Entropy of pebble automata and space complexity
The paper proves that the complexity class NL is distinct from logCFL, a result that further implies the separations L ≠ Ptime and NL ≠ Ptime.
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Author-Reviewed Papers
Papers where the original authors have engaged with our plain-language explanation.
For every paper on this page, at least one of the original authors has seen our plain-language explanation and engaged with it — either confirming it reads accurately or requesting corrections that we then applied. An endorsement does not mean the authors formally approve every sentence, but it does mean the explanation has passed the eyes of the people who wrote the paper.
438 papers reviewed by authors · 191–200 / 438
Latent-Space Causal Discovery from Indirect Neuroimaging Observations
This paper introduces INCAMA, a physics-aware framework that combines latent-space inversion with a delay-aware Mamba encoder to recover directed neural causal structures from distorted neuroimaging signals, demonstrating superior performance over baselines in both simulations and real-world fMRI data.
A Quadratic-Form Representation of the Scalar Casimir Trace from Codimension-Three Riesz Reduction
This paper establishes a quadratic-form representation of the scalar Casimir trace by deriving an induced Green kernel from a codimension-three Riesz reduction, which allows the expectation of a heat-regularized Gaussian source's energy to exactly reproduce the trace and confirms standard finite-part results in Dirichlet parallel-plate geometries.
Black holes at a finite distance: Quasi-local restricted phase space formalism
This paper extends the restricted phase space formalism to quasi-local regimes with static observers at finite distances, demonstrating that RN black holes in this setting exhibit thermodynamic behaviors and phase transitions strikingly similar to asymptotic RN-AdS black holes, including Hawking-Page-like transitions in the neutral limit, provided an extra pair of thermodynamic variables (pressure and boundary area) is included.
An HST Wide Field Survey of the Galactic Bulge: Overview, Strategy, and First Results
This paper presents an overview, observing strategy, and initial results of a coordinated HST imaging survey covering 1.1 square degrees in the Galactic Bulge, designed to create a high-resolution legacy dataset that will significantly enhance the scientific return of the upcoming Nancy Grace Roman Galactic Bulge Time Domain Survey.
Blow-up trick in Combinatorics
This paper generalizes the graph-theoretic concept of "blow-up," where vertices are replaced by copies, to a broader combinatorial framework and explores its potential applications.
You Only Stack Once (YOSO): A Motion-Filtered, Deep-Learning Framework for Detecting Faint Moving Sources
The paper introduces You Only Stack Once (YOSO), a novel deep-learning pipeline that utilizes a Gaussian Motion Filter to efficiently detect faint, slow-moving Solar System objects with an extremely low false positive rate, offering a scalable alternative to traditional shift-and-stack methods for large-scale astronomical surveys.
Broken-symmetry shape discrimination on a driven Duffing ring
This paper investigates how a driven Duffing ring on a cycle graph utilizes linear sorting and symmetry-constrained cubic mode-mixing to distinguish input shapes via a single observable, , which remains robust against noise due to the breaking of time-reversal symmetry by dissipation.
Analytical classification of Majorana zero-mode spatial profiles in extended Kitaev chains: probability maxima can shift inward
This paper presents an analytical framework for extended Kitaev chains that reveals Majorana zero modes can exhibit diverse spatial profiles, including interior probability maxima and distinct decay behaviors, which are fully determined by the characteristic roots of a derived recursion relation.
HBEE: Human Behavioral Entropy Engine -- Pre-Registered Multi-Agent LLM Simulation of Peer-Suspicion-Based Detection Inversion
This pre-registered multi-agent simulation study reveals a counterintuitive detection inversion where an LLM-driven adaptive insider, employing operational security directives, achieves a statistically lower peer-suspicion score than innocent agents, thereby decoupling behavioral anomaly signals from traditional user-entity behavior analytics and exposing a critical generalization gap in current insider threat models.