arXiv subjects

Dongjun Li

Publications and source records attributed to Dongjun Li.

At least 19 recordsLinked to original sources

arXiv2026

From the Test-Mass Limit to Binary Black-Hole Waveforms in Higher-Derivative Gravity

Many higher-derivative theories predict stronger deviations from General Relativity for lower-mass black holes, while their nonlinear field equations often prevent reliable simulations of the full binary evolution. Here we develop a route from controlled black hole perturbation theory based on the modified Teukolsky formalism to comparable-mass waveforms, using parity-even cubic gravity as a representative example. We find that the tidal response of the secondary black hole enters at the same perturbative order as the direct higher-curvature correction and is therefore essential for a consistent leading-order waveform. The resulting strong-field fluxes and conservative dynamics produce an accumulated inspiral dephasing that grows toward merger. Embedding this test-mass information into an effective-one-body model, we construct inspiral-merger-ringdown waveforms for comparable-mass binaries and find coupling-dependent dephasing and waveform-peak shifts. Our results demonstrate how strong-field test-mass calculations can anchor waveform models for higher-derivative gravity when theory-specific numerical-relativity simulations are unavailable.

gr-qc↗

arXiv2026

Chiral symmetry and black hole isospectrality

We prove that black-hole isospectrality between linearly independent solutions follows whenever radiative metric and matter perturbations are reconstructed from complex master variables obeying a closed, complex-linear system with complex-linear boundary conditions. If a phase rotation maps one parity sector to the other, then the even- and odd-parity QNM spectra coincide, and the perturbations are parity isospectral. A broad class of chiral-aligned theories satisfies these criteria. As an application, we demonstrate that subextremal Kerr--de Sitter black holes are parity isospectral.

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arXiv2026

Modified Teukolsky Formalism for Extreme Mass-Ratio Inspirals in Higher-Derivative Gravity

In this work, we study a model problem involving a point particle spiraling into a non-rotating black hole in higher-derivative theories of gravity. In such theories, both the background spacetime and the generation and propagation of gravitational waves differ from those in General Relativity. We develop a modified Teukolsky formalism to describe gravitational waves sourced by the point particle and, as an illustrative example, compute the resulting fluxes to the black hole horizon and null infinity for a cubic gravity theory. The formalism is constructed in a way that can be naturally extended to rotating black holes. These results represent essential steps to build extreme mass-ratio-inspiral waveforms in modified gravity theories, which may also be rescaled to approximate waveforms from comparable-mass binary black hole systems, analogous to existing approaches in General Relativity.

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arXiv2026

Direct Data-driven Predictive Control: A Computationally Efficient Alternative to DeePC for Eco-driving in Mixed Traffic Flows

Improving energy efficiency in the transportation sector is critical for achieving sustainable mobility, with eco-driving emerging as a key strategy. However, implementing effective eco-driving for connected and automated vehicles (CAVs) in mixed traffic presents a significant control challenge due to the heterogeneous, uncertain behavior of human-driven vehicles (HDVs). Data-enabled Predictive Control (DeePC) offers a promising model-free approach but is often hindered by a high computational burden, limiting its real-time feasibility. This paper introduces a novel Direct Data-driven Predictive Control (D3PC) framework to address this limitation. By reformulating the data-driven prediction mechanism, the D3PC significantly reduces computational complexity, making its computation time nearly invariant to historical data size. This computational efficiency directly enables the formulation of a sophisticated eco-driving controller that can solve the complex energy optimization problem in real time, even within diverse and stochastic mixed-traffic environments. Comprehensive simulations demonstrate that the D3PC is orders of magnitude faster than existing DeePC-based methods while achieving superior energy efficiency. Specifically, it reduces total platoon energy consumption by up to 10.71% compared to rule-based cruise control baselines and 3.80% compared to the original DeePC, confirming its effectiveness for real-time, energy-efficient control.

eess.SY↗

arXiv2026

Lane Change Trajectory Planning for Personalized Driving Comfort and Mobility Efficiency

