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We obtain the Courant bracket twisted simultaneously by a 2-form $B$ and a bi-vector $\theta$ by calculating the Poisson bracket algebra of the symmetry generator in the basis obtained acting with the relevant twisting matrix. It is the extension of the Courant bracket that contains well known Schouten-Nijenhuis and Koszul bracket, as well as some new star brackets. We give interpretation to the star brackets as projections on isotropic subspaces.
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high energy physics theory
|
A square matrix $M$ with real entries is said to be algebraically positive (AP) if there exists a real polynomial $p$ such that all entries of the matrix $p(M)>0$. A square sign pattern matrix $S$ is said to allow algebraic positivity if there is an algebraically positive matrix $M$ whose sign pattern class is $S$. On the other hand, $S$ is said to require algebraic positivity if any matrix $M$, having sign pattern class $S$, is algebraically positive. Motivated by open problems raised in the work of Kirkland, Qiao and Zhan (2016) on AP matrices, we list down all nonequivalent irreducible $3\times 3$ sign pattern matrices and classify each of them into three groups (i) those that require AP, (ii) those that allow but not require AP, or (iii) those that do not allow AP. We also give a necessary condition for an irreducible $n\times n$ sign pattern to allow algebraic positivity.
|
mathematics
|
In the standard model, the weak scale is the only parameter with mass dimensions. This means that the standard model itself can not explain the origin of the weak scale. On the other hand, from the results of recent accelerator experiments, except for some small corrections, the standard model has increased the possibility of being an effective theory up to the Planck scale. From these facts, it is naturally inferred that the weak scale is determined by some dynamics from the Planck scale. In order to answer this question, we rely on the multiple point criticality principle as a clue and consider the classically conformal $\mathbb{Z}_2\times \mathbb{Z}_2$ invariant two scalar model as a minimal model in which the weak scale is generated dynamically from the Planck scale. This model contains only two real scalar fields and does not contain any fermions and gauge fields. In this model, due to Coleman-Weinberg-like mechanism, one scalar field spontaneously breaks the $\mathbb{Z}_2$ symmetry with a vacuum expectation value connected with the cutoff momentum. We investigate this using the 1-loop effective potential, renormalization group and large N limit. We also investigate whether it is possible to reproduce the mass term and vacuum expectation value of the Higgs field by coupling this model with the standard model in the Higgs portal framework. In this case, the one scalar field that does not break $\mathbb{Z}_2$ can be a candidate for dark matter, and have a mass of about several TeV in appropriate parameters. On the other hand, the other scalar field breaks $\mathbb{Z}_2$ and has a mass of several tens of GeV. These results can be verified in near future experiments.
|
high energy physics theory
|
Nanophotonics finds ever broadening applications requiring complex component designs with a large number of parameters to be simultaneously optimized. Recent methodologies employing optimization algorithms commonly focus on a single design objective, provide isolated designs, and do not describe how the design parameters influence the device behaviour. Here we propose and demonstrate a machine-learning-based approach to map and characterize the multi-parameter design space of nanophotonic components. Pattern recognition is used to reveal the relationship between an initial sparse set of optimized designs through a significant reduction in the number of characterizing parameters. This defines a design sub-space of lower dimensionality that can be mapped faster by orders of magnitude than the original design space. As a result, multiple performance criteria are clearly visualized, revealing the interplay of the design parameters, highlighting performance and structural limitations, and inspiring new design ideas. This global perspective on high-dimensional design problems represents a major shift in how modern nanophotonic design is approached and provides a powerful tool to explore complexity in next-generation devices.
|
physics
|
Tilted and warped discs inside tilted dark matter haloes are predicted from numerical and semi-analytical studies. In this paper, we use deep imaging to demonstrate the likely existence of tilted outer structures in real galaxies. We consider two SB0 edge-on galaxies, NGC4469 and NGC4452, which exhibit apparent tilted outer discs with respect to the inner structure. In NGC4469, this structure has a boxy shape, inclined by $\Delta$PA$\approx$3$^{\circ}$ with respect to the inner disc, whereas NGC4452 harbours a discy outer structure with $\Delta$PA$\approx$6$^{\circ}$. In spite of the different shapes, both structures have surface brightness profiles close to exponential and make a large contribution ($\sim30$%) to the total galaxy luminosity. In the case of NGC4452, we propose that its tilted disc likely originates from a former fast tidal encounter (probably with IC3381). For NGC4469, a plausible explanation may also be galaxy harassment, which resulted in a tilted or even a tumbling dark matter halo. A less likely possibility is accretion of gas-rich satellites several Gyr ago. New deep observations may potentially reveal more such galaxies with tilted outer structures, especially in clusters. We also consider galaxies, mentioned in the literature, where a central component (a bar or a bulge) is tilted with respect to the stellar disc. According to our numerical simulations, one of the plausible explanations of such observed "tilts" of the bulge/bar is a projection effect due to a not exactly edge-on orientation of the galaxy coupled with a skew angle of the triaxial bulge/bar.
|
astrophysics
|
We present an Automatic Relevance Determination prior Bayesian Neural Network(BNN-ARD) weight l2-norm measure as a feature importance statistic for the model-x knockoff filter. We show on both simulated data and the Norwegian wind farm dataset that the proposed feature importance statistic yields statistically significant improvements relative to similar feature importance measures in both variable selection power and predictive performance on a real world dataset.
|
statistics
|
The energy dissipation rate in a nonequilibirum reaction system can be determined by the reaction rates in the underlying reaction network. By developing a coarse-graining process in state space and a corresponding renormalization procedure for reaction rates, we find that energy dissipation rate has an inverse power-law dependence on the number of microscopic states in a coarse-grained state. The dissipation scaling law requires self-similarity of the underlying network, and the scaling exponent depends on the network structure and the flux correlation. Implications of this inverse dissipation scaling law for active flow systems such as microtubule-kinesin mixture are discussed.
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condensed matter
|
Change detection for remote sensing images is widely applied for urban change detection, disaster assessment and other fields. However, most of the existing CNN-based change detection methods still suffer from the problem of inadequate pseudo-changes suppression and insufficient feature representation. In this work, an unsupervised change detection method based on Task-related Self-supervised Learning Change Detection network with smooth mechanism(TSLCD) is proposed to eliminate it. The main contributions include: (1) the task-related self-supervised learning module is introduced to extract spatial features more effectively. (2) a hard-sample-mining loss function is applied to pay more attention to the hard-to-classify samples. (3) a smooth mechanism is utilized to remove some of pseudo-changes and noise. Experiments on four remote sensing change detection datasets reveal that the proposed TSLCD method achieves the state-of-the-art for change detection task.
|
electrical engineering and systems science
|
Bound states in the continuum (BICs) in photonic crystals represent the unique solutions of wave equations possessing an infinite quality-factor. We design a type of bilayer photonic crystal and study the influence of symmetry and coupling between TE and TM polarizations on BICs. The BIC modes possess $C_{3v}$ symmetry in the x-y plane while the mirror-flip symmetry in the z-direction is broken, and they provide selective coupling into different layers by varying frequency. The enhanced TE-TM coupling due to broken mirror-flip symmetry in the z-direction gives rise to high-Q factor BIC states with unique spatial characteristics. We show the emergence of such BIC states even in the presence of coupling between the TE- and TM-like modes, which is different from the existing single polarization BIC models. We propose to study BICs in multilayer systems, and the results may be helpful in designing photonic settings to observe and manipulate BICs with various symmetries and polarizations for practical applications.
|
physics
|
Federated learning (FL) in a bandwidth-limited network with energy-limited user equipments (UEs) is under-explored. In this paper, to jointly save energy consumed by the battery-limited UEs and accelerate the convergence of the global model in FL for the bandwidth-limited network, we propose the sliding differential evolution-based scheduling (SDES) policy. To this end, we first formulate an optimization that aims to minimize a weighted sum of energy consumption and model training convergence. Then, we apply the SDES with parallel differential evolution (DE) operations in several small-scale windows, to address the above proposed problem effectively. Compared with existing scheduling policies, the proposed SDES performs well in reducing energy consumption and the model convergence with lower computational complexity.
|
computer science
|
Modern statistical learning techniques have often emphasized prediction performance over interpretability, giving rise to "black box" models that may be difficult to understand, and to generalize to other settings. We conceptually divide a prediction model into interpretable and non-interpretable portions, as a means to produce models that are highly interpretable with little loss in performance. Implementation of the model is achieved by considering separability of the interpretable and non-interpretable portions, along with a doubly penalized procedure for model fitting. We specify conditions under which convergence of model estimation can be achieved via cyclic coordinate ascent, and the consistency of model estimation holds. We apply the methods to datasets for microbiome host trait prediction and a diabetes trait, and discuss practical tradeoff diagnostics to select models with high interpretability.
|
statistics
|
Imagine a MIMO communication system that fully exploits the propagation characteristics offered by an electromagnetic channel and ultimately approaches the limits imposed by wireless communications. This is the concept of Holographic MIMO communications. Accurate and tractable channel modeling is critical to understanding its full potential. Classical stochastic models used by communications theorists are derived under the electromagnetic far-field assumption. However, such assumption breaks down when large (compared to the wavelength) antenna arrays are considered - as envisioned in future wireless communications. In this paper, we start from the first principles of wave propagation and provide a Fourier plane-wave series expansion of the channel response, which fully captures the essence of electromagnetic propagation in arbitrary scattering and is also valid in the (radiative) near-field. The expansion is based on the Fourier spectral representation and has an intuitive physical interpretation, as it statistically describes the angular coupling between source and receiver. When discretized, it leads to a low-rank semi-unitarily equivalent approximation of the spatial electromagnetic channel in the angular domain. The developed channel model is used to compute the ergodic capacity of a Holographic MIMO system with different degrees of channel state information.
|
computer science
|
Discretization of continuous-time diffusion processes is a widely recognized method for sampling. However, the canonical Euler-Maruyama discretization of the Langevin diffusion process, also named as Langevin Monte Carlo (LMC), studied mostly in the context of smooth (gradient-Lipschitz) and strongly log-concave densities, a significant constraint for its deployment in many sciences, including computational statistics and statistical learning. In this paper, we establish several theoretical contributions to the literature on such sampling methods. Particularly, we generalize the Gaussian smoothing, approximate the gradient using p-generalized Gaussian smoothing and take advantage of it in the context of black-box sampling. We first present a non-strongly concave and weakly smooth black-box LMC algorithm, ideal for practical applicability of sampling challenges in a general setting.
