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arXiv preprints from January 1, 2026 through September 23, 2026 — 09:49:50 EST

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Posted in cond-mat.str-el · 2026-08-13 · Ryan Flynn, Adam Iaizzi, Sibin Yang, Ying-Jer Kao, Anders W. Sandvik

Imaginary-time correlations in time-sliced stochastic series expansion

Combined with numerical analytic continuation techniques, quantum Monte Carlo (QMC) methods enable the extraction of real-frequency dynamical properties from imaginary-time correlation functions. However, the efficient computation of imaginary-time correlation functions by QMC simulations can (depending on the particular model used)...

💬 0 commentsarXiv:2608.13477v1PDF
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Posted in cs.AI · 2026-08-13 · Saisha Shetty, Satvik Tripathi, Austin Lin, Colin Zhao, Theodore Kim, Don Enwerem, Jacinta Arnold, Shahriar Faghani, Tessa S Cook

MARC v1: An Open-Source Multi-Agent Framework for Clinical AI Reasoning and Coordination

We present Multi-Agent Reasoning and Coordination (MARC), an open-source framework that replaces monolithic LLM prompting with deterministic multi-agent orchestration for clinical reasoning. MARC coordinates role-specialized agents for extraction, reasoning, answer generation, and evaluation, with explicit context passing and...

💬 0 commentsarXiv:2608.13476v1PDF
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Posted in math-ph · 2026-08-13 · Momo Hayashi, Kazumitsu Sakai

Hidden Dyson Universality in Inverse-Spectral Geometry

Dyson universality typically manifests itself in local eigenvalue statistics. Here we show that its signature survives a nonlinear inverse-spectral reconstruction and reappears in the matrix geometry of the reconstructed operator. Using a dressing transformation, we map each unfolded spectrum to a deformation $f(x)$ of a fixed...

💬 0 commentsarXiv:2608.13475v1PDF
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Posted in cs.RO · 2026-08-13 · Atiksh Bhardwaj, Edward Weiyi Duan, Prithwish Dan, Wei-Chiu Ma, Preston Culbertson

Decoding Task Progress from VLA Representations

Vision-language-action models (VLAs) are moving rapidly towards deployment as general-purpose manipulation policies, but we currently lack basic tools for understanding what these models represent internally or for monitoring them at runtime. Leveraging ideas from mechanistic interpretability, we probe the residual stream of $π_{0.5}$...

💬 0 commentsarXiv:2608.13474v1PDF
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Posted in astro-ph.EP · 2026-08-13 · Katherine A. Bennett, Carlos Gascón, Jacob Lustig-Yaeger, Guangwei Fu, David K. Sing, Kevin B. Stevenson, Jonathan Brande, Munazza K. Alam, Jeff A. Valenti, Mercedes López-Morales, Sten J. Vermeiren, Megan Weiner Mansfield, Sarah E. Moran, Kristin S. Sotzen, Jegug Ih, Sarah Peacock

No Helium Detected in LHS 1140 b from Four JWST NIRISS/SOSS Transits

In the effort to determine which low-mass exoplanets have atmospheres, LHS 1140 b remains one of the most favorable targets. Its large size (5.6 $\rm M_{\oplus}$ and 1.7 $\rm R_{\oplus}$) and relatively long orbital period (24.7 days) imply an atmosphere may be likely, and notably, recent interior models favor either a...

💬 0 commentsarXiv:2608.13473v1PDF
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Posted in eess.SY · 2026-08-13 · Mohammed Ayman Habib, Rylan Hart, Morteza Fayazi

AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models

Analog circuit design is a time-consuming, iterative process in a nonlinear and high-dimensional design space that relies heavily on expert intuition. Among recent developments, LLMs have introduced a promising approach by bringing natural language reasoning to circuit design tasks. The majority of conventional LLM-based approaches...

💬 0 commentsarXiv:2608.13472v1PDF
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Posted in eess.SP · 2026-08-13 · Daniel C. Araújo, André A. dos Anjos, Hugerles S. Silva, Constantinos Psomas, Robson D. Vieira

On-Off Digital Noise Modulation with Fluid Antenna Systems over $κ$-$μ$ Fading Channels

This letter proposes the integration of on-off digital noise (OODN) modulation with fluid antenna systems (FASs). A unified analytical framework is developed to evaluate the performance of FAS- assisted OODN receivers over additive white Gaussian noise and generalized \k{appa}-μ fading channels. The analysis incorporates fluid antenna...

💬 0 commentsarXiv:2608.13471v1PDF
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Posted in astro-ph.EP · 2026-08-13 · Michael Radica

Strict Limits on Helium Absorption from LHS 1140 b from Four JWST NIRISS Transits

Orbiting in the habitable zone of its host star, the 1.7 $R_\oplus$, 5.6 $M_\oplus$ planet LHS 1140 b is a target of great interest. Recently Cherubim et al. (2026) published a detection of metastable He escaping from the atmosphere of LHS 1140 b, simultaneously providing the first concrete inference of an atmosphere on this planet...

