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Thesis Tide

Thesis Tide ranks papers based on their relevance to the fields, with the goal of making it easier to find the most relevant papers. It uses AI to analyze the content of papers and rank them!

Synchronization by noise for traveling pulses

We consider synchronization by noise for stochastic partial differential equations which support traveling pulse solutions, such as the FitzHugh-Nagumo equation. We show that any two pulse-like soluti...

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The article presents a novel approach to understanding synchronization in stochastic systems, particularly in the context of traveling pulse solutions. The use of phase reduction to analyze synchronization dynamics is a significant methodological innovation that enhances its contribution to the field. Furthermore, the specific focus on how noise influences pulse synchronization is both timely and relevant, given the current interest in complex systems and their dynamics.

ARCADE: An interactive playground for real-time immersed topology optimization

Topology optimization (TO) has found applications across a wide range of disciplines but remains underutilized in practice. Key barriers to broader adoption include the absence of versatile commercial...

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The article presents a novel approach to topology optimization through immersive technologies, such as AR and VR, addressing significant barriers to the field's adoption. Its methodological rigor is evident in the development of ARCADE, which integrates real-time feedback and interaction into the design process. This indicates strong potential for practical application and adoption in various disciplines, promoting immediate usability and collaborative design. The originality of the immersive topology optimization idea further enhances its relevance for future research.

Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving

Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities; however, these models remain highly susceptible to adversarial attacks. While exi...

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This article presents a novel and practical approach to an underexplored area of adversarial attacks on vision-language models specifically in the context of autonomous driving. It not only identifies key challenges but also proposes an innovative solution (Cascading Adversarial Disruption, CAD) that has demonstrated state-of-the-art effectiveness in real-world scenarios. The release of a comprehensive dataset further enhances its applicability and potential impact on future research.

Charge calibration of MALTA2, a radiation hard depleted monolithic active pixel sensor

MALTA2 is a depleted monolithic active pixel sensor (DMAPS) designed for tracking at high rates and typically low detection threshold of $\sim150\,\mathrm{e^-}$ . A precise knowledge of the thr...

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The article presents a novel calibration method for MALTA2 sensors, addressing a key aspect of sensor performance—charge threshold determination. This is critical for applications that rely on accurate tracking and charge measurement in high-rate environments. The methodology outlined is rigorous and offers potential impacts on the performance of these sensors in real-world applications. Its relevance is heightened by the specificity of the calibration procedure, which adds value for researchers and engineers working with these sensor technologies.

TROPIC -- Trustworthiness Rating of Online Publishers through online Interactions Calculation

Existing methods for assessing the trustworthiness of news publishers face high costs and scalability issues. The tool presented in this paper supports the efforts of specialized organizations by prov...

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The article presents a novel methodological approach to evaluating the trustworthiness of online news publishers, which is a critical issue in today’s digital information landscape. Its emphasis on using real user interactions adds a practical dimension that is often missing in theoretical frameworks. Additionally, the focus on scalability and cost-efficiency enhances its applicability across various organizations, potentially influencing future research and development in this domain.

Transfer matrix approach to quantum systems subject to certain Lindblad evolution

Solving for time evolution of a many particle system whose dynamics is governed by Lindblad equation is hard. We extend the use of transfer matrix approach to a class of Linblad equations that admit a...

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The article presents a novel application of the transfer matrix approach to solve for the dynamics of many-body quantum systems under Lindblad evolution, a crucial area in quantum statistical mechanics and quantum computing. Its methodological advancement, notably the solution's ability to yield analytical results in the thermodynamic limit, enhances the computational efficiency for studying large systems. These features unlock new possibilities for exploring quantum systems and their dynamics, marking it as a relevant contribution to the field.

Overcoming temperature limitations in laser cooling using dressed states and diamond vacancies

The established approach to laser cooling of solids relies on anti-Stokes fluorescence, for example from rare earth impurities in glass. Although successful, there is a minimum temperature to which su...

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The article introduces a novel approach to laser cooling that overcomes significant limitations of current technologies. The methodology involving dressed states is innovative and has the potential to advance both theoretical understanding and practical applications in laser cooling, making it particularly impactful. The discussion of tuning spectral gaps to optimize heat absorption adds significant depth and applicability. However, the paper would benefit from more extensive experimental validation to affirm the proposed concepts.

