Unwanted Terms Research Articles

Compressible and anelastic governing-equation solution methods for thermospheric gravity waves with realistic background parameters

Abstract abstract A previously developed numerical-multilayer modeling approach for systems of governing equations is extended so that unwanted terms, resulting from vertical variations in certain background parameters, can be removed from the dispersion-relation polynomial associated with the system. The new approach is applied to linearized anelastic and compressible systems of governing equations for gravity waves including molecular viscosity and thermal diffusion. The ability to remove unwanted terms from the dispersion-relation polynomial is crucial for solving the governing equations when realistic background parameters, such as horizontal velocity and temperature, with strong vertical gradients, are included. With the unwanted terms removed, previously studied dispersion-relation polynomials, for which methods for defining upgoing and downgoing vertical wavenumber roots already exist, are obtained. The new methods are applied to a comprehensive set of medium-scale time-wavepacket examples, with realistic background parameters, lower boundary conditions at 30 km altitude, and modeled wavefields extending up to 500 km altitude. Results from the compressible and anelastic model versions are compared, with compressible governing-equation solutions understood as the more physically accurate of the two. The new methods provide significantly less computationally expensive alternatives to nonlinear time-step methods, which makes them useful for comprehensive studies of the behavior of viscous/diffusive gravity waves and also for large studies of cases based on observational data. Additionally, they generalize previously existing Fourier methods that have been applied to inviscid problems while providing a theoretical framework for the study of viscous/diffusive gravity waves. Graphic abstract

Wide-Band Unambiguous Quantum Sensing via Geodesic Evolution.

We present a quantum sensing technique that utilizes a sequence of π pulses to cyclically drive the qubit dynamics along a geodesic path of adiabatic evolution. This approach effectively suppresses the effects of both decoherence noise and control errors while simultaneously removing unwanted resonance terms, such as higher harmonics and spurious responses commonly encountered in dynamical decoupling control. As a result, our technique offers robust, wide-band, unambiguous, and high-resolution quantum sensing capabilities for signal detection and individual addressing of quantum systems, including spins. To demonstrate its versatility, we showcase successful applications of our method in both low-frequency and high-frequency sensing scenarios. The significance of this quantum sensing technique extends to the detection of complex signals and the control of intricate quantum environments. By enhancing detection accuracy and enabling precise manipulation of quantum systems, our method holds considerable promise for a variety of practical applications.

Innovative Forward Fusion Feature Selection Algorithm for Sentiment Analysis Using Supervised Classification

Sentiment analysis is considered one of the significant trends of the recent few years. Due to the high importance and increasing use of social media and electronic services, the need for reviewing and enhancing the provided services has become crucial. Revising the user services is based mainly on sentiment analysis methodologies for analyzing users’ polarities to different products and applications. Sentiment analysis for Arabic reviews is a major concern due to high morphological linguistics and complex polarity terms expressed in the reviews. In addition, the users can present their orientation towards a service or a product by using a hybrid or mix of polarity terms related to slang and standard terminologies. This paper provides a comprehensive review of recent sentiment analysis methods based on lexicon or machine learning (ML). The comparison provides a clear vision of the number of classes, the used dialect, the annotated algorithms, and their performance. The proposed methodology is based on cross-validation of Arabic data using a k-fold mechanism that splits the dataset into training and testing folds; subsequently, the data preprocessing is executed to clean sentiments from unwanted terms that can affect data analysis. A vectorization of the dataset is then applied using TF–IDF for counting word and polarity terms. Furthermore, a feature selection stage is processed using Pearson, Chi2, and Random Forest (RF) methods for mapping the compatibility between input and target features. This paper also proposed an algorithm called the forward fusion feature for sentiment analysis (FFF-SA) to provide a feature selection that applied different machine learning (ML) classification models for each chunk of k features and accumulative features on the Arabic dataset. The experimental results measured and scored all accuracies between the feature importance method and ML models. The best accuracy is recorded with the Naïve Bayes (NB) model with the RF method.