Lane changing entails simultaneous longitudinal and lateral motions that affect driving comfort and mobility efficiency. Because these motions are tightly coupled and subject to substantial inter-vehicle variability, trajectory planning for lane-change maneuvers is characterized by a highly personalized nature. This study proposes a neural network-driven planner that integrates a third-order polynomial trajectory generator with a learning module that infers optimal trajectory parameters across diverse driving conditions. Using a shared backbone with dual heads, one head ensures all-condition operational guarantees, while the other captures driver-specific preferences for comfort or mobility efficiency. A head-gated switching mechanism, realized through a statistical gate based on error-winner logistic regression, adaptively selects the appropriate head under varying driving conditions, which enables context-aware lane-change trajectory planning. Representative cases and Monte Carlo simulations show that the proposed planner achieves personalized comfort and mobility during lane changes, while the baseline ensures feasible trajectories under driving conditions where personalized data are insufficient or inaccessible.

cs.RO↗

arXiv2026

Metric Reconstruction for Generic Black-Hole Perturbations

Standard (radiation-gauge) metric reconstruction excludes generic sources because it requires a tracefree metric perturbation. We remove this obstruction for perturbations of Petrov type D spacetimes by introducing a traceful radiation gauge. Two first-order transport equations determine the metric trace from the stress-energy tensor, and the remaining metric components follow hierarchically from the Newman-Penrose equations. We illustrate the method for a Schwarzschild black hole with a thin static shell, including a source-supported static completion sector.

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arXiv2026

Modified Teukolsky formalism: Null testing and numerical benchmarking

Next-generation gravitational-wave detectors will make black-hole ringdown an increasingly sensitive probe of small departures from General Relativity in the strong-field regime. This motivates obtaining high-precision predictions of gravitational effective field theory, as spectral shifts can be quite small. Here we perform a focused stress test of the modified-Teukolsky framework by designing two null diagnostics. First, we consider an action with redundant operators that must produce zero first-order vacuum QNM shifts. Second, we exploit a Ricci-flat identity relating two physical cubic Riemann to test such a relation is satisfied by the ringdown spectra obtained. We compute the shifts using two independent numerical approaches: the eigenvalue-perturbation and generalized continued-fraction (Leaver-type) methods. Both null tests are passed across multiple multipoles and overtones, and the control-operator results agree in magnitude with the benchmark values reported in Ref. [1]. These validations support using the framework for obtaining accurate predictions for robust strong-field tests, with straightforward extensions to rotating backgrounds and coupling with matter fields.

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arXiv2025

Towards Realistic Earth-Observation Constellation Scheduling: Benchmark and Methodology

Agile Earth Observation Satellites (AEOSs) constellations offer unprecedented flexibility for monitoring the Earth's surface, but their scheduling remains challenging under large-scale scenarios, dynamic environments, and stringent constraints. Existing methods often simplify these complexities, limiting their real-world performance. We address this gap with a unified framework integrating a standardized benchmark suite and a novel scheduling model. Our benchmark suite, AEOS-Bench, contains $3,907$ finely tuned satellite assets and $16,410$ scenarios. Each scenario features $1$ to $50$ satellites and $50$ to $300$ imaging tasks. These scenarios are generated via a high-fidelity simulation platform, ensuring realistic satellite behavior such as orbital dynamics and resource constraints. Ground truth scheduling annotations are provided for each scenario. To our knowledge, AEOS-Bench is the first large-scale benchmark suite tailored for realistic constellation scheduling. Building upon this benchmark, we introduce AEOS-Former, a Transformer-based scheduling model that incorporates a constraint-aware attention mechanism. A dedicated internal constraint module explicitly models the physical and operational limits of each satellite. Through simulation-based iterative learning, AEOS-Former adapts to diverse scenarios, offering a robust solution for AEOS constellation scheduling. Experimental results demonstrate that AEOS-Former outperforms baseline models in task completion and energy efficiency, with ablation studies highlighting the contribution of each component. Code and data are provided in https://github.com/buaa-colalab/AEOSBench.

