ShantanuT01/DACTYL-Pretraining huggingface dataset:
We show that macroscopic thermodynamical properties - such as functions of internal energy and magnetization - can detect quantum entanglement in solids at nonzero temperatures in the thermodynamical limit. We identify the parameter regions (critical values of magnetic field and temperature) within which entanglement is witnessed by these thermodynamical quantities.
In this paper we consider higher isoperimetric numbers of a (finite directed) graph. In this regard we focus on the $n$th mean isoperimetric constant of a directed graph as the minimum of the mean outgoing normalized flows from a given set of $n$ disjoint subsets of the vertex set of the graph. We show that the second mean isoperimetric constant in this general setting, coincides with (the mean version of) the classical Cheeger constant of the graph, while for the rest of the spectrum we show that there is a fundamental difference between the $n$th isoperimetric constant and the number obtained by taking the minimum over all $n$-partitions. In this direction, we show that our definition is the correct one in the sense that it satisfies a Federer-Fleming-type theorem, and we also define and present examples for the concept of a supergeometric graph as a graph whose mean isoperimetric constants are attained on partitions at all levels. Moreover, considering the ${\bf NP}$-completeness of the isoperimetric problem on graphs, we address ourselves to the approximation problem where we prove general spectral inequalities that give rise to a general Cheeger-type inequality as well. On the other hand, we also consider some algorithmic aspects of the problem where we show connections to orthogonal representations of graphs and following J.~Malik and J.~Shi ($2000$) we study the close relationships to the well-known $k$-means algorithm and normalized cuts method.
We find a remarkably enhanced production rate in star clusters (relative to the field) of very short period, massive double-white-dwarf stars and of giant-white dwarf binaries. These results are based on N-body simulations performed with the new GRAPE-6 special purpose hardware and are important in identifying and characterizing the progenitors of type Ia supernovae. The high incidence of very close double-white-dwarf systems is the result of dynamical encounters between (mostly) primordial binaries and other cluster stars. Orbital hardening rapidly drives these degenerate binaries to periods under ~10 hours. Gravitational radiation emission and mergers producing supra-Chandrasekhar objects follow in less than a Hubble time. If most stars are born in clusters then estimates of the double white dwarf merger rates in galaxies (due to cluster dynamical interaction) must be increased more than tenfold. A majority of the Roche lobe overflow giant-white dwarf binaries are not primordial; they are produced in exchange reactions. Most cases resulted in a common-envelope and formation of a double-white-dwarf binary rather than Supersoft X-ray sources leading possibly to a type Ia supernova.
We present the results of a detailed investigation of the Galactic supernova remnant RCW 86 using the XMM-Newton X-ray telescope. RCW 86 is the probable remnant of SN 185 A.D, a supernova that likely exploded inside a wind-blown cavity. We use the XMM-Newton Reflection Grating Spectrometer (RGS) to derive precise temperatures and ionization ages of the plasma, which are an indication of the interaction history of the remnant with the presumed cavity. We find that the spectra are well fitted by two non-equilibrium ionization models, which enables us to constrain the properties of the ejecta and interstellar matter plasma. Furthermore, we performed a principal component analysis on EPIC MOS and pn data to find regions with particular spectral properties. We present evidence that the shocked ejecta, emitting Fe-K and Si line emission, are confined to a shell of approximately 2 pc width with an oblate spheroidal morphology. Using detailed hydrodynamical simulations, we show that general dynamical and emission properties at different portions of the remnant can be well-reproduced by a type Ia supernova that exploded in a non-spherically symmetric wind-blown cavity. We also show that this cavity can be created using general wind properties for a single degenerate system. Our data and simulations provide further evidence that RCW 86 is indeed the remnant of SN 185, and is the likely result of a type Ia explosion of single degenerate origin.
The phenomenon of quantum erasure has long intrigued physicists, but has surprisingly found limited practical application. Here, we propose an erasure-based protocol for quantum key distribution (QKD) that promises inherent security against detector attacks.
