Advancements in Photonic System Technologies

Using light as a neural network, as this viral video depicts, is actually closer than you think. In 5-10yrs, we could have matrix multiplications in constant time O(1) with 95% less energy. This is the next era of Moore's Law. Let's talk about Silicon Photonics... The core concept: Replace electrical signals with photons. While current processors push electrons through metal pathways, photonic systems use light beams, operating at fundamentally higher speeds (electronic signals in copper are 3x slower) with minimal heat generation. It's way faster. While traditional chips operate at 3-5 GHz, photonic devices can achieve >100 GHz switching speeds. Current interconnects max out at ~100 Gb/s. Photonic links have demonstrated 2+ Tb/s on a single channel. A single optical path can carry 64+ signals. It's way more energy efficient. Current chip-to-chip communication costs ~1-10pJ/bit. Photonic interconnects demonstrate 0.01-0.1pJ/bit. For data centers processing exabytes, this 200x improvement means the difference between megawatt and kilowatt power requirements. The AI acceleration potential is revolutionary. Matrix operations, fundamental to deep learning, become near-instantaneous: Traditional chips: O(n²) operations. Photonic chips: O(1) - parallel processing through optical interference. 1000×1000 matmuls in picoseconds. Where are we today? Real products are shipping: — Intel's 400G transceivers use silicon photonics. — Ayar Labs demonstrates 2Tb/s chip-to-chip links with AMD EPYC processors. Performance scales with wavelength count, not just frequency like traditional electronics. The manufacturing challenges are immense. — Current yield is ~30%. Silicon's terrible at emitting light and bonding III-V materials to it lowers yield — Temp control is a barrier. A 1°C change shifts frequencies by ~10GHz. — Cost/device is $1000s To reach mass production we need: 90%+ yield rates, sub-$100 per device costs, automated testing solutions, and reliable packaging techniques. Current packaging alone can cost more than the chip itself. We're 5+ years from hitting these targets. Companies to watch: ASML (manufacturing), Intel (data center), Lightmatter (AI), Ayar Labs (chip interconnects). The technology requires major investment, but the potential returns are enormous as we hit traditional electronics' physical limits.

Researchers from Columbia University and Cornell University recently reported a 3D-photonic transceiver that features 80 channels on a single chip and consumes only 120fJ/bit from its electro-optic front ends. The #transceiver achieves low energy consumption through low-capacitance 3D connections between photonics and co-designed #CMOS electronics. Each channel has a relatively low data rate of 10Gbps, allowing the transceiver's electronics to operate with high sensitivity and minimal energy consumption. The large array of channels compensates for the low per-channel data rates, delivering a high aggregate data rate of 800Gbps in a compact transceiver area of only 0.15mm2 (@5.3Tbps/mm2). In addition, having many low-data-rate channels relaxes signal processing and time multiplexing of data streams native to the processor. Furthermore, wavelength-division-multiplexing (#WDM) sources for numerous data streams are becoming available with the advent of chip-scale microcombs. The EIC is bonded to the PIC based on a 15μm spacing and a 10μm bump diameter (@25μm pitch) in an array of 2,304 bonds. This process mitigates two potential failure risks: 1) excessive tin causing flow and electrical short to adjacent bonds and 2) insufficient tin leading to brittle bonds. 👇Figure 1: a) An illustration of the 3D-integrated photonic-electronic system combining arrays of electronic cells with arrays of photonic devices. b) A microscope image of the 80-channel photonic device arrays with an inset of two transmitter and two receiver cells. c) Microscope images of the photonic and electronic chips. The active photonic circuits occupy an area outlined in white, while the outer photonic chip area is used to fan out the optical/electrical lanes for fiber coupling and wire bonding. The blue overlay shows a four-channel transmitter and receiver #waveguide path; the disk and ring overlays are not to scale. An inset shows a diagram of the fiber-to-chip edge coupler, consisting of a silicon nitride (Si3N4) inverse taper and escalator to silicon. d) A scanning electron microscope image of the bonded electronic and photonic chip cross-section. e) An image of the wire-bonded transceiver die bonded to a printed circuit board and optically coupled to a fiber array with a US dime for scale. f) A cross-sectional diagram of the electronic and photonic chips and their associated material stacks. Both chips consist of a crystalline silicon substrate, doped-silicon devices and metal interconnection layers. Daudlin, S. et al. Three-dimensional photonic integration for ultra-low-energy, high-bandwidth interchip data links. Nat. Photon. (2025).👉https://lnkd.in/gpeVGZna #SemiconductorIndustry #Semiconductor #Semiconductors #AI #HPC #Datacenter #Optics #Photonics #SiliconPhotonics #Optical #Networking #OCI #Ethernet #Infrastructure #Interconnect #CloudAI #AICluster AIM Photonics TSMC Defense Advanced Research Projects Agency (DARPA) #FiberCoupling #SiP

