Search:
Match:
5 results
Research Paper#Nuclear Physics, Relativistic Heavy Ion Collisions🔬 ResearchAnalyzed: Jan 3, 2026 06:38

Dissipative Corrections to Particle Momentum Spectrum at Decoupling

Published:Dec 31, 2025 17:40
1 min read
ArXiv

Analysis

This paper investigates the impact of dissipative effects on the momentum spectrum of particles emitted from a relativistic fluid at decoupling. It uses quantum statistical field theory and linear response theory to calculate these corrections, offering a more rigorous approach than traditional kinetic theory. The key finding is a memory effect related to the initial state, which could have implications for understanding experimental results from relativistic nuclear collisions.
Reference

“The gradient expansion includes an unexpected zeroth order term depending on the differences between thermo-hydrodynamic fields at the decoupling and the initial hypersurface. This term encodes a memory of the initial state...”

PermalinkArXiv
Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 12:02

Explicit and Non-asymptotic Query Complexities of Rank-Based Zeroth-order Algorithm on Stochastic Smooth Functions

Published:Dec 22, 2025 07:18
1 min read
ArXiv

Analysis

The article likely presents a theoretical analysis of a specific optimization algorithm. The focus is on the computational cost (query complexity) of the algorithm when applied to a class of functions with certain properties (stochastic smoothness). The terms "explicit" and "non-asymptotic" suggest a rigorous mathematical treatment, providing concrete bounds on performance rather than just asymptotic behavior.

Key Takeaways

    Reference

    “”

    PermalinkArXiv
    Research#Optimization🔬 ResearchAnalyzed: Jan 10, 2026 10:10

    Analyzing Query Complexity in Rank-Based Zeroth-Order Optimization

    Published:Dec 18, 2025 05:46
    1 min read
    ArXiv

    Analysis

    This research paper explores the query complexities of rank-based zeroth-order optimization algorithms, focusing on smooth functions. It likely provides valuable insights for improving the efficiency of black-box optimization methods, especially in settings where gradient information is unavailable.
    Reference

    “The paper focuses on rank-based zeroth-order algorithms and their query complexities.”

    PermalinkArXiv
    Research#Physics🔬 ResearchAnalyzed: Jan 10, 2026 11:06

    Dynamical Stability Derives Gibbs State: Challenging the Zeroth Law

    Published:Dec 15, 2025 15:49
    1 min read
    ArXiv

    Analysis

    This ArXiv paper explores a novel perspective on foundational physics, potentially offering a more unified framework for understanding equilibrium. The claim of redundancy in the zeroth law is significant and warrants further scrutiny within the physics community.
    Reference

    “The paper argues that the Gibbs state postulate can be derived from dynamical stability, implying a redundancy of the zeroth law.”

    PermalinkArXiv
    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 06:58

    On-Device Fine-Tuning via Backprop-Free Zeroth-Order Optimization

    Published:Nov 14, 2025 14:46
    1 min read
    ArXiv

    Analysis

    This article likely discusses a novel method for fine-tuning large language models (LLMs) directly on devices, such as smartphones or edge devices. The key innovation seems to be the use of zeroth-order optimization, which avoids the need for backpropagation, a computationally expensive process. This could lead to more efficient and accessible fine-tuning, enabling personalized LLMs on resource-constrained devices. The source being ArXiv suggests this is a research paper, indicating a focus on technical details and potentially novel contributions to the field.
    Reference

    “”

    PermalinkArXiv