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Related Articles from SNS
Strategic Users in a Priority Queue with Bulk Service on Blockchains
Announce Type: cross Abstract: This paper analyzes transaction fees on blockchains by considering that they form a priority queue and users play a queueing game. Using an M/G^K/1 priority queue model, we provide new insights into the dynamics governing transaction fees and their impact on user behavior. We derive semi-closed form expressions for steady-state quantities and extend the relationship between user delay costs and transaction fees to general block generation times.
Finite-Resolution Information from Collision Statistics
arXiv:2606.01218v1 Announce Type: new Abstract: Collision statistics provide a finite-resolution view of information by measuring how often a fixed number of independent samples fall on the same state. These directly countable quantities form the basis of integer-order R\'enyi entropies. Here, we use low-order R\'enyi entropies to approximate Shannon entropy and mutual information, while characterizing what is necessarily lost when only finitely many collision moments are used.
Cellular Sheaf Neural Operators for Structure-Preserving Surrogate Modeling of Constrained PDEs
arXiv:2606.00937v1 Announce Type: cross Abstract: Neural operators provide fast surrogate models for PDE simulations, but standard architectures often treat geometry and discretization as secondary to field data. Physical states are usually represented as grid-channel stacks, even when different quantities naturally belong on vertices, edges, faces, cells, boundaries, or interfaces and must satisfy compatibility constraints. We propose Cellular Sheaf Neural Operators, a discretization-aware...
Identifying sensitivity-dominant parameters via active subspaces in reduced-order modeling of fluid dynamics
new Abstract: Reduced-order models (ROMs) are widely employed to describe complex system dynamics when simulations with full-order models (FOMs) are computationally prohibitive. This study presents POD-AS-PRS, a novel model-reduction framework based on the active subspaces (AS) technique, which performs dimensionality reduction in both the state and parameter spaces, enabling efficient and high-fidelity approximations of quantities of interest (QoI). The approach employs proper orthogonal...
Lie algebraic invariants in quantum linear optics
arXiv:2409.12223v3 Announce Type: replace-cross Abstract: Quantum linear optics without post-selection is not powerful enough to produce any quantum state from a given input state. This limits its utility since some applications require entangled resources that are difficult to prepare.
Uncovering Extreme Event Mechanisms for Prediction and Control with Sensitivity-Balanced Projections
arXiv:2606.05618v1 Announce Type: cross Abstract: Extreme events -- such as earthquakes and coronal mass ejections -- are common in many chaotic dynamical systems, yet are difficult to characterize and predict due to the subtle instability mechanisms that drive them. In this work, we develop an interpretable technique that reveals the underlying mechanisms behind extreme events and uses them to build data-driven forecasts and intuitive event suppression controllers. In particular, we utilize...
Learned Response-Field Inertia Operator for HEC-RAS 2D Water-Surface Elevation Prediction
arXiv:2606.06385v1 Announce Type: new Abstract: This article presents a cross-dataset evaluation of learned native-cell surrogate models for solver-consistent water-surface elevation (WSE) prediction in HEC-RAS 2D. To avoid raster remapping error and information-access confounding, surrogates are evaluated directly on the original nonuniform computational cells under an explicit policy that separates static project inputs, current hydraulic state, project-input forcing, calibration-derived...
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
Announce Type: replace Abstract: Sparse attention reduces the quadratic complexity of full self-attention but faces two challenges: (1) an attention gap, where applying sparse attention to full-attention-trained models causes performance degradation due to train-inference distribution mismatch, and (2) a capability gap, where models trained purely with sparse attention lack complete gradient flow, preventing them from matching full-attention performance. We propose SSA (Sparse Sparse...
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
arXiv:2511.20102v4 Announce Type: replace Abstract: Sparse attention reduces the quadratic complexity of full self-attention but faces two challenges: (1) an attention gap, where applying sparse attention to full-attention-trained models causes performance degradation due to train-inference distribution mismatch, and (2) a capability gap, where models trained purely with sparse attention lack complete gradient flow, preventing them from matching full-attention performance. We propose SSA...
Bondi inquiry calls for better policing of Jewish events
An Australian inquiry into an antisemitic mass shooting at Bondi Beach which killed 15 people has recommended that the authorities should bolster security at Jewish events. The royal commission's interim report revealed that an Australian Jewish group had warned of a terrorist attack just days before the incident. The Australian prime minister Anthony Albanese says major changes have already been made.