Tootfinder

Observable Optimization for Precision Theory: Machine Learning Energy Correlators
Arindam Bhattacharya, Katherine Fraser, Matthew D. Schwartz
https://arxiv.org/abs/2508.10988 ht…

Observable Optimization for Precision Theory: Machine Learning Energy Correlators
The practice of collider physics typically involves the marginalization of multi-dimensional collider data to uni-dimensional observables relevant for some physics task. In any cases, such as classification or anomaly detection, the observable can be arbitrarily complicated, such as the output of a neural network. However, for precision measurements, the observable must correspond to something computable systematically beyond the level of current simulation tools. In this work, we demonstrate t…

Probing minimal observable length with dark modes in an optomechanical detector
Wenlin Li, Xingli Li, Najmeh Eshaqi-Sani, Wen-zhao Zhang, Jiong Cheng
https://arxiv.org/abs/2508.10389

Probing minimal observable length with dark modes in an optomechanical detector
Several theories that attempt to unify quantum theory and gravitational theory assume that space has an observable limiting resolution related to the Planck length, denoted by $\sqrt{β_0}L_p$. Quantum mechanically, this concept derives a generalized uncertainty principle (GUP) and the corresponding modified commutator. The prediction and observation of GUP-induced new physics, as well as the quantitative measurement of the value of $β_0$, may provide substantial support for the establishment …

On the Feasibility of Inter-Flow Service Degradation Detection
Balint Bicski, Adrian Pekar
https://arxiv.org/abs/2509.11140 https://arxiv.org/pdf/2509.1114…

On the Feasibility of Inter-Flow Service Degradation Detection
Hardware acceleration in modern networks creates monitoring blind spots by offloading flows to a non-observable state, hindering real-time service degradation (SD) detection. To address this, we propose and formalize a novel inter-flow correlation framework, built on the hypothesis that observable flows can act as environmental sensors for concurrent, non-observable flows. We conduct a comprehensive statistical analysis of this inter-flow landscape, revealing a fundamental trade-off: while the …

Observable thin accretion disk around a self-dual black hole in loop quantum gravity
Tursunali Xamidov, Javokhir Sharipov, Sanjar Shaymatov
https://arxiv.org/abs/2509.10953 http…

Observable thin accretion disk around a self-dual black hole in loop quantum gravity
In this paper, we study a self-dual black hole (BH) in Loop Quantum Gravity (LQG), analyzing both timelike and null geodesics. Using observational data from Mercury's perihelion shift and the orbit of the S2 star around Sagittarius A$^{\star}$ (Sgr A$^{\star}$), we derive constraints on the polymeric function $P$. We further investigate photon trajectories near the self-dual BH under various scenarios to explore their observational relevance. Finally, we examine the properties of accretion disk…

Compositional shield synthesis for safe reinforcement learning in partial observability
Steven Carr, Georgios Bakirtzis, Ufuk Topcu
https://arxiv.org/abs/2509.12085 https://

Compositional shield synthesis for safe reinforcement learning in partial observability
Agents controlled by the output of reinforcement learning (RL) algorithms often transition to unsafe states, particularly in uncertain and partially observable environments. Partially observable Markov decision processes (POMDPs) provide a natural setting for studying such scenarios with limited sensing. Shields filter undesirable actions to ensure safe RL by preserving safety requirements in the agents' policy. However, synthesizing holistic shields is computationally expensive in complex depl…

Pulsations change the structures of massive stars before they explode: interpreting the nearby supernova SN 2023ixf
Eva Laplace, Vincent A. Bronner, Fabian R. N. Schneider, Philipp Podsiadlowski
https://arxiv.org/abs/2508.11088

Pulsations change the structures of massive stars before they explode: interpreting the nearby supernova SN 2023ixf
It is known that massive red supergiants (RSGs) become hydrodynamically unstable and experience radial pulsations before they explode. Still, the vast majority of supernova (SN) models assume RSG progenitors in hydrostatic equilibrium. Here, we self-consistently follow the hydrodynamic evolution of RSGs with different masses and the development of radial envelope pulsations. Pulsations significantly alter the observable pre- and post-SN properties, and their importance increases substantially a…

Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin
Hang Xu, Tailong Xiao, Jingzheng Huang, Jianping Fan, Guihua Zeng
https://arxiv.org/abs/2508.11198

Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin
Quantum sensors leverage nonclassical resources to achieve sensing precision at the Heisenberg limit, surpassing the standard quantum limit attainable through classical strategies. However, a critical issue is that the environmental noise induces rapid decoherence, fundamentally limiting the realizability of the Heisenberg limit. In this Letter, we propose a quantum digital twin protocol to overcome this issue. The protocol first establishes observable-constrained state reconstruction to infer …

Deriving accurate galaxy cluster masses using X-ray thermodynamic profiles and graph neural networks
Asif Iqbal, Subhabrata Majumdar, Elena Rasia, Gabriel W. Pratt, Daniel de Andres, Jean-Baptiste Melin, Weiguang Cui
https://arxiv.org/abs/2509.12199

Deriving accurate galaxy cluster masses using X-ray thermodynamic profiles and graph neural networks
Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) to estimate galaxy cluster masses from radially sampled profiles of the intra-cluster medium (ICM) inferred from X-ray observations. GNNs naturally handle inputs of variable length and resolution by representing each ICM profile as a graph, enabling accurate and flexible modeling across diverse observational conditions…

Towards detecting the time perturbations from GWs in asynchronous gauges
Stefano Bondani, Sergio Luigi Cacciatori
https://arxiv.org/abs/2509.13321 https://…

Towards detecting the time perturbations from GWs in asynchronous gauges
The experimental possibility of detecting gravitational waves via their induced time perturbations is explored here, expanding from previous work. The oscillations of the time-time component in the metric are made explicit when working in asynchronous gauges: the desynchronization between a perturbed clock and a reference unperturbed clock constitutes the corresponding observable core target of a detector. To this end we explore the experimental techniques currently available for a preliminary …

Identifying Network Structure of Nonlinear Dynamical Systems: Contraction and Kuramoto Oscillators
Jaidev Gill, Jing Shuang Li
https://arxiv.org/abs/2509.13505 https://

Identifying Network Structure of Nonlinear Dynamical Systems: Contraction and Kuramoto Oscillators
In this work, we study the identifiability of network topologies for networked nonlinear systems when partial measurements of the nodes are taken. We explore scenarios where different candidate topologies can yield similar measurements, thus limiting identifiability. To do so, we apply the contraction theory framework to facilitate comparisons between candidate topologies. We show that semicontraction in the observable space is a sufficient condition for two systems to become indistinguishable …

A shortcut through the macroscopic fluctuation theory: a generalised Fick law
Th\'eotim Berlioz, Olivier B\'enichou, Aur\'elien Grabsch
https://arxiv.org/abs/2509.12017

A shortcut through the macroscopic fluctuation theory: a generalised Fick law
The macroscopic fluctuation theory is a powerful tool to characterise the large scale dynamical properties of diffusive systems, both in- and out-of-equilibrium. It relies on an action formalism in which, at large scales, the dynamics is fully determined by the minimum of the action. Within this formalism, the analysis of the statistical properties of a given observable reduces to solving the Euler-Lagrange equations with the appropriate boundary conditions. One must then compute the action at …

De Sitter Complexity Grows Linearly in the Static Patch
Vyshnav Mohan, Watse Sybesma
https://arxiv.org/abs/2508.10093 https://arxiv.org/pdf/2508.10093

De Sitter Complexity Grows Linearly in the Static Patch
The observable universe has undergone periods of expansion that are well approximated by de Sitter (dS) space. Still lacking is a quantum mechanical description of dS, both globally and when restricted to the static patch. We develop a novel prescription for computing holographic complexity in the dS static patch to determine its microscopic features. Specifically, we propose that the natural candidate for dS complexity is the volume of extremal timelike surfaces restricted to the static patch,…

DeepMET: Improving missing transverse momentum estimation with a deep neural network
CMS Collaboration
https://arxiv.org/abs/2509.12012 https://arxiv.org/p…

DeepMET: Improving missing transverse momentum estimation with a deep neural network
At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $\vec{p}_\mathrm{T}^\text{miss}$) is a crucial observable in many analyses. In the standard model, $\vec{p}_\mathrm{T}^\text{miss}$ originates from neutrinos. Many beyond-the-standard-model particles, such as dark matter candidates, are also expected to leave the experimental apparatus undetected. This paper presents a novel $\vec{p}_\mathrm{T}^\text{miss}$ estimato…

