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We present a comparison of different particles' velocity and acceleration statistics in two paradigmatic turbulent swirling flows: the von K\'arm\'an flow in a laboratory experiment, and the Taylor-Green flow in direct numerical simulations. Tracers, as well as inertial particles, are considered. Results indicate that, in spite of the differences in boundary conditions and forcing mechanisms, scaling properties and statistical quantities reveal similarities between both flows, pointing to new methods to calibrate and compare models for particles dynamics in numerical simulations, as well as to characterize the dynamics of particles in simulations and experiments.
|
physics
|
There has been considerable recent interest in holographic complexity. The two leading conjectures on this subject hold that the quantum complexity of the boundary thermofield double state should be dual to either the volume of the Einstein-Rosen bridge connecting the two sides (CV conjecture) or to the action of the Wheeler-de-Witt patch of the bulk spacetime (CA conjecture). Although these conjectures are frequently studied in the context of pure Einstein gravity, from the perspective of string theory it is also natural to consider models of gravity in which general relativity is perturbed by higher powers of the Riemann tensor, suppressed by powers of the string length; in a holographic context, these corrections are dual to corrections in inverse powers of the 't Hooft coupling. In this paper, we investigate the CV and CA conjectures in two stringy models of higher-curvature gravity. We find that the CV complexification rate remains well-behaved, but conversely that these corrections induce new divergences in the CA complexification rate that are absent in pure Einstein gravity. These divergences are intrinsically linked to the singularity, and appear to be generic in higher curvature theories. To the best of our knowledge, infinities originating at the singularity have not yet been observed elsewhere in the literature. We argue that these divergences imply that, in the CA picture, the complexification rate of the boundary theory is a nonanalytic function of the 't Hooft coupling.
|
high energy physics theory
|
The concept of quantum memory plays an incisive role in the quantum information theory. As confirmed by several recent rigorous mathematical studies, the quantum memory inmate in the bipartite system $\rho_{AB}$ can reduce uncertainty about the part $B$, after measurements done on the part $A$. In the present work, we extend this concept to the systems with a spin-orbit coupling and introduce a notion of spin-orbit quantum memory. We self-consistently explore Uhlmann fidelity, pre and post measurement entanglement entropy and post measurement conditional quantum entropy of the system with spin-orbit coupling and show that measurement performed on the spin subsystem decreases the uncertainty of the orbital part. The uncovered effect enhances with the strength of the spin-orbit coupling. We explored the concept of macroscopic realism introduced by Leggett and Garg and observed that POVM measurements done on the system under the particular protocol are non-noninvasive. For the extended system, we performed the quantum Monte Carlo calculations and explored reshuffling of the electron densities due to the external electric field.
|
quantum physics
|
Berta et al [Phys. Rev. Lett., 121, 040504 (2018)] claim that their result provides a conceptually new extension of the decoupling approach to quantum information theory. We provide an alternate proof using the plain-vanilla decoupling approach for the achievable rates of their main result and hence, their claim is unwarranted, and the title can be misleading when taken in conjunction with the claim.
|
quantum physics
|
We introduce optical polarization-insensitive high pass filters based on total internal reflection of light at the interface of two dielectric media (1D) and Bragg reflection of a multilayer stack (2D) in transmission mode. The wavevectors in the stopband become coupled to evanescent waves in our design, rather than the zero of a narrow-band resonant mode. This provides remarkable resolution enhancement for edge detection applications. Rigorous analysis based on plane wave expansion is carried out and the results are verified by full-wave numerical simulation. Also for the case of multilayer structure, the thickness of layers is tuned using an optimization algorithm to represent a better approximation of an ideal high pass filter. The application of the designed high pass filters for edge detection of input field profiles is demonstrated for both 1D and 2D operations. The proposed devices are compact and no Fourier lens is required, since the operator is directly implemented in the spatial Fourier domain.
|
physics
|
A wide range of experimental systems including gliding, swarming and swimming bacteria, in-vitro motility assays as well as shaken granular media are commonly described as self-propelled rods. Large ensembles of those entities display a large variety of self-organized, collective phenomena, including formation of moving polar clusters, polar and nematic dynamic bands, mobility-induced phase separation, topological defects and mesoscale turbulence, among others. Here, we give a brief survey of experimental observations and review the theoretical description of self-propelled rods. Our focus is on the emergent pattern formation of ensembles of dry self-propelled rods governed by short-ranged, contact mediated interactions and their wet counterparts that are also subject to long-ranged hydrodynamic flows. Altogether, self-propelled rods provide an overarching theme covering many aspects of active matter containing well-explored limiting cases. Their collective behavior not only bridges the well-studied regimes of polar self-propelled particles and active nematics, and includes active phase separation, but also reveals a rich variety of new patterns.
|
condensed matter
|
We propose a $\mu-\tau$ reflection symmetric Littlest Seesaw ($\mu\tau$-LSS) model. In this model the two mass parameters of the LSS model are fixed to be in a special ratio by symmetry, so that the resulting neutrino mass matrix in the flavour basis (after the seesaw mechanism has been applied) satisfies $\mu-\tau$ reflection symmetry and has only one free adjustable parameter, namely an overall free mass scale. However the physical low energy predictions of the neutrino masses and lepton mixing angles and CP phases are subject to renormalisation group (RG) corrections, which introduces further parameters. Although the high energy model is rather complicated, involving $(S_4\times U(1))^2$ and supersymmetry, with many flavons and driving fields, the low energy neutrino mass matrix has ultimate simplicity.
|
high energy physics phenomenology
|
The dynamic dispatch (DD) of battery energy storage systems (BESSs) in microgrids integrated with volatile energy resources is essentially a multiperiod stochastic optimization problem (MSOP). Because the life span of a BESS is significantly affected by its charging and discharging behaviors, its lifecycle degradation costs should be incorporated into the DD model of BESSs, which makes it non-convex. In general, this MSOP is intractable. To solve this problem, we propose a reinforcement learning (RL) solution augmented with Monte-Carlo tree search (MCTS) and domain knowledge expressed as dispatching rules. In this solution, the Q-learning with function approximation is employed as the basic learning architecture that allows multistep bootstrapping and continuous policy learning. To improve the computation efficiency of randomized multistep simulations, we employed the MCTS to estimate the expected maximum action values. Moreover, we embedded a few dispatching rules in RL as probabilistic logics to reduce infeasible action explorations, which can improve the quality of the data-driven solution. Numerical test results show the proposed algorithm outperforms other baseline RL algorithms in all cases tested.
|
electrical engineering and systems science
|
The R\'enyi entropies of quasiparticle excitations in the many-body gapped systems show a remarkable universal picture which can be understood partially by combination of a semiclassical argument with the quantum effect of (in)distinguishability. The universal R\'enyi entropies are independent of the model, the quasiparticle momenta, and the connectedness of the subsystem. In this letter we calculate exactly the single-interval and double-interval R\'enyi entropies of quasiparticle excitations in the many-body gapped fermions, bosons, and XY chains. We find additional contributions to the universal R\'enyi entropy in the excited states with quasiparticles of different momenta. The additional terms are different in the fermionic and bosonic chains, depend on the momentum differences of the quasiparticles, and are different for the single interval and the double interval. We derive the analytical R\'enyi entropy in the extremely gapped limit, matching perfectly the numerical results as long as either the intrinsic correlation length of the model or all the de Broglie wavelengths of the quasiparticles are small. When the momentum difference of any pair of distinct quasiparticles is small, the additional terms are non-negligible. On the contrary, when the difference of the momenta of each pair of distinct quasiparticles is large, the additional terms could be neglected. The universal single-interval R\'enyi entropy and its additional terms in the XY chain are the same as those in the fermionic chain, while the universal R\'enyi entropy of the double intervals and its additional terms are different, due to the fact that the local degrees of freedom of the XY chain are the Pauli matrices not the spinless fermions. We argue that the derived formulas have universal properties and can be applied for a wider range of models than those discussed here.
|
condensed matter
|
A few decades earlier, Kirkaldy and Lane proposed an indirect method of estimating the tracer and intrinsic diffusion coefficients in a ternary system (without showing experimental verification), which is otherwise impossible following the Kirkendall marker experiments. Subsequently, Manning proposed the relations between the tracer and intrinsic diffusion coefficients in the multicomponent system by extending the Onsager formalism (although could not be estimated by intersecting the diffusion couples). By solving these issues in this article, we have now proposed the equations and method for estimating these parameters in pseudo-ternary diffusion couples in which diffusion paths can be intersected in multicomponent space. We have chosen NiCoFeCr system for verification of this method because of the availability of good quality diffusion couple experiments and estimated tracer diffusion coefficients of all the components measured by the radiotracer method. An excellent match is found when the tracer diffusion coefficients estimated following the newly proposed method are compared with the data estimated following the radiotracer method. Following, the intrinsic diffusion coefficients are estimated experimentally in a multicomponent system for the first time highlighting diffusional interactions between the components. We have further shown that the intrinsic diffusion coefficients are the same (if the vacancy wind effect is negligible/neglected) when estimated from other types of diffusion couples (pseudo-binary and body diagonal) in the same multi-component system. This method can be now extended to the Al, Ga, Si containing systems in which the estimation of tracer diffusion coefficients following the radiotracer method is difficult/impossible because of various reasons.
|
condensed matter
|
Results from the LSND and MiniBooNE experiments have been interpreted as evidence for a sterile neutrino with a mass near the electronvolt scale. Here we propose to test such a scenario by measuring the coherent elastic scattering rate of neutrinos from a pulsed spallation source. Coherent scattering is universal across all active neutrino flavors, and thus can provide a measurement of the total Standard Model neutrino flux. By performing measurements over different baselines and making use of timing information, it is possible to significantly reduce the systematic uncertainties and to independently measure the fluxes of neutrinos that originate as $\nu_{\mu}$ or as either $\nu_e$ or $\bar{\nu}_{\mu}$. We find that a 100 kg CsI detector would be sensitive to the large fraction of the sterile neutrino parameter space that could potentially account for the LSND and MiniBooNE anomalies.
|
high energy physics phenomenology
|
Perturbative string amplitudes are correctly derived from the string geometry theory, which is one of the candidates of a non-perturbative formulation of string theory. In order to derive non-perturbative effects rather easily, we formulate topological string geometry theory. We derive the perturbative partition function of the topological string theory from fluctuations around a classical solution in the topological string geometry theory.
