ShantanuT01/DACTYL-Pretraining huggingface dataset:
For tracking a spacecraft and doing radio science, the transformation between the proper time $\tau$ given by a clock carried on board a spacecraft and the barycentric coordinate time (TCB) is investigated under IAU resolutions. In order to show more clearly physical pictures and improve computational efficiency, an analytic approach is adopted. After numerical checks, it shows this method is qualified for a Mars orbiter during one year, especially being good at describing the influence from perturbing bodies. Further analyses demonstrate that there are two main effects in the transformation: the gravitational field of the Sun and the velocity of the spacecraft in the barycentric coordinate reference system (BCRS). The whole contribution of them is at the level of a few sub-seconds.
In this paper, we study the optimal multiple stopping problem under the filtration consistent nonlinear expectations. The reward is given by a set of random variables satisfying some appropriate assumptions rather than an RCLL process. We first construct the optimal stopping time for the single stopping problem, which is no longer given by the first hitting time of processes. We then prove by induction that the value function of the multiple stopping problem can be interpreted as the one for the single stopping problem associated with a new reward family, which allows us to construct the optimal multiple stopping times. If the reward family satisfies some strong regularity conditions, we show that the reward family and the value functions can be aggregated by some progressive processes. Hence, the optimal stopping times can be represented as hitting times.
Structural, electronic and optical properties of Cu2ZnSn(SxSe1-x)4 semiconductors are studied theoretically for different concentration of S and Se anions. The optical properties are calculated at three levels of theory, in the generalized gradient approximation (GGA), meta-GGA, and with a hybrid functional. The GGA and meta-GGA calculations are corrected with an on-site Coulomb Ud term. Lattice constants, dielectric constants, and band-gaps are found to vary almost linearly with the concentration of S. We also show that a dense sampling of the Brillouin zone is required to accurately account for the shape of the dielectric function, which is hard to attain with hybrid functionals. This issue is resolved with a recently developed k dot p based interpolation scheme, which allows us to compare results of the hybrid functional calculations on an equal footing with the GGA and meta-GGA results. We find that the hybrid functionals provide the overall best agreement with the experimental dielectric function.
The structure of the NGC 6251 jet on the milliarcsecond scale is investigated using images taken with the European VLBI Network and the Very Long Baseline Array. We detect a structural transition of the jet from a parabolic to a conical shape at a distance of (1-2) x 10^5 times the Schwarzschild radius from the central engine, which is close to the sphere of gravitational influence of the supermassive black hole (SMBH). We also examine the jet pressure profiles with the synchrotron minimum energy assumption to discuss the physical origin of the structural transition. The NGC 6251 jet, together with the M87 jet, suggests a fundamental process of structural transition in the jets of active galactic nuclei (AGNs). Collimated AGN jets are characterized by their external galactic medium, showing that AGN jets interplay with the SMBH and its host galaxy.
Recent progresses on the relativistic modeling of neutrino-nucleus reactions are presented and the results are compared with high precision experimental data in a wide energy range.
We introduce the notion of induced automorphisms in order to state a criterion to determine whether a given automorphism on a manifold of $K3^{[n]}$ type is, in fact, induced by an automorphism of a $K3$ surface and the manifold is a moduli space of stable objects on the $K3$. This criterion is applied to the classification of non-symplectic prime order automorphisms on manifolds of $K3^{[2]}$ type and we prove that almost all cases are covered. Variations of this notion and the above criterion are introduced and discussed for the other known deformation types of irreducible symplectic manifolds. Furthermore we provide a description of the Picard lattice of several irreducible symplectic manifolds having a lagrangian fibration.
