ShantanuT01/DACTYL-Pretraining huggingface dataset:
A three-terminal thermoelectric device based on a $p$-$i$-$n$ semiconductor junction is proposed, where the intrinsic region is mounted onto a, typically bosonic, thermal terminal. Remarkably, the figure of merit of the device is governed also by the energy distribution of the {\em bosons} participating in the transport processes, in addition to the electronic one. An enhanced figure of merit can be obtained when the relevant distribution is narrow and the electron-boson coupling is strong (such as for optical phonons). We study the conditions for which the figure of merit of the three-terminal junction can be greater than those of the usual thermoelectric devices made of the same material. A possible setup with a high figure of merit, based on Bi$_2$Te$_3$/Si superlattices, is proposed.
Recent observational progress has led to the establishment of the standard $\Lambda$CDM model for cosmology. This development is based on different cosmological probes that are usually combined through their likelihoods at the latest stage in the analysis. We implement here an integrated scheme for cosmological probes, which are combined in a common framework starting at the map level. This treatment is necessary as the probes are generally derived from overlapping maps and are thus not independent. It also allows for a thorough test of the cosmological model and of systematics through the consistency of different physical tracers. As a first application, we combine current measurements of the Cosmic Microwave Background (CMB) from the Planck satellite, and galaxy clustering and weak lensing from SDSS. We consider the spherical harmonic power spectra of these probes including all six auto- and cross-correlations along with the associated full Gaussian covariance matrix. This provides an integrated treatment of different analyses usually performed separately including CMB anisotropies, cosmic shear, galaxy clustering, galaxy-galaxy lensing and the Integrated Sachs-Wolfe (ISW) effect with galaxy and shear tracers. We derive constraints on $\Lambda$CDM parameters that are compatible with existing constraints and highlight tensions between data sets, which become apparent in this integrated treatment. We discuss how this approach provides a complete and powerful integrated framework for probe combination and how it can be extended to include other tracers in the context of current and future wide field cosmological surveys.
The twice-dimensionally reduced Seiberg-Witten monopole equations admit solutions depending on two real parameters (b,c) and an arbitrary analytic function f(z) determining a solution of Liouville's equation. The U(1) and manifold curvature 2-forms F and R^1_2 are invariant under fractional SL(2,R) transformations of f(z). When b=1/2 and c=0 and f(z) is the Fuchsian function uniformizing an algebraic function whose Riemann surface has genus p \geq 2 , the solutions, now SL(2,R) invariant, are the same surfaces accompanied by a U(1) bundle of c_1=\pm (p-1) and a 1-component constant spinor.
Our objective is to detect anomalies in video while also automatically explaining the reason behind the detector's response. In a practical sense, explainability is crucial for this task as the required response to an anomaly depends on its nature and severity. However, most leading methods (based on deep neural networks) are not interpretable and hide the decision making process in uninterpretable feature representations. In an effort to tackle this problem we make the following contributions: (1) we show how to build interpretable feature representations suitable for detecting anomalies with state of the art performance, (2) we propose an interpretable probabilistic anomaly detector which can describe the reason behind it's response using high level concepts, (3) we are the first to directly consider object interactions for anomaly detection and (4) we propose a new task of explaining anomalies and release a large dataset for evaluating methods on this task. Our method competes well with the state of the art on public datasets while also providing anomaly explanation based on objects and their interactions.
NJL-type effective models represent a low-energy realization of QCD and incorporate pertinent aspects such as chiral symmetry and its spontaneous breaking, the center symmetry in the heavy-quark limit as well as the axial anomaly. One such model, the Polyakov-quark-meson model for three light quark flavors, is introduced in order to study the phase structure of strongly-interacting matter. With recent high-statistics lattice QCD simulations of the finite-temperature equation of state, a detailed comparison with model results becomes accessible. Such comparisons allow to estimate volume and truncation effects of quantities, obtained on the lattice and provide possible lattice extrapolation procedures to finite chemical potential which are important to locate a critical endpoint in the QCD phase diagram.
