Tensor Channels Research Articles

Exponential error reduction for glueball calculations using a two-level algorithm in pure gauge theory

This study explores the application of a two-level algorithm to enhance the signal-to-noise ratio of glueball calculations in four-dimensional SU(3) pure gauge theory. Our findings demonstrate that the statistical errors exhibit an exponential reduction, enabling reliable extraction of effective masses at distances where current standard methods would demand exponentially more samples. However, at shorter distances, standard methods prove more efficient due to a saturation of the variance reduction using the multilevel method. We discuss the physical distance at which the multilevel sampling is expected to outperform the standard algorithm, supported by numerical evidence across different lattice spacings and glueball channels. Additionally, we construct a variational basis comprising 35 Wilson loops up to length 12 and 5 smearing sizes each, presenting results for the first state in the spectrum for the scalar, pseudoscalar, and tensor channels. Published by the American Physical Society 2024

Approximate Effective Interaction for Nuclear Matter and Finite Nuclei

In this paper, an approximate effective nucleon-nucleon interaction for nuclear matter and finite studies has been derived using the lowest order constrained variational (LOCV) approach. The LOCV method, a functional minimization procedure, uses a normalization constraint to keep higher-order terms as small as possible. As a first step, two-body matrix elements based on the Reid93 nucleon-nucleon potential were calculated for the nuclear system A = 16 in a harmonic oscillator basis, with the oscillator size parameter <i>ћω </i>= 14.0 MeV, and separated into the central, spin-orbit and tensor channels in conformity with the potentials for Inelastic scattering. Following this, a least squares fitting of the matrix elements to a sum of Yukawa functions was performed to determine the strengths of the effective interaction in the singlet-even, singlet-odd, triplet-even and triplet-odd (Central); tensor-even and tensor-odd (Tensor); spin-orbit-even and spin-orbit-odd (Spin-orbit) channels. Of all the matrix elements, only the triplet-even and tensor-even components, being attractive, are affected by the tensor correlations (<i>a </i>= 0.05); and are shown to exhibit the same trend of variation in conformity with past work, in terms of magnitude, as one goes from the lower-node quantum numbers (n’, n) = (0, 0) to higher ones (n’, n) = (2, 2). When compared with the G-matrix results of previous researchers, the results obtained herein have been found to be in good agreement. This, therefore, gives hope that the new effective interaction promises to be a reliable tool for nuclear matter and nuclear structure studies.

Automatic diagnosis of depression based on attention mechanism and feature pyramid model.

Currently, most diagnoses of depression are evaluated by medical professionals, with the results of these evaluations influenced by the subjective judgment of physicians. Physiological studies have shown that depressed patients display facial movements, head posture, and gaze direction disorders. To accurately diagnose the degree of depression of patients, this paper proposes a comprehensive framework, Cross-Channel Attentional Depression Detection Network, which can automatically diagnose the degree of depression of patients by inputting information from the facial images of depressed patients. Specifically, the comprehensive framework is composed of three main modules: (1) Face key point detection and cropping for video images based on Multi-Task Convolutional Neural Network. (2) The improved Feature Pyramid Networks model can fuse shallow features and deep features in video images and reduce the loss of miniscule features. (3) A proposed Cross-Channel Attention Convolutional Neural Network can enhance the interaction between tensor channel layers. Compared to other methods for automatic depression identification, a superior method was obtained by conducting extensive experiments on the depression dataset AVEC 2014, where the Root Mean Square Error and the Mean Absolute Error were 8.65 and 6.66, respectively.

Dynamic Parallel Pyramid Networks for Scene Recognition.