Glimpsing at Electron's Form Factor through Quasiparticle Interference in Twisted Bilayer Graphene
D. -H. -Minh Nguyen, Francisco Guinea, Dario Bercioux
https://arxiv.org/abs/2509.11223

Glimpsing at Electron's Form Factor through Quasiparticle Interference in Twisted Bilayer Graphene
We show that characteristics of the electron's form factor in two-dimensional materials are observable in quasiparticle interference (QPI) spectrum. We study QPI in twisted bilayer graphene using real-space tight-binding calculations combined with the kernel polynomial method, which agrees excellently with the form factor norm obtained from the continuum Hamiltonian. The QPI signals, displaying a chiral structure, reveal all distinct interference processes between states near the Dirac points. …

Policy Optimization in Multi-Agent Settings under Partially Observable Environments
Ainur Zhaikhan, Malek Khammassi, Ali H. Sayed
https://arxiv.org/abs/2508.06061 https://

Policy Optimization in Multi-Agent Settings under Partially Observable Environments
This work leverages adaptive social learning to estimate partially observable global states in multi-agent reinforcement learning (MARL) problems. Unlike existing methods, the proposed approach enables the concurrent operation of social learning and reinforcement learning. Specifically, it alternates between a single step of social learning and a single step of MARL, eliminating the need for the time- and computation-intensive two-timescale learning frameworks. Theoretical guarantees are provid…

Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach
Haosheng Zhou, Daniel Ralston, Xu Yang, Ruimeng Hu
https://arxiv.org/abs/2509.03727

Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach
Adversarial decision-making in partially observable multi-agent systems requires sophisticated strategies for both deception and counter-deception. This paper presents a sequential hypothesis testing (SHT)-driven framework that captures the interplay between strategic misdirection and inference in adversarial environments. We formulate this interaction as a partially observable Stackelberg game, where a follower agent (blue team) seeks to fulfill its primary task while actively misleading an ad…

Unified $g$-mode and $r$-mode Analysis of Accreting White Dwarf Stars
Praphull Kumar, Dean M. Townsley
https://arxiv.org/abs/2509.09984 https://arxiv.org/p…

Unified $g$-mode and $r$-mode Analysis of Accreting White Dwarf Stars
Dwarf novae are a subset of cataclysmic variables that accrete material intermittently in short-duration outbursts with sometimes long quiescent intervals in between. During the quiescent state, the white dwarf (WD) photosphere may be observable. Some of these systems show periodic variability consistent with a non-radial oscillation. Asteroseismology has become a unique tool for the measurement of internal structure of the WDs, such as their masses, radii, temperatures and rotation profiles. A…

What You Don't Know Can Hurt You: How Well do Latent Safety Filters Understand Partially Observable Safety Constraints?
Matthew Kim, Kensuke Nakamura, Andrea Bajcsy
https://arxiv.org/abs/2510.06492

What You Don't Know Can Hurt You: How Well do Latent Safety Filters Understand Partially Observable Safety Constraints?
Safe control techniques, such as Hamilton-Jacobi reachability, provide principled methods for synthesizing safety-preserving robot policies but typically assume hand-designed state spaces and full observability. Recent work has relaxed these assumptions via latent-space safe control, where state representations and dynamics are learned jointly through world models that reconstruct future high-dimensional observations (e.g., RGB images) from current observations and actions. This enables safety …

Structured Kernel Regression VAE: A Computationally Efficient Surrogate for GP-VAEs in ICA
Yuan-Hao Wei, Fu-Hao Deng, Lin-Yong Cui, Yan-Jie Sun
https://arxiv.org/abs/2508.09721 …

Structured Kernel Regression VAE: A Computationally Efficient Surrogate for GP-VAEs in ICA
The interpretability of generative models is considered a key factor in demonstrating their effectiveness and controllability. The generated data are believed to be determined by latent variables that are not directly observable. Therefore, disentangling, decoupling, decomposing, causal inference, or performing Independent Component Analysis (ICA) in the latent variable space helps uncover the independent factors that influence the attributes or features affecting the generated outputs, thereby…

To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning
Yuda Song, Dhruv Rohatgi, Aarti Singh, J. Andrew Bagnell
https://arxiv.org/abs/2510.03207

To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning
Partial observability is a notorious challenge in reinforcement learning (RL), due to the need to learn complex, history-dependent policies. Recent empirical successes have used privileged expert distillation--which leverages availability of latent state information during training (e.g., from a simulator) to learn and imitate the optimal latent, Markovian policy--to disentangle the task of "learning to see" from "learning to act". While expert distillation is more computationally efficient tha…

Estimating carbon pools in the shelf sea environment: reanalysis or model-informed machine learning?
Jozef Skakala
https://arxiv.org/abs/2508.10178 https://

Estimating carbon pools in the shelf sea environment: reanalysis or model-informed machine learning?
Shelf seas are important for carbon sequestration and carbon cycle, but available in situ, or satellite data for carbon pools in the shelf sea environment are often sparse, or highly uncertain. Alternative can be provided by reanalyses, but these are often expensive to run. We propose to use an ensemble of neural networks (NN) to learn from a coupled physics-biogeochemistry model the relationship between the directly observable variables and carbon pools. We demonstrate for North-West European …

Semiclassical analytical solutions of the eigenstate thermalization hypothesis in a quantum billiard
Yaoqi Ye, Chengkai Lin, Xiao Wang
https://arxiv.org/abs/2510.12517 https://

Semiclassical analytical solutions of the eigenstate thermalization hypothesis in a quantum billiard
We derive semiclassical analytical solutions for both the diagonal and off-diagonal functions in the eigenstate thermalization hypothesis (ETH) in a quarter-stadium quantum billiard. For a representative observable, we obtain an explicit expression and an asymptotic closed-form solution that naturally separate into a local contribution and a phase-space correlation term. These analytical results predict the band structure of the observable matrix, including its bandwidth and scaling behavior. W…

Topological superconductivity in a dimerized Kitaev chain revealed by nonlocal transport
Rafael Pineda Medina, Pablo Burset, William J. Herrera
https://arxiv.org/abs/2509.10412 …

Topological superconductivity in a dimerized Kitaev chain revealed by nonlocal transport
Artificial Kitaev chains engineered from semiconducting quantum dots coupled by superconducting segments offer a promising route to realize and control Majorana bound states for topological quantum computation. We study a dimerized Kitaev chain--equivalent to a superconducting Su-Schrieffer-Heeger model--and analyze the behavior of the resulting two coupled chains. We show that interference between Majorana edge modes from each chain gives rise to observable signatures in nonlocal conductance. …

ViewSparsifier: Killing Redundancy in Multi-View Plant Phenotyping
Robin-Nico Kampa, Fabian Deuser, Konrad Habel, Norbert Oswald
https://arxiv.org/abs/2509.08550 https://…

ViewSparsifier: Killing Redundancy in Multi-View Plant Phenotyping
Plant phenotyping involves analyzing observable characteristics of plants to better understand their growth, health, and development. In the context of deep learning, this analysis is often approached through single-view classification or regression models. However, these methods often fail to capture all information required for accurate estimation of target phenotypic traits, which can adversely affect plant health assessment and harvest readiness prediction. To address this, the Growth Model…

Self-lensing binaries as probes of Supernova physics
Grzegorz Wiktorowicz, Matthew Middleton, Aleksandra Olejak, Cordelia Dashwood-Brown, Madeleine-Mai Ward, Adam Ingram
https://arxiv.org/abs/2509.11726

Self-lensing binaries as probes of Supernova physics
Self-lensing (SL) in binary systems has the potential to provide a unique observational window into the Galactic population of compact objects. Using the $\mathtt{startrack}$ and COSMIC population synthesis codes, we investigate how different supernova mechanisms affect the observable population of SL systems, with particular attention to the mass gap (2$\mathrm{-}$5 M$_\odot$) in compact object distributions. We test three supernova remnant formation models with different convective growth tim…

Quantum-Theoretical Re-interpretation of Pricing Theory
Tian Xin
https://arxiv.org/abs/2510.06287 https://arxiv.org/pdf/2510.06287

Quantum-Theoretical Re-interpretation of Pricing Theory
Motivated by Heisenberg's observable-only stance, we replace latent "information" (filtrations, hidden diffusions, state variables) with observable transitions between price states. On a discrete price lattice with a Hilbert-space representation, shift operators and the spectral calculus of the price define observable frequency operators and a translation-invariant convolution generator. Combined with jump operators that encode transition intensities, this yields a completely positive, translat…

