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The integration of membranes into optical resonators plays a key role in a variety of applications, including optomechanics. Membranes hosting single photon emitters, ideally with access to spin states, open new avenues in optomechanics,…
Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on difficult problems: when a model cannot generate any correct solutions, it receives \textit{zero}…
Detecting staypoints from raw trajectory data is fundamental to numerous spatial computing applications. This process transforms raw numeric sequences of geolocations into semantically meaningful locations, such as homes, workplaces, or…
This paper introduces a class of observation-driven models whose systematic component includes a tempered fractional differencing term. This specification generalizes long-range dependent models based on the fractional differencing…
Flexible electronics (FE) based on indium gallium zinc oxide thin-film transistors (IGZO-TFTs) are emerging for ultra-low-power wearable applications. However, lack of packaging, limited pins, and high device variability make conventional…
A Cayley graph $\operatorname{Cay}(\Gamma,S)$ over a finite group $\Gamma$ is said to be normal if its connection set $S$ is a union of some conjugacy classes of $\Gamma$. This paper investigates perfect state transfer in Grover walks on…
Misfit layered compounds (MLCs) offer a unique bulk platform for realizing exotic quantum states typically associated with two-dimensional transition-metal dichalcogenides (TMDs), most notably Ising-protected superconductivity. Yet a…
Electrochemical impedance spectroscopy (EIS) is a powerful tool for probing kinetic and transport processes in electrochemical systems, but its practical use is often limited by the long acquisition time and noise sensitivity of…
Autonomous flight in cluttered environments requires a robot to build a geometric map of its surroundings and plan safe, dynamically feasible trajectories, all onboard and in real time. Conventional approaches treat mapping and planning as…
Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific manifolds, rely on Euclidean approximations, or require costly and numerically fragile geometric…
Discoveries regarding the dusty rings of Jupiter and the Galilean satellites' dust environment have been continuously refined by orbiters and flybys. Leveraging Juno Waves instrument electric field data, we developed a hybrid recognition…
Momentum-dependent nonrelativistic spin splitting provides a symmetry fingerprint of collinear magnets and can govern unconventional electronic, magnonic, and transport phenomena. Whereas even-parity $s$-, $d$-, $g$-, and $i$-wave…
Controlling dynamical systems in real-time across multiple scenarios is critical to enabling adaptive control strategies, ensuring stability and efficiency. However, to tailor control actions in response to varying scenarios, traditional…
GraphRAG improves long-document question answering by introducing structured representations beyond conventional retrieval. However, automatically constructed graphs are inherently incomplete projections of source documents, and treating…
As LLM adoption becomes more widespread, there is a growing interest in detecting LLM-generated content, for example through LLM detection tools and through heuristics based on language patterns. Detectors operate as an intervention that…
Scattered light is a relevant noise source in current ground-based gravitational-wave detectors and a critical design concern for next-generation observatories. Beamtube scattered light estimates usually combine optical propagation…
Gravitational wave astronomy provides an exemplary avenue to study exotic compact stars with utmost precision. Recent analyses of GW170817 have reported possible post-merger gravitational wave echoes with a significance of $4.2\sigma$ and a…
This paper is a practitioner guide to graph-based workflow pathways for long-running, stateful, multi-step generative AI systems in business processes. Rather than treating LangGraph, a low-level orchestration framework for stateful agents,…
Tailings dam-breach analyses are essential for flood-hazard assessment, emergency planning and risk estimation, but their results are strongly affected by uncertainties in breach development, released volume and tailings rheology. This…
Characterizing phase transitions between correlated electronic phases, extracting their critical exponents, and identifying their universality class are of central interest in many-body physics. Here, we propose and demonstrate that photon…