Scene recognition is considered a challenging task of image recognition, mainly due to the presence of multiscale information of global layout and local objects in a given scene. Recent convolutional neural networks (CNNs) that can learn multiscale features have achieved remarkable progress in scene recognition. They have two limitations: 1) the receptive field (RF) size is fixed even though a scene may have large-scale variations and 2) they are computing and memory intensive, partially due to the representation of multiscales. To address these limitations, we propose a lightweight dynamic scene recognition approach based on a novel architectural unit, namely, a dynamic parallel pyramid (DPP) block, that can adaptively select RF size based on multiscale information from the input regarding channel dimensions. We encode multiscale features by applying different convolutional (CONV) kernels on different input tensor channels and then dynamically merge their output using a group attention mechanism followed by channel shuffling to generate the parallel feature pyramid. DPP can be easily incorporated with existing CNNs to develop new deep models, called DPP networks (DPP-Nets). Extensive experiments on large-scale scene image datasets, Places365 standard, Places365 challenge, the Massachusetts Institute of Technology (MIT) Indoor67, and Sun397 confirmed that the proposed method provides significant performance improvement compared with current state-of-the-art (SOTA) approaches. We also verified general applicability from compelling results on lightweight models of MobileNetV2 and ShuffleNetV2 on ImageNet-1k and small object centralized benchmarks on CIFAR-10 and CIFAR-100.

X(3872) , X(4014) , and their bottom partners at finite temperature

The properties of the $X(3872)$ and its spin partner, the $X(4014)$, are studied both in vacuum and at finite temperature. Using an effective hadron theory based on the hidden-gauge Lagrangian, the $X(3872)$ is dynamically generated from the $s$-wave rescattering of a pair of pseudoscalar and vector charm mesons. By incorporating the thermal spectral functions of open charm mesons, the calculation is extended to finite temperature. Similarly, the properties of the $X(4014)$ are obtained out of the scattering of charm vector mesons. By applying heavy-quark flavor symmetry, the properties of their bottom counterparts in the axial-vector and tensor channels are also predicted. All the dynamically generated states show a decreasing mass and acquire an increasing decay width with temperature, following the trend observed in their meson constituents. These results are relevant in relativistic heavy-ion collisions at high energies, in analyses of the collective medium formed after hadronization or in femtoscopic studies, and can be tested in lattice-QCD calculations exploring the melting of heavy mesons at finite temperature.

Capacity Performance of Tensor Multi-Domain Communication Systems With Discrete Signalling Constellations

Modern communication systems employ multi-domain modulation and coding techniques for effectively exploiting all available resources. Hence in such systems the transmit and receive signals have an inherent multi-domain structure which can be represented using tensors. This work considers the capacity of higher order tensor channels associated with such multi-domain communication systems when the elements of the input tensor are constrained to be drawn from discrete signalling constellations. We establish a relationship between the tensor gradient of the mutual information and the error covariance tensor associated with the minimum mean squared error estimator at the receiver. This relation is used to iteratively find a multi-linear precoder at the input which achieves capacity of the tensor channel under the signalling constellation constraints. Through numerical examples, we show the convergence behavior of the proposed precoder, and compare the capacity achieved under different constellations with the capacity when the input is Gaussian. Further, we exploit the tensor formulation of the problem to find the channel capacity under a variety of different power constraints spanning across several domains. At high SNR, the constellation constraints saturates the capacity while at low SNRs, the constellation constraints are not too relevant, and the power constraints dominate and limit the performance. The capacity saturation level depends on the input order and distribution.

