arXiv subjects

Yang Chen

Publications and source records attributed to Yang Chen.

At least 631 records · Page 35Linked to original sources

arXiv2019

FERMI observation of the jets of the microquasar SS433

We report our analysis of the data obtained with the Large Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope (Fermi) for the SS 433/W50 region. The total data length is ten years. Different from the previous results reported for this region (for which an old version of database was used), we show that excess emission is detected around the w1 region in the western lobe of the jets from SS 433. The region is bright at X-rays due to the interaction between the jet and the ambient medium. This detection also matches well the recent results of the very-high-energy detection of SS 433/W50 with the High Altitude Water Cherenkov (HAWC). However, the eastern regions that are slightly brighter in HAWC's observation are not detected in the Fermi data. Constructing the broad-band spectral energy distribution (SED) for the western region, we compare with the HAWC results for the eastern regions and discuss the possible origin of the emission. A leptonic scenario can provide a fit to the Fermi GeV spectrum and HAWC TeV detection, where the former and latter are due to the synchrotron radiation and inverse-Compton process respectively. However, the model can not explain the X-ray and radio emission from the region simultaneously, which thus requires further observational and theoretical studies of the region in order to clarify the reasons.

astro-ph.HE↗

arXiv2019

Linear Statistics of Random Matrix Ensembles at the Spectrum Edge Associated with the Airy Kernel

In this paper, we study the large $N$ behavior of the moment-generating function (MGF) of the linear statistics of $N\times N$ Hermitian matrices in the Gaussian unitary, symplectic, orthogonal ensembles (GUE, GSE, GOE) and Laguerre unitary, symplectic, orthogonal ensembles (LUE, LSE, LOE) at the edge of the spectrum. From the finite $N$ Fredholm determinant expression of the MGF of the linear statistics, we find the large $N$ asymptotics of the MGF associated with the Airy kernel in these Gaussian and Laguerre ensembles. Then we obtain the mean and variance of the suitably scaled linear statistics. We show that there is an equivalence between the large $N$ behavior of the MGF of the scaled linear statistics in Gaussian and Laguerre ensembles, which leads to the statistical equivalence between the mean and variance of suitably scaled linear statistics in Gaussian and Laguerre ensembles. In the end, we use the Coulomb fluid method to obtain the mean and variance of another type of linear statistics in GUE, which reproduces the result of Basor and Widom.

math-ph↗

arXiv2019

CDEX dark matter experiment: Status and prospects

The China Dark Matter Experiment (CDEX) aims at direct searches of light Weakly Interacting Massive Particles (WIMPs) at the China Jinping Underground Laboratory (CJPL) with an overburden of about 2400m rock. Results from a prototype CDEX-1 994 g p-type Point Contact Germanium(pPCGe) detector are reported. Research programs are pursued to further reduce the physics threshold by improving hardware and data analysis. The CDEX-10 experiment with a pPCGe array of 10 kg target mass range is being tested. The evolution of CDEX program into "CDEX-1T Experiment" with ton-scale germanium detector arrays will also be introduced in this study.

hep-ex↗

arXiv2019

Spatially Resolved X-ray Spectroscopy of Kepler's Supernova Remnant: Distinct Properties of the Circumstellar Medium and the Ejecta

Kepler's supernova remnant (SNR) is believed to result from a Type Ia supernova, but be interacting with dense circumstellar material (CSM), which makes its progenitor system a mystery. Using the Chandra ACIS-S 741 ks effective exposure data and an advanced adaptive binning algorithm, we analyse the spectra from tessellated regions in Kepler's SNR. For the first time, we map out the detailed spatial distributions of emission measure (EM), electron temperature, ionization parameter, and metal abundances for both the low- and high-temperature plasma components. The low-temperature plasma diverges into two branches in the temperature v.s. ionization parameter diagram, which appear to be spatially associated with the warm CSM dusts and the Si- and S-rich ejecta, respectively. We construct the probability distribution functions of abundance ratios of O and Mg to L-shell emitting Fe ([O]/[Fe]$_{\rm L}$ and [Mg]/[Fe]$_{\rm L}$), and fit them with double Gaussians. Thereby, we distinguish the CSM from the ejecta: the CSM is characterized by [O]/[Fe]$_{\rm L}$ $= 0.77^{+0.30}_{-0.23}$ and [Mg]/[Fe]$_{\rm L}$ $= 1.11^{+0.46}_{-0.32}$, while the ejecta by [O]/[Fe]$_{\rm L}$ $= 0.31^{+0.17}_{-0.10}$ and [Mg]/[Fe]$_{\rm L}$ $= 0.38^{+0.36}_{-0.19}$. We estimate the total hydrogen mass of the shocked CSM as $\sim 1.4 M_\odot$ and the EM-weighted mean [Mg]/[O] $= 1.14 \pm 0.49$, which can be reproduced with an asymptotic giant branch donor star with initial mass of $\sim 4 M_\odot$. The abundance ratios from the shocked ejecta are well compatible with the predicted results from spherical delayed-detonation models for Type Ia supernovae. We also find that the two `ears' of the remnant are dominated by Si- and S-rich ejecta, thus favoring a pre-explosion jets scenario.

