Tootfinder

Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
G\'erard Ben Arous, Murat A. Erdogdu, N. Mert Vural, Denny Wu
https://arxiv.org/abs/2508.03688

Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
We study the optimization and sample complexity of gradient-based training of a two-layer neural network with quadratic activation function in the high-dimensional regime, where the data is generated as $y \propto \sum_{j=1}^{r}λ_j σ\left(\langle \boldsymbol{θ_j}, \boldsymbol{x}\rangle\right), \boldsymbol{x} \sim N(0,\boldsymbol{I}_d)$, $σ$ is the 2nd Hermite polynomial, and $\lbrace\boldsymbolθ_j \rbrace_{j=1}^{r} \subset \mathbb{R}^d$ are orthonormal signal directions. We consider the ex…

AttZoom: Attention Zoom for Better Visual Features
Daniel DeAlcala, Aythami Morales, Julian Fierrez, Ruben Tolosana
https://arxiv.org/abs/2508.03625 https://

AttZoom: Attention Zoom for Better Visual Features
We present Attention Zoom, a modular and model-agnostic spatial attention mechanism designed to improve feature extraction in convolutional neural networks (CNNs). Unlike traditional attention approaches that require architecture-specific integration, our method introduces a standalone layer that spatially emphasizes high-importance regions in the input. We evaluated Attention Zoom on multiple CNN backbones using CIFAR-100 and TinyImageNet, showing consistent improvements in Top-1 and Top-5 cla…

Replaced article(s) found for cond-mat.soft. https://arxiv.org/list/cond-mat.soft/new
[1/1]:
- Solvent-induced ion clusters generate long-ranged double-layer forces at high ionic strengths
David Ribar, Clifford E. Woodward, Jan Forsman

Stable, which is building a new Layer 1 blockchain for stablecoins, raised a $28M seed co-led by Bitfinex and Hack VC (Yogita Khatri/The Block)
https://www.theblock.co/post/364952/tether-focused-layer-1-stable-raises-28-mi…

Viability of perturbative expansion for quantum field theories on neurons
Srimoyee Sen, Varun Vaidya
https://arxiv.org/abs/2508.03810 https://arxiv.org/pdf…

Viability of perturbative expansion for quantum field theories on neurons
Neural Network (NN) architectures that break statistical independence of parameters have been proposed as a new approach for simulating local quantum field theories (QFTs). In the infinite neuron number limit, single-layer NNs can exactly reproduce QFT results. This paper examines the viability of this architecture for perturbative calculations of local QFTs for finite neuron number $N$ using scalar $ϕ^4$ theory in $d$ Euclidean dimensions as an example. We find that the renormalized $O(1/N)$ …

Impact of rotation on synthetic mass-radius relationships of two-layer rocky planets and water worlds
J. -M. Hur\'e, P. No\'e, C. Staelen, E. Di Folco
https://arxiv.org/abs/2507.02112

Impact of rotation on synthetic mass-radius relationships of two-layer rocky planets and water worlds
We have analyzed the effects of rotation on mass-radius relationships for single-layer and two-layer planets having a core and an envelope made of pure materials among iron, perovskite and water in solid phase. The numerical surveys use the DROP code updated with a modified polytropic equation-of-state (EOS) and investigate flattening parameters $f$ up to $0.2$. In the mass range $0.1 M_\oplus < M < 10 M_\oplus$, we find that rotation systematically shifts the curves of composition towards larg…

Crosslisted article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[1/1]:
- A Fluid Antenna Enabled Physical Layer Key Generation for Next-G Wireless Networks
Jiacheng Guo, Ning Gao, Yiping Zuo, Hao Xu, Shi Jin, Kai Kit Wong

Crosslisted article(s) found for eess.IV. https://arxiv.org/list/eess.IV/new
[1/1]:
- T-MLP: Tailed Multi-Layer Perceptron for Level-of-Detail Signal Representation
Chuanxiang Yang, Yuanfeng Zhou, Guangshun Wei, Siyu Ren, Yuan Liu, Junhui Hou, Wenping Wang

Flat bands, Dirac cones, and higher-order band crossings in twisted multilayer graphene
Bryan Li, Mengxuan Yang
https://arxiv.org/abs/2508.02011 https://ar…

Flat bands, Dirac cones, and higher-order band crossings in twisted multilayer graphene
For the chiral limit of two sheets of $n$-layer Bernal-stacked graphene established in the Physical Review Letters arXiv:2109.10325 and arXiv:2109.11514, we prove a trichotomy: depending on the twisting angle, we have either (1) generically, the band crossing of the first two bands is of order $n$; or (2) at a discrete set of magic angles, the first two bands are completely flat; or (3) for another discrete set of twisting parameters, the bands exhibit Dirac cones. This new mathematical discove…

Stripe and Paradigm unveil Tempo, a Layer-1 blockchain for stablecoins; a source says Tempo will not launch with its own token and there is no launch timeline (Leo Schwartz/Fortune)
https://fortune.com/crypto/2025/09/04/stripe-paradigm-…

Stripe and Paradigm announce new payments-focused blockchain Tempo
Led by Paradigm managing partner Matt Huang, Tempo is Big Tech’s first major move into crypto.

Replaced article(s) found for physics.flu-dyn. https://arxiv.org/list/physics.flu-dyn/new
[1/1]:
- Surface bubble lifetime in the presence of a turbulent air flow, and the effect of surface layer ...
Tristan Aur\'egan, Luc Deike

Anyon superfluid in trilayer quantum Hall systems
Taige Wang, Ya-Hui Zhang
https://arxiv.org/abs/2508.00058 https://arxiv.org/pdf/2508.00058

Anyon superfluid in trilayer quantum Hall systems
Intertwining intrinsic topological order with gapless collective modes remains a central challenge in many-body physics. We show that a quantum-Hall trilayer at $ν_{1}=ν_{2}=ν_{3}= \frac13$, tuned solely by the inter-layer spacing $d$, realizes this goal. Large-scale density-matrix renormalization group (DMRG) calculations and a Chern-Simons field theory analysis reveal an intermediate ``anyon-exciton condensate'' separating the familiar $ν_{\mathrm{tot}}=1$ exciton condensate ($d \to 0$) f…

Layer-specific changes in sensory cortex across the lifespan in mice and humans #7T

Layer-specific changes in sensory cortex across the lifespan in mice and humans - Nature Neuroscience
The principal layer architecture of the sensory cortex is altered with aging. The authors show that overall thinning of the primary somatosensory cortex is driven by deep layer degeneration but that layer IV is more pronounced in old age.

