ShantanuT01/DACTYL-Pretraining huggingface dataset:
The dynamic heat transfer between two half-spaces separated by a vacuum gap due to coupling of their surface modes is modelled using the theory that describes the dynamic energy transfer between two coupled harmonic oscillators each separately connected to a heat bath and with the heat baths maintained at different temperatures. The theory is applied for the case when the two surfaces are made up of a polar crystal which supports surface polaritons that can be excited at room temperature and the predicted heat transfer is compared with the steady state heat transfer value calculated from standard fluctuational electrodynamics theory. It is observed that for small time intervals the value of heat flux can reach as high as 1.5 times that of steady state value.
We have observed 433 z<=0.08 brightest cluster galaxies (BCGs) in a full-sky survey of Abell clusters. The BCG Hubble diagram is consistent to within 2% of a Omega_m=0.3, Lambda=0.7 Hubble relation. The L_m-alpha relation for BCGs, which uses alpha, the log-slope of the BCG photometric curve of growth, to predict metric luminosity, L_m, has 0.27 mag residuals. We measure central stellar velocity dispersions, sigma, of the BCGs, finding the Faber-Jackson relation to flatten as the metric aperture grows to include an increasing fraction of the total BCG luminosity. A 3-parameter "metric plane" relation using alpha and sigma together gives the best prediction of L_m, with 0.21 mag residuals. The projected spatial offset, r_x, of BCGs from the X-ray-defined cluster center is a gamma=-2.33 power-law over 1<r_x<10^3 kpc. The median offset is ~10 kpc, but ~15% of the BCGs have r_x>100 kpc. The absolute cluster-dispersion normalized BCG peculiar velocity |Delta V_1|/sigma_c follows an exponential distribution with scale length 0.39+/-0.03. Both L_m and alpha increase with sigma_c. The alpha parameter is further moderated by both the spatial and velocity offset from the cluster center, with larger alpha correlated with the proximity of the BCG to the cluster mean velocity or potential center. At the same time, position in the cluster has little effect on L_m. The luminosity difference between the BCG and second-ranked galaxy, M2, increases as the peculiar velocity of the BCG within the cluster decreases. Further, when M2 is a close luminosity "rival" of the BCG, the galaxy that is closest to either the velocity or X-ray center of the cluster is most likely to have the larger alpha. We conclude that the inner portions of the BCGs are formed outside the cluster, but interactions in the heart of the galaxy cluster grow and extend the envelopes of the BCGs.
Certain aspects of the behaviour of the gravitational field near null and spatial infinity for the developments of asymptotically Euclidean, conformally flat initial data sets are analysed. Ideas and results from two different approaches are combined: on the one hand the null infinity formalism related to the asymptotic characteristic initial value problem and on the other the regular Cauchy initial value problem at spatial infinity which uses Friedrich's representation of spatial infinity as a cylinder. The decay of the Weyl tensor for the developments of the class of initial data under consideration is analysed under some existence and regularity assumptions for the asymptotic expansions obtained using the cylinder at spatial infinity. Conditions on the initial data to obtain developments satisfying the Peeling Behaviour are identified. Further, the decay of the asymptotic shear on null infinity is also examined as one approaches spatial infinity. This decay is related to the possibility of selecting the Poincar\'e group out of the BMS group in a canonical fashion. It is found that for the class of initial data under consideration, if the development peels, then the asymptotic shear goes to zero at spatial infinity. Expansions of the Bondi mass are also examined. Finally, the Newman-Penrose constants of the spacetime are written in terms of initial data quantities and it is shown that the constants defined at future null infinity are equal to those at past null infinity.