astro-ph.HE↗

arXiv2019

On-chip transverse-mode entangled photon pair source

Integrated entangled photon pair source is an essential resource for both fundamental investigations and practical applications of quantum information science. Currently there have been several types of entanglement, among which the transverse-mode entanglement is becoming attractive because of its unique advantages. Here, we report an on-chip transverse-mode entangled photon pair source via the spontaneous four-wave mixing processes in a multimode silicon waveguide. Transverse-mode photon pairs are verified over multiple frequency channels within a bandwidth of $\sim$2~THz, and a maximally entangled Bell state is also produced with a net fidelity of $0.96\pm0.01$. Our entangled photon pair source is the key element for quantum photonics based on transverse-mode, and also has the possibility to extend to higher-dimensional Hilbert space. Furthermore, the transverse-mode entanglement can be converted coherently to path and polarization entanglement, which paves the way to realizing highly complex quantum photonic circuits with multiple degrees of freedom.

quant-ph↗

arXiv2019

On determinant expansions for Hankel operators

Let $w$ be a semiclassical weight which is generic in Magnus's sense, and $(p_n)_{n=0}^\infty$ the corresponding sequence of orthogonal polynomials. The paper expresses the Christoffel--Darboux kernel as a sum of products of Hankel integral operators. For $ψ\in L^\infty (i{\mathbb R})$, let $W(ψ)$ be the Wiener-Hopf operator with symbol $ψ$. The paper gives sufficient conditions on $ψ$ such that $1/\det W(ψ)W(ψ^{-1})=\det (I-Γ_{ϕ_1}Γ_{ϕ_2})$ where $Γ_{ϕ_1}$ and $Γ_{ϕ_2}$ are Hankel operators that are Hilbert--Schmidt. For certain $ψ$, Barnes's integral leads to an expansion of this determinant in terms of the generalised hypergeometric ${}_nF_m$. These results extend those of Basor and Chen [2], who obtained ${}_4F_3$ likewise. The paper includes examples where the Wiener--Hopf factors are found explicitly.

math.FA↗

arXiv2019

Painlevé V, Painlevé XXXIV and the Degenerate Laguerre Unitary Ensemble

In this paper, we study the Hankel determinant associated with the degenerate Laguerre unitary ensemble. This problem originates from the largest or smallest eigenvalue distribution of the degenerate Laguerre unitary ensemble. We derive the ladder operators and its compatibility condition with respect to a general perturbed weight. By applying the ladder operators to our problem, we obtain two auxiliary quantities $R_n(t)$ and $r_n(t)$ and show that they satisfy the coupled Riccati equations, from which we find that $R_n(t)$ satisfies the Painlevé V equation. Furthermore, we prove that $σ_{n}(t)$, a quantity related to the logarithmic derivative of the Hankel determinant, satisfies both the continuous and discrete Jimbo-Miwa-Okamoto $σ$-form of the Painlevé V. In the end, by using Dyson's Coulomb fluid approach, we consider the large $n$ asymptotic behavior of our problem at the soft edge, which gives rise to the Painlevé XXXIV equation.

math-ph↗

arXiv2018

Quantum sensing of local magnetic field texture in strongly correlated electron systems under extreme conditions

