arXiv subjects

Yi Feng

Publications and source records attributed to Yi Feng.

At least 91 records · Page 5Linked to original sources

arXiv2024

The Variability of Persistent Radio Sources of Fast Radio Bursts

Over 700 bright millisecond-duration radio transients, known as Fast Radio Bursts (FRBs), have been identified to date. Nevertheless, the origin of FRBs remains unknown. The two repeating FRBs (FRB 20121102A and FRB 20190520B) have been verified to be associated with persistent radio sources (PRSs), making them the best candidates to study the nature of FRBs. Monitoring the variability in PRSs is essential for understanding their physical nature. We conducted 22 observations of the PRSs linked to FRB 20121102A and FRB 20190520B using the Karl G. Jansky Very Large Array (VLA), to study their variability. We have observed significant flux variability for the PRSs of FRB 20121102A and FRB 20190520B, with a confidence level exceeding 99.99%, based on the observations covering the longest timescale recorded to date. The observed variability of the two PRSs exhibits no significant difference in amplitude across both short and long timescales. We found that the radio-derived star formation rates of the two FRB hosts are significantly higher than those measured by the optical $H_α$ emissions, indicating that their host galaxies are highly obscured or most radio emissions are not from star formation processes. The observed timescale of PRS flux evolution constrained the magnetic field of FRB 20121102A with $B_\parallel\gtrsim1~{\rm mG}$ and FRB 20190520B with $B_\parallel\gtrsim0.1~{\rm mG}$.

astro-ph.HE↗

arXiv2024

Multi-frequency Electrical Impedance Tomography Reconstruction with Multi-Branch Attention Image Prior

Multi-frequency Electrical Impedance Tomography (mfEIT) is a promising biomedical imaging technique that estimates tissue conductivities across different frequencies. Current state-of-the-art (SOTA) algorithms, which rely on supervised learning and Multiple Measurement Vectors (MMV), require extensive training data, making them time-consuming, costly, and less practical for widespread applications. Moreover, the dependency on training data in supervised MMV methods can introduce erroneous conductivity contrasts across frequencies, posing significant concerns in biomedical applications. To address these challenges, we propose a novel unsupervised learning approach based on Multi-Branch Attention Image Prior (MAIP) for mfEIT reconstruction. Our method employs a carefully designed Multi-Branch Attention Network (MBA-Net) to represent multiple frequency-dependent conductivity images and simultaneously reconstructs mfEIT images by iteratively updating its parameters. By leveraging the implicit regularization capability of the MBA-Net, our algorithm can capture significant inter- and intra-frequency correlations, enabling robust mfEIT reconstruction without the need for training data. Through simulation and real-world experiments, our approach demonstrates performance comparable to, or better than, SOTA algorithms while exhibiting superior generalization capability. These results suggest that the MAIP-based method can be used to improve the reliability and applicability of mfEIT in various settings.

eess.IV↗

arXiv2024

An extremely active repeating fast radio burst source in a likely non-magneto-ionic environment

Fast radio bursts (FRBs) are bright radio bursts originating at cosmological distances. Only three repeating FRBs FRB 20121102A, FRB 20190520B and FRB 20201124A among $\sim$ 60 known repeating FRBs have circular polarization. We observed the FRB 20220912A with the Robert C. Byrd Green Bank Telescope (GBT) at L-band on 24 October 2022 and detected 128 bursts in 1.4 hours, corresponding to a burst rate of about 90 hr$^{-1}$, which is the highest yet for FRBs observed by the GBT. The average rotation measure (RM) was $-$0.4$\pm$0.3$\,$rad$\,$m$^{-2}$ with negligible intraday RM change, indicating a likely non-magneto-ionic environment. 61% bursts have linear polarization fraction greater than 90%. Approximately 56% of the bright bursts have circular polarization. A downward drift in frequency and polarization angle swings were found in our sample. The characterization of FRB 20220912A indicates that the circular polarization is unlikely to be caused by the magneto-ionic environment for at least some of the repeating FRB population.

