Synopsys Photonic Solutions

Synopsys recently hosted the Optica PECC Summit, bringing together industry leaders to discuss advancements in photonic and optical technologies. Experts shared their groundbreaking work aimed at enabling faster and more power-efficient cloud computing environments. Learn more about the key takeaways: https://lnkd.in/gRetgZCm Did you join us that week? If so, let us know what you thought about the event below in the comments. Blog mentions: M. Ashkan Seyedi, NVIDIA Marco Fiorentino, Hewlett Packard Enterprise Thomas Liljeberg, Intel Corporation Karun Sharma and Manmeet Walia from Synopsys Inc #AI #Photonics #OpticalTechnology #TechSummit #Innovation #IndustryInsights #Synopsys #OpticaPECC #Optica

The shift to photonics for data center networks and AI is gaining momentum. As data demands grow, photonics offers a promising solution to enhance speed and efficiency. This technology leverages light for data transmission, potentially revolutionizing data centers and AI infrastructure. Read more about this exciting development in Laser Focus World: https://ow.ly/y7Hs50U2KCJ

We are proud to have participated in the JePPIX training held in Eindhoven on the topic of "Electronics and Photonics Chip Design." Attendees had hands-on training of our photonic solutions software for designing photonic integrated circuits. Check out how Synopsys OptoCompiler enables fast, accurate photonic IC development: https://lnkd.in/dJ6HSb4 https://lnkd.in/gSTFMJzN

A recent study published in Nature Photonics introduces a new approach to in-memory photonic computing using magneto-optic memory cells. Researchers have demonstrated the use of cerium-substituted yttrium iron garnet (Ce:YIG) integrated on silicon micro-ring resonators to encode optical weights. This method offers advantages such as fast programming speed (1 ns), high energy efficiency (143 fJ per bit), and robust endurance (2.4 billion programming cycles). This innovation aims to enhance the speed and energy efficiency of optical information processing for applications in artificial intelligence and machine learning. Read article: https://lnkd.in/gw7crTBE Citation: Figure 1 from Pintus, P., Dumont, M., Shah, V. et al. Integrated non-reciprocal magneto-optics with ultra-high endurance for photonic in-memory computing. Nat. Photon. (2024). https://lnkd.in/gqKMFw-K

Sandia National Laboratories and Arizona State University are collaborating to advance quantum technology by shrinking large optical systems into compact integrated microsystems. Led by physicist Nils Otterstrom, this effort focuses on miniaturizing optical systems to enhance performance and scalability, with applications in advanced computing and secure communications. The partnership has been formalized through a Cooperative Research and Development Agreement funded by the Quantum Collaborative, aiming to accelerate quantum information and technology research. Read more: https://lnkd.in/dGDXSdnb

Researchers at Tsinghua National University in Taiwan have developed the first room-temperature desktop quantum computer using photonics. Led by Professor Chu Zhisong, the system uses a single photonic qubit with 32 modes. This breakthrough could advance integration with silicon photonics and classical supercomputers, enhancing Taiwan's semiconductor technology. Learn more via eeNews Europe: https://lnkd.in/ghANjwjw

Researchers have made significant advancements in silicon photonic physical unclonable functions (PUFs) for enhancing security in optical communication networks. Published in Scientific Reports, the study details the design, fabrication, and evaluation of advanced PUFs using Contra-Directional Coupler (CDC) structures. These photonic PUFs generate unique identifiers by leveraging inherent physical variations, offering robust security without the vulnerabilities associated with electronic PUFs. The innovative design enhancements and experimental validation underscore the potential of CDC-based PUFs to provide secure key generation and authentication in modern optical communication systems. https://lnkd.in/gV5ihi3y Citation: Figure 2 is from Mahdian, M.A., Taheri, E., Rahbardar Mojaver, K. et al. Hardware assurance with silicon photonic physical unclonable functions. Sci Rep 14, 25591 (2024). https://lnkd.in/gWN9S_iG

This recent article discusses how 3D integrated photonics is accelerating computing by using photonic circuits to improve data processing speed and efficiency. This development represents a major step forward in overcoming the constraints of electronic systems. Full details here: https://lnkd.in/gyy-GGxP

A recent study from Newcastle University, published in Advanced Photonics Nexus, introduces a novel photonic computing method using electromagnetic waves to solve partial differential equations (PDEs) rapidly. This innovative approach leverages a network of waveguides filled with dielectric inserts, mimicking traditional circuit elements to offer fast and efficient solutions for complex equations. This advancement represents a significant step forward in analogue computing, providing new avenues for computational physics, mathematical modeling, and engineering applications. https://lnkd.in/gPcffhW7 Open Access Paper available via #SPIE Digital Library: https://lnkd.in/gBEZz5CT SPIE, the international society for optics and photonics

Researchers from the University of Pittsburgh Swanson School of Engineering, University of California, Santa Barbara (UC Santa Barbara), University of Cagliari, and Tokyo Institute of Technology (now Institute of Science Tokyo) have achieved a significant breakthrough in optical computing. They have developed a photonic memory solution that combines nonvolatility, multibit storage, high switching speed, low switching energy, and high endurance in a single platform. This innovation leverages magneto-optical materials to improve performance and efficiency, potentially transforming data processing and AI applications. https://lnkd.in/g2RwiPBN #Photonics #OpticalComputing #AI #DataProcessing #UniversityOfPittsburgh #UCSB #UniversityOfCagliari #TokyoInstituteOfTechnology