|
high energy physics theory
|
A fractional matching of a graph $G$ is a function $f:E(G) \to [0,1]$ such that for any $v\in V(G)$, $\sum_{e\in E_G(v)}f(e)\leq 1$ where $E_G(v) = \{e \in E(G): e$ is incident with $v$ in $G\}$. The fractional matching number of $G$ is $\mu_{f}(G) = \max\{\sum_{e\in E(G)} f(e): f$ is fractional matching of $G\}$. For any real numbers $a \ge 0$ and $k \in (0, n)$, it is observed that if $n = |V(G)|$ and $\delta(G) > \frac{n-k}{2}$, then $\mu_{f}(G)>\frac{n-k}{2}$. We determine a function $\varphi(a, n,\delta, k)$ and show that for a connected graph $G$ with $n = |V(G)|$, $\delta(G) \leq\frac{n-k}{2}$, spectral radius $\lambda_1(G)$ and complement $\overline{G}$, each of the following holds. (i) If $\lambda_{1}(aD(G)+A(G))<\varphi(a, n, \delta, k),$ then $\mu_{f}(G)>\frac{n-k}{2}.$ (ii) If $\lambda_{1}(aD(\overline{G})+A(\overline{G}))<(a+1)(\delta+k-1),$ then $\mu_{f}(G)>\frac{n-k}{2}.$ As corollaries, sufficient spectral condition for fractional perfect matchings and analogous results involving $Q$-index and $A_{\alpha}$-spectral radius are obtained, and former spectral results in [European J. Combin. 55 (2016) 144-148] are extended.
|
mathematics
|
We demonstrate the realization of the resonant spin amplification (RSA) effect in Faraday geometry where a magnetic field is applied parallel to the optically induced spin polarization so that no RSA is expected. However, model considerations predict that it can be realized for a central spin interacting with a fluctuating spin environment. As a demonstrator, we choose an ensemble of singly-charged (In,Ga)As/GaAs quantum dots, where the resident electron spins interact with the surrounding nuclear spins. The observation of RSA in Faraday geometry requires intense pump pulses with a high repetition rate and can be enhanced by means of the spin-inertia effect. Potentially, it provides the most direct and reliable tool to measure the longitudinal $g$ factor of the charge carriers.
|
condensed matter
|
We investigate the nature of the time-reversal breaking pairing state in the hole-doped monolayer MoS$_{2}$ on the basis of the realistic three-orbital attractive Hubbard-like model with the atomic spin-orbit coupling. Due to the multi-band features arising from the Mo $d$ orbitals in the noncentrosymmetric crystal structure, the Lifshitz transition takes place upon hole doping. Across the Lifshitz transition point, the sign of the relative phase between the Cooper-pair components drastically changes, leading to the emergence of the time-reversal breaking phase with complex gap functions. It is shown that this intriguing pairing state is characterized by the finite momentum-space distributions of the orbital and spin angular momentum with three-fold rotational symmetry on the Fermi-surface pockets around K and K$'$ points. The present mechanism for the time-reversal breaking superconductivity can ubiquitously be applied to spin-orbit-coupled metals in noncentrosymmetric crystal structures.
|
condensed matter
|
Performing multiple experiments is common when learning internal mechanisms of complex systems. These experiments can include perturbations to parameters or external disturbances. A challenging problem is to efficiently incorporate all collected data simultaneously to infer the underlying dynamic network. This paper addresses the reconstruction of dynamic networks from heterogeneous datasets under the assumption that underlying networks share the same Boolean structure across all experiments. Parametric models for dynamical structure functions are derived to describe causal interactions between measured variables. Multiple datasets are integrated into one regression problem with additional demands of group sparsity to assure network sparsity and structure consistency. To acquire structured group sparsity, we propose a sampling-based method, together with extended versions of l1 methods and sparse Bayesian learning. The performance of the proposed methods is benchmarked in numerical simulation. In summary, this paper presents efficient methods on network reconstruction from multiple experiments, and reveals practical experience that could guide applications.
|
computer science
|
A classical local cellular automaton can describe an interacting quantum field theory for fermions. We construct a simple classical automaton for a particular version of the Thirring model with imaginary coupling. This interacting fermionic quantum field theory obeys a unitary time evolution and shows all properties of quantum mechanics. Classical cellular automata with probabilistic initial conditions admit a description in the formalism of quantum mechanics. Our model exhibits interesting features as spontaneous symmetry breaking or solitons. The same model can be formulated as a generalized Ising model. This euclidean lattice model can be investigated by standard techniques of statistical physics as Monte Carlo simulations. Our model is an example how quantum mechanics emerges from classical statistics.
|
quantum physics
|
We show that the constraints which follow from the {\it Trans-Planckian Censorship Conjecture} for inflationary cosmology can be strengthened if the pre-inflationary universe was dominated by radiation. The resulting upper bound on the energy scale of inflation is $\eta \sim 10^4 {\rm GeV}$, close to the scale accessible to accelerator experiments.
|
high energy physics theory
|
We consider the thermodynamical behavior of Banks-Zaks theory close to the conformal point in a cosmological setting. Due to the anomalous dimension, the resulting pressure and energy density deviate from that of radiation and result in various interesting cosmological scenarios. Specifically, for a given range of parameters one avoids the cosmological singularity. We provide a full "phase diagram" of possible Universe evolution for the given parameters. For a certain range of parameters, the thermal averaged Banks-Zaks theory alone results in an exponentially contracting universe followed by a non-singular bounce and an exponentially expanding universe, i.e. \textit{Inflation without a Big Bang singularity}, or shortly termed "dS Bounce". The temperature of such a universe is bounded from above and below. The result is a theory violating the classical Null Energy Condition (NEC). Considering the Banks-Zaks theory with an additional perfect fluid, yields an even richer phase diagram that includes the standard Big Bang model, stable single "normal" bounce, dS Bounce and stable cyclic solutions. The bouncing and cyclic solutions are with no singularities, and the violation of the NEC happens only near the bounce. We also provide simple analytical conditions for the existence of these non-singular solutions. Hence, within effective field theory, we have a new alternative non-singular cosmology based on the anomalous dimension of Bank-Zaks theory that may include inflation and without resorting to scalar fields.
|
high energy physics theory
|
We present a slot-wise, object-based transition model that decomposes a scene into objects, aligns them (with respect to a slot-wise object memory) to maintain a consistent order across time, and predicts how those objects evolve over successive frames. The model is trained end-to-end without supervision using losses at the level of the object-structured representation rather than pixels. Thanks to its alignment module, the model deals properly with two issues that are not handled satisfactorily by other transition models, namely object persistence and object identity. We show that the combination of an object-level loss and correct object alignment over time enables the model to outperform a state-of-the-art baseline, and allows it to deal well with object occlusion and re-appearance in partially observable environments.
|
computer science
|
We present an algorithm for the generalized search problem (searching $k$ marked items among $N$ items) based on a continuous Hamiltonian and exploiting resonance. This resonant algorithm has the same time complexity $O(\sqrt{N/k})$ as the Grover algorithm. A natural extension of the algorithm, incorporating auxiliary "monitor" qubits, can determine $k$ precisely, if it is unknown. The time complexity of our counting algorithm is $O(\sqrt{N})$, similar to the best quantum approximate counting algorithm, or better, given appropriate physical resources.
|
quantum physics
|
We develop a new twistorial field formulation of a massless infinite spin particle. Unlike our previous approach arXiv:1805.09706, the quantization of such a world-line infinite spin particle model is carried without any gauge fixing. As a result, we construct a twistorial infinite spin field and derive its helicity decomposition. Using the field twistor transform, we construct the space-time infinite (continuous) spin field, which depends on the coordinate four-vector and additional commuting Weyl spinor. The equations of motion for infinite spin fields in the cases of integer and half-integer helicities are derived. We show that the infinite integer-spin field and infinite half-integer-spin field form the $\mathcal{N}{=}\,1$ infinite spin supermultiplet. The corresponding supersymmetry transformations are formulated and their on-shell algebra is derived. As a result, we find the field realization of the infinite spin $\mathcal{N}{=}\,1$ supersymmetry.
|
high energy physics theory
|
This paper targets at the problem of radio resource management for expected long-term delay-power tradeoff in vehicular communications. At each decision epoch, the road side unit observes the global network state, allocates channels and schedules data packets for all vehicle user equipment-pairs (VUE-pairs). The decision-making procedure is modelled as a discrete-time Markov decision process (MDP). The technical challenges in solving an optimal control policy originate from highly spatial mobility of vehicles and temporal variations in data traffic. To simplify the decision-making process, we first decompose the MDP into a series of per-VUE-pair MDPs. We then propose an online long short-term memory based deep reinforcement learning algorithm to break the curse of high dimensionality in state space faced by each per-VUE-pair MDP. With the proposed algorithm, the optimal channel allocation and packet scheduling decision at each epoch can be made in a decentralized way in accordance with the partial observations of the global network state at the VUE-pairs. Numerical simulations validate the theoretical analysis and show the effectiveness of the proposed online learning algorithm.
|
electrical engineering and systems science
|
Active particles often swim in confined environments. The transport mechanisms, especially the global one as reflected by the Taylor dispersion model, are of great practical interest to various applications. For active dispersion process in confined flows, previous analytical studies focused on the long-time asymptotic values of dispersion characteristics. Only several numerical studies preliminarily investigated the temporal evolution. Extending recent studies of Jiang & Chen (J. Fluid Mech., vol. 877, 2019, pp. 1--34; J. Fluid Mech., vol. 899, 2020, A18), this work makes the first analytical attempt to investigate the transient process. The temporal evolution of the local distribution in the confined-section--orientation space, drift, dispersivity and skewness, is explored based on moments of distributions. We introduce the biorthogonal expansion method for solutions because the classic integral transform method for passive transport problems is not applicable due to the self-propulsion effect. Two types of boundary condition, the reflective condition and the Robin condition for wall accumulation, are imposed respectively. A detailed study on spherical and ellipsoidal swimmers dispersing in a plane Poiseuille flow demonstrates the influences of the swimming, shear flow, wall accumulation and particle shape on the transient dispersion process after a point-source release. The swimming-induced diffusion makes the local distribution reach its equilibrium state faster than that of passive particles. Though the wall accumulation significantly affects the evolution of the local distribution and the drift, the time scale to reach the Taylor regime is not obviously changed. The shear-induced alignment of ellipsoidal particles can enlarge the dispersivity but has less influence on the drift and the skewness.