Significant Mobility Enhancement in Coupled AlGaN/GaN Quantum Wells considering Inter-Well Distance and Asymmetric Widths
Le Tri Dat, Tran Trong Tai, Truong Van Tuan, Vo Van Tai, Nguyen Duy Vy
https://arxiv.org/abs/2508.02024

Significant Mobility Enhancement in Coupled AlGaN/GaN Quantum Wells considering Inter-Well Distance and Asymmetric Widths
We demonstrate that coupled AlGaN/GaN quantum wells with asymmetric widths ($L_1-L_2<30 $ A achieve up to 4.5 times higher mobility than single wells at optimal separation (d = 100 A). Crucially, mobility surpasses single wells when d>40 A reversing the trend at smaller distances. This enhancement stems from double-layer screening that suppresses remote/background impurities and dislocations, while LO phonon scattering remains unaffected. For identical wells, coupled systems underperform single…

Pathwidth of 2-Layer $k$-Planar Graphs
Yuto Okada
https://arxiv.org/abs/2507.21864 https://arxiv.org/pdf/2507.21864…

Pathwidth of 2-Layer $k$-Planar Graphs
A bipartite graph $G = (X \cup Y, E)$ is a 2-layer $k$-planar graph if it admits a drawing on the plane such that the vertices in $X$ and $Y$ are placed on two parallel lines respectively, edges are drawn as straight-line segments, and every edge involves at most $k$ crossings. Angelini, Da Lozzo, Förster, and Schneck [GD 2020; Comput. J., 2024] showed that every 2-layer $k$-planar graph has pathwidth at most $k + 1$. In this paper, we show that this bound is sharp by giving a 2-layer $k$-plan…

Crosslisted article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Zero-Shot KWS for Children's Speech using Layer-Wise Features from SSL Models
Subham Kutum, Abhijit Sinha, Hemant Kumar Kathania, Sudarsana Reddy Kadiri, Mahesh Chandra Govil

Challenges in Scaling ScAlN Bulk Acoustic Wave Filters toward Ku-Band Frequencies
Sinwoo Cho, Byeongjin Kim, Lezli Matto, Omar Barrera, Pietro Simeoni, Yinan Wang, Michael Liao, Tzu-Hsuan Hsu, Jack Kramer, Matteo Rinaldi, Mark S. Goorsky, Ruochen Lu
https://arxiv.org/abs/2509.03679

Challenges in Scaling ScAlN Bulk Acoustic Wave Filters toward Ku-Band Frequencies
This paper reports an 11.7 GHz compact filter based on Scandium Aluminum Nitride (ScAlN) Film Bulk Acoustic Resonators (FBARs) and provides a detailed analysis of the fundamental challenges that limit performance when scaling to higher frequencies. A 50 Ω ladder filter based on single-layer thin film ScAlN with Platinum (Pt) electrodes was demonstrated at 11.7 GHz with a 3 dB fractional bandwidth (FBW) of 4.0% and an out of band rejection greater than 23.1 dB. However, the filter exhibits a mo…

Crosslisted article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- T-MLP: Tailed Multi-Layer Perceptron for Level-of-Detail Signal Representation
Chuanxiang Yang, Yuanfeng Zhou, Guangshun Wei, Siyu Ren, Yuan Liu, Junhui Hou, Wenping Wang

Crosslisted article(s) found for cs.SD. https://arxiv.org/list/cs.SD/new
[1/1]:
- Can Layer-wise SSL Features Improve Zero-Shot ASR Performance for Children's Speech?
Abhijit Sinha, Hemant Kumar Kathania, Sudarsana Reddy Kadiri, Shrikanth Narayanan

Crosslisted article(s) found for eess.SP. https://arxiv.org/list/eess.SP/new
[1/1]:
- Can Layer-wise SSL Features Improve Zero-Shot ASR Performance for Children's Speech?
Abhijit Sinha, Hemant Kumar Kathania, Sudarsana Reddy Kadiri, Shrikanth Narayanan

Replaced article(s) found for cs.SI. https://arxiv.org/list/cs.SI/new
[1/1]:
- Design of A* based heuristic algorithm for efficient interdiction in multi-Layer networks
Sukanya Samanta

Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling
Lucas Benigni, Elliot Paquette
https://arxiv.org/abs/2508.20036 https://arxiv…

Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling
We compute the asymptotic eigenvalue distribution of the neural tangent kernel of a two-layer neural network under a specific scaling of dimension. Namely, if $X\in\mathbb{R}^{n\times d}$ is an i.i.d random matrix, $W\in\mathbb{R}^{d\times p}$ is an i.i.d $\mathcal{N}(0,1)$ matrix and $D\in\mathbb{R}^{p\times p}$ is a diagonal matrix with i.i.d bounded entries, we consider the matrix \[ \mathrm{NTK} = \frac{1}{d}XX^\top \odot \frac{1}{p} σ'\left( \frac{1}{\sqrt{d}}XW \right)D…

Now out in #TMLR:
🍇 GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks 🍇
There's lots of work on sampling subgraphs for GNNs, but relatively little on making this sampling process _adaptive_. That is, learning to select the data from the graph that is relevant for your task.
We introduce an RL-based and a GFLowNet-based sampler and show that the approach perf…

Massive Supervised Fine-tuning Experiments Reveal How Data, Layer, and Training Factors Shape LLM Alignment Quality
Yuto Harada, Yusuke Yamauchi, Yusuke Oda, Yohei Oseki, Yusuke Miyao, Yu Takagi
https://arxiv.org/abs/2506.14681

Massive Supervised Fine-tuning Experiments Reveal How Data, Layer, and Training Factors Shape LLM Alignment Quality
Supervised fine-tuning (SFT) is a critical step in aligning large language models (LLMs) with human instructions and values, yet many aspects of SFT remain poorly understood. We trained a wide range of base models on a variety of datasets including code generation, mathematical reasoning, and general-domain tasks, resulting in 1,000+ SFT models under controlled conditions. We then identified the dataset properties that matter most and examined the layer-wise modifications introduced by SFT. Our…

Word-Representable Graphs and Locality of Words
Philipp B\"oll, Pamela Fleischmann, Annika Huch, Jana Krei{\ss}, Tim L\"ock, Kajus Park, Max Wiedenh\"oft
https://arxiv.org/abs/2506.19493

Word-Representable Graphs and Locality of Words
In this work, we investigate the relationship between $k$-repre\-sentable graphs and graphs representable by $k$-local words. In particular, we show that every graph representable by a $k$-local word is $(k+1)$-representable. A previous result about graphs represented by $1$-local words is revisited with new insights. Moreover, we investigate both classes of graphs w.r.t. hereditary and in particular the speed as a measure. We prove that the latter ones belong to the factorial layer and that th…

Replaced article(s) found for cs.MM. https://arxiv.org/list/cs.MM/new
[1/1]:
- PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adapti...
Yibo Lyu, Rui Shao, Gongwei Chen, Yijie Zhu, Weili Guan, Liqiang Nie

Determining the magnetic field of active region plages using the whole CLASP2/2.1 spectral window
David Afonso Delgado, Tanaus\'u del Pino Alem\'an, Javier Trujillo Bueno, Ryohko Ishikawa, Ernest Alsina Ballester, David E. McKenzie, Luca Belluzzi, Christian Bethge, Ken Kobayashi, Takenori J. Okamoto, Laurel A. Rachmeler, Donguk Song, Ji\v{r}\'i \'St\v{e}p\'an, Bart de Pontieu, Adam R. Kobelski, Genevieve D. Vigil, Fr\'ed\'eric Auch\`ere, Ryouhei Kano, Amy Wi…

