Tootfinder

Hierarchical Federated Learning for Crop Yield Prediction in Smart Agricultural Production Systems
Anas Abouaomar, Mohammed El hanjri, Abdellatif Kobbane, Anis Laouiti, Khalid Nafil
https://arxiv.org/abs/2510.12727

Hierarchical Federated Learning for Crop Yield Prediction in Smart Agricultural Production Systems
In this paper, we presents a novel hierarchical federated learning architecture specifically designed for smart agricultural production systems and crop yield prediction. Our approach introduces a seasonal subscription mechanism where farms join crop-specific clusters at the beginning of each agricultural season. The proposed three-layer architecture consists of individual smart farms at the client level, crop-specific aggregators at the middle layer, and a global model aggregator at the top le…

Increasing science yield with a twilight observing program with the SCALES instrument at Keck
Isabel J. Kain, Carlos Alvarez, John M. O'Meara, Marc Kassis, Peter Wizinowich, Antonin Bouchez, Jim Lyke, Randy Campbell, Avinash Surendran, Imke de Pater, Katherine de Kleer, Ned Molter, Erin Redwing, Rosalie McGurk, Steph Sallum, Andrew Skemer
https://

Increasing science yield with a twilight observing program with the SCALES instrument at Keck
While astronomical twilight closes the observing window for optical astronomers, the infrared sky remains dark even through sunrise, allowing IR astronomers to observe through twilight. The Slicer Combined with an Array of Lenslets for Exoplanet Spectroscopy (SCALES) instrument is a 2-5 micron coronagraphic integral field spectrograph scheduled to arrive at Keck in early 2026. SCALES has the potential to execute exciting science and support the astronomical community and upcoming NASA missions …

Spontaneous formation of subsystem and bath under accordion-type driving
Suyang Lin, Ming Gong, Congjun Wu
https://arxiv.org/abs/2509.12761 https://arxiv.o…

Spontaneous formation of subsystem and bath under accordion-type driving
Floquet modulations often yield effective Hamiltonians not easily accessible in traditional time-dependent systems, which brings opportunities for exploring novel physics of quantum dynamics. We investigate a Floquet system exhibiting translational symmetry at any fixed time but the spatial periodicity is time-dependent. Such a system is a natural platform for studying thermalization and novel dynamical structures. We find that the single-particle Hilbert space spontaneously develops a structur…

This Year’s Nice Rice Price Marks an 18-year Low Amid a Doubling of Per-Acre Yield https://www.goodnewsnetwork.org/this-years-nice-rice-price-marks-an-18-year-low-amid-a-doubling-of-per-acre-yield/

This Year's Nice Rice Price Marks an 18-year Low Amid a Doubling of Per-Acre Yield
Humanity continues to make advancements with even the most primitive technologies, epitomized by this year's incredible Asian rice crop. 

A Comparison of Selected Image Transformation Techniques for Malware Classification
Rishit Agrawal, Kunal Bhatnagar, Andrew Do, Ronnit Rana, Mark Stamp
https://arxiv.org/abs/2509.10838

A Comparison of Selected Image Transformation Techniques for Malware Classification
Recently, a considerable amount of malware research has focused on the use of powerful image-based machine learning techniques, which generally yield impressive results. However, before image-based techniques can be applied to malware, the samples must be converted to images, and there is no generally-accepted approach for doing so. The malware-to-image conversion strategies found in the literature often appear to be ad hoc, with little or no effort made to take into account properties of execu…

Effect of organic fertilizer and nano calcium spray on growth, yield and storage characteristics of fig fruits cv. waziri
Aram Sabir Ahmed, Mohamad Abdul Aziz Lateef
https://arxiv.org/abs/2507.11578

Effect of organic fertilizer and nano calcium spray on growth, yield and storage characteristics of fig fruits cv. waziri
This study was carried out to estimate the effect of organic fertilizer and Nano Calcium spray on the growth, yield, and storage of fig fruits cv. Waziri. It was conducted in the village of Kani Sard in the Sharbazhir district near the Sitak area. This is about 35 km northeast of the center of Sulaymaniyah. This study was conducted at 54 plants with three-year-old fig trees cultivated using the cordon method during the 2024 growth season. The controlled environment of the plastic house enabled …

Gruden’s feud with the NFL won’t die https://www.arkansasonline.com/news/2025/aug/17/grudens-feud-with-the-nfl-wont-die/

Beyond Gaze Overlap: Analyzing Joint Visual Attention Dynamics Using Egocentric Data
Kumushini Thennakoon, Yasasi Abeysinghe, Bhanuka Mahanama, Vikas Ashok, Sampath Jayarathna
https://arxiv.org/abs/2509.12419

Beyond Gaze Overlap: Analyzing Joint Visual Attention Dynamics Using Egocentric Data
Joint visual attention (JVA) provides informative cues on human behavior during social interactions. The ubiquity of egocentric eye-trackers and large-scale datasets on everyday interactions offer research opportunities in identifying JVA in multi-user environments. We propose a novel approach utilizing spatiotemporal tubes centered on attention rendered by individual gaze and detect JVA using deep-learning-based feature mapping. Our results reveal object-focused collaborative tasks to yield hi…

Signature 0 toric varieties, wall crossings, and cross polytope-like structures
Soohyun Park
https://arxiv.org/abs/2509.13296 https://arxiv.org/pdf/2509.13…

Signature 0 toric varieties, wall crossings, and cross polytope-like structures
We describe the structure of simplicial locally convex fans associated to even-dimensional complete toric varieties with signature 0. They belong to the set of such toric varieties whose even degree Betti numbers yield a gamma vector equal to 0. The gamma vector is an invariant of palindromic polynomials whose nonnegativity lies between unimodality and real-rootedness. It is expected that the cases where the gamma vector is 0 form ``building blocks'' among those where it is nonnegative. This me…

Preference-restricted parking functions
Jasper Bown, Peter Kagey, Alan Kappler, Michael E. Orrison, Jayden Thadani
https://arxiv.org/abs/2507.11701 https:/…

Preference-restricted parking functions
A parking function is a function $π:[n]\to [n]$ whose $i$th-smallest output is at most $i,$ corresponding to a parking procedure for $n$ cars on a one-way street. We refine this concept by introducing preference-restricted parking functions, which are parking functions with codomain restricted to some $S\subseteq[n]$. Particular choices of $S$ yield new combinatorial interpretations of previous results about variant parking procedures, and new results too. In particular we consider prime parki…

Branched Broomrape Detection in Tomato Farms Using Satellite Imagery and Time-Series Analysis
Mohammadreza Narimani, Alireza Pourreza, Ali Moghimi, Parastoo Farajpoor, Hamid Jafarbiglu, Mohsen Mesgaran
https://arxiv.org/abs/2509.10804

Branched Broomrape Detection in Tomato Farms Using Satellite Imagery and Time-Series Analysis
Branched broomrape (Phelipanche ramosa (L.) Pomel) is a chlorophyll-deficient parasitic plant that threatens tomato production by extracting nutrients from the host, with reported yield losses up to 80 percent. Its mostly subterranean life cycle and prolific seed production (more than 200,000 seeds per plant, viable for up to 20 years) make early detection essential. We present an end-to-end pipeline that uses Sentinel-2 imagery and time-series analysis to identify broomrape-infested tomato fie…

MinatoLoader: Accelerating Machine Learning Training Through Efficient Data Preprocessing
Rahma Nouaji, Stella Bitchebe, Ricardo Macedo, Oana Balmau
https://arxiv.org/abs/2509.10712

MinatoLoader: Accelerating Machine Learning Training Through Efficient Data Preprocessing
Data loaders are used by Machine Learning (ML) frameworks like PyTorch and TensorFlow to apply transformations to data before feeding it into the accelerator. This operation is called data preprocessing. Data preprocessing plays an important role in the ML training workflow because if it is inefficiently pipelined with the training, it can yield high GPU idleness, resulting in important training delays. Unfortunately, existing data loaders turn out to waste GPU resources, with $76\%$ GPU idlene…

The Senator Will Not Yield -- REVIEW: 'Charles Sumner: Conscience of a Nation' by Zaakir Tameez (H.W. Brands/The Washington Free Beacon)
https://freebeacon.com/culture/the-senator-will-not-yield/
http://www.memeorandum.com/250810/p18#a250810p18

Uniqueness of tangent planes and (non-)removable singularities at infinity for collapsed translators
Eddygledson Souza Gama, Francisco Mart\'in, Niels Martin M{\o}ller
https://arxiv.org/abs/2509.11473

