ShantanuT01/DACTYL-Pretraining huggingface dataset:
The adoption of large-scale iris recognition systems around the world has brought to light the importance of detecting presentation attack images (textured contact lenses and printouts). This work presents a new approach in iris Presentation Attack Detection (PAD), by exploring combinations of Convolutional Neural Networks (CNNs) and transformed input spaces through binarized statistical image features (BSIF). Our method combines lightweight CNNs to classify multiple BSIF views of the input image. Following explorations on complementary input spaces leading to more discriminative features to detect presentation attacks, we also propose an algorithm to select the best (and most discriminative) predictors for the task at hand.An ensemble of predictors makes use of their expected individual performances to aggregate their results into a final prediction. Results show that this technique improves on the current state of the art in iris PAD, outperforming the winner of LivDet-Iris2017 competition both for intra- and cross-dataset scenarios, and illustrating the very difficult nature of the cross-dataset scenario.
In this paper, we formulate black hole solutions through extended gravitational decoupling scheme in the framework of self-interacting Brans-Dicke theory. The addition of a new source in the matter distribution increases the degrees of freedom in the system of field equations. Transformations in radial as well as temporal metric functions split the system into two arrays. Each array includes the effects of only one source (either seed or additional). The seed source is assumed to be a vacuum and the corresponding system is specified through the Schwarzschild metric. In order to construct a suitable solution of the second system, constraints are applied on the metric potentials and energy-momentum tensor of the additional source. We obtain three solutions corresponding to different values of the decoupling parameter in the presence of a massive scalar field. The extra source is classified as normal or exotic through energy conditions. It is found that two solutions agree with the energy bounds and thus have normal matter as their source.
Given a bridgeless graph $G$, the Cycle Double Cover Conjecture posits that there is a list of cycles of $G$, such that every edge appears in exactly two cycles on the list. This conjecture was originally posed independently in 1973 by Szekeres and 1979 by Seymour. In 1985, Jaeger demonstrated that it is sufficient to prove in the case that $G$ is a cubic graph. We here present a proof that every bridgeless cubic graph has a cycle double cover by analyzing certain kinds of cycles in the line graph of $G$. Further, in the case that $G$ is cubic, we prove the stronger conjecture that given a bridgeless graph $G$ and a cycle $C$ in $G$, then there exists a cycle double cover of $G$ containing $C$.
Quantum error correction codes are usually designed to correct errors regardless of their physical origins. In large-scale devices, this is an essential feature. In smaller-scale devices, however, the main error sources are often understood, and this knowledge could be exploited for more efficient error correction. Optimizing the quantum error correction protocol is therefore a promising strategy in smaller devices. Typically, this involves tailoring the protocol to a given decoherence channel by solving an appropriate optimization problem. Here we introduce a new optimization-based approach, which maximizes the robustness to faults in the recovery. Our approach is inspired by recent experiments, where such faults have been a significant source of logical errors. We illustrate this approach with a three-qubit model, and show how near-term experiments could benefit from more robust quantum error correction protocols.
We prove that the topological cycle space C(G) of a locally finite graph G is generated by its geodetic topological circles. We further show that, although the finite cycles of G generate C(G), its finite geodetic cycles need not generate C(G).
There have been extensive studies of a random walk among a field of immobile traps (or obstacles), where one is interested in the probability of survival as well as the law of the random walk conditioned on its survival up to time $t$. In contrast, very little is known when the traps are mobile. We will briefly review the literature on the trapping problem with immobile traps, and then review some recent results on a model with mobile traps, where the traps are represented by a Poisson system of independent random walks on ${\mathbb Z}^d$. Some open questions will be given at the end.
In the recent paper by Sokolov et al. (Int. J. of Heat and Mass Transfer 176, 2021, 121442) ballistic heat propagation in 1D harmonic crystal is considered and the properties of the exact discrete solution and the solution of the ballistic heat equation introduced by Krivtsov are numerically compared. The aim of this note is to demonstrate that the latter continuum fundamental solution can be formally obtained as the slow time-varying component of the large-time asymptotics for the exact discrete solution on a moving point of observation.
We revisit the excursion set approach to calculate void abundances in chameleon-type modified gravity theories, which was previously studied by Clampitt, Cai and Li (2013). We focus on properly accounting for the void-in-cloud effect, i.e., the growth of those voids sitting in over-dense regions may be restricted by the evolution of their surroundings. This effect may change the distribution function of voids hence affect predictions on the differences between modified gravity and GR. We show that the thin-shell approximation usually used to calculate the fifth force is qualitatively good but quantitatively inaccurate. Therefore, it is necessary to numerically solve the fifth force in both over-dense and under-dense regions. We then generalise the Eulerian void assignment method of Paranjape, Lam and Sheth (2012) to our modified gravity model. We implement this method in our Monte Carlo simulations and compare its results with the original Lagrangian methods. We find that the abundances of small voids are significantly reduced in both modified gravity and GR due to the restriction of environments. However, the change in void abundances for the range of void radii of interest for both models is similar. Therefore, the difference between models remains similar to the results from the Lagrangian method, especially if correlated steps of the random walks are used. As Clampitt, Cai and Li (2013), we find that the void abundance is much more sensitive to modified gravity than halo abundances. Our method can then be a faster alternative to N-body simulations for studying the qualitative behaviour of a broad class of theories. We also discuss the limitations and other practical issues associated with its applications.