astro-ph.HE↗

arXiv2024

Synthesis pathways to thin films of stable layered nitrides

Controlled synthesis of metastable materials away from equilibrium is of interest in materials chemistry. Thin film deposition methods with rapid condensation of vapor precursors can readily synthesize metastable phases, but often struggle to yield the thermodynamic ground state. Growing thermodynamically-stable structures using kinetically-limited synthesis methods in important for practical applications in electronics and energy conversion. Here, we reveal a synthesis pathway to thermodynamically-stable ordered layered ternary nitride materials, and discuss why disordered metastable intermediate phases tend to form. We show that starting from elemental vapor precursors leads to a 3D long-range disordered MgMoN2 thin film metastable intermediate structure, with a layered short-range order that has a low-energy transformation barrier to the layered 2D-like stable structure. This synthesis approach is extended to ScTaN2, MgWN2 and MgTa2N3, and may lead to the synthesis of other layered nitride thin films with unique semiconducting and quantum properties.

cond-mat.mtrl-sci↗

arXiv2024

X-ray hardening preceding the onset of SGR 1935+2154's radio pulsar phase

Magnetars are neutron stars with extremely strong magnetic fields, frequently powering high-energy activity in X-rays. Pulsed radio emission following some X-ray outbursts have been detected (\citealt{Camilo2006,camilo2007a}), albeit its physical origin is unclear. It has long been speculated that the origin of magnetars' radio signals is different from those from canonical pulsars, although convincing evidence is still lacking. Five months after magnetar SGR 1935+2154's X-ray outburst and its associated Fast Radio Burst (FRB) 20200428, a radio pulsar phase was discovered. Here we report the discovery of X-ray spectral hardening associated with the emergence of periodic radio pulsations from SGR 1935+2154 and a detailed analysis of the properties of the radio pulses. The observations suggest that radio emission originates from the outer magnetosphere of the magnetar, and the surface heating due to the bombardment of inward-going particles from the radio emission region is responsible for the observed X-ray spectral hardening.

astro-ph.HE↗

arXiv2024

An Efficient Convex-Hull Relaxation Based Algorithm for Multi-User Discrete Passive Beamforming

Intelligent reflecting surface (IRS) is an emerging technology to enhance spatial multiplexing in wireless networks. This letter considers the discrete passive beamforming design for IRS in order to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among multiple users in an IRS-assisted downlink network. The main design difficulty lies in the discrete phase-shift constraint. Differing from most existing works, this letter advocates a convex-hull relaxation of the discrete constraints which leads to a continuous reformulated problem equivalent to the original discrete problem. This letter further proposes an efficient alternating projection/proximal gradient descent and ascent algorithm for solving the reformulated problem. Simulation results show that the proposed algorithm outperforms the state-of-the-art methods significantly.

cs.IT↗

arXiv2024

Simple Combinatorial Construction of the $k^{o(1)}$-Lower Bound for Approximating the Parameterized $k$-Clique

In the parameterized $k$-clique problem, or $k$-Clique for short, we are given a graph $G$ and a parameter $k\ge 1$. The goal is to decide whether there exist $k$ vertices in $G$ that induce a complete subgraph (i.e., a $k$-clique). This problem plays a central role in the theory of parameterized intractability as one of the first W[1]-complete problems. Existing research has shown that even an FPT-approximation algorithm for $k$-Clique with arbitrary ratio does not exist, assuming the Gap-Exponential-Time Hypothesis (Gap-ETH) [Chalermsook et al., FOCS'17 and SICOMP]. However, whether this inapproximability result can be based on the standard assumption of $\mathrm{W} 1\ne \mathrm{FPT}$ remains unclear. The recent breakthrough of Bingkai Lin [STOC'21] and subsequent works by Karthik C.S. and Khot [CCC'22], and by Lin, Ren, Sun Wang [ICALP'22] give a technique that bypasses Gap-ETH, thus leading to the inapproximability ratio of $O(1)$ and $k^{o(1)}$ under $\mathrm{W}[1]$-hardness (the first two) and ETH (for the latter one). All the work along this line follows the framework developed by Lin, which starts from the $k$-vector-sum problem and requires some involved algebraic techniques. This paper presents an alternative framework for proving the W[1]-hardness of the $k^{o(1)}$-FPT-inapproximability of $k$-Clique. Using this framework, we obtain a gap-producing self-reduction of $k$-Clique without any intermediate algebraic problem. More precisely, we reduce from $(k,k-1)$-Gap Clique to $(q^k, q^{k-1})$-Gap Clique, for any function $q$ depending only on the parameter $k$, thus implying the $k^{o(1)}$-inapproximability result when $q$ is sufficiently large. Our proof is relatively simple and mostly combinatorial. At the core of our construction is a novel encoding of $k$-element subset stemming from the theory of "network coding" and a "Sidon set" representation of a graph.

