongly interacting systems.
I summarize recent analytical and numerical studies of the common envelope (CE) process and suggest to replace the commonly used alpha-prescription for the CE ejection by a prescription based on final migration and jets launched by the companion or the core of the giant stellar primary. In the migration process the core-companion binary systems is surrounded by a highly oblate (flatten) envelope, a thick circumbinary disk, formed by the large angular momentum transferred from the core-companion system to the envelope. I then show that the energy that can be released by an accreting main sequence companion can surpass the mutual gravitational energy of the core and the companion. An efficient channel to leash the accretion energy to expel the CE is through jets operating via a feedback mechanism (JFM).
We theoretically consider g factor and spin lifetimes of holes in a longitudinal Ge/Si core/shell nanowire quantum dot that is exposed to external magnetic and electric fields. For the ground states, we find a large anisotropy of the g factor which is highly tunable by applying electric fields. This tunability depends strongly on the direction of the electric field with respect to the magnetic field. We calculate the single-phonon hole spin relaxation times T1 for zero and small electric fields and propose an optimal setup in which very large T1 of the order of tens of milliseconds can be reached. Increasing the relative shell thickness or the longitudinal confinement length further prolongs T1. In the absence of electric fields, the dephasing vanishes and the decoherence time T2 is determined by T2 = 2 T1.
Eigenenergies of a non-Hermitian system without parity-time symmetry are complex in general. Here, we show that the chiral boundary states of higher-dimensional (two-dimensional and three-dimensional) non-Hermitian topological insulators without parity-time symmetry can be Hermitian with real eigenenergies under certain conditions. Our approach allows one to construct Hermitian chiral edge and hinge states from non-Hermitian two-dimensional Chern insulators and three-dimensional second-order topological insulators, respectively. Such Hermitian chiral boundary channels have perfect transmission coefficients (quantized values) and are robust against disorders. Furthermore, a non-Hermitian topological insulator can undergo the topological Anderson insulator transition from a topological trivial non-Hermitian metal or insulator to a topological Anderson insulator with quantized transmission coefficients at finite disorders.
It is well known that the full compressible Navier-Stokes equations can be deduced via the Chapman-Enskog expansion from the Boltzmann equation as the first-order correction to the Euler equations with viscosity and heat-conductivity coefficients of order of the Knudsen number $\epsilon>0$. In the paper, we carry out the rigorous mathematical analysis of the compressible Navier-Stokes approximation for the Boltzmann equation regarding the initial-boundary value problems in general bounded domains. The main goal is to measure the uniform-in-time deviation of the Boltzmann solution with diffusive reflection boundary condition from a local Maxwellian with its fluid quantities given by the solutions to the corresponding compressible Navier-Stokes equations with consistent non-slip boundary conditions whenever $\epsilon>0$ is small enough. Specifically, it is shown that for well chosen initial data around constant equilibrium states, the deviation weighted by a velocity function is $O(\epsilon^{1/2})$ in $L^\infty_{x,v}$ and $O(\epsilon^{3/2})$ in $L^2_{x,v}$ globally in time. The proof is based on the uniform estimates for the remainder in different functional spaces without any spatial regularity. One key step is to obtain the global-in-time existence as well as uniform-in-$\epsilon$ estimates for regular solutions to the full compressible Navier-Stokes equations in bounded domains when the parameter $\epsilon>0$ is involved in the analysis.
The spectrum structure of the linearized relativistic Boltzmann equation around a global Maxwellian is studied in this paper. Based on the spectrum analysis, we establish the optimal time-convergence rates of the global solution to the Cauchy problem for the relativistic Boltzmann equation.
We study relations between bosonic quadrature squeezing and atomic spin squeezing, and find that the latter reduces to the former in the limit of a large number of atoms for even and odd states. We demonstrate this reduction by treating even and odd spin coherent states, for which analytical solutions are readily obtained, and prove that even spin coherent states always exhibit spin squeezing, whereas odd spin coherent states do not, analogous to the squeezing characteristic of even and odd bosonic coherent states. Finally, we examine the squeezing transfer between photons and atoms via the Dicke Hamiltonian, where a perfect transfer of squeezing is demonstrated in the limit of a large number of atoms.
In this article we give a method to construct preimages for the Shimura correspondence on Hilbert modular forms of odd and square-free level. The method relies in the ideas presented for the rational case by Pacetti and Tornar\'ia, and is such that the Fourier coefficients of the preimages constructed can be computed explicitly.
We present a survey of how the spectral features of black hole X-ray binary systems depend on spin, accretion rate, viewing angle, and Fe abundance when predicted on the basis of first principles physical calculations. The power law component hardens with increasing spin. The thermal component strengthens with increasing accretion rate. The Compton bump is enhanced by higher accretion rate and lower spin. The Fe K$\alpha$ equivalent width grows sub-linearly with Fe abundance. Strikingly, the K$\alpha$ profile is more sensitive to accretion rate than to spin because its radial surface brightness profile is relatively flat, and higher accretion rate extends the production region to smaller radii. The overall radiative efficiency is at least 30--100% greater than as predicted by the Novikov-Thorne model.
We develop a martingale approximation approach to studying the limiting behavior of quadratic forms of Markov chains. We use the technique to examine the asymptotic behavior of lag-window estimators in time series and we apply the results to Markov Chain Monte Carlo simulation. As another illustration, we use the method to derive a central limit theorem for U-statistics with varying kernels.