Nucleon isovector couplings in Nf=2+1 lattice QCD at the physical point

We present results for the scalar and tensor isovector-couplings ($g_S$ and $g_T$) of the nucleon measured at the physical point ($M_{\pi}=135$ MeV) with a single lattice spacing of $0.085\ \mathrm{fm}$ in 2+1 flavor QCD. Our calculations are carried out with two ensembles of gauge configurations generated by the PACS Collaboration with nonperturbatively ${\cal O}(a)$ improved Wilson quark action and Iwasaki gauge action on $(10.9\ {\rm fm})^4$ and $(5.5\ {\rm fm})^4$ lattices, where the finite-size effect on the nucleon mass was not shown at the level of the statistical precision less than 0.5%. We compute the nucleon three-point correlation functions in the vector, axial, scalar, and tensor channels. We confirm that our previous result of the nucleon axial coupling on the large spatial volume of $(10.9\ {\rm fm})^4$ has no finite-size effect at the level of the statistical precision of 1.9%. For the renormalization, we first renormalize $g_S$ and $g_T$ nonperturbatively using the RI/SMOM$_{(\gamma_\mu)}$ scheme, a variant of Rome-Southampton RI/MOM scheme with reduced systematic errors, as the intermediate scheme. We evaluate our final results at the renormalization scale of 2 GeV in the $\overline{\rm MS}$ scheme through matching procedure between the RI/SMOM$_{(\gamma_\mu)}$ and $\overline{\rm MS}$ schemes with the help of perturbation theory, and then obtain $g_S=0.927(71)_{\rm stat}(22)_{\rm syst}$ and $g_T=1.036(6)_{\rm stat}(20)_{\rm syst}$.

Ultrasonic-Aided Fast-Layered Alternating Iterative Tensor Channel Estimation for V2X Millimeter-Wave Massive MIMO Systems

Millimeter-wave massive multiple-input multiple-output (MIMO) vehicle-to-everything (V2X) communications can support enhanced V2X applications for connected and automated vehicles. The design of millimeter-wave V2X communications is, however, not exempt from challenges as a result of fast time-varying propagation and highly dynamic vehicular networks and topologies. To address some of these challenges, we propose an ultrasonic-aided tensor channel estimation for V2X millimeter-wave massive MIMO systems to improve the safety and traffic efficiency of cooperative automated driving. At the receiver, the dimension of multidimensional complex V2X information is reduced by the subspace tensor decomposition model. In order to quickly track beam angle changes caused by vehicle position changes, the ultrasonic-aided direction of arrival (DOA) tracking method is adopted to provide information about the surrounding environment. Based on the ultra-high resolution quantization grid and adaptive iterative update of the dictionary matrix, the DOA of the ultrasonic signal can be tracked. The angle update information of the millimeter-wave signal can be obtained by converting the estimated angle information. Using the cost function with global characteristics and ultrasonic-aided DOA tracking, a fast-layered alternating iterative tensor algorithm is proposed for joint iterative channel estimation. Simulation results show that the proposed solution outperforms some advanced alternative methods.

Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation

Background and objective: Accurate lung tumor segmentation from computed tomography (CT) is complex due to variations in tumor sizes, shapes, patterns and growing locations. Learning semantic and spatial relations between different feature channels, image regions and positions is critical yet challenging. Methods: We propose a new segmentation method, PRCS, by learning and integrating multi-channel contextual relations, and spatial and position dependencies across image regions. Firstly, to extract contextual relationships between different deep image feature tensor channels, we propose a new convolutional bi-directional gated recurrent unit based module for forward and backward learning. Secondly, a novel cross-channel region-level attention mechanism is proposed to discriminate the contributions of different local regions and associated features in the global learning process. Finally, spatial and position dependencies are formulated by a new position-enhanced self-attention mechanism. The new attention can measure the diverse contributions of other positions to a target position and obtain an enhanced adaptive feature vector for the target position.Results: Our model outperformed seven state-of-the-art segmentation methods on both public and in-house lung tumor datasets in terms of spatial overlapping and shape similarity. Ablation study results proved the effectiveness of three technical innovations and generalization ability on different 3D CNN segmentation backbones. Conclusion: The proposed model enhanced the learning and propagation of contextual, spatial and position relations in 3D volumes, improving lung tumours’ segmentation performance with large variations and indistinct boundaries. PRCS provides an effective automated approach to support precision diagnosis and treatment planning of lung cancer.

