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Bin Chen

Publications and source records attributed to Bin Chen.

At least 487 records · Page 27Linked to original sources
arXiv2021

Efficient Sampling Policy for Selecting a Good Enough Subset

The note studies the problem of selecting a good enough subset out of a finite number of alternatives under a fixed simulation budget. Our work aims to maximize the posterior probability of correctly selecting a good subset. We formulate the dynamic sampling decision as a stochastic control problem in a Bayesian setting. In an approximate dynamic programming paradigm, we propose a sequential sampling policy based on value function approximation. We analyze the asymptotic property of the proposed sampling policy. Numerical experiments demonstrate the efficiency of the proposed procedure.

math.OC↗
arXiv2021

The Origin of Underdense Plasma Downflows Associated with Magnetic Reconnection in Solar Flares

Magnetic reconnection is a universal process that powers explosive energy release events such as solar flares, geomagnetic substorms, and some astrophysical jets. A characteristic feature of magnetic reconnection is the production of fast reconnection outflow jets near the plasma Alfvén speeds. In eruptive solar flares, dark, finger-shaped plasma downflows moving toward the flare arcade have been commonly regarded as the principal observational evidence for such reconnection-driven outflows. However, they often show a speed much slower than that expected in reconnection theories, challenging the reconnection-driven energy release scenario in standard flare models. Here, we present a three-dimensional magnetohydrodynamics model of solar flares. By comparing the model-predictions with the observed plasma downflow features, we conclude that these dark downflows are self-organized structures formed in a turbulent interface region below the flare termination shock where the outflows meet the flare arcade, a phenomenon analogous to the formation of similar structures in supernova remnants. This interface region hosts a myriad of turbulent flows, electron currents, and shocks, crucial for flare energy release and particle acceleration.

astro-ph.SR↗
arXiv2021

QED Effects on Kerr Black Hole Shadows immersed in uniform magnetic fields

In this work, taking the QED effect into account, we investigate the shadows of the Kerr black holes immersed in uniform magnetic fields through the numerical backward ray-tracing method. We introduce a dimensionless parameter $Λ$ to characterize the strength of magnetic fields and studied the influence of magnetic fields on the Kerr black hole shadows for various spins of the black holes and inclination angles of the observers. In particular, we find that the photon "hairs" appear near the left edge of the shadow in the presence of magnetic fields. The photon hairs may be served as a signature of the magnetic fields. We notice that the photon hairs become more evident when the strength of magnetic fields or the spin of the black hole becomes larger. In addition, we study the deformation of the shadows by bringing in quantitative parameters that can describe the position and shape of the shadow edge.

gr-qc↗
arXiv2021

Layer-dependent pressure effect on electronic structures of 2D black phosphorus

Through infrared spectroscopy, we systematically study the pressure effect on electronic structures of few-layer black phosphorus (BP) with layer number ranging from 2 to 13. We reveal that the pressure-induced shift of optical transitions exhibits strong layer-dependence. In sharp contrast to the bulk counterpart which undergoes a semiconductor to semimetal transition under ~1.8 GPa, the bandgap of 2 L increases with increasing pressure until beyond 2 GPa. Meanwhile, for a sample with a given layer number, the pressure-induced shift also differs for transitions with different indices. Through the tight-binding model in conjunction with a Morse potential for the interlayer coupling, this layer- and transition-index-dependent pressure effect can be fully accounted. Our study paves a way for versatile van der Waals engineering of two-dimensional BP.

cond-mat.mes-hall↗
arXiv2021

Low-Complexity Geometrical Shaping for 4D Modulation Formats via Amplitude Coding

Signal shaping is vital to approach Shannon's capacity, yet it is challenging to implement at very high speeds. For example, probabilistic shaping often requires arithmetic coding to realize the target distribution. Geometric shaping requires look-up tables to store the constellation points. In this paper, we propose a four-dimensional amplitude coding (4D-AC) geometrical shaper architecture. The proposed architecture can generate in real time geometrically shaped 4D formats via simple logic circuit operations and two conventional quadrature amplitude modulation (QAM) modulators. This paper describes the 4D-AC used in generating approximated versions of two recently proposed 4D orthant symmetric modulation formats with spectral efficiencies of 6 bit/4D-sym and 7 bit/4D-sym, respectively. Numerical results show losses below 0.05 dB when compared against the baseline formats.