Uniqueness of tangent planes and (non-)removable singularities at infinity for collapsed translators
We show that mean curvature flow translators may exhibit non-removable singularities at infinity, due to jump discontinuities in their asymptotic profiles, and that oscillation can persist so as to yield a continuum of subsequential limit tangent planes. Nonetheless, we prove that as time $t\to\pm \infty$, any finite entropy, finite genus, embedded, collapsed translating soliton in $\mathbb{R}^3$ converges to a uniquely determined collection of planes. This requires global analysis of quasili…

Model averaging in the space of probability distributions
Emmanouil Androulakis, Georgios I. Papayiannis, Athanasios N. Yannacopoulos
https://arxiv.org/abs/2507.11719

Model averaging in the space of probability distributions
This work investigates the problem of model averaging in the context of measure-valued data. Specifically, we study aggregation schemes in the space of probability distributions metrized in terms of the Wasserstein distance. The resulting aggregate models, defined via Wasserstein barycenters, are optimally calibrated to empirical data. To enhance model performance, we employ regularization schemes motivated by the standard elastic net penalization, which is shown to consistently yield models en…

The iterated Golub-Kahan-Tikhonov method
Davide Bianchi, Marco Donatelli, Davide Furch\`i, Lothar Reichel
https://arxiv.org/abs/2507.12307 https://

The iterated Golub-Kahan-Tikhonov method
The Golub-Kahan-Tikhonov method is a popular solution technique for large linear discrete ill-posed problems. This method first applies partial Golub-Kahan bidiagonalization to reduce the size of the given problem and then uses Tikhonov regularization to compute a meaningful approximate solution of the reduced problem. It is well known that iterated variants of this method often yield approximate solutions of higher quality than the standard non-iterated method. Moreover, it produces more accur…

Bounded powers of edge ideals: symmetric exchange binomials
Takayuki Hibi, Seyed Amin Seyed Fakhari
https://arxiv.org/abs/2507.11815 https://

Bounded powers of edge ideals: symmetric exchange binomials
It has been conjectured that the toric ideal of the base ring of a discrete polymatroid is generated by symmetric exchange binomials. In the present paper, we give several classes of discrete polymatroids which yield toric ideals generated by symmetric exchange binomials. Especially, we are interested in the discrete polymatroids arising from bounded powers of edge ideals of finite graphs.

The Polya-Szego principle in the fractional setting: a glimpse on nonlocal functional inequalities
Alessandro Carbotti
https://arxiv.org/abs/2509.12023 https://

The Polya-Szego principle in the fractional setting: a glimpse on nonlocal functional inequalities
In this survey we present the fractional Polya Szego principle and its main consequences in the study of nonlocal functional inequalities. In particular, we show how symmetrization methods work also in the fractional setting and yield sharp results such as isoperimetric type inequalities. Further developments including stability issues and generalizations in the anisotropic and the Gaussian setting are also discussed.

Inverse design of drying-induced assembly of multicomponent colloidal-particle films using surrogate models
Mayukh Kundu, Michaela Bush, Chris A. Kieslich, Michael P. Howard
https://arxiv.org/abs/2509.10645

Inverse design of drying-induced assembly of multicomponent colloidal-particle films using surrogate models
The properties of films assembled by drying colloidal-particle suspensions depend sensitively on both the particles and the processing conditions, making them challenging to engineer. In this work, we develop and test an inverse-design strategy based on surrogate modeling to identify conditions that yield a target film structure. We consider a two-component hard-sphere colloidal suspension whose designable parameters are the particle sizes, the initial composition of particles, and the drying r…

Rates of convergence for multivariate SDEs driven by L\'evy processes in the small-time stable domain of attraction
Jorge Gonz\'alez C\'azares, David Kramer-Bang
https://arxiv.org/abs/2509.12377

Rates of convergence for multivariate SDEs driven by Lévy processes in the small-time stable domain of attraction
This paper explores the rates of convergence of solutions for multivariate stochastic differential equations (SDEs) driven by Lévy processes within the small-time stable domain of attraction (DoA). Explicit bounds are derived for the uniform Wasserstein distance between solutions of two Lévy-driven SDEs, expressed in terms of driver characteristics. These bounds establish convergence rates in probability for drivers in the DoA, and yield uniform Wasserstein distance convergence for SDEs with …

Haussdorff consistency of MLE in folded normal and Gaussian mixtures
Koustav Mallik
https://arxiv.org/abs/2509.12206 https://arxiv.org/pdf/2509.12206

Haussdorff consistency of MLE in folded normal and Gaussian mixtures
We develop a constant-tracking likelihood theory for two nonregular models: the folded normal and finite Gaussian mixtures. For the folded normal, we prove boundary coercivity for the profiled likelihood, show that the profile path of the location parameter exists and is strictly decreasing by an implicit-function argument, and establish a unique profile maximizer in the scale parameter. Deterministic envelopes for the log-likelihood, the score, and the Hessian yield elementary uniform laws of …

Unlocking Zero-Shot Plant Segmentation with Pl@ntNet Intelligence
Simon Rav\'e, Jean-Christophe Lombardo, Pejman Rasti, Alexis Joly, David Rousseau
https://arxiv.org/abs/2510.12579

Unlocking Zero-Shot Plant Segmentation with Pl@ntNet Intelligence
We present a zero-shot segmentation approach for agricultural imagery that leverages Plantnet, a large-scale plant classification model, in conjunction with its DinoV2 backbone and the Segment Anything Model (SAM). Rather than collecting and annotating new datasets, our method exploits Plantnet's specialized plant representations to identify plant regions and produce coarse segmentation masks. These masks are then refined by SAM to yield detailed segmentations. We evaluate on four publicly avai…

Observation of charmonium sequential suppression in heavy-ion collisions at the Relativistic Heavy Ion Collider
The STAR Collaboration
https://arxiv.org/abs/2509.12842 https://

Observation of charmonium sequential suppression in heavy-ion collisions at the Relativistic Heavy Ion Collider
We report measurements of charmonium sequential suppression in $^{96}_{44}\rm{Ru}$+$^{96}_{44}\rm{Ru}$ and $^{96}_{40}\rm{Zr}$+$^{96}_{40}\rm{Zr}$ collisions at \sqrtsnn\ = 200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The inclusive yield ratio of $ψ$(2S) to J/$ψ$ as a function of transverse momentum is reported, along with the centrality dependence of the double ratio, defined as the $ψ$(2S) to J/$ψ$ ratio in heavy-ion collisions relative to that in $p$+$p…

Localised solution of stochastic Schr\"odinger equation describing simultaneous continuous measurement of position and momentum
Daniel J. Bedingham
https://arxiv.org/abs/2509.11832

Localised solution of stochastic Schrödinger equation describing simultaneous continuous measurement of position and momentum
A stochastic Schrödinger equation is presented to describe simultaneous continuous measurement of the position and momentum of a non-relativistic particle. The equation is solved to yield a state localised in position and momentum contingent on the uncertainty principle. The state is understood as that to which the particle tends after a period of continuous measurement. The solution takes the form of a wave packet of fixed Gaussian shape whose centre undergoes random motion in phase space. It…

Helical Locomotion in Yield Stress Fluids
Farshad Nazari Kourosh Shoele, Hadi Mohammadigoushki
https://arxiv.org/abs/2509.06655 https://arxiv.org/pdf/2509.…

Helical Locomotion in Yield Stress Fluids
We report three stages for locomotion of a helical swimmer in yield stress fluids. In the first stage, the swimmer must overcome material's yield strain to generate rotational motion. However, exceeding the first threshold is not sufficient for locomotion. Only when the viscous forces are sufficiently strong to plastically deform the material to a finite distance away from the swimmer, net locomotion will occur. Once locomotion is underway in the third stage, the yield stress retards swimming a…

SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model
Lin Lin, Jiefeng Long, Zhihe Wan, Yuchi Wang, Dingkang Yang, Shuang Yang, Yueyang Yao, Xu Chen, Zirui Guo, Shengqiang Li, Weiran Li, Hanyu Li, Yaling Mou, Yan Qiu, Haiyang Yu, Xiao Liang, Hongsheng Li, Chao Feng
https://arxiv.org/abs/2510.12709

SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model
Multimodal embedding models aim to yield informative unified representations that empower diverse cross-modal tasks. Despite promising developments in the evolution from CLIP-based dual-tower architectures to large vision-language models, prior works still face unavoidable challenges in real-world applications and business scenarios, such as the limited modality support, unstable training mechanisms, and industrial domain gaps. In this work, we introduce SAIL-Embedding, an omni-modal embedding …

💥 Engineers overcome radiation challenge with custom silicon chips
#electronics

Engineers overcome radiation challenge with custom silicon chips
The Large Hadron Collider (LHC) is tough on electronics. Situated inside a 17-mile-long tunnel that runs in a circle under the border between Switzerland and France, this massive scientific instrument accelerates particles close to the speed of light before smashing them together. The collisions yield tiny maelstroms of particles and energy that hint at answers to fundamental questions about the building blocks of matter.

THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures
Alish Kanani, Lukas Pfromm, Harsh Sharma, Janardhan Rao Doppa, Partha Pratim Pande, Umit Y. Ogras
https://arxiv.org/abs/2508.10691

THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures
Chiplet-based integration enables large-scale systems that combine diverse technologies, enabling higher yield, lower costs, and scalability, making them well-suited to AI workloads. Processing-in-Memory (PIM) has emerged as a promising solution for AI inference, leveraging technologies such as ReRAM, SRAM, and FeFET, each offering unique advantages and trade-offs. A heterogeneous chiplet-based PIM architecture can harness the complementary strengths of these technologies to enable higher perfo…

Durbin to Bondi
in this morning's Senate hearing:
"Although you've been a registered foreign agent for Qatar,
you didn't recuse yourself from signing off on Trump's solicitation of a free jet from the royal family,
even though this gift was clearly illegal.
Connections to Bondi seem to yield more favorable outcomes for defendants."

Aaron Rupar (@atrupar.com)
Durbin to Bondi: "Although you've been a registered foreign agent for Qatar, you didn't recuse yourself from signing off on Trump's solicitation of a free jet from the royal family, even though this gift was clearly illegal. Connections to Bondi seem to yield more favorable outcomes for defendants."

Harvests and Hooky in the Hills: Crop Yield Variability and Gendered School Enrollment in Rwanda
Maxwell Fogler
https://arxiv.org/abs/2510.10780 https://ar…

Harvests and Hooky in the Hills: Crop Yield Variability and Gendered School Enrollment in Rwanda
This paper investigates the trade-off that households in agrarian economies face between immediate production needs and long-term human capital investment. We ask how exogenous agricultural productivity shocks affect primary and secondary school enrollment in Rwanda, a country characterized by a heavy reliance on rain-fed agriculture alongside ambitious development goals. Using a district-level panel dataset for the years 2010-2021, we employ a two-stage least squares (2SLS) instrumental variab…

Magnetic Decay Index Profile and Coronal Mass Ejection Speed
Bernhard Kliem, Georgios Chintzoglou, Tibor T\"or\"ok, Jie Zhang
https://arxiv.org/abs/2510.11889 https://…

Magnetic Decay Index Profile and Coronal Mass Ejection Speed
We study the relationship between the speed of coronal mass ejections (CMEs) and the height profile of the ambient magnetic field, quantified by its decay index, n(h). Our sample is composed of 15 very fast CMEs (Vcme > 1500 km/s; all halo CMEs) and 22 halo CMEs below this speed limit from Solar Cycle 23. The very fast CMEs yield a high correlation of 0.81 between Vcme and the slope of n(h) in a height range above the onset height of the torus instability if one extremely fast outlier, which cl…

Neural Bandit Based Optimal LLM Selection for a Pipeline of Tasks
Baran Atalar, Eddie Zhang, Carlee Joe-Wong
https://arxiv.org/abs/2508.09958 https://arxiv…

Neural Bandit Based Optimal LLM Selection for a Pipeline of Tasks
With the increasing popularity of large language models (LLMs) for a variety of tasks, there has been a growing interest in strategies that can predict which out of a set of LLMs will yield a successful answer at low cost. This problem promises to become more and more relevant as providers like Microsoft allow users to easily create custom LLM "assistants" specialized to particular types of queries. However, some tasks (i.e., queries) may be too specialized and difficult for a single LLM to han…

Sub-Laplacian comparison theorems on Riemannian foliations with minimal leaves and applications
Fabrice Baudoin
https://arxiv.org/abs/2509.13276 https://ar…

Sub-Laplacian comparison theorems on Riemannian foliations with minimal leaves and applications
We prove comparison theorems for the horizontal Laplacian of the Riemannian distance in the context of Riemannian foliations with minimal leaves. This general framework generalizes previous works and allow us to consider the sub-Laplacian of Carnot groups of arbitrary steps. The comparison theorems yield a Bonnet-Myers type theorem, stochastic completeness and Lipschitz regularization property for the sub-Riemannian semigroup.

Starobinsky in Stereo: SKA-CMB Synergy in SBI
Benedikt Schosser, Caroline Heneka, Bj\"orn Malte Sch\"afer
https://arxiv.org/abs/2508.10094 https://

Starobinsky in Stereo: SKA-CMB Synergy in SBI
Modern machine learning techniques can unlock the vast cosmological information encoded in forthcoming Square Kilometre Array (SKA) observations. We show that tomographic 21 cm data from the reionisation era can yield stringent tests of inflationary models - here illustrated with Starobinsky $R+R^2$ inflation. Using a simulation-based inference (SBI) framework, we compare neural summaries (convolutional network and vision transformer) with a traditional power spectrum summary and perform a full…

A Relativity-Based Framework for Statistical Testing Guided by the Independence of Ancillary Statistics: Methodology and Nonparametric Illustrations
Albert Vexler, Douglas Landsittel
https://arxiv.org/abs/2507.11816

A Relativity-Based Framework for Statistical Testing Guided by the Independence of Ancillary Statistics: Methodology and Nonparametric Illustrations
This paper introduces a decision-theoretic framework for constructing and evaluating test statistics based on their relationship with ancillary statistics-quantities whose distributions remain fixed under the null and alternative hypotheses. Rather than focusing solely on maximizing discriminatory power, the proposed approach emphasizes reducing dependence between a test statistic and relevant ancillary structures. We show that minimizing such dependence can yield most powerful (MP) procedures.…

Optimal trap cropping investments to maximize agricultural yield
Matthew H Holden
https://arxiv.org/abs/2508.05896 https://arxiv.org/pdf/2508.05896

Optimal trap cropping investments to maximize agricultural yield
Trap cropping is a pest management strategy where a grower plants an attractive "trap crop" alongside the primary crop to divert pests away from it. We propose a simple framework for optimizing the proportion of a grower's field or greenhouse allocated to a main crop and a trap crop to maximize agricultural yield. We implement this framework using a model of pest movement governed by trap crop attractiveness, the potential yield threatened by pests, and functional relationships between yield lo…

Global existence and decay of small solutions in a viscous half Klein-Gordon equation
Louis Gar\'enaux, Bj\"orn de Rijk
https://arxiv.org/abs/2509.13188 https://…

Global existence and decay of small solutions in a viscous half Klein-Gordon equation
We establish global existence and decay of solutions of a viscous half Klein-Gordon equation with a quadratic nonlinearity considering initial data, whose Fourier transform is small in L1 cap Linfty. Our analysis relies on the observation that nonresonant dispersive effects yield a transformation of the quadratic nonlinearity into a subcritical nonlocal quartic one, which can be controlled by the linear diffusive dynamics through a standard L1 - Linfty argument. This transformation can be reali…

Requirements for Early Quantum Advantage and Quantum Utility in the Capacitated Vehicle Routing Problem
Chinonso Onah, Kristel Michielsen
https://arxiv.org/abs/2509.11469 https:…

Requirements for Early Quantum Advantage and Quantum Utility in the Capacitated Vehicle Routing Problem
We introduce a transparent, encoding-agnostic framework for determining when the Capacitated Vehicle Routing Problem (CVRP) can achieve early quantum advantage. Our analysis shows this is unlikely on noisy intermediate scale quantum (NISQ) hardware even in best case scenarios that use the most qubit-efficient direct encodings. Closed-form resource counts, combined with recent device benchmarks, yield three decisive go/no-go figures of merit: the quantum feasibility point and the qubit- and gate…

Nonreciprocal constitutive laws for oriented active solids
Bal\'azs N\'emeth, Takuya Kobayashi, Ronojoy Adhikari
https://arxiv.org/abs/2509.11430 https://

