ShantanuT01/DACTYL-Pretraining huggingface dataset:
The source 4U 1901+03 is a high-mass X-ray pulsar than went into outburst in 2003. Observation performed with the Rossi X-ray Timing Explorer showed spectral and timing variability, including the detection of flares, quasi-periodic oscillations, complex changes in the pulse profiles, and pulse phase dependent spectral variability. We re-analysed the data covering the 2003 X-ray outburst and focused on several aspects of the variability that have not been discussed so far. These are the 10 keV feature and the X-ray spectral states and their association with accretion regimes, including the transit to the propeller state at the end of the outburst. We find that 4U 1901+03 went through three accretion regimes over the course of the X-ray outburst. At the peak of the outburst and for a very short time, the X-ray flux may have overcome the critical limit that marks the formation of a radiative shock at a certain distance above the neutron star surface. Most of the time, however, the source is in the subcritical regime. Only at the end of the outburst, when the luminosity decreased below ~10^{36} (d/10 kpc)^2 erg/s, did the source enter the propeller regime. Evidence for the existence of these regimes comes from the pulse profiles, the shape of the hardness-intensity diagram, and the correlation of various spectral parameters with the flux. The 10 keV feature appears to strongly depend on the X-ray flux and on the pulse phase, which opens the possibility to interpret this feature as a cyclotron line.
The denoising of magnetic resonance (MR) images is a task of great importance for improving the acquired image quality. Many methods have been proposed in the literature to retrieve noise free images with good performances. Howerever, the state-of-the-art denoising methods, all needs a time-consuming optimization processes and their performance strongly depend on the estimated noise level parameter. Within this manuscript we propose the idea of denoising MRI Rician noise using a convolutional neural network. The advantage of the proposed methodology is that the learning based model can be directly used in the denosing process without optimization and even without the noise level parameter. Specifically, a ten convolutional layers neural network combined with residual learning and multi-channel strategy was proposed. Two training ways: training on a specific noise level and training on a general level were conducted to demonstrate the capability of our methods. Experimental results over synthetic and real 3D MR data demonstrate our proposed network can achieve superior performance compared with other methods in term of both of the peak signal to noise ratio and the global of structure similarity index. Without noise level parameter, our general noise-applicable model is also better than the other compared methods in two datasets. Furthermore, our training model shows good general applicability.
We start from a system of six interacting constituent quarks and examine how the picture of two nucleons can change when substructure of the nucleons are taken into account.
We present a framework to calculate the anisotropic and non-linear photoconductivity for two band systems with application to graphene. In contrast to the usual perturbative (second order in the optical field strength) techniques, we calculate photoconductivity to all orders in the optical field strength. In particular, for graphene, we find the photoresponse to be giant (at large optical field strengths) and anisotropic. The anisotropic photoresponse in graphene is correlated with polarization of the incident field, with the response being similar to that of a half-wave plate. We predict that the anisotropy in the simultaneous measurement of longitudinal ($\sigma_{xx}$) and transverse $(\sigma_{yx})$ photoconductivity, with four probes, offers a unique experimental signature of the photo-voltaic response, distinguishing it from the thermal-Seebeck and bolometric effects in photoresponse.
We have carefully selected a sample of 60 galaxies that reside in the deepest underdensities of geometrically identified voids within the SDSS. HI imaging of 55 galaxies with the WSRT reveals morphological and kinematic signatures of ongoing interactions and gas accretion. We probe a total volume of 485 Mpc^3 within the voids, with an angular resolution of 8 kpc at an average distance of 85 Mpc. We reach column density sensitivities of 5 x 10^19 cm^-2, corresponding to an HI mass limit of 3 x 10^8 M_sun. We detect HI in 41 galaxies, with total masses ranging from 1.7 x 10^8 to 5.5 x 10^9 M_sun. The upper limits on the 14 non-detections are not inconsistent with their luminosities, given their expected HI mass to light ratios. We find that the void galaxies are generally gas rich, low luminosity, blue disk galaxies, with optical and HI properties that are not unusual for their luminosity and morphology. The sample spans a range of absolute magnitudes (-16.1 > M_r > -20.4) and colors (0.06 < g-r < 0.87), and includes disk and irregular galaxies. We also identify three as early type galaxies, all of which are not detected in HI. All galaxies have stellar masses less than 3 x 10^10 M_sun, and many have kinematic and morphological signs of ongoing gas accretion, suggesting that the void galaxy population is still in the process of assembling. The small scale clustering in the void, within 600 kpc and 200 km/s, is similar to that in higher density regions, and we identify 18 HI rich neighboring galaxies in the voids. Most are within 100 kpc and 100 km/s of the targeted galaxy, and we find no significant population of HI rich low luminosity galaxies filling the voids, contrary to what is predicted by simulations.