Determining the magnetic field of active region plages using the whole CLASP2/2.1 spectral window
The Chromospheric LAyer SpectroPolarimeter missions, CLASP2 and CLASP2.1, demonstrated that the near-UV spectral region between 279.30 and 280.68 nm is suitable for studying the magnetism of the solar chromosphere. In particular, the spectropolarimetric observations in the Mg II h and k resonant doublet, Mn I 279.91 and 280.19 nm resonant lines, and Fe II 279.79 and 280.66 nm lines acquired by these suborbital space experiments have been proven useful for inferring the magnetic field stratifica…

SeDA: Secure and Efficient DNN Accelerators with Hardware/Software Synergy
Wei Xuan, Zhongrui Wang, Lang Feng, Ning Lin, Zihao Xuan, Rongliang Fu, Tsung-Yi Ho, Yuzhong Jiao, Luhong Liang
https://arxiv.org/abs/2508.18924

SeDA: Secure and Efficient DNN Accelerators with Hardware/Software Synergy
Ensuring the confidentiality and integrity of DNN accelerators is paramount across various scenarios spanning autonomous driving, healthcare, and finance. However, current security approaches typically require extensive hardware resources, and incur significant off-chip memory access overheads. This paper introduces SeDA, which utilizes 1) a bandwidth-aware encryption mechanism to improve hardware resource efficiency, 2) optimal block granularity through intra-layer and inter-layer tiling patte…

Vor genau 30 Jahren wurde ein kleines Stück Technikgeschichte geschrieben, das unseren Musikkonsum für immer verändern sollte! Am 14. Juli 1995 legten die Forscher am Fraunhofer-Institut die Dateiendung ".mp3" fest. 🎧
Zum Artikel: https://heise.de/-1…

Crosslisted article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- 2-Layer Fan-Planarity in Polynomial Time
Yasuaki Kobayashi, Yuto Okada
https://

Magnetic order dependent photoluminescence from high energy excitons in hBN protected few-layer CrSBr
Xiaohua Wu, Junyang Chen, Mingqiang Gu, Yujun Zhang, Shanmin Wang, Yanan Dai, Qihang Liu, Yue Zhao, Mingyuan Huang
https://arxiv.org/abs/2507.23301

Magnetic order dependent photoluminescence from high energy excitons in hBN protected few-layer CrSBr
The detection and manipulation of the spin configurations in layered magnetic semiconductors hold significant interest for developing spintronic devices in two-dimensional limit. In this letter, we report a systematical study on the photoluminescence (PL) from the high energy excitons in few-layer CrSBr and its application on detecting the spin configurations. Besides the broad excitonic emission peak (Xl) at around 1.34 eV, we also observed another strong excitonic emission peak (Xh) at around…

Misfit layered superconductor (PbSe)1.14(NbSe2)3 with possible layer-selective FFLO state
Yuki M. Itahashi, Yamato Nohara, Michiya Chazono, Hideki Matsuoka, Koichiro Arioka, Tetsuya Nomoto, Yoshimitsu Kohama, Youichi Yanase, Yoshihiro Iwasa, Kaya Kobayashi
https://arxiv.org/abs/2506.14106

Misfit layered superconductor (PbSe)1.14(NbSe2)3 with possible layer-selective FFLO state
Two-dimensional (2D) superconductors are known for their novel emergent phenomena, however, lack of experimental probes beyond resistivity has hindered further exploration of diverse superconducting states. Bulk 2D superconductors, with superconducting layers separated by non-superconducting layers, offer a unique opportunity to break this limit. Here, we synthesized a single crystal of misfit layered compound (PbSe)1.14(NbSe2)3, composed of alternately stacked tri-layer NbSe2 and non-supercond…

Fully atomic layer deposited transparent carrier selective contacts for bifacial Cd-free Cu2ZnSnSe4 thin-film solar cells
Rosa Almache-Hern\'andeza, Gerard Masmitj\`a, Benjam\'in Pusay, Eloi Ros, Kunal J. Tiwari, Pedro Vidal-Fuentes, Victor Izquierdo-Roca, Edgardo Saucedo, Crist\'obal Voz, Joaquim Puigdollers, Pablo Ortega
https://…

Fully atomic layer deposited transparent carrier selective contacts for bifacial Cd-free Cu2ZnSnSe4 thin-film solar cells
Thin-film solar cells based on kesterite (Cu2ZnSnSe4) material are a promising alternative for photovoltaic devices due to their composition consisting of earth abundant elements, ease of production at a relatively low temperatures and excellent optical absorption properties. Additionally, this absorber compound allows a tuneable bandgap energy in the 1 to 1.5 eV window range, which makes it an attractive candidate either as a top or a bottom solar cell in tandem technologies combined with tran…

Boundary layer profiles of positive solutions for logistic equation with sublinear nonlinearity on the boundary
Kenichiro Umezu
https://arxiv.org/abs/2506.19237

Boundary layer profiles of positive solutions for logistic equation with sublinear nonlinearity on the boundary
In this paper, we consider the logistic elliptic equation $-Δu = u- u^{p}$ in a smooth bounded domain $Ω\subset \mathbb{R}^{N}$, $N\geq2$, equipped with the sublinear Neumann boundary condition $\frac{\partial u}{\partial ν} = μu^{q}$ on $\partial Ω$, where $0

Google Cloud says its Universal Ledger, a layer-1 blockchain for financial products, is in a private testnet, and more details will be revealed at a later date (Danny Park/The Block)
https://www.theblock.co/post/368399/google-cloud-blockchain-gcul

@… Hi Sean. I’ve been doing science all night, and I think I’ve uncovered a new layer to Autechre (the “tapestry behind the cotton wool”, as Virgina Woolf might put it.) Please bear with me as I explain:
A = 1
U = 21
T = 20
E = 5
C = 3
H = 8
R = 18
E = 5
− [1, 21, 20, 5, 3, 8, 18, 5]
Sum = 81
Your name, Se…

FAFO: Over 1 million TPS on a single node running EVM while still Merkleizing every block
Ryan Zarick, Isaac Zhang, Daniel Wong, Thomas Kim, Bryan Pellegrino, Mignon Li, Kelvin Wong
https://arxiv.org/abs/2507.10757

FAFO: Over 1 million TPS on a single node running EVM while still Merkleizing every block
Current blockchain execution throughput is limited by data contention, reducing execution layer parallelism. Fast Ahead-of-Formation Optimization (FAFO) is the first blockchain transaction scheduler to address this problem by reordering transactions before block formation for maximum concurrency. FAFO uses CPU-optimized cache-friendly Bloom filters to efficiently detect conflicts and schedule parallel transaction execution at high throughput and low overhead. We integrate the Rust EVM client …

Game-Theoretic Gradient Control for Robust Neural Network Training
Maria Zaitseva, Ivan Tomilov, Natalia Gusarova
https://arxiv.org/abs/2507.19143 https://…