eess.SP↗
arXiv2021

Memory-Augmented Deep Unfolding Network for Compressive Sensing

Mapping a truncated optimization method into a deep neural network, deep unfolding network (DUN) has attracted growing attention in compressive sensing (CS) due to its good interpretability and high performance. Each stage in DUNs corresponds to one iteration in optimization. By understanding DUNs from the perspective of the human brain's memory processing, we find there exists two issues in existing DUNs. One is the information between every two adjacent stages, which can be regarded as short-term memory, is usually lost seriously. The other is no explicit mechanism to ensure that the previous stages affect the current stage, which means memory is easily forgotten. To solve these issues, in this paper, a novel DUN with persistent memory for CS is proposed, dubbed Memory-Augmented Deep Unfolding Network (MADUN). We design a memory-augmented proximal mapping module (MAPMM) by combining two types of memory augmentation mechanisms, namely High-throughput Short-term Memory (HSM) and Cross-stage Long-term Memory (CLM). HSM is exploited to allow DUNs to transmit multi-channel short-term memory, which greatly reduces information loss between adjacent stages. CLM is utilized to develop the dependency of deep information across cascading stages, which greatly enhances network representation capability. Extensive CS experiments on natural and MR images show that with the strong ability to maintain and balance information our MADUN outperforms existing state-of-the-art methods by a large margin. The source code is available at https://github.com/jianzhangcs/MADUN/.

cs.CV↗
arXiv2021

Learning a self-supervised tone mapping operator via feature contrast masking loss

High Dynamic Range (HDR) content is becoming ubiquitous due to the rapid development of capture technologies. Nevertheless, the dynamic range of common display devices is still limited, therefore tone mapping (TM) remains a key challenge for image visualization. Recent work has demonstrated that neural networks can achieve remarkable performance in this task when compared to traditional methods, however, the quality of the results of these learning-based methods is limited by the training data. Most existing works use as training set a curated selection of best-performing results from existing traditional tone mapping operators (often guided by a quality metric), therefore, the quality of newly generated results is fundamentally limited by the performance of such operators. This quality might be even further limited by the pool of HDR content that is used for training. In this work we propose a learning-based self-supervised tone mapping operator that is trained at test time specifically for each HDR image and does not need any data labeling. The key novelty of our approach is a carefully designed loss function built upon fundamental knowledge on contrast perception that allows for directly comparing the content in the HDR and tone mapped images. We achieve this goal by reformulating classic VGG feature maps into feature contrast maps that normalize local feature differences by their average magnitude in a local neighborhood, allowing our loss to account for contrast masking effects. We perform extensive ablation studies and exploration of parameters and demonstrate that our solution outperforms existing approaches with a single set of fixed parameters, as confirmed by both objective and subjective metrics.

cs.CV↗
arXiv2021

Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare

Magnetic flux ropes are the centerpiece of solar eruptions. Direct measurements for the magnetic field of flux ropes are crucial for understanding the triggering and energy release processes, yet they remain heretofore elusive. Here we report microwave imaging spectroscopy observations of an M1.4-class solar flare that occurred on 2017 September 6, using data obtained by the Expanded Owens Valley Solar Array. This flare event is associated with a partial eruption of a twisted filament observed in Hα by the Goode Solar Telescope at the Big Bear Solar Observatory. The extreme ultraviolet (EUV) and X-ray signatures of the event are generally consistent with the standard scenario of eruptive flares, with the presence of double flare ribbons connected by a bright flare arcade. Intriguingly, this partial eruption event features a microwave counterpart, whose spatial and temporal evolution closely follow the filament seen in Hα and EUV. The spectral properties of the microwave source are consistent with nonthermal gyrosynchrotron radiation. Using spatially resolved microwave spectral analysis, we derive the magnetic field strength along the filament spine, which ranges from 600-1400 Gauss from its apex to the legs. The results agree well with the non-linear force-free magnetic model extrapolated from the pre-flare photospheric magnetogram. We conclude that the microwave counterpart of the erupting filament is likely due to flare-accelerated electrons injected into the filament-hosting magnetic flux rope cavity following the newly reconnected magnetic field lines.