|
statistics
|
In recent years, transition metal dichalcogenides (TMDs) have garnered great interest as topological materials -- monolayers of centrosymmetric $\beta$-phase TMDs have been identified as 2D topological insulators (TIs), and bulk crystals of noncentrosymmetric $\gamma$-phase MoTe$_2$ and WTe$_2$ have been identified as type-II Weyl semimetals. However, ARPES and STM probes of these TMDs have revealed huge, "arc-like" surface states that overwhelm, and are sometimes mistaken for, the much smaller topological surface Fermi arcs of bulk type-II Weyl points. In this letter, we use first-principles calculations and (nested) Wilson loops to analyze the bulk and surface electronic structure of both $\beta$- and $\gamma$-MoTe$_2$, finding that $\beta$-MoTe$_2$ ($\gamma$-MoTe$_2$ gapped with symmetry-preserving distortion) is an inversion-symmetry-indicated $\mathbb{Z}_{4}$-nontrivial ($noncentrosymmetric, non$-$symmetry$-$indicated$) higher-order TI (HOTI) driven by double band inversion. Both structural phases of MoTe$_2$ exhibit the same surface features as WTe$_2$, revealing that the large Fermi arcs are in fact not topologically trivial, but are rather the characteristic split and gapped fourfold surface states of a HOTI. We also show that, when the effects of SOC are neglected, $\beta$-MoTe$_2$ is a nodal-line semimetal with $\mathbb{Z}_{2}$-nontrivial monopole nodal lines (MNLSM). This finding confirms that MNLSMs driven by double band inversion are the weak-SOC limit of HOTIs, implying that MNLSMs are higher-order topological $semimetals$ with flat-band-like hinge states, which we find to originate from the corner modes of 2D "fragile" TIs.
|
condensed matter
|
In this work we propose an autoencoder based framework for simultaneous reconstruction and classification of biomedical signals. Previously these two tasks, reconstruction and classification were treated as separate problems. This is the first work to propose a combined framework to address the issue in a holistic fashion. Reconstruction techniques for biomedical signals for tele-monitoring are largely based on compressed sensing (CS) based method, these are designed techniques where the reconstruction formulation is based on some assumption regarding the signal. In this work, we propose a new paradigm for reconstruction we learn to reconstruct. An autoencoder can be trained for the same. But since the final goal is to analyze classify the signal we learn a linear classification map inside the autoencoder. The ensuing optimization problem is solved using the Split Bregman technique. Experiments have been carried out on reconstruction and classification of ECG arrhythmia classification and EEG seizure classification signals. Our proposed tool is capable of operating in a semi-supervised fashion. We show that our proposed method is better and more than an order magnitude faster in reconstruction than CS based methods; it is capable of real-time operation. Our method is also better than recently proposed classification methods. Significance: This is the first work offering an alternative to CS based reconstruction. It also shows that representation learning can yield better results than hand-crafted features for signal analysis.
|
electrical engineering and systems science
|
The weighted \emph{Sitting Closer to Friends than Enemies} (SCFE) problem is to find an injection of the vertex set of a given weighted graph into a given metric space so that, for every pair of incident edges with different weight, the end vertices of the heavier edge are closer than the end vertices of the lighter edge. The \emph{Seriation} problem is to find a simultaneous reordering of the rows and columns of a symmetric matrix such that the entries are monotone nondecreasing in rows and columns when moving towards the diagonal. If such a reordering exists, it is called a \emph{Robinson} ordering. In this work, we establish a connection between the SCFE problem and the Seriation problem. We show that if the \emph{extended adjacency matrix} of a given weighted graph $G$ has no Robinson ordering then $G$ has no injection in $\mathbb{R}$ that solves the SCFE problem. On the other hand, if the extended adjacency matrix of $G$ has a Robinson ordering, we construct a polyhedron that is not empty if and only if there is an injection of the vertex set of $G$ in $\mathbb{R}$ that solves the SCFE problem. As a consequence of these results, we conclude that deciding the existence of (and constructing) such an injection in $\mathbb{R}$ for a given \emph{complete} weighted graph can be done in polynomial time. On the other hand, we show that deciding if an \emph{incomplete} weighted graph has such an injection in $\mathbb{R}$ is NP-Complete.
|
mathematics
|
A unified formalism was developed in [S. Adhikary et. al., arXiv:1710.04371 [quant-ph]], for describing non-classicality of states by introducing pseudo projection operators in which both quantum logic and quantum probability are naturally embedded. In this paper we show, as the first practical application, how non-locality and entanglement emerge as two such important manifestations. It provides a perspective complementary to (i) the understanding of them that we have currently (in terms of LHV models) and (ii) to the algebraic approaches employed. The work also makes it possible to obtain, in a systematic manner, an infinite number of conditions for non-classicality, for future applications.
|
quantum physics
|
Strong-Disorder Renormalization Group (SDRG), despite being a relatively simple real-space renormalization procedure, provides in principle exact results on the critical properties at the infinite-randomness fixed point of random quantum spin chains. Numerically, SDRG can be efficiently implemented as a renormalization of Matrix Product Operators (MPO-RG). By considering larger blocks than SDRG, MPO-RG was recently used to compute non-critical quantities of finite chains that are inaccessible to SDRG. In this work, the accuracy of this approach is studied and two simple and fast improvements are proposed. The accuracy on the ground state energy is improved by a factor at least equal to 4 for the random Ising chain in a transverse field. Finally, the proposed algorithms are shown to yield Binder cumulants of the 3-color random Ashkin-Teller chain that are compatible with a second-order phase transition while a first-order one is predicted by the original MPO-RG algorithm.
|
condensed matter
|
In this paper we presented the modified algorithm for astrometric reduction of the wide-field images. This algorithm is based on the iterative using of the method of ordinary least squares (OLS) and statistical Student t-criterion. The proposed algorithm provides the automatic selection of the most probabilistic reduction model. This approach allows eliminating almost all systematic errors that are caused by imperfections in the optical system of modern large telescopes.
|
astrophysics
|
As elderly population grows, social and health care begin to face validation challenges, in-home monitoring is becoming a focus for professionals in the field. Governments urgently need to improve the quality of healthcare services at lower costs while ensuring the comfort and independence of the elderly. This work presents an in-home monitoring approach based on off-the-shelf WiFi, which is low-costs, non-wearable and makes all-round daily healthcare information available to caregivers. The proposed approach can capture fine-grained human pose figures even through a wall and track detailed respiration status simultaneously by off-the-shelf WiFi devices. Based on them, behavioral data, physiological data and the derived information (e.g., abnormal events and underlying diseases), of the elderly could be seen by caregivers directly. We design a series of signal processing methods and a neural network to capture human pose figures and extract respiration status curves from WiFi Channel State Information (CSI). Extensive experiments are conducted and according to the results, off-the-shelf WiFi devices are capable of capturing fine-grained human pose figures, similar to cameras, even through a wall and track accurate respiration status, thus demonstrating the effectiveness and feasibility of our approach for in-home monitoring.
|
electrical engineering and systems science
|
Strange metals possess highly unconventional transport characteristics, such as a linear-in-temperature ($T$) resistivity, an inverse Hall angle that varies as $T^2$ and a linear-in-field ($H$) magnetoresistance. Identifying the origin of these collective anomalies has proved profoundly challenging, even in materials such as the hole-doped cuprates that possess a simple band structure. The prevailing dogma is that strange metallicity in the cuprates is tied to a quantum critical point at a doping $p*$ inside the superconducting dome. Here, we study the high-field in-plane magnetoresistance of two superconducting cuprate families at doping levels beyond $p*$. At all dopings, the magnetoresistance exhibits quadrature scaling and becomes linear at high $H/T$ ratios. Moreover, its magnitude is found to be much larger than predicted by conventional theory and insensitive to both impurity scattering and magnetic field orientation. These observations, coupled with analysis of the zero-field and Hall resistivities, suggest that despite having a single band, the cuprate strange metal phase hosts two charge sectors, one containing coherent quasiparticles, the other scale-invariant `Planckian' dissipators.
|
condensed matter
|
We study the category of modules admitting compatible actions of the Lie algebra $\mathcal{V}$ of vector fields on an affine space and the algebra $\mathcal{A}$ of polynomial functions. We show that modules in this category which are finitely generated over $\mathcal{A}$, are free. We also show that this pair of compatible actions is equivalent to commuting actions of the algebra of differential operators and the Lie algebra of vector fields vanishing at the origin. This allows us to construct explicit realizations of such modules as gauge modules.
|
mathematics
|
We calculate the mass and residue of the newly observed $\Omega_c(3000)$ and $\Omega_c(3066)$ states with quantum numbers $J^P = \frac{1}{2}^{-}$ and $\frac{3}{2}^{-}$ within QCD sum rules. Our predictions on masses are in good agreement with the experimental results.
|
high energy physics phenomenology
|
Using the concept of non-degenerate Bell inequality, we show that quantum entanglement, the critical resource for various quantum information processing tasks, can be quantified for any unknown quantum states in a semi-device-independent manner, where the quantification is based on the experimentally obtained probability distribution and beforehand knowledge on quantum dimension only. Specifically, as an application of our approach on multi-level systems, we experimentally quantify the entanglement of formation and the entanglement of distillation for qutrit-qutrit quantum systems. In addition, to demonstrate our approach for multi-partite systems, we further quantify the geometry measure of entanglement of three-qubit quantum systems. Our results supply a general way to reliably quantify entanglement in multi-level and multi-partite systems, thus paving the way to characterize many-body quantum systems by quantifying involved entanglement.
|
quantum physics
|
In this article, we utilize machine learning to dynamically determine if a point on the computational grid requires implicit numerical dissipation for large eddy simulation (LES). The decision making process is learnt through \emph{a priori} training on quantities derived from direct numerical simulation (DNS) data. In particular, we compute eddy-viscosities obtained through the coarse graining of DNS quantities and utilize their distribution to categorize areas that require dissipation. If our learning determines that closure is necessary, an upwinded scheme is utilized for computing the non-linear Jacobian. In contrast, if it is determined that closure is unnecessary, a symmetric and second-order accurate energy and enstrophy preserving Arakawa scheme is utilized instead. This results in a closure framework that precludes the specification of any model-form for the small scale contributions of turbulence but deploys an appropriate numerical dissipation from explicit closure driven hypotheses. This methodology is deployed for the Kraichnan turbulence test-case and assessed through various statistical quantities such as angle-averaged kinetic energy spectra and vorticity structure functions. Our framework thus establishes a direct link between the use of explicit LES ideologies for closure and numerical scheme-based modeling of turbulence leading to improved statistical fidelity of \emph{a posteriori} simulations.
|
physics
|
We present the visual orbit of the double-lined spectroscopic binary HD 224355 from interferometric observations with the CHARA Array, as well as an updated spectroscopic analysis using echelle spectra from the Apache Point Observatory 3.5m telescope. By combining the visual and spectroscopic orbital solutions, we find the binary components to have masses of M1 = 1.626 +/- 0.005 Msun and M2 = 1.608 +/- 0.005 Msun, and a distance of d = 63.98 +/- 0.26 pc. Using the distance and the component angular diameters found by fitting spectrophotometry from the literature to spectral energy distribution models, we estimate the stellar radii to be R1 = 2.65 +/- 0.21 Rsun and R2 = 2.47 +/- 0.23 Rsun. We then compare these observed fundamental parameters to the predictions of stellar evolution models, finding that both components are evolved towards the end of the main sequence with an estimated age of 1.9 Gyr.
