arXiv subjects

Lei Wu

Publications and source records attributed to Lei Wu.

At least 145 records · Page 8Linked to original sources

arXiv2024

Footprints of Axion-Like Particle in Pulsar Timing Array Data and James Webb Space Telescope Observations

Several Pulsar Timing Array (PTA) collaborations have recently reported the evidence for a stochastic gravitational-wave background (SGWB), which can unveil the formation of primordial seeds of inhomogeneities in the early universe. With the SGWB parameters inferred from PTAs data, we can make a prediction of the seeds for early galaxy formation from the domain walls in the axion-like particles (ALPs) field distribution. This also naturally provides a solution to the observation of high redshifts by the James Webb Space Telescope. The predicted photon coupling of the ALP is within the reach of future experimental searches.

hep-ph↗

arXiv2024

Multiscale simulation of rarefied gas flows in Divertor Tokamak Test facility

Simulating gas flow within the divertor, which is a crucial component in nuclear fusion reactors, is essential for assessing and enhancing its design and performance. Traditional methods, such as the direct simulation Monte Carlo and the discrete velocity method, often fall short in efficiency for these simulations. In this study, we utilize the general synthetic iterative scheme to simulate a simplified Tokamak divertor model, demonstrating its fast convergence and asymptotic-preserving properties in complex three-dimensional scenarios. A conservative estimate of speedup by three orders of magnitude is achieved by the general synthetic iterative scheme when compared to the direct simulation Monte Carlo method. We further investigate the relationship between pumping efficiency and factors like temperature, absorptivity, and the Knudsen number, providing valuable insights to guide the design and optimization of divertor structures.

physics.plasm-ph↗

arXiv2024

Bernstein-Sato ideals

In this paper, we review several results on the zero loci of Bernstein-Sato ideals related to singularities of hypersurfaces. This is an exposition for the Frontiers of Science Awards in Mathematics presenting results from one of our articles, with history, motivation, and further developments.

math.AG↗

arXiv2024

Temperature jump coefficients in polyatomic gas with strong translational/internal non-equilibrium

The temperature jump problem in polyatomic gas flow with translational/internal non-equilibrium is investigated, where the internal temperature is excited by volumetric heating, while the translational temperature is heated via the inelastic translational-internal energy relaxation. In the near-continuum flow regime, analytical temperature profiles are derived, based on which the first and second temperature jump coefficients are extracted from the numerical solution of the Boltzmann equation. Analytical expressions for temperature jump coefficients are fitted over a wide range of inelastic collision number and accommodation coefficient.

physics.flu-dyn↗

arXiv2024

GSIS-ALE for moving boundary problems in rarefied gas flows

Multiscale rarefied gas flows with moving boundaries pose significant challenges to the numerical simulation, where the primary difficulties involve robustly managing the mesh movement and ensuring computational efficiency across all flow regimes. Build upon recent advancements of the general synthetic iterative scheme (GSIS), this paper presents an efficient solver to simulate the large displacement of rigid-body in rarefied gas flows. The newly developed solver utilizes a dual time step method to solve the mesoscopic kinetic and macroscopic synthetic equations alternately, in an arbitrary Lagrangian-Eulerian framework. Additionally, the overset mesh is used and the six degree-of-freedom rigid body dynamics equation is integrated to track the motion of solids. Four moving boundary problems encompassing a wide range of flow velocities and gas rarefaction are simulated, including the periodic pitching of airfoil, particle motion in lid-driven cavity flow, two-body separation in supersonic flow, and three-dimensional lunar landing, demonstrating the accuracy and efficiency of the GSIS in handling multi-scale moving boundary problems within an overset framework.

physics.comp-ph↗

arXiv2024

Multiscale simulation of coexisting turbulent and rarefied gas flows

Simulating complex gas flows from turbulent to rarefied regimes is a long-standing challenge, since turbulence and rarefied flow represent contrasting extremes of computational aerodynamics. We propose a multiscale method to bridge this gap. Our method builds upon the general synthetic iterative scheme for the mesoscopic Boltzmann equation, and integrates the $k$-$ω$ model in the macroscopic synthetic equation to address turbulent effects. We have not only validated this approach using the experimental data of turbulent flows, but also confirmed that the turbulence model exerts no undue influence on highly rarefied flows. Our method is then applied to opposing jet problems in hypersonic flight surrounding by rarefied gas flows, showing that the turbulence could cause significant impacts on the surface heat flux, which cannot be captured by the turbulent model nor the laminar Boltzmann solution alone. This study provides a viable framework for advancing our understanding of the interaction between turbulent and rarefied gas flows.