|
physics
|
Medical Ultrasound (US), despite its wide use, is characterized by artifacts and operator dependency. Those attributes hinder the gathering and utilization of US datasets for the training of Deep Neural Networks used for Computer-Assisted Intervention Systems. Data augmentation is commonly used to enhance model generalization and performance. However, common data augmentation techniques, such as affine transformations do not align with the physics of US and, when used carelessly can lead to unrealistic US images. To this end, we propose a set of physics-inspired transformations, including deformation, reverb and Signal-to-Noise Ratio, that we apply on US B-mode images for data augmentation. We evaluate our method on a new spine US dataset for the tasks of bone segmentation and classification.
|
electrical engineering and systems science
|
Optical dual-pulse pumping actively creates quantum-mechanical superposition of the electronic and phononic states in a bulk solid. We here made transient reflectivity measurements in an n-GaAs using a pair of relative-phase-locked femtosecond pulses and found characteristic interference fringes. This is a result of quantum-path interference peculiar to the dual-pulse excitation as indicated by theoretical calculation. Our observation reveals that the pathway of coherent phonon generation in the n-GaAs is impulsive stimulated Raman scattering at the displaced potential due to the surface-charge field, even though the photon energy lies in the opaque region.
|
condensed matter
|
We prove $L^2$ stability estimates for entropic shocks among weak, possibly \emph{non-entropic}, solutions of scalar conservation laws $\partial_t u+\partial_x f(u)=0$ with strictly convex flux function $f$. This generalizes previous results by Leger and Vasseur, who proved $L^2$ stability among entropy solutions. Our main result, the estimate \begin{align*} \int_{\mathbb R} |u(t,\cdot)-u_0^{shock}(\cdot -x(t))|^2\,dx\leq \int_{\mathbb R}|u_0-u_0^{shock}|^2 +C\mu_+([0,t]\times\R), \end{align*} for some Lipschitz shift $x(t)$, includes an error term accounting for the positive part of the entropy production measure $\mu=\partial_t(u^2/2)+\partial_x q(u)$, where $q'(u)=uf'(u)$. Stability estimates in this general non-entropic setting are of interest in connection with large deviation principles for the hydrodynamic limit of asymmetric interacting particle systems. Our proof adapts the scheme devised by Leger and Vasseur, where one constructs a shift $x(t)$ which allows to bound from above the time-derivative of the left-hand side. The main difference lies in the fact that our solution $u(t,\cdot)$ may present a non-entropic shock at $x=x(t)$ and new bounds are needed in that situation. We also generalize this stability estimate to initial data with bounded variation.
|
mathematics
|
Indoor autonomous navigation requires a precise and accurate localization system able to guide robots through cluttered, unstructured and dynamic environments. Ultra-wideband (UWB) technology, as an indoor positioning system, offers precise localization and tracking, but moving obstacles and non-line-of-sight occurrences can generate noisy and unreliable signals. That, combined with sensors noise, unmodeled dynamics and environment changes can result in a failure of the guidance algorithm of the robot. We demonstrate how a power-efficient and low computational cost point-to-point local planner, learnt with deep reinforcement learning (RL), combined with UWB localization technology can constitute a robust and resilient to noise short-range guidance system complete solution. We trained the RL agent on a simulated environment that encapsulates the robot dynamics and task constraints and then, we tested the learnt point-to-point navigation policies in a real setting with more than two-hundred experimental evaluations using UWB localization. Our results show that the computational efficient end-to-end policy learnt in plain simulation, that directly maps low-range sensors signals to robot controls, deployed in combination with ultra-wideband noisy localization in a real environment, can provide a robust, scalable and at-the-edge low-cost navigation system solution.
|
computer science
|
Two of the important implications of the seesaw mechanism are: (i) a simple way to understand the small neutrino masses, and (ii) the origin of matter-anti-matter asymmetry in the universe via the leptogenesis mechanism. For TeV-scale seesaw models, successful leptogenesis requires that the right-handed neutrinos (RHNs) must be quasi-degenerate and if they have CP violating phases, they also contribute to the CP asymmetry. We investigate this in the TeV-scale left-right models for seesaw and point out a way to probe the quasi-degeneracy possibility with CP violating mixings for RHNs in hadron colliders using simple observables constructed out of same-sign dilepton charge asymmetry (SSCA). In particular, we isolate the parameter regions of the model, where the viability of leptogenesis can be tested using the SSCA at the Large Hadron Collider, as well as future 27 TeV and 100 TeV hadron colliders. We also independently confirm an earlier result that there is a generic lower bound on the $W_R$ mass of about 10 TeV for leptogenesis to work.
|
high energy physics phenomenology
|
Recently, the first ever lattice computation of the $\gamma W$-box radiative correction to the rate of the semileptonic pion decay allowed for a reduction of the theory uncertainty of that rate by a factor of $\sim3$. A recent dispersion evaluation of the $\gamma W$-box correction on the neutron also led to a significant reduction of the theory uncertainty, but shifted the value of $V_{ud}$ extracted from the neutron and superallowed nuclear $\beta$ decay, resulting in a deficit of the CKM unitarity in the top row. A direct lattice computation of the $\gamma W$-box correction for the neutron decay would provide an independent cross-check for this result but is very challenging. Before those challenges are overcome, we propose a hybrid analysis, converting the lattice calculation on the pion to that on the neutron by a combination of dispersion theory and phenomenological input. The new prediction for the universal radiative correction to free and bound neutron $\beta$-decay reads $\Delta_R^V=0.02477(24)$, in excellent agreement with the dispersion theory result $\Delta_R^V=0.02467(22)$. Combining with other relevant information, the top-row CKM unitarity deficit persists.
|
high energy physics phenomenology
|
We study a model of a large number of strongly coupled phonons that can be viewed as a bosonic variant of the Sachdev-Ye-Kitaev model. We determine the phase diagram of the model which consists of a glass phase and a disordered phase, with a first-order phase transition separating them. We compute the specific heat of the disordered phase, with which we diagnose the high-temperature crossover to the classical limit. We further study the real-time dynamics of the disordered phase, where we identify three dynamical regimes as a function of temperature. Low temperatures are associated with a semiclassical regime, where the phonons can be described as long-lived normal modes. High temperatures are associated with the classical limit of the model. For a large region in parameter space, we identify an intermediate-temperatures regime, where the phonon lifetime is of the order of the Planckian time scale $\hbar/k_B T$.
|
condensed matter
|
Recently, there has been growth in providers of speech transcription services enabling others to leverage technology they would not normally be able to use. As a result, speech-enabled solutions have become commonplace. Their success critically relies on the quality, accuracy, and reliability of the underlying speech transcription systems. Those black box systems, however, offer limited means for quality control as only word sequences are typically available. This paper examines this limited resource scenario for confidence estimation, a measure commonly used to assess transcription reliability. In particular, it explores what other sources of word and sub-word level information available in the transcription process could be used to improve confidence scores. To encode all such information this paper extends lattice recurrent neural networks to handle sub-words. Experimental results using the IARPA OpenKWS 2016 evaluation system show that the use of additional information yields significant gains in confidence estimation accuracy. The implementation for this model can be found online.
|
electrical engineering and systems science
|
Many unsupervised representation learning methods belong to the class of similarity learning models. While various modality-specific approaches exist for different types of data, a core property of many methods is that representations of similar inputs are close under some similarity function. We propose EMDE (Efficient Manifold Density Estimator) - a framework utilizing arbitrary vector representations with the property of local similarity to succinctly represent smooth probability densities on Riemannian manifolds. Our approximate representation has the desirable properties of being fixed-size and having simple additive compositionality, thus being especially amenable to treatment with neural networks - both as input and output format, producing efficient conditional estimators. We generalize and reformulate the problem of multi-modal recommendations as conditional, weighted density estimation on manifolds. Our approach allows for trivial inclusion of multiple interaction types, modalities of data as well as interaction strengths for any recommendation setting. Applying EMDE to both top-k and session-based recommendation settings, we establish new state-of-the-art results on multiple open datasets in both uni-modal and multi-modal settings.
|
statistics
|
Pulsar candidate sifting is an essential process for discovering new pulsars. It aims to search for the most promising pulsar candidates from an all-sky survey, such as High Time Resolution Universe (HTRU), Green Bank Northern Celestial Cap (GBNCC), Five-hundred-meter Aperture Spherical radio Telescope (FAST), etc. Recently, machine learning (ML) is a hot topic in pulsar candidate sifting investigations. However, one typical challenge in ML for pulsar candidate sifting comes from the learning difficulty arising from the highly class-imbalance between the observation numbers of pulsars and non-pulsars. Therefore, this work proposes a novel framework for candidate sifting, named multi-input convolutional neural networks (MICNN). The MICNN is an architecture of deep learning with four diagnostic plots of a pulsar candidate as its inputs. To train our MICNN in a highly class-imbalanced dataset, a novel image augment technique, as well as a three-stage training strategy, is proposed. Experiments on observations from HTRU and GBNCC show the effectiveness and robustness of these proposed techniques. In the experiments on HTRU, our MICNN model achieves a recall of 0.962 and a precision rate of 0.967 even in a highly class-imbalanced test dataset.
|
astrophysics
|
Velocity statistics is a direct probe of the dynamics of interstellar turbulence. Its observational measurements are very challenging due to the convolution between density and velocity and projection effects. We introduce the projected velocity structure function, which can be generally applied to statistical studies of both sub- and super-sonic turbulence in different interstellar phases. It recovers the turbulent velocity spectrum from the projected velocity field in different regimes, and when the thickness of a cloud is less than the driving scale of turbulence, it can also be used to determine the cloud thickness and the turbulence driving scale. By applying it to the existing core velocity dispersion measurements of the Taurus cloud, we find a transition from the Kolmogorov to the Burgers scaling of turbulent velocities with decreasing length scales, corresponding to the large-scale solenoidal motions and small-scale compressive motions, respectively. The latter occupy a small fraction of the volume and can be selectively sampled by clusters of cores with the typical cluster size indicated by the transition scale.
|
astrophysics
|
The need to recognise long-term dependencies in sequential data such as video streams has made Long Short-Term Memory (LSTM) networks a prominent Artificial Intelligence model for many emerging applications. However, the high computational and memory demands of LSTMs introduce challenges in their deployment on latency-critical systems such as self-driving cars which are equipped with limited computational resources on-board. In this paper, we introduce a progressive inference computing scheme that combines model pruning and computation restructuring leading to the best possible approximation of the result given the available latency budget of the target application. The proposed methodology enables mission-critical systems to make informed decisions even in early stages of the computation, based on approximate LSTM inference, meeting their specifications on safety and robustness. Our experiments on a state-of-the-art driving model for autonomous vehicle navigation demonstrate that the proposed approach can yield outputs with similar quality of result compared to a faithful LSTM baseline, up to 415x faster (198x on average, 76x geo. mean).