Nonzero θ13, CP-violation and neutrinoless double beta decay for neutrino mixing in the A4×Z2×Z3 flavor symmetry model

In this paper, we study the modification of the Altarelli–Feruglio [Formula: see text] flavor symmetry model by adding three singlet flavons [Formula: see text], [Formula: see text] and [Formula: see text] and the model is augmented with extra [Formula: see text] symmetry to prevent the unwanted terms in our study. The addition of these three flavons leads to two higher order corrections in the form of two perturbation parameters [Formula: see text] and [Formula: see text]. These corrections yield the deviation from exact tri-bimaximal (TBM) neutrino mixing pattern by producing a nonzero [Formula: see text] and other neutrino oscillation parameters which are consistent with the latest experimental data. In both the corrections, the neutrino masses are generated via Weinberg operator. The analysis of the perturbation parameters [Formula: see text] and [Formula: see text], shows that normal hierarchy (NH) and inverted hierarchy (IH) for [Formula: see text] do not change much. However, as the values of [Formula: see text] increase, [Formula: see text] occupies the lower octant for NH case. We further investigate the neutrinoless double beta decay parameter [Formula: see text] using the parameter space of the model for both normal and inverted hierarchies of neutrino masses.

Algebraic Bethe ansatz for Q-operators of the open XXX Heisenberg chain with arbitrary spin

In this note we construct Q-operators for the spin s open Heisenberg XXX chain with diagonal boundaries in the framework of the quantum inverse scattering method. Following the algebraic Bethe ansatz we diagonalise the introduced Q-operators using the fundamental commutation relations. By acting on Bethe off-shell states and explicitly evaluating the trace in the auxiliary space we compute the eigenvalues of the Q-operators in terms of Bethe roots and show that the unwanted terms vanish if the Bethe equations are satisfied.

Type III seesaw under A_4 modular symmetry with leptogenesis

We make an attempt to study neutrino phenomenology in the framework of type-III seesaw by considering A_4 modular symmetry in the super-symmetric context. In addition, we have included a local U(1)_{B-L} symmetry which eventually helps us to avoid certain unwanted terms in the superpotential. Hitherto, the seesaw being type-III, it involves three fermion triplet superfields Sigma _R, along with which, we have included a singlet weighton field (rho ). In here, modular symmetry plays a crucial role by avoiding the usage of excess flavon (weighton) fields. Also, the Yukawa couplings acquire modular forms which are expressed in terms of Dedekind eta function eta (tau ). However, for numerical analysis we use q expansion expressions of these couplings. Therefore, the model discussed here is triumphant enough to accommodate the observed neutrino oscillation data and also successfully explains observed baryon asymmetry of the universe through leptogenesis.

Diagnostic value of water-fat-separated images and CT-like susceptibility-weighted images extracted from a single ultrashort echo time sequence for the evaluation of vertebral fractures and degenerative changes of the spine

ObjectivesTo evaluate the performance of single-echo Dixon water-fat imaging and computed tomography (CT)–like imaging based on a single ultrashort echo time (sUTE) MR sequence for imaging of vertebral fractures as well as degenerative bone changes of the spine in comparison to conventional CT and MR sequences.MethodsThirty patients with suspected acute vertebral fractures were examined using a 3-T MRI, including an sUTE sequence as well as short-tau inversion recovery (STIR) and T1-weighted sequences. During postprocessing, water-fat separation was performed by solving the smoothness-constrained inverse water-fat problem based on a single-complex UTE image. By removing the unwanted low-frequency phase terms, additional MR-based susceptibility-weighted-like (SW-like) images with CT-like contrast were created. Two radiologists evaluated semi-quantitative and quantitative features of fractures and degenerative changes independently and separately on CT and MR images.ResultsIn total, all 58 fractures were accurately detected of whom 24 were correctly classified as acute fractures with an edema detected on the water-fat-separated UTE images, using STIR and T1w sequences as standard of reference. For the morphological assessment of fractures and degenerative changes, the overall agreement between SW-like images and CT was substantial to excellent (e.g., Genant: κ 0.90 (95% confidence interval 0.54–1.00); AO/Magerl: κ 0.75 (95% confidence interval 0.43–1.00)). Overall inter-reader agreement for water-fat-separated UTE images and SW-like images was substantial to almost perfect.ConclusionDetection and assessment of vertebral fractures and degenerative bone changes of the spine were feasible and accurate using water-fat-separated images as well as SW-like images, both derived from the same sUTE-Dixon sequence.Key Points• The detection of acute vertebral fractures was feasible using water-fat-separated images and CT-like images reconstructed from one sUTE sequence.• Assessment of the vertebral fractures using SW-like images with CT-like contrast was found to be comparable to conventional CT.• sUTE imaging of the spine can help reduce examination times and radiation exposure.