|
astrophysics
|
A general field theory for classical particle-field systems is developed. Compared with the standard classical field theory, the distinguish feature of a classical particle-field system is that the particles and fields reside on different manifolds. The fields are defined on the 4D space-time, whereas each particle's trajectory is defined on the 1D time-axis. As a consequence, the standard Noether's procedure for deriving local conservation laws in space-time from symmetries is not applicable without modification. To overcome this difficulty, a weak Euler-Lagrange equation for particles is developed on the 4D space-time, which plays a pivotal role in establishing the connections between symmetries and local conservation laws in space-time. Especially, the non-vanishing Euler derivative in the weak Euler-Lagrangian equation generates a new current in the conservation laws. Several examples from plasma physics are studied as special cases of the general field theory. In particular, the relations between the rotational symmetry and angular momentum conservation for the Klimontovich-Poisson system and the Klimontovich-Darwin system are established.
|
physics
|
A model for the $B^\pm \to \pi^-\pi^+\pi^\pm$ decay amplitude is proposed to study the large CP violation observed at the high mass region of the Dalitz plane. A short distance $ b \to u $ amplitude with the weak phase $\gamma$ is considered together with the contribution of a hadronic charm loop and a s-wave $D\bar{D}\to \pi\pi$ rescattering. In the model, the $\chi_c^0$ appears as a narrow resonant state of the $D\bar D$ system below threshold. It is introduced in an unitary two channel S-matrix model of the coupled $D\bar D$ and $\pi\pi$ channels, where the $\chi_c^0$ complex pole in $D\bar D$ channel shows its signature in the off-diagonal matrix element and in the associated $D\bar{D}\to \pi\pi$ transition amplitude. The strong phase of the resulting decay amplitude has a sharp sign change at the $D\bar D$ threshold, changing the sign of the CP asymmetry, as it is observed in the data. We conclude that the hadronic charm loop and rescattering mechanism are relevant to the broadening of the CP asymmetry around the $\chi_c^0$ resonance in the $\pi\pi$ channel. This novel mechanism provides a possible interpretation of the CP asymmetry defier experimental result presented by the LHCb collaboration for the $B^\pm \to \pi^-\pi^+\pi^\pm$ decay in the high mass region.
|
high energy physics phenomenology
|
Future wireless networks are expected to evolve towards an intelligent and software reconfigurable paradigm enabling ubiquitous communications between humans and mobile devices. They will be also capable of sensing, controlling, and optimizing the wireless environment to fulfill the visions of low-power, high-throughput, massively-connected, and low-latency communications. A key conceptual enabler that is recently gaining increasing popularity is the Holographic Multiple Input Multiple Output Surface (HMIMOS) that refers to a low-cost transformative wireless planar structure comprising of sub-wavelength metallic or dielectric scattering particles, which is capable of impacting electromagnetic waves according to desired objectives. In this article, we provide an overview of HMIMOS communications by introducing the available hardware architectures for reconfigurable such metasurfaces and their main characteristics, as well as highlighting the opportunities and key challenges in designing HMIMOS-enabled communications.
|
computer science
|
It is well known that energy-time entanglement can enhance two photon absorption (TPA) by simultaneously optimizing the two photon resonance and the coincidence rate of photons at the absorber. However, the precise relation between entanglement and the TPA rate depends on the coherences of intermediate states involved in the transition, making it a rather challenging task to identify universal features of TPA processes. In the present paper, we show that the theory can be simplified greatly by separating the two photon resonance from the temporal dynamics of the intermediate levels. The result is a description of the role of entanglement in the TPA process by a one-dimensional coherence in the Hilbert space defined by the arrival time difference of the two photons. Transformation into the frequency difference basis results in Kramers-Kronig relations for the TPA process, separating off-resonant contributions of virtual levels from resonant contributions. In particular, it can be shown that off-resonant contributions are insensitive to the frequencies of the associated virtual states, indicating that virtual-state spectroscopy of levels above the final two photon excited state is not possible.
|
quantum physics
|
We present new Doppler images of both components of the double-lined binary $\sigma^{2}$ CrB, based on the high-resolution spectroscopic data collected during 11 nights in 2015 March--April. The observed spectra form two independent data sets with sufficient phase coverage. We apply the least-squares deconvolution to all observed spectra to obtain high signal-to-noise mean profiles, from which we derive the Doppler images of both components of $\sigma^{2}$ CrB simultaneously. The surfaces of both F9 and G0 components are dominated by pronounced polar spots. The F9 component exhibits a weak spot at latitude 30$^{\circ}$ and its mid-to-low latitudes are relatively featureless. The G0 star shows an extended spot structure at latitude 30$^{\circ}$, and its surface spot coverage is larger than that of the F9 star, which suggests a higher level of magnetic activity. With the cross-correlation method, we derive a solar-like surface differential rotation on the G0 star of $\sigma^{2}$ CrB for the first time, and the surface shear rate is $\Delta \Omega = 0.180 \pm 0.004$ rad d$^{-1}$ and $\alpha = \Delta \Omega / \Omega_{eq} = 0.032 \pm 0.001$. We do not obtain a clear surface shear law for the F9 star due to the lack of mid-to-low latitude features, but detect a systematic longitude shift of high-latitude spots, which indicates a slower rotation with respect to the co-rotating frame.
|
astrophysics
|
Donor-modified TiO 2 nanoparticles are interesting hybrid systems shifting the absorption edge of this semiconductor from the ultra-violet to the visible or infrared light spectrum, which is a benefit for several applications ranging from photochemistry, photocatalysis, photovoltaics, or photodynamic therapy. Here, we investigate the absorption properties of two catechol-like molecules, i.e. dopamine and DOPAC ligands, when anchored to a spherical anatase TiO 2 nanoparticle of realistic size (2.2 nm), by means of time-dependent density functional theory calculations. By the differential absorbance spectra with the bare nanoparticle, we show how it is possible to determine the injection mechanism. Since new low-energy absorption peaks are observed, we infer a direct charge transfer injection, which, unexpectedly, does not involve the lowest energy conduction band states. We also find that the more perpendicular the molecular benzene ring is to the surface, the more intense is the absorption, which suggests aiming at high molecular packing in the synthesis. Through a comparative investigation with a flat TiO 2 surface model, we unravel both the curvature and coverage effects.
|
condensed matter
|
We formulate the problem of neural network optimization as Bayesian filtering, where the observations are the backpropagated gradients. While neural network optimization has previously been studied using natural gradient methods which are closely related to Bayesian inference, they were unable to recover standard optimizers such as Adam and RMSprop with a root-mean-square gradient normalizer, instead getting a mean-square normalizer. To recover the root-mean-square normalizer, we find it necessary to account for the temporal dynamics of all the other parameters as they are geing optimized. The resulting optimizer, AdaBayes, adaptively transitions between SGD-like and Adam-like behaviour, automatically recovers AdamW, a state of the art variant of Adam with decoupled weight decay, and has generalisation performance competitive with SGD.
|
statistics
|
We discuss the effect of sequential error injection on information leakage under a network code. We formulate a network code for the single transmission setting and the multiple transmission setting. Under this formulation, we show that the eavesdropper cannot improve the power of eavesdropping by sequential error injection when the operations in the network are linear operations. We demonstrate the usefulness of this reduction theorem by applying a concrete example of network.
|
computer science
|
We unravel the nonequilibrium correlated quantum quench dynamics of an impurity traveling through a harmonically confined Bose-Einstein condensate in one-dimension. For weak repulsive interspecies interactions the impurity oscillates within the bosonic gas. At strong repulsions and depending on its prequench position the impurity moves towards an edge of the bosonic medium and subsequently equilibrates. This equilibration being present independently of the initial velocity, the position and the mass of the impurity is inherently related to the generation of entanglement in the many-body system. Focusing on attractive interactions the impurity performs a damped oscillatory motion within the bosonic bath, a behavior that becomes more evident for stronger attractions. To elucidate our understanding of the dynamics an effective potential picture is constructed. The effective mass of the emergent quasiparticle is measured and found to be generically larger than the bare one, especially for strong attractions. In all cases, a transfer of energy from the impurity to the bosonic medium takes place. Finally, by averaging over a sample of simulated in-situ single-shot images we expose how the single-particle density distributions and the two-body interspecies correlations can be probed.
|
quantum physics
|
We consider conditional photonic non-Gaussian state preparation using multimode Gaussian states and photon-number-resolving detectors in the presence of photon loss. While simulation of such state preparation is often computationally challenging, we show that obtaining the required multimode Gaussian state Fock matrix elements can be reduced to the computation of matrix functions known as loop hafnians, and develop a tailored algorithm for their calculation that is faster than previously known methods. As an example of its utility, we use our algorithm to explore the loss parameter space for three specific non-Gaussian state preparation schemes: Fock state heralding, cat state heralding, and weak cubic-phase state heralding. We confirm that these schemes are fragile with respect to photon loss, yet find that there are regions in the loss parameter space that are potentially accessible in an experimental setting which correspond to heralded states with non-zero non-Gaussianity.
|
quantum physics
|
The "pole-skipping" phenomenon reflects that the retarded Green's function is not unique at a pole-skipping point in momentum space $(\omega,k)$. We explore the universality of the pole-skipping in different geometries. In holography, near horizon analysis of the bulk equation of motion is a simpler way to derive a pole-skipping point and we use this method in Lifshitz, AdS$_2$ and Rindler geometries. We also study the complex hydrodynamic analyses and find that the dispersion relations in terms of dimensionless variables $\frac{\omega}{2\pi T}$ and $\frac{\vert k\vert}{2\pi T}$ pass through pole-skipping points $(\frac{\omega_n}{2\pi T}, \frac{\vert k_n\vert}{2\pi T}$) at small $\omega$ and $k$ in Lifshitz background. We verify that the position of the pole-skipping points does not depend on the standard quantization or alternative quantization in the boundary theory in AdS$_2\times\mathbb{R}^{d-1}$ geometry. In Rindler geometry, we cannot find the corresponding Green's function to calculate pole-skipping points because it is difficult to impose the boundary condition. However we can obtain "special points" near horizon where bulk equations of motion have two incoming solutions. These "special points" correspond to nonunique of the Green's function in physical meaning from the perspective of holography.