cs.CV↗

arXiv2025

Evolving extreme mass-ratio inspirals in a perturbed Schwarzschild spacetime

In this work, we develop the modified Teukolsky formalism that describes the GW radiation from a point mass orbiting around a perturbed Schwarzschild BH. This perturbation of the background spacetime induces a secular change in the orbital phase of the point mass. In turn, this causes a modification in the GW flux, which can be used to probe the background spacetime. We explicitly apply this formalism to a bumpy Schwarzschild spacetime as a proof of principle. The results pave the way for the description of EMRIs in generic perturbed Kerr spacetime in future developments.

gr-qc↗

arXiv2025

Techno-Economic Planning of Spatially-Resolved Battery Storage Systems in Renewable-Dominant Grids Under Weather Variability

The ongoing energy transition is significantly increasing the share of renewable energy sources (RES) in power systems; however, their intermittency and variability pose substantial challenges, including load shedding and system congestion. This study examines the role of the battery storage system (BSS) in mitigating these challenges by balancing power supply and demand. We optimize the location, size, and type of batteries using a two-stage stochastic program, with the second stage involving hourly operational decisions over an entire year. Unlike previous research, we incorporate the comprehensive technical and economic characteristics of battery technologies. The New York State (NYS) power system, currently undergoing a significant shift towards increased RES generation, serves as our case study. Using available load and weather data from 1980-2019, we account for the uncertainty of both load and RES generation through a sample average approximation approach. Our findings indicate that BSS can reduce renewable curtailment by 34% and load shedding by 21%, contributing to a more resilient power system in achieving NYS 2030 energy targets. Furthermore, the cost of employing BSS for the reduction of load shedding and RES curtailment does not increase linearly with additional capacity, revealing a complex relationship between costs and renewable penetration. This study provides valuable insights for the strategic BSS deployment to achieve a cost-effective and reliable power system in the energy transition as well as the feasibility of the NYS 2030 energy targets.

eess.SY↗

arXiv2025

Extreme mass-ratio inspiral within an ultralight scalar cloud I. Scalar radiation

In this work, we study the dynamics of an extreme mass-ratio inspiral (EMRI) embedded within a scalar cloud populated around the massive black hole. This cloud may be generated through the black hole superradiant process if the wavelength of the scalar particle is comparable to the size of the massive black hole. The EMRI motion perturbs the cloud, producing scalar radiation towards infinity and into the black hole horizon. In addition, the backreaction of the scalar radiation onto the orbit modifies the motion of the EMRI and induces an observable gravitational-wave phase shift for a range of system parameters. We quantify the scalar flux and the induced phase shift, as one of the examples of exactly-solvable, environmental effects of EMRIs.

gr-qc↗

arXiv2025

The ringdown of a black hole surrounded by a thin shell of matter

Recent studies have shown that far-field perturbations to the curvature potential of a black hole spacetime may destabilize its quasinormal mode (QNM) spectrum while only mildly affecting time-domain ringdown signals. In this work, we study the QNM spectrum and ringdown behavior of a Schwarzschild black hole with a far-field perturbation to its physical environment -- a thin matter shell with finite surface tension. After accounting for the dynamics of the interaction between GWs and the shell, we find that the fundamental mode can migrate perturbatively or be destabilized by the appearance of new modes with no analogue in the vacuum case, much like studies of ``bumps" in the curvature potential. However, unlike these previous works, we find that the coupling between metric perturbations and oscillations of the shell also sources weakly-damped QNMs which are exclusive to the polar sector. We then study whether the analysis tools of least-squares QNM fits and the full and rational ringdown filters can clearly identify the signatures of the shell in representative ringdown waveforms. We conclude that ringdown at sufficiently early times is insensitive to the shell; weakly-damped QNMs (in the polar sector) and echoes, which may enable the analysis methods considered here to infer the presence of a shell, only appear at late times and are generally weak.

gr-qc↗

arXiv2025

Perturbations of spinning black holes in dynamical Chern-Simons gravity: Slow rotation quasinormal modes

