Electronic-photonic convergence (EPC) represents a crucial technology for addressing performance limitations in traditional electronic systems and improving information processing efficiency. The design of electronic-photonic integrated chips for next-generation computing interconnects and high-speed communications necessitates addressing challenges in cross-domain co-optimization between photonic and electronic components. Current EPC co-simulation methods encounter several technical constraints, including insufficient integration of electronic and photonic toolchains, inefficient cross-platform data exchange, and the lack of unified multiphysics domain solvers. Photonic device modeling can be implemented through hardware description language (HDL) by utilizing established complementary metal oxide semiconductor (CMOS) platforms and electronic design automation (EDA) tools. This methodology enables photonic simulation integration into microelectronic design environments, reduces dependence on specialized photonic simulation tools, and facilitates efficient electronic-photonic system development within a unified platform.

This paper presents a comprehensive review of photonic device modeling in the context of emerging trends in electronic-photonic co-simulation technologies. Photonic devices can be modeled using various hardware description languages, such as Verilog-A or SPICE, which rely on the differential-algebraic equation (DAE) solving framework intrinsic to EDA platforms. These flexible mathematical expression and computational capabilities are particularly well-suited for describing the wave properties and optical field variations of photonic devices. Current photonic device modeling primarily employs hardware description language, including Verilog-A behavioral-level modeling, SPICE circuit-level modeling, and hybrid techniques that combine both methods. Verilog-A, a widely employed hardware description language in integrated circuit design, is intended to model the dynamic behavior of devices and analog circuits. Verilog-A behavioral modeling focuses on describing the relationship between device inputs and outputs from a higher level of abstraction. The modeling principle lies in establishing mathematical relationships, via analytical functions or scattering matrices, between input signals and device responses, thereby avoiding the direct modeling of complex physical mechanisms. With its inherent flexibility and numerical computation capabilities, Verilog-A has been effectively extended to optoelectronic device modeling, enabling accurate representation of the dynamic evolution of optical fields. In 2013, Kononov established a photonic Verilog-A library that included elements such as lasers, photodetectors, waveguides, and directional couplers, enabling optical signal transmission and computation within an EDA environment. Several studies on the Verilog-A modeling approach have aimed to enhance the expressive capabilities for photonic devices. For example, in 2024, Zhang proposed an improved model structure to capture nonlinear effects (Fig. 2).

SPICE typically refers to circuit netlists composed of fundamental electrical components such as resistors, capacitors, inductors, and controlled sources. This modeling language characterizes circuit structures by describing the interconnections of circuit nodes and formulates equations based on Kirchhoff's laws to solve for voltage and current distributions. Since SPICE represents the most fundamental unit in electronic design, modeling photonic devices as equivalent electrical components facilitates the co-design and co-simulation with surrounding driving circuits. For active photonic components such as lasers and photodetectors, the presence of significant carrier transport phenomena makes SPICE equivalent circuit models particularly well-suited for capturing the electrical and optical behavior through rate equation formulations (Fig. 3 and Fig. 4). Meanwhile, as modulators are driven by electrodes, their electrical characteristics can be inherently represented using circuit-level models. In 2017, Shin proposed an equivalent circuit modeling method for modulators, in which the device was divided into three sections based on coupled-mode theory [Figs. 5(a) and 5(b)]. The equivalent circuit modeling of passive devices presents challenges, as their behavior primarily depends on electromagnetic field distributions rather than carrier transport. Consequently, extracting electrical equivalent models directly from their modal characteristics or geometric structures proves difficult. In 2022, Ye proposed an SPICE modeling method for passive devices, where S-parameters were modeled using the complex vector fitting (CVF) algorithm through pole-residue decomposition [Fig. 5(c)]. In 2024, Ming proposed an SPICE equivalent circuit model for photonic devices based on a numerical equivalence approach. By utilizing controlled sources, functional operations were implemented to map the analytical expressions of photonic devices into logic computation circuits [Fig. 5(d)].

In addition, hybrid modeling approaches that integrate SPICE with Verilog-A combine the circuit-level accuracy with the lightweight flexibility of behavioral-level (Fig. 6). This enables efficient mapping of photonic devices into EDA environments, enhancing the capabilities for system-level design and analysis in electronic-photonic integrated systems. A comparison of the functional capabilities of different modeling methods is summarized (Table 1).

However, the fundamental differences in the nature and propagation mechanisms between optical and electrical signals pose significant challenges in directly incorporating photonic devices into conventional microelectronic simulation workflows. In 2015, Agaskar proposed the equivalent baseband shifting solution, in which the optical carrier frequency was shift-down to zero frequency by selecting a reference frequency. To address accuracy degradation caused by cumulative errors in cascaded photonic device models, Jiang proposed an infinite impulse response (IIR) modeling method in 2024. This method enabled frequency-range extrapolation during modeling by adjusting the sampling frequency, effectively suppressing numerical error accumulation. In the same year, Feng from the same research group introduced a polynomial extrapolation approach for frequency-domain S-parameters, further improving the practicality and scalability of the modeling framework (Fig. 7). In 2024, Fang proposed an efficient and high-accuracy simulation method for optoelectronic integrated links based on an EDA platform, significantly improving the efficiency of electronic-photonic co-simulation.

Substantial advances have been achieved in hardware description language modeling of photonic devices, establishing a crucial foundation for EPC. This field enables the design and simulation of integrated optoelectronic systems on established microelectronic platforms, following IC design principles. The integration of photonic models into the electronic design workflow eliminates reliance on external simulation engines and removes technical barriers between these domains, providing a viable pathway toward electronic-photonic design automation (EPDA). This paper reviews the progress in photonic device modeling. While the proposed methodologies and implemented module characteristics vary, the fundamental aim remains consistent: accurately representing optical and physical characteristics of photonic devices within EDA environments. The paper addresses challenges in modeling accuracy and simulation efficiency, presenting corresponding solutions. Future developments should emphasize the hierarchical and collaborative advancement of modeling approaches, progressing from behavioral models to phenomenological models, and ultimately to full-physics models, based on the unified solution of electrical Kirchhoff's laws and optical Maxwell's equations.