Paper List
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Translating Measures onto Mechanisms: The Cognitive Relevance of Higher-Order Information
This review addresses the core challenge of translating abstract higher-order information theory metrics (e.g., synergy, redundancy) into defensible, ...
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Emergent Bayesian Behaviour and Optimal Cue Combination in LLMs
This paper addresses the critical gap in understanding whether LLMs spontaneously develop human-like Bayesian strategies for processing uncertain info...
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Vessel Network Topology in Molecular Communication: Insights from Experiments and Theory
This work addresses the critical lack of experimentally validated channel models for molecular communication within complex vessel networks, which is ...
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Modulation of DNA rheology by a transcription factor that forms aging microgels
This work addresses the fundamental question of how the transcription factor NANOG, essential for embryonic stem cell pluripotency, physically regulat...
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Imperfect molecular detection renormalizes apparent kinetic rates in stochastic gene regulatory networks
This paper addresses the core challenge of distinguishing genuine stochastic dynamics of gene regulatory networks from artifacts introduced by imperfe...
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PanFoMa: A Lightweight Foundation Model and Benchmark for Pan-Cancer
This paper addresses the dual challenge of achieving computational efficiency without sacrificing accuracy in whole-transcriptome single-cell represen...
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Beyond Bayesian Inference: The Correlation Integral Likelihood Framework and Gradient Flow Methods for Deterministic Sampling
This paper addresses the core challenge of calibrating complex biological models (e.g., PDEs, agent-based models) with incomplete, noisy, or heterogen...
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Contrastive Deep Learning for Variant Detection in Wastewater Genomic Sequencing
This paper addresses the core challenge of detecting viral variants in wastewater sequencing data without reference genomes or labeled annotations, ov...
Macroscopic Dominance from Microscopic Extremes: Symmetry Breaking in Spatial Competition
Department of Mathematics, Florida State University | Department of Mathematics and Statistics, Cleveland State University | Institute of Molecular Biophysics, Florida State University
30秒速读
IN SHORT: This paper addresses the fundamental question of how microscopic stochastic advantages in spatial exploration translate into macroscopic resource dominance, revealing that initial discovery and final monopolization are governed by distinct physical mechanisms.
核心创新
- Methodology Introduces a dimensionless scaling parameter χ = (N₂/N₁)8^(d₁-d₂) that completely determines competitive symmetry, showing that a linear spatial disadvantage requires an exponential population advantage to overcome.
- Theory Demonstrates that extreme first-passage statistics govern initial discovery, while non-reciprocal interaction bias (β) controls the sharpness of the competitive phase transition and stability of the absorbing state.
- Biology Reveals a strict hierarchy of symmetry-breaking factors: proximity to resource > population size > interaction bias, with β being necessary but not sufficient for dominance.
主要结论
- Proximity imparts the strongest competitive advantage: a colony with distance d₁ < d₂ requires N₂/N₁ ~ 8^(d₂-d₁) ants to compensate (Equation 3).
- The interaction bias β acts as a phase transition tuner: for β → 0, outcomes remain probabilistic; for large β, the symmetry-breaking boundary sharpens into a step function (Figure 3).
- Discovery and monopolization are decoupled: extreme first-passage statistics govern initial finding (⟨T_i⟩ = d_i + (1-p_i)^(N_i)), while β strictly controls stability of the absorbing state.
摘要: How do competing populations convert a spatial advantage into macroscopic dominance? We introduce a stochastic model for resource competition that decouples the transient discovery phase from monopolization. Initial symmetry breaking is governed by extreme value statistics of first-passage times: a linear spatial disadvantage requires an exponentially larger population to overcome. However, transient superiority cannot stabilize dominance. A non-reciprocal interaction bias is strictly necessary to arrest local fluctuations and drive the system into a robust absorbing state.