GoDe: Gaussians on Demand for Progressive Level of Detail and Scalable Compression

3D Gaussian Splatting enhances real-time performance in novel view synthesis by representing scenes with mixtures of Gaussians and utilizing differentiable rasterization. However, it typically require...

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The proposed method introduces a novel, model-agnostic approach to Gaussian Splatting that significantly enhances scalability and adaptability while maintaining low distortion. Its ability to facilitate real-time performance in novel view synthesis makes it highly relevant to current challenges in computer graphics and 3D rendering. The use of hierarchical layers for progressive Level of Detail is particularly innovative and addresses important limitations of existing methods. The validation on typical datasets indicates methodological rigor and potential applicability in various real-world scenarios.

Duality Theorems and Vector Measures in Optimal Transportation Theory

The optimal transportation problem, first suggested by Gaspard Monge in the 18th century and later revived in the 1940s by Leonid Kantorovich, deals with the question of transporting a certain measure...

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This article presents a significant advancement in the field of optimal transportation theory by generalizing the duality theorem and its applicability to vector measures. The methodological rigor demonstrated in the generalization of the problem and the implications for related fields such as game theory and linear programming enhance its novelty. Moreover, the abstract formulation has broader applicability across various disciplines, making it especially relevant for future research.

How to seed ergodic dynamics of interacting bosons under conditions of many-body quantum chaos

We demonstrate how the initial state of ultracold atoms in an optical lattice controls the emergence of ergodic dynamics as the underlying spectral structure is tuned into the quantum chaotic regime. ...

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This article presents a novel investigation into the connection between initial states of ultracold atoms and ergodic dynamics, highlighting practical thrusts in quantum chaotic behavior. The rigorous identification of chaos thresholds and their implications on dynamical observables marks it as a significant step toward further understanding many-body quantum systems. Its methodology appears robust, targeting an emerging area in quantum physics that could influence future research directions.

Instantaneous Core Loss -- Cycle-by-cycle Modeling of Power Magnetics in PWM DC-AC Converters

Nowadays, PWM excitation is one of the most common waveforms seen by magnetic components in power electronic converters. Core loss modeling approaches such as the improved Generalized Steinmetz Equati...

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The article introduces a novel concept of instantaneous core loss in power magnetics, which addresses a critical gap in the modeling of core losses in PWM DC-AC converters. Its methodological rigor, empirical validation, and potential to influence design practices highlight its relevance and impact within its field. The cycle-by-cycle modeling approach presents significant advancements for both academia and industry, particularly in optimizing power electronic converters.

Compiler Support for Speculation in Decoupled Access/Execute Architectures

Irregular codes are bottlenecked by memory and communication latency. Decoupled access/execute (DAE) is a common technique to tackle this problem. It relies on the compiler to separate memory address ...

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The article addresses a significant limitation in decoupled access/execute architectures by proposing a novel compiler technique that enhances speculation, thereby improving performance in memory-intensive applications. This work is highly relevant due to its potential applications to various architectures and its promise to reduce latency issues which are prevalent in contemporary computing. The method's robustness is indicated by its ability to maintain sequential consistency and its applicability to both CPU/GPU environments and specialized accelerators, which broadens its impact.

Explainable AI-aided Feature Selection and Model Reduction for DRL-based V2X Resource Allocation

Artificial intelligence (AI) is expected to significantly enhance radio resource management (RRM) in sixth-generation (6G) networks. However, the lack of explainability in complex deep learning (DL) m...

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This paper addresses a significant challenge in machine learning applications in communications—explainability in deep learning models. The proposed framework is innovative, providing a systematic method that not only enhances model interpretability but also improves computational efficiency without sacrificing performance. The rigorous methodology and substantial performance improvements, alongside clear applicability to 6G networks, underscore its relevance.

Minimizing Queue Length Regret for Arbitrarily Varying Channels

We consider an online channel scheduling problem for a single transmitter-receiver pair equipped with $N$ arbitrarily varying wireless channels. The transmission rates of the channels might be...