Text sentiment analysis on E‐shopping product reviews using chaotic coyote optimized deep belief network approach

AbstractText sentiment analysis is mainly used to the customers benefits. In the existing works, the text sentiment analysis faces more troubles such as, disambiguation (removing unwanted terms), discussions, contrast, intensity, and excessive flections and complex sound structure with less accuracy. In this article, the text sentiment analysis on E‐shopping product using chaotic coyote optimized deep belief network approach is proposed to minimize the troubles in the sentiment analysis and increase the accuracy. The other name of sentiment analysis is subjective analysis. The main objective of this article is “classify the text sentiments according to the polarity (positive and negative) and to increase the accuracy.” Here, the E‐shopping Kaggle datasets are preprocessed and the features are extracted. Then, the extracted features of the trained data's are given using deep belief network (DBN) classifier to get pure sentiments (positive or negative) with accuracy. Here, the performance metrics of the accuracy, recall, and precision, F‐measure, specificity, and sensitivity are calculated. The simulation process is executed in Python platform. The proposed chaotic coyote optimized deep belief network (CCO‐DBN) attains accuracy 9.8%, precision 17.2%, recall 5.61%, F‐measure 17.07%, specificity 2.247%, sensitivity 13.25% is higher than the existing methods such as FCM‐DFA, GA, SVM‐RFA.

Twitter Sentiment Analysis Using Social-Spider Lex Feature-Based Syntactic-Senti Rule Recurrent Neural Network Classification

Social platforms have become one of the major sources of unstructured text. Investigating the unstructured text and interpreting the meaning is a complex job. Sentiment Analysis is an emerging approach as the social platforms have lot of opinionated data. 1 It uses language processing, classification of texts and linguistics to retrieve the opinions from the text. Twitter is a micro blogging site which is popular amongst the social users as it is a vast open data-platform and it witnesses lot of sentiments. Twitter Sentiment Analysis is a process of automatic mining of user tweets for opinions, emotions, attitude to derive useful insights into community opinions and classify the opinions as well. Due to the enormous increase in the number of collaborative tweets, it has become complex to identify the terms that carries sentiments. Also, the unstructured tweets may have non-relevant terms and reduce the classification accuracy. To address these issues, we propose a Social-Spider Lex Feature Ensemble Model-Based Syntactic-Senti Rule prediction Recurrent Neural Network Classifier (S2LFEM-S2RRNN) to obtain better classification accuracy. Twitter is used as source of data and we have extracted the tweets using Twitter API. Initially, data pre-processing is done to remove unwanted data, symbols and content terms are extracted to improvise the dataset. Then, the significant lexical content terms are extracted employing the proposed Social Spider Lex Feature Ensemble Model (S2LFEM) based on Syntactic-Senti Rule Prediction. The semantics 4 of the terms are analysed on the verbs, subjectivity of the tweet patterns to count the overall weightage of tweets. Based on tweet weightage Recurrent Neural Network is trained to classify the tweets int to positive, negative and neutral. The experiment results show that the proposed classifier outperforms the existing models for sentiment classification in terms of accuracy with a performance score 94.1%.

