arXiv subjects

Yang Chen

Publications and source records attributed to Yang Chen.

At least 469 records · Page 26Linked to original sources

arXiv2022

GeV Gamma-ray Emission and Molecular Clouds towards Supernova Remnant G35.6$-$0.4 and the TeV Source HESS J1858+020

It is difficult to distinguish hadronic process from the leptonic one in $γ$-ray observation, which is however crucial in revealing the origin of cosmic rays. As an endeavor in the regard, we focus in this work on the complex $γ$-ray emitting region, which partially overlaps with the unidentified TeV source HESS~J1858+020 and includes supernova remnant (SNR) G35.6$-$0.4 and HII region G35.6$-$0.5. We reanalyze CO-line, HI, and Fermi-LAT GeV $γ$-ray emission data of this region. The analysis of the molecular and HI data suggests that SNR G35.6$-$0.4 and HII region G35.6$-$0.5 are located at different distances. The analysis the GeV $γ$-rays shows that GeV emission arises from two point sources: one (SrcA) coincident with the SNR, and the other (SrcB) coincident with both HESS J1858+020 and HII region G35.6$-$0.5. The GeV emission of SrcA can be explained by the hadronic process in the SNR-MC association scenario. The GeV-band spectrum of SrcB and the TeV-band spectrum of HESS J1858+020 can be smoothly connected by a power-law function, with an index of $\sim$2.2. The connected spectrum is well explained with a hadronic emission, with the cutoff energy of protons above 1 PeV. It thus indicates that there is a potential PeVatron in the HII region and should be further verified with ultra-high energy observations with, e.g., LHAASO.

astro-ph.HE↗

arXiv2022

Optical vortex Brillouin laser

Optical vortices, which have been extensively studied over the last decades, offer an additional degree of freedom useful in many applications, such as optical tweezers and quantum control. Stimulated Brillouin scattering, providing a narrow linewidth and a strong nonlinear response, has been used to realise quasi-continuous wave (CW) lasers. Here, we report stable oscillation of optical vortices and acoustic modes in a Brillouin laser based on chiral photonic crystal fibre, which robustly supports helical Bloch modes (HBMs) that carry circularly-polarized optical vortex and display circular birefringence. We implement a narrow-linewidth Brillouin fibre laser that stably emits 1st- and 2nd-order vortex-carrying HBMs. Angular momentum conservation selection rules dictate that pump and backward Brillouin signals have opposite topological charge and spin. Additionally, we show that when the chiral PCF is placed within a laser ring cavity, the linewidth-narrowing associated with lasing permits the peak of the Brillouin gain that corresponds to acoustic mode to be measured with resolution of 10 kHz and accuracy of 520 kHz. The results pave the way to a new generation of vortex-carrying SBS systems with applications in quantum information processing, vortex-carrying nonreciprocal systems.

physics.optics↗

arXiv2022

WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma (LUAD) is the most common subtype. Exploiting the potential value of the histopathology images can promote precision medicine in oncology. Tissue segmentation is the basic upstream task of histopathology image analysis. Existing deep learning models have achieved superior segmentation performance but require sufficient pixel-level annotations, which is time-consuming and expensive. To enrich the label resources of LUAD and to alleviate the annotation efforts, we organize this challenge WSSS4LUAD to call for the outstanding weakly-supervised semantic segmentation (WSSS) techniques for histopathology images of LUAD. Participants have to design the algorithm to segment tumor epithelial, tumor-associated stroma and normal tissue with only patch-level labels. This challenge includes 10,091 patch-level annotations (the training set) and over 130 million labeled pixels (the validation and test sets), from 87 WSIs (67 from GDPH, 20 from TCGA). All the labels were generated by a pathologist-in-the-loop pipeline with the help of AI models and checked by the label review board. Among 532 registrations, 28 teams submitted the results in the test phase with over 1,000 submissions. Finally, the first place team achieved mIoU of 0.8413 (tumor: 0.8389, stroma: 0.7931, normal: 0.8919). According to the technical reports of the top-tier teams, CAM is still the most popular approach in WSSS. Cutmix data augmentation has been widely adopted to generate more reliable samples. With the success of this challenge, we believe that WSSS approaches with patch-level annotations can be a complement to the traditional pixel annotations while reducing the annotation efforts. The entire dataset has been released to encourage more researches on computational pathology in LUAD and more novel WSSS techniques.