We study electron-positron pair production in polar caps of energetic pulsars to determine the maximum multiplicity of pair plasma a pulsar can produce under the most favorable conditions. This paper complements and updates our study of pair cascades presented in Timokhin & Harding (2015) with more accurate treatment of the effects of ultra strong B>3x10^{12}G magnetic fields and emission processes of primary and secondary particles. We include pairs produced by curvature and synchrotron radiation photons as well as resonant Compton scattered photons. We develop a semi-analytical model of electron-positrons cascades which can efficiently simulate pair cascades with an arbitrary number of microphysical processes and use it to explore cascade properties for a wide range of pulsar parameters. We argue that the maximum cascade multiplicity can not exceed ~ a few x 10^5 and the multiplicity has a rather weak dependence on pulsar period on pulsar period. The highest multiplicity is achieved in pulsars with magnetic field 4x10^{12}<B<10^{13}G and hot surfaces, with T>10^6K. We also derive analytical expressions for several physical quantities relevant for electromagnetic cascade in pulsars which may be useful in future works on pulsar cascades, including the upper limit on cascade multiplicity and various approximations for the parameter \chi, the exponential factor in the expression for photon attenuation in strong magnetic field.
Considering $\mathbb{Z}_n$ the ring of integers modulo $n$, the classical Fermat-Euler theorem establishes the existence of a specific natural number $\varphi(n)$ satisfying the following property: $ x^{\varphi(n)}=1%\hspace{1.0cm}\text{for all}\hspace{0.2cm}x\in \mathbb{Z}_n^*, $ for all $x$ belonging to the group of units of $\mathbb{Z}_n$. In this manuscript, this result is extended to a class of rings that satisfies some mild conditions.
Image-to-image translation has been revolutionized with GAN-based methods. However, existing methods lack the ability to preserve the identity of the source domain. As a result, synthesized images can often over-adapt to the reference domain, losing important structural characteristics and suffering from suboptimal visual quality. To solve these challenges, we propose a novel frequency domain image translation (FDIT) framework, exploiting frequency information for enhancing the image generation process. Our key idea is to decompose the image into low-frequency and high-frequency components, where the high-frequency feature captures object structure akin to the identity. Our training objective facilitates the preservation of frequency information in both pixel space and Fourier spectral space. We broadly evaluate FDIT across five large-scale datasets and multiple tasks including image translation and GAN inversion. Extensive experiments and ablations show that FDIT effectively preserves the identity of the source image, and produces photo-realistic images. FDIT establishes state-of-the-art performance, reducing the average FID score by 5.6% compared to the previous best method.
We address two-level systems arranged in ring configurations affected by static disorder. In particular we investigate the role of dephasing in the transport of an excitation along the ring. We compare the efficiency of the transfer process on isotropic rings and on biomimetic rings modelled according to the structure of light-harvesting complexes. Our analysis provides a simple but clear and interesting example of how an interplay between the coherent dynamics of the system and the incoherent action of the environment can enhance the transfer capabilities of disordered lattices.
The Dzyaloshinskii-Moriya interaction (DMI), which only exists in noncentrosymmetric systems, is responsible for the formation of exotic chiral magnetic states. The absence of DMI in most two-dimensional (2D) magnetic materials is due to their intrinsic inversion symmetry. Here, using first-principles calculations, we demonstrate that significant DMI can be obtained in a series of Janus monolayers of manganese dichalcogenides MnXY in which the difference between X and Y on the opposites sides of Mn breaks the inversion symmetry. In particular, the DMI amplitudes of MnSeTe and MnSTe are comparable to those of state-of-the-art ferromagnet/heavy metal (FM/HM) heterostructures. In addition, by performing Monte Carlo simulations, we find that at low temperatures the ground states of the MnSeTe and MnSTe monolayers can transform from ferromagnetic states with worm-like magnetic domains into the skyrmion states by applying external magnetic field. At increasing temperature, the skyrmion states starts fluctuating above 50 K before an evolution to a completely disordered structure at higher temperature. The present results pave the way for new device concepts utilizing chiral magnetic structures in specially designed 2D ferromagnetic materials.