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The article presents a novel approach to an online channel scheduling problem, which has practical implications in the context of arbitrarily varying wireless channels. The use of a weakly adaptive Multi-Armed Bandit (MAB) algorithm in an unstable queueing scenario is innovative and expands the understanding of regret minimization in complex systems. Its methodological rigor, particularly in addressing stability assumptions, adds substantial value to current research methodologies in queue theory and resource allocation.

Mode-Shell correspondence, a unifying phase space theory in topological physics -- part II: Higher-dimensional spectral invariants

The mode-shell correspondence relates the number $I_M$ of gapless modes in phase space to a topological \textit{shell invariant} \Ish defined on a close surface -- the shell -- surro...

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The article presents a significant theoretical advancement in the understanding of gapless modes through a unified framework that has implications across multiple dimensions and various topological phases. Its novel approach to linking bulk and boundary states through the mode-shell correspondence addresses important questions in topological physics and provides a robust basis for future explorations. The rigorous mathematical derivation and the general applicability of the theory to different symmetry classes underpin its high relevance.

Giant end-tunneling effect in two distinct Luttinger liquids coexisting in one quantum wire

Luttinger liquids occupy a special place in physics as the most understood case of essentially quantum many-body systems. The experimental mission of measuring its main prediction, power laws in obser...

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This study presents important findings on the behavior of Luttinger liquids, which are foundational in the understanding of quantum many-body systems. The combination of tunneling spectroscopy with density-dependent transport measurements over a broad temperature range demonstrates methodological rigor. The identification of distinct tunneling behaviors as a function of subband population introduces novel insights, potentially influencing the characterization techniques within this area of study. Its implications for measurement techniques and theoretical predictions in the field of condensed matter physics are significant, thus earning a high relevance score.

A simple recursive representation of the Faulhaber series

We present a simple elementary recursive representation of the so called Faulhaber series $\sum_{k=1}^n k^N$ for integer $n$ and $N$ , without reference to Bernoulli numbers or ...

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The article introduces an innovative approach that simplifies the understanding and representation of the Faulhaber series, a well-known topic in number theory and combinatorics. The novelty lies in the avoidance of Bernoulli numbers and polynomials, which are often complex to deal with in this context. This could make the concept more accessible and inspire further research into alternative methods and representations in related mathematical areas.

Highly Uniform Magnetic and Electronic Environment in Non-Centrosymmetric Superconductor LaRhGe $_3$

We report the results of $^{139}$ La NMR measurements in the non-centrosymmetric superconductor LaRhGe $_3$ . This material crystallizes in a tetragonal structure without inversion symmet...

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This article presents new NMR measurements that provide valuable insights into the magnetic and electronic environment of a novel non-centrosymmetric superconductor. The findings about the uniformity of the magnetic properties and the characterization of LaRhGe$_3$ as a weakly correlated semimetal are significant for understanding the behavior of such materials and may inspire further research on related superconductors. The methodological rigor in employing NMR techniques also strengthens the credibility of the results, while the focus on a less-explored class of materials adds novel value to the field.

(111) Si spin qubits constructed on L point of band structure

(001) Si spin qubits are being intensively studied because they have structures similar to that of CMOS devices currently being produced, and thus have the advantage of utilizing state-of-the-art mini...

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The article addresses key challenges in the development of Si spin qubits, an area of significant interest for quantum computing. The proposed solutions showcase methodological innovation and potential advances in device architecture that could directly enhance the functionality and reliability of spin qubits. The focus on addressing decoherence and control issues is particularly relevant for advancing this field.

LLMs Can Plan Only If We Tell Them

Large language models (LLMs) have demonstrated significant capabilities in natural language processing and reasoning, yet their effectiveness in autonomous planning has been under debate. While existi...

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The article presents a significant advancement in the capability of large language models (LLMs) to perform autonomous planning tasks. The introduction of the AoT+ framework shows novelty and methodological rigor, especially as it reportedly achieves superior results on benchmarks compared to both prior models and human performance. This positions the research as potentially impactful for the future of AI development, especially in tasks that require strategic planning. However, the dependency on specific enhancements may limit its generalizability, which slightly reduces the score's maximum potential.