We study the first-passage time, the distribution of the maximum, and the absorption probability of fractional Brownian motion of Hurst parameter $H$ with both a linear and a non-linear drift. The latter appears naturally when applying non-linear variable transformations. Via a perturbative expansion in $\epsilon = H-1/2$, we give the first-order corrections to the classical result for Brownian motion analytically. Using a recently introduced adaptive bisection algorithm, which is much more efficient than the standard Davies-Harte algorithm, we test our predictions for the first-passage time on grids of effective sizes up to $N_{\rm eff}=2^{28}\approx 2.7\times 10^{8}$ points. The agreement between theory and simulations is excellent, and by far exceeds in precision what can be obtained by scaling alone.
Three models of single colloidal quantum dot emission fluctuations (blinking) based on spectral diffusion were considered analytically and numerically. It was shown that the only one of them, namely the Frantsuzov and Marcus model reproduces the key properties of the phenomenon. The other two models, the Diffusion-Controlled Electron Transfer (DCET) model and the Extended DCET model predict that after an initial blinking period, most of the QDs should become permanently bright or permanently dark which is significantly different from the experimentally observed behavior.
We present an infinite lattice DMRG sweeping procedure which can be used as a replacement for the standard infinite lattice blocking schemes. Although the scheme is generally applicable to any system, its main advantages are the correct representation of commensurability issues and the treatment of degenerate systems. As an example we apply the method to a spin chain featuring a highly degenerate ground state space where the new sweeping scheme provides an increase in performance as well as accuracy by many orders of magnitude compared to a recently published work.
We developed a high-performance one-stop system for large-scale genome data analysis with secure secondary use of the data by the data owner and multiple users with different levels of data access control.
A classical result of Cherbonnier and Colmez says that all \'etale $(\varphi, \Gamma)$-modules are overconvergent. In this paper, we give another proof of this fact when the base field $K$ is a finite extension of $\mathbb Q_p$. Furthermore, we obtain an explicit ("uniform") lower bound for the overconvergence radius, which was previously not known. The method is similar to that in a previous joint paper with Tong Liu. Namely, we study Wach models (when $K$ is unramified) in modulo $p^n$ Galois representations, and use them to build an overconvergence basis.
In this paper we consider the inverse problem of determining on a compact Riemannian manifold the metric tensor in the wave equation with Dirichlet data from measured Neumann boundary observations. This information is enclosed in the dynamical Dirichlet-to-Neumann map associated to the wave equation. We prove in dimension $n\geq 2$ that the knowledge of the Dirichlet-to-Neumann map for the wave equation uniquely determines the metric tensor and we establish logarithm-type stability.
Pre-training a recognition model with contrastive learning on a large dataset of unlabeled data has shown great potential to boost the performance of a downstream task, e.g., image classification. However, in domains such as medical imaging, collecting unlabeled data can be challenging and expensive. In this work, we propose to adapt contrastive learning to work with meta-label annotations, for improving the model's performance in medical image segmentation even when no additional unlabeled data is available. Meta-labels such as the location of a 2D slice in a 3D MRI scan or the type of device used, often come for free during the acquisition process. We use the meta-labels for pre-training the image encoder as well as to regularize a semi-supervised training, in which a reduced set of annotated data is used for training. Finally, to fully exploit the weak annotations, a self-paced learning approach is used to help the learning and discriminate useful labels from noise. Results on three different medical image segmentation datasets show that our approach: i) highly boosts the performance of a model trained on a few scans, ii) outperforms previous contrastive and semi-supervised approaches, and iii) reaches close to the performance of a model trained on the full data.
We consider a field theoretical model on the noncommutative cylinder which leads to a discrete-time evolution. Its Euclidean version is shown to be equivalent to a model on the complex $q$-plane. We reveal a direct link between the model on a noncommutative cylinder and the deformed Virasoro algebra constructed earlier on an abstract mathematical background. As it was shown, the deformed Virasoro generators necessarily carry a second index (in addition to the usual one), whose meaning, however, remained unknown. The present field theoretical approach allows one to ascribe a clear meaning to this second index: its origin is related to the noncommutativity of the underlying space-time. The problems with the supersymmetric extension of the model on a noncommutative super-space are briefly discussed.