The Tensor Multi-Linear Channel and Its Shannon Capacity

Tensors are multi-way arrays which can be used to model systems spanning many domains. This work proposes to use tensors for characterizing, analyzing, and designing multi-domain communication systems. Most modern day communication systems make use of coding and modulation across different domains such as space, frequency, time. Hence a unified mathematical framework characterizing such a multiple-domain system in an intuitive manner is well needed. In this paper, we present such a unified framework that characterizes a communication system with <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> input domains, <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> output domains and an <inline-formula> <tex-math notation="LaTeX">$M+N$ </tex-math></inline-formula> domains multi-linear tensor channel. The proposed framework is generic where the physical interpretation of the domains is system specific. We illustrate a few examples from multi-antenna multi-carrier and multi-user systems that fit the proposed framework. Assuming a fixed tensor channel, we provide an information theoretic analysis by deriving its Shannon capacity and input power allocation under a variety of power constraints. In this paper we show how the tensor framework&#x2019;s suitability to mathematically describe a family of power constraints can be used to design and analyze various multiple domain communication systems. The tensor based approach extends water-filling from a matrix setting to tensors, encapsulating the effects of multiple domains thereby allowing joint multi-domain precoding. We show that the capacity pre-log for a tensor channel increases exponentially in the number of domains, indicating the potential of tensor based multi-domain communication systems to provide the large information transmission rates envisaged for 5G and beyond systems. We also show the application of the tensor framework in characterizing the capacity and rate regions of multi-user MIMO channels. Both multiple access and interference channels are considered where the tensor based approach leads to a coordinated users transmission scheme. Such a scheme ensures higher achievable sum rates as compared to independent user transmissions.

Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

Most modern communication systems, such as those intended for deployment in IoT applications or 5G and beyond networks, utilize multiple domains for transmission and reception at the physical layer. Depending on the application, these domains can include space, time, frequency, users, code sequences, and transmission media, to name a few. As such, the design criteria of future communication systems must be cognizant of the opportunities and the challenges that exist in exploiting the multi-domain nature of the signals and systems involved for information transmission. Focussing on the Physical Layer, this paper presents a novel mathematical framework using tensors, to represent, design, and analyze multi-domain systems. Various domains can be integrated into the transceiver design scheme using tensors. Tools from multi-linear algebra can be used to develop simultaneous signal processing techniques across all the domains. In particular, we present tensor partial response signaling (TPRS) which allows the introduction of controlled interference within elements of a domain and also across domains. We develop the TPRS system using the tensor contracted convolution to generate a multi-domain signal with desired spectral and cross-spectral properties across domains. In addition, by studying the information theoretic properties of the multi-domain tensor channel, we present the trade-off between different domains that can be harnessed using this framework. Numerical examples for capacity and mean square error are presented to highlight the domain trade-off revealed by the tensor formulation. Furthermore, an application of the tensor framework to MIMO Generalized Frequency Division Multiplexing (GFDM) is also presented.

Glueball spectrum from Nf = 2 lattice QCD study on anisotropic lattices**The numerical calculations were carried out on Tianhe-1A at the National Supercomputer Center (NSCC) in Tianjin and the GPU cluster at Hunan Normal University. This work is supported in part by the National Science Foundation of China (NSFC) (11575196, 11575197, 11335001, 11405053, 11405178, 11275169). Y. C., Z. L. and

The lowest-lying glueballs are investigated in lattice QCD using Nf = 2 clover Wilson fermions on anisotropic lattices. We simulate at two different and relatively heavy quark masses, corresponding to physical pion masses of mπ ∼ 938 MeV and 650 MeV. The quark mass dependence of the glueball masses has not been investigated in the present study. Only the gluonic operators built from Wilson loops are utilized in calculating the corresponding correlation functions. In the tensor channel, we obtain the ground state mass to be 2.363(39) GeV and 2.384(67) GeV at mπ ∼ 938 MeV and 650 MeV, respectively. In the pseudoscalar channel, when using the gluonic operator whose continuum limit has the form of εijk TrBiDjBk, we obtain the ground state mass to be 2.573(55) GeV and 2.585(65) GeV at the two pion masses. These results are compatible with the corresponding results in the quenched approximation. In contrast, if we use the topological charge density as field operators for the pseudoscalar, the masses of the lowest state are much lighter (around 1 GeV) and compatible with the expected masses of the flavor singlet meson. This indicates that the operator εijk TrBiDjBk and the topological charge density couple rather differently to the glueball states and mesons. The observation of the light flavor singlet pseudoscalar meson can be viewed as the manifestation of effects of dynamical quarks. In the scalar channel, the ground state masses extracted from the correlation functions of gluonic operators are determined to be around 1.4-1.5 GeV, which is close to the ground state masses from the correlation functions of the quark bilinear operators. In all cases, the mixing between glueballs and conventional mesons remains to be further clarified in the future.