Disorder induced by chemical inhomogeneity and Jahn-Teller (JT) distortions is often observed in mixed valence perovskite manganites. The main reasons for the evolution of this disorder are connected with the cationic size differences and the ratio between JT active and non-JT active ions. The quenched disorder leads to a spin-cluster state above the magnetic transition temperature. The effect of Cu, a B-site substitution in the La0.8Sr0.2MnO3 compound, on the disordered phase has been addressed here. X-ray powder diffraction reveals rhombohedral (R-3c) structures for the two compounds with negligible change of lattice volume. The chemical compositions of the two compounds were verified by ion beam analysis technique. With the change of electronic bandwidth, the magnetic phase transition temperature has been tuned towards room temperature (318 K), an important requirement for room temperature magnetic refrigeration. However, a small decrease of the isothermal entropy was observed with Cu-substitution, related to the decrease of the saturation magnetization.
One of the most intriguing features of quantum physics is the non-locality of correlations that can be obtained by measuring entangled particles. Recently, it has been noticed that non-locality can be studied without reference to the Hilbert space formalism. I review here the properties of the basic mathematical tool used for such studies, the so called Popescu-Rohrlich-box, in short PR-box. Among its feats, are the simulation of the correlations of the singlet and of other non-local probability distributions. Among its features, the "anomaly of non-locality" and a great power for information-theoretical tasks. Among its failures, the impossibility of reproducing all multi-partite distributions and the triviality of the allowed dynamics.
In the inner-most regions of radiation pressure supported accretion disks, the turbulent magnetic pressure may greatly exceed that of the gas. If this is the case, it is possible for bulk Alfvenic motions driven by the magnetorotational instability (MRI) to surpass the electron thermal velocity. Bulk rather than thermal Comptonization may then be the dominant radiative process which mediates gravitational energy release. For sufficiently large turbulent stresses, we show that turbulent Comptonization produces a significant contribution to the far-UV and X-ray emission of black hole accretion disks. The existence of this spectral component provides a means of obtaining direct observational constraints on the nature of the turbulence itself. We describe how this component may affect the spectral energy distributions and variability properties of X-ray binaries and active galactic nuclei.
We report a nonsaturating linear magnetoresistance in charge-compensated bilayer graphene in a temperature range from 1.5 to 150 K. The observed linear magnetoresistance disappears away from charge neutrality ruling out the traditional explanation of the effect in terms of the classical random resistor network model. We show that experimental results qualitatively agree with a phenomenological two-fluid model taking into account electron-hole recombination and finite-size sample geometry.
In order to understand how the combination of domain evolution and impulsive harvesting affect the dynamics of a population, we propose a diffusive logistic population model with impulsive harvesting on a periodically evolving domain. Initially the ecological reproduction index of the impulsive problem is introduced and given by an explicit formula, which depends on the domain evolution rate and the impulsive function. Then the threshold dynamics of the population under monotone or nonmonotone impulsive harvesting is established based on this index. Finally numerical simulations are carried out to illustrate our theoretical results, and reveal that a large domain evolution rate can improve the population survival, no matter which impulsive harvesting takes place. Contrary, impulsive harvesting has a negative effect on the population survival, and can even lead to the extinction of the population.
High performance face detection remains a very challenging problem, especially when there exists many tiny faces. This paper presents a novel single-shot face detector, named Selective Refinement Network (SRN), which introduces novel two-step classification and regression operations selectively into an anchor-based face detector to reduce false positives and improve location accuracy simultaneously. In particular, the SRN consists of two modules: the Selective Two-step Classification (STC) module and the Selective Two-step Regression (STR) module. The STC aims to filter out most simple negative anchors from low level detection layers to reduce the search space for the subsequent classifier, while the STR is designed to coarsely adjust the locations and sizes of anchors from high level detection layers to provide better initialization for the subsequent regressor. Moreover, we design a Receptive Field Enhancement (RFE) block to provide more diverse receptive field, which helps to better capture faces in some extreme poses. As a consequence, the proposed SRN detector achieves state-of-the-art performance on all the widely used face detection benchmarks, including AFW, PASCAL face, FDDB, and WIDER FACE datasets. Codes will be released to facilitate further studies on the face detection problem.
We consider the Schr\"odinger Map equation in $2+1$ dimensions, with values into $\S^2$. This admits a lowest energy steady state $Q$, namely the stereographic projection, which extends to a two dimensional family of steady states by scaling and rotation. We prove that $Q$ is unstable in the energy space $\dot H^1$. However, in the process of proving this we also show that within the equivariant class $Q$ is stable in a stronger topology $X \subset \dot H^1$.