An important feature of strong correlated electron systems is the tunability between interesting ground states such as unconventional superconductivity and exotic magnetism. Pressure is a clean, continuous and systematic tuning parameter. However, due to the restricted accessibility introduced by high-pressure devices, compatible magnetic field sensors with sufficient sensitivity are rare. This greatly limits the detections and detailed studies of pressure-induced phenomena. Here, we utilize nitrogen vacancy (NV) centers in diamond as a powerful, spatially-resolved vector field sensor for material research under pressure at cryogenic temperatures. Using a single crystal of BaFe2(As0:59P0:41)2 as an example, we extract the superconducting transition temperature (Tc), the local magnetic field profile in the Meissner state and the critical fields (Hc1 and Hc2). The method developed in this work will become a unique tool for tuning, probing and understanding quantum many body systems.

cond-mat.mes-hall↗

arXiv2018

Observatory science with eXTP

In this White Paper we present the potential of the enhanced X-ray Timing and Polarimetry (eXTP) mission for studies related to Observatory Science targets. These include flaring stars, supernova remnants, accreting white dwarfs, low and high mass X-ray binaries, radio quiet and radio loud active galactic nuclei, tidal disruption events, and gamma-ray bursts. eXTP will be excellently suited to study one common aspect of these objects: their often transient nature. Developed by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Science, the eXTP mission is expected to be launched in the mid 2020s.

astro-ph.HE↗

arXiv2018

Powerful genome-wide design and robust statistical inference in two-sample summary-data Mendelian randomization

Two-sample summary-data Mendelian randomization (MR) has become a popular research design to estimate the causal effect of risk exposures. With the sample size of GWAS continuing to increase, it is now possible to utilize genetic instruments that are only weakly associated with the exposure. To maximize the statistical power of MR, we propose a genome-wide design where more than a thousand genetic instruments are used. For the statistical analysis, we use an empirical partially Bayes approach where instruments are weighted according to their strength, thus weak instruments bring less variation to the estimator. The estimator is highly efficient with many weak genetic instruments and is robust to balanced and/or sparse pleiotropy. We apply our method to estimate the causal effect of body mass index (BMI) and major blood lipids on cardiovascular disease outcomes and obtain substantially shorter confidence intervals. Some new and statistically significant findings are: the estimated causal odds ratio of BMI on ischemic stroke is 1.19 (95% CI: 1.07--1.32, p-value < 0.001); the estimated causal odds ratio of high-density lipoprotein cholesterol (HDL-C) on coronary artery disease (CAD) is 0.78 (95% CI 0.73--0.84, p-value < 0.001). However, the estimated effect of HDL-C becomes substantially smaller and statistically non-significant when we only use the strong instruments. By employing a genome-wide design and robust statistical methods, the statistical power of MR studies can be greatly improved. Our empirical results suggest that, even though the relationship between HDL-C and CAD appears to be highly heterogeneous, it may be too soon to completely dismiss the HDL hypothesis.

stat.AP↗

arXiv2018

Student's t-Generative Adversarial Networks

Generative Adversarial Networks (GANs) have a great performance in image generation, but they need a large scale of data to train the entire framework, and often result in nonsensical results. We propose a new method referring to conditional GAN, which equipments the latent noise with mixture of Student's t-distribution with attention mechanism in addition to class information. Student's t-distribution has long tails that can provide more diversity to the latent noise. Meanwhile, the discriminator in our model implements two tasks simultaneously, judging whether the images come from the true data distribution, and identifying the class of each generated images. The parameters of the mixture model can be learned along with those of GANs. Moreover, we mathematically prove that any multivariate Student's t-distribution can be obtained by a linear transformation of a normal multivariate Student's t-distribution. Experiments comparing the proposed method with typical GAN, DeliGAN and DCGAN indicate that, our method has a great performance on generating diverse and legible objects with limited data.

cs.LG↗

arXiv2018

Structure Learning of Deep Networks via DNA Computing Algorithm

Convolutional Neural Network (CNN) has gained state-of-the-art results in many pattern recognition and computer vision tasks. However, most of the CNN structures are manually designed by experienced researchers. Therefore, auto- matically building high performance networks becomes an important problem. In this paper, we introduce the idea of using DNA computing algorithm to automatically learn high-performance architectures. In DNA computing algorithm, we use short DNA strands to represent layers and long DNA strands to represent overall networks. We found that most of the learned models perform similarly, and only those performing worse during the first runs of training will perform worse finally than others. The indicates that: 1) Using DNA computing algorithm to learn deep architectures is feasible; 2) Local minima should not be a problem of deep networks; 3) We can use early stop to kill the models with the bad performance just after several runs of training. In our experiments, an accuracy 99.73% was obtained on the MNIST data set and an accuracy 95.10% was obtained on the CIFAR-10 data set.