Game-Theoretic Gradient Control for Robust Neural Network Training
Feed-forward neural networks (FFNNs) are vulnerable to input noise, reducing prediction performance. Existing regularization methods like dropout often alter network architecture or overlook neuron interactions. This study aims to enhance FFNN noise robustness by modifying backpropagation, interpreted as a multi-agent game, and exploring controlled target variable noising. Our "gradient dropout" selectively nullifies hidden layer neuron gradients with probability 1 - p during backpropagation, w…

KKT-based optimality conditions for neural network approximation
Vinesha Peiris, Nadezda Sukhorukova, Julien Ugon
https://arxiv.org/abs/2506.17305 https://…

KKT-based optimality conditions for neural network approximation
In this paper, we obtain necessary optimality conditions for neural network approximation. We consider neural networks in Manhattan ($l_1$ norm) and Chebyshev ($\max$ norm). The optimality conditions are based on neural networks with at most one hidden layer. We reformulate nonsmooth unconstrained optimisation problems as larger dimension constrained problems with smooth objective functions and constraints. Then we use KKT conditions to develop the necessary conditions and present the optimalit…

This https://arxiv.org/abs/2505.17282 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Attention with Trained Embeddings Provably Selects Important Tokens
Token embeddings play a crucial role in language modeling but, despite this practical relevance, their theoretical understanding remains limited. Our paper addresses the gap by characterizing the structure of embeddings obtained via gradient descent. Specifically, we consider a one-layer softmax attention model with a linear head for binary classification, i.e., $\texttt{Softmax}( p^\top E_X^\top ) E_X v = \frac{ \sum_{i=1}^T \exp(p^\top E_{x_i}) E_{x_i}^\top v}{\sum_{j=1}^T \exp(p^\top E_{x_{j…

Efficient and Fault-Tolerant Memristive Neural Networks with In-Situ Training
Santlal Prajapat, Manobendra Nath Mondal, Susmita Sur-Kolay
https://arxiv.org/abs/2507.20193 https:…

Efficient and Fault-Tolerant Memristive Neural Networks with In-Situ Training
Neuromorphic architectures, which incorporate parallel and in-memory processing, are crucial for accelerating artificial neural network (ANN) computations. This work presents a novel memristor-based multi-layer neural network (memristive MLNN) architecture and an efficient in-situ training algorithm. The proposed design performs matrix-vector multiplications, outer products, and weight updates in constant time $\mathcal{O}(1)$, leveraging the inherent parallelism of memristive crossbars. Each s…

Monopole Traps for Position-Based Information Coding
Prakash Timsina, Andres Chappa, Deema Alyones, Boris Kiefer, Ludi Miao
https://arxiv.org/abs/2507.22315 https://

Monopole Traps for Position-Based Information Coding
We propose a spin-ice-based heterostructure capable of encoding magnetic monopole quasiparticle positions for non-volatile information storage applications. Building upon two-dimensional magnetic monopole gases formed at the interface between 2-in-2-out spin ice and all-in-all-out antiferromagnetic pyrochlore iridate, the design introduces a 3-in-1-out/1-in-3-out fragmented barrier layer into the spin-ice matrix, defining two energetically stable monopole traps. The occupancy of these traps can…

Crosslisted article(s) found for physics.geo-ph. https://arxiv.org/list/physics.geo-ph/new
[1/1]:
- Magnetic reversals in a geodynamo model with a stably-stratified layer
Nicol\'as Pablo M\"uller, Christophe Gissinger, Fran\c{c}ois P\'etr\'elis

Electromagnetic responses of bilayer excitonic insulators
Yuelin Shao, Hao Shi, Xi Dai
https://arxiv.org/abs/2509.02142 https://arxiv.org/pdf/2509.02142

Electromagnetic responses of bilayer excitonic insulators
We investigate the electromagnetic responses of a bilayer excitonic insulators (EI) and identify two types of collective modes: (1) Two gapped plasmon modes couple to the layer symmetric gauge field. The transverse mode is nearly dispersionless in the long-wavelength limit, while the longitudinal mode, accounting for total charge fluctuations, has a linear dispersion with velocity proportional to two dimensional (2D) electrical polarizability. (2) A gapless phase (Goldstone) mode and a gapp…

Replaced article(s) found for physics.med-ph. https://arxiv.org/list/physics.med-ph/new
[1/1]:
- Cerebral blood flow monitoring using a deep learning implementation of the two-layer DCS analytic...
Pan, Li, Zhang, Mollins, Wang, Erdogan, Hua, Zang, Finlayson, Henderson, Li

Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon
Tongtong Liang, Dan Qiao, Yu-Xiang Wang, Rahul Parhi
https://arxiv.org/abs/2506.20779

Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon
We study the implicit bias of flatness / low (loss) curvature and its effects on generalization in two-layer overparameterized ReLU networks with multivariate inputs -- a problem well motivated by the minima stability and edge-of-stability phenomena in gradient-descent training. Existing work either requires interpolation or focuses only on univariate inputs. This paper presents new and somewhat surprising theoretical results for multivariate inputs. On two natural settings (1) generalization g…

Early Emission from Double Detonation Type Ia Supernovae
Anthony L. Piro, Ehud Nakar
https://arxiv.org/abs/2507.14290 https://arxiv.o…

Early Emission from Double Detonation Type Ia Supernovae
A popular model for Type Ia supernovae (SNe Ia) is the detonation of a CO white dwarf (WD) that is triggered by the prior detonation of a thin surface layer of helium, known as a double detonation (DD). We explore the unique early electromagnetic signatures that are expected from collision of the CO detonation with the He detonation. The three features are (1) a shock breakout flash, (2) a stage of planar shock breakout cooling, and finally (3) shock cooling emission from the thermal energy rel…

Laser-induced ultrafast structural transformations in thin Fe layer revealed by time-resolved X-ray diffraction
O. Liubchenko, J. Antonowicz, K. Sokolowski-Tinten, P. Zalden, R. Minikayev, I. Milov, T. J. Albert, C. Bressler, M. Chojnacki, P. D{\l}u\.zewski, P. Dzi\k{e}gielewski, A. Rodriguez-Fernandez, K. Fronc, W. Gawe{\l}da, K. Georgarakis, A. L. Greer, I. Jacyna, R. W. E. van de Kruijs, R. Kami\'nski, D. Khakhulin, D. Klinger, K. Kosyl, K. Kubicek, A. Olczak, N. T. Panagiotopou…

Laser-induced ultrafast structural transformations in thin Fe layer revealed by time-resolved X-ray diffraction
The ultrafast response of iron lattice to sub-ps pulsed laser-induced heating has been investigated using time-resolved XRD in the partial melting regime. Strong electron-phonon coupling in Fe leads to rapid heating within 1-2 ps post laser-irradiation, followed by lattice expansion and melting on the 2-5 ps timescale. A tetragonal distortion of the remaining bcc-phase emerges at 6 ps and the unit-cell volume increases up to a value characteristic for the bcc-Fe phase. Under the experimental co…

