arXiv subjects

Lei Ye

Publications and source records attributed to Lei Ye.

17 recordsLinked to original sources

arXiv2026

CFR without Unbiasedness: Deterministic Guarantees for Persistent Public-Chance Schedules

At a finite public-chance cut, counterfactual regret minimization (CFR) must choose how many outcomes to evaluate before each regret update. Exact evaluation processes the full cut at one strategy profile; persistent partial evaluation processes a fixed without-replacement order across evolving profiles. The latter covers every outcome once per epoch, yet its feedback is generally conditionally biased because earlier batches influence the profiles seen by later batches. We establish a deterministic target-transfer theorem for uniform, nonnested additive public cuts. The theorem bounds full-cut exploitability by regret on the delivered feedback and a public-debit term that couples prefix coverage discrepancy with motion along the realized strategy path. Consecutively balanced schedules consequently converge for additive signed regret matching (RM) and RM+ under predetermined averaging weights, while a fixed RM+ construction proves that the discrepancy--path product is necessary in general. A component-resolved form of the theorem converts an execution trace into a numerical exploitability certificate. On two released heads-up no-limit hold'em turn endgames, persistent order improves substantially over fresh reshuffling despite identical epochwise coverage, and partial coverage wins every registered shallow matched-budget comparison. A depth study locates a crossover between 32 and 64 full-cut outcome budgets, after which complete coverage dominates. These results characterize public-chance width and order as learning variables and provide a deterministic basis for designing and auditing persistent CFR schedules.

cs.GT↗

arXiv2026

Linear and nonlinear benchmark of gyrokinetic simulation of energetic particle driven toroidal Alfven eigenmodes in ITPA TAE benchmark case

A new gyrokinetic code, TEK, was benchmarked in simulating energetic particle (EP) driven toroidal Alfven eigenmodes (TAEs) in the simple tokamak configuration chosen by the ITPA-EP group for code benchmarking purpose. Linear benchmark has been well established by other codes, whereas nonlinear benchmark for this case is lacking. This paper presents, besides the linear benchmark, nonlinear results for both single-n and multiple-n simulations (n is the toroidal mode number). The nonlinear results are in good agreement with an analytical theory on zonal field beat-driven by Alfven eigenmodes, partially verifying correctness of the nonlinear simulations. The saturation level and the resulting EP transport are examined. This provides data for future inter-code nonlinear benchmarking. In TEK, all species (electrons, thermal ions, EPs) are treated on the same footing using the gyrokinetic model (with electrons in the zero Larmor radius limit). The electromagnetic cancellation problem is mitigated by using the mixed-variable pullback method. Numerical details related to electromagnetic gyrokinetic simulation are discussed.

physics.plasm-ph↗

arXiv2026

Development and validation of a local neoclassical transport module in NLT with applications to EAST-relevant impurity transport and trapped-electron-mode stability

A local neoclassical transport module has been developed and validated in the semi-Lagrangian gyrokinetic code NLT for multi-species collisional plasmas. The module incorporates a linearized multi-species Sugama collision operator and provides two complementary solution strategies. In the initial-value formulation, a composite substep source-integration scheme is introduced to accurately evaluate the neoclassical drive along unperturbed particle trajectories while retaining large macroscopic time steps. A direct steady-state solver is also implemented to obtain the stationary neoclassical response without long-time relaxation. The two approaches are benchmarked against the Eulerian neoclassical code NEO for electron-ion plasmas and three-species plasmas with carbon impurities. The NLT results reproduce the NEO particle and heat fluxes, parallel flows, and bootstrap current over a broad collisionality range. As representative applications, the validated framework is applied to EAST-relevant tungsten impurity transport and core trapped-electron-mode stability. The results show that tungsten neoclassical transport is sensitive to local profile gradients, while the increased effective collisionality associated with larger $Z_{\rm eff}$ can reduce the linear TEM growth rate under the considered EAST-relevant conditions. These developments extend NLT toward realistic multi-species collisional transport simulations.

physics.plasm-ph↗

arXiv2026

Implicit discretization schemes for full-kinetic ion and drift-kinetic electron simulations