We apply Tsuji's theory of numerically trivial fibrations to the abundance problem.
This tutorial outlines the basic theoretical concepts and tools which underpin the fundamentals of phase-coherent electron transport through single molecules. The key quantity of interest is the transmission coefficient T(E), which yields the electrical conductance, current-voltage relations, the thermopower S and the thermoelectric figure of merit ZT of single-molecule devices. Since T(E) is strongly affected by quantum interference (QI), three manifestations of QI in single-molecules are discussed, namely Mach-Zehnder interferometry, Breit-Wigner resonances and Fano resonances. A simple MATLAB code is provided, which allows the novice reader to explore QI in multi-branched structures described by a tight-binding (Huckel) Hamiltonian. More generally, the strengths and limitations of materials-specific transport modelling based on density functional theory are discussed.
A new geometrical interpretation of chiral perturbation theory based on topological QCD is presented in picture format. This work is a written summary of a talk given at NAPP 2003 in Dubrovnik, Croatia.
We report on resonant tunneling magnetoresistance via localized states through a ZnSe semiconducting barrier which can reverse the sign of the effective spin polarization of tunneling electrons. Experiments performed on Fe/ZnSe/Fe planar junctions have shown that positive, negative or even its sign-reversible magnetoresistance can be obtained, depending on the bias voltage, the energy of localized states in the ZnSe barrier and spatial symmetry. The averaging of conduction over all localized states in a junction under resonant condition is strongly detrimental to the magnetoresistance.
We introduce a new stereo formulation which does not use pixel and disparity models. Many problems in vision are treated as assigning each pixel a label. Disparities are labels for stereo. Such pixel-labeling problems are naturally represented in terms of energy minimization, where the energy function has two terms: one term penalizes solutions that inconsistent with the observed data, the other term enforces spatial smoothness. Graph cuts are one of the effi- cient methods for solving energy minimization. However, exact minimization of multi labeling problems can be performed by graph cuts only for the case with convex smoothness terms. In pixel-disparity formulation, convex smoothness terms do not generate well reconstructed 3D results. Thus, truncated linear or quadratic smoothness terms, etc. are used, where approximate energy minimization is necessary. In this paper, we introduce a new site-labeling formulation, where the sites are not pixels but lines in 3D space, labels are not disparities but depth numbers. For this formulation, visibility reasoning is naturally included in the energy function. In addition, this formulation allows us to use a small smoothness term, which does not affect the 3D results much. This makes the optimization step very simple, so we could develop an approximation method for graph cut itself (not for energy minimization) and a high performance GPU graph cut program. For Tsukuba stereo pair in Middlebury data set, we got the result in 5ms using GTX1080GPU, 19ms using GTX660GPU.
Creating realistic animations of human faces with computer graphic models is still a challenging task. It is often solved either with tedious manual work or motion capture based techniques that require specialised and costly hardware. Example based animation approaches circumvent these problems by re-using captured data of real people. This data is split into short motion samples that can be looped or concatenated in order to create novel motion sequences. The obvious advantages of this approach are the simplicity of use and the high realism, since the data exhibits only real deformations. Rather than tuning weights of a complex face rig, the animation task is performed on a higher level by arranging typical motion samples in a way such that the desired facial performance is achieved. Two difficulties with example based approaches, however, are high memory requirements as well as the creation of artefact-free and realistic transitions between motion samples. We solve these problems by combining the realism and simplicity of example-based animations with the advantages of neural face models. Our neural face model is capable of synthesising high quality 3D face geometry and texture according to a compact latent parameter vector. This latent representation reduces memory requirements by a factor of 100 and helps creating seamless transitions between concatenated motion samples. In this paper, we present a marker-less approach for facial motion capture based on multi-view video. Based on the captured data, we learn a neural representation of facial expressions, which is used to seamlessly concatenate facial performances during the animation procedure. We demonstrate the effectiveness of our approach by synthesising mouthings for Swiss-German sign language based on viseme query sequences.
