ShantanuT01/DACTYL-Pretraining huggingface dataset:
This paper studies a practically meaningful ship detection problem from synthetic aperture radar (SAR) images by the neural network. We broadly extract different types of SAR image features and raise the intriguing question that whether these extracted features are beneficial to (1) suppress data variations (e.g., complex land-sea backgrounds, scattered noise) of real-world SAR images, and (2) enhance the features of ships that are small objects and have different aspect (length-width) ratios, therefore resulting in the improvement of ship detection. To answer this question, we propose a SAR-ship detection neural network (call SAR-ShipNet for short), by newly developing Bidirectional Coordinate Attention (BCA) and Multi-resolution Feature Fusion (MRF) based on CenterNet. Moreover, considering the varying length-width ratio of arbitrary ships, we adopt elliptical Gaussian probability distribution in CenterNet to improve the performance of base detector models. Experimental results on the public SAR-Ship dataset show that our SAR-ShipNet achieves competitive advantages in both speed and accuracy.
We investigate the bias-modulated dynamics of a strongly driven two-level system using the counter-rotating-hybridized rotating-wave (CHRW) method. This CHRW method treats the driving field and the bias on equal footing by a unitary transformation with two parameters $\xi$ and $\zeta$, and is nonperturbative in driving strength, tunneling amplitude or bias. In addition, this CHRW method is beyond the traditional rotating-wave approximation (Rabi-RWA) and yet by properly choosing the two parameters $\xi$ and $\zeta$, the transformed Hamiltonian takes the RWA form with a renormalized energy splitting and a renormalized driving strength. The reformulated CHRW method possesses the same mathematical simplicity as the Rabi-RWA approach and thus allows us to calculate analytically the dynamics and explore explicitly the effect of the bias. We show that the CHRW method gives the accurate driven dynamics for a wide range of parameters as compared to the numerically exact results. When energy scales of the driving are comparable to the intrinsic energy scale of the two-level systems, the counter-rotating interactions and static bias profoundly influence the generalized Rabi frequency. In this regime, where ordinary perturbation approaches fail, the CHRW works very well and efficiently. We also demonstrate the dynamics of the system in the strong-driving and off-resonance cases for which the Rabi-RWA method breaks down but the CHRW method remains valid. We obtain analytical expressions for the generalized Rabi frequency and bias-modulated Bloch-Siegert shift as functions of the bias, tunneling and driving field parameters. The CHRW approach is a mathematically simple and physically clear method. It can be applied to treat some complicated problems for which a numerical study is difficult to perform.
In this third paper of our series, we present CCD spectrophotometry of 78 star clusters that were detected by Chandar, Bianchi, & Ford in the nearby spiral galaxy M33. CCD images of M33 were obtained as a part of the BATC Color Survey of the sky in 13 intermediate-band filters from 3800 to 10000{\AA}. By aperture photometry, we obtain the spectral energy distributions of these 78 star clusters. As Chandar, Bianchi, & Ford did, we estimate the ages of our sample clusters by comparing the photometry of each object with theoretical stellar population synthesis models for different values of metallicity. We find that the sample clusters formed continuously in M33 from $\sim 3\times10^6$ -- $10^{10}$ years. This conclusion is consistent with Chandar, Bianchi, & Ford. The results also show that, there are two peaks in cluster formation, at $\sim 8\times10^6$ and $\sim 10^9$ years in these clusters.
3D human pose estimation is frequently seen as the task of estimating 3D poses relative to the root body joint. Alternatively, we propose a 3D human pose estimation method in camera coordinates, which allows effective combination of 2D annotated data and 3D poses and a straightforward multi-view generalization. To that end, we cast the problem as a view frustum space pose estimation, where absolute depth prediction and joint relative depth estimations are disentangled. Final 3D predictions are obtained in camera coordinates by the inverse camera projection. Based on this, we also present a consensus-based optimization algorithm for multi-view predictions from uncalibrated images, which requires a single monocular training procedure. Although our method is indirectly tied to the training camera intrinsics, it still converges for cameras with different intrinsic parameters, resulting in coherent estimations up to a scale factor. Our method improves the state of the art on well known 3D human pose datasets, reducing the prediction error by 32% in the most common benchmark. We also reported our results in absolute pose position error, achieving 80~mm for monocular estimations and 51~mm for multi-view, on average.