We propose a cluster simulation algorithm for statistical ensembles with fixed order parameter. We use the tethered ensemble, which features Helmholtz's effective potential rather than Gibbs's free energy, and in which canonical averages are recovered with arbitrary accuracy. For the D = 2,3 Ising model our method's critical slowing down is comparable to that of canonical cluster algorithms. Yet, we can do more than merely reproduce canonical values. As an example, we obtain a competitive value for the 3D Ising anomalous dimension from the maxima of the effective potential.
We demonstrate how sophisticated graph properties, such as small distances and scale-free degree distributions, arise naturally from a reinforcement mechanism on layered graphs. Every node is assigned an a-priori i.i.d. fitness with max-stable distribution. The fitness determines the node attractiveness w.r.t. incoming edges as well as the spatial range for outgoing edges. For max-stable fitness distributions, we thus obtain complex spatial network, which we coin extremal linkage network.
We analyze various supersymmetry multiplets containing the supercurrent and the energy-momentum tensor. The most widely known such multiplet, the Ferrara-Zumino (FZ) multiplet, is not always well-defined. This can happen once Fayet-Iliopoulos (FI) terms are present or when the Kahler form of the target space is not exact. We present a new multiplet S which always exists. This understanding of the supersymmetry current allows us to obtain new results about the possible IR behavior of supersymmetric theories. Next, we discuss the coupling of rigid supersymmetric theories to supergravity. When the theory has an FZ-multiplet or it has a global R-symmetry the standard formalism can be used. But when this is not the case such simple gauging is impossible. Then, we must gauge the current S. The resulting theory has, in addition to the graviton and the gravitino, another massless chiral superfield Phi which is essential for the consistency of the theory. Some of the moduli of various string models play the role of Phi. Our general considerations, which are based on the consistency of supergravity, show that such moduli cannot be easily lifted thus leading to constraints on gravity/string models.
Anomalies in several short-baseline neutrino oscillation experiments suggest the possible existence of sterile neutrinos at about eV scale having appreciable mixing with the already known three neutrinos. We find that if such a light sterile neutrino exists, through a combined study of the leptonic decays of $\mu^-$, $\tau^-$, $\pi^-$ and $K^-$, some semi-leptonic decays of $\tau^-$ and the invisible decay width of the $Z$ boson, it is possible to constrain the relevant mixing matrix elements. Furthermore, we compare the constraints, derived by using the method presented here, with the experimental results obtained from short-baseline neutrino oscillation experiments. We find that a single light sterile neutrino cannot satisfy the existing short-baseline neutrino oscillation constraints and explain the anomalies mentioned above. Along the way we provide a number of experimentally clean observables which can be used to directly study the light sterile neutrino independently of the neutrino oscillation experiments.
In this paper, an automatic method is proposed to perform image registration in visible and infrared pair of video sequences for multiple targets. In multimodal image analysis like image fusion systems, color and IR sensors are placed close to each other and capture a same scene simultaneously, but the videos are not properly aligned by default because of different fields of view, image capturing information, working principle and other camera specifications. Because the scenes are usually not planar, alignment needs to be performed continuously by extracting relevant common information. In this paper, we approximate the shape of the targets by polygons and use affine transformation for aligning the two video sequences. After background subtraction, keypoints on the contour of the foreground blobs are detected using DCE (Discrete Curve Evolution)technique. These keypoints are then described by the local shape at each point of the obtained polygon. The keypoints are matched based on the convexity of polygon's vertices and Euclidean distance between them. Only good matches for each local shape polygon in a frame, are kept. To achieve a global affine transformation that maximises the overlapping of infrared and visible foreground pixels, the matched keypoints of each local shape polygon are stored temporally in a buffer for a few number of frames. The matrix is evaluated at each frame using the temporal buffer and the best matrix is selected, based on an overlapping ratio criterion. Our experimental results demonstrate that this method can provide highly accurate registered images and that we outperform a previous related method.
We prove the first robust dimension free isoperimetric result for the standard Gaussian measure $\gamma_n$ and the corresponding boundary measure $\gamma_n^+$ in $\mathbb {R}^n$. The main result in the theory of Gaussian isoperimetry (proven in the 1970s by Sudakov and Tsirelson, and independently by Borell) states that if $\gamma_n(A)=1/2$ then the surface area of $A$ is bounded by the surface area of a half-space with the same measure, $\gamma_n^+(A)\leq(2\pi)^{-1/2}$. Our results imply in particular that if $A\subset \mathbb {R}^n$ satisfies $\gamma_n(A)=1/2$ and $\gamma_n^+(A)\leq(2\pi)^{-1/2}+\delta$ then there exists a half-space $B\subset \mathbb {R}^n$ such that $\gamma_n(A\Delta B)\leq C\smash{\log^{-1/2}}(1/\delta)$ for an absolute constant $C$. Since the Gaussian isoperimetric result was established, only recently a robust version of the Gaussian isoperimetric result was obtained by Cianchi et al., who showed that $\gamma_n(A\Delta B)\le C(n)\sqrt{\delta}$ for some function $C(n)$ with no effective bounds. Compared to the results of Cianchi et al., our results have optimal (i.e., no) dependence on the dimension, but worse dependence on $ \delta$.