Programmable photonic integrated circuits are expected to play an increasingly important role in enabling high-bandwidth optical interconnects and large-scale in-memory computing as needed to support the rise of artificial intelligence and machine learning technology. To that end, chalcogenide-based non-volatile phase-change materials (PCMs) present a promising solution due to zero static power. They, for the first time, can truly enable "set and forget" functionality. However, high switching voltage and a small number of operating levels present serious roadblocks to the widespread adoption of PCM-programmable units. In this paper, published in APL Photonics, we demonstrate an electrically programmable wide bandgap SbS-clad silicon ring resonator using a silicon microheater at a complementary-metal–oxide–semiconductor compatible voltage of <3 V. Our device shows a low switching energy of 35.33 nJ (0.48 mJ) for amorphization (crystallization) and reversible phase transitions with high endurance (>2000 switching events) near 1550 nm. Combining a volatile thermo-optic effect with non-volatile PCMs, we demonstrate 7-bit (127 levels) operation with excellent repeatability and reduced power consumption. Our demonstration of low-voltage and low-energy operation, combined with the hybrid volatile–nonvolatile approach, marks a significant step toward integrating PCM-based programmable units in large-scale optical interconnects.

OPTICALLY TUNABLE QUANTUM ENTANGLEMENT VIA NONLINEARITY SYMMETRY BREAKING IN METASURFACES Tunable quantum entanglement refers to the ability to actively control the properties of entangled quantum states, including polarization, spatial mode, spectral bandwidth, or time-bin—in real time. This goes beyond static entanglement, enabling adaptive quantum systems that respond to environmental changes, user input, or computational demands. Recent breakthroughs have enabled dynamic control over quantum entanglement using a range of advanced photonic architectures. Asymmetric nonlinear metasurfaces, based on nanostructured InGaP, allow tunability of entangled photon states by breaking rotational symmetry in nonlinear polarization, adjusting the pump wavelength directly influences the generated entanglement. Similarly, nonlinear waveguide arrays composed of continuously coupled semiconductor structures provide spatial entanglement control by modulating photon interactions along the propagation axis. While spontaneous parametric down-conversion (SPDC) remains a practical route for photon-pair generation at room temperature, the tunability of entangled quantum states has been fundamentally constrained by the symmetry properties of conventional nonlinear materials. Recent efforts leveraging flat optics and metasurfaces have pushed the boundaries of integration and ultracompactness, yet quantum tunability in polarization, spectral, and spatial domains has remained limited. The new paradigm based on controlling asymmetric nonlinear optical responses within resonant InGaP metasurfaces was evaluated experimentally. By engineering nanostructures that break rotational symmetry, we demonstrate dynamic manipulation of the nonlinear polarization tensor, enabling broadband control over second harmonic generation (SHG) and SPDC processes. This mechanism allows the generation of polarization-entangled photon pairs across a wide tunable range, from partially entangled states to maximally entangled Bell states, via pump wavelength control. Spatial anti-correlations further validate the platform’s ability to produce hyperentangled states in polarization and spatial degrees of freedom. InGaP metasurfaces exhibit record-high SPDC rates and coincidence-to-accidental ratios (CAR) at infrared telecommunication wavelengths, outperforming conventional bulk crystal sources in functionality. Moreover, the integration of phase-change materials or liquid crystals offers pathways for dynamic resonance control, potentially enabling ultrafast entanglement switching, wavelength- and time-division multiplexing, and tunable multiphoton states. Combined with III–V semiconductor laser, modulator, and detector platforms, these metasurfaces set the stage for monolithically integrated, ultracompact, and multifunctional quantum photonic chips. # https://lnkd.in/eubcsGVV

