ShantanuT01/DACTYL-Pretraining huggingface dataset:
Topological quantum matter and spintronics research have been developed to a large extent independently. In this Review we discuss a new role that the antiferromagnetic order has taken in combining topological matter and spintronics. This occurs due to the complex microscopic symmetries present in antiferromagnets that allow, e.g., for topological relativistic quasiparticles and the newly discovered N\'{e}el spin-orbit torques to coexist. We first introduce the concepts of topological semimetals and spin-orbitronics. Secondly, we explain the antiferromagnetic symmetries on a minimal Dirac semimetal model and the guiding role of $\textit{ab initio}$ calculations in predictions of examples of Dirac, and Weyl antiferromagnets: SrMnBi$_{\text{2}}$, CuMnAs, and Mn$_{\text{3}}$Ge. Lastly, we illustrate the interplay of Dirac quasiparticles, topology and antiferromagnetism on: (i) the experimentally observed quantum Hall effect in EuMnBi$_{\text{2}}$, (ii) the large anomalous Hall effect in Mn$_{\text{3}}$Ge, and (iii) the theoretically predicted topological metal-insulator transition in CuMnAs.
We propose an entanglement generation scheme that requires neither the coherent evolution of a quantum system nor the detection of single photons. Instead, the desired state is heralded by a {\em macroscopic} quantum jump. Macroscopic quantum jumps manifest themselves as a random telegraph signal with long intervals of intense fluorescence (light periods) interrupted by the complete absence of photons (dark periods). Here we show that a system of two atoms trapped inside an optical cavity can be designed such that a dark period prepares the atoms in a maximally entangled ground state. Achieving fidelities above 0.9 is possible even when the single-atom cooperativity parameter C is as low as 10 and when using a photon detector with an efficiency as low as eta = 0.2.
FU Orionis (FUOR) outbursts are major optical brightening episodes in low-mass protostars that correspond to rapid mass-accretion events in the innermost region of a protostellar disc. The outbursts are accompanied by strong outflows, with the inferred mass outflow rates reaching ~10% of the mass inflow rates. Shu et al. proposed that the outflows represent accreted disc material that is driven centrifugally from the spun-up surface layers of the protostar by the stellar magnetic field. This model was critiqued by Calvet et al., who argued that it cannot reproduce the photospheric absorption-line shifts observed in the prototype object FU Ori. Calvet et al. proposed that the wind is launched, instead, from the surface of the disc on scales of a few stellar radii by a non-stellar magnetic field. In this paper we present results from numerical simulations of disc accretion on to a slowly rotating star with an aligned magnetic dipole moment that gives rise to a kilogauss-strength surface field. We demonstrate that, for parameters appropriate to FU Ori, such a system can develop a strong, collimated disc outflow of the type previously identified by Romanova et al. in simulations of protostars with low and moderate accretion rates. At the high accretion rate that characterizes FUOR outbursts, the radius at which the disc is truncated by the stellar magnetic field moves much closer to the stellar surface, but the basic properties of the outflow, which is launched from the vicinity of the truncation radius along opened-up stellar magnetic field lines, remain the same, and are distinct from those of the mechanism proposed by Shu et al. We show that the simulated outflow can in principle account for the main observed characteristics of FUOR winds, including the photospheric line shifts measured in FU Ori.
How to model fine-grained spatial-temporal dynamics in videos has been a challenging problem for action recognition. It requires learning deep and rich features with superior distinctiveness for the subtle and abstract motions. Most existing methods generate features of a layer in a pure feedforward manner, where the information moves in one direction from inputs to outputs. And they rely on stacking more layers to obtain more powerful features, bringing extra non-negligible overheads. In this paper, we propose an Adaptive Recursive Circle (ARC) framework, a fine-grained decorator for pure feedforward layers. It inherits the operators and parameters of the original layer but is slightly different in the use of those operators and parameters. Specifically, the input of the layer is treated as an evolving state, and its update is alternated with the feature generation. At each recursive step, the input state is enriched by the previously generated features and the feature generation is made with the newly updated input state. We hope the ARC framework can facilitate fine-grained action recognition by introducing deeply refined features and multi-scale receptive fields at a low cost. Significant improvements over feedforward baselines are observed on several benchmarks. For example, an ARC-equipped TSM-ResNet18 outperforms TSM-ResNet50 with 48% fewer FLOPs and 52% model parameters on Something-Something V1 and Diving48.