eess.IV↗

arXiv2022

Geometric Filterless Photodetectors for Mid-infrared Spin Light

Free-space circularly polarized light (CPL) detection, requiring polarizers and waveplates, has been well established, while such spatial degree of freedom is unfortunately absent in integrated on-chip optoelectronics. So far, those reported filterless CPL photodetectors suffer from the intrinsic small discrimination ratio, vulnerability to the non-CPL field components, and low responsivity. Here, we report a distinct paradigm of geometric photodetectors in mid-infrared exhibiting colossal discrimination ratio, close-to-perfect CPL-specific response, a zero-bias responsivity of 392 V/W at room temperature, and a detectivity of ellipticity down to 0.03$^o$ Hz$^{-1/2}$. Our approach employs plasmonic nanostructures array with judiciously designed symmetry, assisted by graphene ribbons to electrically read their near-field optical information. This geometry-empowered recipe for infrared photodetectors provides a robust, direct, strict, and high-quality solution to on-chip filterless CPL detection and unlocks new opportunities for integrated functional optoelectronic devices.

physics.optics↗

arXiv2022

Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data

We consider the flare prediction problem that distinguishes flare-imminent active regions that produce an M- or X-class flare in the future 24 hours, from quiet active regions that do not produce any flare within $\pm 24$ hours. Using line-of-sight magnetograms and parameters of active regions in two data products covering Solar Cycle 23 and 24, we train and evaluate two deep learning algorithms -- CNN and LSTM -- and their stacking ensembles. The decisions of CNN are explained using visual attribution methods. We have the following three main findings. (1) LSTM trained on data from two solar cycles achieves significantly higher True Skill Scores (TSS) than that trained on data from a single solar cycle with a confidence level of at least 0.95. (2) On data from Solar Cycle 23, a stacking ensemble that combines predictions from LSTM and CNN using the TSS criterion achieves significantly higher TSS than the "select-best" strategy with a confidence level of at least 0.95. (3) A visual attribution method called Integrated Gradients is able to attribute the CNN's predictions of flares to the emerging magnetic flux in the active region. It also reveals a limitation of CNN as a flare prediction method using line-of-sight magnetograms: it treats the polarity artifact of line-of-sight magnetograms as positive evidence of flares.

astro-ph.SR↗

arXiv2022

A Possible Gamma-Ray Enhancement Event in Tycho's Supernova Remnant

We report a possible $γ$-ray enhancement event detected from Tycho's supernova remnant (SNR), the outcome of a type Ia supernova explosion that occurred in year 1572. The event lasted for 1.5 years and showed a factor of 3.6 flux increase mainly in the energy range of 4--100 GeV, while notably accompanied with two 478\,GeV photons. Several young SNRs (including Tycho's SNR) were previously found to show peculiar X-ray structures with flux variations in one- or several-year timescales, such an event at $γ$-ray energies is for the first time seen. The year-long timescale of the event suggests a synchrotron radiation process, but the hard $γ$-ray emission requires extreme conditions of either ultra-high energies for the electrons upto $\sim$10 PeV (well above the cosmic-ray "knee" energy) or high inhomogeneity of the magnetic field in the SNR. This event in Tycho's SNR is likely analogous to the $γ$-ray flares observed in the Crab nebula, the comparably short timescales of them both requiring a synchrotron process, and similar magnetohydrodynamic processes such as magnetic reconnection would be at work as well in the SNR to accelerate particles to ultra-relativistic energies. The event, if confirmed, helps reveal the more complicated side of the physical processes that can occur in young SNRs.

astro-ph.HE↗

arXiv2022

Hankel Determinant and Orthogonal Polynomials for a Perturbed Gaussian Weight: from Finite $n$ to Large $n$ Asymptotics

We study the monic polynomials orthogonal with respect to a symmetric perturbed Gaussian weight $$ w(x;t):=\mathrm{e}^{-x^2}\left(1+t\: x^2\right)^λ,\qquad x\in \mathbb{R}, $$ where $t> 0,\;λ\in \mathbb{R}$. This weight is related to the single-user MIMO systems in information theory. It is shown that the recurrence coefficient $β_n(t)$ is related to a particular Painlevé V transcendent, and the sub-leading coefficient $\mathrm{p}(n,t)$ satisfies the Jimbo-Miwa-Okamoto $σ$-form of the Painlevé V equation. Furthermore, we derive the second-order difference equations satisfied by $β_n(t)$ and $\mathrm{p}(n,t)$, respectively. This enables us to obtain the large $n$ full asymptotic expansions for $β_n(t)$ and $\mathrm{p}(n,t)$ with the aid of Dyson's Coulomb fluid approach. We also consider the Hankel determinant $D_n(t)$, generated by the perturbed Gaussian weight. It is found that $H_n(t)$, a quantity allied to the logarithmic derivative of $D_n(t)$, can be expressed in terms of $β_n(t)$ and $\mathrm{p}(n,t)$. Based on this result, we obtain the large $n$ asymptotic expansion of $H_n(t)$ and then that of the Hankel determinant $D_n(t)$.

