Decoherence of a Damped Anisotropic Harmonic Oscillator under Magnetic Field Effects in a Two-Dimensional Noncommutative Phase-Space

In this paper, decoherence of a damped anisotropic harmonic oscillator in the presence of a magnetic field is studied in the framework of the Lindblad theory of open quantum systems in noncommutative phase-space. General fundamental conditions that should follow our quantum mechanical diffusion coefficients appearing in the master equation are kindly derived. From the master equation, the expressions of density operator, the Wigner distribution function, the expectation and variance with respect to coordinates and momenta are obtained. Based on these quantities, the total energy of the system is evaluated and simulations show its dependency to phase-space structure and its improvement due to noncommutativity effects and the environmental temperature as well. In addition, we also evaluate the decoherence time scale and show that it increases with noncommutativity phase-space effects as compared to the commutative case. It turns out from simulations that this time scale is significantly improved under magnetic field effects.

Thermodynamics of charged AdS black hole surrounded by quintessence in restricted phase space

We study thermodynamics of charged AdS black hole surrounded by quintessence in a new formalism which is called the restricted phase space thermodynamics.This context is based on Visser’s holographic thermodynamics with a fixed antide Sitter radius and a variable Newton constant.The conjugate variables,central charge C and the chemical potential m,are introduced as a new pair of thermodynamic variables.We find that the iso-e-charge T-S curve becomes non-monotonic when Q<Q_(c).Correspondingly,the F-T curve exhibits a swallow tail structure.This behavior is considered as a van der Waals-like phase transition.As the value of b related to the energy density of Kiselev’s fluid becomes larger,the critical temperature T_(c)will decrease.Thus,the van derWaals-like phase transition will occur at lower temperature.There is always a non-quilibrium transition from a small unstable black hole to a large stable black hole state in the isocoltage T-S process.There exist a maximum and a Hawking-Page phase transition points in theμ-C plane.As the value of b related to Kiselev’s fluid becomes larger,the Hawking-Page phase transition will occur at lower temperature in the isovoltageμ-T process.For other values of the state parameterω,there also exists van der Waals-like phase transition.

Heterogeneous information phase space reconstruction and stability prediction of filling body–surrounding rock combination

Traditional research believes that the filling body can effectively control stress concentration while ignoring the problems of unknown stability and the complex and changeable stress distribution of the filling body–surrounding rock combination under high-stress conditions.Current monitoring data processing methods cannot fully consider the complexity of monitoring objects,the diversity of monitoring methods,and the dynamics of monitoring data.To solve this problem,this paper proposes a phase space reconstruction and stability prediction method to process heterogeneous information of backfill–surrounding rock combinations.The three-dimensional monitoring system of a large-area filling body–surrounding rock combination in Longshou Mine was constructed by using drilling stress,multipoint displacement meter,and inclinometer.Varied information,such as the stress and displacement of the filling body–surrounding rock combination,was continuously obtained.Combined with the average mutual information method and the false nearest neighbor point method,the phase space of the heterogeneous information of the filling body–surrounding rock combination was then constructed.In this paper,the distance between the phase point and its nearest point was used as the index evaluation distance to evaluate the stability of the filling body–surrounding rock combination.The evaluated distances(ED)revealed a high sensitivity to the stability of the filling body–surrounding rock combination.The new method was then applied to calculate the time series of historically ED for 12 measuring points located at Longshou Mine.The moments of mutation in these time series were at least 3 months ahead of the roadway return dates.In the ED prediction experiments,the autoregressive integrated moving average model showed a higher prediction accuracy than the deep learning models(long short-term memory and Transformer).Furthermore,the root-mean-square error distribution of the prediction results peaked at 0.26,thus outperforming the no-prediction method in 70%of the cases.

USING TWO-DIMENSIONAL TIME RESOLVED LIGHT SCATTERING TO STUDY THE CURE REACTION INDUCED PHASE SEPARATION PROCESS OF EPOXY-AMINE-POLYETHERSULFONE BLEND WITH SECONDARY PHASE SEPARATION

The generalized two-dimensional correlation analysis based on time-resolved light scattering patterns （2D TRLS） has been employed to study the phase separation process of an epoxy-amine-polyethersulfone blend in which the secondary phase separation takes place. The results of the 2D TRLS provided more detailed information that was not readily observed in the 1D TRLS patterns. （i） During the first process of phase separation, the sequential order of coarsening in size of the domains among the larger and smaller ones has been reversed between the diffusion regime and the hydrodynamic regime. （ii） The change of the larger domains in size, due to the hydrodynamic flow in the late stage of the first phase separation process, keeps on taking place earlier than that of the new domains appeared in the secondary phase separation process. （iii） During the secondary phase separation process the size growth of the smaller domains takes place earlier than that of the larger ones, probably due to the assumption that the coarsening mode could decrease the interface tension more quickly.

