ShantanuT01/DACTYL-Pretraining huggingface dataset:
Weighted Updating generalizes Bayesian updating, allowing for biased beliefs by weighting the likelihood function and prior distribution with positive real exponents. I provide a rigorous foundation for the model by showing that transforming a distribution by exponential weighting (and normalizing) systematically affects the information entropy of the resulting distribution. For weights greater than one the resulting distribution has less information entropy than the original distribution, and vice versa. The entropy of a distribution measures how informative a decision maker is treating the underlying observation(s), so this result suggests a useful interpretation of the weights. For example, a weight greater than one on a likelihood function models an individual who is treating the associated observation(s) as being more informative than a perfect Bayesian would.
GRB 170817A/GW 170817 is the first GRB clearly viewed far from the GRB jet's symmetry axis. Its afterglow was densely monitored over a wide range of frequencies and times. It has been modeled extensively, primarily numerically, and although this endeavour was very fruitful, many of the underlying model parameters remain undetermined. We provide analytic modelling of GRB afterglows observed off-axis, considering jets with a narrow core (of half-opening angle $\theta_{\rm c}$) and power-law wings in energy per unit solid angle ($\epsilon=\epsilon_c\Theta^{-a}$ where $\Theta=[1+(\theta/\theta_{\rm c})^2]^{1/2}$) and initial specific kinetic energy ($\Gamma_0-1=[\Gamma_{\rm c,0}-1]\Theta^{-b}$), as well as briefly discuss Gaussian jets. Our study reveals qualitatively different types of lightcurves that can be viewed in future off-axis GRBs, with either single or double peaks, depending on the jet structure and the viewing angle. Considering the lightcurve shape rather than the absolute normalizations of times and / or fluxes, removes the dependence of the lightcurve on many of the highly degenerate burst parameters. This study can be easily used to determine the underlying jet structure, significantly reduce the effective parameter space for numerical fitting attempts and provide physical insights. As an illustration, we show that for GRB 170817A, there is a strong correlation between the allowed values of $\Gamma_{\rm c,0}$ and $b$, leading to a narrow strip of allowed solutions in the $\Gamma_{\rm c,0}$-$b$ plane above some minimal values $\Gamma_{\rm c,0}\gtrsim 40, b\gtrsim1.2$. Furthermore, the Lorentz factor of the material dominating the early lightcurve can be constrained by three independent techniques to be $\Gamma_{0}(\theta_{\rm min,0})\approx5-7$.
Quantization effects due to topological invariants such as Chern numbers have become very relevant in many systems, yet key quantities such as the quantum geometric tensor providing local information about quantum states remain experimentally difficult to access. Recently, it has been shown that multiterminal Josephson junctions constitute an ideal platform to synthesize topological systems in a controlled manner. We theoretically study properties of Andreev states in topological Josephson matter and demonstrate that the quantum geometric tensor of Andreev states can be extracted by synthetically polarized microwaves. The oscillator strength of the absorption rates provides direct evidence of topological quantum properties of the Andreev states.
Context: In the seminal works of Zeldovich et al. (1968) and Peebles (1968), a procedure was outlined to obtain the equation of evolution of the hydrogen fraction without an explicit use of the radiative transfer equation. This procedure is based, explicitly or implicitly, on the concept of escape probability and, using the Sobolev approximation for this problem Sobolev (1960), has extensively been used since then in developing refined approximations.   Aims: To derive in a simple, rigorous and general manner the above mentioned procedure and to obtain exact analytical expressions for the spectral density of radiation generated at one photon and two photon recombination transitions. These expressions are used to estimate the implications of several interesting effects.   Methods: Some slight re-elaborations of basic principles of transport theory.   Results: We have obtained the expressions searched for and used them in several explicit computations. We have found that the relative change in the electronic fraction due to the absorption by the two photon line, 1s->2s, of photons that have escaped from the line 2p-> 1s is 0.67%, that is a result 12% higher than the previous ones obtained using some approximations (Kholupenko & Ivanchik 2006; Hirata 2008). The photons generated by the transition 2s->1s and later absorbed by the same transition (in combination with a photon more energetic than its original partner) imply a 0.05% maximum variation of the electronic fraction. This problem has not been treated previously analytically, although a numerical estimate have been recently carried out in Chluba & Thomas 2011.
