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Fast radio bursts (FRBs) are extra-galactic sources with unknown physical mechanisms. They emit millisecond-duration radio pulses with isotropic equivalent energy of $10^{36}\sim10^{41}$ ergs. This corresponds to a brightness temperature of FRB emission typically reaching the level of $10^{36}$ K, but can be as high as above $10^{40}$ K for sub-microsecond timescale structures, suggesting the presence of underlying coherent relativistic radiation mechanisms. polarization carries the key information to understand the physical origin of FRBs, with linear polarization usually tracing the geometric configuration of magnetic fields and circular polarization probing both intrinsic radiation mechanisms and propagation effects. Here we show that the repeating sources FRB 20201124A emits $90.9\pm 1.1\%$ circularly polarized radio pulses. Such a high degree of circular polarization was unexpected in theory and unprecedented in observation in the case of FRBs, since such a high degree of circular polarization was only common among Solar or Jovian radio activities, attributed to the sub-relativistic electrons. We note that there is no obvious correlation between the degree of circular polarization and burst fluence. Besides the high degree of circular polarization, we also detected rapid swing and orthogonal jump in the position angle of linear polarization. The detection of the high degree circular polarization in FRB 20201124A, together with its linear polarization properties that show orthogonal modes, place strong constraints on FRB physical mechanisms, calling for an interplay between magnetospheric radiation and propagation effects in shaping the observed FRB radiation., Comment: 19 pages, 9 figures, 1 table, accepted for publication in National Science Review

Fast radio bursts (FRBs) are highly dispersed millisecond-duration radio bursts. Recent observations of a Galactic FRB suggest that at least some FRBs originate from magnetars, but the origin of cosmological FRBs is still not settled. Here we report the detection of 1863 bursts in 82 hr over 54 days from the repeating source FRB~20201124A. These observations show irregular short-time variation of the Faraday rotation measure (RM), which probes the density-weighted line-of-sight magnetic field strength, of individual bursts during the first 36 days, followed by a constant RM. We detected circular polarisation in more than half of the burst sample, including one burst reaching a high fractional circular polarisation of 75%. Oscillations in fractional linear and circular polarisations as well as polarisation angle as a function of wavelength were detected. All of these features provide evidence for a complicated, dynamically evolving, magnetised immediate environment within about an astronomical unit (au; Earth-Sun distance) of the source. Our optical observations of its Milky-Way-sized, metal-rich host galaxy reveal a barred spiral, with the FRB source residing in a low stellar density, interarm region at an intermediate galactocentric distance. This environment is inconsistent with a young magnetar engine formed during an extreme explosion of a massive star that resulted in a long gamma-ray burst or superluminous supernova., Comment: 28 pages, 10 figures, updated to match the published version

In this paper, we investigate the impact of correlated noise on fast radio burst (FRB) searching. We found that 1) the correlated noise significantly increases the false alarm probability; 2) the signal-to-noise ratios (S/N) of the false positives become higher; 3) the correlated noise also affects the pulse width distribution of false positives, and there will be more false positives with wider pulse width. We use 55-hour observation for M82 galaxy carried out at Nanshan 26m radio telescope to demonstrate the application of the correlated noise modelling. The number of candidates and parameter distribution of the false positives can be reproduced with the modelling of correlated noise. We will also discuss a low S/N candidate detected in the observation, for which we demonstrate the method to evaluate the false alarm probability in the presence of correlated noise.Possible origins of the candidate are discussed, where two possible pictures, an M82-harbored giant pulse and a cosmological FRB, are both compatible with the observation., Comment: Aceepted for publication in MNRAS. 10 pages, 9 figures

Fast radio bursts (FRBs) are millisecond-duration radio transients of unknown origin. Two possible mechanisms that could generate extremely coherent emission from FRBs invoke neutron star magnetospheres or relativistic shocks far from the central energy source. Detailed polarization observations may help us to understand the emission mechanism. However, the available FRB polarization data have been perplexing, because they show a host of polarimetric properties, including either a constant polarization angle during each burst for some repeaters or variable polarization angles in some other apparently one-off events. Here we report observations of 15 bursts from FRB 180301 and find various polarization angle swings in seven of them. The diversity of the polarization angle features of these bursts is consistent with a magnetospheric origin of the radio emission, and disfavours the radiation models invoking relativistic shocks., Comment: Published online in Nature on 29 Oct, 2020