|
electrical engineering and systems science
|
Let $K=\mathbb{Q}(\alpha)$ be a number field generated by a complex root $\alpha$ of a monic irreducible polynomial $f(x)=x^{12}-m$, with $m\neq 1$ is a square free rational integer. In this paper, we prove that if $m \equiv 2$ or $3$ (mod 4) and $m\not\equiv \mp 1$ (mod 9), then the number field $K$ is monogenic. If $m \equiv 1$ (mod 8) or $m\equiv \mp 1$ (mod 9), then the number field $K$ is not monogenic.
|
mathematics
|
Univariate concepts as quantile and distribution functions involving ranks and signs, do not canonically extend to $\mathbb{R}^d, d\geq 2$. Palliating that has generated an abundant literature. Chapter 1 shows that, unlike the many definitions that have been proposed so far, the measure transportation-based ones introduced in Chernozhukov et al. (2017) enjoy all the properties that make univariate quantiles and ranks successful tools for semiparametric statistical inference. We therefore propose a new center-outward definition of multivariate distribution and quantile functions, along with their empirical counterparts, for which we obtain a Glivenko-Cantelli result. Our approach is geometric and, contrary to the Monge-Kantorovich one in Chernozhukov et al. (2017), does not require any moment assumptions. The resulting ranks and signs are strictly distribution-free, and maximal invariant under the action of a data-driven class of (order-preserving) transformations generating the family of absolutely continuous distributions; that property is the theoretical foundation of the semiparametric efficiency preservation property of ranks. The corresponding quantiles are equivariant under the same transformations. The empirical proposed distribution functions are defined at observed values only. A continuous extension to the entire $\mathbb{R}^d$, yielding continuous empirical quantile contours while preserving the monotonicity and Glivenko-Cantelli features is desirable. Such extension requires solving a nontrivial problem of smooth interpolation under cyclical monotonicity constraints. A complete solution of that problem is given in Chapter 2; we show that the resulting distribution and quantile functions are Lipschitz, and provide a sharp lower bound for the Lipschitz constants. A numerical study of empirical center-outward quantile contours and their consistency is conducted.
|
statistics
|
Porous materials are widely used in different applications, in particular they are used to create various filters. Their quality depends on parameters that characterize the internal structure such as porosity, permeability and so on. Computed tomography (CT) allows one to see the internal structure of a porous object without destroying it. The result of tomography is a gray image. To evaluate the desired parameters, the image should be segmented. Traditional intensity threshold approaches did not reliably produce correct results due to limitations with CT images quality. Errors in the evaluation of characteristics of porous materials based on segmented images can lead to the incorrect estimation of their quality and consequently to the impossibility of exploitation, financial losses and even to accidents. It is difficult to perform correctly segmentation due to the strong difference in voxel intensities of the reconstructed object and the presence of noise. Image filtering as a preprocessing procedure is used to improve the quality of segmentation. Nevertheless, there is a problem of choosing an optimal filter. In this work, a method for selecting an optimal filter based on attributive indicator of porous objects (should be free from 'levitating stones' inside of pores) is proposed. In this paper, we use real data where beam hardening artifacts are removed, which allows us to focus on the noise reduction process
|
computer science
|
Determining the inner structure of protons and nuclei in terms of their fundamental constituents has been one of the main tasks of high energy nuclear and particle physics experiments. This quest started as a mapping of the (average) parton densities as a function of longitudinal momentum fraction and resolution scale. Recently, the field has progressed to more differential imaging, where one important development is the description of the event-by-event quantum fluctuations in the wave function of the colliding hadron. In this Review, recent developments on the extraction of proton and nuclear transverse geometry with event-by-event fluctuations from collider experiments at high energy is presented. The importance of this fundamentally interesting physics in other collider experiments like in studies of the properties of the Quark Gluon Plasma is also illustrated.
|
high energy physics phenomenology
|
Dynamical quantum phase transitions (DQPTs) are characterized by nonanalytic behaviors of physical observables as functions of time. When a system is subject to time-periodic modulations, the nonanalyticity of its observables could recur periodically in time, leading to the phenomena of Floquet DQPTs. In this work, we systematically explore Floquet DQPTs in a class of periodically quenched one-dimensional system with chiral symmetry. By tuning the strength of quench, we find multiple Floquet DQPTs within a single driving period, with more DQPTs being observed when the system is initialized in Floquet states with larger topological invariants. Each Floquet DQPT is further accompanied by the quantized jump of a dynamical topological order parameter, whose values remain quantized in time if the underlying Floquet system is prepared in a gapped topological phase. The theory is demonstrated in a piecewise quenched lattice model, which possesses rich Floquet topological phases and is readily realizable in quantum simulators like the nitrogen-vacancy center in diamonds. Our discoveries thus open a new perspective for the Floquet engineering of DQPTs and the dynamical detection of topological phase transitions in Floquet systems.
|
quantum physics
|
The quark-hadron crossover conjecture was proposed as a continuity between hadronic matter and quark matter with no phase transition. It is based on matching of symmetry and excitations in both the phases. It connects hyperon matter and color-flavor locked (CFL) phase of color superconductivity in the limit of light strange quark mass. We study generalization of this conjecture in the presence of topological vortices. We propose a picture where hadronic superfluid vortices in hyperon matter could be connected to non-Abelian vortices (color magnetic flux tubes) in the CFL phase during this crossover. We propose that three hadronic superfluid vortices must join together to three non-Abelian vortices with different color fluxes with the total color magnetic fluxes canceled out, where the junction is called a colorful boojum.
|
high energy physics phenomenology
|
The methods for controlling spin states of negatively charged nitrogen-vacancy (NV) centers using microwave (MW) or radiofrequency (RF) excitation fields for electron spin and nuclear spin transitions are effective in strong magnetic fields where a level anti-crossing (LAC) occurs. A LAC can also occur at zero field in the presence of transverse strain or electric fields in the diamond crystal, leading to mixing of the spin states. In this paper, we investigate zero-field LAC of NV centers using dual-frequency excitation spectroscopy. Under RF modulation of the spin states, we observe sideband transitions and Autler-Townes splitting in the optically detected magnetic resonance (ODMR) spectra. Numerical simulations show that the splitting originates from Landau-Zener transition between electron spin |$\pm$1> states, which potentially provides a new way of manipulating NV center spin states in zero or weak magnetic field.
|
quantum physics
|
Two-dimensional melting is one of the most fascinating and poorly understood phase transitions in nature. Theoretical investigations often point to a two-step melting scenario involving unbinding of topological defects at two distinct temperatures. Here we report on a novel melting transition of a charge-ordered K-Sn alloy monolayer on a silicon substrate. Melting starts with short-range positional fluctuations in the K sublattice while maintaining long-range order, followed by longer-range K diffusion over small domains, and ultimately resulting in a molten sublattice. Concomitantly, the charge-order of the Sn host lattice collapses in a multi-step process with both displacive and order-disorder transition characteristics. Our combined experimental and theoretical analysis provides a rare insight into the atomistic processes of a multi-step melting transition of a two-dimensional materials system.
|
condensed matter
|
We consider obstacle problems for the Willmore functional in the class of graphs of functions and surfaces of revolution with Dirichlet boundary conditions. We prove the existence of minimisers of the obstacle problems under the assumption that the Willmore energy with the unilateral constraint is below a universal bound. We address the question whether such bounds are necessary in order to ensure the solvability of the obstacle problems. Moreover, we give several instructive examples of obstacles such that minimisers exist.
|
mathematics
|
Depth data provide geometric information that can bring progress in RGB-D scene parsing tasks. Several recent works propose RGB-D convolution operators that construct receptive fields along the depth-axis to handle 3D neighborhood relations between pixels. However, these methods pre-define depth receptive fields by hyperparameters, making them rely on parameter selection. In this paper, we propose a novel operator called malleable 2.5D convolution to learn the receptive field along the depth-axis. A malleable 2.5D convolution has one or more 2D convolution kernels. Our method assigns each pixel to one of the kernels or none of them according to their relative depth differences, and the assigning process is formulated as a differentiable form so that it can be learnt by gradient descent. The proposed operator runs on standard 2D feature maps and can be seamlessly incorporated into pre-trained CNNs. We conduct extensive experiments on two challenging RGB-D semantic segmentation dataset NYUDv2 and Cityscapes to validate the effectiveness and the generalization ability of our method.
|
computer science
|
Distributional data Shapley value (DShapley) has recently been proposed as a principled framework to quantify the contribution of individual datum in machine learning. DShapley develops the foundational game theory concept of Shapley values into a statistical framework and can be applied to identify data points that are useful (or harmful) to a learning algorithm. Estimating DShapley is computationally expensive, however, and this can be a major challenge to using it in practice. Moreover, there has been little mathematical analyses of how this value depends on data characteristics. In this paper, we derive the first analytic expressions for DShapley for the canonical problems of linear regression, binary classification, and non-parametric density estimation. These analytic forms provide new algorithms to estimate DShapley that are several orders of magnitude faster than previous state-of-the-art methods. Furthermore, our formulas are directly interpretable and provide quantitative insights into how the value varies for different types of data. We demonstrate the practical efficacy of our approach on multiple real and synthetic datasets.
|
statistics
|
We use polarized photocurrent spectroscopy in a nanowire device to investigate the band structure of hexagonal Wurtzite InAs. Signatures of optical transitions between four valence bands and two conduction bands are observed which are consistent with the symmetries expected from group theory. The ground state transition energy identified from photocurrent spectra is seen to be consistent with photoluminescence emitted from a cluster of nanowires from the same growth substrate. From the energies of the observed bands we determine the spin orbit and crystal field energies in Wurtzite InAs. This information is essential to the development of crystal phase engineering of this important III-V semiconductor.
|
condensed matter
|
SAGECal has been designed to find the most accurate calibration solutions for low radio frequency imaging observations, with minimum artefacts due to incomplete sky models. SAGECAL is developed to handle extremely large datasets, e.g., when the number of frequency bands greatly exceeds the number of available nodes on a compute cluster. Accurate calibration solutions are derived at the expense of large computational loads, which require distributed computing and modern compute devices, such as GPUs, to decrease runtimes. In this work, we investigate if the GPU version of SAGECal scales well enough to meet the requirements for the Square Kilometre Array and we compare its performance with the CPU version.