In this paper we use splitting technique to estimate the probability of hitting a rare but critical set by the continuous component of a switching diffusion. Instead of following classical approach we use Wonham filter to achieve multiple goals including reduction of asymptotic variance and exemption from sampling the discrete components.
A dynamical coupled-channel formalism for processes $\pi N \to KY$ and $\gamma N \to KY$ is presented which provides a comprehensive investigation of recent data on the $\gamma p \to K^+ \Lambda$ reaction. The non-resonant interactions within the subspace $KY\oplus\pi N$ are derived from effective Lagrangians, using a unitary transformation method. The calculations of photoproduction amplitudes are simplified by casting the coupled-channel equations into a form such that the empirical $\gamma N \to \pi N$ amplitudes are input and only the parameters associated with the $KY$ channel are determined by performing $\chi^2$-fits to all of the available data for $\pi^- p \to K^\circ\Lambda, K^\circ\Sigma^\circ$ and $\gamma p \to K^+\Lambda$. Good agreement between our models and those data are obtained. In the fits to $\pi N \to KY$ channels, most of the parameters are constrained within $\pm 20%$ of the values given by the Particle Data Group and/or quark model predictions, while for $\gamma p \to K^+ \Lambda$ parameters, ranges compatible with broken $SU(6)\otimes O(3)$ symmetry are imposed. The main reaction mechanisms in $K^+ \Lambda$ photoproduction are singled out and issues related to newly suggested resonances $S_{11}$, $P_{13}$, and $D_{13}$ are studied. Results illustrating the importance of using a coupled-channel treatment are reported. Meson cloud effects on the $\gamma N \to N^*$ transitions are also discussed.
Machine learning materials properties measured by experiments is valuable yet difficult due to the limited amount of experimental data. In this work, we use a multi-fidelity random forest model to learn the experimental formation enthalpy of materials with prediction accuracy higher than the empirically corrected PBE functional (PBEfe) and meta-GGA functional (SCAN), and it outperforms the hotly studied deep neural-network based representation learning and transfer learning. We then use the model to calibrate the DFT formation enthalpy in the Materials Project database, and discover materials with underestimated stability. The multi-fidelity model is also used as a data-mining approach to find how DFT deviates from experiments by the explaining the model output.
Deuteron elastic and deep inelastic electromagnetic properties have been studied within the front-form Hamiltonian dynamics, using a Poincar\'e-covariant current operator. The deuteron elastic form factors are strongly sensitive to different realistic $N-N$ interactions, while the relevance of different nucleon form factor models is huge for $A(Q^2)$, weak for $B(Q^2)$ and negligible for the tensor polarization. The possibility to gain information on the neutron charge form factor from an analysis of $A(Q^2)$ has been investigated. The extraction of the neutron structure functions from the deuteron deep inelastic structure functions at high $x$ is largely affected by the use of our Poincar\'e-covariant relativistic approach instead of the usual impulse approximation within an instant-form approach.
We investigate mild solutions for stochastic evolution equations driven by a fractional Brownian motion (fBm) with Hurst parameter H in (1/3, 1/2] in infinite-dimensional Banach spaces. Using elements from rough paths theory we introduce an appropriate integral with respect to the fBm. This allows us to solve pathwise our stochastic evolution equation in a suitable function space.