We present here the analysis of giant micropulses from the Vela pulsar. A total of 4187 giant micropulses with peak flux density $>$2.5 Jy were detected during almost 4 hours of observations carried out with the Yunnan 40-m radio telescope at 6800 MHz. Nine of the giant micropulses arrived approximately 3 to 4 ms earlier than the peak of average pulse profile, longer than that at lower frequencies. The remaining giant micropulses were clustered into three distributions which correspond to three main emission regions, including four occurring on the trailing edge of averaged profile., Comment: 9 pages, 8 figures

For many complex systems the interaction of different scales is among the most interesting and challenging features. It seems not very successful to extract the physical properties in different scale regimes by the existing approaches, such as structure-function and Fourier spectrum method. Fundamentally these methods have their respective limitations, for instance scale mixing, i.e. the so-called infrared and ultraviolet effects. To make improvement in this regard, a new method, multi-level segment analysis (MSA) based on the local extrema statistics, has been developed. Benchmark (fractional Brownian motion) verifications and the important case tests (Lagrangian and two-dimensional turbulence) show that MSA can successfully reveal different scaling regimes, which has been remaining quite controversial in turbulence research. In general the MSA method proposed here can be applied to different dynamic systems in which the concepts of multiscaling and multifractal are relevant., Comment: 18 pages with 9 figures, accepted by Journal of Statistical Mechanics

The classical structure-function (SF) method in fully developed turbulence or for scaling processes in general is influenced by large-scale energetic structures, known as infrared effect. Therefore, the extracted scaling exponents $\zeta(n)$ might be biased due to this effect. In this paper, a detrended structure-function (DSF) method is proposed to extract scaling exponents by constraining the influence of large-scale structures. This is accomplished by removing a $1$st-order polynomial fitting within a window size $\ell$ before calculating the velocity increment. By doing so, the scales larger than $\ell$, i.e., $r\ge \ell$, are expected to be removed or constrained. The detrending process is equivalent to be a high-pass filter in physical domain. Meanwhile the intermittency nature is retained. We first validate the DSF method by using a synthesized fractional Brownian motion for mono-fractal processes and a lognormal process for multifractal random walk processes. The numerical results show comparable scaling exponents $\zeta(n)$ and singularity spectra $D(h)$ for the original SFs and DSFs. When applying the DSF to a turbulent velocity obtained from a high Reynolds number wind tunnel experiment with $Re_{\lambda}\simeq 720$, the 3rd-order DSF demonstrates a clear inertial range with $\mathcal{B}_3(\ell)\simeq 4/5\epsilon \ell$ on the range $10<\ell/\eta<1000$, corresponding to a wavenumber range $0.001

In this work, the scaling statistics of the dissipation along Lagrangian trajectories are investigated by using fluid tracer particles obtained from a high resolution direct numerical simulation with $Re_{\lambda}=400$. Both the energy dissipation rate $\epsilon$ and the local time averaged $\epsilon_{\tau}$ agree rather well with the lognormal distribution hypothesis. Several statistics are then examined. It is found that the autocorrelation function $\rho(\tau)$ of $\ln(\epsilon(t))$ and variance $\sigma^2(\tau)$ of $\ln(\epsilon_{\tau}(t))$ obey a log-law with scaling exponent $\beta'=\beta=0.30$ compatible with the intermittency parameter $\mu=0.30$. The $q$th-order moment of $\epsilon_{\tau}$ has a clear power-law on the inertial range $10<\tau/\tau_{\eta}<100$. The measured scaling exponent $K_L(q)$ agrees remarkably with $q-\zeta_L(2q)$ where $\zeta_L(2q)$ is the scaling exponent estimated using the Hilbert methodology. All these results suggest that the dissipation along Lagrangian trajectories could be modelled by a multiplicative cascade., Comment: 10 pages with 7 figures accepted for Journal of Fluid Mechanics as Rapids

