Photonic Computing - The next frontier

Silicon Computing is under threat from this new technology with potential to alter the AI and high-end computing space. India needs to build expertise in this sector NOW!

Mar 06, 2025

As electronic computing nears its fundamental physical limits, new approaches are emerging. One such option is photonic computing, which uses light (photons) instead of electrons for calculations.

Photonic computing leverages the speed of photons—particles of light— instead of electrons. It offers advantages such as increased speed, energy efficiency, and higher bandwidth, enabling faster information processing and transmission.

Potential Applications & Future Prospects

The future of Photonic computing is promising, with research efforts focused on overcoming existing challenges and commercializing photonic processors. Key areas of future exploration include:

Hybrid Systems: Combining electronic and photonic elements to create hybrid processors that leverage the best of both technologies.
AI and Machine Learning: Enhancing deep learning applications with photonic neural networks to achieve real-time inference.
Optical Data Centers: Implementing fully optical data centres improves efficiency and reduces operational costs.
Quantum Photonic Computing: Developing large-scale quantum computers based on photonic qubits to solve complex problems beyond classical capabilities.
Ultrafast Communication Networks: Photonic computing could enable ultra-fast, high-bandwidth communication networks in telecommunications.
Military Radars: Photonic computing also holds promise in specialized applications such as synthetic-aperture radar (SAR) and optical correlators. These systems can be used for object detection, tracking, and classification of time-domain optical data.
EMP-resistant Networks: Critical infrastructure that may be compromised by Electro Magnetic Pulse or Electronic warfare attacks can be ideal areas for deployment of Photonic computing.

In Sum

I look at the developments in photonic computing from a different perspective. India wants to compete in computing technologies such as chip development. However, we also need to think of ways to leap-frog older technologies.

Photonic computing offers potential. Yes, it can fail. But this is the time to investigate it and develop applications if we want to compete at the cutting edge in the future.

Deep Dive into Photonic Computing

Let us look at some aspects of Photonic computing in a bit more detail.

Principles of Photonic Computing

Photonic computing operates on the principle of manipulating and processing information through light waves. The core components of photonic computing include:

Optical Interconnects: Instead of using copper wires, photonic computers use optical fibres to transmit data at the speed of light with minimal loss (Miller, 2017).
Silicon Photonics: A technology that integrates photonic circuits onto silicon-based chips, allowing compatibility with existing semiconductor fabrication techniques (Sun et al., 2015).
Nonlinear Optical Devices: These devices enable logic operations by controlling light-matter interactions, paving the way for optical transistors and switches (Lipson, 2005).
Photonic Neural Networks: Inspired by biological neurons, these networks process information using optical signals instead of electrical impulses, offering the potential for ultra-fast artificial intelligence applications (Shen et al., 2017).

Advantages of Photonic Computing

The adoption of photonic computing offers several key advantages over traditional electronic systems:

Higher Speed: Since photons travel faster than electrons, photonic processors can achieve speeds several orders of magnitude higher than conventional processors (Sunada, S., & Uchida, A. (2021)).
High Throughput: Using photonics provides high throughput of > 1 TB/s per channel
1. In comparison, copper wire tops out at around 1 GB/s per channel), with greater energy efficiency.
2. This is particularly crucial in an era where data volumes are growing exponentially and the demand for real-time processing is ever-increasing.
3. [Source: https://www.eejournal.com/article/are-we-poised-to-turn-the-optical-computing-corner/]
Energy Efficiency: Optical signals generate less heat than electronic currents, significantly reducing power consumption (Miller, 2010).
1. Electronic circuits suffer from Joule heating (also called Ohmic heating) due to resistive losses as electrons move through the copper.
2. Photonic computing systems primarily dissipate energy through optical absorption and scattering, resulting in much lower thermal output.
3. This property reduces the need for complex cooling mechanisms, making photonic processors more suitable for energy-efficient data centres and high-performance computing environments.
4. Additionally, it improves the longevity of components, further enhancing overall system reliability.
Parallelism: The nature of light allows for impressive parallel processing capabilities in photonic systems.
1. Light can be multiplexed using different wavelengths (wavelength-division multiplexing, WDM), allowing simultaneous data processing (Shen et al., 2017).
2. In simple terms, this means that multiple information streams can travel together without interfering with each other, much like different radio stations broadcasting on separate frequencies.
3. This ability significantly boosts processing power by allowing multiple computations simultaneously, unlike traditional electronic computing, which often processes data sequentially.
Reduced Latency: Optical computing minimizes signal delays, making it ideal for high-performance applications such as supercomputing and deep learning (Shastri et al., 2021).
1. For example, tedious and intensive matrix multiplications can be completed in << 1 nano-second compared to ~1000 nano-seconds for an ASIC/TPU implementation.
Reduced Electro Magnetic interference: One of the major advantages of photonic computing is its resilience to electromagnetic interference (EMI) and electromagnetic pulses (EMP). Traditional electronic systems are vulnerable to EMPs, which can disrupt or destroy electronic circuits, particularly in military and aerospace applications. Since photonic computers rely on light instead of electrical signals, they are naturally resistant to such disruptions, making them highly suitable for mission-critical applications like aircraft flight computing, space exploration, and defence systems. Additionally, photonic computing's low heat generation and high energy efficiency make it ideal for environments where cooling is a challenge, such as high-altitude aircraft and spacecraft.

Challenges in Photonic Computing

Despite its potential, photonic computing faces several challenges that must be overcome for widespread adoption:

Manufacturing Complexity: Integrating photonic components with existing electronic chips requires advanced fabrication techniques and high-precision alignment (Sun et al., 2015).
Material Limitations: Current semiconductor materials, such as silicon, have inherent nonlinear optical limitations, necessitating new materials like lithium niobate or graphene (Lipson, 2005).
Signal Loss and Interference: Optical signals can experience diffraction and scattering, affecting reliability (Sunada, S., & Uchida, A. (2021)).
Lack of Standardization: Unlike electronic computing, which follows established protocols, photonic computing still lacks universal standards and architectures (Miller, 2017).

Recent Developments and Research

Significant progress has been made in photonic computing, driven by advancements in materials science, nanotechnology, and artificial intelligence. Some notable research contributions include:

Photonic Tensor Processing Units (TPUs): Researchers at MIT have developed photonic TPUs capable of accelerating AI computations by utilizing optical interference patterns (Shen et al., 2017).
Silicon Photonic Chips: Companies like Intel and IBM are pioneering silicon photonic chips that integrate lasers and modulators for high-speed data transmission (Sun et al., 2015).
Optical Quantum Computing: Photonic computing may also play a crucial role in quantum computing, where quantum bits (qubits) encoded in photons enable faster quantum operations (Shastri et al., 2021).
Neuromorphic Photonic Processors: Recent developments in neuromorphic computing have demonstrated photonic-based architectures that mimic biological neural networks for ultra-fast computations (Miller, 2010).

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