Nonreciprocal constitutive laws for oriented active solids
We present an overdamped continuum description of oriented active solids in which interactions respect the symmetries of space but do not obey the principle of action and reaction. Taking position and orientation as kinematic variables, we examine the conservation of the linear and angular momentum variables in an elementary volume. We find that nonreciprocal interactions yield, in addition to the areal stresses and moment stresses of classical elasticity, volumetric forces and torques that act…

Mike Johnson tries to sell Americans on the benefits of being occupied (Jarvis DeBerry/MSNBC)
https://www.msnbc.com/opinion/msnbc-opinion/mike-johnson-yield-man-democrats-trump-rcna230141
http://www.memeorandum.com/250910/p43#a250910p43

Random Nonlinear Fusion Frames from Averaged Operator Iterations
James Tian
https://arxiv.org/abs/2509.09927 https://arxiv.org/pdf/2509.09927

Random Nonlinear Fusion Frames from Averaged Operator Iterations
We study random iterations of averaged operators in Hilbert spaces and prove that the associated residuals converge exponentially fast, both in expectation and almost surely. Our results provide quantitative bounds in terms of a single geometric parameter, giving sharp control of convergence rates under minimal assumptions. As an application, we introduce the concept of random nonlinear fusion frames. Here the atoms are generated dynamically from the residuals of the iteration and yield exact s…

Multi-State Modeling of Greenhouse Cucumber Yield Dynamics Under Microclimate Effects
Emiliano Seri, Francesco Biso, Gianluigi Bovesecchi, Nikolaos Katsoulas, Cristina Cornaro
https://arxiv.org/abs/2510.11485

Multi-State Modeling of Greenhouse Cucumber Yield Dynamics Under Microclimate Effects
Greenhouse decisions often rely on static thresholds, yet crop output switches among microclimate-driven regimes. We frame daily cucumber yield as transitions among three ordered states and fit a continuous-time, covariate-dependent multistate model. Data come from four greenhouse compartments in Volos, Greece (24 lines, 62 days). States are defined once from control tertiles and applied across compartments. Transition intensities depend on within-compartment z-scores of relative humidity (RH),…

Entropy Engineering-Regulated Electron-Phonon Coupling for Highly Efficient Photoluminescence in Se-doped WS2
Chi Zhang, Quan Shen, Mengmeng Zhang, Zhiming Deng, Taishen Wu, Xuying Zhong, Gang Ouyang, Dongsheng Tang, Qi Zheng, Jiansheng Dong, Weichang Zhou
https://arxiv.org/abs/2510.11081

Entropy Engineering-Regulated Electron-Phonon Coupling for Highly Efficient Photoluminescence in Se-doped WS2
The limited quantum yield of strained monolayer transition metal dichalcogenides grown by vapor-phase methods and during transfer-based stacking poses a fundamental challenge for their optoelectronic applications. Here, we introduce the concept of "entropy engineering" as a transformative strategy to selectively enhance light-matter interactions through controlled electron-phonon coupling. We unveil how tailored entropy introduced via precise selenium doping or interfacial van der Waals proximi…

The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs
Akshit Sinha, Arvindh Arun, Shashwat Goel, Steffen Staab, Jonas Geiping
https://arxiv.org/abs/2509.09677

The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs
Does continued scaling of large language models (LLMs) yield diminishing returns? Real-world value often stems from the length of task an agent can complete. We start this work by observing the simple but counterintuitive fact that marginal gains in single-step accuracy can compound into exponential improvements in the length of a task a model can successfully complete. Then, we argue that failures of LLMs when simple tasks are made longer arise from mistakes in execution, rather than an inabil…

Interval-Censored Survival Analysis of Grapevine Phenology: Thermal Controls on Flowering and Fruit Ripening
Sara Behnamian, Fatemeh Fogh
https://arxiv.org/abs/2510.09702 https:…

Interval-Censored Survival Analysis of Grapevine Phenology: Thermal Controls on Flowering and Fruit Ripening
European grapevine (\textit{Vitis vinifera} L.) is a climate-sensitive perennial whose flowering and ripening govern yield and quality. Phenological records from monitoring programs are typically collected at irregular intervals, so true transition dates are interval-censored, and many site-years are right-censored. We develop a reproducible workflow that treats phenology as a time-to-event outcome: Status \& Intensity observations from the USA-NPN are converted to interval bounds, linked to NA…

Raiders Busters for Week 6 vs Titans https://raiderswire.usatoday.com/story/sports/nfl/raiders/2025/10/14/raiders-busters-for-week-6-vs-titans/86690529007/

Reanalysis of the eclipses of LHS 1140 c: No evidence of an atmosphere and implications for the internal structure of the planet
Alexandra Rochon, \'Etienne Artigau, Drew Weisserman, Lisa Dang, Ren\'e Doyon, Charles Cadieux, Ryan Cloutier
https://arxiv.org/abs/2510.11397

Reanalysis of the eclipses of LHS 1140 c: No evidence of an atmosphere and implications for the internal structure of the planet
We present the reanalysis of three 15 micron JWST/MIRI secondary eclipses of LHS 1140 c, a warm super-Earth (R$_{\rm{p}}$ = 1.272 R$_{\oplus}$) in a 3.78-day orbit around an M4.5 dwarf. We present a novel method for data reduction that leverages spatial derivatives of the point-spread function and compare it to widely used aperture photometry. Both methods yield eclipse depth consistent within 1 sigma of the values reported in the literature. We measure an eclipse depth of 271$^{+31}_{-30}$ ppm…

A 2-complex containing Sobolev spaces of matrix fields
Jay Gopalakrishnan, Kaibo Hu, Joachim Sch\"oberl
https://arxiv.org/abs/2507.11869 https://

A 2-complex containing Sobolev spaces of matrix fields
Using a generalization of complexes, called 2-complexes, this paper defines and analyzes new Sobolev spaces of matrix fields and their interrelationships within a commuting diagram. These spaces have very weak second-order derivatives. An example is the space of matrix fields of square-integrable components whose row-wise divergence followed by yet another divergence operation yield a function in a standard negative-order Sobolev space. Similar spaces where the double divergence is replaced by …

Extracting temperature of plasma through fusion reactions within a transport approach
Zhe Zhu, Jun Xu
https://arxiv.org/abs/2508.09431 https://arxiv.org/pd…

Extracting temperature of plasma through fusion reactions within a transport approach
We have investigated the method of extracting the temperature from weighted proton-to-neutron yield ratio from fusion reactions as in the previous experiment~[W. Bang, {\it et al.}, Phys. Rev. Lett. \textbf{111}, 055002 (2013).] using the Texas Petawatt laser beam. The Coulomb explosion of deuterium clusters is simulated based on the particle-in-cell model in a box system with periodic boundary conditions, and fusion reactions are incorporated through the stochastic method. As long as the deute…

Sources: Intel's 18A process is facing significant yield challenges, with only ~5% of chips meeting its specifications in late 2024 and ~10% by summer 2025 (Reuters)
https://www.reuters.com/world/asia-pacific/…

In-Field Mapping of Grape Yield and Quality with Illumination-Invariant Deep Learning
Ciem Cornelissen, Sander De Coninck, Axel Willekens, Sam Leroux, Pieter Simoens
https://arxiv.org/abs/2510.04864

In-Field Mapping of Grape Yield and Quality with Illumination-Invariant Deep Learning
This paper presents an end-to-end, IoT-enabled robotic system for the non-destructive, real-time, and spatially-resolved mapping of grape yield and quality (Brix, Acidity) in vineyards. The system features a comprehensive analytical pipeline that integrates two key modules: a high-performance model for grape bunch detection and weight estimation, and a novel deep learning framework for quality assessment from hyperspectral (HSI) data. A critical barrier to in-field HSI is the ``domain shift" ca…

Valid Survey Simulations with Limited Human Data: The Roles of Prompting, Fine-Tuning, and Rectification
Stefan Krsteski, Giuseppe Russo, Serina Chang, Robert West, Kristina Gligori\'c
https://arxiv.org/abs/2510.11408

Valid Survey Simulations with Limited Human Data: The Roles of Prompting, Fine-Tuning, and Rectification
Surveys provide valuable insights into public opinion and behavior, but their execution is costly and slow. Large language models (LLMs) have been proposed as a scalable, low-cost substitute for human respondents, but their outputs are often biased and yield invalid estimates. We study the interplay between synthesis methods that use LLMs to generate survey responses and rectification methods that debias population estimates, and explore how human responses are best allocated between them. Usin…

Cryptocurrencies and Interest Rates: Inferring Yield Curves in a Bondless Market
Philippe Bergault, S\'ebastien Bieber, Olivier Gu\'eant, Wenkai Zhang
https://arxiv.org/abs/2509.03964