💬 0 commentsarXiv:2608.13470v1PDF
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Posted in hep-ph · 2026-08-13 · Kai Xiao, Fei Sun, Shuang Li, Xun Chen

Critical behavior and critical exponents of rotating QCD matter

We investigate the thermodynamic properties and critical behavior of rotating strongly interacting matter within the two-flavor Nambu--Jona-Lasinio (NJL) model in the mean-field approximation. The phase structure and the critical endpoint (CEP) are determined in the temperature--angular velocity \((T,ω)\) plane. By analyzing the...

💬 0 commentsarXiv:2608.13469v1PDF
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Posted in math.CA · 2026-08-13 · Andriy Bondarenko, Kristian Seip

Fourier-invariant functions with dense zero sets

For every $0\leqβ\leq1/2$, we construct a nonzero real-valued continuous function $f_β$ in $L^1(\mathbb R)\cap L^2(\mathbb R)$ such that $\widehat {f}_β=f_β$ and $f_β(\sqrt{n}/[\log(e+n)]^β)=0$ for all $n\geq 0$. The case $β=0$ settles in the negative a question raised by Radchenko and Viazovska regarding their Fourier interpolation...

💬 0 commentsarXiv:2608.13468v1PDF
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Posted in cs.LG · 2026-08-13 · Yuchen Xin, Zhihua Zhang

Active-Trace Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

We study the Moreau--Yosida unadjusted Langevin algorithm (MYULA) for the nonsmooth composite target \[ π(dx)\propto \exp\{-f(x)-g(x)\}\,dx, \qquad x\in\mathbb R^d, \] where \(f\) is \(m\)-strongly convex with \(L_f\)-Lipschitz gradient and \(g\) is convex and \(G\)-Lipschitz. Let \(g_λ\) be the Moreau envelope of \(g\), \(π_λ\) the...

💬 0 commentsarXiv:2608.13467v1PDF
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Posted in econ.EM · 2026-08-13 · Shengbin Wei

Learning about Treatment Effects in Panels under Unknown Interference

When comparison units may also respond to treatment, panel comparisons reflect both the treatment effect and spillovers. If the interference pattern is unknown, observed outcomes alone do not separate the two. I characterize what can nevertheless be learned from panel outcomes under general restrictions, without requiring an exposure...

💬 0 commentsarXiv:2608.13466v1PDF
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Posted in cs.LG · 2026-08-13 · Christofer Washington Berruz Chungata, Martin Jurecek, Katerina Potika, William B. Andreopoulos, Mark Stamp

Concept Drift Detection and Adaptive Retraining of Malware Classification Models

Concept drift refers to changes over time in the statistical properties of data, as compared to the data that was used to train a learning model. Machine learning models for malware detection or classification are particularly susceptible to performance degradation caused by concept drift, as attackers constantly modify existing...

💬 0 commentsarXiv:2608.13465v1PDF
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Posted in astro-ph.IM · 2026-08-13 · Karl D. Gordon, David R. Law

JWST MIRI Medium Resolution Spectrometer Point Fixed Pattern Corrections: Cleaner and Higher Signal-to-Noise Spectra of Point Sources

The JWST Mid-Infrared Instrument Medium Resolution Spectrometer provides the capability to obtain spectra from 5-28 micron. The JWST data reduction pipeline removes the majority but not all of the instrument artifacts and the signal-to-noise (S/N) of the resulting spectra are limited by fixed pattern noise. Building on previous work,...

💬 0 commentsarXiv:2608.13464v1PDF
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Posted in cs.CV · 2026-08-13 · Daniel Perkins, John Squires, Janou Milligan, Chandra Raskoti, Linda Ungerboeck

MLLM-Routed Heterogeneous Ensembles for Robust Cross-Dataset Image Classification

Modern image classification models excel when trained on single task-specific datasets but often struggle to generalize across domains and difficulty levels. We propose ARMDIL, an Adaptive Router for Multi-Domain Image classification with LLMs. ARMDIL is an ensemble that uses a multimodal large language model (MLLM) agent to...

💬 0 commentsarXiv:2608.13463v1PDF
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Posted in quant-ph · 2026-08-13 · Amit Vikram

Aperiodicity is sufficient for macroscopic thermalization

We identify a general mechanism for the finite-time thermalization of macroscopic observables, such as coarse-grained charge densities, in terms of elementary forms of the quantum dynamics of initial states: (1) aperiodicity, which provides a computable measure of (2) a dynamical partially ergodic exploration of the Hilbert space....

💬 0 commentsarXiv:2608.13462v1PDF
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Posted in cs.CV · 2026-08-12 · Youze Huang, Penghui Ruan, Bojia Zi, Xianbiao Qi, Shihao Zhao, Rong Xiao

ScaleVid: Geometry-Aware Video Object Scaling with Mesh-Free Inference

Geometry-aware video object scaling aims to anisotropically resize the object along object-centric axes while preserving geometric plausibility, temporal coherence, and background consistency. Existing text-guided methods mainly operate in the 2D image plane, while depth-guided approaches provide coarse control and mesh-based methods...

