Author-Reviewed Papers

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.

1365 papers reviewed by authors · 1241–1250 / 1365

🤖 machine learning

Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

This paper proposes a semi-supervised teacher-student learning framework that leverages CVaR-optimized labels and synthetic t-copula augmented data to train robust Bayesian and deterministic models for portfolio optimization, demonstrating their ability to outperform traditional methods in data-scarce environments and under regime shifts.

Adhiraj Chattopadhyay2026-04-04✓ Author reviewed ⓘ

🔢 mathematics

Hamilton-Jacobi as model reduction, extension to Newtonian particle mechanics, and a wave mechanical curiosity

This paper reinterprets the Hamilton-Jacobi equation as a model reduction that eliminates velocity degrees of freedom, thereby extending its applicability to general Newtonian systems with non-conservative forces and deriving a dissipative Schrödinger equation through a geometric optics approximation.

Amit Acharya2026-04-03✓ Author reviewed ⓘ

⚛️ quantum physics

Perspectives in and on Quantum Theory

This paper advocates for a pragmatist interpretation of quantum theory that treats measurement outcomes and quantum states as perspectival facts relative to specific physical contexts, thereby resolving the measurement problem and nonlocality while maintaining that the theory's statistical predictions remain objectively valid for science because actual measurements are effectively certified within a single context of assessment.

Richard Healey2026-04-03✓ Author reviewed ⓘ

💻 computer science

Amalgamation of Physics-Informed Neural Network and LBM for the Prediction of Unsteady Fluid Flows in Fractal-Rough Microchannels

This paper proposes a novel Physics-Informed Neural Network (PINN) framework that integrates sparse Lattice Boltzmann Method (LBM) data with Navier-Stokes constraints to accurately and efficiently predict unsteady fluid flows in fractal-rough microchannels, achieving a 150–200-fold reduction in data requirements compared to traditional CFD approaches.

Ganesh Sahadeo Meshram, Partha Pratim Chakrabarti, Suman Chakraborty2026-04-03✓ Author reviewed ⓘ

🔭 astrophysics

Multi-Tracer Cross-Correlations of the Unresolved $\gamma$ -Ray Sky

Using twelve years of Fermi-LAT and three years of DES data, this study establishes the extragalactic origin of the unresolved $\gamma$ -ray background with a 10.31 $\sigma$ significance through multi-tracer cross-correlations, revealing that its faint source populations possess distinct properties from currently resolved $\gamma$ -ray sources.

B. Thakore, M. Regis, M. Negro, S. Camera, D. Gruen, N. Fornengo, A. Roodman2026-04-02✓ Author reviewed ⓘ

⚛️ nuclear experiments

Low-Order Bessel-Type PID Dynamics in Lithium-Based Tritium Breeding and Heat-Removal Systems

This paper presents a low-order analytical framework demonstrating that lithium-based tritium breeding and heat-removal systems in fusion reactors exhibit Bessel-type dynamics, enabling the effective application of PID controllers to manage thermal expansion and tritium inventory errors.

S. A. S. Borges (Federal University of São Carlos), S. D. Campos (Federal University of São Carlos)2026-04-01✓ Author reviewed ⓘ

🔬 physics

Experimental fast channel reactor operating in the traveling wave mode of nuclear fissions with a soft fast neutron spectrum

This paper presents the design principle of an experimental single-channel fast reactor operating in a traveling wave mode with a softened fast neutron spectrum (peaking at 200,000–500,000 eV) to significantly reduce radiation damage to structural materials, utilizing cylindrical uranium dicarbide fuel and hydraulic fuel handling systems.

Viktor Tarasov, Sergey Chernezhenko, Volodymyr Vashchenko, Mykhailo Shcherbina, Vyacheslav Lavrukhin2026-04-01✓ Author reviewed ⓘ

🔭 astrophysics

The Evolving Faber-Jackson Relation: A Unifying Framework for Galaxy Ages and the Baryonic Tully-Fisher Connection

This paper proposes a unified theoretical framework within the Nexus Paradigm of quantum gravity that derives an evolving Faber-Jackson relation from the baryonic Tully-Fisher relation via a common acceleration scale and cosmic time evolution, successfully explaining observed offsets between galaxy populations as differences in formation epochs and validating these dynamically derived ages with high-precision metallicity data.

Stuart Marongwe, Stuart Kauffman2026-04-01✓ Author reviewed ⓘ

🔢 mathematics

Hodge Structures in Sextic Fourfolds Equipped with an Involution

This paper verifies the Generalized Hodge Conjecture for the specific Hodge substructure of a smooth sextic fourfold constructed via Shioda's method from a ternary sextic with minimal Waring rank, thereby partially answering a question posed by Voisin.

Benjamin E. Diamond2026-04-01✓ Author reviewed ⓘ

🔬 physics

Learning the Exact Flux: Neural Riemann Solvers with Hard Constraints

This paper proposes a hard-constrained neural Riemann solver (HCNRS) that enforces five physical constraints—positivity, consistency, mirror symmetry, Galilean invariance, and scaling invariance—to accurately approximate exact Riemann solvers for fluid dynamics while overcoming the conservation errors and symmetry breaking issues found in unconstrained neural approaches.

Yucheng Zhang, Chayanon Wichitrnithed, Shukai Cai, Sourav Dutta, Kyle Mandli, Clint Dawson2026-04-01✓ Author reviewed ⓘ

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