Gravitational waves offer new ways to test general relativity (GR) in the strong-field regime, including tests involving the ringdown phase of binary black hole mergers, characterized by oscillating and quickly decaying quasinormal modes (QNMs). Recent advances have extended QNM calculations to several theories beyond GR through the development of the modified Teukolsky formalism, including higher derivative gravity and dynamical Chern-Simons (dCS) gravity. Using the modified Teukolsky formalism, we previously derived radial second-order differential equations governing curvature and scalar field perturbations in dCS gravity at leading order in spin. In this work, we compute the QNM frequency shifts for slowly rotating black holes in dCS gravity from these modified Teukolsky equations, and (1) show that the radial equations for Weyl scalars $\Psi_{0,4}$ can be separated into even- and odd-parity parts, confirming that the scalar field couples only to the odd-parity sector; (2) extend the eigenvalue perturbation method to coupled fields; (3) compute the QNM spectrum, obtaining consistent results across independent calculations using different radiation gauges; (4) calculate the overtones in the QNM spectra for the first time in dCS gravity; (5) show that our findings align with previous metric perturbation studies and mark the first QNM spectrum calculation in a non-minimally coupled scalar-tensor theory via the modified Teukolsky formalism. This work lays the foundation for studying fast-rotating black holes in dCS gravity, advancing black hole spectroscopy in beyond-GR contexts.

gr-qc↗

arXiv2024

Integrated Power and Thermal Management for Enhancing Energy Efficiency and Battery Life in Connected and Automated Electric Vehicles

Effective power and thermal management are essential for ensuring battery efficiency, safety, and longevity in Connected and Automated Electric Vehicles (CAEVs). However, real-time implementation is challenging due to the multi-timescale dynamics and complex trade-offs between energy consumption, battery degradation, traffic efficiency, and thermal regulation. This paper proposes a novel integrated power and thermal management strategy based on the Multi-Horizon Model Predictive Control (MH-MPC) framework to enhance energy efficiency, optimize battery temperature, ensure traffic safety and efficiency, and reduce battery degradation for CAEVs. The proposed strategy is formulated with a focus on the aging term, allowing it to more effectively manage the trade-offs between energy consumption, battery degradation, and temperature regulation. Moreover, the proposed strategy leverages multi-horizon optimization to achieve substantial improvements, reducing computation time by 7.18%, cooling energy by 14.22%, traction energy by 8.26%, battery degradation loss by over 22%, and battery degradation inconsistency by 36.57% compared to the benchmark strategy. Furthermore, sensitivity analyses of key parameters, including weighting factors, sampling time, and prediction horizons, demonstrate the robustness of the strategy and underscore its potential for practical applications in extending battery lifespan while ensuring safety and efficiency.

eess.SY↗

arXiv2024

Spectroscopy of bumpy BHs: non-rotating case

Recent detections of gravitational waves have made black hole quasinormal modes a powerful tool in testing predictions of general relativity. Understanding the spectrum of these quasinormal modes in a broad class of theories beyond general relativity and a variety of astrophysical environments around black holes remains vital. In this work, we study the quasinormal mode spectrum of parametrized deformations of a non-rotating black hole in the vacuum. Following Vigeland and Hughes, we model these parametrized deformations as axisymmetric multipole moments in the Weyl coordinates with amplitudes much less than the amplitude of the Schwarzschild potential. These tiny bumps in the black hole geometry satisfy the linearized vacuum Einstein equations and are asymptotically flat. We use the recently developed modified Teukolsky formalism to derive one decoupled differential equation for the radiative Weyl scalar $\Psi_0$. We then use the eigenvalue perturbation method to compute the quasinormal mode frequency shifts of both even- and odd-parity modes with $\ell=2,3$ and up to the overtone number $n=2$ for the Weyl multipoles with $\ell_W=2,3$. Our calculation provides an avenue to directly connect the multipole moments of a modified black hole spacetime to the QNM frequency shifts in a parametric way.