Circle reports Q2 revenue up 53% YoY to $658M, USDC circulation up 90% YoY to $61.3B, a $482M net loss, and unveils Arc, a stablecoin-focused Layer-1 blockchain (James Hunt/The Block)
https://www.theblock.co/post/366540/circle-stablecoin-fo…

Layer-Wise Analysis of Self-Supervised Representations for Age and Gender Classification in Children's Speech
Abhijit Sinha, Harishankar Kumar, Mohit Joshi, Hemant Kumar Kathania, Shrikanth Narayanan, Sudarsana Reddy Kadiri
https://arxiv.org/abs/2508.10332

Layer-Wise Analysis of Self-Supervised Representations for Age and Gender Classification in Children's Speech
Children's speech presents challenges for age and gender classification due to high variability in pitch, articulation, and developmental traits. While self-supervised learning (SSL) models perform well on adult speech tasks, their ability to encode speaker traits in children remains underexplored. This paper presents a detailed layer-wise analysis of four Wav2Vec2 variants using the PFSTAR and CMU Kids datasets. Results show that early layers (1-7) capture speaker-specific cues more effectivel…

The gauge theory dual of the bilayer XY model with second order Josephson coupling
Pye Ton How, Sungkit Yip
https://arxiv.org/abs/2507.19401 https://arxiv.…

The gauge theory dual of the bilayer XY model with second order Josephson coupling
We formulate a duality transformation for a bilayer XY model where the layers are coupled by second order Josephson effect, which favors inter-layer phase difference of either $0$ or $π$. The model may represent a bilayer superconductor or a spin-1 ferromagnetic Bose gas in the easy-plane limit. The second order Josephson term is mapped to a U(1) gauge field, known to be trivially confining in two dimensions, and we argue that a Coulomb-gas analysis is not applicable to the dual theory. Instea…

The Secure Overview and Analysis OF 3GPP MAC CE
Jin Cao, Yuanyuan Yang, Ruhui Ma, Sheng Li, Hui Li
https://arxiv.org/abs/2506.09502 https://

The Secure Overview and Analysis OF 3GPP MAC CE
To more effectively control and allocate network resources, MAC CE has been introduced into the network protocol, which is a type of control signaling located in the MAC layer. Since MAC CE lacks encryption and integrity protection mechanisms provided by PDCP, the control signaling carried by MAC CE is vulnerable to interception or tampering by attackers during resource scheduling and allocation. Currently, the 3GPP has analyzed the security risks of Layer 1/Layer 2 Triggered Mobility (LTM), wh…

Sharp uniform approximation for spectral Barron functions by deep neural networks
Yulei Liao, Pingbing Ming, Hao Yu
https://arxiv.org/abs/2507.06789 https:…

Sharp uniform approximation for spectral Barron functions by deep neural networks
This work explores the neural network approximation capabilities for functions within the spectral Barron space $\mathscr{B}^s$, where $s$ is the smoothness index. We demonstrate that for functions in $\mathscr{B}^{1/2}$, a shallow neural network (a single hidden layer) with $N$ units can achieve an $L^p$-approximation rate of $\mathcal{O}(N^{-1/2})$. This rate also applies to uniform approximation, differing by at most a logarithmic factor. Our results significantly reduce the smoothness requi…

Replaced article(s) found for physics.app-ph. https://arxiv.org/list/physics.app-ph/new
[1/1]:
- Tailoring 4H-SiC Surface Electronic States by Atomic-Layer Deposition for Ideal Peta-Ohm Resistors
Xi, Li, Li, Su, Mao, Xu, Hao, Fang, Cui

Symmetry-breaking bifurcation of periodic solutions for a free-boundary tumor model
Wenhua He, Mingxin Wang, Ruixiang Xing
https://arxiv.org/abs/2508.19954 https://

Symmetry-breaking bifurcation of periodic solutions for a free-boundary tumor model
In this paper, we consider a free boundary multi-layer tumor model that incorporates a $T-$periodic provision of external nutrients $Φ(t)$. The simplified model contains three parameters: the mean of periodic external nutrients $Φ(t)$, the threshold concentration $\widetildeσ$ for proliferation and the cell to cell adhesiveness coefficient $γ$. We first study the flat solution and give a complete classification about $\frac{1}{T} \int_0^T Φ(t) d t$ and $\widetildeσ$ according to global st…

TaDiCodec: Text-aware Diffusion Speech Tokenizer for Speech Language Modeling
Yuancheng Wang, Dekun Chen, Xueyao Zhang, Junan Zhang, Jiaqi Li, Zhizheng Wu
https://arxiv.org/abs/2508.16790

TaDiCodec: Text-aware Diffusion Speech Tokenizer for Speech Language Modeling
Speech tokenizers serve as foundational components for speech language models, yet current designs exhibit several limitations, including: 1) dependence on multi-layer residual vector quantization structures or high frame rates, 2) reliance on auxiliary pre-trained models for semantic distillation, and 3) requirements for complex two-stage training processes. In this work, we introduce the Text-aware Diffusion Transformer Speech Codec (TaDiCodec), a novel approach designed to overcome these cha…

Simulation of dark photon sensitivity in $\eta \rightarrow \gamma e^ e^-$ at HIAF
Zaiba Mushtaq, Rong Wang, Xiaolin Kang, Yang Liu, Ye Tian, Xiong He, Hao Qiu, Xurong Chen
https://arxiv.org/abs/2506.11733

Simulation of dark photon sensitivity in $η\rightarrow γe^+e^-$ at HIAF
We present a simulation study of dark photon sensitivity in a suggested $η$ factory experiment at Huizhou. The vast number of $η$ mesons are produced by bombarding the high-intensity HIAF proton beam on a multi-layer target of light nucleus. The kinematic energy of the beam is at 1.8 GeV. For a prior experiment of one-month running, about $5.9 \times 10^{11}$ $η$ samples would be collected, providing substantial data for a sound statistical analysis. A compact spectrometer based on the full …

XR-NPE: High-Throughput Mixed-precision SIMD Neural Processing Engine for Extended Reality Perception Workloads
Tejas Chaudhari, Akarsh J., Tanushree Dewangan, Mukul Lokhande, Santosh Kumar Vishvakarma
https://arxiv.org/abs/2508.13049

XR-NPE: High-Throughput Mixed-precision SIMD Neural Processing Engine for Extended Reality Perception Workloads
This work proposes XR-NPE, a high-throughput Mixed-precision SIMD Neural Processing Engine, designed for extended reality (XR) perception workloads like visual inertial odometry (VIO), object classification, and eye gaze extraction. XR-NPE is first to support FP4, Posit (4,1), Posit (8,0), and Posit (16,1) formats, with layer adaptive hybrid-algorithmic implementation supporting ultra-low bit precision to significantly reduce memory bandwidth requirements, and accompanied by quantization-aware …

