ARTFEED — Contemporary Art Intelligence

Deep Q-Network Variants Compared for Photonic Crystal Laser Design

other · 2026-07-29

A research paper available on arXiv (2607.23469) evaluates the standard Deep Q-Network (DQN) alongside six alternative value-based methods aimed at enhancing photonic-crystal surface-emitting lasers (PCSELs). This design challenge involves seven variables, utilizing a common goal, a simulator, an 83-call limit, and four aligned initializations. Among the variants, only Dueling DQN demonstrates improvements across all four seeds, elevating the mean quality factor and decreasing wavelength error by 64%. This study explores the effectiveness of various value-learning strategies when faced with stringent simulation budgets.

Key facts

  • arXiv paper 2607.23469 compares DQN variants for PCSEL design
  • Seven-variable PCSEL design with 83-call budget
  • Dueling DQN improves all four seeds
  • Wavelength error reduced by 64%
  • Mean quality factor increased

Entities

Institutions

  • arXiv

Sources