Cryptocurrencies and Interest Rates: Inferring Yield Curves in a Bondless Market
In traditional financial markets, yield curves are widely available for countries (and, by extension, currencies), financial institutions, and large corporates. These curves are used to calibrate stochastic interest rate models, discount future cash flows, and price financial products. Yield curves, however, can be readily computed only because of the current size and structure of bond markets. In cryptocurrency markets, where fixed-rate lending and bonds are almost nonexistent as of early 2025…

The invariance of group occupation across the cosmic web
Vicente Izzo Dominguez, Facundo Rodriguez, Antonio D. Montero-Dorta
https://arxiv.org/abs/2509.09800 https://

The invariance of group occupation across the cosmic web
Recent efforts to identify secondary variations in the Halo Occupation Distribution (HOD) have primarily focused on simulations examining the role of large-scale cosmic environments such as superclusters, filaments, and underdense regions or voids. If present, these variations could yield valuable insights into galaxy formation mechanisms, halo assembly processes, and the influence of external factors on cosmic structure. We aim to test whether secondary trends in the HOD driven by the large-sc…

Benchmarking Classical and Quantum Models for DeFi Yield Prediction on Curve Finance
Chi-Sheng Chen, Aidan Hung-Wen Tsai
https://arxiv.org/abs/2508.02685 https://

Benchmarking Classical and Quantum Models for DeFi Yield Prediction on Curve Finance
The rise of decentralized finance (DeFi) has created a growing demand for accurate yield and performance forecasting to guide liquidity allocation strategies. In this study, we benchmark six models, XGBoost, Random Forest, LSTM, Transformer, quantum neural networks (QNN), and quantum support vector machines with quantum feature maps (QSVM-QNN), on one year of historical data from 28 Curve Finance pools. We evaluate model performance on test MAE, RMSE, and directional accuracy. Our results show …

Unlocking the initial neutron density distribution from the two-pion HBT correlation function in heavy-ion collisions
Pengcheng Li, Manzi Nan, Haojie Zhang, Junhuai Xu, Xilong Xiang, Yijie Wang, Yongjia Wang, Gaochan Yong, Tadaaki Isobe, Zhigang Xiao, Qingfeng Li
https://arxiv.org/abs/2510.12226

Unlocking the initial neutron density distribution from the two-pion HBT correlation function in heavy-ion collisions
Revealing the neutron density distribution in the nucleus is one of the crucial tasks of nuclear physics. Within the framework of the ultrarelativistic quantum molecular dynamic model followed by a correlation afterburner program, we investigate the effects of the initial neutron density distribution on the charged-pion yield ratio $π^{-}/π^{+}$, the two-pion momentum correlation function, and the emission source dimension. It is found that the $π^{-}/π^{+}$ ratio is sensitive to the initia…

Analyzing the Performance of a 2.72kWp Rooftop Grid tied Photovoltaic System in Tarlac City, Philippines
Aldrin Joar Rodrigo Taduran, Leo P. Piao
https://arxiv.org/abs/2510.03487

Analyzing the Performance of a 2.72kWp Rooftop Grid tied Photovoltaic System in Tarlac City, Philippines
Residential and industrial areas are using rooftop grid-tied Photovoltaic (PV) systems, which are becoming increasingly popular. This is because solar energy reduces electrical consumption and provides free energy, while also lowering carbon emissions to create a more sustainable environment. This paper aims to analyze the 2.72kW p rooftop grid-tied PV system performance between 2020 and 2023 in Tarlac City, Philippines. The PV generated yearly is measured by Array Yield (YA), Reference Yield (…

"Clearing Gaza rubble could yield 90,000 tonnes of planet-heating emissions"
#Gaza #Emissions
https://www.

Exchange-driven self-diffusion of nanoscale crystalline parahydrogen clusters on graphite
K. M. Kolevski, M. Boninsegni
https://arxiv.org/abs/2508.10883 https://

Exchange-driven self-diffusion of nanoscale crystalline parahydrogen clusters on graphite
Computer simulations yield evidence of superfluid behavior of nanoscale size clusters of parahydrogen adsorbed on a graphite substrate at low temperature ($T\lesssim 0.25 \text{ K}$). Clusters with a number of molecules between 7 and 12 display concurrent superfluidity and crystalline order, reflecting the corrugation of the substrate. Remarkably, it is found that specific clusters with a number of molecules ranging between 7 and 12 self-diffuse on the surface like free particles, despite the s…

Stabilizing the Staking Rate, Dynamically Distributed Inflation and Delay Induced Oscillations
Carlo Brunetta, Amit Chaudhary, Stefano Galatolo, Massimiliano Sala
https://arxiv.org/abs/2510.11065

Stabilizing the Staking Rate, Dynamically Distributed Inflation and Delay Induced Oscillations
Dynamically distributed inflation is a common mechanism used to guide a blockchain's staking rate towards a desired equilibrium between network security and token liquidity. However, the high sensitivity of the annual percentage yield to changes in the staking rate, coupled with the inherent feedback delays in staker responses, can induce undesirable oscillations around this equilibrium. This paper investigates this instability phenomenon. We analyze the dynamics of inflation-based reward s…

Flexibility without foresight: the predictive limitations of mixture models
Stephane Hess, Sander van Cranenburgh
https://arxiv.org/abs/2510.09185 https://…

Flexibility without foresight: the predictive limitations of mixture models
Models allowing for random heterogeneity, such as mixed logit and latent class, are generally observed to obtain superior model fit and yield detailed insights into unobserved preference heterogeneity. Using theoretical arguments and two case studies on revealed and stated choice data, this paper highlights that these advantages do not translate into any benefits in forecasting, whether looking at prediction performance or the recovery of market shares. The only exception arises when using cond…

ReNiL: Relative Neural Inertial Locator with Any-Scale Bayesian Inference
Kaixuan Wu (School of Computer Science, Wuhan University, Wuhan, China, School of Cyber Science and Engineering, Wuhan University, Wuhan, China), Yuanzhuo Xu (School of Computer Science, Wuhan University, Wuhan, China), Zejun Zhang (University of Southern California, Los Angeles, United States), Weiping Zhu (School of Computer Science, Wuhan University, Wuhan, China), Steve Drew (Department of Electrical and Soft…

ReNiL: Relative Neural Inertial Locator with Any-Scale Bayesian Inference
Pedestrian inertial localization is key for mobile and IoT services because it provides infrastructure-free positioning. Yet most learning-based methods depend on fixed sliding-window integration, struggle to adapt to diverse motion scales and cadences, and yield inconsistent uncertainty, limiting real-world use. We present ReNiL, a Bayesian deep-learning framework for accurate, efficient, and uncertainty-aware pedestrian localization. ReNiL introduces Inertial Positioning Demand Points (IPDPs)…

Massive Spinning Fields During Inflation: Feynman rules and correlator comparison
Trevor Cheung, David Stefanyszyn
https://arxiv.org/abs/2509.08888 https://

Massive Spinning Fields During Inflation: Feynman rules and correlator comparison
We consider the dynamics of massive spinning fields during inflation and the resulting signatures in the cosmological correlators of inflaton perturbations computed in the Poincaré patch of de Sitter space. There are (at least) two ways to describe the fluctuations of such new spinning degrees of freedom and these are distinguished by the symmetries of the de Sitter group that they linearly realise. The primary question we ask is: do these two set-ups yield distinct signatures in cosmological …

Sonnet 122 - CXXII
Thy gift, thy tables, are within my brain
Full charactered with lasting memory,
Which shall above that idle rank remain,
Beyond all date, even to eternity:
Or, at the least, so long as brain and heart
Have faculty by nature to subsist;
Till each to razed oblivion yield his part
Of thee, thy record never can be missed.
That poor retention could not so much hold,
Nor need I tallies thy dear love to score;
Ther…

Fluorescence time profile measurement of LAB based liquid scintillator in response to medium relativistic ion particles
Xiaojie Luo, Shuya Jin, Gaosong Li, Zepeng Li, Fenhua Lu, Yazhou Sun, Shitao Wang, Yaoguang Wang, Yifang Wang, Xiaobao Wei, Liangjian Wen
https://arxiv.org/abs/2508.08546