math-ph↗

arXiv2022

Analytical study on magnetic component of geodesic acoustic mode

The magnetic components of geodesic acoustic mode (GAM) are analytically investigated under the gyrokinetic framework with both the m=1 and m=2 harmonics are considered, where m is the poloidal mode number. With the quasi-neutrality condition and Ampere's law, the amplitudes of various poloidal magnetic components are derived. It is shown that both m=1 and m=2 magnetic components exist and are dominated by the cosine and sine components, respectively. In addition, it is found that the amplitudes of all magnetic components increase with respect to the ratio of plasma pressure to magnetic pressure \b{eta} and safety factor q. Most importantly, the amplitude of m=1 magnetic component is significantly enhanced due to the coupling of magnetic drift frequency with the first and second harmonics of the distribution functions, thus it can be comparable to that of m=2 magnetic component under certain conditions.

physics.plasm-ph↗

arXiv2022

foREST: A Tree-based Approach for Fuzzing RESTful APIs

Representational state transfer (REST) is a widely employed architecture by web applications and cloud. Users can invoke such services according to the specification of their application interfaces, namely RESTful APIs. Existing approaches for fuzzing RESTful APIs are generally based on classic API-dependency graphs. However, such dependencies are inefficient for REST services due to the explosion of dependencies among APIs. In this paper, we propose a novel tree-based approach that can better capture the essential dependencies and largely improve the efficiency of RESTful API fuzzing. In particular, the hierarchical information of the endpoints across multiple APIs enables us to construct an API tree, and the relationships of tree nodes can indicate the priority of resource dependencies, \textit{e.g.,} it's more likely that a node depends on its parent node rather than its offspring or siblings. In the evaluation part, we first confirm that such a tree-based approach is more efficient than traditional graph-based approaches. We then apply our tool to fuzz two real-world RESTful services and compare the performance with two state-of-the-art tools, EvoMaster and RESTler. Our results show that foREST can improve the code coverage in all experiments, ranging from 11.5\% to 82.5\%. Besides, our tool finds 11 new bugs previously unknown.

cs.SE↗

arXiv2022

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Since the science white paper of the Large High Altitude Air Shower Observatory (LHAASO) published on arXiv in 2019 [e-Print: 1905.02773 (astro-ph.HE)], LHAASO has completed the transition from a project to an operational gamma-ray astronomical observatory LHAASO is a new generation multi-component facility located in Daocheng, Sichuan province of China, at an altitude of 4410 meters. It aims at measuring with unprecedented sensitivity the spectrum, composition, and anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$~eV, and acting simultaneously as a wide aperture (one stereoradiant) continuously operating gamma-ray telescope in the energy range between 10$^{11}$ and $10^{15}$~eV with the designed sensitivity of 1.3\% of the Crab Unit (CU) above 100 TeV. LHAASO's capability of measuring simultaneously different shower components (electrons, muons, and Cherenkov/fluorescence light), will allow it to investigate the origin, acceleration, and propagation of CR through measurement of the energy spectrum, elemental composition, and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO will play a key role in CR physics and gamma-ray astronomy for a general and comprehensive exploration of the high energy universe and will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. The LHAASO Collaboration organized an editorial working group and finished all editorial work of this science book, to summarize the instrumental features and outline the prospects of scientific researches with the LHAASO experiment.

astro-ph.HE↗

arXiv2022

Individual-Level Inverse Reinforcement Learning for Mean Field Games

The recent mean field game (MFG) formalism has enabled the application of inverse reinforcement learning (IRL) methods in large-scale multi-agent systems, with the goal of inferring reward signals that can explain demonstrated behaviours of large populations. The existing IRL methods for MFGs are built upon reducing an MFG to a Markov decision process (MDP) defined on the collective behaviours and average rewards of the population. However, this paper reveals that the reduction from MFG to MDP holds only for the fully cooperative setting. This limitation invalidates existing IRL methods on MFGs with non-cooperative environments. To measure more general behaviours in large populations, we study the use of individual behaviours to infer ground-truth reward functions for MFGs. We propose Mean Field IRL (MFIRL), the first dedicated IRL framework for MFGs that can handle both cooperative and non-cooperative environments. Based on this theoretically justified framework, we develop a practical algorithm effective for MFGs with unknown dynamics. We evaluate MFIRL on both cooperative and mixed cooperative-competitive scenarios with many agents. Results demonstrate that MFIRL excels in reward recovery, sample efficiency and robustness in the face of changing dynamics.