We address the challenging task of anticipating human-object interaction in first person videos. Most existing methods ignore how the camera wearer interacts with the objects, or simply consider body motion as a separate modality. In contrast, we observe that the international hand movement reveals critical information about the future activity. Motivated by this, we adopt intentional hand movement as a future representation and propose a novel deep network that jointly models and predicts the egocentric hand motion, interaction hotspots and future action. Specifically, we consider the future hand motion as the motor attention, and model this attention using latent variables in our deep model. The predicted motor attention is further used to characterise the discriminative spatial-temporal visual features for predicting actions and interaction hotspots. We present extensive experiments demonstrating the benefit of the proposed joint model. Importantly, our model produces new state-of-the-art results for action anticipation on both EGTEA Gaze+ and the EPIC-Kitchens datasets. Our project page is available at https://aptx4869lm.github.io/ForecastingHOI/
Energetic electrons of up to tens of MeV are created during explosive phenomena in the solar corona. While many theoretical models consider magnetic reconnection as a possible way of generating energetic electrons, the precise roles of magnetic reconnection during acceleration and heating of electrons still remain unclear. Here we show from 2D particle-in-cell simulations that coalescence of magnetic islands that naturally form as a consequence of tearing mode instability and associated magnetic reconnection leads to efficient energization of electrons. The key process is the secondary magnetic reconnection at the merging points, or the `anti-reconnection', which is, in a sense, driven by the converging outflows from the initial magnetic reconnection regions. By following the trajectories of the most energetic electrons, we found a variety of different acceleration mechanisms but the energization at the anti-reconnection is found to be the most important process. We discuss possible applications to the energetic electrons observed in the solar flares. We anticipate our results to be a starting point for more sophisticated models of particle acceleration during the explosive energy release phenomena.
We study the evolution of cooperation in an interacting particle system with two types. The model we investigate is an extension of a two-type biased voter model. One type (called defector) has a (positive) bias $\alpha$ with respect to the other type (called cooperator). However, a cooperator helps a neighbor (either defector or cooperator) to reproduce at rate $\gamma$. We prove that the one-dimensional nearest-neighbor interacting dynamical system exhibits a phase transition at $\alpha=\gamma$. For $\alpha>\gamma$ cooperators always die out, but if $\gamma>\alpha$, cooperation is the winning strategy.
To investigate the Hall resistivity rH of systems with non-trivial spin structures, transport and magnetic properties of the oxygen deficient perovskite system TbBaCo2O5.53 with non-trivial magnetic structures have been adopted. As has been already known, the system exhibits, with decreasing temperature T, a transition to a ferromagnetic (FM) phase with non-collinear magnetic structure at TC 280 K in zero magnetic field and with further decreasing T, the spontaneous magnetization begins to decrease at T1~260 K and becomes zero at TN 245 K, where an antiferromagnetic (AFM) phase with non-collinear magnetic structure is realized. The metamagnetic behavior is induced by the relatively small magnetic field H (< 5 T) in the T region between ~200 K and T1. In this T region, unusual H dependence of rH has been observed. By analyzing the observed rH and magnetization M, the H dependence of the anomalous Hall coefficients Rs has been obtained at various fixed temperatures. Based on the magnetic structure reported previously by our group, the possible relevance of the non-trivial magnetic structure to the observed unusual behavior of rH is pointed out.
We have introduced coherent state neutral pion into Antisymmetrized Molecular Dynamics. With the aid of coherent state technique, it becomes possible to calculate transition matrix elements of the pion field operator and to study excited states containing pions. For large pion-nucleon coupling fpiN > 1.6, pions have a finite expectation value and bring large energy gain in 12C. We discuss two aspects of pionic effects in spectroscopy; the LS interaction like effect and the mixing of different nucleon parity states, which would modify low energy nuclear levels.
