Paper List
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GOPHER: Optimization-based Phenotype Randomization for Genome-Wide Association Studies with Differential Privacy
This paper addresses the core challenge of balancing rigorous privacy protection with data utility when releasing full GWAS summary statistics, overco...
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Real-time Cricket Sorting By Sex A low-cost embedded solution using YOLOv8 and Raspberry Pi
This paper addresses the critical bottleneck in industrial insect farming: the lack of automated, real-time sex sorting systems for Acheta domesticus ...
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Training Dynamics of Learning 3D-Rotational Equivariance
This work addresses the core dilemma of whether to use computationally expensive equivariant architectures or faster symmetry-agnostic models with dat...
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Fast and Accurate Node-Age Estimation Under Fossil Calibration Uncertainty Using the Adjusted Pairwise Likelihood
This paper addresses the dual challenge of computational inefficiency and sensitivity to fossil calibration errors in Bayesian divergence time estimat...
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Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training
This paper addresses the core challenge of accurately predicting protein fitness with only a handful of experimental observations, where data collecti...
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scCluBench: Comprehensive Benchmarking of Clustering Algorithms for Single-Cell RNA Sequencing
This paper addresses the critical gap of fragmented and non-standardized benchmarking in single-cell RNA-seq clustering, which hinders objective compa...
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Simulation and inference methods for non-Markovian stochastic biochemical reaction networks
This paper addresses the computational bottleneck of simulating and performing Bayesian inference for non-Markovian biochemical systems with history-d...
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Assessment of Simulation-based Inference Methods for Stochastic Compartmental Models
This paper addresses the core challenge of performing accurate Bayesian parameter inference for stochastic epidemic models when the likelihood functio...
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.