💬 0 commentsarXiv:2608.12232v1PDF
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Posted in cs.CV · 2026-08-10 · Jingxian Xu, Yuhao Huang, Rusi Chen, Yanfeng Zhou, Dong Ni

Rethinking Medical Landmark Localization with Prototype Learning-based Progressive Offset Correction

Accurate landmark localization in medical images is a fundamental step for quantitative clinical measurement and downstream analysis. Existing localization methods have advanced, among which multi-stage refinement is a superior solution. Although this strategy mitigates the anatomical ambiguity inherent in single-stage global...

💬 1 commentsarXiv:2608.09182v2PDF
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Posted in cs.AI · 2026-08-04 · Xiaohe Li, Yang Lu

State Propagation Also Satisfies: A Complex-Valued State-Space Model for Deterministic State Tracking

Transformer-based architectures have dominated sequence modeling, largely due to the expressive power of attention mechanisms. However, for a class of deterministic state tracking tasks---such as parity checking, modular counting, and parenthesis matching---attention may be overkill. In this paper, we show that \textbf{state...

💬 1 commentsarXiv:2608.03425v2PDF
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Posted in astro-ph.HE · 2026-08-04 · Shaswata Chowdhury, M. A. Krishnakumar, Sharika Dhakappa, Vidit Singh, Debabrata Deb, Jyotijwal Debnath, Kaustubh Rai, Pratik Tarafdar, Abhimanyu Susobhanan, Churchil Dwivedi, Bhal Chandra Joshi, Shantanu Desai, Neelam Dhanda Batra, Jaikhomba Singha, Himanshu Grover, Manjari Bagchi, Mayuresh Surnis, Avinash Kumar Paladi, Aman Srivastava, Arul Pandian B., Suruj Jyoti Das, Jibin Jose, Kuldeep Meena, Sushovan Mondal, K Nobleson, Keitaro Takahashi, Hemanga Tahbildar, Kunjal Vara, Zenia Zuraiq

Profile Reconstruction from Temporally Stable Emission Components for Timing PSR J1713+0747

The assumption of long-term pulse-profile stability underpins high-precision pulsar timing and forms the basis of pulsar timing array experiments. However, several millisecond pulsars exhibit temporal profile variability that can introduce systematic biases in pulse time of arrival measurements and compromise timing precision. We...

💬 1 commentsarXiv:2608.04108v1PDF
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Posted in q-fin.CP · 2026-07-28 · Jirong Zhuang

How Likely and How Deep? Sharp Joint Bounds on Risk-Neutral Crash Probability and Conditional Depth from Option Bid-Ask Quotes

Option quotes with bid-ask spreads do not point-identify the risk-neutral probability of a crash below a given threshold, nor the expected depth of the crash once the threshold is breached. Bounds computed separately for the two quantities can mislead, because their endpoints may be attained by different risk-neutral distributions. We...

💬 0 commentsarXiv:2607.25353v3PDF
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Posted in q-bio.NC · 2026-07-27 · Morteza Salehjahromi, Shayan A. Zadegan, Amgad Muneer, Jia Wu

From Observation to Intervention: Memory in Brains and Large Language Models

Brains and large language models (LLMs) are fundamentally different memory systems, but they can be compared through shared functional questions: where memory-related information is represented, how partial cues recover broader associations, how new information is written or updated, and how memory-related states can be perturbed. In...

💬 0 commentsarXiv:2608.12377v1PDF
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Posted in math.PR · 2026-07-26 · Paulo Monteiro, Rabee Tourky

The one-period Gaussian Kyle model has exactly one equilibrium

In the one-period Gaussian Kyle~(1985) model, a single informed trader observes a Gaussian asset value, while independent Gaussian noise demand is submitted to competitive market makers. The market makers observe aggregate order flow and set the price equal to the inverse regression of value on order flow, while the insider chooses...

💬 0 commentsarXiv:2607.23585v3PDF
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Posted in econ.GN · 2026-07-28 · Jeron Tan Kang

Yield Curve Prediction with Machine Learning: Forecasting Approaches and the Role of Macroeconomic Predictors

This paper compares direct-yield and factor-based approaches to U.S. Treasury yield curve forecasting using a common high-dimensional macroeconomic information set. Forecasts are evaluated on monthly zero-coupon yields over the 2015-2025 out-of-sample period. Gains over the random walk are concentrated at short maturities and in slope...

💬 0 commentsarXiv:2608.07536v1PDF
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Posted in math.LO · 2026-07-28 · Atticus Stonestrom

Some results on NIP groups and their Ellis groups

This paper has several parts. We begin by developing a theory of `piecewise (strong) f-genericity' in NIP groups, where we call a definable set piecewise (strong) f-generic if some union of finitely many translates of it is (strong) f-generic. We show that, in an NIP group, the definable sets that are not piecewise (strong) f-generic...

💬 0 commentsarXiv:2607.26265v2PDF