arXiv subjects

Sheng Long

Publications and source records attributed to Sheng Long.

30 records · Page 2Linked to original sources

arXiv2025

Effective one-body theory of spinless binary evolution dynamics

The effective one-body (EOB) theory provides an innovative framework for analyzing the dynamics of binary systems, as articulated by Hamilton's equations. This paper investigates a self-consistent EOB theory specifically tailored for the dynamics of such systems. Our methodology begins by emphasizing how to effectively utilize the metrics derived from scattering angles in the analysis of binary black hole mergers. We then construct an effective Hamiltonian and formulate a decoupled, variable-separated Teukolsky-like equation for $ψ^B_4$. Furthermore, we present the formal solution to this equation, detailing the energy flux, radiation-reaction force (RRF), and waveforms for the ``plus" and ``cross" modes generated by spinless binaries. Finally, we carry out numerical calculations using the EOB theory and compare the results with numerical relativity (NR) data from the SXS collaboration. The results indicate that to the innermost stable circular orbit, the binding energy -- angular momentum relation differs from the NR results by less than $5$\textperthousand, with a larger mass ratio yielding better agreement.

gr-qc↗

arXiv2025

Scalar-gravitational quasinormal modes and echoes in a five dimensional thick brane

The scalar perturbations of thick braneworld models provide critical insights into their matter-geometry relationship, distinct from tensor modes. This work systematically investigates quasinormal modes and gravitational echoes from scalar perturbations in a thick brane model exhibiting internal structure and brane splitting. Using the WKB method, direct integration, and Bernstein spectral techniques, we compute quasinormal frequencies across different parameter regimes, addressing both single and double-barrier effective potentials. Time-domain evolution of wave packets reveals clear echo signals for split brane configurations ($s > 1, δ> 1$), produced by successive reflections between sub-branes. A key finding is the position-dependence of echo modes within the extra dimension: observers located on a sub-brane detect clean periodic signals, whereas those situated between sub-branes observe more complex, modulated waveforms. This effect offers a distinct signature of the brane's internal structure. The observed echoes, along with consistent frequency- and time-domain results, advance the understanding of thick brane dynamics and open an observational window into warped extra dimensions. Moreover, the similarity between the effective potential in thick brane scenarios and those of black holes and wormholes offers valuable perspectives for studying echo-related phenomena in these gravitational systems.

gr-qc↗

arXiv2025

Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization

Judging the similarity of visualizations is crucial to various applications, such as visualization-based search and visualization recommendation systems. Recent studies show deep-feature-based similarity metrics correlate well with perceptual judgments of image similarity and serve as effective loss functions for tasks like image super-resolution and style transfer. We explore the application of such metrics to judgments of visualization similarity. We extend a similarity metric using five ML architectures and three pre-trained weight sets. We replicate results from previous crowd-sourced studies on scatterplot and visual channel similarity perception. Notably, our metric using pre-trained ImageNet weights outperformed gradient-descent tuned MS-SSIM, a multi-scale similarity metric based on luminance, contrast, and structure. Our work contributes to understanding how deep-feature-based metrics can enhance similarity assessments in visualization, potentially improving visual analysis tools and techniques. Supplementary materials are available at https://osf.io/dj2ms.

cs.HC↗

arXiv2024

Regulation of Algorithmic Collusion

Consider sellers in a competitive market that use algorithms to adapt their prices from data that they collect. In such a context it is plausible that algorithms could arrive at prices that are higher than the competitive prices and this may benefit sellers at the expense of consumers (i.e., the buyers in the market). This paper gives a definition of plausible algorithmic non-collusion for pricing algorithms. The definition allows a regulator to empirically audit algorithms by applying a statistical test to the data that they collect. Algorithms that are good, i.e., approximately optimize prices to market conditions, can be augmented to contain the data sufficient to pass the audit. Algorithms that have colluded on, e.g., supra-competitive prices cannot pass the audit. The definition allows sellers to possess useful side information that may be correlated with supply and demand and could affect the prices used by good algorithms. The paper provides an analysis of the statistical complexity of such an audit, i.e., how much data is sufficient for the test of non-collusion to be accurate.