𝗙𝗿𝗼𝗺 𝗕𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 𝘁𝗼 𝗕𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵: 𝗛𝗼𝘄 𝗣𝗵𝗼𝘁𝗼𝗻𝗶𝗰𝘀 𝗜𝗻𝘁𝗲𝗿𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝘀 𝗮𝗿𝗲 𝗥𝗲𝘄𝗶𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜 & 𝗗𝗮𝘁𝗮 𝗖𝗲𝗻𝘁𝗲𝗿𝘀 The future of AI and high-performance computing won’t be defined by silicon alone. 𝗔𝘀 𝗺𝗼𝗱𝗲𝗹𝘀 𝘀𝗰𝗮𝗹𝗲, 𝗺𝗼𝘃𝗶𝗻𝗴 𝗱𝗮𝘁𝗮—𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗰𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴—𝗵𝗮𝘀 𝗯𝗲𝗰𝗼𝗺𝗲 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 𝗳𝗼𝗿 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿𝘀. The limits of copper wires are now holding back bandwidth, power efficiency, and ultimately, AI’s progress. 𝗖𝘂𝗿𝗿𝗲𝗻𝘁 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀  • 𝗘𝘀𝗰𝗮𝗹𝗮𝘁𝗶𝗻𝗴 𝗽𝗼𝘄𝗲𝗿 𝘂𝘀𝗮𝗴𝗲: High-speed electrical I/O burns enormous power, especially as bandwidth demands rise.  • 𝗕𝗮𝗻𝗱𝘄𝗶𝗱𝘁𝗵 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸𝘀: Copper wires face a ceiling for how much data they can carry, with signal degradation and crosstalk worsening at higher speeds.  • 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 & 𝘀𝗰𝗮𝗹𝗶𝗻𝗴: Traditional interconnects add latency, and scaling to larger multi-chip or multi-rack systems often requires even more energy and complex routing. 𝗣𝗵𝗼𝘁𝗼𝗻𝗶𝗰𝘀: 𝗧𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 #Photonics - using light instead of electricity to move data—offers a path to break through these barriers:  • 𝗨𝗹𝘁𝗿𝗮-𝗵𝗶𝗴𝗵 𝗯𝗮𝗻𝗱𝘄𝗶𝗱𝘁𝗵: Photonic links deliver terabits per second between chips, boards, and racks.  • 𝗟𝗼𝘄𝗲𝗿 𝗽𝗼𝘄𝗲𝗿 𝗽𝗲𝗿 𝗯𝗶𝘁: Photonics reduces wasted energy as heat, enabling higher density and sustainability.  • 𝗟𝗼𝗻𝗴𝗲𝗿 𝗿𝗲𝗮𝗰𝗵, 𝗹𝗼𝘄𝗲𝗿 𝗹𝗮𝘁𝗲𝗻𝗰𝘆: Optical signals maintain integrity over longer distances, crucial for modular and disaggregated architectures. 𝗞𝗲𝘆 𝗛𝘂𝗿𝗱𝗹𝗲𝘀 𝗳𝗼𝗿 𝗠𝗮𝗶𝗻𝘀𝘁𝗿𝗲𝗮𝗺 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻  • 𝗖𝗠𝗢𝗦 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Integrating lasers, modulators, and photodetectors with silicon is still complex.  • 𝗣𝗮𝗰𝗸𝗮𝗴𝗶𝗻𝗴 & 𝘆𝗶𝗲𝗹𝗱: High-precision assembly is required; small misalignments can hurt performance and scale-up.  • 𝗧𝗵𝗲𝗿𝗺𝗮𝗹 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: On-chip lasers and drivers add new thermal challenges.  • 𝗖𝗼𝘀𝘁 & 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺: Photonic components are costlier so volume manufacturing and mature standards are just emerging.  • 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲/𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Fully exploiting photonics requires new networking stacks, protocols, and sometimes rethinking system design. 𝗣𝗵𝗼𝘁𝗼𝗻𝗶𝗰𝘀 𝗶𝘀 𝗻𝗼 𝗹𝗼𝗻𝗴𝗲𝗿 𝗷𝘂𝘀𝘁 𝗮 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝘁𝗼𝗽𝗶𝗰—𝗶𝘁’𝘀 𝗻𝗼𝘄 𝘂𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝗻𝗲𝘄 𝗳𝗿𝗼𝗻𝘁𝗶𝗲𝗿𝘀 𝗶𝗻 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗳𝗼𝗿 #𝗔𝗜 𝗮𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 #𝗰𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴. The transition from electrons to photons is happening, but its tipping point will depend on integration, ecosystem, and system design breakthroughs. 𝗪𝗵𝗲𝗿𝗲 𝗱𝗼 𝘆𝗼𝘂 𝘀𝗲𝗲 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗵𝘂𝗿𝗱𝗹𝗲𝘀—𝗼𝗿 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀—𝗳𝗼𝗿 𝗽𝗵𝗼𝘁𝗼𝗻𝗶𝗰𝘀 𝗶𝗻 𝗿𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝗱𝗮𝘁𝗮 𝗺𝗼𝘃𝗲𝗺𝗲𝗻𝘁 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲? Hrishi Sathwane Tarun Verma Harish Wadhwa Dr. Satya Gupta

