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HARLI CQUINN: Higher Adjusted Randomness with Linear In Complexity QUantum INspired Networks for K-Means
Jiten Oswal, Saumya Biswas
https://arxiv.org/abs/2509.19395 https://

HARLI CQUINN: Higher Adjusted Randomness with Linear In Complexity QUantum INspired Networks for K-Means
We contrast a minimalistic implementation of quantum k-means algorithm to classical k-means algorithm. With classical simulation results, we demonstrate a quantum performance, on and above par, with the classical k-means algorithm. We present benchmarks of its accuracy for test cases of both well-known and experimental datasets. Despite extensive research into quantum k-means algorithms, our approach reveals previously unexplored methodological improvements. The encoding step can be minimalisti…

Sublinear Metric Steiner Forest via Maximal Independent Set
Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski, Ali Vakilian
https://arxiv.org/abs/2510.11627 https://

Sublinear Metric Steiner Forest via Maximal Independent Set
In this work we consider the Metric Steiner Forest problem in the sublinear time model. Given a set $V$ of $n$ points in a metric space where distances are provided by means of query access to an $n\times n$ distance matrix, along with a set of $k$ terminal pairs $(s_1,t_1), \dots, (s_k,t_k)\in V\times V$, the goal is to find a minimum-weight subset of edges that connects each terminal pair. Although sublinear time algorithms have been studied for estimating the weight of a minimum spanning tre…

Do Large Language Models Respect Contracts? Evaluating and Enforcing Contract-Adherence in Code Generation
Soohan Lim, Joonghyuk Hahn, Hyunwoo Park, Sang-Ki Ko, Yo-Sub Han
https://arxiv.org/abs/2510.12047

Do Large Language Models Respect Contracts? Evaluating and Enforcing Contract-Adherence in Code Generation
Prevailing code generation benchmarks, such as HumanEval+ and MBPP+, primarily evaluate large language models (LLMs) with pass@k on functional correctness using well-formed inputs. However, they ignore a crucial aspect of real-world software: adherence to contracts-the preconditions and validity constraints that dictate how ill-formed inputs must be rejected. This critical oversight means that existing benchmarks fail to measure, and models consequently fail to generate, truly robust and reliab…

Nematic Fluctuations and Electronic Correlations in Heavily Hole-Doped Ba$_{1-x}$K$_x$Fe$_2$As$_2$ Probed by Elastoresistance
Franz Eckelt, Steffen Sykora, Xiaochen Hong, Vilmos Koscis, Vadim Grinenko, Bernd B\"uchner, Kunihiro Kihou, Chu-Ho Lee, Christian Hess
https://arxiv.org/abs/2510.09151…

Nematic Fluctuations and Electronic Correlations in Heavily Hole-Doped Ba$_{1-x}$K$_x$Fe$_2$As$_2$ Probed by Elastoresistance
This work investigates nematic fluctuations and electronic correlations in the hole-doped iron pnictide superconductor Ba$_{1-x}$K$_x$Fe$_2$As$_2$ by means of longitudinal and transverse elastoresistance measurements over a wide doping range ($0.63 < x < 0.98$). For this purpose, the orbital character of the electronic response was revealed by decomposition of the elastoresistance into the $A_{1g}$ and $B_{2g}$ symmetry channels. It was shown that at lower doping levels nematic fluctuations in …

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Kernel K-means clustering of distributional data
Amparo Ba\'illo, Jose R. Berrendero, Mart\'in S\'anchez-Signorini
https://arxiv.org/abs/2509.18037 https://

Kernel K-means clustering of distributional data
We consider the problem of clustering a sample of probability distributions from a random distribution on $\mathbb R^p$. Our proposed partitioning method makes use of a symmetric, positive-definite kernel $k$ and its associated reproducing kernel Hilbert space (RKHS) $\mathcal H$. By mapping each distribution to its corresponding kernel mean embedding in $\mathcal H$, we obtain a sample in this RKHS where we carry out the $K$-means clustering procedure, which provides an unsupervised classifica…

Testing the equality of estimable parameters across many populations
Marcos Romero-Madro\~nal, Mar\'ia de los Remedios Sillero-Denamiel, Mar\'ia Dolores Jim\'enez-Gamero
https://arxiv.org/abs/2510.06763

Testing the equality of estimable parameters across many populations
The comparison of a parameter in $k$ populations is a classical problem in statistics. Testing for the equality of means or variances are typical examples. Most procedures designed to deal with this problem assume that $k$ is fixed and that samples with increasing sample sizes are available from each population. This paper introduces and studies a test for the comparison of an estimable parameter across $k$ populations, when $k$ is large and the sample sizes from each population are small when …

Characterizing failure morphologies in fiber-reinforced composites via k-means clustering based multiscale framework
Harpreet Singh
https://arxiv.org/abs/2509.20011 https://

Characterizing failure morphologies in fiber-reinforced composites via k-means clustering based multiscale framework
A novel homogenization methodology is proposed for analyzing the failure of fiber-reinforced composite materials, utilizing elastic and eigen influence tensors within a damage informed transformation field analysis (D-TFA) framework. This approach includes a technique for calculating macroscopic damage under uniform stress and strain conditions, offering more realistic simulations. Computational efficiency is enhanced through a reduced-order modeling strategy, while elastic and eigen strain dis…

Clustering in Varying Metrics
Deeparnab Chakrabarty, Jonathan Conroy, Ankita Sarkar
https://arxiv.org/abs/2510.07860 https://arxiv.org/pdf/2510.07860