cs.CC↗

arXiv2024

The neutron star mass, distance, and inclination from precision timing of the brilliant millisecond pulsar J0437$-$4715

The observation of neutron stars enables the otherwise impossible study of fundamental physical processes. The timing of binary radio pulsars is particularly powerful, as it enables precise characterization of their (three-dimensional) positions and orbits. PSR~J0437$-$4715 is an important millisecond pulsar for timing array experiments and is also a primary target for the Neutron Star Interior Composition Explorer (NICER). The main aim of the NICER mission is to constrain the neutron star equation of state by inferring the compactness ($M_p/R$) of the star. Direct measurements of the mass $M_p$ from pulsar timing therefore substantially improve constraints on the radius $R$ and the equation of state. Here we use observations spanning 26 years from Murriyang, the 64-m Parkes radio telescope, to improve the timing model for this pulsar. Among the new precise measurements are the pulsar mass $M_p=1.418\pm 0.044$ $M_{\odot}$, distance $D=156.96 \pm 0.11$ pc, and orbital inclination angle $i=137.506 \pm 0.016^\circ$, which can be used to inform the X-ray pulse profile models inferred from NICER observations. We demonstrate that these results are consistent between multiple data sets from the Parkes Pulsar Timing Array (PPTA), each modeled with different noise assumptions. Using the longest available PPTA data set, we measure an apparent second derivative of the pulsar spin frequency and discuss how this can be explained either by kinematic effects due to the proper motion and radial velocity of the pulsar or excess low-frequency noise such as a gravitational-wave background.

astro-ph.HE↗

arXiv2024

Reducing instrumental errors in Parkes Pulsar Timing Array data

This paper demonstrates the impact of state-of-the-art instrumental calibration techniques on the precision of arrival times obtained from 9.6 years of observations of millisecond pulsars using the Murriyang 64-m CSIRO Parkes Radio Telescope. Our study focuses on 21-cm observations of 25 high-priority pulsars that are regularly observed as part of the Parkes Pulsar Timing Array (PPTA) project, including those predicted to be the most susceptible to calibration errors. We employ Measurement Equation Template Matching (METM) for instrumental calibration and Matrix Template Matching (MTM) for arrival time estimation, resulting in significantly improved timing residuals with up to a sixfold reduction in white noise compared to arrival times estimated using Scalar Template Matching and conventional calibration based on the Ideal Feed Assumption. The median relative reduction in white noise is 33 percent, and the maximum absolute reduction is 4.5 microseconds. For PSR J0437-4715, METM and MTM reduce the best-fit power-law amplitude (2.7 sigma) and spectral index (1.7 sigma) of the red noise in the arrival time residuals, which can can be tentatively interpreted as mitigation of 1/f noise due to otherwise unmodeled steps in polarimetric response. These findings demonstrate the potential to directly enhance the sensitivity of pulsar timing array experiments through more accurate methods of instrumental calibration and arrival time estimation.

