ShantanuT01/DACTYL-Pretraining huggingface dataset:
We reveal that strong flexoelectric effect of solids can be induced due to the signfi?cant charge migration along the strain gradient direction, which represents a new understanding of the origin of flexoelectricity. Beyond the linear response theory, we illustrate such charge migration that is driven by an electric field effect in bent silicon thinfilms. Due to such charge migration, the variation of atomic charge no longer represents a linear response to strain gradient and the resulting giant flexoelectric coeffcients being size dependent cannot be treated as a bulk property. The obtained flexoelectric coefficients compare well with the typical experimental values as reported in various ceramics. Our results shed light on elucidating the discrepancy between theory and experiment,and pave a new way to discover excellent flexoelectric performance in conventional materials.
Cosmological parameter constraints from observations of time-delay lenses are becoming increasingly precise. However, there may be significant bias and scatter in these measurements due to, among other things, the so-called mass-sheet degeneracy. To estimate these uncertainties, we analyze strong lenses from the largest EAGLE hydrodynamical simulation. We apply a mass-sheet transformation to the radial density profiles of lenses, and by selecting lenses near isothermality, we find that the bias on H0 can be reduced to 5% with an intrinsic scatter of 10%, confirming previous results performed on a different simulation data set. We further investigate whether combining lensing observables with kinematic constraints helps to minimize this bias. We do not detect any significant dependence of the bias on lens model parameters or observational properties of the galaxy, but depending on the source--lens configuration, a bias may still exist. Cross lenses provide an accurate estimate of the Hubble constant, while fold (double) lenses tend to be biased low (high). With kinematic constraints, double lenses show bias and intrinsic scatter of 6% and 10%, respectively, while quad lenses show bias and intrinsic scatter of 0.5% and 10%, respectively. For lenses with a reduced $\chi^2 > 1$, a power-law dependence of the $\chi^2$ on the lens environment (number of nearby galaxies) is seen. Lastly, we model, in greater detail, the cases of two double lenses that are significantly biased. We are able to remove the bias, suggesting that the remaining biases could also be reduced by carefully taking into account additional sources of systematic uncertainty.
We introduce an inverse design framework based on artificial neural networks, genetic algorithms, and tight-binding calculations, capable to optimize the very large configuration space of nanoelectronic devices. Our non-linear optimization procedure operates on trial Hamiltonians through superoperators controlling growth policies of regions of distinct doping. We demonstrate that our algorithm optimizes the doping of graphene-based three-terminal devices for valleytronics applications, monotonously converging to synthesizable devices with high merit functions in a few thousand evaluations (out of $\simeq 2^{3800}$ possible configurations). The best-performing device allowed for a terminal-specific separation of valley currents with $\simeq 96$\% ($\simeq 94\%)$ $K$ ($K'$) valley purity. Importantly, the devices found through our non-linear optimization procedure have both higher merit function and higher robustness to defects than the ones obtained through geometry optimization.
Massless Dirac fermions (MDFs) emerge as quasiparticles in various novel materials such as graphene and topological insulators, and they exhibit several intriguing properties, of which Veselago focusing is an outstanding example with a lot of possible applications. However, up to now Veselago focusing merely occurred in p-n junction devices based on the isotropic MDF, which lacks the tunability needed for realistic applications. Here, motivated by the emergence of novel Dirac materials, we investigate the propagation behaviors of anisotropic MDFs in such a p-n junction structure. By projecting the Hamiltonian of the anisotropic MDF to that of the isotropic MDF and deriving an exact analytical expression for the propagator, precise Veselago focusing is demonstrated without the need for mirror symmetry of the electron source and its focusing image. We show a tunable focusing position that can be used in a device to probe masked atom-scale defects. This study provides an innovative concept to realize Veselago focusing relevant for potential applications, and it paves the way for the design of novel electron optics devices by exploiting the anisotropic MDF.