The old Bohr-Einstein debate about the completeness of quantum mechanics (QM) was held on an ontological ground. The completeness problem becomes more tractable, however, if it is preliminarily discussed from a semantic viewpoint. Indeed every physical theory adopts, explicitly or not, a truth theory for its observative language, in terms of which the notions of semantic objectivity and semantic completeness of the physical theory can be introduced and inquired. In particular, standard QM adopts a verificationist theory of truth that implies its semantic nonobjectivity; moreover, we show in this paper that standard QM is semantically complete, which matches Bohr's thesis. On the other hand, one of the authors has provided a Semantic Realism (or SR) interpretation of QM that adopts a Tarskian theory of truth as correspondence for the observative language of QM (which was previously mantained to be impossible); according to this interpretation QM is semantically objective, yet incomplete, which matches EPR's thesis. Thus, standard QM and the SR interpretation of QM come to opposite conclusions. These can be reconciled within an integrationist perspective that interpretes non-Tarskian theories of truth as theories of metalinguistic concepts different from truth.
In a recent publication, we have discussed the effects of boundary conditions in finite quantum systems and their connection with symmetries. Focusing on the one-dimensional Hubbard Hamiltonian under twisted boundary conditions, we have shown that properties, such as the ground-state and gap energies, converge faster to the thermodynamical limit ($L \rightarrow \infty$) if a special torsion $\Theta^*$ is adjusted to ensure particle-hole symmetry. Complementary to the previous research, the present paper extends our analysis to a key quantity for understanding correlations in many-body systems: the entanglement. Specifically, we investigate the average single-site entanglement $\langle S_j \rangle$ as a function of the coupling $U/t$ in Hubbard chains with up to $L=8$ sites and further examine the dependence of the per-site ground-state $\epsilon_0$ on the torsion $\Theta$ in different coupling regimes. We discuss the scaling of $\epsilon_0$ and $\langle S_j \rangle$ under $\Theta^*$ and analyse their convergence to Bethe Ansatz solution of the infinite Hubbard Hamiltonian. Additionally, we describe the exact diagonalization procedure used in our numerical calculations and show analytical calculations for the case-study of a trimer.
In the paper stochastic Volterra equations of nonscalar type in Hilbert space are studied. The aim of the paper is to provide some results on stochastic convolution and mild solutions to those Volterra equations. The motivation of the paper comes from a model of aging viscoelastic materials. The pseudo-resolvent approach is used.
The sensibility and sensitivity of the environment play a decisive role in the safe and secure operation of autonomous vehicles. This perception of the surrounding is way similar to human visual representation. The human's brain perceives the environment by utilizing different sensory channels and develop a view-invariant representation model. Keeping in this context, different exteroceptive sensors are deployed on the autonomous vehicle for perceiving the environment. The most common exteroceptive sensors are camera, Lidar and radar for autonomous vehicle's perception. Despite being these sensors have illustrated their benefit in the visible spectrum domain yet in the adverse weather conditions, for instance, at night, they have limited operation capability, which may lead to fatal accidents. In this work, we explore thermal object detection to model a view-invariant model representation by employing the self-supervised contrastive learning approach. For this purpose, we have proposed a deep neural network Self Supervised Thermal Network (SSTN) for learning the feature embedding to maximize the information between visible and infrared spectrum domain by contrastive learning, and later employing these learned feature representation for the thermal object detection using multi-scale encoder-decoder transformer network. The proposed method is extensively evaluated on the two publicly available datasets: the FLIR-ADAS dataset and the KAIST Multi-Spectral dataset. The experimental results illustrate the efficacy of the proposed method.