Fluorescence time profile measurement of LAB based liquid scintillator in response to medium relativistic ion particles
Liquid scintillator is widely used in particle physics experiments due to its high light yield, good timing resolution, scalability and low cost. Certain liquid scintillators exhibit pulse shape discrimination capabilities because of difference in fluorescence timing properties induced by different particles. Its fluoresence timing properties have been measured mostly for radioactive decay sources at MeV energies. We present a novel measurement of fluorescence time properties of LAB based liqui…

OCTANE -- Optimal Control for Tensor-based Autoencoder Network Emergence: Explicit Case
Ratna Khatri, Anthony Kolshorn, Colin Olson, Harbir Antil
https://arxiv.org/abs/2509.08169

OCTANE -- Optimal Control for Tensor-based Autoencoder Network Emergence: Explicit Case
This paper presents a novel, mathematically rigorous framework for autoencoder-type deep neural networks that combines optimal control theory and low-rank tensor methods to yield memory-efficient training and automated architecture discovery. The learning task is formulated as an optimization problem constrained by differential equations representing the encoder and decoder components of the network and the corresponding optimality conditions are derived via a Lagrangian approach. Efficient mem…

Large circular dichroism in the total photoemission yield of free chiral nanoparticles created by a pure electric dipole effect
Sebastian Hartweg, Dusan k. Bozanic, Gustavo A. Garcia-Macias, Laurent Nahon
https://arxiv.org/abs/2510.05945

Large circular dichroism in the total photoemission yield of free chiral nanoparticles created by a pure electric dipole effect
Spectroscopic techniques that are sensitive to molecular chirality are important analytical tools to quantitatively determine enantiomeric excess and purity of chiral molecular samples. Many chiroptical processes however produce weak enantio-specific asymmetries due to their origin relying on weak magnetic dipole or electric quadrupole effects. Photoelectron circular dichroism (PECD) in contrast, is an intense effect, that is fully contained in the electric dipole description of light matter in…

Toward better understanding of energy in economics: Improvements to the Garrett thermodynamic economic model yield a robust system
Brian P. Hanley
https://arxiv.org/abs/2508.08723

Toward better understanding of energy in economics: Improvements to the Garrett thermodynamic economic model yield a robust system
In a series of papers, Garrett, et al, presents a thermodynamic economic model first laid out in "Are there basic physical constraints on future anthropogenic emissions of carbon dioxide?". This model contains a key conceptual issue that obscures a robust system. This system can link to the Energy Based Cobb-Douglas equation. The key conceptual problem is the belief that $λ$, the symbol for growth in Garrett 2011 would disprove the model if it was not constant. However, $λ$ cannot be a cons…

The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton
Natalie Abreu, Nikhil Vyas, Sham Kakade, Depen Morwani
https://arxiv.org/abs/2510.09378 https…

The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton
Recent efforts to accelerate LLM pretraining have focused on computationally-efficient approximations that exploit second-order structure. This raises a key question for large-scale training: how much performance is forfeited by these approximations? To probe this question, we establish a practical upper bound on iteration complexity by applying full Gauss-Newton (GN) preconditioning to transformer models of up to 150M parameters. Our experiments show that full GN updates yield substantial gain…

STEEP -- An Alternative To Quantum Key Distribution
Yingbo Hua
https://arxiv.org/abs/2508.05882 https://arxiv.org/pdf/2508.05882

STEEP -- An Alternative To Quantum Key Distribution
Secret-message transmission by echoing encrypted probes (STEEP) is discussed as an alternative to quantum key distribution (QKD). The former only needs classic or non-quantum channels while the latter needs both quantum and classic channels for secret-key generation. STEEP is shown to yield a secrecy rate sufficient for one-time pads encryption in many practical situations including in-air channels or undersea optical cables. Other advantages of STEEP over QKD include cost, complexity, compatib…

Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers
Wenhan Ma, Hailin Zhang, Liang Zhao, Yifan Song, Yudong Wang, Zhifang Sui, Fuli Luo
https://arxiv.org/abs/2510.11370

Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers
Reinforcement learning (RL) has emerged as a crucial approach for enhancing the capabilities of large language models. However, in Mixture-of-Experts (MoE) models, the routing mechanism often introduces instability, even leading to catastrophic RL training collapse. We analyze the training-inference consistency of MoE models and identify a notable discrepancy in routing behaviors between the two phases. Moreover, even under identical conditions, the routing framework can yield divergent expert …

The Brian\c{c}on-Skoda theorem for pseudo-rational and Du~Bois singularities
Linquan Ma, Peter M. McDonald, Rebecca R. G., Karl Schwede
https://arxiv.org/abs/2510.11540 https://…

The Briançon-Skoda theorem for pseudo-rational and Du~Bois singularities
Suppose $J = (f_1, \dots, f_n)$ is an $n$-generated ideal in a ring $R$. We prove a general Briançon-Skoda-type containment relating the integral closure of powers of $J$ with ordinary powers of $J$. We prove that our result implies the full standard Briançon-Skoda containment $\overline{J^{n+k-1}} \subseteq J^k$ for pseudo-rational singularities (for instance regular rings), and even for the weaker condition of birational derived splinters. Our methods also yield the containment $\overline{J…

Studying Exoplanets in the Radio from the Moon
Jake D. Turner, Jack O. Burns, David Rapetti, Philippe Zarka, Jean-Mathias Grie{\ss}meier, Judd Bowman, Gregg Hallinan, Joshua Hibbard, Johnny Dorigo Jones, Laurent Lamy, Corentin K. Louis, Richard Lovelace, Nivedita Mahesh, Ronald Polidan, Xiang Zhang
https://arxiv.org/abs/2508.09222

Studying Exoplanets in the Radio from the Moon
Exoplanets with and without a magnetic field are predicted to form, behave, and evolve very differently. Therefore, there is great need to directly constrain these fields to holistically understand the properties of exoplanets including their potential habitability. This goal aligns with the Astro2020 Decadal Survey recommendations. Observing planetary auroral radio emissions is among the most promising detection methods, but decades of searching have yet to yield a conclusive detection, though…

A multi-temporal multi-spectral attention-augmented deep convolution neural network with contrastive learning for crop yield prediction
Shalini Dangi, Surya Karthikeya Mullapudi, Chandravardhan Singh Raghaw, Shahid Shafi Dar, Mohammad Zia Ur Rehman, Nagendra Kumar
https://arxiv.org/abs/2509.15966

A multi-temporal multi-spectral attention-augmented deep convolution neural network with contrastive learning for crop yield prediction
Precise yield prediction is essential for agricultural sustainability and food security. However, climate change complicates accurate yield prediction by affecting major factors such as weather conditions, soil fertility, and farm management systems. Advances in technology have played an essential role in overcoming these challenges by leveraging satellite monitoring and data analysis for precise yield estimation. Current methods rely on spatio-temporal data for predicting crop yield, but they …

Multiplicity dependence of $\Xi_c^ $ and $\Xi_c^0$ production in pp collisions at $\sqrt{s} = 13$ TeV
ALICE Collaboration
https://arxiv.org/abs/2508.09955 https://

Multiplicity dependence of $Ξ_c^+$ and $Ξ_c^0$ production in pp collisions at $\sqrt{s} = 13$ TeV
The first measurement at midrapidity ($|y| < 0.5$) of the production yield of the strange-charm baryons $Ξ_c^+$ and $Ξ_c^0$ as a function of charged-particle multiplicity in proton-proton collisions at $\sqrt{s} = 13$ TeV with the ALICE experiment at the LHC is reported. The $Ξ_c^+$ baryon is reconstructed via the $Ξ_c^+ \rightarrow Ξ^-π^+π^+$ decay channel in the range $4 < p_{\rm T} < 12$ GeV/$c$, while the $Ξ_c^0$ baryon is reconstructed via both the $Ξ_c^0 \rightarrow Ξ^…

🚜 One-time nitrogen application boosts ammonia emissions in maize fields
#nitrogen

One-time nitrogen application boosts ammonia emissions in maize fields
Recently, a research team in the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has revealed that one-time nitrogen (N) application, a labor-saving practice favored by many farmers, increases both soil and canopy ammonia (NH3) emissions in maize fields, while reducing grain yield and nitrogen use efficiency.