|
high energy physics theory
|
This paper presents the definition and implementation of a quantum computer architecture to enable creating a new computational device - a quantum computer as an accelerator In this paper, we present explicitly the idea of a quantum accelerator which contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. Important to realise is that qubits are defined as perfect qubits, implying they do not decohere and perform good quantum gate operations. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL. We also have to start thinking about how to verify, validate and test the quantum software such that the compiler generates a correct version of the quantum circuit. The OpenQL compiler translates the program to a common assembly language, called cQASM. We need to develop a quantum operating system that manages all the hardware of the micro-architecture. The layer below the micro-architecture is responsible of the mapping and routing of the qubits on the topology such that the nearest-neighbour-constraint can be be respected. At any moment in the future when we are capable of generating multiple good qubits, the compiler can convert the cQASM to generate the eQASM, which is executable on a particular experimental device incorporating the platform-specific parameters. This way, we are able to distinguish clearly the experimental research towards better qubits, and the industrial and societal applications that need to be developed and executed on a quantum device.
|
quantum physics
|
We characterize equilibrium properties and relaxation dynamics of a two-dimensional lattice containing, at each site, two particles connected by a double-well potential (dumbbell). Dumbbells are oriented in the orthogonal direction with respect to the lattice plane and interact with each other through a Lennard-Jones potential truncated at the nearest neighbor distance. We show that the system's equilibrium properties are accurately described by a two-dimensional Ising model with an appropriate coupling constant. Moreover, we characterize the coarsening kinetics by calculating the cluster size as a function of time and compare the results with Monte Carlo simulations based on Glauber or reactive dynamics rate constants.
|
condensed matter
|
Let $F$ be a non-archimedean local field and $G$ the $F$-points of a connected simply-connected reductive group over $F$. In this paper, we study the unipotent $\ell$-blocks of $G$. To that end, we introduce the notion of $(d,1)$-series for finite reductive groups. These series form a partition of the irreducible representations and are defined using Harish-Chandra theory and $d$-Harish-Chandra theory. The $\ell$-blocks are then constructed using these $(d,1)$-series, with $d$ the order of $q$ modulo $\ell$, and consistent systems of idempotents on the Bruhat-Tits building of $G$. We also describe the stable $\ell$-block decomposition of the depth zero category of an unramified classical group.
|
mathematics
|
In-flight Internet connectivity is a necessity for aircraft passengers as well as aircraft systems. It is challenging to satisfy required quality of service (QoS) levels for flows within aircraft due to the large number of users and the highly varying air to ground (A2G) link capacities composed of satellite and direct air to ground communication (DA2GC). To represent service quality variations, we propose models for the generated traffic flows from aircraft and variations in A2G links. We present three different forwarding schemes based on priority, delay requirements and history of the dropped flows metrics. Forwarding schemes schedule the flows in real time by choosing either satellite or direct air to ground link depending on the delay and capacity requirements of flows to maximize the number of accepted flows with required QoS guarantees in terms of dropped packets and delay. Also, the effect of local caching is studied to fully satisfy the QoS requirement of flows in simulated flights. We implement the forwarding procedures and caching in ns-3 and test their performance in a current connectivity scenario of 100 Mbps capacity for both the satellite spot and ground base station in a one-hour flight. Our study shows that although the forwarding procedure based on a combination of priority and delay requirement has relatively better performance than the other schemes, which are based on priority only and weighted average of all metrics, in dropped packet percentage and delay, the current connectivity setup is not able to satisfy all QoS requirements. Furthermore, at least 0.9 cache hit rate is required to satisfy all flows for at least 50% of simulated flights.
|
electrical engineering and systems science
|
We establish an isomorphism between the Khovanov-Rozansky triply graded link homology and the geometric triply graded homology due to the authors. Hence we provide an interpretation of the Khovanov-Rozansky homology of the closure of a braid $\beta$ as the space of derived sections of a $\mathbb{C}^*\times \mathbb{C}^*$- equivariant sheaf $Tr(\beta)$ on the Hilbert scheme $Hilb_n(\mathbb{C}^2)$, thus proving a version of Gorsky-Negut-Rasmussen conjecture \cite{GorskyNegutRasmussen16}. As a consequence we prove that Khovanov-Rozansky homology of knots satisfies the $q\to t/q$ symmetry conjectured by Dunfield-Gukov-Rasmussen \cite{DunfieldGukovRasmussen06}. We also apply our main result to compute the Khovanov-Rozansky homology of torus links.
|
mathematics
|
The fragility of quantum systems makes them ideally suited for sensing applications at the nanoscale. However, interpreting the output signal of a qubit-based sensor is generally complicated by background clutter due to out-of-band spectral leakage, as well as ambiguity in signal origin when the sensor is operated with noisy hardware. We present a sensing protocol based on optimally band-limited "Slepian functions" that can overcome these challenges, by providing narrowband sensing of ambient dephasing noise, coupling additively to the sensor along the ${z}$-axis, while permitting isolation of the target noise spectrum from other contributions coupling along a different axis. This is achieved by introducing a finite-difference control modulation, which linearizes the sensor's response and affords tunable band-limited "windowing" in frequency. Building on these techniques, we experimentally demonstrate two spectral estimation capabilities using a trapped-ion qubit sensor. We first perform efficient experimental reconstruction of a "mixed" dephasing spectrum, composed of a broadband $1/f$-type spectrum with discrete spurs. We then demonstrate the simultaneous reconstruction of overlapping dephasing and control noise spectra from a single set of measurements, in a setting where the two noise sources contribute equally to the sensor's response. Our approach provides a direct means to augment quantum-sensor performance in the presence of both complex broadband noise environments and imperfect control signals, by optimally complying with realistic time-bandwidth constraints.
|
quantum physics
|
One of the challenging questions in time series forecasting is how to find the best algorithm. In recent years, a recommender system scheme has been developed for time series analysis using a meta-learning approach. This system selects the best forecasting method with consideration of the time series characteristics. In this paper, we propose a novel approach to focusing on some of the unanswered questions resulting from the use of meta-learning in time series forecasting. Therefore, three main gaps in previous works are addressed including, analyzing various subsets of top forecasters as inputs for meta-learners; evaluating the effect of forecasting error measures; and assessing the role of the dimensionality of the feature space on the forecasting errors of meta-learners. All of these objectives are achieved with the help of a diverse state-of-the-art pool of forecasters and meta-learners. For this purpose, first, a pool of forecasting algorithms is implemented on the NN5 competition dataset and ranked based on the two error measures. Then, six machine-learning classifiers known as meta-learners, are trained on the extracted features of the time series in order to assign the most suitable forecasting method for the various subsets of the pool of forecasters. Furthermore, two-dimensionality reduction methods are implemented in order to investigate the role of feature space dimension on the performance of meta-learners. In general, it was found that meta-learners were able to defeat all of the individual benchmark forecasters; this performance was improved even after applying the feature selection method.
|
statistics
|
Audio event localization and detection (SELD) have been commonly tackled using multitask models. Such a model usually consists of a multi-label event classification branch with sigmoid cross-entropy loss for event activity detection and a regression branch with mean squared error loss for direction-of-arrival estimation. In this work, we propose a multitask regression model, in which both (multi-label) event detection and localization are formulated as regression problems and use the mean squared error loss homogeneously for model training. We show that the common combination of heterogeneous loss functions causes the network to underfit the data whereas the homogeneous mean squared error loss leads to better convergence and performance. Experiments on the development and validation sets of the DCASE 2020 SELD task demonstrate that the proposed system also outperforms the DCASE 2020 SELD baseline across all the detection and localization metrics, reducing the overall SELD error (the combined metric) by approximately 10% absolute.
|
electrical engineering and systems science
|
We have employed the generalized Bloch theorem to evaluate the spin stiffness constants of 3$d$ transition metals (bcc-Fe, fcc-Co, and fcc-Ni) within the linear combination of pseudo-atomic orbitals (LCPAO). The spin stiffness constants were obtained by fitting the spin-wave energy curve, which relates to the total energy difference and the spiral vectors. In order to convince the reliable spin stiffness constants, we also provided the convergences of spin stiffness constants in terms of the cutoff radius and the number of orbitals. After observing the specific cutoff radius and the basis orbital, at which the spin stiffness constant converges, we used those two parameters to compute the Curie temperature by using the mean field approximation and the random phase approximation. For the latter approximation, we applied the so-called Debye approximation, which is intended to reduce very significantly many required wavevectors to evaluate the Curie temperature. We claimed that our results are in good agreement with both other calculations and experiments.
|
condensed matter
|
We study phenomenological constraints on a simple $3-3-1$ model with flavor violating Yukawa couplings. Both triplets Higgs couple to leptons and quarks, which generates flavor violating signals in both lepton and quark sectors. We have shown that this model can allow for large Higgs lepton flavor-violating rate decay $h \rightarrow \mu \tau$ and also can be reached to perfect agreements with other experimental constraints such as $\tau \rightarrow \mu \gamma$ and $(g-2)_\mu$. The contributions of flavor-changing neutral current (FCNC) couplings, Higgs-quark-quark couplings, to the mesons mixing are investigated. Br$(h \rightarrow q q^\prime )$ can be enhanced with keeping from the measurements of meson mixing. The branching ratio for $t \rightarrow q h$ can reach up to $10^{-3}$, but it could be as low as $10^{-8}$.
|
high energy physics phenomenology
|
Based on the self-consistent T-matrix approximation (SCTMA), analytical theory of density of states (DOS) in three-dimensional quantum magnets with the bond disorder is proposed. It successfully describes DOS in both cases of resonant and non-resonant scattering which appearance is governed by the ratio of scattering length and the average distance between impurities. Corrections to the quasiparticles band gap in these cases are shown to be $\propto c^{2/3}$ and $\propto c$, respectively. Moreover, the theory yields a semi-circle form of DOS for the bound states inside the gap which results in highly nontrivial DOS in the intermediate parameters region between two limiting cases when the band DOS and the semi-circle are overlapped. Long-wavelength excitations are discussed. In the resonant regime their damping is almost constant $\propto c^{2/3}$, which according to Ioffe-Regel criterion means their localization. Applicability of the theory is illustrated by a quantitative description of the recent experimental data on spin-dimer system Ba$_{3-x}$Sr$_x$Cr$_2$O$_8$.
|
condensed matter
|
We discuss some general aspects of commutators of local operators in Lorentzian CFTs, which can be obtained from a suitable analytic continuation of the Euclidean operator product expansion (OPE). Commutators only make sense as distributions, and care has to be taken to extract the right distribution from the OPE. We provide explicit computations in two and four-dimensional CFTs, focusing mainly on commutators of components of the stress-tensor. We rederive several familiar results, such as the canonical commutation relations of free field theory, the local form of the Poincar\'e algebra, and the Virasoro algebra of two-dimensional CFT. We then consider commutators of light-ray operators built from the stress-tensor. Using simplifying features of the light sheet limit in four-dimensional CFT we provide a direct computation of the BMS algebra formed by a specific set of light-ray operators. In four-dimensional CFT we define a new infinite set of light-ray operators constructed from the stress-tensor, which all have well-defined matrix elements. These are a direct generalization of the two-dimensional Virasoro light-ray operators that are obtained from a conformal embedding of Minkowski space in the Lorentzian cylinder. They obey Hermiticity conditions similar to their two-dimensional analogues, and also share the property that a semi-infinite subset annihilates the vacuum.