A Dark Matter Model with Quadratic Equation of State: Background Evolution and Structure Formation
Kazem Rezazadeh, Ebrahim Yusofi, Alireza Talebian
https://arxiv.org/abs/2509.11138

A Dark Matter Model with Quadratic Equation of State: Background Evolution and Structure Formation
We propose that dark matter (DM) possesses a quadratic equation of state, which becomes significant at high densities, altering the Universe's evolution during its early stages. We derive the modified background evolution equations for the Hubble parameter $H(z)$ and the DM density parameter $Ω_{\text{dm}}(z)$. We then perturb the governing equations to study the linear growth of matter fluctuations, computing the observable growth factor $fσ_8(z)$. Finally, we compare the model with the late…

Society of Mind Meets Real-Time Strategy: A Hierarchical Multi-Agent Framework for Strategic Reasoning
Daechul Ahn, San Kim, Jonghyun Choi
https://arxiv.org/abs/2508.06042 https…

Society of Mind Meets Real-Time Strategy: A Hierarchical Multi-Agent Framework for Strategic Reasoning
Large Language Models (LLMs) have recently demonstrated impressive action sequence prediction capabilities but often struggle with dynamic, long-horizon tasks such as real-time strategic games. In a game such as StarCraftII (SC2), agents need to manage resource constraints and adapt to evolving battlefield situations in a partially observable environment. This often overwhelms exisiting LLM-based approaches. To address these challenges, we propose a hierarchical multi-agent framework that emplo…

I love my SwiftUI Observable view-models, how I use some 150 of them in Xogot:
https://blog.la-terminal.net/blissful-ui-development-with-swiftui-and-godot/

Blissful UI Development with SwiftUI and Godot.
Xogot is a SwiftUI interface built on top of the Godot engine. To speed up development, we needed a way to build large portions of the user interface without having to compile and deploy the entire project every time. A full build of the app in Godot takes a couple

Dynamically generated tilt of isocurvature fluctuations
Saarik Kalia
https://arxiv.org/abs/2510.11803 https://arxiv.org/pdf/2510.11803

Dynamically generated tilt of isocurvature fluctuations
Light scalar fields acquire isocurvature fluctuations during inflation. While these fluctuations could lead to interesting observable signatures at small scales, they are strongly constrained on large scales by cosmic microwave background observations. When the mass of the scalar is much lighter than the inflationary Hubble scale, $m\ll H_I$, the spectrum of these fluctuations is flat. Meanwhile, if $m\gg H_I$, the fluctuations are suppressed. A blue-tilted isocurvature spectrum which exhibits …

Algebraically Observable Physics-Informed Neural Network and its Application to Epidemiological Modelling
Mizuka Komatsu
https://arxiv.org/abs/2508.04590 https://

Algebraically Observable Physics-Informed Neural Network and its Application to Epidemiological Modelling
Physics-Informed Neural Network (PINN) is a deep learning framework that integrates the governing equations underlying data into a loss function. In this study, we consider the problem of estimating state variables and parameters in epidemiological models governed by ordinary differential equations using PINNs. In practice, not all trajectory data corresponding to the population described by models can be measured. Learning PINNs to estimate the unmeasured state variables and epidemiological pa…

Locally induced traveling waves generate globally observable traveling waves #neuroscience

Locally induced traveling waves generate globally observable traveling waves
Cortical traveling waves have been proposed as a fundamental mechanism for neural communication and computation. Methodological uncertainties currently limit the interpretability of non-invasive, extracranial traveling wave data, sparking debates about their cortical origin. Studies using EEG or MEG typically report waves that cover large portions of the sensor array which are often interpreted as reflecting long range cortical waves. Meanwhile, invasive, intracranial recordings in humans and a…

Two-dimensional superconducting diode effect in topological insulator/superconductor heterostructure
Soma Nagahama, Yuki Sato, Minoru Kawamura, Ilya Belopolski, Ryutaro Yoshimi, Atsushi Tsukazaki, Naoya Kanazawa, Kei S Takahashi, Masashi Kawasaki, Yoshinori Tokura
https://arxiv.org/abs/2510.09921

Two-dimensional superconducting diode effect in topological insulator/superconductor heterostructure
The superconducting diode effect (SDE) is characterized by the nonreciprocity of Cooper-pair motion with respect to current direction. In three-dimensional (3D) materials, SDE results in a critical current that varies with direction, making the effect distinctly observable: the material exhibits superconductivity in one direction while behaving as a resistive metal in the opposite direction. However, in genuinely two-dimensional (2D) materials, the critical current density is theoretically zero…

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Ziteng Chen (Infrawaves), Xiaohe Hu (Infrawaves), Menghao Zhang (Beihang University), Yanmin Jia (Infrawaves), Yan Zhang (Infrawaves), Mingjun Zhang (Infrawaves), Da Liu (Infrawaves), Fangzheng Jiao (Beihang University), Jun Chen (Infrawaves), He Liu (Infrawaves), Aohan Zeng (Tsinghua University), Shuaixing Duan (Zhipu AI), Ruya Gu (Infrawaves), Yang Jing (Infrawaves), Bowen Han …

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Large-scale LLM training requires collective communication libraries to exchange data among distributed GPUs. As a company dedicated to building and operating large-scale GPU training clusters, we encounter several challenges when using NCCL in production, including 1) limited efficiency with costly and cumbersome P2P communication, 2) poor tolerance to frequent RNIC port failures, and 3) insufficient observability of transient collective communication anomalies. To address these issues, we pro…

Emergence of Symmetry in a System of Distinguishable but Identical Particles
Allan Tameshtit
https://arxiv.org/abs/2509.11779 https://arxiv.org/pdf/2509.11…

Emergence of Symmetry in a System of Distinguishable but Identical Particles
Instead of the conventional construction of symmetric and antisymmetric states by abruptly projecting with the symmetrizer or antisymmetrizer, this paper investigates rapid but continuous symmetrization via environment-induced decoherence. Density operators are transformed to a symmetric observable via a semigroup map obtained from an interacting Hamiltonian. Likewise, a completely positive dynamical map transforms a completely asymmetric state to either a symmetric or antisymmetric state. The …

Pre-perihelion radio observations of comet 12P/Pons-Brooks with Tianma radio telescope
Juncen Li, Xian Shi, Jianchun Shi, Yuehua Ma, Bin Yang, Jian-Yang Li, Zexi Xing, Man-To Hui, Zhen Wang, Ruining Zhao
https://arxiv.org/abs/2508.06936

Pre-perihelion radio observations of comet 12P/Pons-Brooks with Tianma radio telescope
{The multiple outburst events of comet 12P/Pons-Brooks during its 2024 apparition offer a unique window into highly-active volatile releasing processes not observable during quiescent periods. We performed radio observations of comet 12P/Pons-Brooks with the Tianma-65m radio telescope, targeting the OH and NH$_3$ inversion lines at 18-cm and 1.3-cm, respectively. By monitoring 12P at different heliocentric distances on its inbound journey, we aim to provide insights into the comet's volatile co…

"Le Monde – Une éclipse totale de Lune visible en France le 7 septembre"
https://www.lemonde.fr/autour-du-ciel/article/2025/09/03/une-eclipse-totale-de-lune-visible-en-france-le-7-septembre_6638741_65…

Une éclipse totale de Lune visible en France le 7 septembre
Le disque éblouissant de la Pleine Lune va être éclipsé par l’ombre de la Terre et ce magnifique phénomène naturel sera observable en métropole au crépuscule et en début de nuit.