We study the effects of dissipation and decoherence induced on a harmonic oscillator by the coupling to a chaotic system with two degrees of freedom. Using the Feynman-Vernon approach and treating the chaotic system semiclassically we show that the effects of the low dimensional chaotic environment are in many ways similar to those produced by thermal baths. The classical correlation and response functions play important roles in both classical and quantum formulations. Our results are qualitatively similar to the high temperature regime of the Caldeira-Leggett model.
Quantum error correction (QEC) is one of the central concepts in quantum information science and also has wide applications in fundamental physics. The capacity theorems provide solid foundations of QEC. We here provide a general and highly applicable form of capacity theorem for both classical and quantum information, i.e., hybrid information, with assistance of a limited resource of entanglement in one-shot scenario, which covers broader situations than the existing ones. Harnessing the wide applicability of the theorem, we show that a demonstration of QEC by short random quantum circuits is feasible and that QEC is intrinsic in quantum chaotic systems. Our results bridge the progress in quantum information theory, near-future quantum technology, and fundamental physics.
We present detailed clustering analysis of a large K-band selected local galaxy sample, which is constructed from the 2MASS and the SDSS and consists of $82,486$ galaxies with $10 < K < 13.5$ and $0.01 < z < 0.1$. The two-point correlation function of the magnitude-limited sample in real space at small scales is well described by a power law $\xi(r)=(r/6.44\pm0.23)^{-1.81\pm0.02}$. The pairwise velocity dispersion is derived from the anisotropic two-point correlation function and find the dispersion $\sigma_{12}=685\pm 17\kms$ if its scale invariance is assumed, which is larger than values measured in optical bands selected galaxy samples. We further investigate the dependence of the two-point correlation function and the $\sigma_{12}$ on the $g-r$ color and the $K$-band luminosity, obtain similar results to previous works in optical bands. Comparing a mock galaxy sample with our real data indicates that the semi-analytical model can not mimic the $\sigma_{12}$ in observation albeit it can approximate the two-point correlation function within measurement uncertainties.
We show that, in the Regge limit, beam asymmetries in $\eta$ and $\eta'$ photoproduction are sensitive to hidden strangeness components. Under reasonable assumptions about the couplings we estimate the contribution of the $\phi$ Regge pole, which is expected to be the dominant hidden strangeness contribution. The ratio of the asymmetries in $\eta'$ and $\eta$ production is estimated to be close to unity in the forward region $0 < -t/\text{GeV}^2 \leq 1$ at the photon energy $E_\text{lab} = 9$~GeV, relevant for the upcoming measurements at Jefferson Lab.
Knowledge Distillation (KD) is a widely-used technology to inherit information from cumbersome teacher models to compact student models, consequently realizing model compression and acceleration. Compared with image classification, object detection is a more complex task, and designing specific KD methods for object detection is non-trivial. In this work, we elaborately study the behaviour difference between the teacher and student detection models, and obtain two intriguing observations: First, the teacher and student rank their detected candidate boxes quite differently, which results in their precision discrepancy. Second, there is a considerable gap between the feature response differences and prediction differences between teacher and student, indicating that equally imitating all the feature maps of the teacher is the sub-optimal choice for improving the student's accuracy. Based on the two observations, we propose Rank Mimicking (RM) and Prediction-guided Feature Imitation (PFI) for distilling one-stage detectors, respectively. RM takes the rank of candidate boxes from teachers as a new form of knowledge to distill, which consistently outperforms the traditional soft label distillation. PFI attempts to correlate feature differences with prediction differences, making feature imitation directly help to improve the student's accuracy. On MS COCO and PASCAL VOC benchmarks, extensive experiments are conducted on various detectors with different backbones to validate the effectiveness of our method. Specifically, RetinaNet with ResNet50 achieves 40.4% mAP in MS COCO, which is 3.5% higher than its baseline, and also outperforms previous KD methods.