|
high energy physics theory
|
We discuss how the stability of the theoretical prediction for exclusive $J/\psi$ photoproduction has been improved through a systematic taming of the known $\overline{\text{MS}}$ coefficient functions by accounting for a formally power suppressed, but numerically significant, correction encoded within a $Q_0$ cut. The phenomenological implications of this will be emphasised meaning, ultimately, the possibility to include the exclusive data into a global fitter framework to provide constraints on the small $x$ gluon.
|
high energy physics phenomenology
|
Recently, the author, together with L. Leustean and A. Nicolae, introduced the notion of jointly firmly nonexpansive families of mappings in order to investigate in an abstract manner the convergence of proximal methods. Here, we further the study of this concept, by giving a characterization in terms of the classical resolvent identity, by improving on the rate of convergence previously obtained for the uniform case, and by giving a treatment of the asymptotic behaviour at infinity of such families.
|
mathematics
|
Spatially separating electrons of different spins and efficiently generating spin currents are crucial steps towards building practical spintronics devices. Transverse magnetic focusing is a potential technique to accomplish both those tasks. In a material where there is significant Rashba spin-orbit interaction, electrons of different spins will traverse different paths in the presence of an external magnetic field. Experiments have demonstrated the viability of this technique by measuring conductance spectra that indicate the separation of spin-up and spin-down electrons. However the effect that the geometry of the leads has on these measurements is not well understood. We show that a trumpet-like shape opening for the leads offers better resolution of features in the conductance spectra than other shapes, and demonstrate that this resolution depends strongly on the width of the leads. Furthermore, the width of the leads affects the ratio between the amplitudes of the spin-split peaks in the spectra, by changing the number of subbands occupied by the electrons. We simulated devices with disorder and observed that this ratio between the amplitudes of the spin-split peaks is also affected by disorder. Ultimately careful choice and characterisation of device geometry is crucial for correctly interpreting the results of transverse magnetic focusing experiments.
|
condensed matter
|
We present a new method of gap control in two-dimensional periodic systems with the perturbation consisting of a second-order differential operator and a family of narrow potential `walls' separating the period cells in on direction. We show that under appropriate assumptions one can open gaps around points determined by dispersion curves of the associated `waveguide' system, in general any finite number of them, and to control their widths in terms of the perturbation parameter. Moreover, the distinctive feature of those gaps is that their edge values are attained by the corresponding band functions at internal points of the Brillouin zone.
|
mathematics
|
In this note, we proved that weak limits, of sums of independent positive identically distributed random variables which are re-normalized by a non-linear shrinking transform $\max(0, x-r)$, are either degenerate or (some) compound Poisson distributions.
|
mathematics
|
The issue of combining individual $p$-values to aggregate multiple small effects is prevalent in many scientific investigations and is a long-standing statistical topic. Many classical methods are designed for combining independent and frequent signals in a traditional meta-analysis sense using the sum of transformed $p$-values with the transformation of light-tailed distributions, in which Fisher's method and Stouffer's method are the most well-known. Since the early 2000, advances in big data promoted methods to aggregate independent, sparse and weak signals, such as the renowned higher criticism and Berk-Jones tests. Recently, Liu and Xie(2020) and Wilson(2019) independently proposed Cauchy and harmonic mean combination tests to robustly combine $p$-values under "arbitrary" dependency structure, where a notable application is to combine $p$-values from a set of often correlated SNPs in genome-wide association studies. The proposed tests are the transformation of heavy-tailed distributions for improved power with the sparse signal. It calls for a natural question to investigate heavy-tailed distribution transformation, to understand the connection among existing methods, and to explore the conditions for a method to possess robustness to dependency. In this paper, we investigate the regularly varying distribution, which is a rich family of heavy-tailed distribution and includes Pareto distribution as a special case. We show that only an equivalent class of Cauchy and harmonic mean tests have sufficient robustness to dependency in a practical sense. We also show an issue caused by large negative penalty in the Cauchy method and propose a simple, yet practical modification. Finally, we present simulations and apply to a neuroticism GWAS application to verify the discovered theoretical insights and provide practical guidance.
|
statistics
|
Rough sleeping is a chronic problem faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link, a UK-based charity, in developing a data-driven approach to assess the quality of incoming alerts from members of the public aimed at connecting people sleeping rough on the streets with outreach service providers. Alerts are prioritised based on the predicted likelihood of successfully connecting with the rough sleeper, helping to address capacity limitations and to quickly, effectively, and equitably process all of the alerts that they receive. Initial evaluation concludes that our approach increases the rate at which rough sleepers are found following a referral by at least 15\% based on labelled data, implying a greater overall increase when the alerts with unknown outcomes are considered, and suggesting the benefit in a trial taking place over a longer period to assess the models in practice. The discussion and modelling process is done with careful considerations of ethics, transparency and explainability due to the sensitive nature of the data in this context and the vulnerability of the people that are affected.
|
statistics
|
Fully-heavy tetraquark states, i.e. $cc\bar{c}\bar{c}$, $bb\bar{b}\bar{b}$, $bb\bar{c}\bar{c}$ ($cc\bar{b}\bar{b}$), $cb\bar{c}\bar{c}$, $cb\bar{b}\bar{b}$, and $cb\bar{c}\bar{b}$, are systematically investigated by means of a non-relativistic quark model based on lattice-QCD studies of the two-body $Q\bar{Q}$ interaction, which exhibits a spin-independent Cornell potential along with a spin-spin term. The four-body problem is solved using the Gaussian expansion method; additionally, the so-called complex scaling technique is employed so that bound, resonance, and scattering states can be treated on the same footing. Moreover, a complete set of four-body configurations, including meson-meson, diquark-antidiquark, and K-type configurations, as well as their couplings, are considered for spin-parity quantum numbers $J^{P(C)}=0^{+(+)}$, $1^{+(\pm)}$, and $2^{+(+)}$ in the $S$-wave channel. Several narrow resonances, with two-meson strong decay widths less than 30 MeV, are found in all of the tetraquark systems studied. Particularly, the fully-charm resonances recently reported by the LHCb Collaboration, at the energy range between 6.2 and 7.2 GeV in the di-$J/\psi$ invariant spectrum, can be well identified in our calculation. Focusing on the fully-bottom tetraquark spectrum, resonances with masses between 18.9 and 19.6 GeV are found. For the remaining charm-bottom cases, the masses are obtained within a energy region from 9.8 GeV to 16.4 GeV. All these predicted resonances can be further examined in future experiments.
|
high energy physics phenomenology
|
The resonance state of $\Delta$ baryon existing in four isospin ($I=\frac{3}{2}$) states, has been studied using Hypercentral Constituent Quark Model (hCQM) with a simple linear potential with added first order correction. The calculated data range for 1S-5S, 1P-5P, 1D-4D and 1F-2F with possible spin-parity assignments of all the states. The magnetic moments have also been obtained for all four configuration. The $N\pi$ decay channel width has been calculated for few states. The linear nature of the data has been verified through Regge trajectories.
|
high energy physics phenomenology
|
The ground-state (lightest) hybrid nonet with exotic quantum numbers $J^{PC}=1^{-+}$ and the nonet of their chiral partners with $J^{PC}=1^{+-}$ build a homochiral multiplet involving left- and right-handed currents, which under chiral transformation change just as (axial-)vector mesons. Masses and interactions of hybrids can be obtained in the context of the extended Linear Sigma Model. Here, we concentrate on the decays oh hybrids into two pseudoscalar mesons, such as $\eta\pi$ and $\eta^{\prime}\pi$ modes. Indeed, $\pi_{1}(1400)\rightarrow\pi\eta$ and $\pi_{1}(1600)\rightarrow\pi\eta ^{\prime}$ have been seen in experiments. Assuming that $\pi_{1}(1400)$ and $\pi_{1}(1600)$ correspond to the same state $\pi_{1}^{hyb}$, we show that these decays (and similar ones) follow from a chirally symmetric interaction term that breaks explicitly the axial anomaly. In this respect, these decays would be an additional manifestation of the axial (or chiral) anomaly in the mesonic sector.
|
high energy physics phenomenology
|
Located at the South Pole, the IceCube Neutrino Observatory is the world largest neutrino telescope, instrumenting one cubic kilometre of Antarctic ice at a depth between 1450m to 2450m. In 2013 IceCube reported the first observations of a diffuse astrophysical high-energy neutrino flux. Although the IceCube Collaboration has identified more than 100 high-energy neutrino events, the origin of this neutrino flux is still not known. Blazars, a subclass of Active Galactic Nuclei and one of the most powerful classes of objects in the Universe, have long been considered promising sources of high energy neutrinos. A blazar origin of this high-energy neutrino flux can be examined using stacking methods testing the correlation between IceCube neutrinos and catalogs of hypothesized sources. Here we present the results of a stacking analysis for 1301 blazars from the third catalog of hard \textit{Fermi}-LAT sources (3FHL). The analysis is performed on 8 years of through-going muon data from the Northern Hemisphere, recorded by IceCube between 2009 and 2016. No excess of neutrinos from the blazar position was found and first limits on the neutrino production of these sources will be shown.
|
astrophysics
|
We study the different quantum phases that occur in massive ${\cal N}=2$ supersymmetric QCD with gauge groups $SU(2)$ and $SU(3)$ as the coupling $\Lambda/M$ is gradually increased from 0 to infinity. The phases can be identified by computing the exact partition function by saddle-points, combining supersymmetric localization and the Seiberg-Witten formalism. In all cases, we find two phases, a weak coupling and a strong coupling phase, separated by a critical point described by a superconformal field theory or involving superconformal sectors. In crossing the critical point, the dominant saddle-point hops from one singularity of the curve to another one. The theories seem to undergo a second-order phase transition with divergent susceptibility.
|
high energy physics theory
|
Here, we address the problem of trend estimation for functional time series. Existing contributions either deal with detecting a functional trend or assuming a simple model. They consider neither the estimation of a general functional trend nor the analysis of functional time series with a functional trend component. Similarly to univariate time series, we propose an alternative methodology to analyze functional time series, taking into account a functional trend component. We propose to estimate the functional trend by using a tensor product surface that is easy to implement, to interpret, and allows to control the smoothness properties of the estimator. Through a Monte Carlo study, we simulate different scenarios of functional processes to show that our estimator accurately identifies the functional trend component. We also show that the dependency structure of the estimated stationary time series component is not significantly affected by the error approximation of the functional trend component. We apply our methodology to annual mortality rates in France.
