Field-programmable gate arrays (FPGAs) can provide adaptability at the hardware level -- a blank slate of digital hardware engineers can rewire at will.
Photonics is experiencing a boom many of us have hoped for. From self-driving car light detection and ranging (LiDAR) to fiber-optic networks and medical imaging, optical technologies are taking on bigger roles than ever. But as photonics goes mainstream, it's hitting a wall. It must deliver ultrahigh-performance at unprecedented low cost -- all under intense time pressure. The usual approach of throwing general-purpose processors or off-the-shelf instruments at these challenges is no longer enough. What photonics needs now is adaptability at the hardware level -- the type we get from FPGAs.
Traditional photonic systems often relied on a patchwork of fixed-function modules and personal computer (PC)-based processing. A company developing a new laser sensor might buy a pricey external control box, write some software, and call it a day. This may work in a lab, but it falls apart when you try to scale up or integrate into a real product. These ready-made solutions, while reliable, tend to be bulky, expensive, and inflexible. In a world where startups are shrinking spectrometers onto chips and driving LiDAR costs down by orders of magnitude, a "black box" approach becomes a competitive liability.
This is where FPGAs come in. FPGAs are essentially a blank slate of digital hardware engineers can rewire at will. Need to process gigabit-per-second data from a coherent optical link? Program the FPGA to do it in parallel. Want a control loop that tweaks a laser's wavelength with microsecond latency? It's trivial in FPGA logic, but a tall order for a central processing unit (CPU). The key benefits are precise timing, true real-time processing at the source, and reconfigurability as requirements evolve. In short: FPGAs let photonics teams build custom low-latency pipelines tailored to their needs and to update them on the fly.
Several photonics sectors have already embraced this adaptability. Consider LiDAR: to map the world in three dimensions (3D), a unit must send laser pulses and measure return timing with extreme precision (tens of picoseconds). You won't meet that spec with a PC or microcontroller -- the timing uncertainty alone would ruin accuracy. FPGAs, by contrast, excel at timestamping events and crunching time-of-flight calculations quickly. This type of precision is why every modern high-end LiDAR has an FPGA in its signal chain. And optical coherence tomography (OCT) in medicine uses an FPGA-based OCT system to achieve real-time imaging where PC setups had struggled. For fiber-optic communications, FPGAs are a prototyping workhorse for custom multigigabit links. The pattern is clear: When photonics demands high bandwidth or tight feedback loops, static architectures crack while reconfigurable hardware shines.
We're also seeing a cultural shift. Not long ago, many photonics engineers saw FPGAs as a daunting detour. But this mindset is changing fast as open-source FPGA platforms lower the barrier to custom hardware design. One example is LongPath Technologies, a startup deploying laser-based methane sensors. Instead of buying expensive test boxes, LongPath built its own system on open FPGA hardware and iterated quickly. This shift is not limited to startups -- institutions like NASA and CERN have also turned to open FPGA platforms for various projects, valuing their adaptability, compactness, and ease of integration. Tools like Red Pitaya are quietly supporting this evolution by offering affordable, flexible instrumentation that teams can tailor to demanding research and deployment environments.
If a small team can spin up a custom photonic system on an FPGA in weeks, the old excuses no longer hold water. It's not to say adopting FPGAs is effortless. It requires a shift in mindset and a willingness to invest in crossdisciplinary skills. Engineers must bridge the gap between optical physics and digital logic, which isn't always comfortable. But the alternative -- sticking with off-the-shelf boxes and slow software loops -- will leave you lagging behind. The good news is that the ecosystem is maturing and high-level tools and ready-made reference designs are making FPGA development more approachable.
Beyond having the proper FPGA hardware, it's equally important to have efficient and compatible development tools to fully harness FPGA capabilities. FPGA design requires specialized software environments for tasks such as design entry, programming, simulation, synthesis, and debugging. Tools like AMD Xilinx Vivado, Intel Quartus Prime, and Lattice Diamond provide comprehensive suites tailored to different FPGA families, enabling developers to create and optimize complex custom logic effectively. These tools bridge the gap between hardware and software, offering libraries and intellectual property (IP) cores that accelerate development while ensuring precise control over timing and resource allocation. The right tools are critical to reducing development time and achieving high-performance results in demanding applications.
One example of leveraging FPGA capabilities for photonics applications is PyRPL (Python Red Pitaya Lockbox) software, which is an open-source FPGA-controlled software package designed for the Red Pitaya platform and widely used for photonics and quantum optics. It simplifies interfacing with FPGA hardware via a flexible Python interface and graphical user interface (GUI) for real-time feedback control, signal processing, and advanced filtering. This combination of powerful FPGA hardware and accessible software tools empowers researchers and engineers to build custom, high-precision photonic systems efficiently. It shows how adaptable FPGA systems become significantly more usable and impactful with strong supporting software ecosystems.
In 2025, you don't need an army of hardware description language (HDL) coders because the latest FPGAs with built-in processors and high-level design environments make it easier to combine software with custom logic. This fusion of software flexibility and hardware speed is exactly what our industry needs. Reconfigurable, low-latency hardware is a necessity as we enter an era in which products must adapt to ever-changing signals and standards in real time. You simply can't get this kind of agility with static designs or closed black boxes.
Ask yourself: Will my current architecture meet the demands of the next-generation LiDAR or the next breakthrough in optical microscopy? Often, the answer points to a FPGA-centric solution. Embracing FPGA-level adaptability means ensuring our systems can evolve as quickly as the photonic innovations they support. The sooner we do, the better prepared we'll be for photonics' bright future.