RESEARCH SPOTLIGHT
Hi, I am
Mohammadreza Mokhtari
HOST INSTITUTE
IFISC (UIB-CSIC)
PROJECT TITLE
Coupled laser networks for information processing
KEY WORDS
Photonic Reservoir Computing, Coupled Laser Networks, Laser Dynamics, Laser Synchronization, Semiconductor Lasers
RESEARCH AIM
My research aims to develop scalable photonic reservoir computing using coupled semiconductor lasers so that complex information-processing tasks can be performed faster and more energy-efficiently in hardware.
RESEARCH OVERVIEW
Similar to how a network of neurons in our brain interact to process information, a coupled network of several lasers together can function as a computational core, with each laser producing a rich response to input signals. My research explores how light can be used to process information faster and more efficiently. Instead of relying on conventional digital electronics circuits, I study how complex dynamics of lasers' light can help solve computational tasks. The aim is to develop photonic computing hardware that could support faster, more sustainable, and lower-energy information processing for artificial intelligence and signal-processing technologies.
RESEARCH CHALLENGE
The main challenge is to make photonic reservoir computing more scalable without losing its speed advantage. In single delayed-feedback reservoirs, increasing response richness, the number of virtual nodes, often requires a longer delay line, which can slow down processing. My research asks whether a network of coupled physical laser nodes can increase computational richness and dimensionality while keeping the system fast and experimentally practical. A second challenge is that the behaviour of coupled laser networks depends on many interacting parameters and degrees of freedom, which makes identifying and characterizing the optimal operating regimes a difficult task.
RESEARCH INNOVATION
The innovative aspect is the combination of temporal multiplexing with spatial multiplexing in a coupled semiconductor-laser network. Instead of treating synchronization as only a limitation or a phenomenon to avoid, I study how partial synchronization and nonlinear laser dynamics can become useful computational resources. This allows the network to generate diverse but correlated responses to a common input, which may improve performance compared with independent single-laser reservoirs.
RESEARCH IMPACT
The aspect that excites me the most is that complex laser dynamics, which can look unstable or chaotic at first, can become a useful computational resource. It is fascinating that by tuning some parameters, a physical optical system can transform information in a way that is useful for machine learning tasks.
RESEARCH SUMMARY
My PhD investigates photonic reservoir computing based on networks of mutually coupled semiconductor lasers as physical nonlinear processors. In the experimental fibre-based platform, several lasers are all-to-all coupled through common optical feedback and are subject to external optical injection carrying infromation. The lasers' delayed, nonlinear, and partially synchronized dynamics provide both memory and computational diversity, essential components for reservoir computing. I experimentally characterise how parameters such as injection-frequency detuning, bias current, feedback strength, coupling, and synchronization shape the reservoir states and determine computing performance. The work combines high-speed measurements with high bandwidth, RF and optical spectral analysis, synchronization analysis, and benchmarking on information-processing tasks. The research question is whether a laser network can combine temporal multiplexing with spatial multiplexing to increase dimensionality and performance without simply lengthening the delay line. This could guide the design of fast, GHz-rate, scalable photonic reservoirs, including future integrated implementations for optical signal processing.
RESEARCH VISUAL
RESEARCH JOURNEY
RESEARCH SECONDMENT
VLC Photonics, Spain (2 months) & Aston University, United Kingdom (2 months)
During my secondments at VLC Photonics, Spain, and Aston University, United Kingdom, I will strengthen my expertise in integrated photonic technologies and their applications in optical computing and telecommunications. At VLC Photonics, I will receive advanced training in photonic integrated circuit (PIC) hybrid design and chip-level testing while exploring how proof-of-concept coupled laser networks can be translated into integrated photonic platforms. At Aston University, I will investigate the application of coupled laser-network transformations to telecom signal-processing tasks, connecting this approach with optical communication systems and gaining expertise in telecom-oriented signal processing.
LEARNING GOALS
I am most looking forward to being exposed to a diversity of perspectives. Similar to the lasers in my work, I believe that when my ideas interact with new research groups, they can generate richer responses than they would on their own. The combination of industrial and academic secondments makes this learning process special. I want to understand both how research questions are tackled in academia and how photonics technologies are developed, tested, and embedded in real-world applications in industry.
RESEARCH BENEFITS
The secondments will be complementary sources of expertise, facilities, and scientific perspectives. VLC Photonics will help connect my fibre-based experimental setup to future integrated photonic implementations, while Aston University will help link the coupled laser network concept to telecom-relevant signal-processing tasks.
CAREER DEVELOPMENT
My PhD and research will support my goal of building a stronger professional profile in photonics. I am constantly exposed to different ideas in photonics, benefit from working in an interdisciplinary and international research institute, and have the opportunity to develop hands-on experience in the lab. The secondments will strengthen this further: VLC Photonics will give me experience in PIC design and testing, while Aston will expose me to a broader range of research in photonics. These experiences will prepare me well for a future career in photonics.
MORE THAN PHD
Why did you decide to join POSTDIGITAL+ ?
POSTDIGITAL+ focuses on one of the key challenges of modern computing: developing faster and more energy-efficient processing beyond conventional digital architectures. It has a unique international environment connecting different fileds, such as photonics and AI, and different sectors, including academia, and industry.
What do you think is the biggest advantage of being part of the International Doctoral Network?
The sense of belonging to a larger international scientific community where different perspectives connect together for a common objective.
What skill have you developed the most so far?
What I have developed most is the way I approach research. I have strengthened my ability to plan experiments, troubleshoot technical issues, develop and test ideas, and decide on the next steps based on the results. I have also learned the importance of patience, as rigorous research often requires much more time, questioning, testing, iteration, and refinement than initially expected. The collaborative nature of the project has strengthened my ability to exchange perspectives and know when another point of view can be valuable. One thing I am still working on is balancing my tendency to focus on details with stepping back to see the bigger picture.
What are your career ambitions after completing your doctorate?
I would like to continue working at the intersection of photonics and neuromorphic computing, because this is the direction that excites me and also matches my skills and where technology is going. I see myself more in applied R&D, preferablly an environment where industry and academia are connected.
What inspired you to pursue this research Area?
I was inspired by the idea that something as complex as laser dynamics can become useful for computation. I liked the challenge of turning physical complexity into an information-processing resource.
What surprised you most since starting your PhD?
The biggest surprise was that how much work and refinement lies behind a single research result. What may look straightforward in a finished paper often requires repeated experiments, troubleshooting, many rounds of refinement, and reconsidering details.