Interaction-Driven Giant Electrostatic Modulation of Ion Permeation in Atomically Small Capillaries
Dhal Biswabhusan, Yechan Noh, Sanat Nalini Paltasingh, Chandrakar Naman, Siva Sankar Nemala, Rathi Aparna, Kaushik Suvigya, Andrea Capasso, Saroj Kumar Nayak, Li-Hsien Yeh, Kalon Gopinadhan
https://arxiv.org/abs/2507.00536

Interaction-Driven Giant Electrostatic Modulation of Ion Permeation in Atomically Small Capillaries
Manipulating the electrostatic double layer and tuning the conductance in nanofluidic systems at salt concentrations of 100 mM or higher has been a persistent challenge. The primary reasons are (i) the short electrostatic proximity length, ~3-10 Å, and (ii) difficulties in fabricating atomically small capillaries. Here, we successfully fabricate in-plane vermiculite laminates with transport heights of ~3-5 Å, which exhibit a cation selectivity close to 1 even at a 1000 mM concentration, sugge…

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs
Ziyue Li, Yang Li, Tianyi Zhou
https://arxiv.org/abs/2507.07996 https://arxiv.org/pdf/2507.07996 https://arxiv.org/html/2507.07996
arXiv:2507.07996v1 Announce Type: new
Abstract: Can a pretrained neural network adapt its architecture to different inputs without any finetuning? Do we need all layers for simple tasks, and are they adequate for challenging tasks? We found that the layers of a pretrained large language model (LLM) can be manipulated as separate modules to build a better and even shallower model customized for each test sample. In particular, each layer from the pretrained model can be skipped/pruned or repeated multiple times as recurrent neural networks (RNN), and stacked with others in arbitrary orders, yielding a chain-of-layers (CoLa) per sample. This compositional space greatly expands the scope of existing works on looped/recurrent pretrained modules, layer pruning, or early-exit networks. We develop a Monte Carlo Tree Search (MCTS) protocol to explore and identify the optimal CoLa for each sample from math and commonsense reasoning benchmarks. Compared to a static model of a fixed depth, CoLa allows shortcut paths (fast thinking), recurrence of the same layer(s) (slow thinking), and combining both, offering more flexible, dynamic architectures for different inputs. We conduct an extensive analysis of the MCTS-optimized CoLa, which leads to two key findings: (1) For >75% of samples with correct predictions by the original LLM, we can find shorter CoLa, suggesting a large space for improving inference efficiency; (2) For >60% of samples with originally incorrect predictions, we can identify CoLa achieving correct predictions, suggesting a large space of performance enhancement. Our results highlight the shortcomings of using a fixed architecture of pre-trained LLMs for inference on different samples and pave the way to unlock the generalization power of test-time depth adaptation.
toXiv_bot_toot

Replaced article(s) found for cs.ET. https://arxiv.org/list/cs.ET/new
[1/1]:
- Fortifying the Agentic Web: A Unified Zero-Trust Architecture Against Logic-layer Threats
Ken Huang, Yasir Mehmood, Hammad Atta, Jerry Huang, Muhammad Zeeshan Baig, Sree Bhargavi Balija

Crosslisted article(s) found for cond-mat.soft. https://arxiv.org/list/cond-mat.soft/new
[1/1]:
- Diffuse-Layer Capacitance at the Potential of Zero Charge in Binary Mixtures
Yuki Uematsu

Replaced article(s) found for physics.flu-dyn. https://arxiv.org/list/physics.flu-dyn/new
[1/1]:
Physics-Informed Priors with Application to Boundary Layer Velocity

Evidence of .Ia Supernova Detonations in 3D Hydrodynamical Simulations of Double Degenerate Mergers
Uri Pierre Burmester, Lilia Ferrario, R\"udiger Pakmor, Ivo R. Seitenzahl
https://arxiv.org/abs/2507.08237

Evidence of .Ia Supernova Detonations in 3D Hydrodynamical Simulations of Double Degenerate Mergers
We report detailed 3D simulations of 1.1 $\mathrm{M_{\odot}}$ Oxygen-Neon (ONe) white dwarfs (WDs) merging with a 0.35 $\mathrm{M_{\odot}}$ helium WD, conducted with the moving-mesh hydrodynamic code AREPO. The simulations utilise self-consistent chemical profiles for the primary WD which were generated by a stellar evolution code incorporating the effects of semi-degenerate carbon burning. We find that a helium detonation is ignited at the base of the helium layer, starting a thermonuclear run…

Replaced article(s) found for nlin.PS. https://arxiv.org/list/nlin.PS/new
[1/1]:
- Evolution of internal cnoidal waves with local defects in a two-layer fluid with rotation
Korsarun Nirunwiroj, Dmitri Tseluiko, Karima Khusnutdinova

Replaced article(s) found for eess.IV. https://arxiv.org/list/eess.IV/new/
[1/1]:
Variable Rate Learned Wavelet Video Coding using Temporal Layer Adaptivity

Quantum Mechanical Approach for Modeling of Ternary Based Strained-Layer Superlattice
Arash Dehzangi, Jiakai Li
https://arxiv.org/abs/2507.12813 https://…

Quantum Mechanical Approach for Modeling of Ternary Based Strained-Layer Superlattice
Ternary-based InAs/InAs1-xSbx Strained-Layer Superlattice (SLS)material with type-II band alignment belongs to the 6.1 A family with reasonably small lattice mismatch with GaSb substrate for epitaxial growth. InAs/InAs1-xSbx SLS have been proven to have more advantages such as longer carrier lifetime, better control on growth and manufacturability, and being considered as an alternative material system for infrared photodetectors. In this article a quantum mechanical based modelling on electron…

Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
Krishnakumar Balasubramanian, Nathan Ross
https://arxiv.org/abs/2507.12686

Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
We study the Finite-Dimensional Distributions (FDDs) of deep neural networks with randomly initialized weights that have finite-order moments. Specifically, we establish Gaussian approximation bounds in the Wasserstein-$1$ norm between the FDDs and their Gaussian limit assuming a Lipschitz activation function and allowing the layer widths to grow to infinity at arbitrary relative rates. In the special case where all widths are proportional to a common scale parameter $n$ and there are $L-1$ hid…

Replaced article(s) found for nlin.SI. https://arxiv.org/list/nlin.SI/new
[1/1]:
- Evolution of internal cnoidal waves with local defects in a two-layer fluid with rotation
Korsarun Nirunwiroj, Dmitri Tseluiko, Karima Khusnutdinova

Estimation of Electron Screening Potential in the 6Li(d,{\alpha})4He Reaction Using Multi-Layer Perceptron Neural Network
D. Chattopadhyay
https://arxiv.org/abs/2506.08044

Estimation of Electron Screening Potential in the 6Li(d,α)4He Reaction Using Multi-Layer Perceptron Neural Network
Reactions between light charged nuclei at sub-Coulomb energies are crucial in astrophysical environments, but accurate cross-section measurements are hindered by electron screening. Traditional methods, including polynomial extrapolation and the Trojan Horse Method, often yield screening potentials exceeding adiabatic predictions. Building on the success of an MLP-based Artificial Neural Network (ANN) for the 6Li(p, α)3He reaction [1], this work applies the same approach to the 6Li(d, α)4He r…