The effect of temperature in high purity Ar (low oxygen partial pressure) on the oxidation and crystal phase evolution of c-Al0.66Ti0.33N arc-PVD coatings was investigated. High temperature tribology in Ar jet and adhesion behavior of the oxidized coating were addressed. The use of Ar protects the coating from the oxidation reactions and allowed to shed light into the details and paths of the nitride oxidation process. The c-Al0.66Ti0.33N nitrides were slightly oxidized in Ar even at high temperature. The surface chemistry evaluation shows very thin Al- and Ti-based oxide layers formation after 700C in Ar. However, the onset formation of the rutile TiO2 oxide was detected only after 900C and was clearly found by low-angle XRD diffraction after 1000C. XPS analysis of the oxidized samples at 800C indicated the formation of extremely thin layers mainly composed of mixed oxides a-Al2O3 g-Al2O3 and r-TiO2. Gradual changes in the chemical composition of the oxidized coatings observed at 900C clearly demonstrate the formation of gradient boundaries between Al-rich and Ti-rich oxy-nitride layers. After 1000C at least four oxides and oxi-nitrides layers and interlayers were found. Additionally, it is suspected that the transition oxide phases such as c-TiO, c-Al0.54Ti2.46O0.28N4.58, alpha-Al2TiO5 and TiOxNy might be precursors leading to the formation of thermodynamically stable rutile and alumina phases. Surface inspection after high temperature tribology in Ar jet showed formation of tensile cracks in the wear tracks and wear processes due to high size particle adhesion-abrasion and low size particle micro-ploughing of hard nitrides, oxi-nitrides and brittle oxide particles. Adhesion tests performed after high temperature tribology in Ar showed critical load decrease related to cohesive and adhesive damages at the contact point of the scratch track.
In quantum information processing it may be possible to have efficient computation and secure communication beyond the limitations of classical systems. In a fundamental point of view, however, evolution of quantum systems by the laws of quantum mechanics is more restrictive than classical systems, identified to a specific form of dynamics, that is, unitary transformations and, consequently, positive and completely positive maps to subsystems. This also characterizes classes of disallowed transformations on quantum systems, among which positive but not completely maps are of particular interest as they characterize entangled states, a general resource in quantum information processing. Structural physical approximation offers a systematic way of approximating those non-physical maps, positive but not completely positive maps, with quantum channels. Since it has been proposed as a method of detecting entangled states, it has stimulated fundamental problems on classifications of positive maps and the structure of Hermitian operators and quantum states, as well as on quantum measurement such as quantum design in quantum information theory. It has developed efficient and feasible methods of directly detecting entangled states in practice, for which proof-of-principle experimental demonstrations have also been performed with photonic qubit states. Here, we present a comprehensive review on quantum information processing with structural physical approximations and the related progress. The review mainly focuses on properties of structural physical approximations and their applications toward practical information applications.
Given a vector bundle with integrable connection $(V,\nabla)$ on a curve, if $V$ is not itself semistable as a vector bundle then we can iterate a construction involving modification by the destabilizing subobject to obtain a Hodge-like filtration $F^p$ which satisfies Griffiths transversality. The associated graded Higgs bundle is the limit of $(V,t\nabla)$ under the de Rham to Dolbeault degeneration. We get a stratification of the moduli space of connections, with as minimal stratum the space of opers. The strata have fibrations whose fibers are Lagrangian subspaces of the moduli space.
Recent experimental measurements for near-field radiative heat transfer between two bodies have been able to approach the gap distance within $2 \; \textrm{nm}$, where the contributions of Coulomb fluctuation and electron's tunneling are comparable. Using the nonequilibrium Green's function method in the $G_{0}W_{0}$ approximation, based on a tight-binding model, we obtain for the energy current a Caroli formula from the Meir-Wingreen formula in the local equilibrium approximation. Also, the Caroli formula is consistent with the evanescent part of the heat transfer from the theory of fluctuational electrodynamics. We go beyond the local equilibrium approximation to study the energy transfer in the crossover region from electron tunneling to Coulomb fluctuation based on a numerical calculation.