Let $\mathcal{H}$ be a given finite (possibly empty) family of connected graphs, each containing a cycle, and let $G$ be an arbitrary finite $\mathcal{H}$-free graph with minimum degree at least $k$. For $p \in [0,1]$, we form a $p$-random subgraph $G_p$ of $G$ by independently keeping each edge of $G$ with probability $p$. Extending a classical result of Ajtai, Koml\'os, and Szemer\'edi, we prove that for every positive $\varepsilon$, there exists a positive $\delta$ (depending only on $\varepsilon$) such that the following holds: If $p \ge \frac{1+\varepsilon}{k}$, then with probability tending to $1$ as $k \to \infty$, the random graph $G_p$ contains a cycle of length at least $n_{\mathcal{H}}(\delta k)$, where $n_{\mathcal{H}}(k)>k$ is the minimum number of vertices in an $\mathcal{H}$-free graph of average degree at least $k$. Thus in particular $G_p$ as above typically contains a cycle of length at least linear in $k$.
The two-dimensional mapping of the phonon dispersions around the $K$ point of graphite by inelastic x-ray scattering is provided. The present work resolves the longstanding issue related to the correct assignment of transverse and longitudinal phonon branches at $K$. We observe an almost degeneracy of the three TO, LA and LO derived phonon branches and a strong phonon trigonal warping. Correlation effects renormalize the Kohn anomaly of the TO mode, which exhibits a trigonal warping effect opposite to that of the electronic band structure. We determined the electron--phonon coupling constant to be 166$\rm(eV/\AA)^2$ in excellent agreement to $GW$ calculations. These results are fundamental for understanding angle-resolved photoemission, double--resonance Raman and transport measurements of graphene based systems.
The EDGES experiment has observed an excess trough ($-500^{+200}_{-500}$ mK) in the brightness temperature $T_{21}$ of the 21cm absorption line of neutral Hydrogen atom (HI) from the era of cosmic dawn ($z \simeq 17.2$). We consider possible interaction of Dark Matter and Dark Energy fluid along with the cooling off of the baryon matter by its collision with Dark Matter to explain the observed excess trough of $T_{21}$. We make use of three different Dark Matter-Dark Energy (DM-DE) interaction models to taste the viability of those models in explaining the EDGES results. The evolution of Hubble parameter is modified by DM-DE interactions and this is also addressed in this work. This in turn influences the optical depth of HI 21cm as well as the baryon temperature and thus effects the $T_{21}$ brightness temperature. In addition we also find that the DM-DE interaction enables us to explore Dark Matter with varied mass regimes and their viabilities in terms of satisfying the EDGES result.
Recent discoveries in graphene bilayers revealed that when one of the layers is rotated, superconductivity emerges. We provide an explanation for this phenomenon . We find that due to the layer rotations, the spinors are modified in such way that a repulsive interaction, becomes attractive in certain directions.   This result is obtained following a sequence of steps: when layer $2$ is rotated by an angle $\theta$ ,this rotation is equivalent to a rotation of an angle $-\theta$ of the linear momentum .Due to the discreet lattice, in layer $1$, the Fourier transform conserves the linear momentum $modulo$ the hexagonal reciprocal lattice vector . In layer $2$, due to the rotation, the linear momentum is conserved $modulo$ the $Moire$ reciprocal lattice vector . Periodicity is achieved at the $magical $ angles obtained from the condition of commensuration of the two lattices. We find that the rotations transform the spinors around the nodal points, such that a repulsive interaction becomes attractive, giving rise to superconductivity.
The interplay between the Kondo effect and disorder is studied. This is done by applying a matrix coherent potential approximation (CPA) and treating the Kondo interaction on a mean-field level. The resulting equations are shown to agree with those derived by the dynamical mean-field method (DMFT). By applying the formalism to a Bethe tree structure with infinite coordination the effect of diagonal and off-diagonal disorder are studied. Special attention is paid to the behavior of the Kondo- and the Fermi liquid temperature as function of disorder and concentration of the Kondo ions. The non monotonous dependence of these quantities is discussed.
