Beyond the Usual Rules: Factorization at High Energies
![The study reveals how factorization-a cornerstone of theoretical calculations in particle physics-breaks down at specific energy scales, demonstrated by collinear splittings connecting soft modes via Glauber-gluon exchange, and signaled by measurements indicated by colored blobs on lines representing these interactions-a phenomenon ultimately challenging the completeness of any perturbative approach to understanding high-energy collisions as expressed by the hard scattering amplitude [latex]\mathcal{M}_{N}[/latex].](https://arxiv.org/html/2603.12383v1/x2.png)
New research reveals that standard methods for predicting particle collisions break down when subtle quantum effects become dominant.
Science
Scaling Combinatorial Optimization with Lock-Free Parallelism
A new framework, LLP-FW, streamlines the development of parallel solvers for complex combinatorial problems by decoupling problem definition from implementation.
Taming DRAM’s Hidden Instability
New research details a rapid testing methodology for pinpointing the limits of data reliability in modern DRAM chips, revealing significant performance gains with targeted error mitigation.
When State Space Models Forget: A New Attack and Its Defense
![Under adversarial attack utilizing HiSPA, the Mamba-130M model experiences a precipitous decline in information retention-falling from [latex]\rho(\bar{A}) = 0.98[/latex] to [latex]0.32[/latex]-resulting in a [latex]52.5[/latex] percentage-point accuracy collapse, manifested as a contraction of hidden-state trajectories toward the origin, though this collapse can be mitigated by SpectralGuard intervention.](https://arxiv.org/html/2603.12414v1/figures/hidden_state_trajectories_3d.png)
Researchers have discovered a vulnerability in State Space Models where adversarial attacks can cause a ‘spectral radius collapse’, leading to performance degradation, and propose a novel monitoring system to detect and mitigate these attacks.
Faster Private Inference: Giving Priority Requests a Boost
![The system demonstrates effective tail packing within the cipher of [latex]r\_0^\widehat{\bm{r}\_{0}}[/latex], achieved through strategic management of in-queue inputs.](https://arxiv.org/html/2603.12946v1/x5.png)
A new framework significantly reduces the performance overhead of prioritizing inference requests when using privacy-preserving machine learning techniques.
Safe Skies for Drone Swarms: A New Approach to Collision Avoidance
![The system explores the inherent limitations of multi-UAV collision avoidance, demonstrating that successful navigation depends not simply on finding <i>a</i> solution-a control input within admissible bounds-but on the <i>existence</i> of a consistent intersection among all collision-avoidance constraints [latex] \bigcap_{i} C_i \neq \emptyset [/latex], a condition termed ‘internal compatibility’ which precedes any consideration of feasible control actions.](https://arxiv.org/html/2603.13103v1/x1.png)
Researchers have developed a refined method for ensuring the safe navigation of multiple drones in complex environments, focusing on enhancing the reliability of safety constraints.
Coding for Design: Building Structures with Linear Codes
This review details how linear codes can be leveraged to construct and analyze $q$-ary $t$-designs, offering a powerful bridge between coding theory and design theory.
Graph Cipher: A New Approach to Block Encryption
![A cryptographic layer leverages a 3-regular expander graph-where each of the 64 vertices connects to three neighbors defined by modular arithmetic [latex]n_1(i)=(i-1)\bmod 64[/latex], [latex]n_2(i)=(i+1)\bmod 64[/latex], and [latex]n_3(i)=(i+16)\bmod 64[/latex]-to achieve efficient hardware implementation alongside rapid data mixing, despite the inevitable accumulation of technical debt inherent in complex designs.](https://arxiv.org/html/2603.12637v1/x1.png)
Researchers have developed a novel block cipher, ExpanderGraph-128, that harnesses the power of graph theory for enhanced security and streamlined hardware implementation.
Beyond Surface Answers: Testing Diagnostic Reasoning in AI
A new benchmark challenges large language models to move past shortcut learning and demonstrate genuine understanding of complex medical cases.
Hidden Symmetries: Quantum Physics and the Secrets of Number Theory
![The distribution of exponents within a mass hierarchy, determined through minimum-weight matching, reveals a spectrum of solutions-those exhibiting symmetry in paired exponents [latex]e\_{1}=e\_{2}[/latex] and [latex]e\_{3}=e\_{4}[/latex], alongside non-symmetric alternatives-all normalized to a unified frequency.](https://arxiv.org/html/2603.12320v1/x1.png)
A surprising link between the search for dark matter and a classic problem in number theory is revealing unexpected constraints on particle physics.