|
astrophysics
|
We employ a three-dimensional molecular dynamics to simulate translocation of a polymer through a nanopore driven by an external force. The translocation is investigated for different three pore diameter and two different external forces. In order to see the polymer and pore interaction effects on translocation time, we studied 9 different interaction energies. Moreover, to better understand the simulation results we investigate polymer center of mass, shape factor and the monomer distribution through the translocation. Our results unveil that while increasing the polymer-pore interaction energy slows down the translocation, expanding the pore diameter, makes the translocation faster. The shape analysis of the results reveals that the polymer shape is very sensitive to the interaction energy. In high interactions, the monomers come close to the pore from both sides. As a result, the translocation becomes fast at first and slows down at last.
|
physics
|
The spin Hall effect (SHE) and the magnetic spin Hall effect (MSHE) are responsible for electrical spin current generation, which is a key concept of modern spintronics. We theoretically investigated the spin conductivity induced by spin-dependent s-d scattering in a ferromagnetic 3d alloy model by employing microscopic transport theory based on the Kubo formula. We derived a novel extrinsic mechanism that contributes to both the SHE and MSHE. This mechanism can be understood as the contribution from anisotropic (spatial-dependent) spin-flip scattering due to the combination of the orbital-dependent anisotropic shape of s-d hybridization and spin flipping, with the orbital shift caused by spin-orbit interaction with the d-orbitals. We also show that this mechanism is valid under crystal-field splitting among the d-orbitals in either the cubic or tetragonal symmetry.
|
condensed matter
|
Modern particle accelerators and their applications increasingly rely on precisely coordinated interactions of intense charged particle and laser beams. Femtosecond-scale synchronization alongside micrometre-scale spatial precision are essential e.g. for pump-probe experiments, seeding and diagnostics of advanced light sources and for plasma-based accelerators. State-of-the-art temporal or spatial diagnostics typically operate with low-intensity beams to avoid material damage at high intensity. As such, we present a plasma-based approach, which allows measurement of both temporal and spatial overlap of high-intensity beams directly at their interaction point. It exploits amplification of plasma afterglow arising from the passage of an electron beam through a laser-generated plasma filament. The corresponding photon yield carries the spatiotemporal signature of the femtosecond-scale dynamics, yet can be observed as a visible light signal on microsecond-millimetre scales.
|
physics
|
We analyze a model demonstrating the co-existence of subsystem symmetry breaking (SSB) and symmetry-protected topological (SPT) order, or subsystem LSPT order for short. Its mathematical origin is the existence of both a subsystem and a local operator, both of which commute with the Hamiltonian but anti-commute between themselves. The reason for the exponential growth of the ground state degeneracy is attributed to the existence of subsystem symmetries, which allows one to define both the Landau order parameter and the SPT-like order for each independent loop.
|
condensed matter
|
The possibility that a discrete process can be fruitfully approximated by a continuous one, with the latter involving a differential system, is fascinating. Important theoretical insights, as well as significant computational efficiency gains may lie in store. A great success story in this regard are the Navier-Stokes equations, which model many phenomena in fluid flow rather well. Recent years saw many attempts to formulate more such continuous limits, and thus harvest theoretical and practical advantages, in diverse areas including mathematical biology, image processing, game theory, computational optimization, and machine learning. Caution must be applied as well, however. In fact, it is often the case that the given discrete process is richer in possibilities than its continuous differential system limit, and that a further study of the discrete process is practically rewarding. Furthermore, there are situations where the continuous limit process may provide important qualitative, but not quantitative, information about the actual discrete process. This paper considers several case studies of such continuous limits and demonstrates success as well as cause for caution. Consequences are discussed.
|
mathematics
|
We study (1+1)-dimensional non-linear sigma models whose target space is the flag manifold $U(N)\over U(N_1)\times U(N_2)\cdots U(N_m)$, with a specific focus on the special case $U(N)/U(1)^{N}$. These generalize the well-known $\mathbb{CP}^{N-1}$ model. The general flag model exhibits several new elements that are not present in the special case of the $\mathbb{CP}^{N-1}$ model. It depends on more parameters, its global symmetry can be larger, and its 't Hooft anomalies can be more subtle. Our discussion based on symmetry and anomaly suggests that for certain choices of the integers $N_I$ and for specific values of the parameters the model is gapless in the IR and is described by an $SU(N)_1$ WZW model. Some of the techniques we present can also be applied to other cases.
|
high energy physics theory
|
The self-supervised loss formulation for jointly training depth and egomotion neural networks with monocular images is well studied and has demonstrated state-of-the-art accuracy. One of the main limitations of this approach, however, is that the depth and egomotion estimates are only determined up to an unknown scale. In this paper, we present a novel scale recovery loss that enforces consistency between a known camera height and the estimated camera height, generating metric (scaled) depth and egomotion predictions. We show that our proposed method is competitive with other scale recovery techniques that have more information available. Further, we demonstrate how our method facilitates network retraining within new environments, whereas other scale-resolving approaches are incapable of doing so. Notably, our egomotion network is able to produce more accurate estimates than a similar method that only recovers scale at test time.
|
computer science
|
We present an overview of state of the art lattice quantum chromodynamcis calculations for heavy-light quantities. Special focus is given to the calculation of form factors for semi-leptonic decays of $B_{(s)}$ and $D$ mesons, the extraction of the Cabibbo-Kobayashi-Maskawa matrix elements $|V_{ub}|$ and $|V_{cb}|$ as well as the determination of $R(D^{(*)})$ testing the universality of lepton flavors in $b\to c$ transitions. In addition we report on the determination of $b$ and $c$ quark masses as well as on neutral $B_{(s)}$ meson mixing. Recent results are summarized and new developments highlighted.
|
high energy physics phenomenology
|
Data-driven modeling increasingly requires to find a Nash equilibrium in multi-player games, e.g. when training GANs. In this paper, we analyse a new extra-gradient method for Nash equilibrium finding, that performs gradient extrapolations and updates on a random subset of players at each iteration. This approach provably exhibits a better rate of convergence than full extra-gradient for non-smooth convex games with noisy gradient oracle. We propose an additional variance reduction mechanism to obtain speed-ups in smooth convex games. Our approach makes extrapolation amenable to massive multiplayer settings, and brings empirical speed-ups, in particular when using a heuristic cyclic sampling scheme. Most importantly, it allows to train faster and better GANs and mixtures of GANs.
|
statistics
|
We describe a regularized regression model for the selection of gene-environment (GxE) interactions. The model focuses on a single environmental exposure and induces a main-effect-before-interaction hierarchical structure. We propose an efficient fitting algorithm and screening rules that can discard large numbers of irrelevant predictors with high accuracy. We present simulation results showing that the model outperforms existing joint selection methods for (GxE) interactions in terms of selection performance, scalability and speed, and provide a real data application. Our implementation is available in the gesso R package.
|
statistics
|
The low temperature reaction between CN and benzene (C$_6$H$_6$) is of significant interest in the astrochemical community due to the recent detection of benzonitrile, the first aromatic molecule identified in the interstellar medium (ISM) using radio astronomy. Benzonitrile is suggested to be a low temperature proxy for benzene, one of the simplest aromatic molecules, which may be a precursor to polycyclic aromatic hydrocarbons (PAHs). In order to assess the robustness of benzonitrile as a proxy for benzene, low temperature kinetics measurements are required to confirm whether the reaction remains rapid at the low gas temperatures found in cold dense clouds. Here, we study the C$_6$H$_6$ + CN reaction in the temperature range 15--295 K, using the well-established CRESU technique (a French acronym standing for Reaction Kinetics in Uniform Supersonic Flow) combined with Pulsed Laser Photolysis-Laser-Induced Fluorescence (PLP-LIF). We obtain rate coefficients, $k(T)$, in the range (3.6--5.4) $\times$ 10$^{-10}$ cm$^3$ s$^{-1}$ with no obvious temperature dependence between 15--295 K, confirming that the CN + C$_6$H$_6$ reaction remains rapid at temperatures relevant to the cold ISM.
|
astrophysics
|
This paper proposes a novel approach to stereo visual odometry without stereo matching. It is particularly robust in scenes of repetitive high-frequency textures. Referred to as DSVO (Direct Stereo Visual Odometry), it operates directly on pixel intensities, without any explicit feature matching, and is thus efficient and more accurate than the state-of-the-art stereo-matching-based methods. It applies a semi-direct monocular visual odometry running on one camera of the stereo pair, tracking the camera pose and mapping the environment simultaneously; the other camera is used to optimize the scale of monocular visual odometry. We evaluate DSVO in a number of challenging scenes to evaluate its performance and present comparisons with the state-of-the-art stereo visual odometry algorithms.
|
computer science
|
We revisit the theory of strongly correlated quantum matter perturbed by Harris-marginal random-field disorder, using the simplest holographic model. We argue that for weak disorder, the ground state of the theory is not Lifshitz invariant with a non-trivial disorder-dependent dynamical exponent, as previously found. Instead, below a non-perturbatively small energy scale, we predict infrared physics becomes independent of the disorder strength.
|
high energy physics theory
|
It has recently been pointed out that Gaia is capable of detecting a stochastic gravitational wave background in the sensitivity band between the frequency of pulsar timing arrays and LISA. We argue that Gaia and THEIA has great potential for early universe cosmology, since such a frequency range is ideal for probing phase transitions in asymmetric dark matter, SIMP and the cosmological QCD transition. Furthermore, there is the potential for detecting primordial black holes in the solar mass range produced during such an early universe transition and distinguish them from those expected from the QCD epoch. Finally, we discuss the potential for Gaia and THEIA to probe topological defects and the ability of Gaia to potentially shed light on the recent NANOGrav results.
|
high energy physics phenomenology
|
This paper presents key aspects of the quantum relativistic direct-action theory that underlies the Relativistic Transactional Interpretation. It notes some crucial ways in which traditional interpretations of the direct-action theory have impeded progress in developing its quantum counterpart. Specifically, (1) the so-called 'light tight box' condition is re-examined and it is shown that the quantum version of this condition is much less restrictive than has long been assumed; and (2) the notion of a 'real photon' is disambiguated and revised to take into account that real (on-shell) photons are indeed both emitted and absorbed and therefore have finite lifetimes. Also discussed is the manner in which real, physical non-unitarity naturally arises in the quantum direct-action theory of fields, such that the measurement transition can be clearly defined from within the theory, without reference to external observers and without any need to modify quantum theory itself. It is shown that field quantization arises from the non-unitary interaction.