Replaced article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[2/2]:
- On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
Bal\'azs Csan\'ad Cs\'aji, L\'aszl\'o Gy\"orfi, Ambrus Tam\'as, Harro Walk

Solvable Models of Heat Transport in Quantum Mechanics
R Loganayagam, Prithvi Narayan, Swathi T S
https://arxiv.org/abs/2508.09253 https://arxiv.org/pdf/25…

Solvable Models of Heat Transport in Quantum Mechanics
We investigate solvable models of heat transport between a pair of quantum mechanical systems initialized at two different temperatures. At time $t=0$, a weak interaction is switched on between the systems, and we study the resulting energy transport. Focusing on the heat current as the primary observable, we analyze both the transient dynamics and the long-time behavior of the system. We demonstrate that simple toy models - including Random Matrix Theory like models ({\it RMT models}) and Schw…

AugerPrime: Status and first results
David Schmidt (for the Pierre Auger Collaboration)
https://arxiv.org/abs/2508.08056 https://arxiv.org/pdf/2508.08056…

AugerPrime: Status and first results
With the knowledge and statistical precision derived from two decades of measurement, the Pierre Auger Observatory has significantly deepened our understanding of ultra-high-energy cosmic rays while unearthing an increasingly complex astrophysical landscape and exposing tensions with hadronic interaction models. The field now demands the mass of individual cosmic-ray primaries as an observable with an exposure that only the 3000-square-kilometer surface array of the Observatory can provide. Acc…

Adaptive Science Operations in Deep Space Missions Using Offline Belief State Planning
Grace Ra Kim, Hailey Warner, Duncan Eddy, Evan Astle, Zachary Booth, Edward Balaban, Mykel J. Kochenderfer
https://arxiv.org/abs/2510.08812

Adaptive Science Operations in Deep Space Missions Using Offline Belief State Planning
Deep space missions face extreme communication delays and environmental uncertainty that prevent real-time ground operations. To support autonomous science operations in communication-constrained environments, we present a partially observable Markov decision process (POMDP) framework that adaptively sequences spacecraft science instruments. We integrate a Bayesian network into the POMDP observation space to manage the high-dimensional and uncertain measurements typical of astrobiology missions…

Uncertainties in the supermassive black hole abundance and implications for the GW background
Gabriela Sato-Polito, Matias Zaldarriaga
https://arxiv.org/abs/2509.08041 https://

Uncertainties in the supermassive black hole abundance and implications for the GW background
The present-day mass function of supermassive black holes is the most important observable quantity for the prediction and theoretical interpretation of the gravitational wave background (GWB) measured by pulsar timing arrays (PTAs). Due to the limited sample size of galaxies with dynamically inferred SMBH masses, more readily measurable galaxy properties $X$ that correlate with the black hole mass are used as labels (via scaling relations $M_{\bullet}-X$), which can then be counted in a larger…

Transition from exceptional points to observable nonlinear bifurcation points in anti-PT symmetric coupled cavity systems
Takahiro Uemura, Kenta Takata, Masaya Notomi
https://arxiv.org/abs/2509.01062

Transition from exceptional points to observable nonlinear bifurcation points in anti-PT symmetric coupled cavity systems
Exceptional points (EPs) in anti-parity-time (APT)-symmetric systems have attracted significant interest. While linear APT-symmetric systems exhibit structural similarities with nonlinear dissipative systems, such as mutually injection-locked lasers, the correspondence between exceptional points in linear non-Hermitian Hamiltonians and bifurcation phenomena in nonlinear lasing dynamics has remained unclear. We demonstrated that, in a two-cavity system with APT symmetry and gain saturation nonli…

Black hole mergers beyond general relativity: a self-force approach
Ayush Roy, Lorenzo K\"uchler, Adam Pound, Rodrigo Panosso Macedo
https://arxiv.org/abs/2510.11793 https:…

Black hole mergers beyond general relativity: a self-force approach
Gravitational waves from binary black hole mergers provide a glimpse of gravitational dynamics in its most extreme observable regime, potentially enabling precision tests of general relativity (GR) and of the Kerr description of black holes. However, until recently, numerical simulations of black hole mergers have not been possible in theories beyond GR. While recent breakthroughs have overcome that obstacle, simulations covering the full, interesting range of binary parameters remain unfeasibl…

Eternal inflation bubble collision signature on CMB remote dipole and quadrupole fields
Hongbo Cai, Pengjie Zhang, Yilun Guan
https://arxiv.org/abs/2510.12134 https://

Eternal inflation bubble collision signature on CMB remote dipole and quadrupole fields
The remote dipole and quadrupole fields (RDF/RQF) encode information about the observable universe as seen from remote places within our past light cone. Sensitive to the superhorizon inhomogeneites, they provide a unique way to probe physics at the largest scales, bypassing the limitations of cosmic variance inherent in the primary cosmic microwave background (CMB). In this work, we focus on the bubble collision predicted by the eternal inflation theory, which can leave distinct azimuthally sy…

Jet quenching without energy loss
Liliana Apolin\'ario, Chiara Le Roux, Korinna Zapp
https://arxiv.org/abs/2510.11914 https://arxiv.org/pdf/2510.11914

Jet quenching without energy loss
The onset of jet quenching, i.e. the suppression of high transverse momentum particles and jets, is an important question in the context of understanding the onset of collective behaviour and small collision systems. We investigate a minimal scenario where a hard parton experiences a single soft re-scattering that leaves the kinematics unmodified, but the colour exchange leads to a loss of colour coherence that is observable in the final distribution of fragments. In particular, the formation t…

Reducing quantum resources for observable estimation with window-assisted coherent QPE
Harriet Apel, Cristian L. Cortes, Jessica Lemieux, Mark Steudtner
https://arxiv.org/abs/2508.06677

Reducing quantum resources for observable estimation with window-assisted coherent QPE
Quantum Phase Estimation (QPE) routines are known to fail probabilistically even with perfect gates and input states. This effect stems from an incompatibility of finite-sized quantum registers to capture a phase within QPE with phase angles of infinite precision, and the effect extend even beyond what would be reasonably expected from rounding. This effect can be partially mitigated by biasing the phase register with a window, or taper state, from classical signal processing. This paper focuse…

Reconstructing the Hamiltonian from the local density of states using neural networks
Nisarga Paul, Andrew Ma, Kevin P. Nuckolls
https://arxiv.org/abs/2509.09604 https://…

Reconstructing the Hamiltonian from the local density of states using neural networks
Reconstructing a quantum system's Hamiltonian from limited yet experimentally observable information is interesting both as a practical task and from a fundamental standpoint. We pose and investigate the inverse problem of reconstructing a Hamiltonian from a spatial map of the local density of states (LDOS) near a fixed energy. We demonstrate high-quality recovery of Hamiltonians from the LDOS using supervised learning. In particular, we generate synthetic data from single-particle Hamiltonians…

Decision-Dependent Distributionally Robust Optimization with Application to Dynamic Pricing
Chengrui Qu, Huiwen Jia, Pengcheng You
https://arxiv.org/abs/2508.06965 https://

Decision-Dependent Distributionally Robust Optimization with Application to Dynamic Pricing
We consider decision-making problems under decision-dependent uncertainty (DDU), where the distribution of uncertain parameters depends on the decision variables and is only observable through a finite offline dataset. To address this challenge, we formulate a decision-dependent distributionally robust optimization (DD-DRO) problem, and leverage multivariate interpolation techniques along with the Wasserstein metric to construct decision-dependent nominal distributions (thereby decision-depende…

When not to help: planning for lasting human-AI collaboration
Mark Steyvers, Lukas Mayer
https://arxiv.org/abs/2508.01837 https://arxiv.org/pdf/2508.01837

When not to help: planning for lasting human-AI collaboration
AI systems and technologies that can interact with humans in real time face a communication dilemma: when to offer assistance and how frequently. Overly frequent or contextually redundant assistance can cause users to disengage, undermining the long-term benefits of AI assistance. We introduce a cognitive modeling framework based on Partially Observable Markov Decision Processes (POMDPs) that addresses this timing challenge by inferring a user's latent cognitive state related to AI engagement o…

Confinement, Nonlocal Observables, and Haag Duality Violation in the Algebraic Structure of 1 1-Dimensional Non-Abelian Gauge Theories
Fidele J. Twagirayezu
https://arxiv.org/abs/2508.09172

Confinement, Nonlocal Observables, and Haag Duality Violation in the Algebraic Structure of 1+1-Dimensional Non-Abelian Gauge Theories
This article presents a comprehensive and rigorously formulated algebraic framework for investigating 1+1-dimensional SU(N) gauge theories within the paradigm of Algebraic Quantum Field Theory (AQFT), building upon foundational results established for the Abelian Schwinger model. We meticulously construct a net of local observable C*-algebras, generated by gauge-invariant composite operators such as color-singlet currents and traces of non-Abelian electric fields, with the non-Abelian Gauss's l…

Good things come to those who wait: Watching donor stars evolve towards a mass-transfer instability
Karel D. Temmink, Onno R. Pols, Stephen Justham, Nadia Blagorodnova
https://arxiv.org/abs/2509.09492 …

Good things come to those who wait: Watching donor stars evolve towards a mass-transfer instability
Unstable mass transfer in binary systems can lead to transients such as luminous red novae (LRNe). Observations of such transients are valuable for understanding and testing models of mass transfer. For donor stars in the Hertzsprung gap, there can be a long phase of mass-transfer evolution before instability sets in. Only few case studies of such delayed dynamical instability (DDI) mass transfer exist. None consider the full pre-instability evolution and the effects thereof on the observable p…

