An RF Engineer's Guide To Photonic Computing

By John Oncea, Editor

Photonic computing represents not a radical departure from familiar territory, but rather a natural extension along the electromagnetic spectrum. The transition from gigahertz to hundreds of terahertz brings fundamental physics changes, yet many core engineering principles remain surprisingly applicable.

The electromagnetic spectrum presents continuous progression from RF through microwave, terahertz, and finally to optical frequencies. Electromagnetic fields exist at frequencies from DC to at least 10²⁰ Hz, spanning at least 20 orders of magnitude, according to LibreTexts.

At RF frequencies, according to RP Photonics, wavelengths are measured in meters to centimeters, while optical wavelengths shrink to hundreds of nanometers, with visible light spanning roughly 400 to 700 nm, a scale difference ranging from approximately four to six orders of magnitude depending on which RF sub-band serves as the baseline (comparing, for example, centimeter-scale RF wavelengths to 500 nm optical wavelengths).

This dramatic wavelength compression creates both opportunities and challenges. The terahertz region is commonly defined as roughly 0.1 to 10 THz (some optics communities extend the upper edge toward ~30 THz), occupying the middle ground between mature electronic and optical technologies, according to RP Photonics. This “terahertz gap“ has historically limited technology development, though recent advances in photonic computing increasingly bridge this divide.

Waveguides: From Coaxial To Optical

RF engineers intimately understand waveguide theory: electromagnetic waves confined to propagate along defined structures, with mode profiles determined by boundary conditions and operating frequency. These same principles govern optical waveguides, though implementation details differ substantially. Where RF systems employ hollow metallic waveguides or coaxial transmission lines, photonic circuits use dielectric waveguides fabricated from silicon, silicon nitride, or lithium niobate.

Metal waveguides function effectively at microwave frequencies but become increasingly lossy as skin depth and surface roughness effects matter in the terahertz regime, while many polymers and glasses show frequency-dependent absorption in portions of the THz band. This material challenge drives the adoption of silicon photonics, which leverages mature CMOS fabrication processes while providing low-loss propagation at optical wavelengths.

The physics of light confinement in dielectric waveguides follows from total internal reflection—analogous to RF waveguide modes but governed by refractive index contrasts rather than metallic boundaries. These calculations scale to optical frequencies where waveguide dimensions shrink to micrometers, enabling dense integration impossible at RF.

Impedance Matching In The Optical Domain

Impedance matching remains crucial in photonics, though the concept requires reinterpretation. For non-magnetic materials, the wave impedance η = √(μ/ε), and when μ ≈ μ₀, the impedance scales approximately as 1/n, establishing that refractive index and impedance are inversely related. This mathematical relationship provides a direct bridge between RF transmission line theory and optical propagation.

In photonic integrated circuits, impedance matching concepts from RF technology optimize coupling between optical nanocircuit elements. However, photonic systems introduce unique matching challenges. While RF engineers deal with predominantly 50-ohm systems, optical systems must match between waveguides with effective modal impedances determined by mode field distributions and material properties. Anti-reflection coatings on optical components serve the same function as impedance-matching networks in RF systems, minimizing reflections at interfaces.

S-Parameters: A Universal Language

Scattering parameters provide a universal framework spanning RF and photonic domains. S-parameters represent complex numbers indicating magnitude and phase multiplication acting on light between every port in a device, with the S-matrix representing the complete first-order input-output response. This formalism allows photonic engineers to characterize components identically to RF devices, facilitating system-level design and simulation.

The physical meaning remains consistent: S₁₁ represents the reflection coefficient, S₂₁ represents the transmission, and the matrix framework enables cascade analysis of multi-stage systems. Critically, S-parameter measurements in photonics face similar challenges to RF: accounting for reference impedances, de-embedding fixture effects, and managing frequency-dependent behavior. The primary difference lies in measurement techniques, network analyzers, and directional couplers at RF frequencies versus optical spectrum analyzers and integrated photodetectors at optical frequencies.

Resonance And Q-Factor

Resonant structures pervade both RF and photonic engineering. RF engineers design cavity resonators, helical resonators, and LC tanks; photonic engineers design ring resonators, photonic crystal cavities, and Fabry-Perot structures. The mathematics governing resonance behavior – quality factor, bandwidth, and frequency selectivity – applies identically across the spectrum.

Microring resonators with moderate quality factors achieve resonance peaks with narrow bandwidths, making them particularly effective as tunable filters in wavelength-division multiplexed systems. When coupled power equals power loss in a ring, critical coupling is achieved with improved extinction ratio and sharper resonance peaks, directly analogous to critical coupling in RF resonant circuits.

The primary distinction lies in loss mechanisms: RF resonators lose energy primarily through conductor losses and dielectric absorption, while optical resonators suffer from scattering losses, absorption in materials, and coupling to radiation modes. Despite these differences, the engineering approach to optimizing resonant performance remains remarkably consistent.

Modulation Techniques: From RF To Optical

Signal modulation provides another area where RF concepts translate naturally to photonics. Both domains employ amplitude modulation, phase modulation, and frequency modulation. RF engineers modulate carrier signals using mixers, variable attenuators, and phase shifters; photonic engineers use Mach-Zehnder interferometers, electro-optic phase modulators, and microring modulators.

Commercial high-speed external electro-optic modulators can achieve modulation bandwidths exceeding 100 GHz, with research demonstrations reaching 110 GHz and beyond, according to Science Direct and Optica. Although the optical carrier spans terahertz of potential spectrum – with fiber having enormous available bandwidth of tens of terahertz in its low-loss transmission window – per-channel modulation bandwidth is currently limited by modulator and electronic driver technology, typically ranging from tens to hundreds of gigahertz per channel, according to RP Photonics. Wavelength-division multiplexing (WDM) overcomes this limitation by combining multiple channels, achieving total fiber capacity in the terahertz range.

Key Differences And Limitations

While many RF concepts scale to photonics, critical differences demand attention. First, the energy per photon at optical frequencies exceeds RF photon energy by orders of magnitude, making quantum effects significant. Spontaneous emission, shot noise, and amplified spontaneous emission introduce noise mechanisms absent in classical RF systems.

Second, nonlinear effects become prominent at optical powers that would be negligible in RF systems. Four-wave mixing, two-photon absorption, and self-phase modulation must be carefully managed in photonic circuits. These effects sometimes enable functionality – nonlinear optical switching, for example – but more often impose constraints on signal power and dynamic range.

Third, thermal effects play outsized roles in photonics. Temperature fluctuations shift resonant wavelengths in silicon devices at approximately 80 picometers per degree Celsius (with exact values being device-dependent), necessitating active thermal control rarely required in RF circuits, according to Optica.

The Path Forward

For RF engineers transitioning to photonics, the learning curve is gentler than might be expected. Fundamental electromagnetic theory, network analysis, and system-level thinking transfer directly. The primary adaptation involves internalizing new length scales, understanding optical-specific effects, and learning photonic fabrication constraints. But the conceptual framework – waveguides, impedance, coupling, resonance, modulation – remains fundamentally unchanged across the electromagnetic spectrum.

Photonic computing represents not a foreign domain, but a natural extension of RF engineering principles into the optical spectrum. By recognizing this continuity while respecting the unique physics of optical frequencies, RF engineers possess ideal preparation to contribute meaningfully to photonic system development. The electromagnetic spectrum forms a bridge, and RF engineers are uniquely positioned to cross it.