This paper is concerned with the blowup phenomenon of stochastic parabolic equations both on bounded domain and in the whole space. We introduce a new method to study the blowup phenomenon on bounded domain. Comparing with the existing results, we delete the assumption that the solutions to stochastic heat equations are non-negative. Then the blowup phenomenon in the whole space is obtained by using the properties of heat kernel. We obtain that the solutions will blow up in finite time for nontrivial initial data.
To examine thermoelectric (TE) properties of a semiconductor nanowire (NW) network, we propose a theoretical approach mapping the TE network on a two-port network. In contrast to a conventional single-port (i.e., resistor) network model, our model allows for large scale calculations showing convergence of TE figure of merit, $ZT$, with an increasing number of junctions. Using this model, numerical simulations are performed for the Bi$_2$Te$_3$ branched nanowire (BNW) and Cayley tree NW (CTNW) network. We find that the phonon scattering at the network junctions plays a dominant role in enhancing the network $ZT$. Specifically, disordered BNW and CTNW demonstrate an order of magnitude higher ZT enhancement compared to their ordered counterparts. Formation of preferential TE pathways in CTNW makes the network effectively behave as its BNW counterpart. We provide formalism for simulating large scale nanowire networks hinged upon experimentally measurable TE parameters of a single T-junction.
Starting from an independent-particle model with a finite and arbitrary set of single-particle energies, we develop an analytical approximation to the many-body level density $\rho_A(E)$ and to particle-hole densities. We use exact expressions for the low-order moments and cumulants to derive approximate expressions for the coefficients of an expansion of these densities in terms of orthogonal polynomials. The approach is asymptotically (mass number $A \gg 1$) convergent and, for large $A$, covers about 20 orders of magnitude near the maximum of $\rho_A(E)$ (i.e., about half the spectrum). Densities of accessible states are calculated using the Fermi-gas model.
The task of video and text sequence alignment is a prerequisite step toward joint understanding of movie videos and screenplays. However, supervised methods face the obstacle of limited realistic training data. With this paper, we attempt to enhance data efficiency of the end-to-end alignment network NeuMATCH [15]. Recent research [56] suggests that network components dealing with different modalities may overfit and generalize at different speeds, creating difficulties for training. We propose to employ (1) layer-wise adaptive rate scaling (LARS) to align the magnitudes of gradient updates in different layers and balance the pace of learning and (2) sequence-wise batch normalization (SBN) to align the internal feature distributions from different modalities. Finally, we leverage random projection to reduce the dimensionality of input features. On the YouTube Movie Summary dataset, the combined use of these technique closes the performance gap when the pretraining on the LSMDC dataset is omitted and achieves the state-of-the-art result. Extensive empirical comparisons and analysis reveal that these techniques improve optimization and regularize the network more effectively than two different setups of layer normalization.
Computing quantum state fidelity will be important to verify and characterize states prepared on a quantum computer. In this work, we propose novel lower and upper bounds for the fidelity $F(\rho,\sigma)$ based on the "truncated fidelity" $F(\rho_m, \sigma)$, which is evaluated for a state $\rho_m$ obtained by projecting $\rho$ onto its $m$-largest eigenvalues. Our bounds can be refined, i.e., they tighten monotonically with $m$. To compute our bounds, we introduce a hybrid quantum-classical algorithm, called Variational Quantum Fidelity Estimation, that involves three steps: (1) variationally diagonalize $\rho$, (2) compute matrix elements of $\sigma$ in the eigenbasis of $\rho$, and (3) combine these matrix elements to compute our bounds. Our algorithm is aimed at the case where $\sigma$ is arbitrary and $\rho$ is low rank, which we call low-rank fidelity estimation, and we prove that a classical algorithm cannot efficiently solve this problem. Finally, we demonstrate that our bounds can detect quantum phase transitions and are often tighter than previously known computable bounds for realistic situations.