Integrated photonic optical switches have recently gained increased attention due to the growing interest in AI and the associated challenges of #AI data communication in #datacenter and #HPC systems. Our group has been active in this area, focusing on the development of novel #photonic switching elements, improved switch #topologies, and fast, scalable, performance-aware #reconfiguration solutions. To provide a comprehensive overview of the state-of-the-art, as well as highlight existing challenges and #research opportunities, we recently published an in-depth #survey on integrated photonic switch fabrics. The review covers photonic switching devices (including silicon photonics, III-V, MEMS, etc.), switch fabric topologies, tuning and reconfiguration mechanisms, and control planes and strategies for managing switch fabric operation. Kudos to my talented Ph.D. student, M.Amin Mahdian for his dedicated effort in putting together this comprehensive and valuable survey paper. Also, special thanks to #NSF for supporting this work. Enjoy! Link to the paper (open access): https://lnkd.in/gbi_dMhY #siliconphotonics #switch #network #interconnect #photonics #control #communication

Researchers have made a significant breakthrough in AI hardware with a 3D photonic-electronic platform that enhances efficiency and bandwidth, potentially revolutionizing data communication. Energy inefficiencies and data transfer bottlenecks have hindered the development of next-generation AI hardware. Recent advancements in integrating photonics with electronics are poised to overcome these challenges. 💻 Enhanced Efficiency: The new platform achieves unprecedented energy efficiency, consuming just 120 femtojoules per bit. 📈 High Bandwidth: It offers a bandwidth of 800 Gb/s with a density of 5.3 Tb/s/mm², far surpassing existing benchmarks. 🔩 Integration: The technology integrates photonic devices with CMOS electronic circuits, facilitating widespread adoption. 🤖 AI Applications: This innovation supports distributed AI architectures, enabling efficient data transfer and unlocking new performance levels. 📊 Practical Quantum Advancements: Unlike quantum entanglement for faster-than-light communication, using quantum physics to boost communication speed is more feasible and practical. This breakthrough is long overdue, but the AI boost might create a burning need for this technology. Quantum computing might be seen as a lot of hype, but using advanced quantum physics to enhance communication speed is more down-to-earth than relying on quantum entanglement for faster-than-light communications, which is short-lived #AI #MachineLearning #QuantumEntanglement #QuantumPhysics #PhotonicIntegration #SiliconPhotonics #ArtificialIntelligence #QuantumMechanics #DataScience #DeepLearning

NVIDIA, TSMC Develop Advanced Silicon Photonic Chip Prototype NVIDIA and TSMC reportedly developed a groundbreaking silicon photonics-based chip prototype at the end of last year, blending photonic circuits with traditional ones to tackle the limitations of semiconductor fabrication. Silicon photonics replaces electrons with photons for communication within chips, enabling faster data speeds and higher bandwidth without requiring ultra-advanced manufacturing techniques. This innovation comes alongside their work on optoelectronic integration and advanced packaging technologies, addressing critical constraints in AI chip performance, cost, and supply. As TSMC remains NVIDIA’s primary manufacturing partner, this collaboration underscores their push to overcome scaling challenges and redefine AI chip capabilities. My Take Silicon photonics can potentially redefine Moore’s Law for the AI era, focusing on architectural innovation rather than just transistor density. This shift could unlock new possibilities for edge computing and AI applications, driving unprecedented efficiency in data processing. Silicon photonics can deliver 10–50x higher bandwidth and up to 90% lower power consumption for data transfer. #NVIDIA #TSMC #SiliconPhotonics #AIChips #Semiconductors #AdvancedPackaging #Innovation #TechnologyLeadership Link to article: https://lnkd.in/eMTMcpD6 Credit: Wccftech This post reflects my own thoughts and analysis, whether informed by media reports, personal insights, or professional experience. While enhanced with AI assistance, it has been thoroughly reviewed and edited to ensure clarity and relevance. Get Ahead with the Latest Tech Insights!  Explore my searchable blog: https://lnkd.in/eWESid86