cs.GT↗

arXiv2024

Self-consistent effective-one-body theory for spinning binaries based on post-Minkowskian approximation

This paper extends the research on the self-consistent effective-one-body theory of a real spinless two-body system based on the post-Minkowskian approximation (Science China, 65, 100411, (2022)) to the case of a binary system for the spinning black holes. An effective rotating metric and an improved Hamiltonian for the spinning black hole binaries were constructed. The decoupled equation for the null tetrad component of the gravitational perturbed Weyl tensor $ψ^B_{4}$ in the effective rotating spacetime is found with the help of the gauge transform characteristics of the Weyl tensors. The decoupled equation is then separated between radial and angular variables in the slowly rotating background spacetime, and a formal solution of $ψ^B_{4}$ is obtained. On this basis, the formal expressions of the radiation reaction force and the waveform for the ``plus'' and ``cross'' modes of the gravitational wave are presented. These results, obtained in the same effective spacetime, constitute a self-consistent effective-one-body theory for the spinning black hole binaries based on the post-Minkowskian approximation.

gr-qc↗

arXiv2024

Energy flux and waveform of gravitational wave generated by coalescing slow-spinning binary system in effective one-body theory

We extend our research on the energy flux and waveform characteristics of gravitational waves generated by merging nonspinning binary black holes through self-consistent effective one-body theory \cite{L2023} to include binary systems with slowly spinning black holes. Initially, we decompose the equation for the null tetrad component of the gravitationally perturbed Weyl tensor $ψ^B_{4}$ into radial and angular parts, leveraging the second-order approximation of the rotation parameter $a$. Subsequently, we derive an analytical solution for the radial equation and observe that our results are contingent upon the parameters $a_2$, $a_3$ and $a$, which represent the second- and third-order correction parameters, respectively. Ultimately, we calculate the energy flux, the radiation-reaction force and the waveform for the ``plus" and ``cross" modes of the gravitational waves generated by merging slowly spinning binary black holes.

gr-qc↗

arXiv2024

Energy flux and waveforms by coalescing spinless binary system in effective one-body theory

We present a study on the energy radiation rate and waveforms of the gravitational wave generated by coalescing spinless binary systems up to the third post-Minkowskian approximation in the effective one-body theory. To derive an analytical expansion of the null tetrad components of the gravitational perturbed Weyl tensor $\varPsi_{4}$ in the effective spacetime, we utilize the method proposed by Sasaki $et$ $al.$ During this investigation, we discover more general integral formulas that provide a theoretical framework for computing the results in any order. Subsequently, we successfully compute the energy radiation rate and waveforms of the gravitational wave, which include the results of the Schwarzschild case and the correction terms resulting from the dimensionless parameters $a_{2}$ and $a_{3}$ in the effective metric.

gr-qc↗

arXiv2023

Effective metric of spinless binaries with radiation-reaction effect up to fourth Post-Minkowskian order in effective-one-body theory

By means of the scattering angles, we obtain an effective metric of spinless binaries with radiation-reaction effects up to fourth post-Minkowskian order, which is the foundation of the effective-one-body theory. We note that there are freedoms for the parameters of the effective metric because one equation corresponds to two parameters for each post-Minkowskian order. Accordingly, in order to construct a self-consistent effective-one-body theory in which the Hamiltonian, radiation-reaction forces and waveforms for the ``plus" and ``cross" modes of the gravitational wave should be based on the same physical model, we can fix these freedoms by requiring the null tetrad component of the gravitationally perturbed Weyl tensor $Ψ_4^B$ to be decoupled in the effective spacetime.