cs.LG↗

arXiv2022

Proximal PanNet: A Model-Based Deep Network for Pansharpening

Recently, deep learning techniques have been extensively studied for pansharpening, which aims to generate a high resolution multispectral (HRMS) image by fusing a low resolution multispectral (LRMS) image with a high resolution panchromatic (PAN) image. However, existing deep learning-based pansharpening methods directly learn the mapping from LRMS and PAN to HRMS. These network architectures always lack sufficient interpretability, which limits further performance improvements. To alleviate this issue, we propose a novel deep network for pansharpening by combining the model-based methodology with the deep learning method. Firstly, we build an observation model for pansharpening using the convolutional sparse coding (CSC) technique and design a proximal gradient algorithm to solve this model. Secondly, we unfold the iterative algorithm into a deep network, dubbed as Proximal PanNet, by learning the proximal operators using convolutional neural networks. Finally, all the learnable modules can be automatically learned in an end-to-end manner. Experimental results on some benchmark datasets show that our network performs better than other advanced methods both quantitatively and qualitatively.

cs.CV↗

arXiv2022

Spatially decomposed $γ$-ray features surrounding SNR Kes 79 & PSR J1853+0056

There have been substantial improvements on Fermi Large Area Telescope (LAT) data and analysis tools since the last analysis on the mid-aged supernova remnant (SNR) Kes 79 (Auchettl et al. 2014). Recent multi-wavelength studies confirmed its interaction with molecular clouds. About $0.36\degr$ north from Kes 79, a powerful pulsar -- PSR J1853+0056 also deserves our attention. In this work, we analyse the 11.5-year Fermi-LAT data to investigate the $γ$-ray feature in/around this complex region. Our result shows a more significant detection ($\sim$34.8$σ$ in 0.1--50 GeV) for this region. With $\ge$5 GeV data, we detect two extended sources -- Src-N (the brighter one; radius $\approx0.31\degr$) concentrated at the north of the SNR while enclosing PSR J1853+0056, and Src-S (radius $\approx0.58\degr$) concentrated at the south of the SNR. Their spectra have distinct peak energies ($\sim$1.0 GeV for Src-N and $\lesssim$0.5 GeV for Src-S), suggesting different origins for them. In our hadronic model that includes the leaked cosmic-rays (CRs) from the shock-cloud collision, even with extreme values of parameters, SNR Kes 79 can by no means provide enough CRs reaching clouds at Src-N to explain the local GeV spectrum. We propose that the Src-N emission could be predominantly reproduced by a putative pulsar wind nebula (PWN) powered by PSR J1853+0056. On the other hand, our same hadronic model can reproduce a majority of the GeV emission at Src-S with typical values of parameters, while the three known pulsars inside Src-S release a total power that is too low to account for half of its $γ$-ray emission.

astro-ph.HE↗

arXiv2022

Laguerre Unitary Ensembles with Jump Discontinuities, PDEs and the Coupled Painlevé V System

We study the Hankel determinant generated by the Laguerre weight with jump discontinuities at $t_k, k=1,\cdots,m$. By employing the ladder operator approach to establish Riccati equations, we show that $σ_n(t_1,\cdots,t_m)$, the logarithmic derivative of the $n$-dimensional Hankel determinant, satisfies a generalization of the $σ$-from of Painlevé V equation. Through investigating the Riemann-Hilbert problem for the associated orthogonal polynomials and via Lax pair, we express $σ_n$ in terms of solutions of a coupled Painlevé V system. We also build relations between the auxiliary quantities introduced in the above two methods, which provides connections between the Riccati equations and Lax pair. In addition, when each $t_k$ tends to the hard edge of the spectrum and $n$ goes to $\infty$, the scaled $σ_n$ is shown to satisfy a generalized Painlevé III equation.

nlin.SI↗

arXiv2022

Photonics-Assisted Joint Communication-Radar System Based on a QPSK-Sliced Linearly Frequency-Modulated Signal