Development of a double-MRT pseudopotential model for tridimensional boiling simulation

A new thermal lattice Boltzmann scheme for the simulation of heat transfer and phase change in multiphase flows based on the pseudopotential formulation is introduced. The model includes a novel elaboration of the equilibrium distribution function, source term, and off-diagonal elements of the relaxation matrix. The resulting equation formally recovers the macroscopic advection-diffusion equation for energy transport avoiding unwanted non-physical terms. Moreover, the thermal diffusivity can be controlled using relaxation factors and free parameters of the equilibrium distribution. The new model is applied to simulate the stratification of a van der Waals fluid and the one-dimensional Stefan problem. In particular, the predictive capability of the model is tested against real experimental conditions, finding good agreement in the bubble growth rate and the wall-temperature dependence of the departure diameter.

Back-Projected Cylindrical Modal Filtering for Digital Holographic Reconstruction Phase-Less Near-Field Measurement

In this letter, the cylindrical modal filtering is presented for digital holographic reconstruction (DHR) phase-less near-field (NF) measurement. The DHR phase-less NF facility can reconstruct the complex field of the antenna under test (AUT) by measuring only the intensity of the interference field on the AUT and reference antenna in one NF scanning plane. In addition to the retrieved AUT field, some unwanted items also exist in the reconstructed field. Hence, advanced filtering method is essential to extract the retrieved AUT field from the reconstructed field. In previous work of the DHR phase-less NF measurement, the back-projected (BP) filtering is utilized as the filtering method. In this letter, that filtering method is updated by the BP cylindrical modal filtering to further improve the accuracy of the DHR phase-less NF measurement. To enhance the adequate modal separation between the desired and unwanted terms, the reconstructed field is first BP to the aperture plane, then represented with orthogonal cylindrical modes. Finally, the AUT field is extracted by twice modal filtering to remove the disturbances on two orthogonal directions. The simulation and experiment results indicate that compared with the results by the BP filtering, the accuracy of the DHR phase-less NF measurement has been improved 50% in valid angle by the BP modal filtering.

Assessment of vertebral fractures and edema of the thoracolumbar spine based on water-fat and susceptibility-weighted images derived from a single ultra-short echo time scan.

To develop a methodology to simultaneously perform single echo Dixon water-fat imaging and susceptibility-weighted imaging (SWI) based on a single echo time (TE) ultra-short echo time (UTE) (sUTE) scan to assess vertebral fractures and degenerative bone changes in the thoracolumbar spine. A methodology was developed to solve the smoothness-constrained inverse water-fat problem to separate water and fat while removing unwanted low-frequency phase terms. Additionally, the corrected UTE phase was used for SWI. UTE imaging (TE: 0.14 ms, 3T MRI) was performed in the lumbar spine of nine patients with vertebral fractures and bone marrow edema (BME). All images were reviewed by two radiologists. Water- and fat-separated images were analyzed in comparison with short-tau inversion recovery (STIR) and with respect to BME visibility. The visibility of fracture lines and cortical outlining of the UTE magnitude images were analyzed in comparison with computed tomography. Unwanted phase components, dominated by the B1 phase, were removed from the UTE phase images. The rating of the diagnostic quality of BME visualization showed a high preference for the sUTE-Dixon water- and fat-separated images in comparison with STIR. The UTE magnitude images enabled better visualizing fracture lines compared with STIR and slightly better visibility of cortical outlining. With increasing SWI weighting osseous structures and fatty tissues were enhanced. The proposed sUTE-Dixon-SWI methodology allows the removal of unwanted low-frequency phases and enables water-fat separation and SWI processing from a single complex UTE image. The methodology can be used for the simultaneous assessment of vertebral fractures and BME of the thoracolumbar spine.