PC-bzip2: a phase-space continuity-enhanced lossless compression algorithm for light-field microscopy data

Light-field fluorescence microscopy(LFM)is a powerful elegant compact method for long-term highspeed imaging of complex biological systems,such as neuron activities and rapid movements of organelles.LFM experiments typically generate terabytes of image data and require a substantial amount of storage space.Some lossy compression algorithms have been proposed recently with good compression performance.However,since the specimen usually only tolerates low-power density illumination for longterm imaging with low phototoxicity,the image signal-to-noise ratio(SNR)is relatively low,which will cause the loss of some efficient position or intensity information using such lossy compression algorithms.Here,we propose a phase-space continuity-enhanced bzip2(PC-bzip2)lossless compression method for LFM data as a high-efficiency and open-source tool that combines graphics processing unit-based fast entropy judgment and multicore-CPU-based high-speed lossless compression.Our proposed method achieves almost 10%compression ratio improvement while keeping the capability of high-speed compression,compared with the original bzip2.We evaluated our method on fluorescence beads data and fluorescence staining cells data with different SNRs.Moreover,by introducing temporal continuity,our method shows the superior compression ratio on time series data of zebrafish blood vessels.

Temperature-induced phase transition of two-dimensional semiconductor GaTe

GaTe is a two-dimensional Ⅲ-Ⅵ semiconductor with suitable direct bandgap of~1.65 eV and high photoresponsivity,which makes it a promising candidate for optoelectronic applications.GaTe exists in two crystalline phases:monoclinic(m-GaTe,with space group C2/m) and hexagonal(h-GaTe,with space group P63/mmc).The phase transition between the two phases was reported under temperature-varying conditions,such as annealing,laser irradiation,etc.The explicit phase transition temperature and energy barrier during the temperature-induced phase transition have not been explored.In this work,we present a comprehensive study of the phase transition process by using first-principles energetic and phonon calculations within the quasi-harmonic approximation framework.We predicted that the phase transition from h-GaTe to m-GaTe occurs at the temperature decreasing to 261 K.This is in qualitative agreement with the experimental observations.It is a two-step transition process with energy barriers 199 meV and 288 meV,respectively.The relatively high energy barriers demonstrate the irreversible nature of the phase transition.The electronic and phonon properties of the two phases were further investigated by comparison with available experimental and theoretical results.Our results provide insightful understanding on the process of temperature-induced phase transition of GaTe.

Two-Dimensional Electronic Spectroscopy with Active Phase Management

Two-dimensional elec tronic spec troscopy(2DES)is a powerful met hod to probe the coherent electron dynamics in complicated systems.Stabilizing the phase difference of the incident ultrashort pulses is the mos t challenging par t for experimen tal demonstration of 2DES.Here,we present a tuto rial review on the 2DES proto cols based on active phase managements which are originally developed for quantum optics experiments.We introduce the 2DES techniques in box and pump-probe geometries with phase stabilization realized by interferometry,and outline the fully collinear 2DES approach with the frequency tagging by acoustic optical modulators and frequency combs.The combination of active phase managements,ultrashort pulses and other spectroscopic methods may open new opportunities to tackle essential challenges related to excited states.

Effect of One/Two-dimensional Bonding Phases on Strength and Toughness of Carbon-containing Refractories

Gaseous phases of carbon-containing and metastable oxides will be resulted from the carbonization of phenolic resin binders and the reduced reactions between C and oxides at high temperatures in carbon-containing refractories. With the in-situ catalysis technique, these gaseous phases can be transformed to one-or two-dimensional bonding phases by deposition,which is favorable for the improvement on strength and toughness of carboncontaining refractories,especially low carbon refractories. The research results reveal that：（ 1） the amorphous carbon resulted from phenolic resin can be transformed to carbon nanotubes,thus,the oxidation peak temperature is raised from 506 to 664. 6 ℃;（ 2） onedimensional whiskers of MgO or Mg Al2 O4 can be in-situ formed in MgO-C refractories, and their CMOR,CCS,rupture displacement and residual CCS（ two water quenching cycles,1 100 ℃） are increased by 66%,47%,13% and 26%,respectively;（ 3） two-dimensional array structure of flake β-SiAlON can be in-situ formed in Al2 O3-C refractories,which improves the material strength by 60% and decreases the residual strength after thermal shock by only 4. 5 MPa. It is believed that the in-situ formation of one-or two-dimensional bonding phases at high temperatures can improvethe comprehensive thermal physical properties of carboncontaining refractories,and will be the developing trend of the strengthening and toughening of low carbon-containing refractories.

