ShantanuT01/DACTYL-Pretraining huggingface dataset:
The double-exchange (DE) interaction, that is, a ferromagnetic (FM) interaction due to a combination of electron motion and the Hund coupling, is a well known source of a wide class of FM orders. Here, we show that the DE interaction in highly photoexcited states is antiferromagnetic (AFM). Transient dynamics of quantum electrons coupled with classical spins are analyzed. An ac field applied to a metallic FM state results in an almost perfect N\'eel state. A time characterizing the FM-to-AFM conversion is scaled by light amplitude and frequency. This hidden AFM interaction is attributable to the electron-spin coupling under nonequilibrium electron distribution.
The single glitch observed in PSR B1821-24, a millisecond pulsar in M28, is unusual on two counts. First, the magnitude of this glitch is at least an order of magnitude smaller ($\Delta \nu / \nu \sim 10^{-11}$) than the smallest glitch observed to date. Secondly, all other glitching pulsars have strong magnetic fields with $B \gsim 10^{11} G$ and are young, whereas PSR B1821-24 is an old recycled pulsar with a field strength of $2.25\times10^9 G$. We have suggested earlier that some of the recycled pulsars could actually be strange quark stars. In this work we argue that the crustal properties of such a {\em strange} pulsar are just right to give rise to a glitch of this magnitude, explaining the scarcity of larger glitches in millisecond pulsars.
We present a detailed analysis of spectra and other observables for the entire chain of Zr isotopes, from neutron number 52 to 70, in the framework of the interacting boson model with configuration mixing. The results suggest a remarkable interplay of multiple quantum phase transitions (QPTs). One type of QPT involves an abrupt crossing of normal and intruder configurations, superimposed on a second type of QPT involving gradual shape-changes within each configuration.
The late universe contains a wealth of information about fundamental physics and gravity, wrapped up in non-Gaussian fields. To make use of as much information as possible it is necessary to go beyond two-point statistics. Rather than going to higher order N-point correlation functions, we demonstrate that the probability distribution function (PDF) of spheres in the matter field (a one-point function) already contains a significant amount of this non-Gaussian information. The matter PDF dissects different density environments which are lumped together in two-point statistics, making it particularly useful for probing modifications of gravity or expansion history. Our approach in Cataneo et. al. 2021 extends the success of Large Deviation Theory for predicting the matter PDF in $\Lambda$CDM in these ''extended'' cosmologies. A Fisher forecast demonstrates the information content in the matter PDF via constraints for a Euclid-like survey volume combining the 3D matter PDF with the 3D matter power spectrum. Adding the matter PDF halves the uncertainties on parameters in an evolving dark energy model, relative to the power spectrum alone. Additionally, the matter PDF contains enough non-linear information to substantially increase the detection significance of departures from General Relativity, with improvements up to six times the power spectrum alone. This analysis demonstrates that the matter PDF is a promising non-Gaussian statistic for extracting cosmological information, particularly for beyond $\Lambda$CDM models.
We have made extensive spectroscopic and photometric observations of PG 1224+309, a close binary containing a DA white dwarf primary and an M4+ secondary. The H alpha line is in emission due to irradiation of the M-star by the hot white dwarf and is seen to vary around the orbit. From the radial velocities of the H alpha line we derive a period of P = 0.258689 +/- 0.000004 days and a semi-amplitude of K_Halpha = 160 +/- 8 km/s. We estimate a correction Delta_K = 21 +/- 2 km/s, where K_M = K_Halpha + Delta_K. Radial velocity variations of the white dwarf reveal a semi-amplitude of K_WD = 112 +/- 14 km/s. The blue spectrum of the white dwarf is well fit by a synthetic spectrum having T_eff = 29,300 K and log(g) = 7.38. The white dwarf contributes 97% of the light at 4500 Angstroms and virtually all of the light blueward of 3800 Angstroms. No eclipses are observed. The mass inferred for the white dwarf depends on the assumed mass of the thin residual hydrogen envelope: 0.40 < M_WD < 0.45 solar masses for hydrogen envelope masses of 0 < M_H < 4.0E-4 solar masses. We argue that the mass of the white dwarf is closer to 0.45 solar masses, hence it appears that the white dwarf has a relatively large residual hydrogen envelope. The mass of the M-star is then M_M = 0.28 +/- 0.05 solar masses, and the inclination is i = 77 +/- 7 degrees. We discuss briefly how PG 1224+309 may be used to constrain theories of close binary star evolution, and the past and future histories of PG 1224+309 itself. The star is both a ``post-common envelope'' star and a ``pre-cataclysmic binary'' star. Mass transfer by Roche-lobe overflow should commence in about 10 Gyr.