The propagation of waves in two space dimensions exhibited by two exact solutions to the field equations of Einstein's unified field theory is investigated under the assumption that the metric s_{ik} is the one already chosen by Kursunoglu and by H\'ely in the years 1952-1954. It is shown that, for both exact solutions, with this choice of the metric the propagation of the waves occurs in the wave zone with the fundamental velocity (ds^2=0).
The Phoenix Deep Survey is a multi-wavelength galaxy survey based on deep 1.4 GHz radio imaging (Hopkins et al., 2003). The primary goal of this survey is to investigate the properties of star formation in galaxies and to trace the evolution in those properties to a redshift z=1, covering a significant fraction of the age of the Universe. By compiling a sample of star-forming galaxies based on selection at radio wavelengths we eliminate possible biases due to dust obscuration, a significant issue when selecting objects at optical and ultraviolet wavelengths. In this paper, we present the catalogs and results of deep optical (UBVRI) and near-infrared (Ks) imaging of the deepest region of the existing decimetric radio imaging. The observations and data-processing are summarised and the construction of the optical source catalogs described, together with the details of the identification of candidate optical counterparts to the radio catalogs. Based on our UBVRIKs imaging, photometric redshift estimates for the optical counterparts to the radio detections are explored.
An alternative to the effective field theory approach to treat ghosts in higher derivative theories is to attempt to integrate them out via the Euclidean path integral formalism. It has been suggested that this method could provide a consistent framework within which we might tolerate the ghost degrees of freedom that plague, among other theories, the higher derivative gravity models that have been proposed to explain cosmic acceleration. We consider the extension of this idea to treating a class of terms with order six derivatives, and find that for a general term the Euclidean path integral approach works in the most trivial background, Minkowski. Moreover we see that even in de Sitter background, despite some difficulties, it is possible to define a probability distribution for tensorial perturbations of the metric.
We construct an effective shell-model interaction for the valence space spanned by single-particle neutron and single-hole proton states in $^{100}$Sn. Starting from chiral nucleon-nucleon and three-nucleon forces and single-reference coupled-cluster theory for $^{100}$Sn we apply a second similarity transformation that decouples the valence space. The particle-particle components of the resulting effective interaction can be used in shell model calculations for neutron deficient tin isotopes. The hole-hole interaction can be used to calculate the $N = 50$ isotones south of $^{100}$Sn, and the full particle-hole interaction describes nuclei in the region southeast of $^{100}$Sn. We compute low-lying excited states in selected nuclei southeast of $^{100}$Sn, and find reasonable agreement with data. The presented techniques can also be applied to construct effective shell-model interactions for other regions of the nuclear chart.
We suggest a possible explanation for the high frequency quasi-periodic oscillations (QPOs) in black hole low mass X-ray binaries. By solving the perturbation general relativistic magnetohydrodynamic equations, we find two stable modes of the Alf\'ven wave in the the accretion disks with toroidal magnetic fields. We suggest that these two modes may lead to the double high frequency QPOs if they are produced in the transition region between the inner advection dominated accretion flow and the outer thin disk. This model naturally accounts for the 3 : 2 relation for the upper and lower frequencies of the QPOs, and the relation between the black hole mass and QPO frequency.
The results from the ESA Gaia astrometric mission and deep photometric surveys have revolutionized our knowledge of the Milky Way. There are many ongoing efforts to search these data for stellar substructure to find evidence of individual accretion events that built up the Milky Way and its halo. One of these newly identified features, called Nyx, was announced as an accreted stellar stream traveling in the plane of the disk. Using a combination of elemental abundances and stellar parameters from the GALAH and APOGEE surveys, we find that the abundances of the highest likelihood Nyx members are entirely consistent with membership of the thick disk, and inconsistent with a dwarf galaxy origin. We conclude that the postulated Nyx stream is most probably a high-velocity component of the Milky Way's thick disk. With the growing availability of large data sets including kinematics, stellar parameters, and detailed abundances, the probability of detecting chance associations increases, and hence new searches for substructure require confirmation across as many data dimensions as possible.