UltraHorizon: Benchmarking Agent Capabilities in Ultra Long-Horizon Scenarios
Haotian Luo, Huaisong Zhang, Xuelin Zhang, Haoyu Wang, Zeyu Qin, Wenjie Lu, Guozheng Ma, Haiying He, Yingsha Xie, Qiyang Zhou, Zixuan Hu, Hongze Mi, Yibo Wang, Naiqiang Tan, Hong Chen, Yi R. Fung, Chun Yuan, Li Shen
https://arxiv.org/abs/2509.21766

UltraHorizon: Benchmarking Agent Capabilities in Ultra Long-Horizon Scenarios
Autonomous agents have recently achieved remarkable progress across diverse domains, yet most evaluations focus on short-horizon, fully observable tasks. In contrast, many critical real-world tasks, such as large-scale software development, commercial investment, and scientific discovery, unfold in long-horizon and partially observable scenarios where success hinges on sustained reasoning, planning, memory management, and tool use. Existing benchmarks rarely capture these long-horizon challenge…

Ergodicity and hydrodynamics: from quantum to classical spin systems
Jiaozi Wang, Luca Capizzi, Dario Poletti, Leonardo Mazza
https://arxiv.org/abs/2509.04098 https://

Ergodicity and hydrodynamics: from quantum to classical spin systems
We show that in classical spin systems the precise nature of the late-time hydrodynamic tails of the autocorrelation functions of a generic observable is determined by (i) the dynamical critical exponent and (ii) the equilibrium thermodynamic properties of the corresponding observable. We provide numerical results for one- and two-dimensional systems and present theoretical considerations that only rely on the notion of ergodicity. Our result extends to the classical framework the relaxation-ov…

Multi Robot Coordination in Highly Dynamic Environments: Tackling Asymmetric Obstacles and Limited Communication
Vincenzo Suriani, Daniele Affinita, Domenico D. Bloisi, Daniele Nardi
https://arxiv.org/abs/2509.08859

Multi Robot Coordination in Highly Dynamic Environments: Tackling Asymmetric Obstacles and Limited Communication
Coordinating a fully distributed multi-agent system (MAS) can be challenging when the communication channel has very limited capabilities in terms of sending rate and packet payload. When the MAS has to deal with active obstacles in a highly partially observable environment, the communication channel acquires considerable relevance. In this paper, we present an approach to deal with task assignments in extremely active scenarios, where tasks need to be frequently reallocated among the agents pa…

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/2]:
- On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
Bal\'azs Csan\'ad Cs\'aji, L\'aszl\'o Gy\"orfi, Ambrus Tam\'as, Harro Walk

Engineered over Emergent Communication in MARL for Scalable and Sample-Efficient Cooperative Task Allocation in a Partially Observable Grid
Brennen A. Hill, Mant Koh En Wei, Thangavel Jishnuanandh
https://arxiv.org/abs/2508.02912

Engineered over Emergent Communication in MARL for Scalable and Sample-Efficient Cooperative Task Allocation in a Partially Observable Grid
We compare the efficacy of learned versus engineered communication strategies in a cooperative multi-agent reinforcement learning (MARL) environment. For the learned approach, we introduce Learned Direct Communication (LDC), where agents generate messages and actions concurrently via a neural network. Our engineered approach, Intention Communication, employs an Imagined Trajectory Generation Module (ITGM) and a Message Generation Network (MGN) to formulate messages based on predicted future sta…

Slantwise convection and heat transport in the icy moon oceans
Yaoxuan Zeng, Malte F. Jansen
https://arxiv.org/abs/2508.06480 https://arxiv.org/pdf/2508.06…

Slantwise convection and heat transport in the icy moon oceans
Ocean heat transport on icy moons shapes the ice shell topography, a primary observable of these moons. Two key processes control the heat transport: baroclinic instability driven by surface buoyancy contrasts and convective instability driven by heating from the core. However, global ocean simulations cannot accurately resolve convection under realistic icy moon conditions and instead often use Earth-based convective parameterizations, which capture only vertical convective mixing and cannot r…

Verifiable blind observable estimation: A composably secure protocol for near-term quantum advantage tasks
Bo Yang, Elham Kashefi, Harold Ollivier
https://arxiv.org/abs/2510.08548

Verifiable blind observable estimation: A composably secure protocol for near-term quantum advantage tasks
The rapid advance of quantum hardware is spotlighting pre-fault-tolerant tasks that may no longer be efficiently validated by classical means and are likely to run on potentially untrusted remote quantum servers. This motivates problem-independent verification protocols with rigorous guarantees. The Verifiable Blind Quantum Computation (VBQC) protocol provides delegated computation where the composable security spans the confidentiality and integrity of the computation. However, the success o…

Comparative Analysis of Parameterized Action Actor-Critic Reinforcement Learning Algorithms for Web Search Match Plan Generation
Ubayd Bapoo, Clement N Nyirenda
https://arxiv.org/abs/2510.03064

Comparative Analysis of Parameterized Action Actor-Critic Reinforcement Learning Algorithms for Web Search Match Plan Generation
This study evaluates the performance of Soft Actor Critic (SAC), Greedy Actor Critic (GAC), and Truncated Quantile Critics (TQC) in high-dimensional decision-making tasks using fully observable environments. The focus is on parametrized action (PA) spaces, eliminating the need for recurrent networks, with benchmarks Platform-v0 and Goal-v0 testing discrete actions linked to continuous action-parameter spaces. Hyperparameter optimization was performed with Microsoft NNI, ensuring reproducibility…

Forecasting the Observable Rates of Gravitationally Lensed Supernovae for the PASSAGES Dusty Starbursts
Patrick S. Kamieneski, Rogier A. Windhorst, Brenda L. Frye, Min S. Yun, Kevin C. Harrington, Simon D. Mork, Nicholas Foo, Nikhil Garuda, Massimo Pascale, Belen Alcalde Pampliega, Timothy Carleton, Seth H. Cohen, Carlos Garcia Diaz, Rolf A. Jansen, Eric F. Jimenez-Andrade, Anton M. Koekemoer, James D. Lowenthal, Allison Noble, Justin D. R. Pierel, Amit Vishwas, Q. Daniel Wang, Ilsang …

Forecasting the Observable Rates of Gravitationally Lensed Supernovae for the PASSAGES Dusty Starbursts
More than 60 years have passed since the first formal suggestion to use strongly-lensed supernovae to measure the expansion rate of the Universe through time-delay cosmography. Yet, fewer than 10 such objects have ever been discovered. We consider the merits of a targeted strategy focused on lensed hyperluminous infrared galaxies-- among the most rapidly star-forming galaxies known in the Universe. With star formation rates (SFRs) $\sim {200 - 6000}~\textrm{M}_\odot~\textrm{yr}^{-1}$, the $\sim…

From Product Hilbert Spaces to the Generalized Koopman Operator and the Nonlinear Fundamental Lemma
Mircea Lazar
https://arxiv.org/abs/2508.07494 https://a…

From Product Hilbert Spaces to the Generalized Koopman Operator and the Nonlinear Fundamental Lemma
The generalization of the Koopman operator to systems with control input and the derivation of a nonlinear fundamental lemma are two open problems that play a key role in the development of data-driven control methods for nonlinear systems. Both problems hinge on the construction of observable or basis functions and their corresponding Hilbert space that enable an infinite-dimensional, linear system representation. In this paper we derive a novel solution to these problems based on orthonormal …

Learning-Based Data-Assisted Port-Hamiltonian Control for Free-Floating Space Manipulators
Mostafa Eslami, Maryam Babazadeh
https://arxiv.org/abs/2509.09563 https://

Learning-Based Data-Assisted Port-Hamiltonian Control for Free-Floating Space Manipulators
A generic data-assisted control architecture within the port-Hamiltonian framework is proposed, introducing a physically meaningful observable that links conservative dynamics to all actuation, dissipation, and disturbance channels. A robust, model-based controller combined with a high-gain decentralized integrator establishes large robustness margins and strict time-scale separation, ensuring that subsequent learning cannot destabilize the primary dynamics. Learning, selected for its generaliz…

Beyond Neutrino Mass: Observable $n$-$\overline{n}$ Oscillations in UV Complete Seesaw Models
Ilja Dorsner, Svjetlana Fajfer, Shaikh Saad
https://arxiv.org/abs/2509.00145 https:…