In the marine environment, many fields have fluctuations over a large range of different spatial and temporal scales. These quantities can be nonlinear \red{and} non-stationary, and often interact with each other. A good method to study the multiple scale dynamics of such time series, and their correlations, is needed. In this paper an application of an empirical mode decomposition based time dependent intrinsic correlation, \red{of} two coastal oceanic time series, temperature and dissolved oxygen (saturation percentage) is presented. The two time series are recorded every 20 minutes \red{for} 7 years, from 2004 to 2011. The application of the Empirical Mode Decomposition on such time series is illustrated, and the power spectra of the time series are estimated using the Hilbert transform (Hilbert spectral analysis). Power-law regimes are found with slopes of 1.33 for dissolved oxygen and 1.68 for temperature at high frequencies (between 1.2 and 12 hours) \red{with} both close to 1.9 for lower frequencies (time scales from 2 to 100 days). Moreover, the time evolution and scale dependence of cross correlations between both series are considered. The trends are perfectly anti-correlated. The modes of mean year 3 and 1 year have also negative correlation, whereas higher frequency modes have a much smaller correlation. The estimation of time-dependent intrinsic correlations helps to show patterns of correlations at different scales, for different modes., Comment: 35 pages with 22 figures

We relate the second order structure function of a time series with the power spectrum of the original variable, taking an assumption of statistical stationarity. With this approach, we find that the structure function is strongly influenced by the large scales. The large scale contribution and the contribution range are respectively 79% and 1.4 decades for a Kolmogorov -5/3 power spectrum. We show numerically that a single scale influence range, over smaller scales is about 2 decades. We argue that the structure function is not a good method to extract the scaling exponents when the data possess large energetic scales. An alternative methodology, the arbitrary order Hilbert spectral analysis which may constrain this influence within 0.3 decade, is proposed to characterize the {scaling} property directly in an amplitude-frequency space. An analysis of passive scalar (temperature) turbulence time series is presented to show the influence of large scale structures in real turbulence, and the efficiency of the Hilbert-based methodology. The corresponding scaling exponents $\zeta_{\theta}(q)$ provided by the Hilbert-based approach indicate that the passive scalar turbulence field may be less intermittent than what was previously believed., Comment: 8 pages with 9 figures

In this paper, the scaling property of the inverse energy cascade and forward enstrophy cascade of the vorticity filed $\omega(x,y)$ in two-dimensional (2D) turbulence is analyzed. This is accomplished by applying a Hilbert-based technique, namely Hilbert-Huang Transform, to a vorticity field obtained from a $8192^2$ grid-points direct numerical simulation of the 2D turbulence with a forcing scale $k_f=100$ and an Ekman friction. The measured joint probability density function $p(C,k)$ of mode $C_i(x)$ of the vorticity $\omega$ and instantaneous wavenumber $k(x)$ is separated by the forcing scale $k_f$ into two parts, which corresponding to the inverse energy cascade and the forward enstrophy cascade. It is found that all conditional pdf $p(C\vert k)$ at given wavenumber $k$ has an exponential tail. In the inverse energy cascade, the shape of $p(C\vert k)$ does collapse with each other, indicating a nonintermittent cascade. The measured scaling exponent $\zeta_{\omega}^I(q)$ is linear with the statistical order $q$, i.e., $\zeta_{\omega}^I(q)=-q/3$, confirming the nonintermittent cascade process. In the forward enstrophy cascade, the core part of $p(C\vert k)$ is changing with wavenumber $k$, indicating an intermittent forward cascade. The measured scaling exponent $\zeta_{\omega}^F(q)$ is nonlinear with $q$ and can be described very well by a log-Poisson fitting: $\zeta_{\omega}^F(q)=\frac{1}{3}q+0.45\left(1-0.43^{q}\right)$. However, the extracted vorticity scaling exponents $\zeta_{\omega}(q)$ for both inverse energy cascade and forward enstrophy cascade are not consistent with Kraichnan\rq{}s theory prediction. New theory for the vorticity field in 2D turbulence is required to interpret the observed scaling behavior., Comment: 13 pages with 10 figures