cs.NE↗

arXiv2018

Searching for GeV gamma-ray emission from the bulge of M31

The three major large-scale, diffuse $γ$-ray structures of the Milky Way are the Galactic disk, a bulge-like GeV excess towards the Galactic center, and the Fermi bubble. Whether such structures can also be present in other normal galaxies remains an open question. M31, as the nearest massive normal galaxy, holds promise for spatially-resolving the $γ$-ray emission. Based on more than 8 years of Fermi-LAT observations, we use (1) disk, (2) bulge, and (3) disk-plus-bulge templates to model the spatial distribution of the $γ$-ray emission from M31. Among these, the disk-plus-bulge template delivers the best-fit, in which the bulge component has a TS value 25.7 and a photon-index of $2.57\pm0.17$, providing strong evidence for a centrally-concentrated gamma-ray emission from M31, that is analogous to the Galactic center excess. The total 0.2-300 GeV gamma-ray luminosity from this bulge component is $(1.16\pm0.14)\times10^{38} erg s^{-1}$, which would require $\sim1.5\times10^5$ millisecond pulsars, if they were the dominant source. We also search for a Fermi bubble-like structure in M31 using the full dataset (pass8), but no significant evidence is found. In addition, a likelihood analysis using only photons with the most accurate reconstructed direction (i.e., PSF3-only data) reveals a 4.8 $σ$ point-like source located at $\sim$ 10kpc to the northwest of the M31 disk, with a luminosity of $(0.97\pm0.27)\times10^{38} erg s^{-1}$ and a photon-index of $2.31\pm0.18$. Lacking of a counterpart on the southeast side of the disk, the relation between this point-like source and a bubble-like structure remains elusive.

astro-ph.HE↗

arXiv2018

Quantum plasmonic N00N state in a silver nanowire and its use for quantum sensing

The control of quantum states of light at the nanoscale has become possible in recent years with the use of plasmonics. Here, many types of nanophotonic devices and applications have been suggested that take advantage of quantum optical effects, despite the inherent presence of loss. A key example is quantum plasmonic sensing, which provides sensitivity beyond the classical limit using entangled N00N states and their generalizations in a compact system operating below the diffraction limit. In this work, we experimentally demonstrate the excitation and propagation of a two-plasmon entangled N00N state (N=2) in a silver nanowire, and assess the performance of our system for carrying out quantum sensing. Polarization entangled photon pairs are converted into plasmons in the silver nanowire, which propagate over a distance of 5 um and re-convert back into photons. A full analysis of the plasmonic system finds that the high-quality entanglement is preserved throughout. We measure the characteristic super-resolution phase oscillations of the entangled state via coincidence measurements. We also identify various sources of loss in our setup and show how they can be mitigated, in principle, in order to reach super-sensitivity that goes beyond the classical sensing limit. Our results show that polarization entanglement can be preserved in a plasmonic nanowire and that sensing with a quantum advantage is possible with moderate loss present.

physics.optics↗

arXiv2018

Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage

Calibration data are often obtained by observing several well-understood objects simultaneously with multiple instruments, such as satellites for measuring astronomical sources. Analyzing such data and obtaining proper concordance among the instruments is challenging when the physical source models are not well understood, when there are uncertainties in "known" physical quantities, or when data quality varies in ways that cannot be fully quantified. Furthermore, the number of model parameters increases with both the number of instruments and the number of sources. Thus, concordance of the instruments requires careful modeling of the mean signals, the intrinsic source differences, and measurement errors. In this paper, we propose a log-Normal hierarchical model and a more general log-t model that respect the multiplicative nature of the mean signals via a half-variance adjustment, yet permit imperfections in the mean modeling to be absorbed by residual variances. We present analytical solutions in the form of power shrinkage in special cases and develop reliable MCMC algorithms for general cases. We apply our method to several data sets obtained with a variety of X-ray telescopes such as Chandra. We demonstrate that our method provides helpful and practical guidance for astrophysicists when adjusting for disagreements among instruments.