We approximately solve the Dirac equation for the inversely quadratic Yukawa (IQY) potential including a Coulomb-like tensor potential with arbitrary spin-orbit coupling quantum number . In the framework of the spin and pseudospin (pspin) symmetry, we obtain the energy eigenvalue equation and the corresponding eigenfunctions in closed form by using the Nikiforov-Uvarov method. The numerical results show that the Coulomb-like tensor interaction removes degeneracies between spin and pspin state doublets.
Aim: Present a systematic development of part of the theory of combinatorial games from the ground up.   Approach: Computational complexity. Combinatorial games are completely determined; the questions of interest are efficiencies of strategies.   Methodology: Divide and conquer. Ascend from Nim to chess in small strides at a gradient that's not too steep.   Presentation: Informal; examples of games sampled from various strategic viewing points along scenic mountain trails, which illustrate the theory.
The most popular progenitor model for short duration Gamma-Ray bursts (sGRBs) is the merger of two compact objects. However, the short GRB population exhibit a certain diversity: some bursts display an extended emission (EE), continuing in soft $\gamma$-rays for a few hundreds of seconds post the initial short pulse. It is currently unclear whether the origin of such bursts is linked to compact object mergers.   Within the merger hypothesis, the redshift ($z$) distribution of short GRBs is influenced by the merger delay time, i.e., time elapsed between the merger and the formation of the binary star system, which is dominated by the time-scale for gravitational wave losses during the compact binary phase. We examine redshift distributions of short GRBs with extended emission to see whether their formation channel requires considerable delay post the star formation episode. Our results show that the $z$ distribution of EE bursts is consistent with the merger model. We attempted to compare the delay time distribution of the EE and the non-EE short bursts. However, no statistically significant difference could be seen within the limited sample size.
Motivated by contact resistance on the front side of a crystalline silicon solar cell, we formulate and analyse a two-dimensional mathematical model for electron flow across a poorly conducting (glass) layer situated between silver electrodes, based on the drift-diffusion (Poisson-Nernst-Planck) equations. We devise and validate a novel spectral method to solve this model numerically. We find that the current short-circuits through thin glass layer regions. This enables us to determine asymptotic expressions for the average current density for two different canonical glass layer profiles.
The origin of the diffuse extragalactic gamma-ray background, which was measured with the large area telescope (LAT) aboard the Fermi satellite at energy below 820 GeV, and of the diffuse cosmic background of neutrinos, which was observed at much higher energies with the IceCube detector deep under the south pole ice, are among the current unsolved major cosmic puzzles. Here we show that their properties indicate a common origin: the decay of mesons produced in collisions of cosmic rays accelerated in relativistic jets with matter in/near source. Moreover, their properties are those expected if these highly relativistic jets are those that produce long duration gamma ray bursts in core collapse supernovae of type Ic, which take place mostly in the densest regions of giant molecular clouds in star forming galaxies, and those that are fired by blazars into their broad line region (BLR), which contains millions of mini-clouds.
Unlike most satellite galaxies in the Local Group that have long lost their gaseous disks, the Magellanic Clouds are gas-rich dwarf galaxies most-likely on their first pericentric passage allowing us to study disk evolution on the smallest scales. The Magellanic Clouds show both disk destruction and (re)-creation. The Large Magellanic Cloud has a very extended stellar disk reaching to at least 15 kpc (10 radial scalelengths) while its gaseous disk is truncated at ~5 kpc mainly due to its interaction with the hot gaseous halo of the Milky Way. The stellar disk of the Small Magellanic Cloud, on the other hand, has essentially been destroyed. The old stellar populations show no sign of rotation (being pressure supported) and have an irregular and elongated shape. The SMC has been severely disturbed by its close encounters with the LMC (the most recent only 200 Myr ago) which have also stripped out large quantities of gas creating much of the Magellanic Stream and the Magellanic Bridge. Amazingly, the SMC has an intact, rotating HI disk indicating that either the inner HI was preserved from destruction, or, more likely, that the HI disk reformed quickly after the last close encounter with the LMC.