astro-ph.SR↗
arXiv2021

Multiple electron acceleration instances during a series of solar microflares observed simultaneously at X-rays and microwaves

Even small solar flares can display a surprising level of complexity regarding their morphology and temporal evolution. Many of their properties, such as energy release and electron acceleration can be studied using highly complementary observations at X-ray and radio wavelengths. We present X-ray observations from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and radio observations from the Karl G. Jansky Very Large Array (VLA) of a series of GOES A3.4 to B1.6 class flares observed on 2013 April 23. The flares, as seen in X-ray and extreme ultraviolet (EUV), originated from multiple locations within active region NOAA 11726. A veritable zoo of different radio emissions between 1 GHz and 2 GHz was observed co-temporally with the X-ray flares. In addition to broad-band continuum emission, broad-band short-lived bursts and narrow-band spikes, indicative of accelerated electrons, were observed. However, these sources were located up to 150 arcsec away from the flaring X-ray sources but only some of these emissions could be explained as signatures of electrons that were accelerated near the main flare site. For other sources, no obvious magnetic connection to the main flare site could be found. These emissions likely originate from secondary acceleration sites triggered by the flare, but may be due to reconnection and acceleration completely unrelated to the co-temporally observed flare. Thanks to the extremely high sensitivity of the VLA, not achieved with current X-ray instrumentation, it is shown that particle acceleration happens frequently and at multiple locations within a flaring active region.

astro-ph.SR↗
arXiv2021

$λ$-deformed $AdS_5\times S^5$ superstring from 4D Chern-Simons theory

We present the construction of the $λ$-deformation of $AdS_5\times S^5$ superstring from the four dimensional Chern-Simons-type gauge theory. The procedure is applicable to all the semi-symmetric coset models and generalizes the previous construction of $λ$-deformation of the symmetric coset models.

hep-th↗
arXiv2021

Correspondence of eikonal quasinormal modes and unstable fundamental photon orbits for Kerr-Newman black hole

In this work, we study the relation of the eikonal quasinormal modes (EQNMs) and the unstable fundamental photon orbits (UFPOs) in the Kerr-Newman spacetime. We find that in the eikonal limit the gravitational and electromagnetic perturbations of the Kerr-Newman black hole are naturally decoupled, and a single one-dimensional Schrödinger-like equation encoding the QNM spectrum can be derived. We then show that the decoupled Teukolsky master equation and the Klein-Gordon equation for the massless scalar field in the Kerr-Newman spacetime are of the same form in the eikonal limit. As a direct consequence, taking into account of the boundary conditions for EQNMs we show an exact correspondence between EQNMs and UFPOs, that is, EQNM/UFPO correspondence. More precisely, similar to the Kerr case, the real part of EQNM's frequency is a linear combination of the precessional and (polar) orbital frequencies, while the imaginary part of the frequency is proportional to the Lyapunov exponent of the UFPO.

gr-qc↗
arXiv2021

Unbiased IoU for Spherical Image Object Detection

As one of the most fundamental and challenging problems in computer vision, object detection tries to locate object instances and find their categories in natural images. The most important step in the evaluation of object detection algorithm is calculating the intersection-over-union (IoU) between the predicted bounding box and the ground truth one. Although this procedure is well-defined and solved for planar images, it is not easy for spherical image object detection. Existing methods either compute the IoUs based on biased bounding box representations or make excessive approximations, thus would give incorrect results. In this paper, we first identify that spherical rectangles are unbiased bounding boxes for objects in spherical images, and then propose an analytical method for IoU calculation without any approximations. Based on the unbiased representation and calculation, we also present an anchor free object detection algorithm for spherical images. The experiments on two spherical object detection datasets show that the proposed method can achieve better performance than existing methods.

