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Postselection in lattice bosons undergoing continuous measurements

We study in detail the postselection problem in a specific model: bosons hopping on a lattice subjected to continuous local measurements of quadrature observables. We solve the model analytically and ...

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This article presents a significant advancement in understanding postselection in continuous measurements of lattice bosons, proposing a systematic approach to reduce measurement overhead. The analytical and numerical methods described are methodologically rigorous, with clear implications for both theoretical understanding and experimental implementation. The focus on extracting observable quantities from measurement records highlights its applicability in quantum information science, enhancing the study of quantum trajectories and measurements.

Semantics for Linear-time Temporal Logic with Finite Observations

LTL3 is a multi-valued variant of Linear-time Temporal Logic for runtime verification applications. The semantic descriptions of LTL3 in previous work are given only in terms of the relationship to co...

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The article provides a novel perspective on the semantics of LTL3, which is essential for runtime verification processes. The integration of model-based inductive reasoning adds significant methodological rigor, and the mechanization of definitions and proofs enhances reproducibility and applicability. The direct correspondence to conventional LTL and the formalization of evaluation techniques not only solidify the theoretical underpinnings but also have practical implications for software verification, thereby impacting future research directions.

Synchronisability in Mailbox Communication

We revisit the problem of synchronisability for communicating automata, i.e., whether the language of send messages for an asynchronous system is the same as the language of send messages with a synch...

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The article addresses a significant open problem in the field of automata theory and communication systems, contributing to the understanding of synchronisability in mailbox communication specifically. Its exploration of decidability under different conditions demonstrates methodological rigor and adds a novel dimension to existing literature. Furthermore, the use of the Post Correspondence problem to derive results is a recognized and challenging approach, indicating robustness in the theoretical underpinnings of the work.

Functional Array Programming in an Extended Pi-Calculus

We study the data-parallel language BUTF, inspired by the Futhark language for array programming. We give a translation of BUTF into a version of the pi-calculus with broadcasting and labeled names. T...

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This article presents a novel approach to data-parallel languages by providing a complete and sound translation of BUTF into an extended pi-calculus. The inclusion of a cost model for complexity analysis enhances its applicability and rigor. Its contributions could significantly influence both theoretical and practical advancements in programming language design and parallel computing, making it a strong candidate for future research developments.

Block subspace expansions for eigenvalues and eigenvectors approximation

Let $A\in\mathbb C^{n\times n}$ and let $\mathcal X\subset \mathbb C^n$ be an $A$ -invariant subspace with $\dim \mathcal X=d\geq 1$ , corresponding to exterior eigenvalu...

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The article presents a novel theoretical framework for approximating eigenvalues and eigenvectors using block subspace expansions, a method that shows promise in enhancing precision in numerical linear algebra. The methodological rigor, particularly in its analytical and computational components, indicates substantial potential for improved algorithms in eigenvalue problems. Its relevance is heightened by the specificity of applications both to Hermitian matrices and practical computations, suggesting a strong applicability in both theoretical and practical contexts.

He awa whiria: the tidal streams of interstellar objects

Upcoming surveys are likely to discover a new sample of interstellar objects (ISOs) within the Solar System, but questions remain about the origin and distribution of this population within the Galaxy...

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This article presents a novel approach by applying the concept of tidal streams, typically used in galaxy studies, to interstellar objects (ISOs). The creation of a simulation and a density distribution model is methodologically rigorous and provides new insights into the origins and populations of ISOs. It has significant implications for ongoing and future astronomical surveys, potentially influencing how ISOs are studied and understood.

First-Principles Insights into the Site Occupancy and Stability of Ta-Fe-Al C14 Laves Phases

This study investigates the site occupancy preferences of Al in Ta(Fe $_{1-x}$ Al $_x$ ) $_2$ Laves phases using first-principles calculations, with Al concentrations ranging from 0...

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The article presents novel insights into the site occupancy and stability of Ta-Fe-Al Laves phases through first-principles calculations, making it relevant for advancing materials science, particularly in the context of intermetallic compounds. The exploration of magnetic configurations and the construction of a phase diagram enhances its significance. Its methodological rigor and focus on structure-property relationships provide substantial groundwork for future research.