|
statistics
|
We propose a novel framework to understand the text by converting sentences or articles into video-like 3-dimensional tensors. Each frame, corresponding to a slice of the tensor, is a word image that is rendered by the word's shape. The length of the tensor equals to the number of words in the sentence or article. The proposed transformation from the text to a 3-dimensional tensor makes it very convenient to implement an $n$-gram model with convolutional neural networks for text analysis. Concretely, we impose a 3-dimensional convolutional kernel on the 3-dimensional text tensor. The first two dimensions of the convolutional kernel size equal the size of the word image and the last dimension of the kernel size is $n$. That is, every time when we slide the 3-dimensional kernel over a word sequence, the convolution covers $n$ word images and outputs a scalar. By iterating this process continuously for each $n$-gram along with the sentence or article with multiple kernels, we obtain a 2-dimensional feature map. A subsequent 1-dimensional max-over-time pooling is applied to this feature map, and three fully-connected layers are used for conducting text classification finally. Experiments of several text classification datasets demonstrate surprisingly superior performances using the proposed model in comparison with existing methods.
|
computer science
|
Without proper control of numerical and methodological errors in theoretical predictions at the per mille level it is not possible to study the effect of input parameters in current hadron-collider measurements at the required precision. We present a new version of the parton-level code MCFM that achieves this requirement through its highly-parallelized nature, significant performance improvements and new features. An automatic differential cutoff extrapolation is introduced to assess the cutoff dependence of all results, thus ensuring their reliability and potentially improving fixed-cutoff results by an order of magnitude. The efficient differential study of PDF uncertainties and PDF set differences at NNLO, for multiple PDF sets simultaneously, is achieved by exploiting correlations. We use these improvements to study uncertainties and PDF sensitivity at NNLO, using 371 PDF set members. The work described here permits NNLO studies that were previously prohibitively expensive, and lays the groundwork necessary for a future implementation of NNLO calculations with a jet at Born level in MCFM.
|
high energy physics phenomenology
|
We have studied the structural stability of Sc-substituted rare earth (R) ferrites R1-xScxFeO3, and constructed a structural phase diagram for different R and x. While RFeO3 and ScFeO3 adopt the orthorhombic and the bixbyite structure respectively, the substituted compound R1-xScxFeO3 may be stable in a different structure. Specifically, for R0.5Sc0.5FeO3, the hexagonal structure can be stable for small R, such as Lu and Yb, while the garnet structure is stable for larger R, such as Er and Ho. The formation of garnet structure of the R0.5Sc0.5FeO3 compounds which requires that Sc occupies both the rare earth and the Fe sites, is corroborated by their magnetic properties.
|
condensed matter
|
Semi-supervised learning provides an effective paradigm for leveraging unlabeled data to improve a model's performance. Among the many strategies proposed, graph-based methods have shown excellent properties, in particular since they allow to solve directly the transductive tasks according to Vapnik's principle and they can be extended efficiently for inductive tasks. In this paper, we propose a novel approach for the transductive semi-supervised learning, using a complete bipartite edge-weighted graph. The proposed approach uses the regularized optimal transport between empirical measures defined on labelled and unlabelled data points in order to obtain an affinity matrix from the optimal transport plan. This matrix is further used to propagate labels through the vertices of the graph in an incremental process ensuring the certainty of the predictions by incorporating a certainty score based on Shannon's entropy. We also analyze the convergence of our approach and we derive an efficient way to extend it for out-of-sample data. Experimental analysis was used to compare the proposed approach with other label propagation algorithms on 12 benchmark datasets, for which we surpass state-of-the-art results. We release our code.
|
statistics
|
We study the weak convergence of $\beta$- and $\beta'$-Delaunay tessellations in $\mathbb{R}^{d-1}$ that were introduced in part I of this paper, as $\beta\to\infty$. The limiting stationary simplicial random tessellation, which is called the Gaussian-Delaunay tessellation, is characterized in terms of a space-time paraboloid hull process in $\mathbb{R}^{d-1}\times\mathbb{R}$. The latter object has previously appeared in the analysis of the number of shocks in the solution of the inviscid Burgers' equation and the description of the local asymptotic geometry of Gaussian random polytopes. In this paper it is used to define a new stationary random simplicial tessellation in $\mathbb{R}^{d-1}$. As for the $\beta$- and $\beta'$-Delaunay tessellation, the distribution of volume-power weighted typical cells in the Gaussian-Delaunay tessellation is explicitly identified, establishing thereby a new bridge to Gaussian random simplices. Also major geometric characteristics of these cells such as volume moments, expected angle sums and also the cell intensities of the Gaussian-Delaunay tessellation are investigated.
|
mathematics
|
We present a modified nudged elastic band routine that can reduce the number of force calls by more than 50% for bands with non-uniform convergence. The method, which we call "dyNEB", dynamically and selectively optimizes states based on the perpendicular forces and parallel spring forces acting on that region of the band. The convergence criteria are scaled to focus on the region of interest, i.e., the saddle point, while maintaining continuity of the band and avoiding truncation. We show that this method works well for solid state reaction barriers---non-electrochemical in general and electrochemical in particular---and that the number of force calls can be significantly reduced without loss of resolution at the saddle point.
|
physics
|
We analyze the strong noise limit of one-dimensional stochastic differential equations (SDEs). Our initial motivation comes from continuous measurements of open quantum systems. In this context, Bauer, Bernard and Tilloy pointed out an intriguing behavior. As the noise grows larger, the solutions exhibit locally a collapsing, that is to say, converge to pure jump processes very reminiscent of a metastability phenomenon. But surprisingly the limiting jump process is decorated by a spike process. We give a precise meaning to the convergence and completely prove these statements for a large class of one-dimensional diffusions, thanks to a robust strategy of proof.
|
mathematics
|
Cloud GPU servers have become the de facto way for deep learning practitioners to train complex models on large-scale datasets. However, it is challenging to determine the appropriate cluster configuration---e.g., server type and number---for different training workloads while balancing the trade-offs in training time, cost, and model accuracy. Adding to the complexity is the potential to reduce the monetary cost by using cheaper, but revocable, transient GPU servers. In this work, we analyze distributed training performance under diverse cluster configurations using CM-DARE, a cloud-based measurement and training framework. Our empirical datasets include measurements from three GPU types, six geographic regions, twenty convolutional neural networks, and thousands of Google Cloud servers. We also demonstrate the feasibility of predicting training speed and overhead using regression-based models. Finally, we discuss potential use cases of our performance modeling such as detecting and mitigating performance bottlenecks.
|
computer science
|
In ranking problems, the goal is to learn a ranking function from labeled pairs of input points. In this paper, we consider the related comparison problem, where the label indicates which element of the pair is better, or if there is no significant difference. We cast the learning problem as a margin maximization, and show that it can be solved by converting it to a standard SVM. We use simulated nonlinear patterns, a real learning to rank sushi data set, and a chess data set to show that our proposed SVMcompare algorithm outperforms SVMrank when there are equality pairs.
|
statistics
|
We prove that for every polynomial ODE there exists a Carnot group where the trajectories of the ODE lift to abnormal curves. The proof defines an explicit construction to determine a covector for the resulting abnormal curves. Using this method we give new examples of abnormal curves in Carnot groups of high step. As a byproduct of the argument, we also prove that concatenations of abnormal curves have abnormal lifts.
|
mathematics
|
Magnetic Resonance Imaging (MRI) is a valuable clinical diagnostic modality for spine pathologies with excellent characterization for infection, tumor, degenerations, fractures and herniations. However in surgery, image-guided spinal procedures continue to rely on CT and fluoroscopy, as MRI slice resolutions are typically insufficient. Building upon state-of-the-art single image super-resolution, we propose a reference-based, unpaired multi-contrast texture-transfer strategy for deep learning based in-plane and across-plane MRI super-resolution. We use the scattering transform to relate the texture features of image patches to unpaired reference image patches, and additionally a loss term for multi-contrast texture. We apply our scheme in different super-resolution architectures, observing improvement in PSNR and SSIM for 4x super-resolution in most of the cases.
|
electrical engineering and systems science
|
We investigate the Keplerian (mass-shedding) sequence of rotating neutron stars. Twelve different equations of state are used to describe the nuclear structure. We find four fitting relations which connect the rotating frequency, mass and radius of stars in the mass-shedding limit to the mass and radius of stars in the static sequence. We show the breakdown of approximate relation for the Keplerian frequency derived by Lattimer and Prakash [Science, 304, 536, (2004)] and then we present a new, EOS-independent and more accurate relation. This relation fits the Keplerian frequency of rotating neutron stars to about $2\%$ for a large range of the compactness $M_{S}/R_{S}$ of the reference non-rotating neutron star, namely the static star with the same central density as the rotating one. The performance of the fitting formula is close to $4\%$ for $M_{S}/R_{S}\leq 0.05~M_{\odot}$/km ($f_{K}\leq 350$~Hz). We present additional EOS-independent relations for the Keplerian sequence including relations for $M_{K}f_{K}$ and $R_{K}f_{K}$ in terms of $M_{S}f_{S}$ and $R_{S}f_{S}$, respectively, one of $M_K/R_K$ as a function of $f_{K}/f_{S}$ and $M_S/R_S$, and a relation between the $M_K$, $R_K$ and $f_K$. These new fitting relations are approximately EOS-independent with an error in the worst case of $8\%$. The universality of the Keplerian sequence properties presented here add to the set of other neutron star universal relations in the literature such as the $I$-Love-$Q$ relation, the gravitational binding energy and the energy, angular momentum and radius of the last circular orbit of a test-particle around rotating neutron stars. This set of universal, analytic formulas, facilitate the inclusion of general relativistic effects in the description of relativistic astrophysical systems involving fast rotating neutron stars.
|
astrophysics
|
We developed a novel design of a Micro Pixel Chamber ($\mu$-PIC) with resistive electrodes for a charged-particle-tracking detector in high-rate applications. Diamond-Like Carbon (DLC) thin film is used for the cathodes. The resistivity can be controlled flexibly ($\mathrm{10^{5-7}k\Omega/sq.}$) at high uniformity. The fabrication-process was greatly improved and the resistive $\mu$-PIC could be operated at 10$\times$10 $\mathrm{cm^2}$. Resistors for the HV bias and capacitors for the AC coupling were completely removed by applying PCB and carbon-sputtering techniques, and the resistive $\mu$-PIC became a very compact detector. The performances of our new resistive $\mu$-PIC were measured in various ways. Consequently, it was possible to attain high gas gains ($\mathrm{> 10^{4}}$), high detection efficiency, and position resolution exceeding 100 $\mu$m. The spark current was suppressed, and the new resistive $\mu$-PIC was operated stably under fast-neutrons irradiation. These features offer solutions for a charged-particle-tracking detector in future high-rate applications.
