works on

From the 1 of 9 papers with an AI index.

most citedForecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models

1 citations

9 papers

astro-ph.EP2026

Searching for GEMS: Three warm Saturns and a super-Jupiter orbiting four early M-dwarfs

Pranav H. Premnath, Paul Robertson, Shubham Kanodia +33

The paper confirms and characterizes four short-period giant exoplanets—including three Saturn-mass planets and one dense super‑Jupiter—transiting early M‑dwarf stars, using TESS p…

physics.chem-ph2026

Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory

Siqi Chen, Zhiqiang Wang, Yili Shen +8

Mechanistic understanding and rational design of complex chemical systems depend on fast and accurate predictions of electronic structures beyond individual building blocks. Howeve…

astro-ph.IM2026

Hubble Science in the 2030s White Paper: High-Contrast Optical and UV Spectroscopy with HST/STIS

K. Ward-Duong, J. Debes, J. Aguilar +11

The Space Telescope Imaging Spectrograph (STIS) on the Hubble Space Telescope currently stands as the sole space-based astronomical facility providing visible-light coronagraphic i…

quant-ph2026

Qubit operations using a modular optical system engineered with PyOpticL: a code-to-CAD optical layout tool

Jacob Myers, Christopher Caron, Nishat Helaly +5

Complex optical design is hindered by conventional piecewise setup, which prevents modularization and therefore abstraction of subsystems at the circuit level. This limits multiple…

math.NT2026

Counting primitive integral solutions to spherical generalized Fermat equations

Santiago Arango-Piñeros

A solution to a generalized Fermat equation \[ Ax^a + By^b + Cz^c = 0, \] is called \emph{primitive} if . By work of Beukers…

econ.GN20261 cited

Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models

Stephen J. Lee, Cailinn Drouin

We present a novel framework for high-resolution forecasting of residential heating demand and non-heating electricity demand using probabilistic deep learning models. Because our…