A photonics-assisted joint communication-radar system is proposed and experimentally demonstrated, by introducing a quadrature phase-shift keying (QPSK)-sliced linearly frequency-modulated (LFM) signal. An LFM signal is carrier-suppressed single-sideband modulated onto the optical carrier in one dual-parallel Mach-Zehnder modulator (DPMZM) of a dual-polarization dual-parallel Mach-Zehnder modulator (DPol-DPMZM). The other DPMZM of the DPol-DPMZM is biased as an IQ modulator to implement QPSK modulation on the optical carrier. The polarization orthogonal optical signals from the DPol-DPMZM are further combined and detected in a photodetector to generate the QPSK-sliced LFM signal, which is used to realize efficient data transmission and high-performance radar functions including ranging and imaging. An experiment is carried out. Radar range detection with an error of less than 4 cm, ISAR imaging with a resolution of 14.99 cm*3.25 cm, and communication with a data rate of 105.26 Mbit/s are successfully verified.

eess.SP↗

arXiv2022

Time-varying microwave photonic filter for arbitrary waveform signal-to-noise ratio improvement

A time-varying microwave photonic filter (TV-MPF) based on stimulated Brillouin scattering (SBS) is proposed and utilized to suppress the in-band noise of broadband arbitrary microwave waveforms, thereby improving the signal-to-noise ratio (SNR). The filter-controlling signal is designed according to the signal to be filtered and drives the TV-MPF so that the passband of the filter is always aligned with the frequencies of the signal to be filtered. By continuously tracking the signal spectral component, the TV-MPF only retains the spectral components of the signal and filters out the noise other than the spectral component of the signal at the current time, so as to improve the in-band SNR of the signal to be filtered. An experiment is performed. A variety of signals with different formats and in-band SNRs are used to test the noise suppression capability of the TV-MPF, and the waveform mean-square error is calculated to quantify the improvement of the signal, demonstrating the excellent adaptability of the proposed TV-MPF to different kinds of signals.

eess.SP↗

arXiv2022

Beam pointing stabilization of an acousto-optic modulator with thermal control

Diffraction beams generated by an acousto-optic modulator (AOM) are widely used in various optical experiments, some of which require high angular stability with the temporal modulation of optical power. Usually, it is difficult to realize both angular stability and high-power modulation in a passive setup without a servo system of radio-frequency compensation. Here, we present a method to suppress the angular drift and pointing noise only with the thermal management of the AOM crystal. We analyze the dependence of the angular drift on the refractive index variation, and find that the angular drift is very sensitivity to the temperature gradient which could induce the refractive index gradient inside the AOM crystal. It reminds us such angular drift could be significantly suppressed by carefully overlapping the zero temperature gradient area with the position of the acousto-optic interaction zone. We implement a water-cooling setup, and find that the angular drift of an AOM is reduced over 100 times during the thermal transient, and the angular noise is also suppressed to 1/3 of the non-cooled case. It should be emphasized that this thermal control method is a general to suppress the beam drift in both the diffraction and the perpendicular-to-diffraction directions. The refractive index thermal coefficient of tellurium dioxide crystal at 1064 nm determined by this angular drift-temperature model is 16$\times$10$^{-6}$ K$^{-1}$ consistent with previous studies. This thermal control technique provides potential applications for optical trapping and remote sensoring that demand for intensity ramps.

physics.ins-det↗

arXiv2022

Geometric Conditions for the Discrepant Posterior Phenomenon and Connections to Simpson's Paradox

The discrepant posterior phenomenon (DPP) is a counter-intuitive phenomenon that can frequently occur in a Bayesian analysis of multivariate parameters. It refers to the phenomenon that a parameter estimate based on a posterior is more extreme than both of those inferred based on either the prior or the likelihood alone. Inferential claims that exhibit DPP defy the common intuition that the posterior is a prior-data compromise, and the phenomenon can be surprisingly ubiquitous in well-behaved Bayesian models. In this paper we revisit this phenomenon and, using point estimation as an example, derive conditions under which the DPP occurs in Bayesian models with exponential quadratic likelihoods and conjugate multivariate Gaussian priors. The family of exponential quadratic likelihood models includes Gaussian models and those models with local asymptotic normality property. We provide an intuitive geometric interpretation of the phenomenon and show that there exists a nontrivial space of marginal directions such that the DPP occurs. We further relate the phenomenon to the Simpson's paradox and discover their deep-rooted connection that is associated with marginalization. We also draw connections with Bayesian computational algorithms when difficult geometry exists. Our discovery demonstrates that DPP is more prevalent than previously understood and anticipated. Theoretical results are complemented by numerical illustrations. Scenarios covered in this study have implications for parameterization, sensitivity analysis, and prior choice for Bayesian modeling.

math.ST↗