We utilize machine learning methods to distinguish BL Lacertae objects (BL Lac) from Flat Spectrum Radio Quasars (FSRQ) within a sample of likely X-ray blazar counterparts to Fermi 3FGL unassociated gamma-ray sources. From our previous work, we have extracted 84 sources that were classified as $\geq$ 99% likley to be blazars. We then utilize Swift$-$XRT, Fermi, and WISE (The Wide-field Infrared Survey Explorer) data together to distinguish the specific type of blazar, FSRQs or BL Lacs. Various X-ray and Gamma-ray parameters can be used to differentiate between these subclasses. These are also known to occupy different parameter space on the WISE color-color diagram. Using all these data together would provide more robust results for the classified sources. We utilized a Random Forest Classifier to calculate the probability for each blazar to be associated with a BL Lac or an FSRQ. Based on P$_{bll}$, which is the probability for each source to be a BL Lac, we placed our sources into five different categories based on this value as follows; P$_{bll}$ $\geq$ 99%: highly likely BL Lac, P$_{bll}$ $\geq$ 90%: likely BL Lac, P$_{bll}$ $\leq$ 1%: highly likely FSRQ, P$_{bll}$ $\leq$ 10%: likely FSRQ, and 90% $<$ P$_{bll}$ $<$ 10%: ambiguous. Our results categorize the 84 blazar candidates as 50 likely BL Lacs and the rest 34 being ambiguous. A small subset of these sources have been listed as associated sources in the most recent Fermi catalog, 4FGL, and in these cases our results are in agreement on the classification.
We analyze several aspects of the recent construction of three-dimensional conformal gauge theories by Aharony et al. in various regimes. We pay special attention to understanding how the M-theory geometry and interpretation can be extracted from the analysis of the field theory. We revisit the calculations of the moduli space of vacua and the complete characterization of chiral ring operators by analyzing the field theory compactified on a 2-sphere. We show that many of the states dual to these operators can be interpreted as D-brane states in the weak coupling limit. Also, various features of the dual AdS geometry can be obtained by performing a strong coupling expansion around moduli space configurations, even though one is not taking the planar expansion. In particular, we show that at strong coupling the corresponding weak coupling D-brane states of the chiral ring localize on particular submanifolds of the dual geometry that match the M-theory interpretation. We also study the massive spectrum of fields in the moduli space. We use this to investigate the dispersion relation of giant magnons from the field theory point of view. Our analysis predicts the exact functional form of the dispersion relation as a function of the world-sheet momentum, independently of integrability assumptions, but not the exact form with respect to the 't Hooft coupling. We also get the dispersion relation of bound states of giant magnons from first principles, providing evidence for the full integrability of the corresponding spin chain model at strong 't Hooft coupling.
The 3D reconstruction of objects is a prerequisite for many highly relevant applications of computer vision such as mobile robotics or autonomous driving. To deal with the inverse problem of reconstructing 3D objects from their 2D projections, a common strategy is to incorporate prior object knowledge into the reconstruction approach by establishing a 3D model and aligning it to the 2D image plane. However, current approaches are limited due to inadequate shape priors and the insufficiency of the derived image observations for a reliable alignment with the 3D model. The goal of this paper is to show how 3D object reconstruction can profit from a more sophisticated shape prior and from a combined incorporation of different observation types inferred from the images. We introduce a subcategory-aware deformable vehicle model that makes use of a prediction of the vehicle type for a more appropriate regularisation of the vehicle shape. A multi-branch CNN is presented to derive predictions of the vehicle type and orientation. This information is also introduced as prior information for model fitting. Furthermore, the CNN extracts vehicle keypoints and wireframes, which are well-suited for model-to-image association and model fitting. The task of pose estimation and reconstruction is addressed by a versatile probabilistic model. Extensive experiments are conducted using two challenging real-world data sets on both of which the benefit of the developed shape prior can be shown. A comparison to state-of-the-art methods for vehicle pose estimation shows that the proposed approach performs on par or better, confirming the suitability of the developed shape prior and probabilistic model for vehicle reconstruction.