Polar Express: Rapid Functionalization of Single-Walled Carbon Nanotubes in High Dipole Moment Media
Dominik Just, Ryszard Siedlecki, Maciej Krzywiecki, Oussama Er-Riyahi, Yann Pouillon, Javier Junquera, Karolina Z. Milowska, Dawid Janas
https://arxiv.org/abs/2508.09039

Polar Express: Rapid Functionalization of Single-Walled Carbon Nanotubes in High Dipole Moment Media
Fluorescent semiconducting single-walled carbon nanotubes (SWCNTs) hold considerable promise for photonics. Furthermore, the optical characteristics of the material can be significantly improved by covalent modification, which generates new spectral features in the near-infrared region and enhances its photoluminescence quantum yield. However, despite the dynamic development of this research domain, the importance of the solvent environment in which the SWCNT functionalization is conducted rema…

Modulated deuteron spectra observed with the Magnetic Recoil neutron Spectrometer at the National Ignition Facility
Bao Nguyen, Yousef Lawrence, Christopher Wink, Timothy Mark Johnson, Niels Vanderloo, Benjamin Reichelt, Amber Hennessy, Daniel Thomas Casey, Dave Schlossberg, Nathan Masters, Jose Milovich, Ari Le, Stephen Craxton, Maria Gatu Johnson, Johan Frenje

Modulated deuteron spectra observed with the Magnetic Recoil neutron Spectrometer at the National Ignition Facility
The Magnetic Recoil Spectrometer (MRS) on the National Ignition Facility is used to measure the neutron spectrum from deuterium-tritium fueled inertial confinement fusion implosions via n-d elastic scattering and magnetic dispersion of recoil deuterons. From the MRS-determined neutron spectrum, the yield ($Y_n$), apparent ion temperature ($T_i$) and areal density ($ρR$) are determined. However, anomalous energy modulations in recoil deuterons have been observed in several high-yield indirect d…

Situationally-aware Path Planning Exploiting 3D Scene Graphs
Saad Ejaz, Marco Giberna, Muhammad Shaheer, Jose Andres Millan-Romera, Ali Tourani, Paul Kremer, Holger Voos, Jose Luis Sanchez-Lopez
https://arxiv.org/abs/2508.06283

Situationally-aware Path Planning Exploiting 3D Scene Graphs
3D Scene Graphs integrate both metric and semantic information, yet their structure remains underutilized for improving path planning efficiency and interpretability. In this work, we present S-Path, a situationally-aware path planner that leverages the metric-semantic structure of indoor 3D Scene Graphs to significantly enhance planning efficiency. S-Path follows a two-stage process: it first performs a search over a semantic graph derived from the scene graph to yield a human-understandable h…

The role of rotation on the yields of the two {\gamma}-ray emitters 26Al and 60Fe ejected by massive stars
Agnese Falla, Lorenzo Roberti, Marco Limongi, Alessandro Chieffi
https://arxiv.org/abs/2508.07705

The role of rotation on the yields of the two γ-ray emitters 26Al and 60Fe ejected by massive stars
We show that the observed 60Fe/26Al flux ratio provided by the SPectrometer on INTEGRAL satellite (0.24 +- 0.04) can be reproduced only if rotation is taken into account in the computation of the stellar models. Predictions from non-rotating stellar models yield to a significantly lower ratio (0.062), which is incompatible with the observed value. The adopted models and the associated yields are based on a combination of models already published by Limongi & Chieffi (2018) complemented by addit…

Source: HR software company Gusto paid ~$600M to acquire Guideline, which offers 401(k) plans to SMBs; Guideline raised $340M and had a $1.15B valuation in 2021 (TechCrunch)
https://techcrunch.com/2025/10/01/sources-g…

Sources: Gusto paid $600M to acquire Guideline, plans to divest customers linked to rivals | TechCrunch
While the HR tech Guideline was last valued at $1.15 billion, the sale will likely yield a profit for most investors.

Simultaneous optimization of assembly time and yield in programmable self-assembly
Maximilian C. H\"ubl, Carl P. Goodrich
https://arxiv.org/abs/2510.07876 https://

Simultaneous optimization of assembly time and yield in programmable self-assembly
Rational design strategies for self-assembly require a detailed understanding of both the equilibrium state and the assembly kinetics. While the former is starting to be well understood, the latter remains a major theoretical challenge, especially in programmable systems and the so-called semiaddressable regime, where binding is often nondeterministic and the formation of off-target structures negatively influences the assembly. Here, we show that it is possible to simultaneously sculpt the ass…

Testing Lens Models of PLCK G165.7 67.0 Using Lensed SN H0pe
Aadya Agrawal, J. D. R. Pierel, Gautham Narayan, B. L. Frye, Jose M. Diego, Nikhil Garuda, Matthew Grayling, Anton M. Koekemoer, Kaisey S. Mandel, M. Pascale, David Vizgan, Rogier A. Windhorst
https://arxiv.org/abs/2510.07637

Testing Lens Models of PLCK G165.7+67.0 Using Lensed SN H0pe
Supernova H0pe is a multiply-imaged Type Ia supernova (SN Ia) and the second lensed SN to yield a measurement of the Hubble constant by the time-delay cosmography method, finding $H_0 = 75.4^{+8.1}_{-5.5} \text{km s}^{-1} \text{Mpc}^{-1}$. We investigate the seven lens modeling approaches used to derive $H_0$, assessing their agreement with $Λ\text{CDM}$ constraints from SN Ia surveys through a purely observational comparison. While photometrically derived magnifications yield distance moduli …

Predicting the distribution of yield-stress fluids in branched pipe manifolds
Elliott Sutton, Waldo Rosales Trujillo, Adam Kowalski, Cl\'audio P. Fonte, Anne Juel
https://arxiv.org/abs/2509.22192

Predicting the distribution of yield-stress fluids in branched pipe manifolds
We develop a one-dimensional network model to predict the steady-state distribution of yield-stress fluids in branched pipe manifolds under wall-slip conditions. The model accounts for major friction losses between junctions and incorporates wall slip through a power-law relation calibrated independently via capillary rheometry. Predictions from the model are validated against both bench-scale experiments and fully resolved computational fluid dynamics simulations, showing excellent agreement a…

The impact of organic hazes and graphite on the observation of CO2-rich sub-Neptune atmospheres
Haixin Li, Chao He, Sai Wang, Zhengbo Yang, Yu Liu, Yingjian Wang, Xiao'ou Luo, Sarah E. Moran, Cara Pesciotta, Sarah M. H\"orst, Julianne I. Moses, V\'eronique Vuitton
https://arxiv.org/abs/2508.07161…

The impact of organic hazes and graphite on the observation of CO2-rich sub-Neptune atmospheres
Many sub-Neptune and super-Earth exoplanets are expected to develop metal-enriched atmospheres due to atmospheric loss processes such as photoevaporation or core-powered mass loss. Thermochemical equilibrium calculations predict that at high metallicity and a temperature range of 300-700 K, CO2 becomes the dominant carbon species, and graphite may be the thermodynamically favored condensate under low-pressure conditions. Building on prior laboratory findings that such environments yield organic…

Symmetric Persistent Tensors and their Hessian
Masoud Gharahi, Giorgio Ottaviani
https://arxiv.org/abs/2510.07404 https://arxiv.org/pdf/2510.07404

Symmetric Persistent Tensors and their Hessian
Persistent tensors, introduced in [Quantum 8 (2024), 1238], and inspired by quantum information theory, form a recursively defined class of tensors that remain stable under the substitution method and thereby yield nontrivial lower bounds on tensor rank. In this work, we investigate the symmetric case-namely, symmetric persistent tensors, or equivalently, persistent polynomials. We establish that a symmetric tensor in $\mathrm{Sym}^n \mathbb{C}^d$ is persistent if the determinant of its Hessian…

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality
Botong Zhao, Qijun Shi, Shujing Lyu, Yue Lu
https://arxiv.org/abs/2509.09375 https://

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality
Modern Integrated-Circuit(IC) manufacturing introduces diverse, fine-grained defects that depress yield and reliability. Most industrial defect segmentation compares a test image against an external normal set, a strategy that is brittle for IC imagery where layouts vary across products and accurate alignment is difficult. We observe that defects are predominantly local, while each image still contains rich, repeatable normal patterns. We therefore propose an unsupervised IC defect segmentation…

Transformer-Based Approach to Optimal Sensor Placement for Structural Health Monitoring of Probe Cards
Mehdi Bejani, Marco Mauri, Daniele Acconcia, Simone Todaro, Stefano Mariani
https://arxiv.org/abs/2509.07603

Transformer-Based Approach to Optimal Sensor Placement for Structural Health Monitoring of Probe Cards
This paper presents an innovative Transformer-based deep learning strategy for optimizing the placement of sensors aiming at structural health monitoring of semiconductor probe cards. Failures in probe cards, including substrate cracks and loosened screws, would critically affect semiconductor manufacturing yield and reliability. Some failure modes could be detected by equipping a probe card with adequate sensors. Frequency response functions from simulated failure scenarios are adopted within …