INTERNET TRAFFIC DATA FLOW FORECAST BY RBF NEURAL NETWORK BASED ON PHASE SPACE RECONSTRUCTION

Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a network flow. Some parameters, such as the correlative dimension and the Lyapunov exponent are calculated, and the chaos characteristic is proved to exist in Internet traffic data flows. A neural network model is construct- ed based on radial basis function （RBF） to forecast actual Internet traffic data flow. Simulation results show that, compared with other forecasts of the forward-feedback neural network, the forecast of the RBF neural network based on the chaos theory has faster learning capacity and higher forecasting accuracy.

New conserved quantities of Noether-Mei symmetry of mechanical system in phase space

This paper studies two new types of conserved quantities deduced by Noether Mei symmetry of mechanical system in phase space. The definition and criterion of Noether Mei symmetry for the system are given. A coordination function is introduced, and the conditions under which the Noether- Mei symmetry leads to the two types of conserved quantities and the forms of the two types of conserved quantities are obtained. An illustrative example is given. The coordination function can be selected according to the demand for finding the gauge function, and the choice of the coordination function has multiformity, so more conserved quantities deduced from Noether Mei symmetry of mechanical system can be obtained.

Transverse phase space reconstruction study in Shanghai soft X-ray FEL facility

Phase space is one of the most important parameters used to describe beam properties. Computer tomography, as a method for reconstructing phase space and measuring beam emittance, has been used in many accelerators over the past few decades. In this paper, we demonstrate a transverse phase space reconstruction study in the Shanghai soft X-ray free electron laser facility. First,we discuss the basic principles of phase space reconstruction and the advantage of reconstructing beam distribution in normalized phase space. Then, the phase space reconstruction results by different computer tomography methods based on the maximum entropy(MENT) algorithm and the filtered back projection algorithm in normalized phase space are presented. The simulation results indicate that,with proper configuration of the phase advance between adjacent screens, the MENT algorithm is feasible and has good efficiency. The beam emittance and Twiss parameters are also calculated using the reconstructed phase space.

Prediction of elevator traffic flow based on SVM and phase space reconstruction

To make elevator group control system better follow the change of elevator traffic flow (ETF) in order to adjust the control strategy,the prediction method of support vector machine (SVM) in combination with phase space reconstruction has been proposed for ETF.Firstly,the phase space reconstruction for elevator traffic flow time series (ETFTS) is processed.Secondly,the small data set method is applied to calculate the largest Lyapunov exponent to judge the chaotic property of ETF.Then prediction model of ETFTS based on SVM is founded.Finally,the method is applied to predict the time series for the incoming and outgoing passenger flow respectively using ETF data collected in some building.Meanwhile,it is compared with RBF neural network model.Simulation results show that the trend of factual traffic flow is better followed by predictive traffic flow.SVM algorithm has much better prediction performance.The fitting and prediction of ETF with better effect are realized.

Noether-Mei Symmetry of Mechanical System in Phase Space

In this paper, a new kind of symmetry and its conserved quantities of a mechanical system in phase space are studied. The definition of this new symmetry, i,e., a Noether-Mei symmetry, is presented, and the criterion of this symmetry is also given. The Noether conserved quantity and the Mei conserved quantity deduced from the Noether-Mei symmetry of the system are obtained. Finally, two examples are given to illustrate the Bpplication of the results.

Phase space reconstruction of chaotic dynamical system based on wavelet decomposition

In view of the disadvantages of the traditional phase space reconstruction method, this paper presents the method of phase space reconstruction based on the wavelet decomposition and indicates that the wavelet decomposition of chaotic dynamical system is essentially a projection of chaotic attractor on the axes of space opened by the wavelet filter vectors, which corresponds to the time-delayed embedding method of phase space reconstruction proposed by Packard and Takens. The experimental results show that, the structure of dynamical trajectory of chaotic system on the wavelet space is much similar to the original system, and the nonlinear invariants such as correlation dimension, Lyapunov exponent and Kolmogorov entropy are still reserved. It demonstrates that wavelet decomposition is effective for characterizing chaotic dynamical system.