We present ``just-in-time reconstruction" as real-time image-guided inpainting of a map with arbitrary scale and sparsity to generate a fully dense depth map for the image. In particular, our goal is to inpaint a sparse map --- obtained from either a monocular visual SLAM system or a sparse sensor --- using a single-view depth prediction network as a virtual depth sensor. We adopt a fairly standard approach to data fusion, to produce a fused depth map by performing inference over a novel fully-connected Conditional Random Field (CRF) which is parameterized by the input depth maps and their pixel-wise confidence weights. Crucially, we obtain the confidence weights that parameterize the CRF model in a data-dependent manner via Convolutional Neural Networks (CNNs) which are trained to model the conditional depth error distributions given each source of input depth map and the associated RGB image. Our CRF model penalises absolute depth error in its nodes and pairwise scale-invariant depth error in its edges, and the confidence-based fusion minimizes the impact of outlier input depth values on the fused result. We demonstrate the flexibility of our method by real-time inpainting of ORB-SLAM, Kinect, and LIDAR depth maps acquired both indoors and outdoors at arbitrary scale and varied amount of irregular sparsity.
We discuss a previously discovered [hep-th/9401027] extension of the infinite-dimensional Lie algebras Map(M,g) which generalizes the Kac-Moody algebras in 1+1 dimensions and the Mickelsson-Faddeev algebras in 3+1 dimensions to manifolds M of general dimensions. Furthermore, we review the method of regularizing current algebras in higher dimensions using pseudodifferential operator (PSDO) symbol calculus. In particular, we discuss the issue of Lie algebra cohomology of PSDOs and its relation to the Schwinger terms arising in the quantization process. Finally, we apply this regularization method to the algebra of the above reference with partial success, and discuss the remaining obstacles to the construction of a Fock space representation.
We present an innovative and widely applicable approach for the detection and classification of stellar clusters, developed for the PHANGS-HST Treasury Program, an $NUV$-to-$I$ band imaging campaign of 38 spiral galaxies. Our pipeline first generates a unified master source list for stars and candidate clusters, to enable a self-consistent inventory of all star formation products. To distinguish cluster candidates from stars, we introduce the Multiple Concentration Index (MCI) parameter, and measure inner and outer MCIs to probe morphology in more detail than with a single, standard concentration index (CI). We improve upon cluster candidate selection, jointly basing our criteria on expectations for MCI derived from synthetic cluster populations and existing cluster catalogues, yielding model and semi-empirical selection regions (respectively). Selection purity (confirmed clusters versus candidates, assessed via human-based classification) is high (up to 70$\%$) for moderately luminous sources in the semi-empirical selection region, and somewhat lower overall (outside the region or fainter). The number of candidates rises steeply with decreasing luminosity, but pipeline-integrated Machine Learning (ML) classification prevents this from being problematic. We quantify the performance of our PHANGS-HST methods in comparison to LEGUS for a sample of four galaxies in common to both surveys, finding overall agreement with $50-75\%$ of human verified star clusters appearing in both catalogues, but also subtle differences attributable to specific choices adopted by each project. The PHANGS-HST ML-classified Class 1 or 2 catalogues reach $\sim1$ magnitude fainter, $\sim2\times$ lower stellar mass, and are $2{-}5\times$ larger in number, than attained in the human classified samples.
We report on our observing campaign of the compact binary merger GW190814, detected by the Advanced LIGO and Advanced Virgo detectors on August 14th, 2019. This signal has the best localisation of any observed gravitational wave (GW) source, with a 90% probability area of 18.5 deg$^2$, and an estimated distance of ~ 240 Mpc. We obtained wide-field observations with the Deca-Degree Optical Transient Imager (DDOTI) covering 88% of the probability area down to a limiting magnitude of $w$ = 19.9 AB. Nearby galaxies within the high probability region were targeted with the Lowell Discovery Telescope (LDT), whereas promising candidate counterparts were characterized through multi-colour photometry with the Reionization and Transients InfraRed (RATIR) and spectroscopy with the Gran Telescopio de Canarias (GTC). We use our optical and near-infrared limits in conjunction with the upper limits obtained by the community to constrain the possible electromagnetic counterparts associated with the merger. A gamma-ray burst seen along its jet's axis is disfavoured by the multi-wavelength dataset, whereas the presence of a burst seen at larger viewing angles is not well constrained. Although our observations are not sensitive to a kilonova similar to AT2017gfo, we can rule out high-mass (> 0.1 M$_{\odot}$) fast-moving (mean velocity >= 0.3c) wind ejecta for a possible kilonova associated with this merger.