In fully developed turbulence, the velocity field possesses long-range correlations, denoted by a scaling power spectrum or structure functions. Here we consider the autocorrelation function of velocity increment $ {\Delta u_{\ell}(t)}$ at separation {time} $\ell$. Anselmet et al. [Anselmet et al. J. Fluid Mech. \textbf{140}, 63 (1984)] have found that the autocorrelation function of velocity increment has a minimum value, whose location is approximately equal to $\ell$. Taking statistical stationary assumption, we link the velocity increment and the autocorrelation function with the power spectrum of the original variable. We then propose an analytical model of the autocorrelation function. With this model, we prove that the location of the minimum autocorrelation function is exactly equal to the separation {time} $\ell$ when the scaling of the power spectrum of the original variable belongs to the range $0<\beta<2$. This model also suggests a power law expression for the minimum autocorrelation. Considering the cumulative function of the autocorrelation function, it is shown that the main contribution to the autocorrelation function comes from the large scale part. Finally we argue that the autocorrelation function is a better indicator of the inertial range than the second order structure function., Comment: 11 pages with 9 figures

Hilbert-Huang transform is a method that has been introduced recently to decompose nonlinear, nonstationary time series into a sum of different modes, each one having a characteristic frequency. Here we show the first successful application of this approach to homogeneous turbulence time series. We associate each mode to dissipation, inertial range and integral scales. We then generalize this approach in order to characterize the scaling intermittency of turbulence in the inertial range, in an amplitude-frequency space. The new method is first validated using fractional Brownian motion simulations. We then obtain a 2D amplitude-frequency representation of the pdf of turbulent fluctuations with a scaling trend, and we show how multifractal exponents can be retrieved using this approach. We also find that the log-Poisson distribution fits the velocity amplitude pdf better than the lognormal distribution., Comment: 6 pages with 8 figures

In this paper, we introduce a new way to estimate the scaling parameter of a self-similar process by considering the maximum probability density function (pdf) of tis increments. We prove this for $H$-self-similar processes in general and experimentally investigate it for turbulent velocity and temperature increments. We consider turbulent velocity database from an experimental homogeneous and nearly isotropic turbulent channel flow, and temperature data set obtained near the sidewall of a Rayleigh-B\'{e}nard convection cell, where the turbulent flow is driven by buoyancy. For the former database, it is found that the maximum value of increment pdf $p_{\max}(\tau)$ is in a good agreement with lognormal distribution. We also obtain a scaling exponent $\alpha\simeq 0.37$, which is consistent with the scaling exponent for the first-order structure function reported in other studies. For the latter one, we obtain a scaling exponent $\alpha_{\theta}\simeq0.33$. This index value is consistent with the Kolmogorov-Obukhov-Corrsin scaling for passive scalar turbulence, but different from the scaling exponent of the first-order structure function that is found to be $\zeta_{\theta}(1)\simeq 0.19$, which is in favor of Bolgiano-Obukhov scaling. A possible explanation for these results is also given., Comment: 25 pages with 10 figures