astro-ph.IM↗

arXiv2024

SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning

Unsupervised monocular depth estimation frameworks have shown promising performance in autonomous driving. However, existing solutions primarily rely on a simple convolutional neural network for ego-motion recovery, which struggles to estimate precise camera poses in dynamic, complicated real-world scenarios. These inaccurately estimated camera poses can inevitably deteriorate the photometric reconstruction and mislead the depth estimation networks with wrong supervisory signals. In this article, we introduce SCIPaD, a novel approach that incorporates spatial clues for unsupervised depth-pose joint learning. Specifically, a confidence-aware feature flow estimator is proposed to acquire 2D feature positional translations and their associated confidence levels. Meanwhile, we introduce a positional clue aggregator, which integrates pseudo 3D point clouds from DepthNet and 2D feature flows into homogeneous positional representations. Finally, a hierarchical positional embedding injector is proposed to selectively inject spatial clues into semantic features for robust camera pose decoding. Extensive experiments and analyses demonstrate the superior performance of our model compared to other state-of-the-art methods. Remarkably, SCIPaD achieves a reduction of 22.2\% in average translation error and 34.8\% in average angular error for camera pose estimation task on the KITTI Odometry dataset. Our source code is available at \url{https://mias.group/SCIPaD}.

cs.CV↗

arXiv2024

Scintillation velocity and arc observations of FRB 20201124A

We present the scintillation velocity measurements of FRB~20201124A from the FAST observations, which reveal an annual variation. This annual variation is further supported by changes detected in the scintillation arc as observed from the secondary spectrum. We attribute the annual velocity variation to the presence of a moderately anisotropic scattering screen located at a distance of 0.4$\pm$0.1~kpc from Earth. Our results prove that the scintillation of this FRB is mainly caused by material close to Earth on a Galactic scale. However, scintillation observations of other FRBs may expose their surrounding environment or uncover possible orbital motion if scintillation is caused by materials in their host galaxy.

astro-ph.HE↗

arXiv2024

Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg

We investigate the accuracy of prediction in deterministic learning dynamics of zero-sum games with random initializations, specifically focusing on observer uncertainty and its relationship to the evolution of covariances. Zero-sum games are a prominent field of interest in machine learning due to their various applications. Concurrently, the accuracy of prediction in dynamical systems from mechanics has long been a classic subject of investigation since the discovery of the Heisenberg Uncertainty Principle. This principle employs covariance and standard deviation of particle states to measure prediction accuracy. In this study, we bring these two approaches together to analyze the Follow-the-Regularized-Leader (FTRL) algorithm in two-player zero-sum games. We provide growth rates of covariance information for continuous-time FTRL, as well as its two canonical discretization methods (Euler and Symplectic). A Heisenberg-type inequality is established for FTRL. Our analysis and experiments also show that employing Symplectic discretization enhances the accuracy of prediction in learning dynamics.

cs.GT↗

arXiv2024

Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games

Last-iterate behaviors of learning algorithms in repeated two-player zero-sum games have been extensively studied due to their wide applications in machine learning and related tasks. Typical algorithms that exhibit the last-iterate convergence property include optimistic and extra-gradient methods. However, most existing results establish these properties under the assumption that the game is time-independent. Recently, (Feng et al, 2023) studied the last-iterate behaviors of optimistic and extra-gradient methods in games with a time-varying payoff matrix, and proved that in an unconstrained periodic game, extra-gradient method converges to the equilibrium while optimistic method diverges. This finding challenges the conventional wisdom that these two methods are expected to behave similarly as they do in time-independent games. However, compared to unconstrained games, games with constrains are more common both in practical and theoretical studies. In this paper, we investigate the last-iterate behaviors of optimistic and extra-gradient methods in the constrained periodic games, demonstrating that similar separation results for last-iterate convergence also hold in this setting.

cs.LG↗

arXiv2024

Ask Again, Then Fail: Large Language Models' Vacillations in Judgment

We observe that current conversational language models often waver in their judgments when faced with follow-up questions, even if the original judgment was correct. This wavering presents a significant challenge for generating reliable responses and building user trust. To comprehensively assess this issue, we introduce a \textsc{Follow-up Questioning Mechanism} along with two metrics to quantify this inconsistency, confirming its widespread presence in current language models. To mitigate this issue, we explore various prompting strategies for closed-source models; moreover, we develop a training-based framework \textsc{Unwavering-FQ} that teaches language models to maintain their originally correct judgments through synthesized high-quality preference data. Our experimental results confirm the effectiveness of our framework and its ability to enhance the general capabilities of models.