physics.flu-dyn↗

arXiv2024

Listening for echo from the stimulated axion decay with the 21 CentiMeter Array

The axion is a hypothetical elementary particle that could solve the long-standing strong CP problem in particle physics and the dark matter mystery in the cosmos. Due to the stimulation of the ambient photons, the axion dark matter decay into photons is significantly enhanced so that its echo signal could be detected by terrestrial telescopes. As a pathfinder, we study the expected sensitivity of searching for the axion dark matter in the mass range between $0.41$ and $1.6μ\text{eV}$ with the 21 CentiMeter Array (21CMA). We aim to cover the whole 21CMA frequency range in two years by using a 1MW emitter. We find that the resulting sensitivity on the axion-photon coupling could surpass other existing limits by about one order of magnitude.

hep-ph↗

arXiv2024

Comprehensive characterization of tumor therapeutic response with simultaneous mapping cell size, density, and transcytolemmal water exchange

Early assessment of tumor therapeutic response is an important topic in precision medicine to optimize personalized treatment regimens and reduce unnecessary toxicity, cost, and delay. Although diffusion MRI (dMRI) has shown potential to address this need, its predictive accuracy is limited, likely due to its unspecific sensitivity to overall pathological changes. In this work, we propose a new quantitative dMRI-based method dubbed EXCHANGE (MRI of water Exchange, Confined and Hindered diffusion under Arbitrary Gradient waveform Encodings) for simultaneous mapping of cell size, cell density, and transcytolemmal water exchange. Such rich microstructural information comprehensively evaluates tumor pathologies at the cellular level. Validations using numerical simulations and in vitro cell experiments confirmed that the EXCHANGE method can accurately estimate mean cell size, density, and water exchange rate constants. The results from in vivo animal experiments show the potential of EXCHANGE for monitoring tumor treatment response. Finally, the EXCHANGE method was implemented in breast cancer patients with neoadjuvant chemotherapy, demonstrating its feasibility in assessing tumor therapeutic response in clinics. In summary, a new, quantitative dMRI-based EXCHANGE method was proposed to comprehensively characterize tumor microstructural properties at the cellular level, suggesting a unique means to monitor tumor treatment response in clinical practice.

physics.med-ph↗

arXiv2024

Why Do You Grok? A Theoretical Analysis of Grokking Modular Addition

We present a theoretical explanation of the ``grokking'' phenomenon, where a model generalizes long after overfitting,for the originally-studied problem of modular addition. First, we show that early in gradient descent, when the ``kernel regime'' approximately holds, no permutation-equivariant model can achieve small population error on modular addition unless it sees at least a constant fraction of all possible data points. Eventually, however, models escape the kernel regime. We show that two-layer quadratic networks that achieve zero training loss with bounded $\ell_{\infty}$ norm generalize well with substantially fewer training points, and further show such networks exist and can be found by gradient descent with small $\ell_{\infty}$ regularization. We further provide empirical evidence that these networks as well as simple Transformers, leave the kernel regime only after initially overfitting. Taken together, our results strongly support the case for grokking as a consequence of the transition from kernel-like behavior to limiting behavior of gradient descent on deep networks.

cs.LG↗

arXiv2024

Multiscale simulation of rarefied gas dynamics via direct intermittent GSIS-DSMC coupling

The general synthetic iterative scheme (GSIS) has proven its efficacy in modeling rarefied gas dynamics, where the steady-state solutions are obtained after dozens of iterations of the Boltzmann equation, with minimal numerical dissipation even using large spatial cells. In this paper, the fast convergence and asymptotic-preserving properties of the GSIS are harnessed to remove the limitations of the direct simulation Monte Carlo (DSMC) method. The GSIS, which leverages high-order constitutive relations derived from DSMC, is applied intermittently, which not only rapidly steers the DSMC towards steady state, but also eliminates the requirement that the cell size must be smaller than the molecular mean free path. Several numerical tests have been conducted to validate the accuracy and efficiency of this hybrid GSIS-DSMC approach.

physics.comp-ph↗

arXiv2024

Towards Improving Unit Commitment Economics: An Add-On Tailor for Renewable Energy and Reserve Predictions

Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are raw. In other words, if the predictions are further tailored to assist UC in making the economic operation plans against realizations of the RES and reserve requirements, UC economics will benefit significantly. To this end, this paper presents a cost-oriented tailor of RES-and-reserve predictions for UC, deployed as an add-on to the predict-then-optimize process. The RES-and-reserve tailor is trained by solving a bi-level mixed-integer programming model: the upper level trains the tailor based on its induced operating cost; the lower level, given tailored predictions, mimics the system operation process and feeds the induced operating cost back to the upper level; finally, the upper level evaluates the training quality according to the fed-back cost. Through this training, the tailor learns to customize the raw predictions into cost-oriented predictions. Moreover, the tailor can be embedded into the existing predict-then-optimize process as an add-on, improving the UC economics. Lastly, the presented method is compared to traditional, binary-relaxation, neural network-based, stochastic, and robust methods.

math.OC↗

arXiv2024

Probing Inelastic Dark Matter at the LHC, FASER and STCF

In this work, we explore the potential of probing the inelastic dark matter (DM) model with an extra U(1)D gauge symmetry at the Large Hadron Collider, ForwArd Search ExpeRiment and Super Tau Charm Factory. To saturate the observed DM relic density, the mass splitting between two light dark states has to be small enough, and thus leads to some distinctive signatures at these colliders. By searching for the long-lived particle, the displaced muon-jets, the soft leptons, and the mono-photon events, we find that the inelastic DM mass in the range of 1 MeV to 210 GeV could be tested.

hep-ph↗

arXiv2024

Boosting the convergence of DSMC by GSIS

A deterministic-stochastic coupling scheme is developed for simulating rarefied gas flows, where the key process is the alternative solving of the macroscopic synthetic equations [Su et al., J. Comput. Phys., 407 (2020) 109245] and the mesoscopic equation via the asymptotic-preserving time-relaxed Monte Carlo scheme [Fei, J. Comput. Phys., 486 (2023) 112128]. Firstly, the macroscopic synthetic equations are exactly derived from the Boltzmann equation, incorporating not only the Newtonian viscosity and Fourier thermal conduction laws but also higher-order constitutive relations that capture rarefaction effects; the latter are extracted from the stochastic solver over a defined sampling interval. Secondly, the macroscopic synthetic equations, with the initial field extracted from the stochastic solver over the same sampling interval, are solved to the steady state or over certain iteration steps. Finally, the simulation particles in the stochastic solver are updated to match the density, velocity, and temperature obtained from the macroscopic synthetic equations. Moreover, simulation particles in the subsequent interval will be partly sampled according to the solutions of macroscopic synthetic equations. As a result, our coupling strategy enhances the asymptotic-preserving characteristic of the stochastic solver and substantially accelerates convergence towards the steady state. Several numerical tests are performed, and it is found that our method can reduce the computational cost in the near-continuum flow regime by two orders of magnitude compared to the direct simulation Monte Carlo method.

physics.comp-ph↗

arXiv2024

DeFiGuard: A Price Manipulation Detection Service in DeFi using Graph Neural Networks

The prosperity of Decentralized Finance (DeFi) unveils underlying risks, with reported losses surpassing 3.2 billion USD between 2018 and 2022 due to vulnerabilities in Decentralized Applications (DApps). One significant threat is the Price Manipulation Attack (PMA) that alters asset prices during transaction execution. As a result, PMA accounts for over 50 million USD in losses. To address the urgent need for efficient PMA detection, this paper introduces a novel detection service, DeFiGuard, using Graph Neural Networks (GNNs). In this paper, we propose cash flow graphs with four distinct features, which capture the trading behaviors from transactions. Moreover, DeFiGuard integrates transaction parsing, graph construction, model training, and PMA detection. Evaluations on a dataset of 208 PMA and 2,080 non-PMA transactions show that DeFiGuard with GNN models outperforms the baseline in Accuracy, TPR, FPR, and AUC-ROC. The results of ablation studies suggest that the combination of the four proposed node features enhances DeFiGuard's efficacy. Moreover, DeFiGuard classifies transactions within 0.892 to 5.317 seconds, which provides sufficient time for the victims (DApps and users) to take action to rescue their vulnerable funds. In conclusion, this research offers a significant step towards safeguarding the DeFi landscape from PMAs using GNNs.