Given two graphs $G$ and $H$, we investigate for which functions $p=p(n)$ the random graph $G_{n,p}$ (the binomial random graph on $n$ vertices with edge probability $p$) satisfies with probability $1-o(1)$ that every red-blue-coloring of its edges contains a red copy of $G$ or a blue copy of $H$. We prove a general upper bound on the threshold for this property under the assumption that the denser of the two graphs satisfies a certain balancedness condition. Our result partially confirms a conjecture by the first author and Kreuter, and together with earlier lower bound results establishes the exact order of magnitude of the threshold for the case in which $G$ and $H$ are complete graphs of arbitrary size.   In our proof we present an alternative to the so-called deletion method, which was introduced by R\"odl and Ruci\'{n}ski in their study of symmetric Ramsey properties of random graphs (i.e. the case $G=H$), and has been used in many proofs of similar results since then.
We investigate the ambiguities in the Fock quantization of the scalar perturbations of a Friedmann-Lema\^{i}tre-Robertson-Walker model with a massive scalar field as matter content. We consider the case of compact spatial sections (thus avoiding infrared divergences), with the topology of a three-sphere. After expanding the perturbations in series of eigenfunctions of the Laplace-Beltrami operator, the Hamiltonian of the system is written up to quadratic order in them. We fix the gauge of the local degrees of freedom in two different ways, reaching in both cases the same qualitative results. A canonical transformation, which includes the scaling of the matter field perturbations by the scale factor of the geometry, is performed in order to arrive at a convenient formulation of the system. We then study the quantization of these perturbations in the classical background determined by the homogeneous variables. Based on previous work, we introduce a Fock representation for the perturbations in which: (a) the complex structure is invariant under the isometries of the spatial sections and (b) the field dynamics is implemented as a unitary operator. These two properties select not only a unique unitary equivalence class of representations, but also a preferred field description, picking up a canonical pair of field variables among all those that can be obtained by means of a time-dependent scaling of the matter field (completed into a linear canonical transformation). Finally, we present an equivalent quantization constructed in terms of gauge-invariant quantities. We prove that this quantization can be attained by a mode-by-mode time-dependent linear canonical transformation which admits a unitary implementation, so that it is also uniquely determined.
In this work the INTEGRAL hard X-ray selected sample of AGN has been used to investigate the possible contribution of absorbing material distributed within the host galaxies to the total amount of NH measured in the X-ray band. We collected all the available axial ratio measurements of the galaxies hosting our AGN together with their morphological information and find that also for our hard X-ray selected sample a deficit of edge-on galaxies hosting type 1 AGN is present. We estimate that in our hard X-ray selected sample there is a deficit of 24% (+/- 5%) of type 1 AGN. Possible bias in redshift has been excluded, as we found the same effect in a well determined range of z where the number and the distributions of the two classes are statistically the same. Our findings clearly indicate that material located in the host galaxy on scales of hundreds of parsecs and not aligned with the putative absorbing torus of the AGN can contribute to the total amount of column density. This galactic absorber can be large enough to hide the broad line region of some type 1 AGN causing their classification as type 2 objects and giving rise to the deficiency of type 1 in edge-on galaxies.