We investigate the star formation rates of quiescent galaxies at high redshift (0.3 < z < 2.5) using 3D-HST WFC3 grism spectroscopy and Spitzer mid-infrared data. We select quiescent galaxies on the basis of the widely used UVJ color-color criteria. Spectral energy distribution fitting (rest frame optical and near-IR) indicates very low star formation rates for quiescent galaxies (sSFR ~ 10^-12 yr^-1). However, SED fitting can miss star formation if it is hidden behind high dust obscuration and ionizing radiation is re-emitted in the mid-infrared. It is therefore fundamental to measure the dust-obscured SFRs with a mid-IR indicator. We stack the MIPS-24um images of quiescent objects in five redshift bins centered on z = 0.5, 0.9, 1.2, 1.7, 2.2 and perform aperture photometry. Including direct 24um detections, we find sSFR ~ 10^-11.9 * (1+z)^4 yr^-1. These values are higher than those indicated by SED fitting, but at each redshift they are 20-40 times lower than those of typical star forming galaxies. The true SFRs of quiescent galaxies might be even lower, as we show that the mid-IR fluxes can be due to processes unrelated to ongoing star formation, such as cirrus dust heated by old stellar populations and circumstellar dust. Our measurements show that star formation quenching is very efficient at every redshift. The measured SFR values are at z > 1.5 marginally consistent with the ones expected from gas recycling (assuming that mass loss from evolved stars refuels star formation) and well above that at lower redshifts.
We present a series of models for the plasma properties along open magnetic flux tubes rooted in solar coronal holes, streamers, and active regions. These models represent the first self-consistent solutions that combine: (1) chromospheric heating driven by an empirically guided acoustic wave spectrum, (2) coronal heating from Alfven waves that have been partially reflected, then damped by anisotropic turbulent cascade, and (3) solar wind acceleration from gradients of gas pressure, acoustic wave pressure, and Alfven wave pressure. The only input parameters are the photospheric lower boundary conditions for the waves and the radial dependence of the background magnetic field along the flux tube. For a single choice for the photospheric wave properties, our models produce a realistic range of slow and fast solar wind conditions by varying only the coronal magnetic field. Specifically, a 2D model of coronal holes and streamers at solar minimum reproduces the latitudinal bifurcation of slow and fast streams seen by Ulysses. The radial gradient of the Alfven speed affects where the waves are reflected and damped, and thus whether energy is deposited below or above the Parker critical point. As predicted by earlier studies, a larger coronal ``expansion factor'' gives rise to a slower and denser wind, higher temperature at the coronal base, less intense Alfven waves at 1 AU, and correlative trends for commonly measured ratios of ion charge states and FIP-sensitive abundances that are in general agreement with observations. These models offer supporting evidence for the idea that coronal heating and solar wind acceleration (in open magnetic flux tubes) can occur as a result of wave dissipation and turbulent cascade. (abridged abstract)
We investigate classical and quantum physics-based algorithms for solving the graph isomorphism problem. Our work integrates and extends previous work by Gudkov et al. (cond-mat/0209112) and by Rudolph (quant-ph/0206068). Gudkov et al. propose an algorithm intended to solve the graph isomorphism problem in polynomial time by mimicking a classical dynamical many-particle process. We show that this algorithm fails to distinguish pairs of non-isomorphic strongly regular graphs, thus providing an infinite class of counterexamples. We also show that the simplest quantum generalization of the algorithm also fails. However, by combining Gudkov et al.'s algorithm with a construction proposed by Rudoph in which one examines a graph describing the dynamics of two particles on the original graph, we find an algorithm that successfully distinguishes all pairs of non-isomorphic strongly regular graphs that we tested (with up to 29 vertices).