Modern deep neural network models are large and computationally intensive. One typical solution to this issue is model pruning. However, most current pruning algorithms depend on hand crafted rules or domain expertise. To overcome this problem, we propose a learning based auto pruning algorithm for deep neural network, which is inspired by recent automatic machine learning(AutoML). A two objectives' problem that aims for the the weights and the best channels for each layer is first formulated. An alternative optimization approach is then proposed to derive the optimal channel numbers and weights simultaneously. In the process of pruning, we utilize a searchable hyperparameter, remaining ratio, to denote the number of channels in each convolution layer, and then a dynamic masking process is proposed to describe the corresponding channel evolution. To control the trade-off between the accuracy of a model and the pruning ratio of floating point operations, a novel loss function is further introduced. Preliminary experimental results on benchmark datasets demonstrate that our scheme achieves competitive results for neural network pruning.
We present a spectroscopic study of D461, a giant star belonging to Draco dwarf spheroidal galaxy. From spectral synthesis in LTE we derive a lithium abundance of log e(Li)=3.5+/-0.4 and a C/O ratio between 3 and 5. This is the first detection of a lithium rich C-star in a dwarf spheroidal galaxy. Basing on stellar models of appropriate chemical composition, we show that a similar C enrichment is compatible with that expectedfor a low mass low metallicity thermally pulsing AGB star, undergoing few third dredge up episodes. The position in the log g-log Teff diagram of D461 is also compatible with this theoretical scenario. In particular, the low effective temperature, lower than that expected for a low metallicity giant star, is a consequence of the huge increase of the envelope opacity occurring after the carbon dredge up. The Li enrichment may be explained if a deep circulation would take place during the interpulse period, the so called cool bottom process. In spite of the low resolution of our spectra, we derive a lower limit for the carbon isotopic ratio, namely 12C/13C>40, and a constraint for the Ba abundance, namely 0.5<[Ba/Fe]< 2. The proposed scenario also fits these further constraints. Then, we estimate that the mass of D461 ranges between 1.2 and 2 $M_\odot$, which corresponds to an age ranging between 1 and 3 Gyr. We conclude that this star is more massive and younger than the typical stellar population of Draco.
We consider a range of "theories" that violate the uncertainty relation for anti-commuting observables derived in [JMP, 49, 062105 (2008)]. We first show that Tsirelson's bound for the CHSH inequality can be derived from this uncertainty relation, and that relaxing this relation allows for non-local correlations that are stronger than what can be obtained in quantum mechanics. We continue to construct a hierarchy of related non-signaling theories, and show that on one hand they admit superstrong random access encodings and exponential savings for a particular communication problem, while on the other hand it becomes much harder in these theories to learn a state. We show that the existence of these effects stems from the absence of certain constraints on the expectation values of commuting measurements from our non-signaling theories that are present in quantum theory.
A large deviation technique is used to calculate the microcanonical entropy function s(v,m) of the mean-field phi^4-model as a function of the potential energy v and the magnetization m. As in the canonical ensemble, a continuous phase transition is found. An analytical expression is obtained for the critical energy v_c(J) as a function of the coupling parameter J.
We present a detailed investigation of the impact of astrophysical processes on the shape and amplitude of the kinetic Sunyaev-Zel'dovich (kSZ) power spectrum from the post-reionization epoch. This is achieved by constructing a new model of the kSZ power spectrum which we calibrate to the results of hydrodynamic simulations. By construction, our method accounts for all relevant density and velocity modes and so is unaffected by the limited box size of our simulations. We find that radiative cooling and star-formation can reduce the amplitude of the kSZ power spectrum by up to 33%, or 1 uK^2 at ell = 3000. This is driven by a decrease in the mean gas density in groups and clusters due to the conversion of gas into stars. Variations in the redshifts at which helium reionization occurs can effect the amplitude by a similar fraction, while current constraints on cosmological parameters (namely sigma_8) translate to a further +-15% uncertainty on the kSZ power spectrum. We demonstrate how the models presented in this work can be constrained -- reducing the astrophysical uncertainty on the kSZ signal -- by measuring the redshift dependence of the signal via kSZ tomography. Finally, we discuss how the results of this work can help constrain the duration of reionization via measurements of the kinetic SZ signal sourced by inhomogeneous (or patchy) reionization.