Let $n, s$ be positive integers such that $n$ is sufficiently large and $s\le n/3$. Suppose $H$ is a 3-uniform hypergraph of order $n$. If $H$ contains no isolated vertex and $deg(u)+ deg(v) > 2(s-1)(n-1)$ for any two vertices $u$ and $v$ that are contained in some edge of $H$, then $H$ contains a matching of size $s$. This degree sum condition is best possible and confirms a conjecture of the authors [Electron. J. Combin. 25 (3), 2018], who proved the case when $s= n/3$.
Recent developments in machine learning and signal processing have resulted in many new techniques that are able to effectively capture the intrinsic yet complex properties of hyperspectral imagery. Tasks ranging from anomaly detection to classification can now be solved by taking advantage of very efficient algorithms which have their roots in representation theory and in computational approximation. Time-frequency methods are one example of such techniques. They provide means to analyze and extract the spectral content from data. On the other hand, hierarchical methods such as neural networks incorporate spatial information across scales and model multiple levels of dependencies between spectral features. Both of these approaches have recently been proven to provide significant advances in the spectral-spatial classification of hyperspectral imagery. The 3D Fourier scattering transform, which is introduced in this paper, is an amalgamation of time-frequency representations with neural network architectures. It leverages the benefits provided by the Short-Time Fourier Transform with the numerical efficiency of deep learning network structures. We test the proposed method on several standard hyperspectral datasets, and we present results that indicate that the 3D Fourier scattering transform is highly effective at representing spectral content when compared with other state-of-the-art spectral-spatial classification methods.
For the understanding of the origin and propagation of ultra-high energy cosmic rays (UHECR) we developed a new approach to simulating UHECRs from an arbitrary number of sources based on Monte Carlo technique. The method consists of a combination of three steps. For distant sources we apply commonly accepted parameterizations to calculate the contribution to the observed cosmic ray flux. For sources of the local universe we use forward tracking through realistic matter distributions and magnetic fields resulting from explicit simulations of large-scale structure formation. From the calculations and the forward tracking we generate maps of the probability to observe a particle with a given energy from a discrete direction. To account for deflections in the galactic field, these probability maps are transformed by matrices calculated from backtracking of antiparticles through field parameterizations. Based on the combined probability maps, Monte Carlo production of individual UHECR data is performed which are then used in comparisons with UHECR measurements. The simulated UHECR data serves for optimizing the analysis techniques used in UHECR measurements as well as for constraining the parameter space of the underlying source and magnetic field models.
The paper analyzes the problem fixing the local fermionic gauge symmetry in the Green-Schwarz superstring theory,related to the covariant quantization of this theory.The gauge-fixing procedure reveals the connection between GS and NSR formalisms, conjectured earlier. The analysis relates the kappa-invariance to the Bogomol'ny-type condition,well-known in connection with D-brane theories. The BPS saturation condition appears to be a target space superpartner of the kappa-invariance condition. Relation to RR charges of p-brane solutions of the ten-dimensional supergravity is discussed.
PbTe is a semiconductor with promising properties for topological quantum computing applications. Here we characterize quantum dots in PbTe nanowires selectively grown on InP. Charge stability diagrams at zero magnetic field reveal large even-odd spacing between Coulomb blockade peaks, charging energies below 140$~\mathrm{\mu eV}$ and Kondo peaks in odd Coulomb diamonds. We attribute the large even-odd spacing to the large dielectric constant and small effective electron mass of PbTe. By studying the Zeeman-induced level and Kondo splitting in finite magnetic fields, we extract the electron $g$-factor as a function of magnetic field direction. We find the $g$-factor tensor to be highly anisotropic, with principal $g$-factors ranging from 0.9 to 22.4, and to depend on the electronic configuration of the devices. These results indicate strong Rashba spin-orbit interaction in our PbTe quantum dots.