Practical face recognition has been studied in the past decades, but still remains an open challenge. Current prevailing approaches have already achieved substantial breakthroughs in recognition accuracy. However, their performance usually drops dramatically if face samples are severely misaligned. To address this problem, we propose a highly efficient misalignment-robust locality-constrained representation (MRLR) algorithm for practical real-time face recognition. Specifically, the locality constraint that activates the most correlated atoms and suppresses the uncorrelated ones, is applied to construct the dictionary for face alignment. Then we simultaneously align the warped face and update the locality-constrained dictionary, eventually obtaining the final alignment. Moreover, we make use of the block structure to accelerate the derived analytical solution. Experimental results on public data sets show that MRLR significantly outperforms several state-of-the-art approaches in terms of efficiency and scalability with even better performance.
We present a non-perturbative approach to the problem of quasiparticles coupled to spin-fluctuations. If the fully dressed spin-fluctuation propagator is used in the Feynman graph expansion of the single-particle Green's function, the problem of summing all spin-fluctuation exchange graphs (i.e without virtual fermion loops) can be cast as a functional integral over gaussian distributed random vector fields. A Monte Carlo sampling of this functional integral does not suffer from the 'fermion sign problem' and offers an attractive alternative to perturbative calculations. We compare the results of our computer simulations with perturbation theory and self-consistent one-loop calculations.
A new recursive procedure of the calculation of partition numbers function $W(s,{\bf d}^m)$ is suggested. We find its zeroes and prove a lemma on the function parity properties. The explicit formulas of $W(s,{\bf d}^m)$ and their periods $\tau(G)$ for the irreducible Coxeter groups and a list for the first ten symmetric group ${\cal S}_m$ are presented. A {\it least common multiple} ${\cal L}(m)$ of the series of the natural numbers 1,2,..,$m$ plays a role of the period $\tau({\cal S}_m)$ of $W(s,{\bf d}^m)$ in ${\cal S}_m$. An asymptotic behaviour of ${\cal L}(m)$ with $m \to \infty$ is found.
We search for short-range Hamiltonians of finite spin-1 kagome systems, maximizing the overlaps with lattice Moore-Read states. Our starting point is an exact, long-range parent Hamiltonian for such a state on a finite plane, obtained from conformal field theory. A truncation procedure is applied to it, which retains only short-range terms and makes it easy to define the Hamiltonian on a torus. Finally, the remaining coefficients are optimized, to yield maximized overlaps between exact diagonalization results and model ground states. In the best cases, these overlaps exceed 0.9 and 0.8 for the three lowest states of 12- and 18-site systems, respectively, suggesting that the obtained Hamiltonians are good parent Hamiltonians for a non-Abelian topological order.
We present differential cross sections for Higgs boson and/or two-photon production from intermediate (virtual) Higgs boson within the formalism of $k_t$-factorization. Resulting distributions for two photons from the Higgs boson are compared with recent ATLAS collaboration data. In contrast to a recent calculation the leading order $g g \to H$ contribution is rather small compared to the ATLAS experimental data ($\gamma \gamma$ transverse momentum and rapidity distributions). We include also higher-order contribution $g g \to H (\to \gamma \gamma) g$, $g g \to g H g$ and the contribution of the $W^+ W^-$ and $Z^0 Z^0$ exchanges. The $gg\to Hg$ mechanism gives a similar contribution as the $gg\to H$ mechanism. We argue that there is almost no double counting when adding $gg\to H$ and $gg\to Hg$ contributions due to different topology of corresponding Feynman diagrams. The final sum is comparable with the ATLAS two-photon data.
