Tootfinder

An adaptive time-stepping strategy for the modified phase field crystal model with a strong nonlinear vacancy potential
Wanrong Hao, Yunqing Huang
https://arxiv.org/abs/2510.11475

An adaptive time-stepping strategy for the modified phase field crystal model with a strong nonlinear vacancy potential
This paper develops three linear and energy-stable schemes for a modified phase field crystal model with a strong nonlinear vacancy potential (VMPFC model). This sixth-order phase-field model enables realistic crystal growth simulation. Starting from a Crank-Nicolson scheme based on the stabilized-SAV (S-SAV) method, we optimize it via the generalized positive auxiliary variable (GPAV) and modified exponential scalar auxiliary variable (ESAV) methods, thereby reducing computational complexity o…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
Zhijun Liu, Jiang Hu, Zhidong Bai, Zhihui Lv
https://arxiv.org/abs/2510.04185 h…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
In this paper, we establish the Central Limit Theorem (CLT) for linear spectral statistics (LSSs) of large-dimensional generalized spiked sample covariance matrices, where the spiked eigenvalues may be either bounded or diverge to infinity. Building upon this theorem, we derive the asymptotic distributions of linear hypothesis test statistics under the generalized spiked model, including Wilks' likelihood ratio test statistic U, the Lawley-Hotelling trace test statistic W, and the Bartlett-Nand…

Efficient Coherence Inference Using the Demodulated Band Transform and a Generalized Linear Model
Md Rakibul Mowla, Sukhbinder Kumar, Ariane E. Rhone, Brian J. Dlouhy, Christopher K. Kovach
https://arxiv.org/abs/2510.05559

Efficient Coherence Inference Using the Demodulated Band Transform and a Generalized Linear Model
Statistical significance testing of neural coherence is essential for distinguishing genuine cross-signal coupling from spurious correlations. A widely accepted approach uses surrogate-based inference, where null distributions are generated via time-shift or phase-randomization procedures. While effective, these methods are computationally expensive and yield discrete p-values that can be unstable near decision thresholds, limiting scalability to large EEG/iEEG datasets. We introduce and valida…

Non-exotic wormholes in $f(R,L_m)$ gravity
Sara Rastgoo, Foad Parsaei
https://arxiv.org/abs/2510.11487 https://arxiv.org/pdf/2510.11487

Non-exotic wormholes in $f(R,L_m)$ gravity
In the present analysis, we examine the potential existence of generalized wormhole models within the framework of newly developed extended $f(R,L_m)$ gravity. We investigate both a linear model, $f(R,L_m)=αR+βL_m$, and a non-linear model, $f(R,L_m)=\frac{R}{2}+ L^α_m$, to analyze traversable wormholes. By employing the variational approach, we derive modified versions of the field equations under the influence of an anisotropic matter source. A power-law shape function is applied, resulting…