The origin of the star forming main sequence ( i.e., the relation between star formation rate and stellar mass, globally or on kpc-scales; hereafter SFMS) remains a hotly debated topic in galaxy evolution. Using the ALMA-MaNGA QUEnching and STar formation (ALMaQUEST) survey, we show that for star forming spaxels in the main sequence galaxies, the three local quantities, star-formation rate surface density (\sigsfr), stellar mass surface density (\sigsm), and the \h2~mass surface density (\sigh2), are strongly correlated with one another and form a 3D linear (in log) relation with dispersion. In addition to the two well known scaling relations, the resolved SFMS (\sigsfr~ vs. \sigsm) and the Schmidt-Kennicutt relation (\sigsfr~ vs. \sigh2; SK relation), there is a third scaling relation between \sigh2~ and \sigsm, which we refer to as the `molecular gas main sequence' (MGMS). The latter indicates that either the local gas mass traces the gravitational potential set by the local stellar mass or both quantities follow the underlying total mass distributions. The scatter of the resolved SFMS ($\sigma \sim 0.25$ dex) is the largest compared to those of the SK and MGMS relations ($\sigma \sim$ 0.2 dex). A Pearson correlation test also indicates that the SK and MGMS relations are more strongly correlated than the resolved SFMS. Our result suggests a scenario in which the resolved SFMS is the least physically fundamental and is the consequence of the combination of the SK and the MGMS relations.
The Gaia Data Release 1 (DR1) sample of white dwarf parallaxes is presented, including 6 directly observed degenerates and 46 white dwarfs in wide binaries. This data set is combined with spectroscopic atmospheric parameters to study the white dwarf mass-radius relationship (MRR). Gaia parallaxes and G magnitudes are used to derive model atmosphere dependent white dwarf radii, which can then be compared to the predictions of a theoretical MRR. We find a good agreement between Gaia DR1 parallaxes, published effective temperatures (Teff) and surface gravities (log g), and theoretical MRRs. As it was the case for Hipparcos, the precision of the data does not allow for the characterisation of hydrogen envelope masses. The uncertainties on the spectroscopic atmospheric parameters are found to dominate the error budget and current error estimates for well-known and bright white dwarfs may be slightly optimistic. With the much larger Gaia DR2 white dwarf sample it will be possible to explore the MRR over a much wider range of mass, Teff, and spectral types.
Existing studies in few-shot semantic segmentation only focus on mining the target object information, however, often are hard to tell ambiguous regions, especially in non-target regions, which include background (BG) and Distracting Objects (DOs). To alleviate this problem, we propose a novel framework, namely Non-Target Region Eliminating (NTRE) network, to explicitly mine and eliminate BG and DO regions in the query. First, a BG Mining Module (BGMM) is proposed to extract the BG region via learning a general BG prototype. To this end, we design a BG loss to supervise the learning of BGMM only using the known target object segmentation ground truth. Then, a BG Eliminating Module and a DO Eliminating Module are proposed to successively filter out the BG and DO information from the query feature, based on which we can obtain a BG and DO-free target object segmentation result. Furthermore, we propose a prototypical contrastive learning algorithm to improve the model ability of distinguishing the target object from DOs. Extensive experiments on both PASCAL-5i and COCO-20i datasets show that our approach is effective despite its simplicity.
An analog of the Meir-Wingreen formula for the steady-state heat current through a model molecular junction is derived. The expression relates the heat current to correlation functions that involve operators only acting on the degrees of freedom of the molecular junction. As a result, the macroscopic heat reservoirs are not treated explicitly. This allows one to exploit methods based on a reduced description of the dynamics of a relatively small part of the overall system to evaluate the heat current through a molecular junction. The derived expression is applied to calculate the steady-state heat current in a weak coupling limit, where Redfield theory is used to describe the reduced dynamics of the molecular junction. The results are compared with those from the previously developed approximate and numerically exact methods.