We study various measures of irrationality for hypersurfaces of large degree in projective space and other varieties. These include the least degree of a rational covering of projective space, and the minimal gonality of a covering family of curves. The theme is that positivity properties of canonical bundles lead to lower bounds on these invariants. In particular, we prove that if X is a very general smooth hypersurface of dimension n and degree d \ge 2n+1, then any dominant rational mapping from X to projective n-space must have degree at least d-1. We also propose a number of open problems, and we show how our methods lead to simple new proofs of results of Ran and Beheshti-Eisenbud.
We have tested the two main theoretical models of bubbles around massive star clusters, Castor et al. and Chevalier & Clegg, against observations of the well studied Carina Nebula. The Castor et al. theory over-predicts the X-ray luminosity in the Carina bubble by a factor of 60 and expands too rapidly, by a factor of 4; if the correct radius and age are used, the predicted X-ray luminosity is even larger. In contrast, the Chevalier & Clegg model under-predicts the X-ray luminosity by a factor of 10. We modify the Castor et al. theory to take into account lower stellar wind mass loss rates, radiation pressure, gravity, and escape of or energy loss from the hot shocked gas. We argue that energy is advected rather than radiated from the bubble. We undertake a parameter study for reduced stellar mass loss rates and for various leakage rates and are able to find viable models. The X-ray surface brightness in Carina is highest close to the bubble wall, which is consistent with conductive evaporation from cold clouds. The picture that emerges is one in which the hot gas pressure is far below that found by dividing the time-integrated wind luminosity by the bubble volume; rather, the pressure in the hot gas is set by pressure equilibrium with the photoionized gas at T=10^4 K. It follows that the shocked stellar winds are not dynamically important in forming the bubbles.
The definition of the amplituhedron in terms of sign flips involves both one-loop constraints and the "mutual positivity" constraint. To gain an understanding of the all-loop integrand of $\mathcal{N}=4$ sYM requires understanding the crucial role played by mutual positivity. This paper is an attempt towards developing a procedure to introduce the complexities of mutual positivity in a systematic and controlled manner. As the first step in this procedure, we trivialize these constraints and understand the geometry underlying the remaining constraints to all loops and multiplicities. We present a host of configurations which correspond to various faces of the amplituhedron. The results we derive are valid at all multiplicities and loop orders for the maximally helicity violating (MHV) configurations. These include detailed derivations for the results in arXiv:1810.08208 [hep-th]. We conclude by indicating how one might move beyond trivial mutual positivity by presenting a series of configuration which re-introduce it bit by bit.
Deep learning has recently achieved remarkable performance in image classification tasks, which depends heavily on massive annotation. However, the classification mechanism of existing deep learning models seems to contrast to humans' recognition mechanism. With only a glance at an image of the object even unknown type, humans can quickly and precisely find other same category objects from massive images, which benefits from daily recognition of various objects. In this paper, we attempt to build a generalizable framework that emulates the humans' recognition mechanism in the image classification task, hoping to improve the classification performance on unseen categories with the support of annotations of other categories. Specifically, we investigate a new task termed Comparison Knowledge Translation (CKT). Given a set of fully labeled categories, CKT aims to translate the comparison knowledge learned from the labeled categories to a set of novel categories. To this end, we put forward a Comparison Classification Translation Network (CCT-Net), which comprises a comparison classifier and a matching discriminator. The comparison classifier is devised to classify whether two images belong to the same category or not, while the matching discriminator works together in an adversarial manner to ensure whether classified results match the truth. Exhaustive experiments show that CCT-Net achieves surprising generalization ability on unseen categories and SOTA performance on target categories.
We discuss a new analytic solution to the Einstein-Maxwell field equations that describes electrically charged black holes with a slow rotation and with a single angular momentum in all higher dimensions. We also compute the gyromagnetic ratio of these black holes.