Beyond Neutrino Mass: Observable $n$-$\overline{n}$ Oscillations in UV Complete Seesaw Models
Next-generation experiments, such as the Deep Underground Neutrino Experiment and the European Spallation Source, are set to dramatically improve sensitivity to neutron-antineutron oscillation that is a direct probe of $ΔB = 2$ baryon number violation. The discovery of such a rare process would indicate physics beyond the Standard Model and could point to specific unified theories that allow observable $n-\overline{n}$ transitions. We accordingly examine $n-\overline{n}$ oscillations within a …

Coupled Time-Dependent Proton Acceleration and Leptonic-Hadronic Radiation in Turbulent Supermassive Black Hole Coronae
Chengchao Yuan, Damiano F. G. Fiorillo, Maria Petropoulou, Qinrui Liu
https://arxiv.org/abs/2508.08233

Coupled Time-Dependent Proton Acceleration and Leptonic-Hadronic Radiation in Turbulent Supermassive Black Hole Coronae
Turbulent coronae of supermassive black holes can accelerate non-thermal particles to high energies and produce observable radiation, but capturing this process is challenging due to comparable timescales of acceleration, cooling, and the development of cascades. We present a time-dependent numerical framework that self-consistently couples proton acceleration -- modeled by the Fokker-Planck equation -- with leptonic-hadronic radiation. For the neutrino-emitting Seyfert galaxy NGC 1068, we repr…

Inflationary Models with Gauss-Bonnet Coupling in Light of ACT Observations
Yigan Zhu, Qing Gao, Yungui Gong, Zhu Yi
https://arxiv.org/abs/2508.09707 https://

Inflationary Models with Gauss-Bonnet Coupling in Light of ACT Observations
Recent analyses combining Atacama Cosmology Telescope (ACT) data with other cosmological datasets report a higher scalar spectral index $n_s$, creating tension with a wide range of inflationary models. Since a Gauss-Bonnet term with a coupling function $ξ(ϕ) = 3λ/[4V(ϕ)]$ leaves $n_s$ nearly unchanged (up to a field rescaling) while reducing the tensor-to-scalar ratio $r$ by a factor $(1-λ)$, so choosing $(1-λ)$ sufficiently small effectively removes $r$ as a limiting observable, making i…

Towards Causal Representation Learning with Observable Sources as Auxiliaries
Kwonho Kim, Heejeong Nam, Inwoo Hwang, Sanghack Lee
https://arxiv.org/abs/2509.19058 https://

From Kardar-Parisi-Zhang scaling to soliton proliferation in Josephson junction arrays
Mikheil Tsitsishvili, Reinhold Egger, Karsten Flensberg, Sebastian Diehl
https://arxiv.org/abs/2509.08479

From Kardar-Parisi-Zhang scaling to soliton proliferation in Josephson junction arrays
We propose Josephson junction arrays as realistic platforms for observing nonequilibrium scaling laws characterizing the Kardar-Parisi-Zhang (KPZ) universality class, and space-time soliton proliferation. Focusing on a two-chain ladder geometry, we perform numerical simulations for the roughness function. Together with analytical arguments, our results predict KPZ scaling at intermediate time scales, extending over sufficiently long time scales to be observable, followed by a crossover to the a…

One-third of Sun-like stars are born with misaligned planet-forming disks
Lauren I. Biddle (The University of Texas at Austin), Brendan P. Bowler (University of California Santa Barbara), Marvin Morgan (The University of Texas at Austin, University of California Santa Barbara), Quang H. Tran (Yale University), Ya-Lin Wu (Taiwan Normal University)
https://

One-third of Sun-like stars are born with misaligned planet-forming disks
Exoplanets are organized in a broad array of orbital configurations that reflect their formation along with billions of years of dynamical processing through gravitational interactions. This history is encoded in the angular momentum architecture of planetary systems--the relation between the rotational properties of the central star and the orbital geometry of planets. A primary observable is the alignment (or misalignment) between the rotational axis of the star and the orbital plane of its p…

Finite-Horizon Partially Observable Semi-Markov Games with Risk Probability Criteria
Xin Wen, Li Xia, Zhihui Yu
https://arxiv.org/abs/2508.17791 https://ar…

Finite-Horizon Partially Observable Semi-Markov Games with Risk Probability Criteria
This paper studies partially observable two-person zero-sum semi-Markov games under a probability criterion, in which the system state may not be completely observed. It focuses on the probability that the accumulated rewards of player 1 (i.e., the incurred costs of player 2) fall short of a specified target at the terminal stage, which represents the risk of player 1 and the capacity of player 2. We study the game model via the technology of augmenting state space with the joint conditional di…

Halo Properties from Observable Measures of Environment: II. Central versus Satellite Classification
Haley Bowden, Peter Behroozi
https://arxiv.org/abs/2509.25312 https://

Halo Properties from Observable Measures of Environment: II. Central versus Satellite Classification
A physical understanding of galaxy formation and evolution benefits from an understanding of the connections between galaxies, their host dark matter halos, and their environments. In particular, interactions with more-massive neighbors can leave lasting imprints on both galaxies and their hosts. Distinguishing between populations of galaxies with differing environments and interaction histories is therefore essential for isolating the role of environment in shaping galaxy properties. We presen…

Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environments
Jiahui Yang, Jason Jingzhou Liu, Yulong Li, Youssef Khaky, Kenneth Shaw, Deepak Pathak
https://arxiv.org/abs/2509.06953

Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environments
Generating collision-free motion in dynamic, partially observable environments is a fundamental challenge for robotic manipulators. Classical motion planners can compute globally optimal trajectories but require full environment knowledge and are typically too slow for dynamic scenes. Neural motion policies offer a promising alternative by operating in closed-loop directly on raw sensory inputs but often struggle to generalize in complex or dynamic settings. We propose Deep Reactive Policy (DRP…

Asymptotic Schwarzschild solutions in $f(R)$ gravity and their observable effects on the photon sphere of black holes
Miguel Aparicio Resco
https://arxiv.org/abs/2510.00702 http…

Asymptotic Schwarzschild solutions in $f(R)$ gravity and their observable effects on the photon sphere of black holes
We investigate asymptotic Schwarzschild exterior solutions in the context of modified gravity theories, specifically within the framework of $f(R)$ gravity, where the asymptotic behavior recovers the standard Schwarzschild solution of General Relativity. Unlike previous studies that rely mainly on analytical approximations, our approach combines asymptotic analysis with numerical integration of the underlying differential equations. Using these solutions, we analyze strong lensing effects to ob…

A Highly Predictive Neutrino Model: The Step Toward Precision
Pralay Chakraborty, Sagar Tirtha Goswami, Subhankar Roy
https://arxiv.org/abs/2508.07837 https://

A Highly Predictive Neutrino Model: The Step Toward Precision
A highly predictive neutrino mass matrix texture is proposed. The texture is minimal and carries two interesting correlations. It gives precise and unambiguous answers to almost all the current issues related to observable parameters in neutrino phenomenology. The texture is developed in a framework of type-I + type-II seesaw mechanisms with an extended group structure of $SU(2)_L \times U(1)_Y \times A_4 \times Z_{10} \times Z_{7} \times Z_{3}$.

Analytical and Numerical Analysis of QPO Frequencies in Quantum-Corrected Black Hole Spacetimes
Ahmad Al-Badawi, Faizuddin Ahmed, Orhan Donmez, Fatih Dogan, Behnam Pourhassan, \.Izzet Sakall{\i}, Yassine Sekhmani
https://arxiv.org/abs/2509.08674

Analytical and Numerical Analysis of QPO Frequencies in Quantum-Corrected Black Hole Spacetimes
This investigation examines QPOs in two quantum-corrected BH spacetimes that preserve general covariance while incorporating quantum gravitational effects through a dimensionless parameter ζ. We combine analytical derivations of epicyclic frequencies with comprehensive numerical simulations of BHL accretion to explore how quantum corrections manifest in observable astrophysical phenomena. Using a fiducial BH mass of M=10M_\odot representative of stellar-mass X-ray binaries, we demonstrate that…

HyPlan: Hybrid Learning-Assisted Planning Under Uncertainty for Safe Autonomous Driving
Donald Pfaffmann, Matthias Klusch, Marcel Steinmetz
https://arxiv.org/abs/2510.07210 http…