cs.CV↗
arXiv2021

COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

Recent deep network-based compressive sensing (CS) methods have achieved great success. However, most of them regard different sampling matrices as different independent tasks and need to train a specific model for each target sampling matrix. Such practices give rise to inefficiency in computing and suffer from poor generalization ability. In this paper, we propose a novel COntrollable Arbitrary-Sampling neTwork, dubbed COAST, to solve CS problems of arbitrary-sampling matrices (including unseen sampling matrices) with one single model. Under the optimization-inspired deep unfolding framework, our COAST exhibits good interpretability. In COAST, a random projection augmentation (RPA) strategy is proposed to promote the training diversity in the sampling space to enable arbitrary sampling, and a controllable proximal mapping module (CPMM) and a plug-and-play deblocking (PnP-D) strategy are further developed to dynamically modulate the network features and effectively eliminate the blocking artifacts, respectively. Extensive experiments on widely used benchmark datasets demonstrate that our proposed COAST is not only able to handle arbitrary sampling matrices with one single model but also to achieve state-of-the-art performance with fast speed. The source code is available on https://github.com/jianzhangcs/COAST.

cs.CV↗
arXiv2021

Note on the nonrelativistic $T\bar{T}$ deformation

In this paper, we present our study on the $T\bar{T}$-deformation of non-relativistic complex scalar field theory. We find the closed form of the deformed Lagrangian by using the perturbation and the method of characteristics. Furthermore we compute the exact energy spectrum of the deformed free theory by using the Brillouin-Wigner perturbation theory in an appropriate regularization scheme.

hep-th↗
arXiv2021

Deformed Integrable Models from Holomorphic Chern-Simons Theory

We study the approaches to two-dimensional integrable field theories via a six-dimensional(6D) holomorphic Chern-Simons theory defined on twistor space. Under symmetry reduction, it reduces to a four-dimensional Chern-Simons theory, while under solving along fibres it leads to four-dimensional(4D) integrable theory, the anti-self-dual Yang-Mills or its generalizations. From both four-dimensional theories, various two-dimensional integrable field theories can be obtained. In this work, we try to investigate several two-dimensional integrable deformations in this framework. We find that the $λ$-deformation, the rational $η$-deformation and the generalized $λ$-deformation can not be realized from 4D integrable model approach, even though they could be obtained from 4D Chern-Simons theory. The obstacle stems from the incompatibility between the symmetry reduction and the boundary conditions. Nevertheless, we show that a coupled theory of $λ$-deformation and the $η$-deformation in the trigonometric description could be obtained from the 6D theory in both ways, by considering the case that $(3,0)$-form in the 6D theory is allowed to have zeros.

hep-th↗
arXiv2021

On Parameter Optimization and Reach Enhancement for the Improved Soft-Aided Staircase Decoder

The so-called improved soft-aided bit-marking algorithm was recently proposed for staircase codes (SCCs) in the context of fiber optical communications. This algorithm is known as iSABM-SCC. With the help of channel soft information, the iSABM-SCC decoder marks bits via thresholds to deal with both miscorrections and failures of hard-decision (HD) decoding. In this paper, we study iSABM-SCC focusing on the parameter optimization of the algorithm and its performance analysis, in terms of the gap to the achievable information rates (AIRs) of HD codes and the fiber reach enhancement. We show in this paper that the marking thresholds and the number of modified component decodings heavily affect the performance of iSABM-SCC, and thus, they need to be carefully optimized. By replacing standard decoding with the optimized iSABM-SCC decoding, the gap to the AIRs of HD codes can be reduced to 0.26-1.02 dB for code rates of 0.74-0.87 in the additive white Gaussian noise channel with 8-ary pulse amplitude modulation. The obtained reach increase is up to 22% for data rates between 401 Gbps and 468 Gbps in an optical fiber channel.

cs.IT↗