Clustering in Varying Metrics
We introduce the aggregated clustering problem, where one is given $T$ instances of a center-based clustering task over the same $n$ points, but under different metrics. The goal is to open $k$ centers to minimize an aggregate of the clustering costs -- e.g., the average or maximum -- where the cost is measured via $k$-center/median/means objectives. More generally, we minimize a norm $Ψ$ over the $T$ cost values. We show that for $T \geq 3$, the problem is inapproximable to any finite facto…

Analysis of collision shift assessments in ion-based clocks
M. D. Barrett, K. J. Arnold
https://arxiv.org/abs/2512.05474 https://arxiv.org/pdf/2512.05474 https://arxiv.org/html/2512.05474
arXiv:2512.05474v1 Announce Type: new
Abstract: We consider back-ground gas collision shifts in ion-based clocks. We give both a classical and quantum description of a collision between an ion and a polarizable particle with a simple hard-sphere repulsion. Both descriptions give consistent results, which shows that a collision shift bound is determined by the classical Langevin collision rate reduced by a readily calculated factor describing the decoupling of the clock laser from the ion due to the recoil motion. We also show that the result holds when using a more general Lennard-Jones potential to describe the interaction between the ion and its collision partner. This leads to a simple bound for the collision shift applicable to any single ion clock without resorting to large-scale Monte-Carlo simulations or determination of molecular potential energy curves describing the collision. It also provides a relatively straightforward means to measure the relevant collision rate.
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Generation of C-band entangled photon pairs by biexciton-exciton cascade from symmetric InAs/InP quantum dots
Anna Musia{\l}, Maja Wasiluk, Katarzyna Roszak, Micha{\l} Gawe{\l}czyk, Wojciech Rudno-Rudzi\'nski, Pawe{\l} Wyborski, Johann P. Reithmaier, Mohamed Benyoucef, Grzegorz S\k{e}k
https://arxiv.org/abs/2509.24500

Generation of C-band entangled photon pairs by biexciton-exciton cascade from symmetric InAs/InP quantum dots
Hereby, we study the generation of pairs of polarization-entangled photons at telecom C-band by biexciton-exciton cascade from non-resonantly excited epitaxial InAs/InP quantum dots (QDs). It is realized without external tuning of the fine structure splitting (FSS), which does not exceed 10 $μ$eV in as-grown nanostructures, due to their high in-plane symmetry. Excitonic complexes are identified by means of excitation power-dependent and polarization-resolved magneto)microphotoluminescence. The…

A LOFAR search for coherent radio emission accompanying prompt engine activity in gamma-ray bursts
A. Hennessy, R. L. C. Starling, A. Rowlinson, I. de Ruiter, A. J. van der Horst, G. E. Anderson, N. R. Tanvir, S. ter Veen, K. Wiersema, R. A. M. J. Wijers
https://arxiv.org/abs/2509.21142

A LOFAR search for coherent radio emission accompanying prompt engine activity in gamma-ray bursts
Relativistic jets generated in gamma-ray bursts (GRBs) produce luminous transient events, yet the fundamentals of jet composition and radiation mechanisms remain unclear. One means of identifying a magnetically-dominated outflow would be detection of prompt, coherent radio emission at low frequencies, and we are able to search for this using the LOw Frequency ARray (LOFAR) coupled with modelling of high energy pulses detected by the Neil Gehrels Swift Observatory (Swift). We present the rapid r…

Cu2XSiS4 (X = Ge, Sn, and Pb) materials for solar-cell applications: A DFT SCAPS-1D simulation
H. Laltlanmawii, L. Celestine, R. Zosiamliana, B. Chettri, S. Bhattarai, K. C. Bhamu, D. P. Rai
https://arxiv.org/abs/2509.20845

Cu2XSiS4 (X = Ge, Sn, and Pb) materials for solar-cell applications: A DFT+SCAPS-1D simulation
By means of the first-principles density functional theory (DFT), I2-II-IV-VI4 type Cu-based quaternary chalcogenides Cu 2 XSiS 4 (X = Ge, Sn, and Pb) have been thoroughly investigated. We report the study of Ge and Sn substitution in the divalent cation site for their potential applications in photovoltaics for the first time. The structural, electronic, optical, and mechanical properties have been calculated. The structural and thermal stability is verified by calculating the elastic constant…

Hybrid Quantum-Classical Optimisation of Traveling Salesperson Problem
Christos Lytrosyngounis, Ioannis Lytrosyngounis
https://arxiv.org/abs/2509.26229 https://

Hybrid Quantum-Classical Optimisation of Traveling Salesperson Problem
The Traveling Salesperson Problem (TSP), a quintessential NP-hard combinatorial optimisation challenge, is vital for logistics and network design but limited by exponential complexity in large instances. We propose a hybrid quantum-classical framework integrating variational quantum eigensolver (VQE) optimisation with classical machine learning, using K-means clustering for problem decomposition and a RandomForestRegressor for path refinement. Evaluated on 80 European cities (from 4 to 80 citie…

Sublinear Time Quantum Sensitivity Sampling
Zhao Song, David P. Woodruff, Lichen Zhang
https://arxiv.org/abs/2509.16801 https://arxiv.org/pdf/2509.16801

Sublinear Time Quantum Sensitivity Sampling
We present a unified framework for quantum sensitivity sampling, extending the advantages of quantum computing to a broad class of classical approximation problems. Our unified framework provides a streamlined approach for constructing coresets and offers significant runtime improvements in applications such as clustering, regression, and low-rank approximation. Our contributions include: * $k$-median and $k$-means clustering: For $n$ points in $d$-dimensional Euclidean space, we give an algo…

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