We report new high-quality galaxy scale strong lens candidates found in the Kilo Degree Survey data release 4 using Machine Learning. We have developed a new Convolutional Neural Network (CNN) classifier to search for gravitational arcs, following the prescription by \cite{2019MNRAS.484.3879P} and using only $r-$band images. We have applied the CNN to two "predictive samples": a Luminous red galaxy (LRG) and a "bright galaxy" (BG) sample ($r<21$). We have found 286 new high probability candidates, 133 from the LRG sample and 153 from the BG sample. We have then ranked these candidates based on a value that combines the CNN likelihood to be a lens and the human score resulting from visual inspection (P-value) and we present here the highest 82 ranked candidates with P-values $\ge 0.5$. All these high-quality candidates have obvious arc or point-like features around the central red defector. Moreover, we define the best 26 objects, all with scores P-values $\ge 0.7$ as a "golden sample" of candidates. This sample is expected to contain very few false positives and thus it is suitable for follow-up observations. The new lens candidates come partially from the the more extended footprint adopted here with respect to the previous analyses, partially from a larger predictive sample (also including the BG sample). These results show that machine learning tools are very promising to find strong lenses in large surveys and more candidates that can be found by enlarging the predictive samples beyond the standard assumption of LRGs. In the future, we plan to apply our CNN to the data from next-generation surveys such as the Large Synoptic Survey Telescope, Euclid, and the Chinese Space Station Optical Survey.
An arithmetic framework to string compactification is described. The approach is exemplified by formulating a strategy that allows to construct geometric compactifications from exactly solvable theories at $c=3$. It is shown that the conformal field theoretic characters can be derived from the geometry of spacetime, and that the geometry is uniquely determined by the two-dimensional field theory on the world sheet. The modular forms that appear in these constructions admit complex multiplication, and allow an interpretation as generalized McKay-Thompson series associated to the Mathieu and Conway groups. This leads to a string motivated notion of arithmetic moonshine.
IGR J17511-3057 is the second X-ray transient accreting millisecond pulsar discovered by INTEGRAL. It was in outburst for about a month from September 13, 2009. The broad-band average spectrum is well described by thermal Comptonization with an electron temperature of kT_e ~ 25 keV, soft seed photons of kT_bb ~ 0.6 keV, and Thomson optical depth \tau_T ~ 2 in a slab geometry. During the outburst the spectrum stays remarkably stable with plasma and soft seed photon temperatures and scattering optical depth being constant within errors. We fitted the outburst profile with the exponential model, and using the disk instability model we inferred the outer disk radius to be (4.8 - 5.4) \times 1010 cm. The INTEGRAL and RXTE data reveal the X-ray pulsation at a period of 4.08 milliseconds up to ~ 120 keV. The pulsed fraction is shown to decrease from ~22% at 3 keV to a constant pulsed fraction of ~17-18% between 7-30 keV, and then to decrease again down to ~13% at 60 keV. The nearly sinusoidal pulses show soft lags monotonically increasing with energy to about 0.2 ms at 10-20 keV similar to those observed in other accreting pulsars. The short burst profiles indicate hydrogen-poor material at ignition, which suggests either that the accreted material is hydrogen-deficient, or that the CNO metallicity is up to a factor of 2 times solar. However, the variation of burst recurrence time as a function of m (inferred from the X-ray flux) is much smaller than predicted by helium-ignition models.
We establish a moderate deviations principle (MDP) for the log-determinant $\log | \det (M_n) |$ of a Wigner matrix $M_n$ matching four moments with either the GUE or GOE ensemble. Further we establish Cram\'er--type moderate deviations and Berry-Esseen bounds for the log-determinant for the GUE and GOE ensembles as well as for non-symmetric and non-Hermitian Gaussian random matrices (Ginibre ensembles), respectively.
We prove the existence of a canonical zero-cycle on a Calabi-Yau hypersurface X in a complex projective homogeneous variety. More precisely, we show that the intersection of any n divisors on X, n=dim X, is proportional to the class of a point on a rational curve in X.