We estimate the gravitational wave amplitude as a function of frequency produced during the creation of pulsars from the gravitational collapse of a massive star. The three main quantities needed are the magnitude of the magnetic field producing pulsar kicks, the temperature which determines the velocity of the pulsar and the duration time for the gravitational radiation.res
The multinucleon transfer reactions has been investigated within the dinuclear system model. The nucleon transfer is coupled to the dissipation of relative motion energy and angular momentum by solving a set of microscopically derived master equations. A barrier distribution approach is implemented in the model in order to including the contributions of different orientations and dynamical effects. The available data of fragment production via multinucleon transfer reactions could be understood with the model for the reactions of $^{136}$Xe + $^{198}$Pt/$^{208}$Pb near Coulomb barrier energies. It is found that the production of heavy neutron-rich nuclei weakly depends on the incident energy. However, the yields of proton-rich nuclei increase with the incident energy.
An anisotropic metallic phase dubbed electronic nematic phase bounded by two consecutive metamagnetic transitions has been reported in the bilayer ruthenate Sr3Ru2O7. It has also been shown that the nematic and the accompanying metamagnetic transitions are driven by an effective momentum-dependent quadrupole-type interaction. Here, we study the microscopic origin of such an effective interaction. To elucidate the mechanism behind the spontaneous Fermi surface distortion associated with the nematic, we identify a simple tight binding model based on t2g orbitals, spin-orbit coupling and the rotation of RuO6 octahedra as starting point, consistent with the Fermi surface obtained from recent angle-resolved photoemission data. Within an extended Hubbard model the nematic state, characterized by an anisotropy between the bands near $(\pm \pi,0)$ and $(0,\pm \pi)$, then strongly competes with ferromagnetic order but pre-empts it via a finite nearest neighbor interaction. We discuss experimental means to confirm our proposal.
The magnetic and structural properties of MnAs are studied with ab initio methods, and by mapping total energies onto a Heisenberg model. The stability of the different phases is found to depend mainly on the volume and on the amount of magnetic order, confirming previous experimental findings and phenomenological models. It is generally found that for large lattice constants the ferromagnetic state is favored, whereas for small lattice constants different antiferromagnetic states can be stabilized. In the ferromagnetic state the structure with minimal energy is always hexagonal, whereas it becomes orthorhombically distorted if there is an antiferromagnetic component in the hexagonal plane. For the paramagnetic state the stable cell is found to be orthorhombic up to a critical lattice constant of about 3.7 Angstrom, above which it remains hexagonal. This leads to the second order structural phase transition between paramagnetic states at about 400 K, where the lattice parameter increases above this critical value with rising temperature due to the thermal expansion. For the paramagnetic state an analytic approximation for the magnitude of the orthorhombic distortion as a function of the lattice constant is given. Within the mean field approximation the dependence of the Curie temperature on the volume and on the orthorhombic distortion is calculated. For orthorhombically distorted cells the Curie temperature is much smaller than for hexagonal cells. This is mainly due to the fact that some of the exchange coupling constants in the hexagonal plane become negative for distorted cells. With these results a description of the susceptibility as function of temperature is given.
We present a semi-supervised method for panoptic segmentation based on ConsInstancy regularisation, a novel strategy for semi-supervised learning. It leverages completely unlabelled data by enforcing consistency between predicted instance representations and semantic segmentations during training in order to improve the segmentation performance. To this end, we also propose new types of instance representations that can be predicted by one simple forward path through a fully convolutional network (FCN), delivering a convenient and simple-to-train framework for panoptic segmentation. More specifically, we propose the prediction of a three-dimensional instance orientation map as intermediate representation and two complementary distance transform maps as final representation, providing unique instance representations for a panoptic segmentation. We test our method on two challenging data sets of both, hardened and fresh concrete, the latter being proposed by the authors in this paper demonstrating the effectiveness of our approach, outperforming the results achieved by state-of-the-art methods for semi-supervised segmentation. In particular, we are able to show that by leveraging completely unlabeled data in our semi-supervised approach the achieved overall accuracy (OA) is increased by up to 5% compared to an entirely supervised training using only labeled data. Furthermore, we exceed the OA achieved by state-of-the-art semi-supervised methods by up to 1.5%.