We present a new electromagnetic plasma simulation model with full-kinetic ions and drift-kinetic electrons. This model (termed as FIDES) solves the electric field using the implicit perpendicular Ohm's law and a novel implicit parallel Ampere's law, where the latter requires an implicit scheme for the parallel electric field in advancing the electron weights. To suppress unphysical high-frequency instabilities, ion weights are advanced using an implicit scheme for perpendicular electric fields. Simulations of perpendicular and parallel waves validate the model's capability in handling high-frequency physics. Low-frequency wave simulations demonstrate that the implicit parallel Ampere's law can mitigate the cancellation problem more effectively than the conventional schemes using the parallel Ohm's law. To reduce the numerical damping from implicit time-stepping, we develop a second-order scheme for particle pushing. Meanwhile, an integrated strategy combining the first- and second-order schemes is employed to suppress odd-even decoupling while maintaining the accuracy of the second-order formulation.

physics.plasm-ph↗

arXiv2026

KCFRC: Kinematic Collision-Aware Foothold Reachability Criteria for Legged Locomotion

Legged robots face significant challenges in navigating complex environments, as they require precise real-time decisions for foothold selection and contact planning. While existing research has explored methods to select footholds based on terrain geometry or kinematics, a critical gap remains: few existing methods efficiently validate the existence of a non-collision swing trajectory. This paper addresses this gap by introducing KCFRC, a novel approach for efficient foothold reachability analysis. We first formally define the foothold reachability problem and establish a sufficient condition for foothold reachability. Based on this condition, we develop the KCFRC algorithm, which enables robots to validate foothold reachability in real time. Our experimental results demonstrate that KCFRC achieves remarkable time efficiency, completing foothold reachability checks for a single leg across 900 potential footholds in an average of 2 ms. Furthermore, we show that KCFRC can accelerate trajectory optimization and is particularly beneficial for contact planning in confined spaces, enhancing the adaptability and robustness of legged robots in challenging environments.

cs.RO↗

arXiv2026

Utilizing Earth Foundation Models to Enhance the Simulation Performance of Hydrological Models with AlphaEarth Embeddings

Predicting river flow in places without streamflow records is challenging because basins respond differently to climate, terrain, vegetation, and soils. Traditional basin attributes describe some of these differences, but they cannot fully represent the complexity of natural environments. This study examines whether AlphaEarth Foundation embeddings, which are learned from large collections of satellite images rather than designed by experts, offer a more informative way to describe basin characteristics. These embeddings summarize patterns in vegetation, land surface properties, and long-term environmental dynamics. We find that models using them achieve higher accuracy when predicting flows in basins not used for training, suggesting that they capture key physical differences more effectively than traditional attributes. We further investigate how selecting appropriate donor basins influences prediction in ungauged regions. Similarity based on the embeddings helps identify basins with comparable environmental and hydrological behavior, improving performance, whereas adding many dissimilar basins can reduce accuracy. The results show that satellite-informed environmental representations can strengthen hydrological forecasting and support the development of models that adapt more easily to different landscapes.

cs.LG↗

arXiv2025

PegasusFlow: Parallel Rolling-Denoising Score Sampling for Robot Diffusion Planner Flow Matching

Diffusion models offer powerful generative capabilities for robot trajectory planning, yet their practical deployment on robots is hindered by a critical bottleneck: a reliance on imitation learning from expert demonstrations. This paradigm is often impractical for specialized robots where data is scarce and creates an inefficient, theoretically suboptimal training pipeline. To overcome this, we introduce PegasusFlow, a hierarchical rolling-denoising framework that enables direct and parallel sampling of trajectory score gradients from environmental interaction, completely bypassing the need for expert data. Our core innovation is a novel sampling algorithm, Weighted Basis Function Optimization (WBFO), which leverages spline basis representations to achieve superior sample efficiency and faster convergence compared to traditional methods like MPPI. The framework is embedded within a scalable, asynchronous parallel simulation architecture that supports massively parallel rollouts for efficient data collection. Extensive experiments on trajectory optimization and robotic navigation tasks demonstrate that our approach, particularly Action-Value WBFO (AVWBFO) combined with a reinforcement learning warm-start, significantly outperforms baselines. In a challenging barrier-crossing task, our method achieved a 100% success rate and was 18% faster than the next-best method, validating its effectiveness for complex terrain locomotion planning. https://masteryip.github.io/pegasusflow.github.io/