|
physics
|
Macroscopic dark matter (macros) are a broad class of alternative candidates to particle dark matter. These candidates would transfer energy primarily through elastic scattering, and this linear energy deposition would produce observable signals if a macro were to pass through the atmosphere. We produce constraints for low mass macros from the null observation of bolides formed by a passing macro, across two extensive networks of cameras built originally to observe meteorites. The parameter space that could be probed with planned upgrades to the existing array of cameras in one of these networks still currently in use, the Desert Fireball Network in Australia, is estimated.
|
astrophysics
|
The effect of surfactants on the tail and film dynamics of elongated gas bubbles propagating through circular capillary tubes is investigated by means of an extensive three-dimensional numerical study using a hybrid front-tracking/level-set method. The focus is on the visco-inertial regime, which occurs when the Reynolds number of the flow is much larger than unity. Under these conditions, `clean' bubbles exhibit interface undulations in the proximity of the tail \cite{Magnini_prf_2017}, with an amplitude that increases with the Reynolds number. We perform a systematic analysis of the impact of a wide range of surfactant properties, including elasticity, bulk surfactant concentration, solubility, and diffusivity, on the bubble and flow dynamics in the presence of inertial effects. The results show that the introduction of surfactants is effective in suppressing the tail undulations as they tend to accumulate near the bubble tail. Here, large Marangoni stresses are generated, which lead to a local `rigidification' of the bubble. This effect becomes more pronounced for larger surfactant elasticities and adsorption depths. At reduced surfactant solubility, a thicker rigid film region forms at the bubble rear, where a Couette film flow is established, while undulations still appear at the trailing edge of the downstream `clean' film region. In such conditions, the bubble length becomes an influential parameter, with short bubbles becoming completely rigid.
|
physics
|
We introduce a multi-step protocol for optical quantum state engineering that performs as deterministic "bright quantum scissors" (BQS), namely truncates an arbitrary input quantum state to have at least a certain number of photons. The protocol exploits single-photon pulses and is based on the effect of single-photon Raman interaction, which is implemented with a single three-level $\Lambda$ system (e.g. a single atom) Purcell-enhanced by a single-sided cavity. A single step of the protocol realises the inverse of the bosonic annihilation operator. Multiple iterations of the protocol can be used to deterministically generate a chain of single-photons in a W state. Alternatively, upon appropriate heralding, the protocol can be used to generate Fock-state optical pulses. This protocol could serve as a useful and versatile building block for the generation of advanced optical quantum states that are vital for quantum communication, distributed quantum information processing, and all-optical quantum computing.
|
quantum physics
|
We study the mixed formulation of the abstract Hodge Laplacian on axisymmetric domains with general data through Fourer-finite-element-methods in weighted functions spaces. Closed Hilbert complexes and commuting projectors are used through a family of finite element spaces recently introduced for general axisymmetric problems. In order to get stability results and error estimates for the discrete mixed formulation, we construct commuting projectors that can be applied to functions with low regularity.
|
mathematics
|
This paper presents a cold-start linear branch flow model named modified DistFlow. In modified DistFlow, the active and reactive power are replaced by their ratios to voltage magnitude as state variables, so that errors introduced by conventional branch flow linearization approaches due to their complete ignoring of the quadratic term are reduced. Based on the path-branch incidence matrix, branch power flows and nodal voltage magnitudes can be obtained in a non-iterative and explicit manner. Subsequently, the proposed modified DistFlow model is applied to the problem of reactive power optimization and network reconfiguration, transforming it into a mixed-integer quadratic programming (MIQP). Simulations show that the proposed modified DistFlow has a better accuracy than existing cold-start linear branch flow models for distribution networks, and the resulting MIQP model for reactive power optimization and network reconfiguration is much more computationally efficient than existing benchmarks.
|
electrical engineering and systems science
|
We establish a strong link between two apparently unrelated topics: the study of conflicting information in the formal framework of valuation algebras, and the phenomena of non-locality and contextuality. In particular, we show that these peculiar features of quantum theory are mathematically equivalent to a general notion of \emph{disagreement} between information sources. This result vastly generalises previously observed connections between contextuality, relational databases, constraint satisfaction problems, and logical paradoxes, and gives further proof that contextual behaviour is not a phenomenon limited to quantum physics, but pervades various domains of mathematics and computer science. The connection allows to translate theorems, methods and algorithms from one field to the other, and paves the way for the application of generic inference algorithms to study contextuality.
|
quantum physics
|
The secret key rate of a continuous-variable quantum key distribution (CV-QKD) system is limited by excess noise. A key issue typical to all modern CV-QKD systems implemented with a reference or pilot signal and an independent local oscillator is controlling the excess noise generated from the frequency and phase noise accrued by the transmitter and receiver. Therefore accurate phase estimation and compensation, so-called carrier recovery, is a critical subsystem of CV-QKD. Here, we explore the implementation of a machine learning framework based on Bayesian inference, namely an unscented Kalman filter (UKF), for estimation of phase noise and compare it to a standard reference method. Experimental results obtained over a 20 km fibre-optic link indicate that the UKF can ensure very low excess noise even at low pilot powers. The measurements exhibited low variance and high stability in excess noise over a wide range of pilot signal to noise ratios. This may enable CV-QKD systems with low implementation complexity which can seamlessly work on diverse transmission lines.
|
quantum physics
|
Using first-principles calculations, we investigate the impact of hydrogenation on the Dzyaloshinskii-Moriya interaction (DMI) at graphene/Co interface. We find that both the magnitude and chirality of DMI can be controlled via hydrogenation absorbed on graphene surface. Our analysis using density of states combined with first-order perturbation theory reveals that the spin splitting and the occupation of Co-d orbitals, especially the dxz and dz2 states, play a crucial role in defining the magnitude and the chirality of DMI. Moreover, we find that the DMI oscillates with a period of two atomic layers as a function of Co thickness what could be explained by analysis of out-of-plane of Co orbitals. Our work elucidates the underlying mechanisms of interfacial DMI origin and provides an alternative route of its control for spintronic applications.
|
condensed matter
|
Understanding how the release of stored magnetic energy contributes to the generation of non-thermal high energy particles during solar flares is an important open problem in solar physics. Magnetic reconnection plays a fundamental role in the energy release and conversion processes taking place during flares. A common approach for investigating particle acceleration is to use test particles in fields derived from magnetohydrodynamic (MHD) simulations of reconnection. These MHD simulations use anomalous resistivities that are much larger than the Spitzer resistivity based on Coulomb collisions. The processes leading to enhanced resistivity should also affect the test particles. We explore the link between resistivity and particle orbits building on a previous study using a 2D MHD simulation of magnetic reconnection. This paper extends the previous investigation to a 3D magnetic reconnection configuration and to study the effect on test particle orbits. We carried out orbit calculations using a 3D MHD simulation of separator reconnection. We use the relativistic guiding centre approximation including stochastic pitch angle scattering. The effects of varying the resistivity and the models for pitch angle scattering on particle orbit trajectories, final positions, energy spectra, final pitch angle distribution, and orbit duration are all studied in detail. Pitch angle scattering widens collimated beams of orbit trajectories, allowing orbits to access previously unaccessible field lines; this causes final positions to spread to topological structures that were previously inaccessible. Scattered orbit energy spectra are found to be predominantly affected by the level of anomalous resistivity, with the pitch angle scattering model only playing a role in isolated cases. Scattering is found to play a crucial role in determining the pitch angle and orbit duration distributions.
|
astrophysics
|
Measurement-induced nonlocality (MIN), a quantum correlation measure for the bipartite system, is an indicator of global effects due to locally invariant von Neumann projective measurements. It is well known fact that the correlation measures based on Hilbert-Schmidt norm are not credible measure in capturing nonlocal attributes of a quantum state. In this article, to remedy the local ancilla problem of Hilbert-Schmidt norm based MIN, we propose a new form of MIN-based on affinity. This quantity satisfies all criteria of a bonafide measure of quantum correlation measure. For an arbitrary pure state, it is shown that affinity based MIN equals to other forms of geometric versions of correlation measure. We obtain an upper bound of this measure for m \times n-dimensional arbitrary mixed state. We obtain a closed formula of the proposed version of MIN for 2 \times n dimensional (qubit qudit) mixed state. We apply these results on two-qubit mixed states such as Werner, isotropic and Bell diagonal state. To illustrate the robustness of affinity-based measure against noise, we study the dynamics of MIN under generalized amplitude damping channel.
|
quantum physics
|
We present a description of the function space and the smoothness class associated with a convolutional network using the machinery of reproducing kernel Hilbert spaces. We show that the mapping associated with a convolutional network expands into a sum involving elementary functions akin to spherical harmonics. This functional decomposition can be related to the functional ANOVA decomposition in nonparametric statistics. Building off our functional characterization of convolutional networks, we obtain statistical bounds highlighting an interesting trade-off between the approximation error and the estimation error.
|
statistics
|
Hardy's paradox (equivalently, Hardy's non-locality or Hardy's test) [\href{https://link.aps.org/doi/10.1103/PhysRevLett.68.2981}{L. Hardy, Phys. Rev. Lett. \textbf{68}, 2981 (1992)}] is used to show non-locality without inequalities and it has been tested several times using optical circuits. We, for the first time, experimentally test Hardy's paradox of non-locality in superconducting qubits. For practical verification of Hardy's paradox, we argue that the error-modeling used in optical circuits is not useful for superconducting qubits. So, we propose a new error-modeling for Hardy's paradox and a new method to estimate the lower bound on Hardy's probability (i.e., the probability of a specific event in Hardy's test) for superconducting qubits. Our results confirmed the theory that any non-maximally entangled state of two qubits violates Hardy's equations; whereas, any maximally entangled state and product state of two qubits do not exhibit Hardy's non-locality. Further, we point out the difficulties associated with the practical implementation of quantum protocols based on Hardy's paradox and propose possible remedies. We also propose two performance measures for any two qubits of any quantum computer based on superconducting qubits.
|
quantum physics
|
Let $A = \{0 = a_0 < a_1 < \cdots < a_{\ell + 1} = b\}$ be a finite set of non-negative integers. We prove that the sumset $NA$ has a certain easily-described structure, provided that $N \geqslant b-\ell$, as recently conjectured by Shakan and the first author. We also classify those sets $A$ for which this bound cannot be improved.