HyPlan: Hybrid Learning-Assisted Planning Under Uncertainty for Safe Autonomous Driving
We present a novel hybrid learning-assisted planning method, named HyPlan, for solving the collision-free navigation problem for self-driving cars in partially observable traffic environments. HyPlan combines methods for multi-agent behavior prediction, deep reinforcement learning with proximal policy optimization and approximated online POMDP planning with heuristic confidence-based vertical pruning to reduce its execution time without compromising safety of driving. Our experimental performan…

Robust Belief-State Policy Learning for Quantum Network Routing Under Decoherence and Time-Varying Conditions
Amirhossein Taherpour, Abbas Taherpour, Tamer Khattab
https://arxiv.org/abs/2509.08654

Robust Belief-State Policy Learning for Quantum Network Routing Under Decoherence and Time-Varying Conditions
This paper presents a feature-based Partially Observable Markov Decision Process (POMDP) framework for quantum network routing, combining belief-state planning with Graph Neural Networks (GNNs) to address partial observability, decoherence, and scalability challenges in dynamic quantum systems. Our approach encodes complex quantum network dynamics, including entanglement degradation and time-varying channel noise, into a low-dimensional feature space, enabling efficient belief updates and scala…

Comparison of typicality in quantum and classical many-body systems
Peter Reimann, Nicolas Nessi
https://arxiv.org/abs/2510.06795 https://arxiv.org/pdf/251…

Comparison of typicality in quantum and classical many-body systems
Quantum typicality refers to the phenomenon that the expectation values of any given observable are nearly identical for the overwhelming majority of all normalized vectors in a sufficiently high-dimensional Hilbert (sub-)space. As a consequence, we show that the thermal equilibrium fluctuations in many-body quantum systems can be very closely imitated by the purely quantum mechanical uncertainties (quantum fluctuations) of suitably chosen pure states. On the other hand, we find that analogous …

Signals of Bursts from the Very Early Universe
Leo Stodolsky, J. Silk
https://arxiv.org/abs/2509.00237 https://arxiv.org/pdf/2509.00237

Signals of Bursts from the Very Early Universe
We consider possible observable signals from explosive events in the very early universe, ``bursts". These could be expected in connection with massive black hole or ``baby universe'' formation. We anticipate that such major disruptions of spacetime would be associated with neutrino and perhaps other pulses. While these seem to be not detectable directly, we discuss how they could lead to potentially observable signals. We analyze how the pulses from very early times may ``escape'', tha…

Light Meson Resonances
J. R. Pelaez (U. Complutense de Madrid,IPARCOS)
https://arxiv.org/abs/2509.08648 https://arxiv.org/pdf/2509.08648

Light Meson Resonances
We provide a modern pedagogical introduction to light mesons. We discuss their masses and widths, their classification into multiplets of isospin and flavor SU(3), as well as other quantum numbers, mixing schemes, observable states, and their disposition in Regge trajectories. We briefly introduce the relevant concepts of Quantum Chromodynamics, including confinement, chiral symmetry, and the relationship between poles and resonances. We discuss their interpretation in terms of quark-model ordi…

Gamma-Ray Spectra of $R$-Process Nuclei
Axel Gross, Samuel Cupp, Matthew R Mumpower
https://arxiv.org/abs/2510.08560 https://arxiv.org/pdf/2510.08560

Gamma-Ray Spectra of $R$-Process Nuclei
The radioactive decay of unstable nuclei created in the rapid neutron capture process release a large amount of $γ$-rays. When the ejecta is optically thick, these $γ$-rays may contribute to an associated kilonova. Once transparent, prominent spectral features will be directly observable in current and future $γ$-ray detectors. In this work, we study and compare the $γ$-ray spectra of a limited, weak, strong, and extended $r$-process across a broad timescale, identifying the nuclei which si…

Kete: Predicting Known Minor Bodies in Images
D. Dahlen, Y. G. Kwon, J. R. Masiero, T. Spahr, A. K. Mainzer
https://arxiv.org/abs/2509.04666 https://arxiv.…

Kete: Predicting Known Minor Bodies in Images
Kete is an open-source software package for quickly and accurately predicting the positions and magnitudes of asteroids and comets in large-scale, all-sky surveys. It can predict observable objects for any ground or space-based telescope. Kete contains a collection of tools, including simple optical and thermal modeling, $n$-body orbit calculations, and custom multi-threaded SPICE kernel support. It can be used for observation planning, pre-discovery of detections at a large scale, and labeling…

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Guibin Zhang, Hejia Geng, Xiaohang Yu, Zhenfei Yin, Zaibin Zhang, Zelin Tan, Heng Zhou, Zhongzhi Li, Xiangyuan Xue, Yijiang Li, Yifan Zhou, Yang Chen, Chen Zhang, Yutao Fan, Zihu Wang, Songtao Huang, Yue Liao, Hongru Wang, Mengyue Yang, Heng Ji, Michael Littman, Jun Wang, Shuicheng Yan, Philip Torr, Lei Bai

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
The emergence of agentic reinforcement learning (Agentic RL) marks a paradigm shift from conventional reinforcement learning applied to large language models (LLM RL), reframing LLMs from passive sequence generators into autonomous, decision-making agents embedded in complex, dynamic worlds. This survey formalizes this conceptual shift by contrasting the degenerate single-step Markov Decision Processes (MDPs) of LLM-RL with the temporally extended, partially observable Markov decision processes…

ContextVLA: Vision-Language-Action Model with Amortized Multi-Frame Context
Huiwon Jang, Sihyun Yu, Heeseung Kwon, Hojin Jeon, Younggyo Seo, Jinwoo Shin
https://arxiv.org/abs/2510.04246

ContextVLA: Vision-Language-Action Model with Amortized Multi-Frame Context
Leveraging temporal context is crucial for success in partially observable robotic tasks. However, prior work in behavior cloning has demonstrated inconsistent performance gains when using multi-frame observations. In this paper, we introduce ContextVLA, a policy model that robustly improves robotic task performance by effectively leveraging multi-frame observations. Our approach is motivated by the key observation that Vision-Language-Action models (VLA), i.e., policy models built upon a Visio…

Platform-Agnostic Modular Architecture for Quantum Benchmarking
Neer Patel, Anish Giri, Hrushikesh Pramod Patil, Noah Siekierski, Avimita Chatterjee, Sonika Johri, Timothy Proctor, Thomas Lubinski, Siyuan Niu
https://arxiv.org/abs/2510.08469

Platform-Agnostic Modular Architecture for Quantum Benchmarking
We present a platform-agnostic modular architecture that addresses the increasingly fragmented landscape of quantum computing benchmarking by decoupling problem generation, circuit execution, and results analysis into independent, interoperable components. Supporting over 20 benchmark variants ranging from simple algorithmic tests like Bernstein-Vazirani to complex Hamiltonian simulation with observable calculations, the system integrates with multiple circuit generation APIs (Qiskit, CUDA-Q, C…

Search for gravitational waves from eccentric binary black holes with an effective-one-body template
Yi-Fan Wang, Alexander H. Nitz
https://arxiv.org/abs/2508.05018 https://

Search for gravitational waves from eccentric binary black holes with an effective-one-body template
As gravitational wave astronomy has entered an era of routine detections, it becomes increasingly important to precisely measure the physical parameters of individual events and infer population properties. Eccentricity is a key observable, suggesting that binaries form in a dense stellar environment through dynamical encounters. This work performs the first matched-filtering search for gravitational waves from eccentric binary black holes (BBHs) covering the mass range $[5, 200]~M_\odot$ and e…

Evidence for Supermassive Black Hole Binaries
Martin G. H. Krause, Martin A. Bourne, Silke Britzen, Adi Foord, Jenny E. Greene, Melanie Habouzit, Maya A. Horton, Lucio Mayer, Hannah Middleton, Rebecca Nealon, Julia M. Sisk-Reyn\'es, Christopher S. Reynolds, Debora Sijacki
https://arxiv.org/abs/2510.07534

Evidence for Supermassive Black Hole Binaries
We review the state of the evidence for the existence and observational appearance of supermassive black hole binaries. Such objects are expected from standard hierarchical galaxy evolution to form after two galaxies, each containing a supermassive black hole, have merged, in the centre of the merger remnant. A complex interaction is predicted to take place with stars and gas in the host galaxy, leading to observable signatures in weakly as well as actively accreting phases. Direct observationa…

Entropy and multiplicity of hadrons in the high energy limit within dipole cascade models
Krzysztof Kutak, S\'andor L\"ok\"os
https://arxiv.org/abs/2509.07898 http…