|
quantum physics
|
Testing for a difference in means between two groups is fundamental to answering research questions across virtually every scientific area. Classical tests control the Type I error rate when the groups are defined a priori. However, when the groups are instead defined via a clustering algorithm, then applying a classical test for a difference in means between the groups yields an extremely inflated Type I error rate. Notably, this problem persists even if two separate and independent data sets are used to define the groups and to test for a difference in their means. To address this problem, in this paper, we propose a selective inference approach to test for a difference in means between two clusters obtained from any clustering method. Our procedure controls the selective Type I error rate by accounting for the fact that the null hypothesis was generated from the data. We describe how to efficiently compute exact p-values for clusters obtained using agglomerative hierarchical clustering with many commonly used linkages. We apply our method to simulated data and to single-cell RNA-seq data.
|
statistics
|
We investigate the flavour changing neutral currents (FCNC) generated by dimension six four-fermion operators at the Large Hadron-Electron Collider (LHeC) proposed at CERN in an effective approach. This is performed by monte carlo analysis at the full detector level, as the background is successfully reduced by using invariant mass scheme to require the final states to reconstruct the mass (transverse mass) of the top quark (W boson). Our analysis shows that the future electron proton colliders like the LHeC can probe competitive limits for the top FCNC dimension six four fermion operators such as $C_{lq}^{(1)ee31} < 0.0647$, $C_{lu}^{ee31} < 0.109$, $C_{lequ}^{(1)ee31} < 0.217$ and $C_{lequ}^{(3)ee31} < 0.0209$ in the Warsaw basis.
|
high energy physics phenomenology
|
We briefly review helicity dynamics, inverse and bi-directional cascades in fluid and magnetohydrodynamic (MHD) turbulence, with an emphasis on the latter. The energy of a turbulent system, an invariant in the non-dissipative case, is transferred to small scales through nonlinear mode coupling. Fifty years ago, it was realized that, for a two-dimensional fluid, energy cascades instead to larger scales, and so does magnetic helicity in three-dimensional MHD. However, evidence obtained recently indicates that in fact, for a range of governing parameters, there are systems for which their ideal invariants can be transferred, with constant fluxes, to both the large scales and the small scales, as for MHD or rotating stratified flows, in the latter case including with quasi-geostrophic forcing. Such bi-directional, split, cascades directly affect the rate at which mixing and dissipation occur in these flows in which nonlinear eddies interact with fast waves with anisotropic dispersion laws, due for example to imposed rotation, stratification or uniform magnetic fields. The directions of cascades can be obtained in some cases through the use of phenomenological arguments, one of which we derive here following classical lines in the case of the inverse magnetic helicity cascade in electron MHD. With more highly-resolved data sets stemming from large laboratory experiments, high-performance computing and in-situ satellite observations, machine-learning tools are bringing novel perspectives to turbulence research, e.g. in helping devise new explicit sub-grid scale parameterizations, which may lead to enhanced physical insight, including in the future in the case of these new bi-directional cascades.
|
physics
|
Device-free wireless indoor localization is a key enabling technology for the Internet of Things (IoT). Fingerprint-based indoor localization techniques are a commonly used solution. This paper proposes a semi-supervised, generative adversarial network (GAN)-based device-free fingerprinting indoor localization system. The proposed system uses a small amount of labeled data and a large amount of unlabeled data (i.e., semi-supervised), thus considerably reducing the expensive data labeling effort. Experimental results show that, as compared to the state-of-the-art supervised scheme, the proposed semi-supervised system achieves comparable performance with equal, sufficient amount of labeled data, and significantly superior performance with equal, highly limited amount of labeled data. Besides, the proposed semi-supervised system retains its performance over a broad range of the amount of labeled data. The interactions between the generator, discriminator, and classifier models of the proposed GAN-based system are visually examined and discussed. A mathematical description of the proposed system is also presented.
|
electrical engineering and systems science
|
Recovering 3D human body shape and pose from 2D images is a challenging task due to high complexity and flexibility of human body, and relatively less 3D labeled data. Previous methods addressing these issues typically rely on predicting intermediate results such as body part segmentation, 2D/3D joints, silhouette mask to decompose the problem into multiple sub-tasks in order to utilize more 2D labels. Most previous works incorporated parametric body shape model in their methods and predict parameters in low-dimensional space to represent human body. In this paper, we propose to directly regress the 3D human mesh from a single color image using Convolutional Neural Network(CNN). We use an efficient representation of 3D human shape and pose which can be predicted through an encoder-decoder neural network. The proposed method achieves state-of-the-art performance on several 3D human body datasets including Human3.6M, SURREAL and UP-3D with even faster running speed.
|
computer science
|
In 1985, Callan and Harvey showed a view of gauge anomaly as a missing current into an extra-dimension, and the total contribution, including the Chern-Simons current in the bulk, is conserved. However in their computation, the edge and bulk contributions are separately evaluated and their cross correlations, which should be relevant at boundary, are simply ignored. This issue has been solved in many approaches. In this work, we revisit this issue with a complete set of eigenstates of free domain-wall Hamiltonian and give the systematic evaluation, easy to take in the higher mass correction and extend to the higher dimension.
|
high energy physics theory
|
Non-Hermitian systems can exhibit unique topological and localization properties. Here we elucidate the non-Hermitian effects on disordered topological systems by studying a non-Hermitian disordered Su-Schrieffer-Heeger model with nonreciprocal hoppings. We show that the non-Hermiticity can enhance the topological phase against disorders by increasing energy gaps. Moreover, we uncover a topological phase which emerges only under both moderate non-Hermiticity and disorders, and is characterized by localized insulating bulk states with a disorder-averaged winding number and zero-energy edge modes. Such topological phases induced by the combination of non-Hermiticity and disorders are dubbed non-Hermitian topological Anderson insulators. We also find that the system has non-monotonous localization behaviour and the topological transition is accompanied by an Anderson transition. These properties are general in other non-Hermitian models.
|
quantum physics
|
We theoretically and experimentally investigated transformations of vortex beams subjected to sector perturbations in the form of hard-edged aperture. The transformations of the vortex spectra, the orbital angular momentum, and the informational entropy of the perturbed beam were studied. We found that relatively small angular sector perturbations have almost no effect on OAM, although the informational entropy is rapidly increasing due to the birth of new optical vortices caused by diffraction by diaphragm edges. At large perturbation angles, the uncertainty principle between the angle and OAM involves vortices, with both positive and negative topological charges, so that the OAM decreases to almost zero, and the entropy increases sharply.
|
physics
|
This paper presents a self-improving lifelong learning framework for a mobile robot navigating in different environments. Classical static navigation methods require environment-specific in-situ system adjustment, e.g. from human experts, or may repeat their mistakes regardless of how many times they have navigated in the same environment. Having the potential to improve with experience, learning-based navigation is highly dependent on access to training resources, e.g. sufficient memory and fast computation, and is prone to forgetting previously learned capability, especially when facing different environments. In this work, we propose Lifelong Learning for Navigation (LLfN) which (1) improves a mobile robot's navigation behavior purely based on its own experience, and (2) retains the robot's capability to navigate in previous environments after learning in new ones. LLfN is implemented and tested entirely onboard a physical robot with a limited memory and computation budget.
|
computer science
|
Surgical robots are controlled using a priori models based on robots' geometric parameters, which are calibrated before the surgical procedure. One of the challenges in using robots in real surgical settings is that parameters change over time, consequently deteriorating control accuracy. In this context, our group has been investigating online calibration strategies without added sensors. In one step toward that goal, we have developed an algorithm to estimate the pose of the instruments' shafts in endoscopic images. In this study, we build upon that earlier work and propose a new framework to more precisely estimate the pose of a rigid surgical instrument. Our strategy is based on a novel pose estimation model called MBAPose and the use of synthetic training data. Our experiments demonstrated an improvement of 21 % for translation error and 26 % for orientation error on synthetic test data with respect to our previous work. Results with real test data provide a baseline for further research.
|
computer science
|
In view of noteworthy communications performance improvements for future B5G/6G (such as cognitive Internet of Things, space-ground integration network and so on), cooperative communications (CC) diversity with relays selection algorithms have been extensively studied to significantly improve communications quality, but so far there is still a lot of potential optimization work with CC schemes. In this paper, in the light of NP-hard problem of subsets relays selection, further studies for theorems of relays subsets with K-layers power allocation standard have been put forward to explore better performance in B5G/6G cognitive IoT (Internet of Things) networks, we propose unified layers-based optimized mobile relays subsets algorithms for full-duplex (FD) non-orthogonal multiple access (NOMA) to greatly improve transmission rate. After revealing and taking into account fundamental properties of relays, such as mobile relays nodes state, relays locations, fading characteristics and so on, optimized FD-NOMA algorithm based on these relays features has been presented to improve transmission validity, and a related series of relays subsets theorems have been derived and proved, then minimum upper bound of maximum transmission rates has been estimated to reveal two-way balanced optimal transmission conclusion for FD-NOMA. In general, proposed general and optimized algorithm can be used in multiple future cooperative communications scenarios in B5G/6G networks such as cognitive IoT. Simulations results show that proposed scheme has several times transmission rates than other classical relays selection algorithms
|
computer science
|
Jordan algebras were first introduced in an effort to restructure quantum mechanics purely in terms of physical observables. In this paper we explain why, if one attempts to reformulate the internal structure of the standard model of particle physics geometrically, one arrives naturally at a discrete internal geometry that is coordinatized by a Jordan algebra.
|
high energy physics theory
|
Bidimensionality Theory was introduced by [E.D. Demaine, F.V. Fomin, M.Hajiaghayi, and D.M. Thilikos. Subexponential parameterized algorithms on graphs of bounded genus and H-minor-free graphs, J. ACM, 52 (2005), pp.866--893] as a tool to obtain sub-exponential time parameterized algorithms on H-minor-free graphs. In [E.D. Demaine and M.Hajiaghayi, Bidimensionality: new connections between FPT algorithms and PTASs, in Proceedings of the 16th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), SIAM, 2005, pp.590--601] this theory was extended in order to obtain polynomial time approximation schemes (PTASs) for bidimensional problems. In this work, we establish a third meta-algorithmic direction for bidimensionality theory by relating it to the existence of linear kernels for parameterized problems. In particular, we prove that every minor (respectively contraction) bidimensional problem that satisfies a separation property and is expressible in Countable Monadic Second Order Logic (CMSO), admits a linear kernel for classes of graphs that exclude a fixed graph (respectively an apex graph) H as a minor. Our results imply that a multitude of bidimensional problems g graph classes. For most of these problems no polynomial kernels on H-minor-free graphs were known prior to our work.