Effect of tensor correlations on the depletion of nuclear Fermi sea within the extended BHF approach**Supported by National Natural Science Foundation of China (11435014, 11175219), the 973 Program of China (2013CB834405) and the Knowledge Innovation Project (KJCX2-EW-N01) of the Chinese Academy of Sciences

We have investigated the effect of tensor correlations on the depletion of the nuclear Fermi sea in symmetric nuclear matter within the framework of the extended Brueckner-Hartree-Fock approach by adopting the AV 18 two-body interaction and a microscopic three-body force. The contributions from various partial wave channels including the isospin-singlet T=0 channel, the isospin-triplet T=1 channel and the T=0 tensor 3SD1 channel have been calculated. The T=0 neutron-proton correlations play a dominant role in causing the depletion of nuclear Fermi sea. The T=0 correlation-induced depletion turns out to stem almost completely from the 3SD1 tensor channel. The isospin-singlet T=0 3SD1 tensor correlations are shown to be responsible for most of the depletion, which amounts to more than 70 percent of the total depletion in the density region considered. The three-body force turns out to lead to an enhancement of the depletion at high densities well above the empirical saturation density and its effect increases as a function of density.

Spectral sum rules for conformal field theories in arbitrary dimensions

We derive spectral sum rules in the shear channel for conformal field theories at finite temperature in general d ≥ 3 dimensions. The sum rules result from the OPE of the stress tensor at high frequency as well as the hydrodynamic behaviour of the theory at low frequencies. The sum rule states that a weighted integral of the spectral density over frequencies is proportional to the energy density of the theory. We show that the proportionality constant can be written in terms the Hofman-Maldacena variables t2, t4 which determine the three point function of the stress tensor. For theories which admit a two derivative gravity dual this proportionality constant is given by frac{d}{2left(d+1right)} . We then use causality constraints and obtain bounds on the sum rule which are valid in any conformal field theory. Finally we demonstrate that the high frequency behaviour of the spectral function in the vector and the tensor channel are also determined by the Hofman-Maldacena variables.

Entropy functionals andc-theorems from the second law

We show that for a general four derivative theory of gravity, only the holographic entanglement entropy functionals obey the second law at linearized order in perturbations. We also derive bounds on the higher curvature couplings in several examples, demanding the validity of the second law for higher order perturbations. For the five dimensional Gauss-Bonnet theory in the context of AdS/CFT, the bound arising from black branes coincides with there being no sound channel instability close to the horizon. Repeating the analysis for topological black holes, the bound coincides with the tensor channel causality constraint (which is responsible for the viscosity bound). Furthermore, we show how to recover the holographic c-theorems in higher curvature theories from similar considerations based on the Raychaudhuri equation.

Inhomogeneous phases and chiral symmetry breaking

A significant fraction of the current efforts in the QCD research community is focused on characterizing the phases of strong-interaction matter that occur at finite densities and temperatures. So far, most of the experimental probes have been limited to the relatively narrow window of the QCD phase diagram characterized by high temperatures and low chemical potentials, explored in high-energy ion collision experiments at RHIC and LHC. More recently, some new insight on the finite chemical potential region has been obtained by the energy-beam scan program at RHIC, aimed at possibly determining the existence of a critical point in the QCD phase transition. On the theoretical side, studies of strong interactions are also limited by the reliability of available methods. While the zero density, finite temperature region or the zero temperature, superdense region can be investigated with the help of well-established approaches like lattice and weakly coupled QCD respectively, the study of the intermediate densities and temperatures region has to rely on effective models and nonperturbative methods, some of which are still being developed. In the past few years, a growing number of compelling arguments, backed up by model calculations, pointed out that the intermediate-density region of the QCD phase diagram may be characterized by the formation of inhomogeneous condensates which spontaneously break some of the spatial symmetries of the theory. In the following we provide a brief recapitulation of these arguments and describe some recent results in a 3+1-dimensional QCD-inspired NJL model with quark-hole condensation in the form of a plane wave in the scalar and tensor channels. This model exhibits particular features in close analogy to its 1+1-dimensional counterpart, most notably an asymmetric spectral density and the arising of an anomalous contribution to the free energy.