stat.AP↗

arXiv2018

Smallest Eigenvalue of Large Hankel Matrices at Critical Point: Comparing Conjecture With Parallelised Computation

We propose a novel parallel numerical algorithm for calculating the smallest eigenvalues of highly ill-conditioned matrices. It is based on the {\it LDLT} decomposition and involves finding a $k \times k$ sub-matrix of the inverse of the original $N \times N$ Hankel matrix $H_N^{-1}$ . The computation involves extremely high precision arithmetic, message passing interface, and shared memory parallelisation. We demonstrate that this approach achieves good scalability on a high performance computing cluster (HPCC) which constitute a major improvement of the earlier approaches. We use this method to study a family of Hankel matrices generated by the weight $w(x)={\rm e}^{-x^β},$ supported on $[0,\infty)$ and $β>0.$ Such weight generates Hankel determinant, a fundamental object in random matrix theory. In the situation where $β>1/2,$ the smallest eigenvalue tend to 0, exponentially fast as $N$ gets large. If $β<1/2,$ the situation where the classical moment problem is indeterminate, the smallest eigenvalue is bounded from below by a positive number for all $N$, including infinity. If $β=1/2,$ it is conjectured that the smallest eigenvalue tends to 0 algebraically, with a precise exponent. The algorithm run on the HPCC producing fantastic match between the theoretical value of $2/π$ and the numerical result.

math.NA↗

arXiv2018

Deep Inferential Spatial-Temporal Network for Forecasting Air Pollution Concentrations

Air pollution poses a serious threat to human health as well as economic development around the world. To meet the increasing demand for accurate predictions for air pollutions, we proposed a Deep Inferential Spatial-Temporal Network to deal with the complicated non-linear spatial and temporal correlations. We forecast three air pollutants (i.e., PM2.5, PM10 and O3) of monitoring stations over the next 48 hours, using a hybrid deep learning model consists of inferential predictor (inference for regions without air pollution readings), spatial predictor (capturing spatial correlations using CNN) and temporal predictor (capturing temporal relationship using sequence-to-sequence model with simplified attention mechanism). Our proposed model considers historical air pollution records and historical meteorological data. We evaluate our model on a large-scale dataset containing air pollution records of 35 monitoring stations and grid meteorological data in Beijing, China. Our model outperforms other state-of-art methods in terms of SMAPE and RMSE.

cs.LG↗

arXiv2018

Molecular gas toward supernova remnant Cassiopeia A

We mapped 12CO J=1-0, 12CO J=2-1, 13CO J=1-0, and 13CO J=2-1 lines toward supernova remnant (SNR) Cassiopeia A with the IRAM 30m telescope. The molecular clouds (MCs) along the line of sight of Cas A do not show optically thin, shock-broadened 12CO lines ($ΔV \le 7$ km s$^{-1}$ toward Cas A), or high-temperature features from shock heating ($T_k \le 22$ K toward Cas A). Therefore, we suggest that there is no physical evidence to support that the SNR is impacting the molecular gas. All the detected MCs are likely in front of Cas A, as implied by the HCO+ absorption line detected in the same velocity ranges. These MCs contribute H$_2$ column densities of $5\times 10^{21}$ cm$^{-2}$, $5\times 10^{21}$ cm$^{-2}$, and $2\times 10^{21}$ cm$^{-2}$ in the west, south, and center of the SNR, respectively. The 20 K warm gas at $V_{LSR}\sim -47$ km s$^{-1}$ is distributed along a large-scale molecular ridge in the south of Cas A. Part of the gas is projected onto Cas A, providing a foreground H$_2$ mass of $\sim 200 (d/3 kpc)^2$ Msun, consistent with the mass of cold dust (15--20 K; 2--4 Msun) found in front of the SNR. We suggest that the 20 K warm gas is heated by background cosmic rays with an ionization rate of $ζ({\rm H_2})\sim 2\times 10^{-16}$ s$^{-1}$. The cosmic rays or X-ray emission from Cas A are excluded as the heating sources of the clouds.

astro-ph.HE↗