|
mathematics
|
The recently discovered kagome metal series $A$V$_3$Sb$_5$ ($A$=K, Rb, Cs) exhibits topologically nontrivial band structures, chiral charge order and superconductivity, presenting a unique platform for realizing exotic electronic states. The nature of the superconducting state and the corresponding pairing symmetry are key questions that demand experimental clarification. Here, using a technique based on the tunneling diode oscillator, the magnetic penetration depth $\Delta\lambda(T)$ of CsV$_3$Sb$_5$ was measured down to 0.07 K. A clear exponential behavior in $\Delta\lambda(T)$ with marked deviations from a $T$ or $T^2$ temperature dependence is observed at low temperatures, indicating a deficiency of nodal quasiparticles. Temperature dependence of the superfluid density and electronic specific heat can be described by two-gap $s$-wave superconductivity, consistent with the presence of multiple Fermi surfaces in CsV$_3$Sb$_5$. These results evidence nodeless superconductivity in CsV$_3$Sb$_5$ under ambient pressure, and constrain the allowed pairing symmetry.
|
condensed matter
|
Accurate characterisation of small defects remains a challenge in non-destructive testing (NDT). In this paper, a principle-component parametric-manifold mapping approach is applied to single-frequency eddy-current defect characterisation problems for surface breaking defects in a planar half-space. A broad 1-8 MHz frequency-range FE-circuit model & calibration approach is developed & validated to simulate eddy-current scans of surface-breaking notch defects. This model is used to generate parametric defect databases for surface breaking defects in an aluminium planar half-space and defect characterisation of experimental measurements performed. Parametric-manifold mapping was conducted in N-dimensional principle component space, reducing the dimensionality of the characterisation problem. In a study characterising slot depth, the model & characterisation approach is shown to accurately invert the depth with greater accuracy than a simple amplitude inversion method with normalised percentage characterisation errors of 38% and 17% respectively measured at 2.0 MHz across 5 slot depths between 0.26 - 2.15 mm. The approach is used to characterise the depth of a sloped slot demonstrating good accuracy up to ~2.0 mm in depth over a broad range of sub-resonance frequencies, indicating applications in geometric feature inversion. Finally the technique is applied to finite rectangular notch defects of surface extents smaller than the diameter of the inspection coil (sub-aperture) over a range of frequencies. The results highlight the limitations in characterising these defects and indicate how the inherent instabilities in resonance can severely limit characterisation at these frequencies.
|
physics
|
This paper studies the statistical theory of offline reinforcement learning with deep ReLU networks. We consider the off-policy evaluation (OPE) problem where the goal is to estimate the expected discounted reward of a target policy given the logged data generated by unknown behaviour policies. We study a regression-based fitted Q evaluation (FQE) method using deep ReLU networks and characterize a finite-sample bound on the estimation error of this method under mild assumptions. The prior works in OPE with either general function approximation or deep ReLU networks ignore the data-dependent structure in the algorithm, dodging the technical bottleneck of OPE, while requiring a rather restricted regularity assumption. In this work, we overcome these limitations and provide a comprehensive analysis of OPE with deep ReLU networks. In particular, we precisely quantify how the distribution shift of the offline data, the dimension of the input space, and the regularity of the system control the OPE estimation error. Consequently, we provide insights into the interplay between offline reinforcement learning and deep learning.
|
statistics
|
A diffusive Lotka-Volterra competition model is considered for the combined effect of spatial dispersal and spatial variations of resource on the population persistence and exclusion. First it is shown that in a two-species system in which the diffusion coefficients, resource functions and competition rates are all spatially heterogeneous, the positive equilibrium solution is globally asymptotically stable when it exists. Secondly the existence and global asymptotic stability of the positive and semi-trivial equilibrium solutions are obtained for the model with arbitrary number of species under the assumption of spatially heterogeneous resource distribution. A new Lyapunov functional method is developed to prove the global stability of a non-constant equilibrium solution in heterogeneous environment.
|
mathematics
|
Quantum communication networks enable applications ranging from highly secure communication to clock synchronization and distributed quantum computing. Miniaturized, flexible, and cost-efficient resources will be key elements for ensuring the scalability of such networks as they progress towards large-scale deployed infrastructures. Here, we bring these elements together by combining an on-chip, telecom-wavelength, broadband entangled photon source with industry-grade flexible-grid wavelength division multiplexing techniques, to demonstrate reconfigurable entanglement distribution between up to 8 users in a resource-optimized quantum network topology. As a benchmark application we use quantum key distribution, and show low error and high secret key generation rates across several frequency channels, over both symmetric and asymmetric metropolitan-distance optical fibered links and including finite-size effects. By adapting the bandwidth allocation to specific network constraints, we also illustrate the flexible networking capability of our configuration. Together with the potential of our semiconductor source for distributing secret keys over a 60 nm bandwidth with commercial multiplexing technology, these results offer a promising route to the deployment of scalable quantum network architectures.
|
quantum physics
|
Slow dynamic nonlinearity describes a poorly understood, creep-like phenomena that occurs in brittle composite materials such as rocks and cement. It is characterized by a drop in stiffness induced by a mechanical conditioning, followed by a log(time) recovery. A consensus theoretical understanding of the behavior has not been developed. Here we introduce an alternative experimental venue with which to inform theory. Unconsolidated glass bead packs are studied rather than rocks or cement because the structure and internal contacts of bead packs are less complex and better understood. Slow dynamics has been observed in such systems previously. However, the measurements to date tend to be irregular. Particular care is used here in the experimental design to overcome the difficulties inherent in bead pack studies. This includes the design of the bead pack support, the use of low frequency conditioning, and the use of ultrasonic waves as a probe with coda wave interferometry to assess changes. Slow dynamics is observed in our system after three different methods for low-frequency conditioning, one of which has not been reported in the literature previously.
|
condensed matter
|
We analyse a modified May-Holling-Tanner predator-prey model considering an Allee effect in the prey and alternative food sources for predator. Additionally, the predation functional response or predation consumption rate is linear. The extended model exhibits rich dynamics and we prove the existence of separatrices in the phase plane separating basins of attraction related to oscillation, co-existence and extinction of the predator-prey population. We also show the existence of a homoclinic curve that degenerates to form a limit cycle and discuss numerous potential bifurcations such as saddle-node, Hopf, and Bogadonov-Takens bifurcations. We use simulations to illustrate the behaviour of the model.
|
mathematics
|
Aiming at the difficulty of stability analysis in practical application of existing control methods, a controller strategy based on lyapunov stability theory is proposed to realize stable control for any control method. In order to illustrate the effectiveness of this control scheme, this paper lists two different lyapunov functions to test the control effect of different system models in tracking the target function. The simulation results show that the proposed method has excellent control effect on different types of systems and is advanced.
|
electrical engineering and systems science
|
The cross-spectral density of coherent Gaussian vortex beams propagating through weak oceanic turbulence is derived from extended Huygens-Fresnel principle and Nikishov spectrum. The evolution of a coherent superposition field composed of dual Gaussian vortex beams with $+1$ and $-1$ topological charges respectively through weak oceanic turbulence is investigated in z plane and y plane. It is shown that the non-zero separation distance of two beams in x direction enhances the oceanic turbulence effect on interference light field. The variation of intensity distribution in z plane and on the central axis of two beams in y plane are both related to the strength of oceanic turbulence, separation distance, propagation distance and waist width. The extra fluctuation of the intensity on the central axis of two beams in y plane leads to high sensitivity of oceanic turbulence. This characteristic has potential application in non-contact optical tomography of oceanic turbulence strength along the beam propagation path by lateral scattering intensity.
|
physics
|
Recent progress in generating entangled spin states of neutral atoms provides opportunities to advance quantum sensing technology. In particular, entanglement can enhance the performance of accelerometers and gravimeters based on light-pulse atom interferometry. We study the effects of error sources that may limit the sensitivity of such devices, including errors in the preparation of the initial entangled state, imperfections in the laser pulses, momentum spread of the initial atomic wave packet, measurement errors, spontaneous emission, and atom loss. We determine that, for each of these errors, the expectation value of the parity operator $\Pi$ has the general form, $\overline{\langle \Pi \rangle} = \Pi_0 \cos( N \phi )$, where $\phi$ is the interferometer phase and $N$ is the number of atoms prepared in the maximally entangled Greenberger--Horne--Zeilinger state. Correspondingly, the minimum phase uncertainty has the general form, $\Delta\phi = (\Pi_0 N)^{-1}$. Each error manifests itself through a reduction of the amplitude of the parity oscillations, $\Pi_0$, below the ideal value of $\Pi_0 = 1$. For each of the errors, we derive an analytic result that expresses the dependence of $\Pi_0$ on error parameter(s) and $N$, and also obtain a simplified approximate expression valid when the error is small. Based on the performed analysis, entanglement-enhanced atom interferometry appears to be feasible with existing experimental capabilities.
|
quantum physics
|
Physical-layer security is regaining traction in the research community, due to the performance boost introduced by deep learning classification algorithms. This is particularly true for sender authentication in wireless communications via radio fingerprinting. However, previous research efforts mainly focused on terrestrial wireless devices while, to the best of our knowledge, none of the previous work took into consideration satellite transmitters. The satellite scenario is generally challenging because, among others, satellite radio transducers feature non-standard electronics (usually aged and specifically designed for harsh conditions). Moreover, the fingerprinting task is specifically difficult for Low-Earth Orbit (LEO) satellites (like the ones we focus in this paper) since they orbit at about 800Km from the Earth, at a speed of around 25,000Km/h, thus making the receiver experiencing a down-link with unique attenuation and fading characteristics. In this paper, we propose PAST-AI, a methodology tailored to authenticate LEO satellites through fingerprinting of their IQ samples, using advanced AI solutions. Our methodology is tested on real data -- more than 100M I/Q samples -- collected from an extensive measurements campaign on the IRIDIUM LEO satellites constellation, lasting 589 hours. Results are striking: we prove that Convolutional Neural Networks (CNN) and autoencoders (if properly calibrated) can be successfully adopted to authenticate the satellite transducers, with an accuracy spanning between 0.8 and 1, depending on prior assumptions. The proposed methodology, the achieved results, and the provided insights, other than being interesting on their own, when associated to the dataset that we made publicly available, will also pave the way for future research in the area.
|
computer science
|
We present a unification model for a clumpy obscurer in active galactic nuclei (AGN) and investigate the properties of the resulting X-ray spectrum. Our model is constructed to reproduce the column density distribution of the AGN population and cloud eclipse events in terms of their angular sizes and frequency. We developed and release a generalised Monte Carlo X-ray radiative transfer code, XARS, to compute X-ray spectra of obscurer models. The geometry results in strong Compton scattering, causing soft photons to escape also along Compton-thick sight lines. This makes our model spectra very similar to the Brightman & Nandra TORUS model. However, only if we introduce an additional Compton-thick reflector near the corona, we achieve good fits to NuSTAR spectra. This additional component in our model can be interpreted as part of the dust-free broad-line region, an inner wall or rim, or a warped disk. It cannot be attributed to a simple disk because the reflector must simultaneously block the line of sight to the corona and reflect its radiation. We release our model as an Xspec table model and present corresponding CLUMPY infrared spectra, paving the way for self-consistent multi-wavelength analyses.
|
astrophysics
|
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