Studies on the effect of low-fluence proton and neutron irradiation on n-type LGADs
Veronika Kraus, Marcos Fernandez Garcia, Salvador Hidalgo, Michael Moll, Jairo Villegas
https://arxiv.org/abs/2508.06282

Studies on the effect of low-fluence proton and neutron irradiation on n-type LGADs
The presented study investigates the effects of low fluences from $5\times10^{12}$ up to $1\times10^{14}$ particles/cm$^{2}$ of 60MeV proton and neutron irradiation on n-type Low Gain Avalanche Detectors (nLGADs). An nLGAD is a silicon sensor with a highly doped gain layer that enables controlled charge multiplication via impact ionization. In contrast to the well-established p-type LGADs for high-energy physics (HEP) applications, nLGADs are optimized for the detection of low-penetrating parti…

Qubic, a layer-1 blockchain project that pools mining resources, has been trying a 51% attack on Monero and says it succeeded, causing Monero's price to fall (Adrian Zmudzinski/Cointelegraph)
https://cointelegraph.com/news/monero-qubic-selfish-mining-51-perce…

Statistical State Dynamics based study of turbulence in Eady fronts. Part 1. Instability
Eojin Kim, Brian F. Farrell
https://arxiv.org/abs/2506.11993 https…

Statistical State Dynamics based study of turbulence in Eady fronts. Part 1. Instability
The streamwise roll and streak structure (RSS) is prominent in observations of the planetary boundary layer in the atmosphere and ocean and in unstratified wall-bounded shear flows. Although the RSS in these systems is structurally similar, the mechanism forming and maintaining the RSS in both remains controversial. This study demonstrates that the same turbulence-sustaining mechanism identified to underlie the RSS in the Statistical State Dynamics (SSD) formulation of unstratified wall-bounded…

Replaced article(s) found for cond-mat.soft. https://arxiv.org/list/cond-mat.soft/new
[1/1]:
- Poisson-Nernst-Planck charging dynamics of an electric double layer capacitor: symmetric and asym...
Ivan Palaia, Adelchi J. Asta, Megh Dutta, Patrick B. Warren, Benjamin Rotenberg…

Crosslisted article(s) found for cond-mat.supr-con. https://arxiv.org/list/cond-mat.supr-con/new
[1/1]:
- Correlated phases in rhombohedral N-layer graphene
Arsen Herasymchuk, Sergei G. Sharapov, Oleg V. Yazyev, Yaroslav Zhumagulov

Sources: Stripe appoints Paradigm co-founder Matt Huang to serve as CEO of its planned Layer-1 blockchain Tempo; a source says Huang will remain at Paradigm (Fortune)
https://fortune.com/crypto/2025/08/12/matt-huang-paradigm-stripe-tempo-blockchain-ceo/…

Exclusive: Top crypto VC Matt Huang to lead Stripe blockchain Tempo as CEO, stay at Paradigm
Huang serves on Stripe’s board, and his VC firm Paradigm is helping incubate the fintech’s blockchain.

Enhanced Performance of FeFET Gate Stack via Heterogeneously co-doped Ferroelectric HfO$_2$ Films
Shouzhuo Yang, David Lehninger, Peter Reinig, Fred Sch\"one, Raik Hoffmann, Konrad Seidel, Maximilian Lederer, Gerald Gerlach
https://arxiv.org/abs/2508.16768

Enhanced Performance of FeFET Gate Stack via Heterogeneously co-doped Ferroelectric HfO$_2$ Films
In this work, we explore the impact of spatially controlled Zr and Al heterogeneous co-doping in HfO$_2$ thin films tailored for metal-ferroelectric-insulator-semiconductor (MFIS) gate stacks of ferroelectric field effect transistors (FeFETs). By precisely modulating the vertical arrangement of Zr and Al dopants during atomic layer deposition, we introduce deliberate compositional gradients that affect crystallization dynamics during subsequent annealing. This strategy enables us to systematica…

Growth rate and energy dissipation in wind-forced breaking waves
Nicol\`o Scapin, Jiarong Wu, J. Thomas Farrar, Bertrand Chapron, St\'ephane Popinet, Luc Deike
https://arxiv.org/abs/2506.17802

Growth rate and energy dissipation in wind-forced breaking waves
We investigate the energy growth and dissipation of wind-forced breaking waves using direct numerical simulations of the coupled air-water Navier-Stokes equations. We vary the wind friction velocity over the wave speed $u_\ast/c$ up to 1. A turbulent wind boundary layer drives the growth of a pre-existing narrowband wave field until it breaks and transfers energy into the water column. Under sustained wind forcing, the wave field then resumes growth. We separately analyze energy transfers durin…

Stoner Transition at Finite Temperature in a 2D Isotropic Fermi Liquid
R. David Mayrhofer, Megan Schoenzeit, Andrey V. Chubukov
https://arxiv.org/abs/2507.16026

Stoner Transition at Finite Temperature in a 2D Isotropic Fermi Liquid
We present the results of a mean-field analysis of the temperature evolution of a ferromagnetic Stoner transition in a two-dimensional (2D) system with an isotropic dispersion $\varepsilon_k \propto k^{2α}$, which for $α>1$ models flat dispersions in various multi-layer graphene systems in a displacement field. This study is an extension to a finite $T$ of previous studies at $T=0$, which found both first-order and second-order Stoner transitions, depending on the value of $α$ and special be…

Replaced article(s) found for cond-mat.supr-con. https://arxiv.org/list/cond-mat.supr-con/new
[1/1]:
- Enhanced Superconductivity and Mixed-dimensional Behaviour in Infinite-layer Samarium Nickelate T...
Mingwei Yang, et al.

Trimer superfluidity of antiparallel dipolar excitons in a bilayer heterostructure
Pradyumna P. Belgaonkar, Michal Zimmerman, Snir Gazit, Dror Orgad
https://arxiv.org/abs/2507.15938

Trimer superfluidity of antiparallel dipolar excitons in a bilayer heterostructure
We study the phase diagram of a bilayer of antiparallel dipolar excitons with a 1:2 density ratio between the layers, as a function of temperature and density. Using quantum Monte Carlo simulations, we show that such a system supports the formation of trimers, namely, three-exciton bound states consisting of a single dipole in one layer and two dipoles in the second layer. At sufficiently low temperatures and densities, these trimers condense into a trimer superfluid phase. Increasing the excit…

Willchain: Decentralized, Privacy-Preserving, Self-Executing, Digital Wills
Jovonni L. PHarr
https://arxiv.org/abs/2507.03694 https://

Willchain: Decentralized, Privacy-Preserving, Self-Executing, Digital Wills
This work presents a novel decentralized protocol for digital estate planning that integrates advances distributed computing, and cryptography. The original proof-of-concept was constructed using purely solidity contracts. Since then, we have enhanced the implementation into a layer-1 protocol that uses modern interchain communication to connect several heterogeneous chain types. A key contribution of this research is the implementation of several modern cryptographic primitives to support vari…