Person re-identification (Re-ID) is a challenging task as persons are often in different backgrounds. Most recent Re-ID methods treat the foreground and background information equally for person discriminative learning, but can easily lead to potential false alarm problems when different persons are in similar backgrounds or the same person is in different backgrounds. In this paper, we propose a Foreground-Guided Texture-Focused Network (FTN) for Re-ID, which can weaken the representation of unrelated background and highlight the attributes person-related in an end-to-end manner. FTN consists of a semantic encoder (S-Enc) and a compact foreground attention module (CFA) for Re-ID task, and a texture-focused decoder (TF-Dec) for reconstruction task. Particularly, we build a foreground-guided semi-supervised learning strategy for TF-Dec because the reconstructed ground-truths are only the inputs of FTN weighted by the Gaussian mask and the attention mask generated by CFA. Moreover, a new gradient loss is introduced to encourage the network to mine the texture consistency between the inputs and the reconstructed outputs. Our FTN is computationally efficient and extensive experiments on three commonly used datasets Market1501, CUHK03 and MSMT17 demonstrate that the proposed method performs favorably against the state-of-the-art methods.
We explore voids in dark matter and halo fields from simulations of $\Lambda$CDM and Hu-Sawicki $f(R)$ models. In $f(R)$ gravity, dark matter void abundances are greater than that of general relativity (GR). However, when using haloes to identify voids, the differences of void abundances become much smaller, but can still be told apart, in principle, at the 2, 6 and 14 $\sigma$ level for the $f(R)$ model parameter amplitudes of $|f_{R0}|=10^{-6}$, $10^{-5}$ and $10^{-4}$. In contrast, the abundance of large voids found using haloes in $f(R)$ gravity is lower than in GR. The more efficient halo formation in underdense regions makes $f(R)$ voids less empty of haloes. This counter intuitive result suggests that voids are not necessarily emptier in $f(R)$ if one looks at galaxies in voids. Indeed, the halo number density profiles of voids are not distinguishable from GR. However, the same $f(R)$ voids are more empty of dark matter. This can in principle be observed by weak gravitational lensing of voids, for which the combination of a spec-$z$ and a photo-$z$ survey over the same sky is necessary. For a volume of 1~(Gpc/$h$)$^3$, neglecting the lensing shape noise, $|f_{R0}|=10^{-5}$ and $10^{-4}$ may be distinguished from GR using the lensing tangential shear signal around voids by 4 and 8$\sigma$. The line-of-sight projection of large-scale structure is the main systematics that limits the significance of this signal, limiting the constraining power for $|f_{R0}|=10^{-6}$. The halo void abundance being smaller and the steepening of dark matter void profiles in $f(R)$ models are unique features that can be combined to break the degeneracy between $|f_{R0}|$ and $\sigma_8$. The outflow of mass from void centers and velocity dispersions are greater in $f(R)$. Model differences in velocity profiles imply potential powerful constraints of the model in phase space and in redshift space.
Most massive stars are born in binaries close enough for mass transfer episodes. These modify the appearance, structure, and future evolution of both stars. We compute the evolution of a 100-day period binary consisting initially of a 25 M star and a 17 M star, which experiences stable mass transfer. We focus on the impact of mass accretion on the surface composition, internal rotation, and structure of the accretor. To anchor our models, we show that our accretor broadly reproduces the properties of {\zeta} Ophiuchi, which has long been proposed to have accreted mass before being ejected as a runaway star when the companion exploded. We compare our accretor to models of single rotating stars and find that the later and stronger spin-up provided by mass accretion produces significant differences. Specifically, the core of the accretor retains higher spin at the end of the main sequence, and a convective layer develops that changes its density profile. Moreover, the surface of the accretor star is polluted by CNO-processed material donated by the companion. Our models show effects of mass accretion in binaries that are not captured in single rotating stellar models. This possibly impacts the further evolution (either in a binary or as single stars), the final collapse, and the resulting spin of the compact object.