SRSA: A Cost-Efficient Strategy-Router Search Agent for Real-world Human-Machine Interactions

Recently, as Large Language Models (LLMs) have shown impressive emerging capabilities and gained widespread popularity, research on LLM-based search agents has proliferated. In real-world situations, ...

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This article presents a novel approach to improving the efficiency and effectiveness of human-machine interactions using a Strategy-Router Search Agent (SRSA). The introduction of the Contextual Query Enhancement Dataset (CQED) adds significant value by providing a new resource for evaluating the routing strategies in LLMs. The focus on optimizing computational cost while enhancing response quality demonstrates both practical applicability and methodological rigor. The combination of addressing existing gaps in LLM-based search agents and proposing a systematic solution positions this work as a meaningful contribution to the field.

Capacity-Achieving Entanglement Purification Protocol for Pauli Dephasing Channel

Quantum communication facilitates the secure transmission of information and the distribution of entanglement, but the rates at which these tasks can be achieved are fundamentally constrained by the c...

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This article presents a novel and efficient entanglement purification protocol that addresses a significant limitation in quantum communication related to Pauli dephasing channels. Its methodological rigor in utilizing CNOT gates and Hadamard basis measurements, along with achieving channel capacities, exemplifies a high level of innovation. The practical applicability of this protocol in enhancing quantum repeaters and mitigating decoherence in quantum computing further emphasizes its relevance. The iterative nature of the protocol also suggests potential improvements in various quantum technologies, making it a substantial contribution to the field.

Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective

Retrieval-Augmented Generation (RAG) systems have shown promise in enhancing the performance of Large Language Models (LLMs). However, these systems face challenges in effectively integrating external...

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This article presents a novel and systematic exploration of knowledge integration within Retrieval-Augmented Generation systems, which is crucial for improving Large Language Models' (LLMs) reliability. The focus on representation behaviors and the development of classifiers signifies both methodological rigor and practical applicability, especially in addressing prevalent issues in the field.

Assessment of LLM Responses to End-user Security Questions

Answering end user security questions is challenging. While large language models (LLMs) like GPT, LLAMA, and Gemini are far from error-free, they have shown promise in answering a variety of question...

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This article addresses an important and timely issue regarding the security implications of using large language models (LLMs) in handling sensitive end-user security questions. The systematic evaluation of LLM performance across multiple models and a large question set provides robust data that could inform future improvements in AI systems and user interactions. It strikes a balance between addressing current capabilities and limitations, suggesting both model improvements and practical user strategies which enhances its applicability and practicality.

Gradient-based optimization for variational empirical Bayes multiple regression

Variational empirical Bayes (VEB) methods provide a practically attractive approach to fitting large, sparse, multiple regression models. These methods usually use coordinate ascent to optimize the va...

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The article presents a novel optimization method (GradVI) for variational empirical Bayes multiple regression, which improves upon existing techniques in terms of speed and flexibility. The rigorous comparative analysis with coordinate ascent variational inference (CAVI) demonstrates its practical applications and efficiency in high-dimensional settings. Its open-source implementation enhances accessibility and encourages further research utilization. However, while promising, the article could benefit from additional empirical validation across a broader range of datasets.

Variable Extraction for Model Recovery in Scientific Literature

The global output of academic publications exceeds 5 million articles per year, making it difficult for humans to keep up with even a tiny fraction of scientific output. We need methods to navigate an...

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The study addresses a critical challenge in scientific research: navigating and interpreting vast amounts of literature. Its innovative use of LLMs for variable extraction not only advances methodological frameworks but also supports the automation of model recovery, which is crucial for reproducibility and simulation studies in epidemiology and beyond. The introduction of a benchmark dataset enhances the paper's impact, providing the research community with essential resources for advancing the field.