Spectroscopic confirmation of galaxies at z~7 and above has been extremely difficult, owing to a drop in intensity of Ly-alpha emission in comparison with samples at z~6. This crucial finding could potentially signal the ending of cosmic reionization. However it is based on small datasets, often incomplete and heterogeneous in nature. We introduce a flexible Bayesian framework, useful to interpret such evidence. Within this framework, we implement two simple phenomenological models: a smooth one, where the distribution of Ly-alpha is attenuated by a factor \es with respect to z~6; a patchy one where a fraction \ep is absorbed/non-emitted while the rest is unabsorbed. From a compilation of 39 observed z~7 galaxies we find \es=0.69+-0.12 and \ep=0.66+-0.16. The models can be used to compute fractions of emitters above any equivalent width W. For W>25\AA, we find X^{25}_{z=7}=0.37+-0.11 (0.14+-0.06) for galaxies fainter (brighter) than M_{UV}=-20.25 for the patchy model, consistent with previous work, but with smaller uncertainties by virtue of our full use of the data. At z~8 we combine new deep (5-\sigma flux limit 10^{-17}ergs^{-1}cm^{-2}) Keck-NIRSPEC observations of a bright Y-dropout identified by our BoRG Survey, with those of three objects from the literature and find that the inference is inconclusive. We compute predictions for future near-infrared spectroscopic surveys and show that it is challenging but feasible to constrain the distribution of Ly-alpha emitters at z~8 and distinguish between models.
We present recent advances on Dirichlet forms methods either to extend financial models beyond the usual stochastic calculus or to study stochastic models with less classical tools. In this spirit, we interpret the asymptotic error on the solution of an sde due to the Euler scheme in terms of a Dirichlet form on the Wiener space, what allows to propagate this error thanks to functional calculus.
We show that an information theoretic distance measured by the relative Fisher information between canonical equilibrium phase densities corresponding to forward and backward processes is intimately related to the gradient of the dissipated work in phase space. We present a universal constraint on it via the logarithmic Sobolev inequality. Furthermore, we point out that a possible expression of the lower bound indicates a deep connection in terms of the relative entropy and the Fisher information of the canonical distributions.
We compute exact asymptotic results for the probability of the occurrence of large deviations of the largest (smallest) eigenvalue of random matrices belonging to the Gaussian orthogonal, unitary and symplectic ensembles. In particular, we show that the probability that all the eigenvalues of an (NxN) random matrix are positive (negative) decreases for large N as ~\exp[-\beta \theta(0) N^2] where the Dyson index \beta characterizes the ensemble and the exponent \theta(0)=(\ln 3)/4=0.274653... is universal. We compute the probability that the eigenvalues lie in the interval [\zeta_1,\zeta_2] which allows us to calculate the joint probability distribution of the minimum and the maximum eigenvalue. As a byproduct, we also obtain exactly the average density of states in Gaussian ensembles whose eigenvalues are restricted to lie in the interval [\zeta_1,\zeta_2], thus generalizing the celebrated Wigner semi-circle law to these restricted ensembles. It is found that the density of states generically exhibits an inverse square-root singularity at the location of the barriers. These results are confirmed by numerical simulations.
We present a new methodology for the analysis of the emission lines of the interstellar medium in the Narrow Line Regions around type-2 Active Galactic Nuclei. Our aim is to provide a recipe that can be used for large samples of objects in a consistent way using different sets of optical emission-lines that takes into the account possible variations from the (O/H)-(N/O) relation to use [N II] lines. Our approach consists of a bayesian-like comparison between certain observed emission-line ratios sensitive to total oxygen abundance, nitrogen-to-oxygen ratio and ionization parameter with the predictions from a large grid of photoionization models calculated under the most usual conditions in this environment. We applied our method to a sample of Seyfert 2 galaxies with optical emission-line fluxes and determinations of their chemical properties from detailed models in the literature. Our results agree within the errors with other results and confirm the high metallicity of the objects of the sample, with N/O values consistent wit a large secondary production of N, but with a large dispersion. The obtained ionization parameters for this sample are much larger than those for star-forming object at the same metallicity.