Induced magnetic moment in the magnetic catalysis of chiral symmetry breaking

The chiral symmetry breaking in a Nambu-Jona-Lasinio effective model of quarks in the presence of a magnetic field is investigated. We show that new interaction tensor channels open up via Fierz identities due to the explicit breaking of the rotational symmetry by the magnetic field. We demonstrate that the magnetic catalysis of chiral symmetry breaking leads to the generation of two independent condensates, the conventional chiral condensate and a spin-one condensate. While the chiral condensate generates, as usual, a dynamical fermion mass, the new condensate enters as a dynamical anomalous magnetic moment in the dispersion of the quasiparticles. Since the pair, formed by a quark and an antiquark with opposite spins, possesses a resultant magnetic moment, an external magnetic field can align it giving rise to a net magnetic moment for the ground state. The two condensates contribute to the effective mass of the LLL quasiparticles in such a way that the critical temperature for chiral symmetry restoration becomes enhanced.

Newtonian-noise cancellation in full-tensor gravitational-wave detectors

Terrestrial gravity noise, also known as Newtonian noise, produced by ambient seismic and infrasound fields will pose one of the main sensitivity limitations in low-frequency, ground-based, gravitational-wave (GW) detectors. It was estimated that this noise foreground needs to be suppressed by about 3 -- 5 orders of magnitude in the frequency band 10\,mHz to 1\,Hz, which will be extremely challenging. In this article, we present a new approach that greatly facilitates cancellation of gravity noise in full-tensor GW detectors. The method uses optimal combinations of tensor channels and environmental sensors such as seismometers and microphones to reduce gravity noise. It makes explicit use of the direction of propagation of a GW, and can therefore either be implemented in directional searches for GWs or in observations of known sources. We show that suppression of the Newtonian-noise foreground is greatly facilitated using the extra strain channels in full-tensor GW detectors. Only a modest number of auxiliary, high-sensitivity environmental sensors are required to achieve noise suppression by a few orders of magnitude.

Nuclear tensor interaction in a covariant energy density functional

The origin of the nuclear tensor interaction in the covariant energy density functional (EDF) is presented in this work, associated with the Fock diagrams of Lorentz scalar and vector couplings. With this newly obtained relativistic formalism of the nuclear tensor interaction, more distinct tensor effects are found in the Fock diagrams of the Lorentz scalar and vector couplings, as compared to the Lorentz pseudo-vector and tensor channels. A unified and self-consistent treatment on both the nuclear tensor and spin-orbit interactions, which dominate the spin-dependent features of the nuclear force, is then achieved by the relativistic models. Moreover, careful analysis on the tensor strengths indicates the reliability of the nuclear tensor interaction in the covariant EDF for exploring the nuclear structure, excitation and decay modes.

Spectra of heavy mesons in the Bethe-Salpeter approach

We present a calculation of the spectrum of charmonia, bottomonia and B_c-meson states with `ordinary' and exotic quantum numbers. We discuss the merits and limitations of a rainbow-ladder truncation of Dyson-Schwinger and Bethe-Salpeter equations and explore the effects of different shapes of the effective running coupling on ground and excited states in channels with quantum numbers J <= 3. We furthermore discuss the status of the X(3872) as a potential (excited) quark-antiquark state and give predictions for the masses of charmonia and bottomonia in the tensor channels with J=2,3.