arXiv preprints from January 1, 2026 through September 9, 2026 — 08:56:37 EST
The Plurality rule is vulnerable to vote splitting between similar alternatives. Defying conventional wisdom, we characterize the Plurality rule through a specific type of clone independence condition. We further introduce the notion of a one-parameter family of $p$-Clone Resistance ($p$-CR), and examine the property within the class...
We study coalitional manipulation of interval-valued median correspondences on the single-peaked domain. Under the pessimistic extension, group strategy-proofness rules out any genuinely set-valued choice. Under the optimistic and best--worst extensions, by contrast, group strategy-proofness characterizes target set correspondences....
The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with this ambition remains uncertain. We apply deep learning to high-resolution socioeconomic and sectoral data across EU27 member states till 2023 to project sectoral CO$_2$ trajectories under...
Intra-household joint home-based tours - trips in which household members depart together, engage in shared activities, and return together - represent a significant share of daily travel, yet are systematically ignored in transport simulations. Conflating joint and solo tours within a single mode choice framework introduces bias in...
Most LLM benchmarks rank models on their ability to automate work tasks. In practice, however, models are often used to assist other (human or LLM) agents. The question that drives model selection is therefore not only which model produces the best output, but which model most improves the work of another (weaker) agent. We introduce...
This paper develops asymptotic theory and feasible inference for unbounded-kernel order-k U-statistics under clustered sampling and weakly dependent time-series sampling. The analysis first builds the complete order-2 pipeline, moving from clustered data to exact m-dependence and then to near-epoch dependence. The same logic is...
This paper presents a framework for stable matching markets that accommodates the peer-dependent preferences employed in empirical work. We show the existence of a stable matching in a continuum economy and of an approximately stable matching in a large finite sampled economy under assumptions satisfied by standard empirical...
We study difference-in-differences (DiD) designs in which a binary treatment changes an endogenous time-varying (continuous, discrete, or mixed) mediator that in turn affects an outcome. Under our model assumptions, we show that the usual DiD estimand mixes the average direct effect on the treated, the average indirect effect, and a...
We examine how agents learn when information from original sources only reaches them after noisy relay. A receiver learns if and only if they have access to sufficiently many chains of noisy relay and they perfectly understand the noise process. However, even slight uncertainty over message mutation rates makes learning from long...
We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language model a ``type vector'' and then prompt it to choose actions across settings in which we observe human choices. For instance, the type vector (2,4) becomes ``You are a player characterized...
We classify maximally enhanced, rank-preserving non-supersymmetric heterotic strings in eight dimensions by studying orbifolds of supersymmetric heterotic strings on $T^2$. We first review the construction in nine dimensions, where it reproduces the $95$ maximally semisimple enhancement points obtained from previous extended-Dynkin...
Seasonal precipitation anomalies are largely regulated by atmospheric circulation, which dynamical models predict with greater reliability than precipitation itself. Here, we employ a deep learning model that translates dynamical circulation predictions into precipitation estimates. Predictions initialized from March to May...
One of the most basic conjectures in quantum complexity theory states that every $t$-query quantum algorithm can be simulated on most inputs by a $\mathrm{poly}(t)$-query classical algorithm. If true, this would provide broad justification for the need for structure in quantum speedups. We settle this conjecture for parallel quantum...
Silicon Photomultipliers (SiPMs) based on NUV-MT technology offer improved photo-detection efficiency and reduced correlated noise compared to earlier designs, making them increasingly attractive for particle and astroparticle physics applications. We present a systematic characterisation of commercially available Broadcom AFBR-S4N...
The formation and evolution of galaxies are interconnected with that of their host halos. Given this closely related evolutionary history, it should follow that galaxy properties are correlated with their host halo mass. Previous works have shown that star formation rates of galaxies in cluster halos differ systematically from those...
In this work, we present a unified entropic description of the quantum bounce that is present in Loop Quantum Cosmology (LQG) and dark energy that drives the late time acceleration of the Universe. By considering a minimal area $A_0$ for the Universe and a modified entropy area constructed as the sum of $S_Q$, $S_{BH}$ and $S_{DE}$,...
Horizontal earthquake ground motions exhibit substantial changes in amplitude with changes in orientation. While the effects of style of faulting on central tendency measures of ground motion intensity such as RotD50 are well established in ground motion models, less attention has been given to how faulting mechanism influences the...
In this work, we study the limitations and advantages of using entanglement battery and entanglement catalyst in local state discrimination problems. We consider both cases of such tools, i.e., exact and approximate cases. We show that to distinguish any set of orthogonal pure bipartite entangled states perfectly under local...
The surface $r=\infty$ of the Kerr--Bertotti--Robinson (KBR) spacetime is not the collection of the endpoints of infinitely extended light rays, and the Coulomb type component of gravitational field strength represented by $Ψ_2$ remains nonvanishing there, indicating that this surface is not a real boundary. We construct a natural...
These notes develop the diagnostics of chaos from their classical definitions through to holography, in six lectures given at the ST4 Workshop, Chennai Mathematical Institute, in 2026. No prior exposure to chaos theory is assumed. Lectures 1 and 2 define classical chaos geometrically and build the instruments that measure it, every...
Adding links generally improves classical transport by increasing the number of available paths. We show that coherent quantum transport can display the opposite behavior. Using continuous-time quantum walks on a percolated hierarchical small-world network, we identify a coherent overconnectivity penalty: root-to-boundary transport is...
Complex concentrated alloys (CCAs), including high- and medium-entropy alloys, deform in chemically heterogeneous energy landscapes where dislocation glide, solute aging, twinning, phase transformation and microstructural barriers may all contribute. This review discusses avalanche-like and serrated plasticity in CCAs across scales....
The search for atmospheres on temperate terrestrial planets is important for understanding how these objects form and evolve, and their potential habitability. Recent transit observations of LHS 1140 b, a temperate ($T_{\rm eq}=226$ K) planet straddling the radius valley ($R_{\rm p}\approx1.7 R_\oplus$), with the WINERED...
Quantitative microstructural characterization of Li-ion battery electrode materials using electron backscatter diffraction (EBSD) has been proven as a critical method for optimizing cell performance. However, the inherently slow nature of EBSD can hinder the throughput of analyses needed for statistical representation of a material...
Many problems in disordered materials require sampling beyond fixed composition and volume, where coupled changes in atomic identities and structure create a prohibitively expensive discrete-continuous sampling problem. Here we introduce JANUS, a multimodal neural sampler that couples continuous and masked discrete diffusion through...