In the present work, we present a detailed discussion of a Riemannian metric structure originally introduced in [Gori et al., \textit{J. Stat. Mech.}, \textbf{9} 093204 (2018)] on the configuration space and on phase space allowing us to interpret the derivatives of the configurational microcanonical entropy and of the canonical entropy in terms of integrals of extrinsic geometrical quantities associated with the equipotential level sets.
The (supermassive black hole mass, $M_\text{BH}$)-(bulge stellar mass, $M_{\rm*,sph}$) relation is, obviously, derived using two quantities. We endeavor to provide accurate values for the latter via detailed multicomponent galaxy decompositions for the current full sample of 43 spiral galaxies having directly measured $M_\text{BH}$ values; 35 of these galaxies have been alleged to contain pseudobulges, 21 have water maser measurements, and three appear bulgeless. This more than doubles the previous sample size of spiral galaxies with a finessed image analysis. We have analyzed near-infrared images, accounting for not only the bulge, disk (exponential, truncated, or inclined), and bar but also for spiral arms and rings and additional central components (active galactic nuclei (AGNs), etc.). A symmetric Bayesian analysis finds $\log\left(M_\text{BH}/M_{\odot}\right)=\left(2.44_{-0.31}^{+0.35}\right)\log\left\{M_{\rm*,sph}/[\upsilon(1.15\times10^{10}\,M_{\odot})]\right\}+(7.24\pm0.12)$, with $\upsilon$ a stellar mass-to-light ratio term. The level of scatter equals that about the $M_{\rm BH}$-$\sigma_*$ relation. The nonlinear slope rules out the idea that many mergers, coupled with the central limit theorem, produced this scaling relation, and it corroborates previous observational studies and simulations, which have reported a near-quadratic slope at the low-mass end of the $M_\text{BH}$-$M_{\rm*,sph}$ diagram. Furthermore, bulges with AGNs follow this relation; they are not offset by an order of magnitude, and models that have invoked AGN feedback to establish a linear $M_{\rm BH}$-$M_{\rm*,sph}$ relation need revisiting. We additionally present an updated $M_\text{BH}$-(S\'ersic index, $n_\text{sph}$) relation for spiral galaxy bulges with a comparable level of scatter and a new $M_{\rm*,sph}$-(spiral-arm pitch angle, $\phi$) relation.
Negotiation, as an essential and complicated aspect of online shopping, is still challenging for an intelligent agent. To that end, we propose the Price Negotiator, a modular deep neural network that addresses the unsolved problems in recent studies by (1) considering images of the items as a crucial, though neglected, source of information in a negotiation, (2) heuristically finding the most similar items from an external online source to predict the potential value and an acceptable agreement price, (3) predicting a general price-based action at each turn which is fed into the language generator to output the supporting natural language, and (4) adjusting the prices based on the predicted actions. Empirically, we show that our model, that is trained in both supervised and reinforcement learning setting, significantly improves negotiation on the CraigslistBargain dataset, in terms of the agreement price, price consistency, and dialogue quality.
The rowmotion action on order ideals or on antichains of a finite partially ordered set has been studied (under a variety of names) by many authors. Depending on the poset, one finds unexpectedly interesting orbit structures, instances of (small order) periodicity, cyclic sieving, and homomesy. Many of these nice features still hold when the action is extended to $[0,1]$-labelings of the poset or (via detropicalization) to labelings by rational functions (the birational setting).   In this work, we parallel the birational lifting already done for order-ideal rowmotion to antichain rowmotion. We give explicit equivariant bijections between the birational toggle groups and between their respective liftings. We further extend all of these notions to labellings by noncommutative rational functions, setting an unpublished periodicity conjecture of Grinberg in a broader context.