In the work we have considered Breuil-Kisin module over the ring of witt vectors $W(\kappa)$ over the residue field $\kappa$ of characteristic $p$ and a finite flat $\mathbb{Z}_p$-algebra $R$. Then considered Breuil-Kisin modules $M$ over the ring $W(\kappa)$ and taking the action of $R$ on $W(\kappa)$, we get again a Breuil-Kisin module $M$ over the ring $R \otimes_{\mathbb{Z}_p} W(\kappa)$. We have studied freeness and projectiveness of this module.
A complete calculation of the nuclear matrix elements (NME) for Majoron emitting neutrinoless double beta decay within the framework of IBM-2 for spectral indices $n=1,3,7$ is presented. By combining the results of this calculation with previously calculated phase space factors (PSF) we give predictions for expected half-lives. By comparing with experimental limits on the half-lives we set limits on the coupling constants $\left\langle g_{ee}^{M}\right\rangle $ of all proposed Majoron-emitting models.
The quasi-elastic scattering of muon neutrino and electrons on a carbon target are analyzed using the relativistic distorted-wave impulse approximation (RDWIA). We also evaluate the contribution of the two-particle and two-hole meson exchange current ($2p-2h$ MEC) to electroweak response functions. The nuclear model dependence of the (anti)neutrino cross sections is studied within the RDWIA+MEC approach and RDWIA model with the large nucleon axial mass. It is shown that the results for the squared momentum transfer distribution $d\sigma/dQ^2$ and for invariant mass of the final hadronic system distribution $d\sigma/dW$ obtained within these models are substantially different.
Coherent gate errors are a concern in many proposed quantum computing architectures. These errors can be effectively handled through composite pulse sequences for single-qubit gates, however, such techniques are less feasible for entangling operations. In this work, we benchmark our coherent errors by comparing the actual performance of composite single-qubit gates to the predicted performance based on characterization of individual single-qubit rotations. We then propose a compilation technique, which we refer to as hidden inverses, that creates circuits robust to these coherent errors. We present experimental data showing that these circuits suppress both overrotation and phase misalignment errors in our trapped ion system.
It has been shown that the large--scale correlation functions of the density field (and velocity divergence field) follow a specific hierarchy in the quasilinear regime and for Gaussian initial conditions (Bernardeau 1992). The exact relationships between the cumulants of the probability distribution functions (the so-called $S_p$ parameters) are however sensitive to the smoothing window function applied to the fields. In this paper, I present a method to derive the whole series of the $S_p$ parameters when the density field is smoothed with a top--hat window function. The results are valid for any power spectrum and any cosmological parameters. Similar calculations are presented for the velocity divergence field.   The resulting shapes of the one--point probability distribution functions of the cosmic density and the velocity divergence fields are given as a function of the power spectrum and $\Omega$. Simple analytical fits are proposed when the index of the power spectrum is -1. Comparisons with numerical simulations prove these analytical results to be extremely accurate.
The M{\o}ller energy complex of Schwarzschild black hole solution in several coodinates are evaluated. Our results show that the M{\o}ller energy complex is independent of not only the purely spatial transformation, but also the shift of time coordinate. So, we could conclude that a shift of time coordinates will not change the energy which is obtained by using the definition of M{\o}ller energy complex.
We discuss the feasibility of using the detection of electron antineutrinos produced in fission to monitor the time dependence of the plutonium content of nuclear power reactors. If practical such a scheme would allow world-wide, automated monitoring of reactors and, thereby, the detection of certain proliferation scenarios. For GW$_e$ power reactors the count rates and the sensitivity of the antineutrino spectrum (to the core burn-up) suggest that monitoring of the gross operational status of the reactor from outside the containment vessel is feasible. As the plutonium content builds up in a given burn cycle the total number of antineutrinos steadily drops and this variation is quite detectable, assuming fixed reactor power. The average antineutrino energy also steadily drops, and a measurement of this variation would be very useful to help off set uncertainties in the total reactor power. However, the expected change in the antineutrino signal from the diversion of a significant quantity (SQ) of plutonium, which would typically require the diversion of as little as a single fuel assemblies in a GW$_e$ reactor, would be very difficult to detect.