|
computer science
|
We present a quantum circuit with measurements and post-selection that exhibits a panoply of space- and/or time-ordered phases, from ferromagnetic order to spin-density waves to time crystals. Unlike the time crystals that have been found in unitary models, those that occur here are \emph{incommensurate} with the drive frequency. The period of the incommensurate time-crystal phase may be tuned by adjusting the circuit parameters. We demonstrate that the phases of our quantum circuit, including the inherently non-equilibrium dynamical ones, correspond to complex-temperature equilibrium phases of the exactly solvable square-lattice anisotropic Ising model.
|
condensed matter
|
Transferring graphene flakes onto hexagonal boron nitride (h-BN) has been the most popular approach for the fabrication of graphne/h-BN heterostructures so far. The orientation between graphene and h-BN lattices, however, are not controllable and the h-BN/graphene interfaces are prone to be contaminated during this elaborate process. Direct synthesis of graphene on h-BN is an alternative and rapidly growing approach. Synthesized graphene via such approaches is personally tailored to conform to each specific h-BN flakes, hence the limitations of conventional fabrication approaches are overcome. Reported processes paved the initial steps to improve the scalablity of the device fabrication for industrial applications. Reviewing the developments in the field, from the birth point to the current status is the focus of this letter. We show how the field has been developed to overcome the existing challenges one after the other and discuss where the field is heading to.
|
condensed matter
|
This paper introduces a new dataset, Libri-Adapt, to support unsupervised domain adaptation research on speech recognition models. Built on top of the LibriSpeech corpus, Libri-Adapt contains English speech recorded on mobile and embedded-scale microphones, and spans 72 different domains that are representative of the challenging practical scenarios encountered by ASR models. More specifically, Libri-Adapt facilitates the study of domain shifts in ASR models caused by a) different acoustic environments, b) variations in speaker accents, c) heterogeneity in the hardware and platform software of the microphones, and d) a combination of the aforementioned three shifts. We also provide a number of baseline results quantifying the impact of these domain shifts on the Mozilla DeepSpeech2 ASR model.
|
electrical engineering and systems science
|
We present a general framework for the homogenisation theory of space-time metamaterials. By mapping to a frame co-moving with the space-time modulation, we derive analytical formulae for the effective material parameters for travelling wave modulations in the low frequency limit: electric permittivity, magnetic permeability and magnetoelectric coupling. Remarkably, we show that the theory is exact at all frequencies in the absence of back-reflections, and exact at low frequencies when that condition is relaxed. This allows us to derive exact formulae for the Fresnel drag experienced by light travelling through travelling-wave modulations of electromagnetic media.
|
condensed matter
|
We propose a novel source of gravitational wave emission: the inspirals of compact fragments inside primordial supermassive stars (SMSs). Such systems are thought to be an essential channel in the as-yet little understood formation of supermassive black holes (SMBHs). One model suggests that high accretion rates of $0.1$-1 M$_\odot$/yr attainable in atomically-cooled primordial halos can lead to the formation of a nuclear-burning SMS. This will ultimately undergo collapse through a relativistic instability, leaving a massive BH remnant. Recent simulations suggest that supermassive stars rarely form in isolation, and that companion stars and even black holes formed may be captured/accreted and inspiral to the SMS core due to gas dynamical friction. Here, we explore the GW emission produced from such inspirals, which could probe the formation and evolution of SMS and seeds of the first supermassive black holes. We use a semi-analytic gas-dynamical friction model of the inspirals in the SMS to characterize their properties. We find such sources could potentially be observable by upcoming space-born GW-detectors at their formation redshifts with the benefit of gravitational lensing. Mergers within closely-related quasi-stars may produce a much stronger signal, though disambiguating such events from other high-z events may prove challenging.
|
astrophysics
|
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN, (Denoising Fully Connected Network) for the detection of COVID-19 using laboratory tests and chest x-rays. Since medical facilities around the world differ enormously in what laboratory tests or chest imaging may be available, DFCN is designed to be robust to missing input data. An ablation study extensively evaluates the performance benefits of the DFCN architecture as well as its robustness to missing inputs. Data from 1088 patients with confirmed RT-PCR results are obtained from two independent medical facilities. The data collected includes results from 27 laboratory tests and a chest x-ray scored by a deep learning network. Training and test datasets are defined based on the source medical facility. Data is made publicly available. The performance of DFCN in predicting the RT-PCR result is compared with 3 related architectures as well as a Random Forest baseline. All models are trained with varying levels of masked input data to encourage robustness to missing inputs. Missing data is simulated at test time by masking inputs randomly. Using area under the receiver operating curve (AUC) as a metric, DFCN outperforms all other models with statistical significance using random subsets of input data with 2-27 available inputs. When all 28 inputs are available DFCN obtains an AUC of 0.924, higher than achieved by any other model. Furthermore, with clinically meaningful subsets of parameters consisting of just 6 and 7 inputs respectively, DFCN also achieves higher AUCs than any other model, with values of 0.909 and 0.919.
|
electrical engineering and systems science
|
We analyse the transverse momentum ($p_{\rm T}$)-spectra as a function of charged-particle multiplicity at midrapidity ($|y| < 0.5$) for various identified particles such as $\pi^{\pm}$, $K^{\pm}$, $K_S^0$, $p+\overline{p}$, $\phi$, $K^{*0} + \overline {K^{*0}}$, and $\Lambda$ + $\bar{\Lambda}$ in proton-proton collisions at $\sqrt{s}$ = 7 TeV using Boltzmann-Gibbs Blast Wave (BGBW) model and thermodynamically consistent Tsallis distribution function. We obtain the multiplicity dependent kinetic freeze-out temperature ($T_{\rm kin}$) and radial flow ($\beta$) of various particles after fitting the $p_{\rm T}$-distribution with BGBW model. Here, $T_{\rm kin}$ exhibits mild dependence on multiplicity class while $\beta$ shows almost independent behaviour. The information regarding Tsallis temperature and the non-extensivity parameter ($q$) are drawn by fitting the $p_{\rm T}$-spectra with Tsallis distribution function. The extracted parameters of these particles are studied as a function of charged particle multiplicity density ($dN_{ch}/d\eta$). In addition to this, we also study these parameters as a function of particle mass to observe any possible mass ordering. All the identified hadrons show a mass ordering in temperature, non-extensive parameter and also a strong dependence on multiplicity classes, except the lighter particles. It is observed that as the particle multiplicity increases, the $q$-parameter approaches to Boltzmann-Gibbs value, hence a conclusion can be drawn that system tends to thermal equilibrium. The observations are consistent with a differential freeze-out scenario of the produced particles.
|
high energy physics phenomenology
|
Expanding nebulae are produced by mass loss from stars, especially during late stages of evolution. Multi-dimensional simulation of these nebulae requires high resolution near the star and permits resolution that decreases with distance from the star, ideally with adaptive timesteps. We report the implementation and testing of static mesh-refinement in the radiation-magnetohydrodynamics code PION, and document its performance for 2D and 3D calculations. The bow shock produced by a hot, magnetized, slowly rotating star as it moves through the magnetized ISM is simulated in 3D, highlighting differences compared with 2D calculations. Latitude-dependent, time-varying magnetized winds are modelled and compared with simulations of ring nebulae around blue supergiants from the literature. A 3D simulation of the expansion of a fast wind from a Wolf-Rayet star into the slow wind from a previous red supergiant phase of evolution is presented, with results compared with results in the literature and analytic theory. Finally the wind-wind collision from a binary star system is modelled with 3D MHD, and the results compared with previous 2D hydrodynamic calculations. A python library is provided for reading and plotting simulation snapshots, and the generation of synthetic infrared emission maps using torus is also demonstrated. It is shown that state-of-the-art 3D MHD simulations of wind-driven nebulae can be performed using PION with reasonable computational resources. The source code and user documentation is made available for the community under a BSD3 licence.
|
astrophysics
|
Existing protocols for benchmarking current quantum co-processors fail to meet the usual standards for assessing the performance of High-Performance-Computing platforms. After a synthetic review of these protocols -- whether at the gate, circuit or application level -- we introduce a new benchmark, dubbed Atos Q-score (TM), that is application-centric, hardware-agnostic and scalable to quantum advantage processor sizes and beyond. The Q-score measures the maximum number of qubits that can be used effectively to solve the MaxCut combinatorial optimization problem with the Quantum Approximate Optimization Algorithm. We give a robust definition of the notion of effective performance by introducing an improved approximation ratio based on the scaling of random and optimal algorithms. We illustrate the behavior of Q-score using perfect and noisy simulations of quantum processors. Finally, we provide an open-source implementation of Q-score that makes it easy to compute the Q-score of any quantum hardware.
|
quantum physics
|
We forecast constraints on the amplitude of matter clustering sigma_8(z) achievable with the combination of cluster weak lensing and number counts, in current and next-generation weak lensing surveys. We advocate an approach, analogous to galaxy-galaxy lensing, in which the observables in each redshift bin are the mean number counts and the mean weak lensing profile of clusters above a mass proxy threshold. The primary astrophysical nuisance parameter is the logarithmic scatter between the mass proxy and true mass near the threshold. For surveys similar to the Dark Energy Survey (DES), the Roman Space Telescope High Latitude Survey (HLS), and the Rubin Observatory Legacy Survey of Space and Time (LSST), we forecast aggregate precision on sigma_8 of 0.26%, 0.24%, and 0.10%, respectively, if the mass-observable scatter has an external prior better than 0.01. These constraints would be degraded by about 20% for a 0.05 prior on scatter in the case of DES or HLS and for a 0.016 prior for LSST. A one-month observing program with Roman Space Telescope targeting approximately 2500 massive clusters could achieve a 0.5% constraint on sigma_8(z=0.7) on its own, or a ~0.33% constraint in combination with the HLS. Realizing the constraining power of clusters requires accurate knowledge of the mass-observable relation and stringent control of systematics. We provide analytic approximations to our numerical results that allow easy scaling to other survey assumptions or other methods of cluster mass estimation.
|
astrophysics
|
In this paper, we investigate basic geometric quantities of a random hyperbolic surface of genus $g$ with respect to the Weil-Petersson measure on the moduli space $\mathcal{M}_g$. We show that as $g$ goes to infinity, a generic surface $X\in \mathcal{M}_g$ satisfies asymptotically: (1) the separating systole of $X$ is about $2\log g$; (2) there is a half-collar of width about $\frac{\log g}{2}$ around a separating systolic curve of $X$; (3) the length of shortest separating closed multi-geodesics of $X$ is about $2\log g$. As applications, we also discuss the asymptotic behavior of the extremal separating systole, the non-simple systole and the expectation value of lengths of shortest separating closed multi-geodesics as $g$ goes to infinity.