Molecular static simulations of 190 symmetric tilt grain boundaries in HCP metals were used to understand the energetics of vacancy segregation, which is important for designing stable interfaces in harsh environments. Simulation results show that the local arrangements of grain boundaries and the resulting structural units have a significant influence on the magnitude of vacancy binding energies, and the site-to-site variation within each boundary is substantial. Comparing the vacancy binding energies for each site in different c/a ratio materials shows that the binding energy increases significantly with an increase in c/a ratio. For example, in the [1-210] tilt axis, Ti and Zr with c/a=1.5811 have a lower vacancy binding energy than the Mg with c/a=1.6299. Furthermore, when the grain boundary energies of all 190 boundaries in all three elements are plotted against the vacancy binding energies of the same boundaries, a highly negative correlation (r = -0.7144) is revealed that has a linear fit with a proportionality constant of -25 ang^2. This is significant for applications where extreme environmental damage generates lattice defects and grain boundaries act as sinks for both vacancies and interstitial atoms.
The ion-bombardment induced nanopatterning of Si(001) has been simulated by atomistic simulations with and without Fe impurity. The surface contamination has been simulated by using a new force field developed for FeSi. This is a fitted bond order potential (BOP) given for Si and for Fe by Albe et al. This BOP formula has been optimized simultaneously for FeSi, Si and for Fe. Using this new force field we are able to follow the ion-beam assisted deposition for Si in the presence of Fe contamination in the surface region. As an overall result, we get an unexpectedly rich variety of nanopatterns formed by the reorganization of the crater rims of the individual ion impacts. The previously thought simple atomistically roughened surfaces show unprecedented landscapes and topography with nanoscale features. The characteristic size of the units of the pattern is in the range of a few nms. Typical of the occurred pattern is the network of interconnected elongated adatom islands. We also see the self-organization of this pattern upon ion-bombardments. At $50^{\circ}$ impact angle we get a nanoporous surface (sponge-like) both for Fe-contaminated and Fe-free simulations. At $70^{\circ}$ of impact (grazing angle of incidence) the pattern resembles to that of elongated atomic chains (adatom islands) along the ion impact direction. This latter pattern could be understood as a prepattern state towards rippling. At lower angles ($30^{\circ}$) nanoholes rule the landsdcape. The obtained pattern corresponds to low fluence experiments which are used to consider as simple roughening without showing any sing of patterning.
A systematic study of terminating states in A$\sim$50 mass region using the self-consistent Skyrme-Hartree-Fock model is presented. The objective is to demonstrate that the terminating states, due to their intrinsic simplicity, offer unique and so far unexplored opportunities to study different aspects of the effective NN interaction or nuclear local energy density functional. In particular, we demonstrate that the agreement of the calculations to the data depend on the spin fields and the spin-orbit term which, in turn, allows to constrain the appropriate Landau parameters and the strength of the spin-orbit potential.
For $2\leq p<4$, we study the $L^p$ norms of restrictions of eigenfunctions of the Laplace-Beltrami operator on smooth compact $2$-dimensional Riemannian manifolds. Burq, G\'erard, and Tzvetkov \cite{BurqGerardTzvetkov2007restrictions}, and Hu \cite{Hu2009lp} found the eigenfunction estimates restricted to a curve with nonvanishing geodesic curvatures. We will explain how the proof of the known estimates helps us to consider the case where the given smooth compact Riemannian manifold has nonpositive sectional curvatures. For $p=4$, we will also obtain a logarithmic analogous estimate, by using arguments in Xi and Zhang \cite{XiZhang2017improved}, Sogge \cite{Sogge2017ImprovedCritical}, and Bourgain \cite{Bourgain1991Besicovitch}.
In this paper, explicit error bounds are derived in the approximation of rank $k$ projections of certain $n$-dimensional random vectors by standard $k$-dimensional Gaussian random vectors. The bounds are given in terms of $k$, $n$, and a basis of the $k$-dimensional space onto which we project. The random vectors considered are two generalizations of the case of a vector with independent, identically distributed components. In the first case, the random vector has components which are independent but need not have the same distribution. The second case deals with finite exchangeable sequences of random variables.
Quantum Hamilton-Jacobi Theory and supersymmetric quantum mechanics (SUSYQM) are two parallel methods to determine the spectra of a quantum mechanical systems without solving the Schr\"odinger equation. It was recently shown that the shape invariance, which is an integrability condition in SUSYQM formalism, can be utilized to develop an iterative algorithm to determine the quantum momentum functions. In this paper, we show that shape invariance also suffices to determine the eigenvalues in Quantum Hamilton-Jacobi Theory.
General regular black ring solution with two angular momenta is presented, found by the inverse scattering problem method. The mass, angular momenta and the event horizon volume are given explicitly as functions of the metric parameters.