Maximum Solar Energy Tracking Leverage High-DoF Robotics System with Deep Reinforcement Learning

Solar trajectory monitoring is a pivotal challenge in solar energy systems, underpinning applications such as autonomous energy harvesting and environmental sensing. A prevalent failure mode in sustai...

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This article presents a novel approach to solar energy tracking using deep reinforcement learning combined with an objectness regularization framework, which can significantly enhance the robustness of solar tracking systems. The integration of high-DoF robots adds a dimension of flexibility, addressing a critical failure mode in existing systems. The innovation in methodology and its potential logistic applications for solar energy systems make this research relevant and impactful for the future development of autonomous energy harvesting technologies.

Energy Efficient Automated Driving as a GNEP: Vehicle-in-the-loop Experiments

In this paper, a multi-agent motion planning problem is studied aiming to minimize energy consumption of connected automated vehicles (CAVs) in lane change scenarios. We model this interactive motion ...

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This article tackles an important problem in the realm of connected automated vehicles by applying a novel multi-agent approach that combines motion planning with generalized Nash equilibrium concepts, presenting both theoretical and practical contributions. The use of vehicle-in-the-loop experiments adds significant methodological rigor and provides empirical evidence of the benefits of the proposed approach, which enhances its applicability. The emphasis on energy efficiency is particularly timely given current sustainability trends in transportation.

A canonical Ramsey theorem for even cycles in random graphs

The celebrated canonical Ramsey theorem of Erdős and Rado implies that for $2\leq k\in \mathbb{N}$ , any colouring of the edges of $K_n$ with $n$ sufficiently large gives a copy...

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The paper addresses a significant problem in combinatorial graph theory by establishing a threshold for the canonical Ramsey property concerning even cycles in random graphs. The novelty lies in applying probabilistic methods to determine a threshold in the context of edge colorings of random graphs, which broadens our understanding of Ramsey theory. Its rigorous approach and clear implications add considerable value to both theoretical work and potential applications.

Privacy-Preserving Video Anomaly Detection: A Survey

Video Anomaly Detection (VAD) aims to automatically analyze spatiotemporal patterns in surveillance videos collected from open spaces to detect anomalous events that may cause harm without physical co...

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The article addresses a significant and timely topic at the intersection of AI, surveillance, and privacy, highlighting critical gaps in the current literature. Its systematic review and proposed taxonomy strengthen the understanding of P2VAD, aiding researchers in navigating this emerging field. The inclusion of challenges and future opportunities enhances its applicability, making it a valuable resource for academics and practitioners.

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understand...

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This article addresses a significant issue related to the upcoming LSST, specifically focusing on blending effects in galaxy catalogs, which is crucial for accurate cosmic analyses. The methodological rigor demonstrated through the use of simulations enhances its credibility. The implications on galaxy clustering measures suggest a valuable contribution to cosmology, particularly in improving large-scale structure measurements. However, further general applicability beyond simulations could limit its broader impact.

Constructing Trustworthy Smart Contracts

Smart contracts form the core of Web3 applications. Contracts mediate the transfer of cryptocurrency, making them irresistible targets for hackers. We introduce ASP, a system aimed at easing the const...

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The article presents a highly relevant and novel contribution to the field of smart contracts by introducing a comprehensive system (ASP) that significantly enhances security. The integration of a programming language, defensive compiler, and proof checker is a robust approach addressing critical vulnerabilities. Its focus on functional correctness and common exploitation scenarios is timely and crucial given recent exploits in the space, making it applicable to both current and future developments in blockchain technology.

Brill-Noether loci of pencils with prescribed ramification on moduli of curves and on Severi varieties on $K3$ surfaces

Under the assumption that the adjusted Brill-Noether number $\widetildeρ$ is at least $-g$ , we prove that the Brill-Noether loci in $\mathcal{M}_{g,n}$ of pointed curves carryi...

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The article presents significant advancements in the understanding of Brill-Noether loci in moduli spaces and their implications for Hurwitz schemes and Severi varieties. The combination of theoretical depth and applicability to classical problems enhances its relevance. Moreover, the results build on existing literature while expanding into new dimensions, particularly in ramification, which is novel and impactful.