Antiferroelectrics are promising materials for high energy density capacitors and the search for environmentally-friendly and efficient systems is actively pursued. An elegant strategy to create and design new (anti)ferroic system relies on the use of nanoscale superlattices. We report here the use of such strategy and the fabrication of nanoscale BiFeO3/NdFeO3 superlattices and in depth characterization using high resolution X-ray diffraction and Transmission Electron Microscopy. The structural analysis at atomic scale demonstrates that such superlattices host anti-polar ordering most likely described by an antiferroelectric-like Pbnm symmetry. Temperature dependence of anti-polar state and structural transition further hint that the stability of the anti-polar state is controlled by the BiFeO3 layer thickness within the stacking and, in a more moderate way, by interlayer strain. Discovery of such polar arrangement in superlattices and the possible generalization to the whole rare-earth family pave the way to new platforms for energy storage application as well as nano-electronic devices.
The $\eta$ Carinae binary system is the first $\gamma$-ray binary ever observed which does not contain a compact object. The dense wind of the primary star shocks against the fast light wind coming from the companion star, creating the conditions to accelerate particles up to relativistic energies via Fermi mechanisms. These relativistic particles subsequently dissipates non-thermal radiation. Fermi-LAT and H.E.S.S. detection of $\eta$ Carinae confirm such hypotheses. Hydrodynamic simulations provide a convincing match to the observations if a few percent of the wind mechanical energy dissipated in the shock goes into particle acceleration. The intrinsic $\pi^0$ decay spectrum is a complex convolution of the maximum energy, luminosity, particle drift and obscuration. Accelerated particles cool down mainly via inverse-Compton, synchrotron radiation, and photo-pion production. High-energy $\gamma$-rays interact also with the pool of anisotropic UV photons emitted by both luminous stars, creating $e^\pm$ pairs and strongly modifying the observed spectrum. Quick variations of the optical depth are expected along the orbit, due to changes in shape, position, and gas density of the shocked region. Various CTA simulations confirm that flux variabilities down to few days timescale could be detected above 30 GeV. These variations will disentangle the intrinsic particle spectral cut off from that related to $\gamma$-$\gamma$ opacity and determine the flux of relativistic protons and positrons injected in the interstellar medium, the geometry of the colliding wind region and the magnetic field configuration, as well as the geometrical orientation of the binary system. CTA will also enlighten the nature of the high-energy component, the mechanisms and the percentage of kinetic energy channelled into particle acceleration.
Quantum measurements play a fundamental role in quantum mechanics and quantum information processing, but it is not easy to implement generalized measurements, the most powerful measurements allowed by quantum mechanics. Here we propose a simple recipe for implementing generalized measurements on a qudit via quantum walks. With this recipe, any discrete quantum measurement can be implemented via a one-dimensional discrete quantum walk; the number of steps is only two times the number of measurement outcomes. As an illustration, we present a unified solution for implementing arbitrary symmetric informationally complete measurements in dimension 3.
Using orthogonal projections, we investigate distance of a given elasticity tensor to classes of elasticity tensors exhibiting particular material symmetries. These projections depend on the orientation of the elasticity tensor, hence the distance is obtained as the minimization of corresponding expressions with respect to the action of the orthogonal group. These expressions are stated in terms of the eigenvalues of both the given tensor and the projected one. The process of minimization is facilitated by the fact that, as we prove, the traces of the corresponding Voigt and dilatation tensors are invariant under these orthogonal projections. For isotropy, cubic symmetry and transverse isotropy, we formulate algorithms to find both the orientation and the eigenvalues of the elasticity tensor that is endowed with a particular symmetry and is closest to the given elasticity tensor.
We prove that the set of growth rates of permutation classes includes an infinite sequence of intervals whose infimum is $\theta_B\approx2.35526$, and that it also contains every value at least $\lambda_B\approx2.35698$. These results improve on a theorem of Vatter, who determined that there are permutation classes of every growth rate at least $\lambda_A\approx2.48187$. Thus, we also refute his conjecture that the set of growth rates below $\lambda_A$ is nowhere dense. Our proof is based upon an analysis of expansions of real numbers in non-integer bases, the study of which was initiated by R\'enyi in the 1950s. In particular, we prove two generalisations of a result of Pedicini concerning expansions in which the digits are drawn from sets of allowed values.