We study semi-stable degenerations of quasi-Fano varieties to unions of two pieces. We conjecture that the higher rank Landau-Ginzburg models mirror to these two pieces can be glued together to lower rank Landau-Ginzburg models which are mirror to the original quasi-Fano varieties. We prove this conjecture by relating their Euler characteristics, generalized functional invariants as well as periods. We also use it to conjecture a relation between the degenerations to the normal cones and the fibrewise compactifications of higher rank Landau-Ginzburg models. Furthermore, we use it to iterate the Doran-Harder-Thompson conjecture and obtain higher codimension Calabi-Yau fibrations.
We present a novel statistical analysis aimed at deriving the intrinsic shapes and magnetic field orientations of molecular clouds using dust emission and polarization observations by the Hertz polarimeter. Our observables are the aspect ratio of the projected plane-of-the-sky cloud image, and the angle between the mean direction of the plane-of-the-sky component of the magnetic field and the short axis of the cloud image. To overcome projection effects due to the unknown orientation of the line-of-sight, we combine observations from 24 clouds, assuming that line-of-sight orientations are random and all are equally probable. Through a weighted least-squares analysis, we find that the best-fit intrinsic cloud shape describing our sample is an oblate disk with only small degrees of triaxiality. The best-fit intrinsic magnetic field orientation is close to the direction of the shortest cloud axis, with small (~24 deg) deviations toward the long/middle cloud axes. However, due to the small number of observed clouds, the power of our analysis to reject alternative configurations is limited.
Although they were first synthesized in chemistry laboratories nearly fifty years ago, the physical properties of the metals PdCoO2, PtCoO2 and PdCrO2 have only more recently been studied in detail. The delafossite structure contains triangular co-ordinated atomic layers, and electrical transport in the delafossite metals is strongly two-dimensional. Their most notable feature is their in-plane conductivity, which is amazingly high for oxide metals. At room temperature, the conductivity of non-magnetic PdCoO2 and PtCoO2 is higher per carrier than those of any alkali metal and even the most conductive elements, copper and silver. At low temperatures the best crystals have resistivities of a few n{\Omega}cm, corresponding to mean free paths of tens of microns. PdCrO2 is a frustrated antiferromagnetic metal, with magnetic scattering contributing to the resistivity at high temperatures and small gaps opening in the Fermi surface below the N\'eel temperature. There is good evidence that electronic correlations are weak in the Pd/Pt layers but strong in the Co/Cr layers; indeed the Cr layer in PdCrO2 is thought to be a Mott insulator. The delafossite metals therefore act like natural heterostructures between strongly correlated and nearly free electron sub-systems. Combined with the extremely high conductivity, they provide many opportunities to study electrical transport and other physical properties in new regimes. The purpose of this review is to describe current knowledge of these fascinating materials and set the scene for what is likely to be a considerable amount of future research.
This paper provides a discrete time LIBOR analog, which can be used for arbitrage-free discretization of Levy LIBOR models or discrete approximation of continuous time LIBOR market models. Using the work of Eberlein and Oezkan as an inspiration, we build a discrete forward LIBOR market model by starting with a discrete exponential martingale. We take this pure jump process and calculate the appropriate measure change between the forward measures. Next we prove weak convergence of the discrete analog to the continuous time LIBOR model, provided the driving process converges weakly to the continuous time one and the driving processes are PII's. This especially implies the weak convergence of the model to a Levy LIBOR market model if the driving process variables are infinitely divisible distributions. This also relates our model to an Euler discretization.