We analyze the angular momentum evolution from the red giant branch (RGB) to the horizontal branch (HB) and along the HB. Using rotation velocities for stars in the globular cluster M13, we find that the required angular momentum for the fast rotators is up to 1-3 orders of magnitude (depending on some assumptions) larger than that of the sun. Planets of masses up to five times Jupiter's mass and up to an initial orbital separation of about 2 AU are sufficient to spin-up the RGB progenitors of most of these fast rotators. Other stars have been spun-up by brown dwarfs or low-mass main sequence stars. Our results show that the fast rotating HB stars must have been spun-up by companions while they evolved on the RGB. The angular momentum considerations presented in this paper further supports the "planet second parameter" model. In this model the "second parameter" process is interaction with low-mass companions, in most cases gas giant planets, and in a minority of cases with brown dwarfs or low-mass main sequence stars.
A key assumption in quasar absorption line studies of the circumgalactic medium (CGM) is that each absorption component maps to a spatially isolated "cloud" structure that has single valued properties (e.g. density, temperature, metallicity). We aim to assess and quantify the degree of accuracy underlying this assumption. We used adaptive mesh refinement hydrodynamic cosmological simulations of two $z=1$ dwarf galaxies and generated synthetic quasar absorption-line spectra of their CGM. For the SiII $\lambda 1260$ transition, and the CIV $\lambda\lambda1548, 1550$ and OVI $\lambda\lambda1031, 1037$ fine-structure doublets, we objectively determined which gas cells along a line-of-sight (LOS) contribute to detected absorption. We implemented a fast, efficient, and objective method to define individual absorption components in each absorption profile. For each absorption component, we quantified the spatial distribution of the absorbing gas. We studied a total of 1,302 absorption systems containing a total of 7,755 absorption components. 48% of SiII, 68% of CIV, and 72% of OVI absorption components arise from two or more spatially isolated "cloud" structures along the LOS. Spatially isolated "cloud" structures were most likely to have cloud-cloud LOS separations of 0.03$R_{vir}$, 0.11$R_{vir}$, and 0.13$R_{vir}$ for SiII, CIV, and OVI, respectively. There can be very little overlap between multi-phase gas structures giving rise to absorption components. If our results reflect the underlying reality of how absorption lines record CGM gas, they place tension on current observational analysis methods as they suggest that component-by-component absorption line formation is more complex than is assumed and applied for chemical-ionisation modelling.
An investigation of the P/T phase diagram of the quarter-filled organic conductors, [EDT-TTF-CONMe2]2X, is reported on the basis of transport and NMR studies of two members, X=AsF6 and Br of the family. The strongly insulating character of these materials in the low pressure regime has been attributed to a remarkably stable charge ordered state confirmed by 13C NMR and the only existence of 1/4 Umklapp e-e scattering favoring a charge ordering instead of the 1D Mott localization seen in (TM)2X which are quarter-filled compounds with dimerization. A non magnetic insulating phase instead of the spin density wave state is stabilized in the deconfined regime of the phase diagram. This sequence of phases observed under pressure may be considered as a generic behavior for 1/4-filled conductors with correlations.
We give an exact solution to the generalized Langevin equation of motion of a charged Brownian particle in a uniform magnetic field that is driven internally by an exponentially-correlated stochastic force. A strong dissipation regime is described in which the ensemble-averaged fluctuations of the velocity exhibit transient oscillations that arise from memory effects. Also, we calculate generalized diffusion coefficients describing the transport of these particles and briefly discuss how they are affected by the magnetic field strength and correlation time. Our asymptotic results are extended to the general case of internal driving by correlated Gaussian stochastic forces with finite autocorrelation times.