Efficient Biexciton State Preparation in a Semiconductor Quantum Dot‐Metallic Nanoparticle Hybrid Structure Using Transitionless Quantum Driving

AbstractHow to efficiently prepare the biexciton state in a semiconductor quantum dot placed in the vicinity of a metal nanoparticle is investigated, with control pulses calculated using shortcuts to adiabaticity and specificaly transitionless quantum driving. The quantum dot is considered to be initialized in its ground state. It is numerically demonstrated that the proposed scheme can generate biexciton population values close to unity, for a broad span of interparticle distances and small to moderate values of the biexciton binding energy, when using short laser pulses. It is also shown that these results are robust for small errors in the nanoparticle placement. When the interparticle distance is decreased or the duration of the applied pulses is increased, the population transfer to the biexciton state is reduced. The reason is that for shorter distances the nonlinear terms in the density matrix equation, arising due to exciton‐plasmon interaction, become stronger, while for longer pulses the influence of these unwanted terms is prolonged. Similarly, the fidelity is also reduced for larger values of the biexciton binding energy and longer pulses. This work may be exploited in research fields like quantum information processing and high speed nanoswitches, where a key procedure is the efficient biexciton state preparation in quantum dots.

Demonstration of a High-Fidelity cnot Gate for Fixed-Frequency Transmons with Engineered ZZ Suppression.

Improving two-qubit gate performance and suppressing cross talk are major, but often competing, challenges to achieving scalable quantum computation. In particular, increasing the coupling to realize faster gates has been intrinsically linked to enhanced cross talk due to unwanted two-qubit terms in the Hamiltonian. Here, we demonstrate a novel coupling architecture for transmon qubits that circumvents the standard relationship between desired and undesired interaction rates. Using two fixed frequency coupling elements to tune the dressed level spacings, we demonstrate an intrinsic suppression of the static ZZ while maintaining large effective coupling rates. Our architecture reveals no observable degradation of qubit coherence (T_{1},T_{2}>100 μs) and, over a factor of 6 improvement in the ratio of desired to undesired coupling. Using the cross-resonance interaction, we demonstrate a 180ns single-pulse controlled not (cnot) gate, and measure a cnot fidelity of 99.77(2)% from interleaved randomized benchmarking.

A Novel Lattice Boltzmann Model for Fourth Order Nonlinear Partial Differential Equations

In this paper, a novel lattice Boltzmann (LB) equation model is proposed to solve the fourth order nonlinear partial differential equation (NPDE). Different from existing LB models, a source distribution function is introduced to remove some unwanted terms in the nonlinear part of the equation. Hereby, the equilibrium distribution function is designed to follow the rule of Chapman–Enskog (C–E) analysis. Through the C–E procedure, the fourth order NPDE can be recovered perfectly from the proposed LB model. A series of numerical experiments have been carried out to solve some widely studied fourth order NPDEs, including the Kuramoto–Sivashinsky equation, Cahn–Hilliard equation with double-well potential and a fourth order diffuse interface model with Peng–Robinson equation of state. Numerical results show that the performance of the present LB model is much better than other existing LB models.

Reservoir-engineered entanglement in an unresolved-sideband optomechanical system

We study theoretically the generation of strong entanglement of two mechanical oscillators in an unresolved-sideband optomechanical cavity, using a reservoir engineering approach. In our proposal, the effect of unwanted counter-rotating terms is suppressed via destructive quantum interference by the optical field of two auxiliary cavities. For arbitrary values of the optomechanical interaction, the entanglement is obtained numerically. In the weak-coupling regime, we derive an analytical expression for the entanglement of the two mechanical oscillators based on an effective master equation, and obtain the optimal parameters to achieve strong entanglement. Our analytical results are in accord with numerical simulations.

Incipient fault detection in nonlinear non-Gaussian noisy environment

Incipient fault detection in real-time nonlinear closed-loop systems in the presence of unwanted stochastic terms remains a challenging issue, especially in mixed Gaussian and non-Gaussian environments. This paper is concerned with incipient-fault detection in such systems. To this goal, based on the autocorrelation of the windowed residual signal and the reasonable assumptions in the nonlinear system, an online incipient fault detection with acceptable computational efforts and an adaptive-robust residual scheme is provided. Also, a closed-loop form of the three-tank system (DTS200) has been devised and simulated to demonstrate the effectiveness of the proposed solution.