Entropy and multiplicity of hadrons in the high energy limit within dipole cascade models
We investigate and compare QCD dipole cascade models, the 1D Mueller dipole model, its high energy limit and its generalization that follows from studies of 1D systems with conformal symmetry. To address the ambiguity stemming from different definitions of the rapidity ranges in experimental measurements, we propose the entropy as the function of the logarithm of the average multiplicity, $S(\ln\langle n \rangle)$, as a universal observable. From the solutions of the models, we calculate both t…

Uncertainty Principle from Operator Asymmetry
Xingze Qiu
https://arxiv.org/abs/2509.06760 https://arxiv.org/pdf/2509.06760…

Uncertainty Principle from Operator Asymmetry
The uncertainty principle is fundamentally rooted in the algebraic asymmetry between observables. We introduce a new class of uncertainty relations grounded in the resource theory of asymmetry, where incompatibility is quantified by an observable's intrinsic, state-independent capacity to break the symmetry associated with another. This ``operator asymmetry,'' formalized as the asymmetry norm, leads to a variance-based uncertainty relation for pure states that can be tighter than the standard R…

MobRT: A Digital Twin-Based Framework for Scalable Learning in Mobile Manipulation
Yilin Mei, Peng Qiu, Wei Zhang, WenChao Zhang, Wenjie Song
https://arxiv.org/abs/2510.04592 ht…

MobRT: A Digital Twin-Based Framework for Scalable Learning in Mobile Manipulation
Recent advances in robotics have been largely driven by imitation learning, which depends critically on large-scale, high-quality demonstration data. However, collecting such data remains a significant challenge-particularly for mobile manipulators, which must coordinate base locomotion and arm manipulation in high-dimensional, dynamic, and partially observable environments. Consequently, most existing research remains focused on simpler tabletop scenarios, leaving mobile manipulation relativel…

Large-scale peculiar velocities in the universe
Christos G. Tsagas, Leandros Perivolaropoulos, Kerkyra Asvesta
https://arxiv.org/abs/2510.05340 https://arx…

Large-scale peculiar velocities in the universe
Observations have repeatedly confirmed the presence of large-scale peculiar motions in the universe, commonly referred to as ``bulk flows''. These are vast regions of the observable universe, typically spanning scales of several hundred Mpc, that move coherently with speeds of the order of several hundred km/sec. While there is a general consensus on the direction of these motions, discrepancies persist in their reported sizes and velocities, with some of them exceeding the predictions of the s…

Quantum Entanglement without Spin-Analyzing Power Dependence at the Colliders
Junle Pei, Tianjun Li, Lina Wu, Xiqing Hao, Xiaochuan Wang
https://arxiv.org/abs/2510.08031 https:/…

Quantum Entanglement without Spin-Analyzing Power Dependence at the Colliders
We study the quantum entanglement at the colliders which is independent of the spin-analyzing powers. Taking $Λ(\to pπ^-)\barΛ(\to \bar{p}π^+)$ as an example, we investigate whether quantum entanglement in fermion pairs produced at colliders can be certified by using only angular information from final-state decays, while remaining independent of the parity-violating decay parameters $α_Λ$ and $α_{\barΛ}$. Building on a general decomposition of any angular observable in terms of Wigner …

Quantum Measurement Trees, II: Quantum Observables as Ortho-Measurable Functions and Density Matrices as Ortho-Probability Measures
Peter J. Hammond
https://arxiv.org/abs/2509.22617

Quantum Measurement Trees, II: Quantum Observables as Ortho-Measurable Functions and Density Matrices as Ortho-Probability Measures
Given a quantum state in the finite-dimensional Hilbert space $ \C^n $, the range of possible values of a quantum observable is usually identified with the discrete spectrum of eigenvalues of a corresponding Hermitian matrix. Here any such observable is identified with: (i) an ``ortho-measurable'' function defined on the Boolean ``ortho-algebra'' generated by the eigenspaces that form an orthogonal decomposition of $ \C^n $; (ii) a ``numerically identified'' orthogonal decomposition of $ \C^n $…

An analysis of the fragmentation function of gluon at next-to-leading order approximation
H. S. Nakhaei, G. R. Boroun
https://arxiv.org/abs/2508.05256 https://

An analysis of the fragmentation function of gluon at next-to-leading order approximation
We are investigating the behavior of the fragmentation function of a gluon, denoted as $ D_{g}(x,μ^2)$, where $μ$ represents the observable scale. This function is derived from the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution equations. Our objective is to evolve the fragmentation function of a gluon for heavy-quark-antiquark bound states with large transverse momentum using a Laplace transform technique. This method enables us to calculate numerical solutions for two and four…

Limits on the Axion-Photon Coupling from Chandrayaan-2
Tanmoy Kumar, N. P. S. Mithun, Subhendra Mohanty, Sourov Roy, B. S. Bharath Saiguhan, Santosh Vadawale
https://arxiv.org/abs/2510.06087

Limits on the Axion-Photon Coupling from Chandrayaan-2
Axions and axion-like particles (ALPs) have gained immense attention in searches for beyond Standard Model (BSM) physics. Experiments searching for axions leverage their predicted couplings to Standard Model (SM) particles to look for observable signals. Though weak, these couplings allow axions to be produced abundantly in the interiors of stars such as the Sun. Once created, axions can escape the Sun and while passing through the solar atmosphere, oscillate into photons in the magnetic field …

Fermionic-Adapted Shadow Tomography for dynamical correlation functions
Taehee Ko, Mancheon Han, Sangkook Choi
https://arxiv.org/abs/2508.03192 https://arx…

Fermionic-Adapted Shadow Tomography for dynamical correlation functions
Dynamical correlation functions are essential for characterizing the response of the quantum many-body systems to the external perturbation. As their calculation is classically intractible in general, quantum algorithms are promising in this aspect, but most rely on brute force measurement strategies that evaluate one body observable pair per circuit. In this work, we introduce Fermionic-Adapted Shadow Tomography (FAST) protocols, a new framework for the efficient calculation of multiple dynami…

Relativistic spin precession in homogeneous background fields
Yunhua Ding, Alan Kostelecky, Arnaldo J. Vargas
https://arxiv.org/abs/2509.05098 https://arxi…

Relativistic spin precession in homogeneous background fields
The Bargmann-Michel-Telegdi equation, which describes the precession of the spin of a charged Dirac particle moving in a homogeneous electromagnetic field, is generalized to include also other homogeneous background fields. The treatment incorporates observable coefficients that govern operators of mass dimensions three through six in the underlying Dirac effective field theory. A relativistic formulation valid in arbitrary inertial frames is obtained. The results are applicable to searches for…

Helicity correlation of dihadron in current and target fragmentation regions of unpolarized SIDIS
Xue-Qi Xi, Kai-Bao Chen, Xuan-Bo Tong, Shu-Yi Wei, Jing Wu
https://arxiv.org/abs/2510.06103

Helicity correlation of dihadron in current and target fragmentation regions of unpolarized SIDIS
We study the helicity correlation of two $Λ$ hyperons produced in unpolarized semi-inclusive deep inelastic scatterings (SIDIS), with one hyperon detected in the current fragmentation region and the other in the target fragmentation region. This observable provides direct access to the spin-dependent fragmentation function $G_{1Lq}$ and the spin-dependent fracture function $l_{1q}^L$ even in unpolarized lepton nucleon collisions. Utilizing the perturbative matching of the fracture function, we…

Strengthening the Uncertainty and the Reverse Uncertainty Relation Limits
M. Y. Abd-Rabbou, Cong-Feng Qiao
https://arxiv.org/abs/2508.02036 https://arxiv.o…

Strengthening the Uncertainty and the Reverse Uncertainty Relation Limits
Uncertainty relations are pivotal in delineating the limits of simultaneous measurements for observables. In this paper, we derive four novel uncertainty and reverse uncertainty relations for the sum of variances of two incompatible observables, leveraging the mathematical framework of the Maligranda inequality. These relations are shown to provide tighter bounds than several well-known existing relations. Furthermore, we extend these results to multi-observable scenarios by employing an inequa…

Overview of the latest developments in understanding the initial state and thermalization
Kirill Boguslavski
https://arxiv.org/abs/2510.04661 https://arxiv…

Overview of the latest developments in understanding the initial state and thermalization
A proper description of the non-equilibrium matter preceding the quark-gluon plasma (QGP) in heavy-ion collisions and its observable consequences remain a major theoretical challenge, while at the same time offering new opportunities for experimental exploration. In these proceedings, I provide an overview of studies presented in talks and posters at Quark Matter 2025 on this topic. We will focus on the latest developments regarding the features and the numerical description of the non-equilibr…