In this paper we present an extended version of Hilbert-Huang transform, namely arbitrary-order Hilbert spectral analysis, to characterize the scale-invariant properties of a time series directly in an amplitude-frequency space. We first show numerically that due to a nonlinear distortion, traditional methods require high-order harmonic components to represent nonlinear processes, except for the Hilbert-based method. This will lead to an artificial energy flux from the low-frequency (large scale) to the high-frequency (small scale) part. Thus the power law, if it exists, is contaminated. We then compare the Hilbert method with structure functions (SF), detrended fluctuation analysis (DFA), and wavelet leader (WL) by analyzing fractional Brownian motion and synthesized multifractal time series. For the former simulation, we find that all methods provide comparable results. For the latter simulation, we perform simulations with an intermittent parameter {\mu} = 0.15. We find that the SF underestimates scaling exponent when q > 3. The Hilbert method provides a slight underestimation when q > 5. However, both DFA and WL overestimate the scaling exponents when q > 5. It seems that Hilbert and DFA methods provide better singularity spectra than SF and WL. We finally apply all methods to a passive scalar (temperature) data obtained from a jet experiment with a Taylor's microscale Reynolds number Relambda \simeq 250. Due to the presence of strong ramp-cliff structures, the SF fails to detect the power law behavior. For the traditional method, the ramp-cliff structure causes a serious artificial energy flux from the low-frequency (large scale) to the high-frequency (small scale) part. Thus DFA and WL underestimate the scaling exponents. However, the Hilbert method provides scaling exponents {\xi}{\theta}(q) quite close to the one for longitudinal velocity., Comment: 13 pages, 10 figures

By using the method of density-matrix renormalization-group to solve the different spin-spin correlation functions, the nearest-neighbouring entanglement(NNE) and next-nearest-neighbouring entanglement(NNNE) of one-dimensional alternating Heisenberg XY spin chain is investigated in the presence of alternating nearest neighbour interactions of exchange couplings, external magnetic fields and next-nearest neighbouring interactions. For dimerized ferromagnetic spin chain, NNNE appears only above the critical dimerized interaction, meanwhile, the dimerized interaction effects quantum phase transition point and improves NNNE to a large value. We also study the effect of ferromagnetic or antiferromagnetic next-nearest neighboring (NNN) interactions on the dynamics of NNE and NNNE. The ferromagnetic NNN interaction increases and shrinks NNE below and above critical frustrated interaction respectively, while the antiferromagnetic NNN interaction always decreases NNE. The antiferromagnetic NNN interaction results to a larger value of NNNE in comparison to the case when the NNN interaction is ferromagnetic., Comment: 13 pages, 4 figures,. accepted by Chinese Physics B 2008 11 (in press)

The impurities of exchange couplings, external magnetic fields and Dzyaloshinskii--Moriya (DM) interaction considered as Gaussian distribution, the entanglement in one-dimensional random $XY$ spin systems is investigated by the method of solving the different spin-spin correlation functions and the average magnetization per spin. The entanglement dynamics at central locations of ferromagnetic and antiferromagnetic chains have been studied by varying the three impurities and the strength of DM interaction. (i) For ferromagnetic spin chain, the weak DM interaction can improve the amount of entanglement to a large value, and the impurities have the opposite effect on the entanglement below and above critical DM interaction. (ii) For antiferromagnetic spin chain, DM interaction can enhance the entanglement to a steady value. Our results imply that DM interaction strength, the impurity and exchange couplings (or magnetic field) play competing roles in enhancing quantum entanglement., Comment: 12 pages, 3 figures

The entanglement in one-dimensional random XY spin systems where the impurities of exchange couplings and the external magnetic fields are considered as random variables is investigated by solving the different spin-spin correlation functions and the average magnetization per spin. The entanglement dynamics near particular locations of the system is also studied when the exchange couplings (or the external magnetic fields) satisfy three different distributions(the Gaussian distribution, double-Gaussian distribution, and bimodal distribution). We find that the entanglement can be controlled by varying the strength of external magnetic field and the different distributions of impurities. Moreover, the entanglement of some nearest-neighboring qubits can be increased for certain parameter values of the three different distributions., Comment: 13 pages, 4 figures

In this paper, we study entanglement dynamics of a two-qubit extended Werner-like state locally interacting with independent noisy channels, i.e., amplitude damping, phase damping and depolarizing channels. We show that the purity of initial entangled state has direct impacts on the entanglement robustness in each noisy channel. That is, if the initial entangled state is prepared in mixed instead of pure form, the state may exhibit entanglement sudden death (ESD) and/or be decreased for the critical probability at which the entanglement disappear., Comment: 11 pages, 6 figures