cs.CR↗

arXiv2024

Gravitational Wave as a Probe of Light Feebly Interacting Dark Matter

Light feebly interacting dark matter is widely predicted in a plethora of new physics models. However, due to very feeble couplings with the Standard Model particles, its relic density produced via the relativistic thermal freeze-out process easily exceeds the observed value. The entropy dilution in an early matter-dominated era provides an attractive mechanism for solving such an overabundance problem. In this work, we note that this dark matter dilution mechanism will lead to two distinctive kinks in the primordial GW spectrum, whose frequencies strongly correlate with the DM mass. We show that the GW detectors, such as Cosmic Explorer (CE) and Big Bang Observer (BBO), can measure the kinks in the primordial GW spectrum and will offer a new avenue to probe light feebly interacting dark matter.

hep-ph↗

arXiv2024

Light Thermal Dark Matter Beyond $p$-Wave Annihilation in Minimal Higgs Portal Model

This study explores a minimal renormalizable dark matter (DM) model, incorporating a sub-GeV Majorana DM and a singlet scalar particle $ϕ$. Using scalar and pseudo-scalar interactions (couplings $c_s$ and $c_p$), we investigate implications for DM detection, considering $s$-wave, $p$-wave, and combined ($s$+$p$ wave) contributions in DM annihilation cross-section, as well as loop-correction contributions to DM-nucleon elastic scattering. Identifying a broad parameter space ($10 \,\rm{MeV} < m_χ\lesssim m_ϕ$) within the $2σ$ allowed region, we explore scenarios ($\left|c_s\right|\gg \left|c_p\right|$, $\left|c_s\right|\ll \left|c_p\right|$, and $\left|c_s\right|\approx \left|c_p\right|$). We find that (i) a non-zero pseudo-scalar coupling alleviates direct detection constraints as a comparison with the previous pure scalar coupling case; (ii) CMB observations set stringent limits on pseudo-scalar interaction dominant cases, making $s$-wave annihilation viable only for $m_χ>1\,\rm{GeV}$; (iii) the preferred $ϕ$-resonance region can be tested in the future indirect detection experiments, such as e-ASTROGAM.

hep-ph↗

arXiv2024

Can supercooled phase transitions explain the gravitational wave background observed by pulsar timing arrays?

Several pulsar timing array collaborations recently reported evidence of a stochastic gravitational wave background (SGWB) at nHz frequencies. Whilst the SGWB could originate from the merger of supermassive black holes, it could be a signature of new physics near the 100 MeV scale. Supercooled first-order phase transitions (FOPTs) that end at the 100 MeV scale are intriguing explanations, because they could connect the nHz signal to new physics at the electroweak scale or beyond. Here, however, we provide a clear demonstration that it is not simple to create a nHz signal from a supercooled phase transition, due to two crucial issues that could rule out many proposed supercooled explanations and should be checked. As an example, we use a model based on non-linearly realized electroweak symmetry that has been cited as evidence for a supercooled explanation. First, we show that a FOPT cannot complete for the required transition temperature of around 100 MeV. Such supercooling implies a period of vacuum domination that hinders bubble percolation and transition completion. Second, we show that even if completion is not required or if this constraint is evaded, the Universe typically reheats to the scale of any physics driving the FOPT. The hierarchy between the transition and reheating temperature makes it challenging to compute the spectrum of the SGWB.

hep-ph↗

arXiv2024

General synthetic iterative scheme for rarefied gas mixture flows

The numerical simulation of rarefied gas mixtures with disparate mass and concentration is a huge research challenge. Based on our recent kinetic modelling for monatomic gas mixture flows, this problem is tackled by the general synthetic iterative scheme (GSIS), where the mesoscopic kinetic and macroscopic synthetic equations are alternately solved by the finite-volume discrete velocity method. Three important features of GSIS are highlighted. First, the synthetic equations are precisely derived from the kinetic equation, naturally reducing to the Navier-Stokes equations in the continuum flow regime; in other flow regimes, the kinetic equation provides high-order closure of the constitutive relations to capture the rarefaction effects. Second, these synthetic equations, which can be solved quickly, help to adjust the kinetic system to relax rapidly toward the steady state. Furthermore, in such a two-way coupling, the constraint on the spatial cell size is relieved. Third, the linear Fourier stability analysis demonstrates that the error decay rate in GSIS is smaller than 0.5 for various combinations of mass, concentration and viscosity ratios, such that the error can be reduced by three orders of magnitude after 10 iterations. The efficiency and accuracy of GSIS are demonstrated through several challenging cases covering a wide range of mass ratio, species concentration, and flow speed.

physics.comp-ph↗