|
mathematics
|
The Einstein-Podolsky-Rosen (EPR) entanglement of a neutral K-meson (kaon) pair enjoys the peculiar quantum behaviour of mixing, charge-parity ${\cal CP}$ violation (${\cal C}$ - charge conjugation, ${\cal P}$ - parity) and two non-orthogonal eigenstates of definite time evolution $K_L$ and $K_S$ with very different lifetimes. The dynamics of this "strange entanglement", experimentally accessible at the $\phi$-factory, makes possible the search for novel phenomena not accessible in any other system, i.e. at interference times and at decoherence times of the single partners after their disentanglement, in order to unveil the nature of the correlation between the two neutral kaons. Until now, the studies have been concentrated on the single kaon intensity distribution between the two decay times $t_1$ and $t_2$ with $\Delta t = t_2 - t_1 > 0$. Here we show that the entire two single time distributions, before each decay, are physical in both senses: "from past to future", leading to the state of the living partner at time $t_2$ from the observation of the first decay channel at $t_1$, and "from future to past", leading to the past state of the decayed kaon at time $t_1$ from the observation of the second decay channel at $t_2$. Our results thus demonstrate an affirmative answer to the title: it does, the past decayed state depends on the result of the future measurement for the living partner. This novel effect is truly observable through the first decay time distributions. Besides the implications for quantum physics for all $\Delta t$, at large decoherence times the resulting first decayed state is always $K_S$, providing a genuine tag of this kaon state in the decoherence region, and a unique and important experimental tool to prepare a pure $K_S$ beam.
|
quantum physics
|
We propose Qubit4Sync, a synchronization method for Quantum Key Distribution (QKD) setups, based on the same qubits exchanged during the protocol and without requiring additional hardware other than the one necessary to prepare and measure the quantum states. Our approach introduces a new cross-correlation algorithm achieving the lowest computational complexity, to our knowledge, for high channel losses. We tested the robustness of our scheme in a real QKD implementation.
|
quantum physics
|
In this work we use a multiscale approach toward a realistic design of a permanent magnet based on MnAl $\tau$-phase and elucidate how the antiphase boundary defects present in this material affect the energy product. We show how the extrinsic properties of a microstructure depend on the intrinsic properties of a structure with defects by performing micromagnetic simulations. For an accurate estimation of the energy product of a realistic permanent magnet based on the MnAl $\tau$-phase with antiphase boundaries, we quantify for the first time the exchange interaction strength across the antiphase boundary defect with a simple approach derived from the first-principles calculations. These two types of calculations performed at different scales are linked via atomistic spin dynamic simulations performed at an intermediate scale.
|
condensed matter
|
The number of leptons may or may not be a conserved quantity. The Standard Model predicts that it is (in perturbative processes), but there is the well known possibility that new physics violates lepton number in one or two units. The first case ($\Delta L=1$) is associated to proton decay into mesons plus a lepton or an anti-lepton, while the second one ($\Delta L=2$) is usually associated to Majorana neutrino masses and neutrinoless double beta decay. It is also conceivable that leptons can only be created or destroyed in groups of three ($\Delta L=3$). Colliders and proton decay experiments can explore this possibility.
|
high energy physics phenomenology
|
In this paper, we generalize the definition of backward reachable tube. The classic definition of backward reachable tube is a set of system state that can be driven into the target set within a given time horizon. Sometimes, the concern of researchers is not only the time consumption, but some other forms of cost of driving the system state toward the target set. Under this background, the definition of cost-limited backward reachable tube is put forward in this paper, where the cost is the time integral of a running cost. And the running cost is a scalar function of system state and control input. A method to compute the cost-limited backward reachable tube is proposed. In this method, a cost-limited backward reachable tube is characterized by a non-zero level set of a value function, which is approximated using recursion and interpolation. At the end of this paper, some examples are taken to illustrate the validity and accuracy of the proposed method.
|
electrical engineering and systems science
|
Let $R$ be a commutative ring with identity. In this note, we study the property: If $ I \subsetneqq J$ are ideals in $R$, then $ I^n \subsetneqq J^n$ for all $ n\geq 1$. We define the notion of a big ideal (Definition 1.2). It is noted that the property has close relationship with the notions of reduction of an ideal and Ratliff-Rush ideal [7]. Apart from other results, it is proved that a Noetherian domain satifies the property if and only if every ideal in $R$ is a Ratliff-Rush ideal. We also prove that ideals having no proper reduction are big ideals, and maximal ideals in regular rings are big.
|
mathematics
|
In this paper, we compute the contribution to the coherent elastic neutrino-nucleus scattering cross section from new physics models in the neutrino sector. We use this information to calculate the maximum value of the so-called neutrino floor for direct dark matter detection experiments, which determines when these detectors are sensitive to the neutrino background. After including all relevant experimental constraints in different simplified neutrino models, we have found that the neutrino floor can increase by various orders of magnitude in the region of dark matter masses below 10 GeV in the case of scalar mediators, however, this spectacular enhancement is subject to the re-examination of supernovae bounds. The increase is approximately a factor of two for vector mediators. In the light of these results, future claims by direct detection experiments exploring the low-mass window must be carefully examined if a signal is found well above the expected Standard Model neutrino floor.
|
high energy physics phenomenology
|
This paper explores the prospect of CMOS devices to assay lead in drinking water, using calorimetry. Lead occurs together with traces of radioisotopes, e.g. Lead-210, producing $\gamma$-emissions with energies ranging from 10 keV to several 100 keV when they decay; this range is detectable in silicon sensors. In this paper we test a CMOS camera (Oxford Instruments Neo 5.5) for its general performance as a detector of x-rays and low energy $\gamma$-rays and assess its sensitivity relative to the World Health Organization upper limit on lead in drinking water. Energies from 6 keV to 60 keV are examined. The CMOS camera has a linear energy response over this range and its energy resolution is for the most part slightly better than 2 %. The Neo sCMOS is not sensitive to x-rays with energies below $\sim\!\!10 keV$. The smallest detectable rate is 40$\pm$3 mHz, corresponding to an incident activity on the chip of 7$\pm$4 Bq. The estimation of the incident activity sensitivity from the detected activity relies on geometric acceptance and the measured efficiency vs. energy. We report the efficiency measurement, which is 0.08$\pm$0.02 % (0.0011$\pm$0.0002 %) at 26.3 keV (59.5 keV). Taking calorimetric information into account we measure a minimal detectable rate of 4$\pm$1 mHz (1.5$\pm$0.1 mHz) for 26.3 keV (59.5 keV) $\gamma$-rays, which corresponds to an incident activity of 1.0$\pm$0.6 Bq (57$\pm$33 Bq). Toy Monte Carlo and Geant4 simulations agree with these results. These results show this CMOS sensor is well-suited as a $\gamma$- and x-ray detector with sensitivity at the few to 100 ppb level for Lead-210 in a sample.
|
physics
|
Visual search is an important strategy of the human visual system for fast scene perception. The guided search theory suggests that the global layout or other top-down sources of scenes play a crucial role in guiding object searching. In order to verify the specific roles of scene layout and regional cues in guiding visual attention, we executed a psychophysical experiment to record the human fixations on line drawings of natural scenes with an eye-tracking system in this work. We collected the human fixations of ten subjects from 498 natural images and of another ten subjects from the corresponding 996 human-marked line drawings of boundaries (two boundary maps per image) under free-viewing condition. The experimental results show that with the absence of some basic features like color and luminance, the distribution of the fixations on the line drawings has a high correlation with that on the natural images. Moreover, compared to the basic cues of regions, subjects pay more attention to the closed regions of line drawings which are usually related to the dominant objects of the scenes. Finally, we built a computational model to demonstrate that the fixation information on the line drawings can be used to significantly improve the performances of classical bottom-up models for fixation prediction in natural scenes. These results support that Gestalt features and scene layout are important cues for guiding fast visual object searching.
|
computer science
|
We examine the spatial distribution and mass segregation of dense molecular cloud cores in a number of nearby star forming regions that span about four orders of magnitude in star formation activity. We use an approach based on the calculation of the minimum spanning tree, and for each region, we calculate the structure parameter Q and the mass segregation ratio measured for various numbers of the most massive cores. Our results indicate that the distribution of dense cores in young star forming regions is very substructured and that it is likely that this substructure will be imprinted onto the nascent clusters that will emerge out of these clouds. With the exception of Taurus in which there is nearly no mass segregation, we observe mild-to-significant levels of mass segregation for the ensemble of the 6, 10, and 14 most massive cores in Aquila, CrA, and W43, respectively. Our results suggest that the clouds' star formation activity are linked to their structure, as traced by their population of dense cores. We also find that the fraction of massive cores that are the most mass segregated in each region correlates with the surface density of star formation in the clouds. The Taurus region with low star-forming activity is associated with a highly hierarchical spatial distribution of the cores (low Q value) and the cores show no sign of being mass segregated. On the other extreme, the mini-starburst region W43-MM1 has a higher Q that is suggestive of a more centrally condensed structure and it possesses a higher fraction of massive cores that are segregated by mass. While some limited evolutionary effects might be present, we attribute the correlation between the star formation activity of the clouds and their structure to a dependence on the physical conditions that have been imprinted on them by the large scale environment at the time they started to assemble
|
astrophysics
|
The subject of this paper is an algebraic version of the irregular Riemann-Hilbert correspondence which was mentioned in [arXiv:1910.09954] by the author. In particular, we prove an equivalence of categories between the triangulated category of algebraic holonomic D-modules on a smooth algebraic variety and the one of algebraic C-constructible enhanced ind-sheaves. Moreover we show that there exists a t-structure on the triangulated category of algebraic C-constructible enhanced ind-sheaves whose heart is equivalent to the abelian category of algebraic holonomic D-modules. Furthermore we shall consider simple objects of its heart and minimal extensions of objects of its heart.
|
mathematics
|
In a recent paper by M. Pollicott, an efficient algorithm was proposed, applying Ruelle's theory of transfer operators and Grothendieck's classical work on nuclear operators, to compute the Lyapunov exponent associated with the i.i.d. products of positive matrices. In this article, we generalise the result to Markovian products and correct some minor mistakes in Pollicott's original paper.
|
mathematics
|
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