The Boson-Fermion model, describing a mixture of hybridized localized Bosons and itinerant Fermions on a lattice, is known to exhibit spectral properties for the Fermions which upon lowering the temperature develop into a three pole structure in the vicinity of the Fermi level. These spectral features go hand in hand with the opening of a pseudogap in the density of states upon approaching the critical temperature Tc when superconductivity sets in. In the present work we study this model, in the atomic limit where the three pole structure arises naturally from the local bonding, anti-bonding and non-bonding states between the Bosons and Fermions.
Due to domain bias, directly deploying a deep person re-identification (re-ID) model trained on one dataset often achieves considerably poor accuracy on another dataset. In this paper, we propose an Adaptive Exploration (AE) method to address the domain-shift problem for re-ID in an unsupervised manner. Specifically, in the target domain, the re-ID model is inducted to 1) maximize distances between all person images and 2) minimize distances between similar person images. In the first case, by treating each person image as an individual class, a non-parametric classifier with a feature memory is exploited to encourage person images to move far away from each other. In the second case, according to a similarity threshold, our method adaptively selects neighborhoods for each person image in the feature space. By treating these similar person images as the same class, the non-parametric classifier forces them to stay closer. However, a problem of the adaptive selection is that, when an image has too many neighborhoods, it is more likely to attract other images as its neighborhoods. As a result, a minority of images may select a large number of neighborhoods while a majority of images have only a few neighborhoods. To address this issue, we additionally integrate a balance strategy into the adaptive selection. We evaluate our methods with two protocols. The first one is called "target-only re-ID", in which only the unlabeled target data is used for training. The second one is called "domain adaptive re-ID", in which both the source data and the target data are used during training. Experimental results on large-scale re-ID datasets demonstrate the effectiveness of our method. Our code has been released at https://github.com/dyh127/Adaptive-Exploration-for-Unsupervised-Person-Re-Identification.
We report the first detection of high-energy X-ray (E>10 keV) emission from the Galactic Center non-thermal filament G359.89-0.08 (Sgr A-E) using data acquired with the Nuclear Spectroscopic Telescope Array (NuSTAR). The bright filament was detected up to ~50 keV during a NuSTAR Galactic Center monitoring campaign. The featureless power-law spectrum with a photon index of ~2.3 confirms a non-thermal emission mechanism. The observed flux in the 3-79 keV band is ~ 2.0e-12 erg/cm^2/s, corresponding to an unabsorbed X-ray luminosity of ~2.6e34 erg/s assuming a distance of 8.0 kpc. Based on theoretical predictions and observations, we conclude that Sgr A-E is unlikely to be a pulsar wind nebula (PWN) or supernova remnant-molecular cloud (SNR-MC) interaction, as previously hypothesized. Instead, the emission could be due to a magnetic flux tube which traps TeV electrons. We propose two possible TeV electron sources: old PWNe (up to ~100 kyr) with low surface brightness and radii up to ~30 pc or molecular clouds (MCs) illuminated by cosmic rays (CRs) from CR accelerators such as SNRs or Sgr A*.
In this note we study the geometry of the component of the origin in the Uniform Spanning Forest of $\mathbb{Z}^d$, as well as in the Uniform Spanning Tree of wired subgraphs of $\mathbb{Z}^d$, when $d \ge 5$. In particular, we study connectivity properties with respect to the Euclidean and the intrinsic distance. We intend to supplement these with further estimates in the future. We are making this preliminary note available, as one of our estimates is used in work of Bhupatiraju, Hanson and J\'arai on sandpiles.
