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Collective intent prediction in multi-agent systems focuses on predicting the shared objectives and future behaviours of groups of interacting agents. The problem is particularly challenging because collective intent emerges from complex…
This paper investigates how to extract energy from a non-Kerr rotating spacetime with an anomalous quadrupole moment via the magnetic reconnection mechanism. Unlike many other rotating spacetimes, this spacetime possesses closed timelike…
Sensory advertising evokes human senses through visual cues, enabling audiences to mentally simulate experiences and increasing persuasive impact. Despite the recent increase in using AI in generating and understanding creative and…
The nuclear spin state of deuterium-tritium (D-T) fuel sets both the D-T fusion cross section and the emission direction of the fusion-born alphas and neutrons. We show two ways that spin-polarized fuel (SPF) could enhance alpha channeling,…
Sampling-based methods offer a principled approach to uncertainty quantification in Bayesian neural networks. Their practical use, however, is often challenged by the computational cost of exploring high-dimensional and multimodal posterior…
Modifications to General Relativity can significantly alter the perturbative response of black holes, leaving imprints on quasinormal-mode spectra, waveform amplitudes and phases, and late-time tails. The parametrized beyond-Teukolsky…
Hyperspectral imaging (HSI) is useful for material discrimination, but operational mine screening also depends on how many false alarms must be inspected before targets are found. This paper studies PFM-1 landmine detection in unmanned…
Rydberg atoms have attracted considerable attention in recent years as a novel platform for microwave sensing, owing to their unique physical merits: large transition dipole moments between Rydberg levels and broad frequency coverage. As a…
Training large language models (LLMs) to act in long-horizon games is a promising step toward generalist decision-making, yet reinforcement learning with verifiable rewards (RLVR) relies on sparse final rewards that reveal little about…
We develop a record-based account of internal time in quantum mechanics, where the formation of a stable record is represented as conditioning on actualized information, and along a history the accumulated record algebras are ordered by…
We show that internal loss and survival conditioning can activate anomalous generalized bunching in passive linear optical circuits. We introduce a conditional bunching probability that all photons occupy a target region of accessible…
Macroareas are geographical areas used in typological research for grouping variables of interest. In linguistic typology, languages in a given macroarea are considered to have potential for contact, in contrast to those outside the area,…
The identification of the $21\,\mu\mathrm{m}$ feature in some protoplanetary nebulae remains a longstanding puzzle, whose interpretation requires characterization of the molecular gas environments of associated sources. Here, we present…
In atomic physics, tuning the light frequency across a resonance reverses the trapping force between bright and dark field regions, yet a unified analytical description of this principle applicable to photonic resonators in general has not…
We show that rim surgery on a smooth, oriented, properly embedded surface in $B^4$ does not change the map on Khovanov homology induced by the surface, answering a question raised by Hayden and Sundber. More generally, the same…
Resting heart rate is an established marker of cardiovascular risk, but population-scale measurement has depended on clinical or survey instruments. We ask whether passively sensed consumer-wearable physiology recovers the socioeconomic…
Video editing is fundamentally message-driven: even from the same source footage, the selected shots change depending on the narrative the editor wishes to convey. Benchmarks for a closely related task, video summarization, reduce editorial…
Optimization over the Stiefel manifold plays a significant role in various machine learning tasks. Existing methods either use the retraction operators, requiring costly orthonormalization for large-scale matrices, or employ landing methods…
The high proportion of wind power connected to the grid places higher demands on fine-grained knowledge of regional wind fields. Since the wind information directly obtainable in actual operations is mostly sparse, discrete, and irregularly…
The rapid development of large language model (LLM) agents has enabled their broad adoption across diverse real-world tasks. To standardize interactions between LLM agents and external environments, Model Context Protocol (MCP) tools have…