Detecting transparent objects in natural scenes is challenging due to the low contrast in texture, brightness and colors. Recent deep-learning-based works reveal that it is effective to leverage boundaries for transparent object detection (TOD). However, these methods usually encounter boundary-related imbalance problem, leading to limited generation capability. Detailly, a kind of boundaries in the background, which share the same characteristics with boundaries of transparent objects but have much smaller amounts, usually hurt the performance. To conquer the boundary-related imbalance problem, we propose a novel content-dependent data augmentation method termed FakeMix. Considering collecting these trouble-maker boundaries in the background is hard without corresponding annotations, we elaborately generate them by appending the boundaries of transparent objects from other samples into the current image during training, which adjusts the data space and improves the generalization of the models. Further, we present AdaptiveASPP, an enhanced version of ASPP, that can capture multi-scale and cross-modality features dynamically. Extensive experiments demonstrate that our methods clearly outperform the state-of-the-art methods. We also show that our approach can also transfer well on related tasks, in which the model meets similar troubles, such as mirror detection, glass detection, and camouflaged object detection. Code will be made publicly available.
We develop in detail a model of the charge order in NbSe$_2$ deriving from a strong electron-phonon coupling dependent on the ingoing and outgoing electron momenta as well as the electronic orbitals scattered between. Including both dependencies allows us to reproduce the full range of available experimental observations on this material. The stability of both experimentally-observed charge-ordered geometries (1Q and 3Q) is studied within this model as a function of temperature and uniaxial strain. It is found that a small amount of bulk strain suffices to stabilize the unidirectional order, and that in both ordering geometries, lattice fluctuations arising from the strong electron-phonon coupling act to suppress the onset temperature of charge order, giving a pseudogap regime characterized by local order and strong phase fluctuations.
We show that arbitrarily small antisymmetric perturbations of the zero function are sufficient to produce the stickiness phenomenon for planar nonlocal minimal graphs (with the same quantitative bounds obtained for the case of even symmetric perturbations, up to multiplicative constants).   In proving this result, one also establishes an odd symmetric version of the maximum principle for nonlocal minimal graphs, according to which the odd symmetric minimizer is positive in the direction of the positive bump and negative in the direction of the negative bump.
We establish bounds on the spectral radii for a large class of sparse random matrices, which includes the adjacency matrices of inhomogeneous Erd\H{o}s-R\'enyi graphs. Our error bounds are sharp for a large class of sparse random matrices. In particular, for the Erd\H{o}s-R\'enyi graph $G(n,d/n)$, our results imply that the smallest and second-largest eigenvalues of the adjacency matrix converge to the edges of the support of the asymptotic eigenvalue distribution provided that $d \gg \log n$. Together with the companion paper [3], where we analyse the extreme eigenvalues in the complementary regime $d \ll \log n$, this establishes a crossover in the behaviour of the extreme eigenvalues around $d \sim \log n$. Our results also apply to non-Hermitian sparse random matrices, corresponding to adjacency matrices of directed graphs. The proof combines (i) a new inequality between the spectral radius of a matrix and the spectral radius of its nonbacktracking version together with (ii) a new application of the method of moments for nonbacktracking matrices.
Anomalies near the conductance threshold of nearly perfect semiconductor quantum wires are explained in terms of singlet and triplet resonances of conduction electrons with a single weakly-bound electron in the wire. This is shown to be a universal effect for a wide range of situations in which the effective single-electron confinement is weak. The robustness of this generic behavior is investigated numerically for a wide range of shapes and sizes of cylindrical wires with a bulge. The dependence on gate voltage, source-drain voltage and magnetic field is discussed within the framework of an extended Hubbard model. This model is mapped onto an extended Anderson model, which in the limit of low temperatures is expected to lead to Kondo resonance physics and pronounced many-body effects.