Telecentric in-line-and-off-axis hybrid digital holographic high-resolution reconstruction method

In-line digital holography usually employs a phase retrieval algorithm to decouple the phase information but fails to eliminate the unwanted DC and twin image terms when the measured sample does not agree with the sparsity. While the off-axis digital holography can efficiently remove the unwanted image terms but can not reserve the high frequencies of the sample to realize high resolution. The in-line-and-off-axis hybrid digital holography was then developed to provide a relatively high resolution digital holographic imaging without considering the effect of the unwanted terms. In other words, the in-line-and-off-axis hybrid digital holography merges all of the best virtues of the mentioned-above methods in an efficient and elegant way. However, this state-of-the-art method requires prior knowledge about the diffraction distance, which results in time-consuming and low accuracy. In other sense, telecentric technology can realize non-diffractive imaging without the knowledge about the diffraction distance or spherical aberration or defocusing aberration. Therefore, in this paper, a novel in-line-and-off-axis hybrid digital holography is proposed by introducing telecentric imaging architecture, and the corresponding reconstruction method is further proposed by utilizing constrained iterative approach. In this method, telecentric in-line-and-off-axis hybrid digital holography is first used to acquire focused off-axis and in-line holograms, respectively. The low resolution phase information is reconstructed from the off-axis hologram by using Fourier transform method with the help of the sample-free off-axis hologram, and then multiplexed with the amplitude information obtained from the in-line hologram to act as the initial complex amplitude in the iterative recovery process. As a result, constrained iterations are carried out in the spatial domain and frequency domain to realize high resolution and high speed reconstruction. After simulations, we build an experimental setup and demonstrate the operation of the method with USAF resolution target, onion cells and bee wings. Both the simulation and experimental results show that the proposed method can require no prior knowledge to suppress the phase disturbance caused by the unwanted image terms and optical aberrations, resulting in high speed and full utilization of spatial bandwidth product of the digital camera to yield high resolution reconstruction. We hope that the proposed method will have most practical applications in the case where large resolution, high speed and good quality are needed.

A Unified SO(3) Approach to the Attitude Control Design for Quadrotors

This paper proposes a two-phased problem reformulation approach to solve the quadrotor UAV attitude control problem. Given an initial attitude, the objective is to design a control to drive it toward a desired value. The first phase begins with the definition of three types of errors pertaining to attitude discrepancy, followed by the utilization of virtual control with which the dynamics of quadrotor’s attitude and angular velocity are then unified under the framework of SO(3), rendering the original control problem much more transparent to tackle. Through cancellation of certain unwanted terms emerging from the unification process, entry-wise treatment of the remaining matrix dynamics is then employed in the second phase to transform it further into the stabilization problem of a 3-dimensional linear time-invariant system that is fairly easy to solve since to which standard feedback designs such as linear quadratic regulator and pole placement are readily applicable. In addition to the classical designs, a specialized and structurally simple controller is provided to reduce the number of gains. To account for system parametric uncertainties, external disturbances, and sensor measurement errors and noises, a second controller based on classical $H_{\infty }$ theory is presented to enhance the robustness of the design. A numerical example is given, and computer simulations are conducted to generate error and control trajectories to assess and compare the effectiveness of the presented designs.

Generalized Hamiltonian to describe imperfections in ion-light interaction

We derive a general Hamiltonian that governs the interaction between an $N$-ion chain and an externally controlled laser field, where the ion motion is quantized and the laser field is considered beyond the plane-wave approximation. This general form not only explicitly includes terms that are used to drive ion-ion entanglement, but also a series of unwanted terms that can lead to quantum gate infidelity. We demonstrate the power of our expressivity of the general Hamiltonian by singling out the effect of axial mode heating and confirm this experimentally. We discuss pathways forward in furthering the trapped-ion quantum computational quality, guiding hardware design decisions.