gr-qc↗

arXiv2024

A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data

Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning offers a promising solution, while the development of such technologies is hindered by the scarcity of data on rare conditions and the demand for models that are both interpretable and trustworthy in a clinical context. Interpretable AI, with its capacity for human-readable outputs, can facilitate validation by clinicians and contribute to medical education. In the current work, we focus on choroid neoplasias, the most prevalent form of eye cancer in adults, albeit rare with 5.1 per million. We built the so-far largest dataset consisting of 750 patients, incorporating three distinct imaging modalities collected from 2004 to 2022. Our work introduces a concept-based interpretable model that distinguishes between three types of choroidal tumors, integrating insights from domain experts via radiological reports. Remarkably, this model not only achieves an F1 score of 0.91, rivaling that of black-box models, but also boosts the diagnostic accuracy of junior doctors by 42%. This study highlights the significant potential of interpretable machine learning in improving the diagnosis of rare diseases, laying a groundwork for future breakthroughs in medical AI that could tackle a wider array of complex health scenarios.

cs.LG↗

arXiv2024

Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances

This paper presents a safe learning-based eco-driving framework tailored for mixed traffic flows, which aims to optimize energy efficiency while guaranteeing safety during real-system operations. Even though reinforcement learning (RL) is capable of optimizing energy efficiency in intricate environments, it is challenged by safety requirements during the training process. The lack of safety guarantees is the other concern when deploying a trained policy in real-world application. Compared with RL, model predicted control (MPC) can handle constrained dynamics systems, ensuring safe driving. However, the major challenges lie in complicated eco-driving tasks and the presence of disturbances, which respectively challenge the MPC design and the satisfaction of constraints. To address these limitations, the proposed framework incorporates the tube-based enhanced MPC (RMPC) to ensure the safe execution of the RL policy under disturbances, thereby improving the control robustness. RL not only optimizes the energy efficiency of the connected and automated vehicle in mixed traffic but also handles more uncertain scenarios, in which the energy consumption of the human-driven vehicle and its diverse and stochastic driving behaviors are considered in the optimization framework. Simulation results demonstrate that the proposed algorithm, compared with RMPC technique, shows an average improvement of 10.88% in holistic energy efficiency, while compared with RL algorithm, it effectively prevents inter-vehicle collisions.

eess.SY↗

arXiv2023

Perturbations of spinning black holes in dynamical Chern-Simons gravity I. Slow rotation equations

The detection of gravitational waves resulting by the LIGO-Virgo-Kagra collaboration has inaugurated a new era in gravitational physics, providing an opportunity to test general relativity and its modifications in the strong gravity regime. One such test involves the study of the ringdown phase of gravitational waves from binary black-hole coalescence, which can be decomposed into a superposition of quasinormal modes. In general relativity, the spectra of quasinormal modes depend on the mass, spin, and charge of the final black hole, but they can be influenced by additional properties of the black hole, as well as corrections to general relativity. In this work, we employ the modified Teukolsky formalism developed in a previous study to investigate perturbations of slowly rotating black holes in a modified theory known as dynamical Chern-Simons gravity. Specifically, we derive the master equations for the $\Psi_0$ and $\Psi_4$ Weyl scalar perturbations that characterize the radiative part of gravitational perturbations, as well as for the scalar field perturbations. We employ metric reconstruction techniques to obtain explicit expressions for all relevant quantities. Finally, by leveraging the properties of spin-weighted spheroidal harmonics to eliminate the angular dependence from the evolution equations, we derive two, radial, second-order, ordinary differential equations for $\Psi_0$ and $\Psi_4$, respectively. These equations are coupled to another radial, second-order, ordinary differential equation for the scalar field perturbations. This work is the first attempt to derive a master equation for black holes in dynamical Chern-Simons gravity using curvature perturbations. The master equations can be numerically integrated to obtain the quasinormal mode spectrum of slowly rotating black holes in this theory, making progress in the study of ringdown in dynamical Chern-Simons gravity.

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