cs.CL↗

arXiv2024

A Preliminary Empirical Study on Prompt-based Unsupervised Keyphrase Extraction

Pre-trained large language models can perform natural language processing downstream tasks by conditioning on human-designed prompts. However, a prompt-based approach often requires "prompt engineering" to design different prompts, primarily hand-crafted through laborious trial and error, requiring human intervention and expertise. It is a challenging problem when constructing a prompt-based keyphrase extraction method. Therefore, we investigate and study the effectiveness of different prompts on the keyphrase extraction task to verify the impact of the cherry-picked prompts on the performance of extracting keyphrases. Extensive experimental results on six benchmark keyphrase extraction datasets and different pre-trained large language models demonstrate that (1) designing complex prompts may not necessarily be more effective than designing simple prompts; (2) individual keyword changes in the designed prompts can affect the overall performance; (3) designing complex prompts achieve better performance than designing simple prompts when facing long documents.

cs.CL↗

arXiv2024

A discovery of Two Slow Pulsars with FAST: "Ronin" from the Globular Cluster M15

Globular clusters harbor numerous millisecond pulsars, but long-period pulsars ($P \gtrsim 100$ ms) are rarely found. In this study, we employed a fast folding algorithm to analyze observational data from multiple globular clusters obtained by the Five-hundred-meter Aperture Spherical radio Telescope (FAST), aiming to detect the existence of long-period pulsars. We estimated the impact of the median filtering algorithm in eliminating red noise on the minimum detectable flux density ($S_{\rm min}$) of pulsars. Subsequently, we successfully discovered two isolated long-period pulsars in M15 with periods approximately equal to 1.928451 seconds and 3.960716 seconds, respectively. On the $P-\dot{P}$ diagram, both pulsars are positioned below the spin-up line, suggesting a possible history of partial recycling in X-ray binary systems disrupted by dynamical encounters later on. According to timing results, these two pulsars exhibit remarkably strong magnetic fields. If the magnetic fields were weakened during the accretion process, then a short duration of accretion might explain the strong magnetic fields of these pulsars.

astro-ph.HE↗

arXiv2024

Two-Step Iterative GMM Structure for Estimating Mixed Correlation Coefficient Matrix

In this article, we propose a new method for calculating the mixed correlation coefficient (Pearson, polyserial and polychoric) matrix and its covariance matrix based on the GMM framework. We build moment equations for each coefficient and align them together, then solve the system with Two-Step IGMM algorithm. Theory and simulation show that this estimation has consistency and asymptotic normality, and its efficiency is asymptotically equivalent to MLE. Moreover, it is much faster and the model setting is more flexible (the equations for each coefficient are blocked designed, you can only include the coefficients of interest instead of the entire correlation matrix), which can be a better initial estimation for structural equation model.

stat.CO↗

arXiv2024

SNE-RoadSegV2: Advancing Heterogeneous Feature Fusion and Fallibility Awareness for Freespace Detection

Feature-fusion networks with duplex encoders have proven to be an effective technique to solve the freespace detection problem. However, despite the compelling results achieved by previous research efforts, the exploration of adequate and discriminative heterogeneous feature fusion, as well as the development of fallibility-aware loss functions remains relatively scarce. This paper makes several significant contributions to address these limitations: (1) It presents a novel heterogeneous feature fusion block, comprising a holistic attention module, a heterogeneous feature contrast descriptor, and an affinity-weighted feature recalibrator, enabling a more in-depth exploitation of the inherent characteristics of the extracted features, (2) it incorporates both inter-scale and intra-scale skip connections into the decoder architecture while eliminating redundant ones, leading to both improved accuracy and computational efficiency, and (3) it introduces two fallibility-aware loss functions that separately focus on semantic-transition and depth-inconsistent regions, collectively contributing to greater supervision during model training. Our proposed heterogeneous feature fusion network (SNE-RoadSegV2), which incorporates all these innovative components, demonstrates superior performance in comparison to all other freespace detection algorithms across multiple public datasets. Notably, it ranks the 1st on the official KITTI Road benchmark.

cs.CV↗