Compressive Learning is an emerging topic that combines signal acquisition via compressive sensing and machine learning to perform inference tasks directly on a small number of measurements. Many data modalities naturally have a multi-dimensional or tensorial format, with each dimension or tensor mode representing different features such as the spatial and temporal information in video sequences or the spatial and spectral information in hyperspectral images. However, in existing compressive learning frameworks, the compressive sensing component utilizes either random or learned linear projection on the vectorized signal to perform signal acquisition, thus discarding the multi-dimensional structure of the signals. In this paper, we propose Multilinear Compressive Learning, a framework that takes into account the tensorial nature of multi-dimensional signals in the acquisition step and builds the subsequent inference model on the structurally sensed measurements. Our theoretical complexity analysis shows that the proposed framework is more efficient compared to its vector-based counterpart in both memory and computation requirement. With extensive experiments, we also empirically show that our Multilinear Compressive Learning framework outperforms the vector-based framework in object classification and face recognition tasks, and scales favorably when the dimensionalities of the original signals increase, making it highly efficient for high-dimensional multi-dimensional signals.
We report a Raman study of the so-called buffer layer with $(6\sqrt3\times6\sqrt3)R30^{\circ}$ periodicity which forms the intrinsic interface structure between epitaxial graphene and SiC(0001). We show that this interface structure leads to a nonvanishing signal in the Raman spectrum at frequencies in the range of the D- and G-band of graphene and discuss its shape and intensity. Ab-initio phonon calculations reveal that these features can be attributed to the vibrational density of states of the buffer-layer.
We study the Picard variety of the Fano surface of nodal and mildly cuspidal cubic threefolds in arbitrary characteristic by relating divisors on the Fano surface to divisors on the symmetric product of a curve of genus 4.
By stacking PbTe layers there is a non-monotonic topological phase transition as a function of the number of monolayers. Based on first principles calculations we find that the proper stacked crystal symmetry determines the topological nature of the slab. While a single PbTe monolayer has a nontrivial phase, pressure can induce topological phase transition in bulk PbTe. Between these two limits, where finite size effects are inherent, we verified that, by applying an external pressure, odd stacking layers can be tuned easily to a topological phase, while even stacking keeps a larger band gap, avoiding band inversion. The quite distinct behavior for odd/even layer is due to the symmetry of the finite stacking. Odd layers preserve the bulk symmorphic symmetry with strong surface hybridization, while even layers belong to a nonsymmorphic group symmetry. Nonsymmorphism induces extra degeneracy reducing the hybridization, thus protecting band inversion, postponing topological phase transitions.
In this Letter we explore the effects of the scattering of photons incident on a dark matter halo through their interaction with either electrons or photons produced by dark matter annihilation. Particularly, we examine the effects of this scattering upon the observed spectrum of a distant AGN or of the Cosmic Microwave Background. Our results indicate that ultra-compact mini halos and other dense dark matter clumps can induce an observable Comptonisation of AGN spectra as well as a Sunyaev-Zel'dovich effect (SZE) with an optical depth similar to that attained by thermal electrons in the Coma cluster. The rate of encounters between a distant AGN and these dense mini-halos is also estimated using micro-lensing limits existing on the population of dark compact bodies.
We study the temperature dependence of the single particle spectral function as well as of the dynamical spin and charge structure factors for the one-dimensional Hubbard model using the finite temperature auxiliary field quantum Monte Carlo algorithm. The parameters of our simulations are chosen so to at best describe the low temperature photoemission spectra of the organic conductor TTF-TCNQ. Defining a magnetic energy scale, T_J, which marks the onset of short ranged 2k_f magnetic fluctuations, we conclude that for temperatures T < T_J the ground state features of the single particle spectral function are apparent in the finite temperature data. Above T_J spectral weight transfer over a scale set by the hopping t is observed. In contrast, photoemission data points to a lower energy scale below which spectral weight transfer occurs. Discrepancies between Hubbard model calculations and experiments are discussed.