The future of AI isn't just about smarter algorithms, it's about reimagining the physical infrastructure that powers them While the industry focuses on the latest AI models, a fundamental shift is happening at the hardware level POET Technologies just announced a $25M strategic investment to accelerate their breakthrough in optical computing for AI systems Here's why this matters: Traditional AI systems are increasingly bottlenecked by the physics of moving data through copper interconnects POET's revolutionary POET Optical Interposer™ technology changes the game by enabling seamless integration of electronic and photonic devices into a single chip, solving bandwidth and latency problems that become critical as AI workloads scale exponentially The impact is significant: • Bandwidth: Optical interconnects carry vastly more data than electrical connections • Power efficiency: Photonic systems consume significantly less power for data transmission • Speed: Light-based communication eliminates delays inherent in electronic systems This isn't just incremental improvement, it's infrastructure transformation From chip-to-chip communication within AI servers to high-speed connections supporting 800G and 1.6T+ data rates, optical computing addresses the physical limitations that could otherwise constrain AI advancement The market validation is compelling too POET has raised over $100M in equity capital at increasingly higher prices over the past year, with strong interest from institutional and strategic investors recognizing the compelling value proposition for AI networks and systems As AI infrastructure spending explodes and organizations race to build more capable systems, the companies that recognize and invest in optical computing early will likely gain sustainable competitive advantages The physics of light create natural performance moats that can't be replicated through software optimization alone The next generation of AI won't just think differently, it will be built differently Read more: https://lnkd.in/gUzFK3RM #AI #OpticaIComputing #AIInfrastructure #TechInnovation #FutureOfAI #DataCenters #QuantumComputing #TechLeadership

𝐊𝐞𝐲 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐅𝐨𝐜𝐮𝐬 𝐢𝐧 𝐎𝐩𝐭𝐢𝐜𝐚𝐥 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 2024 2024 has been a transformative year for optical communications as vendors, engineers, and researchers pushed the boundaries of innovation. Their efforts focused on increasing transmission capacity, simplifying complex networks, enhancing security, and reducing both costs and power consumption. Here are five significant areas of progress: 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐎𝐩𝐭𝐢𝐜𝐚𝐥 𝐅𝐢𝐛𝐞𝐫𝐬: The industry made strides in spatial division multiplexing technologies, such as multicore and few-mode fibers, to boost capacity. Vendors like Sumitomo delivered multicore fibers specifically designed for undersea cable applications. 𝐒𝐩𝐞𝐜𝐭𝐫𝐚𝐥 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐚𝐧𝐝 𝐇𝐢𝐠𝐡𝐞𝐫 𝐁𝐚𝐮𝐝 𝐑𝐚𝐭𝐞𝐬: Efforts to enhance spectral efficiency by narrowing channel spacing and increasing channel counts in the C and L bands saw significant progress. The industry also achieved breakthroughs in higher baud rates, exemplified by CIENA's WaveLogic 6, capable of delivering single-carrier 1.6 Tb/s using 200 Gbaud technology. 𝐏𝐡𝐨𝐭𝐨𝐧𝐢𝐜 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐂𝐢𝐫𝐜𝐮𝐢𝐭𝐬 (𝐏𝐈𝐂𝐬): Development of PICs continued at a rapid pace to increase capacity while reducing power consumption and minimizing device footprints. 𝐀𝐈-𝐃𝐫𝐢𝐯𝐞𝐧 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐂𝐨𝐧𝐭𝐫𝐨𝐥: Innovations in integrating artificial intelligence into optical networking advanced dynamic control and optimization of optical networks. 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐊𝐞𝐲 𝐂𝐫𝐲𝐩𝐭𝐨𝐠𝐫𝐚𝐩𝐡𝐲: The field saw considerable activity in quantum key cryptography to enhance network security and protect data integrity. For a detailed overview of these innovations, check out our video highlighting the key advancements in optical communications this year. James Burris David Robles Dino DiPerna Takahiko Aoyama A https://lnkd.in/gBNb-sSF