cs.RO↗

arXiv2025

An Improved Boris Algorithm for Charge Particle Orbit in Tokamak Plasmas

An improved Boris algorithm for simulating the motion of charged particles in electromagnetic fields has been developed. This enhancement addresses the issue of inaccurate fast-scale cyclotron phase calculations present in the original Boris algorithm, while preserving its advantage in simulating slow-scale guiding center motion. As a result, it strikes a balance between low and high-frequency dynamics, overcoming the limitations of traditional second-order volume-preserving algorithms (VPAs) which are constrained to a single characteristic frequency. Test particle simulations indicate that, in most cases, the improved Boris algorithm achieves significantly higher accuracy than conventional VPAs when simulating cases involving various frequencies of electric field within a typical Tokamak magnetic field, highlighting its superior efficacy in handling problems across a wide range of characteristic frequencies.

physics.plasm-ph↗

arXiv2025

Phase Stability Analysis of Volume-preserving Algorithms for Accurate Single Particle Orbit Simulations in Tokamak Plasmas

Second-order Volume-preserving algorithms (VPAs) for simulating charged particle motion in electromagnetic fields have been generalized to a rotating angle formulation by using the matrix decomposition methods. Based on this method, the phase stability of this class of VPAs has been analyzed by using the Discrete Fourier Transformations (DFT) technique. It is found that two prominent VPAs, namely the $G_h^2$ and the Boris algorithm, exhibit optimal phase precision for high-frequency (gyro motion) and low-frequency dynamics (transit/bounce motion), respectively. These findings have been empirically verified through numerical experiments. The insights gained from this study enable the selection of an appropriate VPA for practical simulations based on the characteristic frequencies of specific physics problems, which can substantially enhance numerical accuracy and improve computational efficiency for long-term simulations.

physics.plasm-ph↗

arXiv2024

Nonlinear saturation of reversed shear Alfven eigenmode via high-frequency quasi-mode generation

A nonlinear saturation mechanism for reversed shear Alfven eigenmode (RSAE) is proposed and analysed, and is shown to be of relevance to typical reactor parameter region. The saturation is achieved through the generation of high-frequency quasi-mode due to nonlinear coupling of two RSAEs, which is then damped due to coupling with the shear Alfven continuum, and leads to the nonlinear saturation of the primary RSAEs . An estimation of the nonlinear damping rate is also provided.

physics.plasm-ph↗

arXiv2024

Interpretable Interaction Modeling for Trajectory Prediction via Agent Selection and Physical Coefficient

A thorough understanding of the interaction between the target agent and surrounding agents is a prerequisite for accurate trajectory prediction. Although many methods have been explored, they assign correlation coefficients to surrounding agents in a purely learning-based manner. In this study, we present ASPILin, which manually selects interacting agents and replaces the attention scores in Transformer with a newly computed physical correlation coefficient, enhancing the interpretability of interaction modeling. Surprisingly, these simple modifications can significantly improve prediction performance and substantially reduce computational costs. We intentionally simplified our model in other aspects, such as map encoding. Remarkably, experiments conducted on the INTERACTION, highD, and CitySim datasets demonstrate that our method is efficient and straightforward, outperforming other state-of-the-art methods.

cs.CV↗

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↗

arXiv2021

Effects of resonant magnetic perturbations on neutral beam heating in a tokamak

Effects of resonant magnetic perturbations (RMPs) on tangential neutral beam heating in the EAST tokamak are studied numerically. RMPs with linear resistive magnetohydrodynamics response are used in the modeling. A variety of representing configurations of RMP coil currents are examined and their effects on the NBI heating efficiency are compared, in order to find a parameter window where deleterious effects of RMPs on NBI heating efficiency are minimized. It is found that the internal redistribution of fast ions by RMPs induces local accumulation of fast ions, resulting in higher local fast ion pressure than the case without RMPs. It is also found that the toroidal phasing of the RMP with respect to the fast ion source has slight effects on the steady-state radial profile of fast ions. The dependence of fast ion loss fraction on the RMP up-down phase difference shows similar behavior as the dependence of the radial width of chaotic magnetic field on the phase difference. A statistical method of identifying resonances between RMPs and lost fast ions is proposed and the results indicate that some resonances between RMPs and lost passing particles may be of non-integer fractional order, rather than the usual integer order.