In 2003, Kuan, Charnley, and co-workers reported the detection of interstellar glycine (NH2CH2COOH) based on observations of 27 lines in 19 different spectral bands in one or more of the sources Sgr B2(N-LMH), Orion KL, and W51 e1/e2. They supported their detection report with rotational temperature diagrams for all three sources. In this paper, we present essential criteria which can be used in a straightforward analysis technique to confirm the identity of an interstellar asymmetric rotor such as glycine. We use new laboratory measurements of glycine as a basis for applying this analysis technique, both to our previously unpublished 12 m telescope data and to the previously published SEST data of Nummelin and colleagues. We conclude that key lines necessary for an interstellar glycine identification have not yet been found. We identify some common molecular candidates that should be examined further as more likely carriers of several of the lines reported as glycine. Finally, we illustrate that a rotational temperature diagram used without the support of correct spectroscopic assignments is not a reliable tool for the identification of interstellar molecules.
With the tremendous growth of videos over the Internet, video thumbnails, providing video content previews, are becoming increasingly crucial to influencing users' online searching experiences. Conventional video thumbnails are generated once purely based on the visual characteristics of videos, and then displayed as requested. Hence, such video thumbnails, without considering the users' searching intentions, cannot provide a meaningful snapshot of the video contents that users concern. In this paper, we define a distinctively new task, namely sentence specified dynamic video thumbnail generation, where the generated thumbnails not only provide a concise preview of the original video contents but also dynamically relate to the users' searching intentions with semantic correspondences to the users' query sentences. To tackle such a challenging task, we propose a novel graph convolved video thumbnail pointer (GTP). Specifically, GTP leverages a sentence specified video graph convolutional network to model both the sentence-video semantic interaction and the internal video relationships incorporated with the sentence information, based on which a temporal conditioned pointer network is then introduced to sequentially generate the sentence specified video thumbnails. Moreover, we annotate a new dataset based on ActivityNet Captions for the proposed new task, which consists of 10,000+ video-sentence pairs with each accompanied by an annotated sentence specified video thumbnail. We demonstrate that our proposed GTP outperforms several baseline methods on the created dataset, and thus believe that our initial results along with the release of the new dataset will inspire further research on sentence specified dynamic video thumbnail generation. Dataset and code are available at https://github.com/yytzsy/GTP.
We present the second part (days 19 to 102) of our high-resolution Echelle atlas of the spectral evolution of RS Oph during the 2021 nova outburst. Some quick conclusions that can be drawn are: (1) the spectra evolution has progressed smoothly, suggesting that both the expansion of the ejecta through the pre-existing RG wind and the photo-ionization from the central source did not encountered sudden discontinuities prior to switch-off of the nuclear burning; (2) the 2021 spectral evolution is similar to that of the 2006 eruption, with a mirror-appearance of the triple-peaked line profiles (blue peak brighter than red in 2006, the opposite in 2021); (3) the evolution of the triple-peaked profiles progressed similarly through different excitation and ionization degrees, suggesting an origin in a bipolar outflow nested to an equatorial torus; (4) the time-behavior of coronal emission lines appears quite smooth, both in terms of radiated flux as well as evolution of the triple-peaked profiles, with a plateau at maximum lasting up to about day 87; (5) there seems to exist within RS Oph two distinct types of ejecta: one fast moving and producing Gaussian-like line profiles (primarely [NII] and [OIII]), that keep expanding at FWHM=1000 km/s with no sign of ongoing deceleration during the two months leading up to Solar conjunction, and slower moving ejecta giving rise to the triple-peaked line profiles (HeI, HeII, coronal lines, and also Balmer lines at later times), for which the separation in velocity of blue and red peaks is still shrinking at the time of Solar conjunction when it reaches an average of 330 km/s; (6) the "symbiotic band" at 6825 Ang, due to Raman scattering of OVI 1032 by neutral hydrogen, appears simultaneously with the coronal lines: its very presence indicates that a sizeable part of the wind of the red giant has remained neutral during the development of coronal lines.