Critical behaviour of the O(n)-symmetric $\phi^{4}$-model with an antisymmetric tensor order parameter is studied by means of the field-theoretic renormalization group (RG) in the leading order of the $\varepsilon=4-d$-expansion (one-loop approximation). For $n=2$ and 3 the model is equivalent to the scalar and the O(3)-symmetric vector models, for $n\ge4$ it involves two independent interaction terms and two coupling constants. It is shown that for $n>4$ the RG equations have no infrared (IR) attractive fixed points and their solutions (RG flows) leave the stability region of the model. This means that fluctuations of the order parameter change the nature of the phase transition from the second-order type (suggested by the mean-field theory) to the first-order one. For $n=4$, the IR attractive fixed point exists and the IR behaviour is non-universal: if the coupling constants belong to the basin of attraction for the IR point, the phase transition is of the second order and the IR critical scaling regime realizes. The corresponding critical exponents $\nu$ and $\eta$ are presented in the order $\varepsilon$ and $\varepsilon^{2}$, respectively. Otherwise the RG flows pass outside the stability region and the first-order transition takes place.
In the present work we formally extend the theory of port-Hamiltonian systems to include random perturbations. In particular, suitably choosing the space of flow and effort variables we will show how several elements coming from possibly different physical domains can be interconnected in order to describe a dynamic system perturbed by general continuous semimartingale. Relevant enough, the noise does not enter into the system solely as an external random perturbation, since each port is itself intrinsically stochastic. Coherently to the classical deterministic setting, we will show how such an approach extends existing literature of stochastic Hamiltonian systems on pseudo-Poisson and pre-symplectic manifolds. Moreover, we will prove that a power-preserving interconnection of stochastic port-Hamiltonian systems is a stochastic port-Hamiltonian system as well.
We present a theory for the estimation of a scalar or a vector magnetic field by its influence on an ensemble of trapped spin polarized atoms. The atoms interact off-resonantly with a continuous laser field, and the measurement of the polarization rotation of the probe light, induced by the dispersive atom-light coupling, leads to spin-squeezing of the atomic sample which enables an estimate of the magnetic field which is more precise than that expected from standard counting statistics. For polarized light and polarized atoms, a description of the non-classical components of the collective spin angular momentum for the atoms and the collective Stokes vectors of the light-field in terms of effective gaussian position and momentum variables is practically exact. The gaussian formalism describes the dynamics of the system very effectively and accounts explicitly for the back-action on the atoms due to measurement and for the estimate of the magnetic field. Multi-component magnetic fields are estimated by the measurement of suitably chosen atomic observables and precision and efficiency is gained by dividing the atomic gas in two or more samples which are entangled by the dispersive atom-light interaction.
We present a detailed study of the collapse of a spherical matter overdensity and the non-linear growth of large scale structures in the Galileon ghost condensate (GGC) model. This model is an extension of the cubic covariant Galileon (G3) which includes a field derivative of type $(\nabla_\mu\phi\nabla^\mu\phi)^2$ in the Lagrangian. We find that the cubic term activates the modifications in the main physical quantities whose time evolution is then strongly affected by the additional term. Indeed, the GGC model shows largely mitigated effects in the linearised critical density contrast, non-linear effective gravitational coupling and the virial overdensity with respect to G3 but still preserves peculiar features with respect to the standard $\Lambda$CDM cosmological model, e.g. both the linear critical density contrast and the virial overdensity are larger than those in $\Lambda$CDM. The results of the spherical collapse model are then used to predict the evolution of the halo mass function, non-linear matter and lensing power spectra. While at low masses the GGC model presents about 10% fewer objects with respect to $\Lambda$CDM, at higher masses for $z>0$ it predicts 10% ($z=0.5$)-20% ($z=1$) more objects per comoving volume. Using a phenomenological approach to include the screening effect in the matter power spectrum, we show that the difference induced by the modifications of gravity are strongly dependent on the screening scale and that differences can be up to 20% with respect to $\Lambda$CDM. These differences translate to the lensing power spectrum where qualitatively the largest differences with respect to the standard cosmological model are for $\ell<10^3$. Depending on the screening scale, they can be up to 25% on larger angular scales and then decrease for growing $\ell$. These results are obtained for the best fit parameters from linear cosmological data for each model.