physics.plasm-ph↗

arXiv2021

Gyrokinetic simulations of electric current generation in ion temperature gradient driven turbulence

Gyrokinetic simulations in the collisionless limit demonstrate the physical mechanisms and the amplitude of the current driven by turbulence. Simulation results show the spatio-temporal variation of the turbulence driven current and its connection to the divergence of the Reynolds stress and the turbulence acceleration. Fine structures (a few ion Larmor radii) of the turbulence induced current are observed near the rational surfaces with the arbitrary wavelength solver of the quasi-neutrality equation. The divergence of the Reynolds stress plays a major role in the generation of these fine structures. The so-called "spontaneous" current is featured with large local magnitude near the rational surfaces.

physics.plasm-ph↗

arXiv2021

Continental-scale streamflow modeling of basins with reservoirs: towards a coherent deep-learning-based strategy

A large fraction of major waterways have dams influencing streamflow, which must be accounted for in large-scale hydrologic modeling. However, daily streamflow prediction for basins with dams is challenging for various modeling approaches, especially at large scales. Here we examined which types of dammed basins could be well represented by long short-term memory (LSTM) models using readily-available information, and delineated the remaining challenges. We analyzed data from 3557 basins (83% dammed) over the contiguous United States and noted strong impacts of reservoir purposes, degree of regulation (dor), and diversion on streamflow modeling. While a model trained on a widely-used reference-basin dataset performed poorly for non-reference basins, the model trained on the whole dataset presented a median Nash-Sutcliffe efficiency coefficient (NSE) of 0.74. The zero-dor, small-dor (with storage of approximately a month of average streamflow or less), and large-dor basins were found to have distinct behaviors, so migrating models between categories yielded catastrophic results, which means we must not treat small-dor basins as reference ones. However, training with pooled data from different sets yielded optimal median NSEs of 0.72, 0.79, and 0.64 for these respective groups, noticeably stronger than existing models. These results support a coherent modeling strategy where smaller dams (storing about a month of average streamflow or less) are modeled implicitly as part of basin rainfall-runoff processes; then, large-dor reservoirs of certain types can be represented explicitly. However, dammed basins must be present in the training dataset. Future work should examine separate modeling of large reservoirs for fire protection and irrigation, hydroelectric power generation, and flood control.

cs.LG↗

arXiv2018

Room temperature infrared photodetectors with hybrid structure based on 2D materials

Two-dimensional (2D) materials, such as graphene, transition metal dichalcogenides (TMDs), black phosphorus (BP) and related derivatives, have attracted great attention due to their advantages of flexibility, strong light-matter interaction, broadband absorption and high carrier mobility, and have become a powerful contender for next-generation infrared photodetectors. However, since the thickness of two-dimensional materials is on the order of nanometers, the absorption of two-dimensional materials is very weak, which limits the detection performance of 2D materials-based infrared photodetector. In order to solve this problem, scientific researchers have tried to use optimized device structures to combine with two-dimensional materials for improving the performance of infrared photodetector. In this review, we review the progress of room temperature infrared photodetectors with hybrid structure based on 2D materials in recent years, focusing mainly on 2D-nD (n = 0, 1, 2) heterostructures, the integration between 2D materials and on-chip or plasmonic structure. Finally, we summarize the current challenges and point out the future development direction.

physics.app-ph↗

arXiv2018

In-Out impurity density asymmetry due to the Coriolis force in a rotating tokamak plasma

The effect of the Coriolis force due to the impurity toroidal and poloidal rotation on the in-out impurity density asymmetry in a rotating tokamak plasma is identified. The in-out impurity density asymmetry can be induced by the Coriolis force with q*v_theta_z*omega_z, in this case, when moving along the magnetic field line from the outboard side to the inboard side in a magnetic flux surface, one sees a positive Coriolis force. The proposed theory is consistent with the ASDEX Upgrade experimental observations.

physics.plasm-ph↗