A scalable photonic quantum interconnect platform
Daniel Riedel, Teodoro Graziosi, Zhuoxian Wang, Chawina De-Eknamkul, Alex Abulnaga, Jonathan Dietz, Andrea Mucchietto, Michael Haas, Madison Sutula, Pierre Barral, Matteo Pompili, Carsten Robens, Jeonghoon Ha, Denis Sukachev, David Levonian, Mihir Bhaskar, Matthew Markham, Bartholomeus Machielse
https://

A scalable photonic quantum interconnect platform
Many quantum networking applications require efficient photonic interfaces to quantum memories which can be produced at scale and with high yield. Synthetic diamond offers unique potential for the implementation of this technology as it hosts color centers which retain coherent optical interfaces and long spin coherence times in nanophotonic structures. Here, we report a technique enabling wafer-scale processing of thin-film diamond that combines ion implantation and membrane liftoff, high-qual…

Determining the Density of In-gap States in Organic Semiconductors: A Pitfall of Photoelectron Yield Spectroscopy
Ryotaro Nakazawa, Masaya Kitaoka, Ryota Kaimori, Manato Tateno, Runa Hoshikawa, Yuya Tanaka, Hisao Ishii
https://arxiv.org/abs/2510.00865

Determining the Density of In-gap States in Organic Semiconductors: A Pitfall of Photoelectron Yield Spectroscopy
Accurate determination of electronic states with low density in the bandgap (in-gap states) is crucial for understanding and optimizing the performance of organic optoelectronic devices. In the device research field, photoelectron yield spectroscopy (PYS) has been widely used to evaluate such states, and its derivative is commonly employed to estimate the density of states (DOS). However, low-energy photons in PYS can generate excitons and anions in organic semiconductors, raising questions abo…

FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolution
Yuchan Jie, Yushen Xu, Xiaosong Li, Fuqiang Zhou, Jianming Lv, Huafeng Li
https://arxiv.org/abs/2509.09427

FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolution
As an influential information fusion and low-level vision technique, image fusion integrates complementary information from source images to yield an informative fused image. A few attempts have been made in recent years to jointly realize image fusion and super-resolution. However, in real-world applications such as military reconnaissance and long-range detection missions, the target and background structures in multimodal images are easily corrupted, with low resolution and weak semantic inf…

Vi-TacMan: Articulated Object Manipulation via Vision and Touch
Leiyao Cui, Zihang Zhao, Sirui Xie, Wenhuan Zhang, Zhi Han, Yixin Zhu
https://arxiv.org/abs/2510.06339 https://…

Vi-TacMan: Articulated Object Manipulation via Vision and Touch
Autonomous manipulation of articulated objects remains a fundamental challenge for robots in human environments. Vision-based methods can infer hidden kinematics but can yield imprecise estimates on unfamiliar objects. Tactile approaches achieve robust control through contact feedback but require accurate initialization. This suggests a natural synergy: vision for global guidance, touch for local precision. Yet no framework systematically exploits this complementarity for generalized articulate…

Diabatic quantum annealing for training energy-based generative models
Gilhan Kim, Ju-Yeon Ghym, Daniel K. Park
https://arxiv.org/abs/2509.09374 https://ar…

Diabatic quantum annealing for training energy-based generative models
Energy-based generative models, such as restricted Boltzmann machines (RBMs), require unbiased Boltzmann samples for effective training. Classical Markov chain Monte Carlo methods, however, converge slowly and yield correlated samples, making large-scale training difficult. We address this bottleneck by applying the analytic relation between annealing schedules and effective inverse temperature in diabatic quantum annealing. By implementing this prescription on a quantum annealer, we obtain tem…

DeepPrune: Parallel Scaling without Inter-trace Redundancy
Shangqing Tu, Yaxuan Li, Yushi Bai, Lei Hou, Juanzi Li
https://arxiv.org/abs/2510.08483 https://…

DeepPrune: Parallel Scaling without Inter-trace Redundancy
Parallel scaling has emerged as a powerful paradigm to enhance reasoning capabilities in large language models (LLMs) by generating multiple Chain-of-Thought (CoT) traces simultaneously. However, this approach introduces significant computational inefficiency due to inter-trace redundancy -- our analysis reveals that over 80% of parallel reasoning traces yield identical final answers, representing substantial wasted computation. To address this critical efficiency bottleneck, we propose DeepPru…

Ergotropic advantage in a measurement-fueled quantum heat engine
Sidhant Jakhar, Ramandeep S. Johal
https://arxiv.org/abs/2509.09402 https://arxiv.org/pdf/…

Ergotropic advantage in a measurement-fueled quantum heat engine
This paper investigates a coupled two-qubits heat engine fueled by generalized measurements of the spin components and using a single heat reservoir as sink. Our model extends the four-stroke engine proposed by Yi and coworkers [Phys. Rev. E {\bf 96}, 022108 (2017)] by introducing an ergotropy-extracting stroke, resulting in a five-stroke cycle. For measurements along z-z directions, we find two possible occupation distributions that yield an active state and the ergotropic stroke improves the …

Draft, Verify, and Improve: Toward Training-Aware Speculative Decoding
Shrenik Bhansali, Larry Heck
https://arxiv.org/abs/2510.05421 https://arxiv.org/pdf/…

Draft, Verify, and Improve: Toward Training-Aware Speculative Decoding
Autoregressive (AR) decoding is a major latency bottleneck for large language models. Speculative decoding (SD) accelerates AR by letting a drafter propose multi-token blocks that a verifier accepts or rejects. However, many SD systems require heavy offline training or extra components. These choices raise data/compute cost and can yield brittle drafters under distribution drift. We introduce \emph{Draft, Verify, \& Improve (DVI)}, a training-aware self-speculative framework that combines infer…

The Majority is not always right: RL training for solution aggregation
Wenting Zhao, Pranjal Aggarwal, Swarnadeep Saha, Asli Celikyilmaz, Jason Weston, Ilia Kulikov
https://arxiv.org/abs/2509.06870

The Majority is not always right: RL training for solution aggregation
Scaling up test-time compute, by generating multiple independent solutions and selecting or aggregating among them, has become a central paradigm for improving large language models (LLMs) on challenging reasoning tasks. While most prior work relies on simple majority voting or reward model ranking to aggregate solutions, these approaches may only yield limited benefits. In this work, we propose to learn aggregation as an explicit reasoning skill: given a set of candidate solutions, we train an…

Zero-shot 3D-Aware Trajectory-Guided image-to-video generation via Test-Time Training
Ruicheng Zhang, Jun Zhou, Zunnan Xu, Zihao Liu, Jiehui Huang, Mingyang Zhang, Yu Sun, Xiu Li
https://arxiv.org/abs/2509.06723

Zero-shot 3D-Aware Trajectory-Guided image-to-video generation via Test-Time Training
Trajectory-Guided image-to-video (I2V) generation aims to synthesize videos that adhere to user-specified motion instructions. Existing methods typically rely on computationally expensive fine-tuning on scarce annotated datasets. Although some zero-shot methods attempt to trajectory control in the latent space, they may yield unrealistic motion by neglecting 3D perspective and creating a misalignment between the manipulated latents and the network's noise predictions. To address these challenge…

The quantum communication power of indefinite causal order
Xuanqiang Zhao, Benchi Zhao, Giulio Chiribella
https://arxiv.org/abs/2510.08507 https://arxiv.or…

The quantum communication power of indefinite causal order
Quantum theory is in principle compatible with scenarios where physical processes take place in an indefinite causal order, a possibility that was shown to yield advantages in several information processing tasks. However, advantages in communication, the most basic form of information processing, have so far remained controversial and hard to prove. Here we develop a framework that can be used to rigorously assess the role of causal order in a scenario where communication links are built by as…

Randomized truncation of quantum states
Aram W. Harrow, Angus Lowe, Freek Witteveen
https://arxiv.org/abs/2510.08518 https://arxiv.org/pdf/2510.08518

Randomized truncation of quantum states
A fundamental task in quantum information is to approximate a pure quantum state in terms of sparse states or, for a bipartite system, states of bounded Schmidt rank. The optimal deterministic approximation in each case is straightforward, and maximizes the fidelity: keep the largest entries or singular values. On the other hand, random mixtures of sparse states can achieve quadratically improved trace distances, and yield nontrivial bounds on other distance measures like the robustness. In thi…