We use an extended two-band Kondo lattice model (KLM) to investigate the occurrence of different (anti-)ferromagnetic phases or phase separation depending on several model parameters. With regard to CMR-materials like the manganites we have added a Jahn-Teller term, direct antiferromagnetic coupling and Coulomb interaction to the KLM. The electronic properties are self-consistently calculated in an interpolating self-energy approach with no restriction to classical spins and going beyond mean-field treatments. Further on we do not have to limit the Hund's coupling to low or infinite values. Zero-temperature phase diagrams are presented for large parameter intervals. There are strong influences of the type of Coulomb interaction (intraband, interband) and of the important parameters (Hund's coupling, direct antiferromagnetic exchange, Jahn-Teller distortion), especially at intermediate couplings.
The strain dependent functional properties of epitaxial transition metal oxide films can be significantly modified via substrate selection. However, large lattice mismatches preclude dislocation-free epitaxial growth on ferroelectric substrates, whose strain states are modified by applied electric fields. Here we overcome this mismatch problem by depositing an epitaxial film of ferromagnetic La0.7Sr0.3MnO3 on a single crystal substrate of well lattice matched SrTiO3 via a film of SrRuO3 that we subsequently dissolved, permitting the transfer of unstrained La0.7Sr0.3MnO3 to a ferroelectric substrate of 0.68Pb(Mg1/3Nb2/3)O3 0.32PbTiO3 in a different crystallographic orientation. Ferroelectric domain switching, and a concomitant ferroelectric phase transition, produced large non volatile changes of magnetization that were mediated by magnetic domain rotations at locations defined by the microstructure - as revealed via high resolution vector maps of magnetization constructed from photoemission electron microscopy data, with contrast from x-ray magnetic circular dichroism. In future, our method may be exploited to control functional properties in dislocation free epitaxial films of any composition.
We use the Kerr-Schild type Teukolsky equation (horizon penetrating) to evolve binary black hole initial data as proposed by Bishop {\em et al.} in the close limit. Our results are in agreement with those recently obtained by Sarbach {\em et al.} from the Zerilli equation evolution of the same initial data.
We study the LFV Higgs production processes $e^-\gamma\to\ell^-\phi\;(\ell=\mu,\tau; \phi=H, A)$ as a probe of Higgs mediated LFV couplings at an electron-photon collider, where $H$ and $A$ are extra CP even and odd Higgs bosons, respectively, in the two Higgs doublet model. Under the constraints from the current data of muon and tau rare decay, the cross section can be significantly large. It would improve the experimental upper bounds on the effective LFV coupling constants. In addition, the chirality nature of the LFV Higgs coupling constants can be measured by selecting electron beam polarizations.
MAX phases are nanolaminated ternary materials that combine metallic and ceramic properties. Currently, the A-site elements replacement in traditional ones by later transition-metals opens a door to explore new types of MAX phases. In this work, we performed a systematic first-principle study to explore trends in stability, electronic structure and mechanical properties of 288 compositions of M2AX phases (M=Ti, V, Cr, Zr, Nb, Mo, Hf, Ta, W; A=Al, Si, P, S, Ga, Ge, As, Se, In, Sn, Sb, Te, Tl, Pb, Bi, Mn, Fe, Co, Ni, Cu, Zn, Tc, Ru, Rh, Pd, Ag, Cd, Os, Ir, Pt, Au, Hg; X=C). Such a dataset, combined with the rigid-band model been applied to most transition metal carbides, shows us the fundamental trends in bonding mechanisms and mechanical properties of MAX phases endowed with the periodic arrangements of M/A-site elements. It worth noting, in particular, the M-A d-d interactions of MAX phases uniquely contribute to the elastic constant C33.