Degradation Process of Coated Tinplate by Phase Space Reconstruction Theory

The degradation process of organosol coated tinplate in beverage was investigated by electrochemical noise (EN) technique combined with morphology characterization.EN data were analyzed using phase space reconstruction theory.With the correlation dimensions obtained from the phase space reconstruction,the chaotic behavior of EN was quantitatively evaluated.The results show that both electrochemical potential noise (EPN) and electrochemical current noise (ECN) have chaotic properties.The correlation dimensions of EPN increase with corrosion extent,while those of ECN seem nearly unchanged.The increased correlation dimensions of EPN during the degradation process are associated with the increased susceptibility to local corrosion.

A New Kind of Two-Fold Integration Transformation in Phase Space and Its Uses in Weyl Ordering of Operators

We propose a new two-fold integration transformation in p-q phase space∫∫^∞-∞dpdq/π e^2i（p-x）（q-y）f（p,q）≡G（x,y）,which possesses some well-behaved transformation properties. We apply this transformation to the Weyl ordering of operators, especially those Q-P ordered and P-Q ordered operators.

Study on resource quantity of surface water based on phase space reconstruction and neural network

Proposed a new method to disclose the complicated non-linearity structure of the water-resource system, introducing chaos theory into the hydrology and water resources field, and combined with the chaos theory and artificial neural networks. Training data construction and networks structure were determined by the phase space reconstruction, and establishing nonlinear relationship of phase points with neural networks, the forecasting model of the resource quantity of the surface water was brought forward. The keystone of the way and the detailed arithmetic of the network training were given. The example shows that the model has highly forecasting precision.

A Forecasting Model of Vector Similarity in Phase Space for Flood and Drought over the Huanghe-Huaihe-Haihe Plain in China

To represent well the characteristics of temporal and spatial distributions, chart of 3-dekad moving total precipitation is proposed in this paper first. Then this kind of chart is expanded in terms of Chebyshev polynomial at irregular grids, and the quantitative representation of precipitation is got. Finally the Chebyshev coefficients are forecasted by using the forecasting method of vector similarity in phase space proposed by Zhou (1992). Using above mentioned procedures temporal and spatial distributions of precipitation over the Huanghe-- Huaihe-- H aihe Plain in China are forecasted.

Analysis of dynamic of two-phase flow in small channel based on phase space reconstruction combined with data reduction sub-frequency band wavelet

A new method of nonlinear analysis is established by combining phase space reconstruction and data reduction sub-frequency band wavelet. This method is applied to two types of chaotic dynamic systems(Lorenz and Rssler) to examine the anti-noise ability for complex systems. Results show that the nonlinear dynamic system analysis method resists noise and reveals the internal dynamics of a weak signal from noise pollution. On this basis, the vertical upward gas–liquid two-phase flow in a 2 mm × 0.81 mm small rectangular channel is investigated. The frequency and energy distributions of the main oscillation mode are revealed by analyzing the time–frequency spectra of the pressure signals of different flow patterns. The positive power spectral density of singular-value frequency entropy and the damping ratio are extracted to characterize the evolution of flow patterns and achieve accurate recognition of different vertical upward gas–liquid flow patterns(bubbly flow:100%, slug flow: 92%, churn flow: 96%, annular flow: 100%). The proposed analysis method will enrich the dynamics theory of multi-phase flow in small channel.

Classification of power quality combined disturbances based on phase space reconstruction and support vector machines

Power Quality (PQ) combined disturbances become common along with ubiquity of voltage flickers and harmonics. This paper presents a novel approach to classify the different patterns of PQ combined disturbances. The classification system consists of two parts, namely the feature extraction and the automatic recognition. In the feature extraction stage, Phase Space Reconstruction (PSR), a time series analysis tool, is utilized to construct disturbance signal trajectories. For these trajectories, several indices are proposed to form the feature vectors. Support Vector Machines (SVMs) are then implemented to recognize the different patterns and to evaluate the efficiencies. The types of disturbances discussed include a combination of short-term dis-turbances (voltage sags, swells) and long-term disturbances (flickers, harmonics), as well as their homologous single ones. The feasibilities of the proposed approach are verified by simulation with thousands of PQ events. Comparison studies based on Wavelet Transform (WT) and Artificial Neural Network (ANN) are also reported to show its advantages.