Andrews introduced the partition function $\overline{C}_{k, i}(n)$, called singular overpartition, which counts the number of overpartitions of $n$ in which no part is divisible by $k$ and only parts $\equiv \pm i\pmod{k}$ may be overlined. He also proved that $\overline{C}_{3, 1}(9n+3)$ and $\overline{C}_{3, 1}(9n+6)$ are divisible by $3$ for $n\geq 0$. Recently Aricheta proved that for an infinite family of $k$, $\overline{C}_{3k, k}(n)$ is almost always even. In this paper, we prove that for any positive integer $k$, $\overline{C}_{3, 1}(n)$ is almost always divisible by $2^k$ and $3^k.$
Intermediate mass galaxies (logM(Msun)>10) at z~0.6 are the likeliest progenitors of the present-day numerous population of spirals. There is growing evidence that they have evolved rapidly since the last 6 to 8 Gyr ago, and likely have formed a significant fraction of their stellar mass, often showing perturbed morphologies and kinematics. We have gathered a representative sample of 88 such galaxies and have provided robust estimates of their gas phase metallicity. For doing so, we have used moderate spectral resolution spectroscopy at VLT/FORS2 with unprecedented high S/N allowing to remove biases coming from interstellar absorption lines and extinction to establish robust values of R23=([OII]3727 + [OIII]4959,5007)/Hbeta. We definitively confirm that the predominant population of z~0.6 starbursts and luminous IR galaxies (LIRGs) are on average, two times less metal rich than the local galaxies at a given stellar mass. We do find that the metal abundance of the gaseous phase of galaxies is evolving linearly with time, from z=1 to z=0 and after comparing with other studies, from z=3 to z=0. Combining our results with the reported evolution of the Tully Fisher relation, we do find that such an evolution requires that ~30% of the stellar mass of local galaxies have been formed through an external supply of gas, thus excluding the close box model. Distant starbursts & LIRGs have properties (metal abundance, star formation efficiency & morphologies) similar to those of local LIRGs. Their underlying physics is likely dominated by gas infall probably through merging or interactions. Our study further supports the rapid evolution of z~0.4-1 galaxies. Gas exchanges between galaxies is likely the main cause of this evolution.
Manganites with double perovskite structure are being attractive because of their interesting magnetoelectric and dielectric responses. Particularly, colossal dielectric constant (CDC) behavior has been observed in La$_2$CoMnO$_6$ (LCMO), at radio frequencies and room temperature. In this paper, we employed infrared-reflectivity spectroscopy onto a LCMO ceramic obtained through a modified Pechini's method to determine the phonon contribution to the intrinsic dielectric response of the system and to investigate the CDC origin. The analysis of the main polar modes and of the obtained phonon parameters show that CDC effect of LCMO is of pure extrinsic origin. In addition, we have estimated the dielectric constant and quality factor of the material in microwave region, $e'_s \sim 16$ and $Q_u \times f \sim 124$ THz, which shows that LCMO is appropriate for applications into microwave devices and circuitry.
Structured pruning methods are among the effective strategies for extracting small resource-efficient convolutional neural networks from their dense counterparts with minimal loss in accuracy. However, most existing methods still suffer from one or more limitations, that include 1) the need for training the dense model from scratch with pruning-related parameters embedded in the architecture, 2) requiring model-specific hyperparameter settings, 3) inability to include budget-related constraint in the training process, and 4) instability under scenarios of extreme pruning. In this paper, we present ChipNet, a deterministic pruning strategy that employs continuous Heaviside function and a novel crispness loss to identify a highly sparse network out of an existing dense network. Our choice of continuous Heaviside function is inspired by the field of design optimization, where the material distribution task is posed as a continuous optimization problem, but only discrete values (0 or 1) are practically feasible and expected as final outcomes. Our approach's flexible design facilitates its use with different choices of budget constraints while maintaining stability for very low target budgets. Experimental results show that ChipNet outperforms state-of-the-art structured pruning methods by remarkable margins of up to 16.1% in terms of accuracy. Further, we show that the masks obtained with ChipNet are transferable across datasets. For certain cases, it was observed that masks transferred from a model trained on feature-rich teacher dataset provide better performance on the student dataset than those obtained by directly pruning on the student data itself.