Semantic scene completion is the task of producing a complete 3D voxel representation of volumetric occupancy with semantic labels for a scene from a single-view observation. We built upon the recent work of Song et al. (CVPR 2017), who proposed SSCnet, a method that performs scene completion and semantic labelling in a single end-to-end 3D convolutional network. SSCnet uses only depth maps as input, even though depth maps are usually obtained from devices that also capture colour information, such as RGBD sensors and stereo cameras. In this work, we investigate the potential of the RGB colour channels to improve SSCnet.
Robust object tracking requires knowledge of tracked objects' appearance, motion and their evolution over time. Although motion provides distinctive and complementary information especially for fast moving objects, most of the recent tracking architectures primarily focus on the objects' appearance information. In this paper, we propose a two-stream deep neural network tracker that uses both spatial and temporal features. Our architecture is developed over ATOM tracker and contains two backbones: (i) 2D-CNN network to capture appearance features and (ii) 3D-CNN network to capture motion features. The features returned by the two networks are then fused with attention based Feature Aggregation Module (FAM). Since the whole architecture is unified, it can be trained end-to-end. The experimental results show that the proposed tracker TRAT (TRacking by ATtention) achieves state-of-the-art performance on most of the benchmarks and it significantly outperforms the baseline ATOM tracker.
We study an experimental scheme to generate Gaussian two-mode entangled states via beam splitter. Specifically, we consider a nonclassical Gaussian state (squeezed state) and a thermal state as two input modes, and evaluate the degree of entanglement at the output. Experimental conditions to generate entangled outputs are completely identified and the critical thermal noise to destroy entanglement is analytically obtained. By doing so, we discuss the possibility to link the resistance to noise in entanglement generation with the degree of single-mode nonclassicality.
In 1969 Leighton developed a quasi-1D mathematical model of the solar dynamo, building upon the phenomenological scenario of Babcock(1961). Here we present a modification and extension of Leighton's model. Using the axisymmetric component of the magnetic field, we consider the radial field component at the solar surface and the radially integrated toroidal magnetic flux in the convection zone, both as functions of latitude. No assumptions are made with regard to the radial location of the toroidal flux. The model includes the effects of turbulent diffusion at the surface and in the convection zone, poleward meridional flow at the surface and an equatorward return flow affecting the toroidal flux, latitudinal differential rotation and the near-surface layer of radial rotational shear, downward convective pumping of magnetic flux in the shear layer, and flux emergence in the form of tilted bipolar magnetic regions. While the parameters relevant for the transport of the surface field are taken from observations, the model condenses the unknown properties of magnetic field and flow in the convection zone into a few free parameters (turbulent diffusivity, effective return flow, amplitude of the source term, and a parameter describing the effective radial shear). Comparison with the results of two-dimensional flux transport dynamo codes shows that the model captures the essential features of these simulations. We carry out a parameter study over the four-dimensional parameter space and identify the parameter ranges that provide solar-like solutions. Dipole parity is always preferred and solutions with periods around 22 years and a correct phase difference between flux emergence in low latitudes and the strength of the polar fields are found for a return flow speed around 2~m/s, turbulent diffusivity <80~km^2/s, and dynamo excitation not too far above the threshold (linear growth rate <0.1/yr).
It is known that the connected graphs that are $p$-good for all $p$ are the trees. In this paper, we ask which ordered trees are order-$p$-good for all $p$.