The effect of fiber plasticity on domain formation in soft biological composites -- Part II: An imperfection analysis
Dimitris Iordanidis, Fernanda F. Fontenele, Konstantinos Poulios, Michalis Agoras, Nikolaos Bouklas
https://arxiv.org/abs/2507.14764

The effect of fiber plasticity on domain formation in soft biological composites -- Part II: An imperfection analysis
The main objective of this work is to numerically investigate the effect of geometric imperfections on the macroscopic response and domain formation in soft biological composites that exhibit plasticity in the stiff (fiber) phase.This work builds on the corresponding bifurcation analysis in Part I of this study for simple laminates with perfectly flat layers under plane strain, nonmonotonic loading conditions, aligned with the layer direction. The post-bifurcation solution obtained in Part I fo…

Replaced article(s) found for physics.med-ph. https://arxiv.org/list/physics.med-ph/new
[1/1]:
- Unsupervised deep learning model for fast energy layer pre-selection of delivery-efficient proton...
Yang, Liu, Zhong, Dao, Qian, Shi, Tang, Luo, Kong, Liu

Electronic structure of SLSiN under charge density modulation
Ashkan Shekaari
https://arxiv.org/abs/2507.15883 https://arxiv.org/pdf/…

Electronic structure of SLSiN under charge density modulation
First-principles density-functional theory calculations were carried out to assess how incremental unit-cell charging alters the electronic behavior of SLSiN (single-layer Si$_3$N$_4$). The net charge per cell was systematically tuned from $n\,=\,0$ (the neutral/reference configuration) to $n\,=\,\pm\,1,\pm\,2$, and $\pm\,3$ elementary charges, and for each charged configuration the band structure and density of states were evaluated at the PBE level. In its neutral state, SLSiN exhibits zero e…

Boundary layers in quasi-static magnetoconvection with a vertical field and their implications for heat transport
Talal AlRefae, Michael A. Calkins
https://arxiv.org/abs/2508.08623

Boundary layers in quasi-static magnetoconvection with a vertical field and their implications for heat transport
Heat transport in quasi-static magnetoconvection with a vertical magnetic field in a plane layer geometry is investigated with direct numerical simulations and asymptotic theory in the limit of large Chandrasekhar number ($Q$). It is shown that thermal and magnetic boundary layers with thickness $O(Q^{-1/6})$, of the same order as the horizontal scale of the convection, are persistent over the range of investigated parameters. Thermal boundary layer control of the heat transport indicates that …

Replaced article(s) found for cond-mat.mes-hall. https://arxiv.org/list/cond-mat.mes-hall/new
[1/1]:
- Evaluating Metal-Organic Precursors for Focused Ion Beam Induced Deposition through Solid-Layer D...
Jany, Madajska, Butrymowicz-Kubiak, Krok, Szyma\'nsk…

Vortex topology in the lee of a 6:1 prolate spheroid
Marc Plasseraud, Krishnan Mahesh
https://arxiv.org/abs/2507.03187 https://arxiv.…

Vortex topology in the lee of a 6:1 prolate spheroid
A large scale parametric study of the flow over the prolate spheroid is presented to understand the effect of Reynolds number and angle of attack on the separation, the wake formation and the loads. Large-Eddy Simulation is performed for six Reynolds numbers ranging from Re = 0.15M to Re = 4M and for eight angles of attack ranging from 10 degrees to 90 degrees. For all the cases considered, the boundary layer separates symmetrically and forms a recirculation region. Several distinct flow topolo…

Current Crowding in a High-Efficiency Black Phosphorus Light-Emitting Diode Using a Reflective Back Contact
Julien Brodeur, \'Elo\"ise Rahier, Mathieu Chartray-Pronovost, \'Etienne Robert, Oussama Moutanabbir, St\'ephane K\'ena-Cohen
https://arxiv.org/abs/2506.09835 …

Current Crowding in a High-Efficiency Black Phosphorus Light-Emitting Diode Using a Reflective Back Contact
We demonstrate a high-performance mid-infrared (MIR) light-emitting diode (LED) based on a black phosphorus (b-P)/n-MoS$_2$ heterojunction. A gold back contact combined with a rhenium-doped n-type MoS$_2$ layer is used to enhance light extraction. The device shows a MIR peak external quantum efficiency (EQE) of (1.6 $\pm$ 0.2) % at room temperature and a record (7.0 $\pm$ 0.5) % EQE at 77 K, with a maximum radiant power density of (108 $\pm$ 8) W/cm2. Finite-element simulations highlight the im…

Replaced article(s) found for cond-mat.mes-hall. https://arxiv.org/list/cond-mat.mes-hall/new/
[1/1]:
Layer Coherence Origin of Planar Hall Effect: from Charge to Multipole and Valley

Physics-Informed Neural Networks for the Korteweg-de Vries Equation for Internal Solitary Wave Problem: Forward Simulation and Inverse Parameter Estimation
Ming Kang, Hang Li, Qiwen Tan, Zhan Wang, Ruipeng Li, Junfang Zhao, Hui Xiang, Dixia Fan
https://arxiv.org/abs/2506.14236

Physics-Informed Neural Networks for the Korteweg-de Vries Equation for Internal Solitary Wave Problem: Forward Simulation and Inverse Parameter Estimation
Physics-informed neural networks (PINNs) have emerged as a transformative framework for addressing operator learning and inverse problems involving the Korteweg-de Vries (KdV) equation for internal solitary waves. By integrating physical constraints with data-driven optimization, PINNs overcome the critical challenges of parameter unmeasurability in the KdV equation for internal solitary waves in two-layer fluid systems. This work addresses two problems: (1) Operator learning constructs a mappi…

Compressible boundary layers over isotropic porous surfaces
Ludovico Foss\`a, Pierre Ricco
https://arxiv.org/abs/2508.10422 https://arxiv.org/pdf/2508.1042…

Compressible boundary layers over isotropic porous surfaces
A compressible laminar boundary layer developing over an isotropic porous substrate is investigated by asymptotic and numerical methods. The substrate is modeled as an array of cubes. The momentum and enthalpy balance equations are derived by volume averaging. The self-similar solution proposed by Tsiberkin (2018) [Transp. Porous Media 121(1):109-120] for streamwise-growing permeability is extended to include compressibility, heat conduction and a nonlinear drag. The velocity profile shows an i…

Non-Abelian Chern band in rhombohedral graphene multilayers
Taketo Uchida, Takuto Kawakami, Mikito Koshino
https://arxiv.org/abs/2508.07366 https://arxiv.o…

Non-Abelian Chern band in rhombohedral graphene multilayers
Moiré flat bands in rhombohedral multilayer graphene provide a platform for exploring interaction-driven topological phases, where a single isolated band often forms a Chern band. However, non-Abelian degenerate Chern bands with internal symmetries such as SU($N$) have so far been realized only in highly engineered systems. Here, we show that a doubly degenerate non-Abelian Chern band with Chern number $|C|=1$ emerges spontaneously at filling $ν=2$ in rhombohedral 3-, 4-, and 5-laye…