This paper revisits recognition of natural image pleasantness by employing deep convolutional neural networks and affordable eye trackers. There exist several approaches to recognize image pleasantness: (1) computer vision, and (2) psychophysical signals. For natural images, computer vision approaches have not been as successful as for abstract paintings and is lagging behind the psychophysical signals like eye movements. Despite better results, the scalability of eye movements is adversely affected by the sensor cost. While the introduction of affordable sensors have helped the scalability issue by making the sensors more accessible, the application of such sensors in a loosely controlled human-computer interaction setup is not yet studied for affective image tagging. On the other hand, deep convolutional neural networks have boosted the performance of vision-based techniques significantly in recent years. To investigate the current status in regard to affective image tagging, we (1) introduce a new eye movement dataset using an affordable eye tracker, (2) study the use of deep neural networks for pleasantness recognition, (3) investigate the gap between deep features and eye movements. To meet these ends, we record eye movements in a less controlled setup, akin to daily human-computer interaction. We assess features from eye movements, visual features, and their combination. Our results show that (1) recognizing natural image pleasantness from eye movement under less restricted setup is difficult and previously used techniques are prone to fail, and (2) visual class categories are strong cues for predicting pleasantness, due to their correlation with emotions, necessitating careful study of this phenomenon. This latter finding is alerting as some deep learning approaches may fit to the class category bias.
We derive a microscopic relativistic point-coupling model of nuclear many-body dynamics constrained by in-medium QCD sum rules and chiral symmetry. The effective Lagrangian is characterized by density dependent coupling strengths, determined by chiral one- and two-pion exchange and by QCD sum rule constraints for the large isoscalar nucleon self-energies that arise through changes of the quark condensate and the quark density at finite baryon density. This approach is tested in the analysis of the equations of state for symmetric and asymmetric nuclear matter, and of bulk and single-nucleon properties of finite nuclei. In comparison with purely phenomenological mean-field approaches, the built-in QCD constraints and the explicit treatment of pion exchange restrict the freedom in adjusting parameters and functional forms of density dependent couplings. It is shown that chiral (two-pion exchange) fluctuations play a prominent role for nuclear binding and saturation, whereas strong scalar and vector fields of about equal magnitude and opposite sign, induced by changes of the QCD vacuum in the presence of baryonic matter, generate the large effective spin-orbit potential in finite nuclei.
Radio continuum surveys can detect galaxies over a very wide range in redshift, making them powerful tools for studying the distant universe. Until recently, though, identifying the optical counterparts of faint radio sources and measuring their redshifts was a slow and laborious process which could only be carried out for relatively small samples of galaxies.   Combining data from all-sky radio continuum surveys with optical spectra from the new large-area redshift surveys now makes it possible to measure redshifts for tens of thousands of radio-emitting galaxies, as well as determining unambiguously whether the radio emission in each galaxy arises mainly from an active nucleus (AGN) or from processes related to star formation. Here we present some results from a recent study of radio-source populations in the 2dF Galaxy Redshift Survey, including a new derivation of the local star-formation density, and discuss the prospects for future studies of galaxy evolution using both radio and optical data.
Planar functions in odd characteristic were introduced by Dembowski and Ostrom in order to construct finite projective planes in 1968. They were also used in the constructions of DES-like iterated ciphers, error-correcting codes, and signal sets. Recently, a new notion of pseudo-planar functions in even characteristic was proposed by Zhou. These new pseudo-planar functions, as an analogue of planar functions in odd characteristic, also bring about finite projective planes. There are three known infinite families of pseudo-planar monomial functions constructed by Schmidt and Zhou, and Scherr and Zieve. In this paper, three new classes of pseudo-planar binomials are provided. Moreover, we find that each pseudo-planar function gives an association scheme which is defined on a Galois ring.
Correlations between intrinsic ellipticities of galaxies are a potentially important systematic error when constraining dark energy properties from weak gravitational lensing (cosmic shear) surveys. In the absence of perfectly known galaxy redshifts some modeling of the galaxy intrinsic alignments is likely to be required to extract the lensing signal to sufficient accuracy. We present a new model based on the placement of galaxies into dark matter halos. The central galaxy ellipticity follows the large scale potential and, in the simplest case, the satellite galaxies point at the halo center. The two-halo term is then dominated by the linear alignment model and the one-halo term provides a motivated extension of intrinsic alignment models to small scales. We provide fitting formulae for the spatial projected source power spectra for both intrinsic-intrinsic (II) and shear-intrinsic (GI) correlations. We illustrate the potential impact of ignoring intrinsic alignments on cosmological parameter constraints from non-tomographic surveys, finding that sigma_8 could be underestimated by up to the size of the current 1-sigma error bar from cosmic shear if very small scales are included in the analysis. Finally, we highlight areas of interest for numerical simulations of dark matter clustering and galaxy formation that can further constrain the intrinsic alignment signal.