We define a characteristic energy density based on the measurement of the two first moments of the extrinsic injected power smoothed over time. Using the stationarity, we show that this definition characterizes an energy per degrees freedom of the intrinsic dissipation. Our framework can be applied to systems in contact with thermostats put out of equilibrium by an external driving but it holds also for intrinsically dissipative macroscopic systems that go at rest when the forcing is stopped. Moreover, we are not concerned about the fluctuations around zero of the smoothed injected power that can be extremely rare and difficult to catch experimentally. Then we show that the characteristic energy density we defined, reduces to the kinetic energy of a Brownian-like particle described by a set of Langevin equations with a viscous damping term. The particle can be either in contact with a thermostat or intrinsically dissipative and driven by a random force. In the first case, we recover the result obtained in the framework of the fluctuation relation but extended to a correlated thermal noise. Our characteristic energy density is measured in an experimental system of nonlinear waves generated by a large shaker in a thin elastic plate. A smaller shaker attached to the moving plate is used as a probe to measure the energy exchanged with the plate excited by the large shaker. For both, the proportionality of our characteristic energy density with the kinetic energy is demonstrated. It is a consequence of the viscous damping driving the dissipation in this system. Another system with nonlinear frictional dissipation is investigated numerically model. In this case, our definition of energy density deduced from fluctuations of injected power still characterizes the dissipation but is no more proportional to the kinetic energy because the dissipative process is not a viscous damping.
We count permutations avoiding a nonconsecutive instance of a two- or three-letter pattern, that is, the pattern may occur but only as consecutive entries in the permutation. Two-letter patterns give rise to the Fibonacci numbers. The counting sequences for the two representative three-letter patterns, 321 and 132, have respective generating functions (1+x^2)(C(x)-1)/(1+x+x^2-x C(x)) and C(x+x^3) where C(x) is the generating function for the Catalan numbers.
The content of Einstein's theory of gravitation is encoded in the properties of the solutions to his field equations. There has been obtained a wealth of information about these solutions in the ninety years the theory has been around. It led to the prediction and the observation of physical phenomena which confirm the important role of general relativity in physics. The understanding of the domain of highly dynamical, strong field configurations is, however, still quite limited. The gravitational wave experiments are likely to provide soon observational data on phenomena which are not accessible by other means. Further theoretical progress will require, however, new methods for the analysis and the numerical calculation of the solutions to Einstein's field equations on large scales and under general assumptions. We discuss some of the problems involved, describe the status of the field and recent results, and point out some open problems.
Image captioning is a task in the field of Artificial Intelligence that merges between computer vision and natural language processing. It is responsible for generating legends that describe images, and has various applications like descriptions used by assistive technology or indexing images (for search engines for instance). This makes it a crucial topic in AI that is undergoing a lot of research. This task however, like many others, is trained on large images labeled via human annotation, which can be very cumbersome: it needs manual effort, both financial and temporal costs, it is error-prone and potentially difficult to execute in some cases (e.g. medical images). To mitigate the need for labels, we attempt to use self-supervised learning, a type of learning where models use the data contained within the images themselves as labels. It is challenging to accomplish though, since the task is two-fold: the images and captions come from two different modalities and usually handled by different types of networks. It is thus not obvious what a completely self-supervised solution would look like. How it would achieve captioning in a comparable way to how self-supervision is applied today on image recognition tasks is still an ongoing research topic. In this project, we are using an encoder-decoder architecture where the encoder is a convolutional neural network (CNN) trained on OpenImages dataset and learns image features in a self-supervised fashion using the rotation pretext task. The decoder is a Long Short-Term Memory (LSTM), and it is trained, along within the image captioning model, on MS COCO dataset and is responsible of generating captions. Our GitHub repository can be found: https://github.com/elhagry1/SSL_ImageCaptioning_RotationPrediction
Cyclotomic polynomials play an important role in several areas of mathematics and their study has a very long history, which goes back at least to Gauss (1801). In particular, the properties of their coefficients have been intensively studied by several authors, and in the last 10 years there has been a burst of activity in this field of research.   This concise survey attempts to collect the main results regarding the coefficients of the cyclotomic polynomials and to provide all the relevant references to their proofs. Previous surveys on this topic were given by Lenstra (1979), Vaughan (1989), and Thangadurai (2000).