Genuine leather, such as the hides of cows, crocodiles, lizards and goats usually contain natural and artificial defects, like holes, fly bites, tick marks, veining, cuts, wrinkles and others. A traditional solution to identify the defects is by manual defect inspection, which involves skilled experts. It is time consuming and may incur a high error rate and results in low productivity. This paper presents a series of automatic image processing processes to perform the classification of leather defects by adopting deep learning approaches. Particularly, the leather images are first partitioned into small patches,then it undergoes a pre-processing technique, namely the Canny edge detection to enhance defect visualization. Next, artificial neural network (ANN) and convolutional neural network (CNN) are employed to extract the rich image features. The best classification result achieved is 80.3 %, evaluated on a data set that consists of 2000 samples. In addition, the performance metrics such as confusion matrix and Receiver Operating Characteristic (ROC) are reported to demonstrate the efficiency of the method proposed.
Our objective is to evaluate the efficacy of methods that use deep learning (DL) for the automatic fine-grained segmentation of optical coherence tomography (OCT) images of the retina. OCT images from 10 patients with mild non-proliferative diabetic retinopathy were used from a public (U. of Miami) dataset. For each patient, five images were available: one image of the fovea center, two images of the perifovea, and two images of the parafovea. For each image, two expert graders each manually annotated five retinal surfaces (i.e. boundaries between pairs of retinal layers). The first grader's annotations were used as ground truth and the second grader's annotations to compute inter-operator agreement. The proposed automated approach segments images using fully convolutional networks (FCNs) together with Gaussian process (GP)-based regression as a post-processing step to improve the quality of the estimates. Using 10-fold cross validation, the performance of the algorithms is determined by computing the per-pixel unsigned error (distance) between the automated estimates and the ground truth annotations generated by the first manual grader. We compare the proposed method against five state of the art automatic segmentation techniques. The results show that the proposed methods compare favorably with state of the art techniques, resulting in the smallest mean unsigned error values and associated standard deviations, and performance is comparable with human annotation of retinal layers from OCT when there is only mild retinopathy. The results suggest that semantic segmentation using FCNs, coupled with regression-based post-processing, can effectively solve the OCT segmentation problem on par with human capabilities with mild retinopathy.
Magnetic anisotropies and magnetization reversal properties of the epitaxial Heusler compound Co$_2$Cr$_{0.6}$Fe$_{0.4}$Al (CCFA) deposited on Fe and Cr buffer layers are studied. Both samples exhibit a growth-induced fourfold anisotropy, and magnetization reversal occurs through the formation of stripy domains or 90 degree domains. During rotational magnetometric scans the sample deposited on Cr exhibits about 2 degree sharp peaks in the angular dependence of the coercive field, which are oriented along the hard axis directions. These peaks are a consequence of the specific domain structure appearing in this particular measurement geometry. A corresponding feature in the sample deposited on Fe is not observed.
Considering the optimal alignment of two i.i.d. random sequences of length $n$, we show that when the scoring function is chosen randomly, almost surely the empirical distribution of aligned letter pairs in all optimal alignments converges to a unique limiting distribution as $n$ tends to infinity. This result is interesting because it helps understanding the microscopic path structure of a special type of last passage percolation problem with correlated weights, an area of long-standing open problems. Characterizing the microscopic path structure yields furthermore a robust alternative to optimal alignment scores for testing the relatedness of genetic sequences.
We report on the storage and non-resonant parametric recovery of microwave signals carried by a dipolar surface spin-wave pulse in a thin ferrimagnetic film. The information about the intensity of the spectral components of the signal within a narrow frequency band is saved due to the excitation of a dipolar-exchange standing spin-wave mode across the film thickness and is afterwards restored by means of parametric amplification of this mode. The intensity of the restored signal measured for varying shifts between the signal carrier frequency and half of the pumping frequency, which is equal to the frequency of the standing mode, reveals information about the entire frequency spectrum of the input microwave signal.