gr-qc↗

arXiv2023

Screening with Disadvantaged Agents

Motivated by school admissions, this paper studies screening in a population with both advantaged and disadvantaged agents. A school is interested in admitting the most skilled students, but relies on imperfect test scores that reflect both skill and effort. Students are limited by a budget on effort, with disadvantaged students having tighter budgets. This raises a challenge for the principal: among agents with similar test scores, it is difficult to distinguish between students with high skills and students with large budgets. Our main result is an optimal stochastic mechanism that maximizes the gains achieved from admitting ``high-skill" students minus the costs incurred from admitting ``low-skill" students when considering two skill types and $n$ budget types. Our mechanism makes it possible to give higher probability of admission to a high-skill student than to a low-skill, even when the low-skill student can potentially get higher test-score due to a higher budget. Further, we extend our admission problem to a setting in which students uniformly receive an exogenous subsidy to increase their budget for effort. This extension can only help the school's admission objective and we show that the optimal mechanism with exogenous subsidies has the same characterization as optimal mechanisms for the original problem.

cs.GT↗

arXiv2023

Adapting Step-size: A Unified Perspective to Analyze and Improve Gradient-based Methods for Adversarial Attacks

Learning adversarial examples can be formulated as an optimization problem of maximizing the loss function with some box-constraints. However, for solving this induced optimization problem, the state-of-the-art gradient-based methods such as FGSM, I-FGSM and MI-FGSM look different from their original methods especially in updating the direction, which makes it difficult to understand them and then leaves some theoretical issues to be addressed in viewpoint of optimization. In this paper, from the perspective of adapting step-size, we provide a unified theoretical interpretation of these gradient-based adversarial learning methods. We show that each of these algorithms is in fact a specific reformulation of their original gradient methods but using the step-size rules with only current gradient information. Motivated by such analysis, we present a broad class of adaptive gradient-based algorithms based on the regular gradient methods, in which the step-size strategy utilizing information of the accumulated gradients is integrated. Such adaptive step-size strategies directly normalize the scale of the gradients rather than use some empirical operations. The important benefit is that convergence for the iterative algorithms is guaranteed and then the whole optimization process can be stabilized. The experiments demonstrate that our AdaI-FGM consistently outperforms I-FGSM and AdaMI-FGM remains competitive with MI-FGSM for black-box attacks.

cs.LG↗

arXiv2022

New self-consistent effective one-body theory for spinless binaries based on the post-Minkowskian approximation

The effective one-body theories, introduced by Buonanno and Damour, are novel approaches to constructing a gravitational waveform template. By taking a gauge in which $ψ_{1}^{B}$ and $ψ_{3}^{B}$ vanish, we find a decoupled equation with separable variables for $ψ^{B}_{4}$ for gravitational perturbation in the effective metric obtained in the post-Minkowskian approximation. Furthermore, we set up a new self-consistent effective one-body theory for spinless binaries, which can be applicable to any post-Minkowskian orders. This theory not only releases the assumption that $v/c$ should be a small quantity but also resolves the contradiction that the Hamiltonian, radiation-reaction force, and waveform are constructed from different physical models in the effective one-body theory with the post-Newtonian approximation. Compared with our previous theory (Science China, 65, 260411, (2022)), the computational effort for the radiation-reaction force and waveform in this new theory will be tremendously reduced.

gr-qc↗

arXiv2021

The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods

The adaptive stochastic gradient descent (SGD) with momentum has been widely adopted in deep learning as well as convex optimization. In practice, the last iterate is commonly used as the final solution to make decisions. However, the available regret analysis and the setting of constant momentum parameters only guarantee the optimal convergence of the averaged solution. In this paper, we fill this theory-practice gap by investigating the convergence of the last iterate (referred to as individual convergence), which is a more difficult task than convergence analysis of the averaged solution. Specifically, in the constrained convex cases, we prove that the adaptive Polyak's Heavy-ball (HB) method, in which only the step size is updated using the exponential moving average strategy, attains an optimal individual convergence rate of $O(\frac{1}{\sqrt{t}})$, as opposed to the optimality of $O(\frac{\log t}{\sqrt {t}})$ of SGD, where $t$ is the number of iterations. Our new analysis not only shows how the HB momentum and its time-varying weight help us to achieve the acceleration in convex optimization but also gives valuable hints how the momentum parameters should be scheduled in deep learning. Empirical results on optimizing convex functions and training deep networks validate the correctness of our convergence analysis and demonstrate the improved performance of the adaptive HB methods.

cs.LG↗