arXiv subjects

Ergun Simsek

Publications and source records attributed to Ergun Simsek.

7 recordsLinked to original sources

arXiv2026

Two Complementary Approaches to Determine the Effective Index of Dielectric Ring Resonators

Open-source finite-element frameworks for modal analysis of dielectric ring resonators are presented based on two complementary approaches. The first computes resonant wavelengths for discrete azimuthal mode numbers and obtains the effective index at a target wavelength by interpolation; the second solves directly for the azimuthal mode number at a prescribed wavelength via a quadratic eigenvalue formulation. Both approaches are validated against a commercial electromagnetic mode solver and yield nearly identical effective indices and dispersion curves. The fixed-mode-number approach requires slightly longer computation time but uses half as much memory, making it the preferred choice for memory-limited computers.

physics.optics↗

arXiv2026

On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists

With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remain in question: many scientists simply view them as probabilistic systems without the expertise to evaluate research, while other researchers are more optimistic about their readiness without concrete evidence. Understanding what AI reviewers do well, where they fall short, and what challenges remain is essential. However, existing evaluations of AI reviewers have focused on whether their verdicts match human verdicts (e.g., score alignment, acceptance prediction), which is insufficient to characterize their capabilities and limits. In this paper, we close this gap through a large-scale expert annotation study, in which 45 domain scientists in Physical, Biological, and Health Sciences spent 469 hours rating 2,960 individual criticisms (each targeting one specific aspect of a paper) from human-written and AI-generated reviews of 82 Nature-family papers on correctness, significance, and sufficiency of evidence. On a composite of all three dimensions, a reviewing agent powered by GPT-5.2 scores above each paper's top-rated human reviewer (60.0% vs. 48.2%, p = 0.009), while all three AI reviewers (including Gemini 3.0 Pro and Claude Opus 4.5) exceed the lowest-rated human across every dimension. AI reviewers' accurate criticisms are also more often rated significant and well-evidenced, and surface a distinct 26% of issues no human raises. However, AI reviewers overlap far more than humans do (21% vs. 3% for cross-reviewer pairs), and exhibit 16 recurring weaknesses humans do not share, such as limited subfield knowledge, lack of long context management over multiple files, and overly critical stance on minor issues. Overall, our results position current AI reviewers as complements to, not substitutes for, human reviewers.

cs.CL↗

arXiv2026

And Yet Another FEM-Based Mode Solver for Dielectric Waveguides

We present a full-vector finite element method (FEM) mode solver for dielectric waveguides based on a mixed Nedelec-Lagrange discretization of Maxwell's curl equations in the frequency domain. The formulation combines edge elements for transverse field components with nodal elements for the longitudinal component, enabling accurate modeling of hybrid modes while effectively suppressing spurious solutions. The solver is implemented in both MATLAB and Python with an emphasis on reproducibility, computational efficiency, and accessibility, including compatibility with cloud-based platforms. Numerical validation is performed on representative waveguide structures, demonstrating excellent agreement with COMSOL Multiphysics, with relative errors below 0.05%. Convergence studies confirm the expected accuracy trends with mesh refinement, while highlighting the trade-off between computational cost and precision. The proposed implementation provides a flexible and reliable open-source tool for integrated photonics research and education.

physics.optics↗

arXiv2026

Microring Resonator Dispersion Metrology with Neural Networks

Precise knowledge of resonator dispersion, from both geometric and material contributions, is essential for reliable high-performance nonlinear integrated photonics devices, such as optical parametric oscillators, frequency doublers, and integrated optical frequency combs. However, direct measurements at the fabrication level provide limited knowledge, whether through destructive cross-section imaging or non-destructive ellipsometry, while complete optical characterization that enables precise dispersion metrology is time-consuming and poorly suited for mass-scale foundry fabrication. In this work, we develop a machine learning framework to solve three complementary problems: (i) predicting resonator geometric dimensions, (ii) identifying the correct material dispersion, and last, but not least, (iii) precisely reconstructing the integrated dispersion spectrum directly from ring dimensions. These three neural networks together enable both inverse and forward characterization of microring resonators. Using numerically generated datasets based on Sellmeier-type material models, we demonstrate <1 nm ring dimension prediction accuracy without noise, <8 nm prediction accuracy with ~45 dispersion samples under a realistic frequency measurement noise level (50 MHz), and ~16 nm prediction accuracy at a higher noise level (200 MHz). The Sellmeier model classification exceeds 99% accuracy in all cases. Importantly, dispersion sampled far from the pump resonances proves most informative, reducing full-spectrum characterization requirements. The forward-prediction network reconstructs dispersion spectra from the ring dimensions with high accuracy. Our results highlight the potential of machine learning applied to dispersion data as a rapid, non-destructive tool for wafer-scale quality control and process monitoring in photonic foundries.

physics.optics↗

arXiv2025

Mixed Fields Formulation for Electromagnetic Waves Confined in Dielectric Rings

We present an easy-to-implement numerical method for analyzing electromagnetic wave propagation in dielectric rings. Our approach employs a finite-difference-based solver in cylindrical coordinates, solving a mixed electric-magnetic field formulation to accurately enforce boundary conditions and compute resonant modes. The method avoids geometric transformations; instead, it directly discretizes the Helmholtz wave equation in cylindrical coordinates and solves the resulting generalized eigenvalue problem. We validate our model against commercial solvers for various structures, including a Si3N4 ring embedded in SiO2, a ring on a thin-film-coated substrate, and a torus, achieving agreement in effective refractive indices within 0.3%. The formulation accurately captures field confinement, curvature effects, and dispersion, enabling precise determination of propagation constants and mode profiles. As an application, we model optical frequency comb generation in a high-Q microresonator, predicting a free spectral range of 99.6 GHz and a loaded quality factor of 1.6 million, corroborated by experimental measurements.

physics.optics↗

arXiv2025

Practical Vectorial Mode Solver for Dielectric Waveguides Based on Finite Differences

This study presents a finite-difference-based numerical solver designed for the electric field formulation of vector wave equations in optically linear, non-magnetic, dielectric waveguides. We construct a generalized eigenvalue problem by incorporating all three components of the electric field into a self-consistent formulation. This ensures accurate enforcement of boundary conditions and reduces numerical artifacts, particularly at permittivity discontinuities. We validate the solver's performance through two representative waveguide structures, demonstrating its accuracy in computing both propagation constants and mode profiles.

physics.optics↗

arXiv2014

Gold on WSe2 Single Crystal Film as a Substrate for Surface Enhanced Raman Scattering (SERS) Sensing

Synthesis and characterization of high-quality single-crystal WSe2 films on highly-insulating substrate is presented. We demonstrate for the first time that the presence of gold nanoparticles in the basal plane of a WSe2 film can enhance its Raman scattering intensity. The experimentally observed enhancement ratio in the Raman signal correlates well with the simulated electric field intensity using a three-dimensional electromagnetic software and theoretical calculation. This work provides guidelines for the use of two-dimensional WSe2 films as a SERS substrate.

cond-mat.mes-hall↗