Waterloo Researchers Create Precise Light Absorber for Quantum Tech

Underlying Framework of All-optical Controlled Synaptic Devices for Neuromorphic Computing Dunan Hu, Ruqi Yang, Zhizhen Ye & Jianguo Lu* Nano-Micro Lett. 18, 320 (2026). https://lnkd.in/g8Je__6w   This work is led by Prof. Dr. Jianguo Lu (Zhejiang University) and co-workers. Prof. Lu’s research centers on semiconductor thin films and optoelectronic devices, electrochemical energy storage and system integration, nanomaterials and smart coatings. This review articulates the framework and motivations for all-optical controlled (AOC) synaptic devices that use exclusively optical signals to emulate bidirectional synaptic weight modulation, bypassing the complexity and energy costs of electrical or electro-optical hybrid signals. It systematically summarizes current progress, highlighting synergistic relationships among physical mechanisms, material behaviors, device architectures, and neuromorphic computing based on optical writing/erasing, and proposes scalable design strategies. #AOC #synapse #neuromorphic #optical #AI

Great news from the SCTS ecosystem! Heriot-Watt University researchers have achieved a world-first breakthrough in controlling light, opening new possibilities for medical technologies, quantum computing and secure communications. ⬇️Read the full story. https://lnkd.in/d82n6-Rp

Monash researchers have built a fully integrated nanoscale circuit that can generate, steer and read light‑based information,  all on a single chip operating at room temperature. This breakthrough pushes valleytronics from theory toward real‑world technology. For the first time, one device can create special light signals, route them with precision, and convert them into electrical outputs, a complete on‑chip system. The work is significant because it represents: 🔵 a new pathway to faster, more energy‑efficient computing 🔵 scalable platforms for quantum and AI technologies 🔵 compact, programmable photonic devices using the valley degree of freedom   🔵demonstrated ability to process multiple images simultaneously. Led by Dr Chi Li, Dr Kaijian Xing and Dr Haoran Ren from the School of Physics and Astronomy with collaborators across Australia, Singapore, Germany and Japan, this work marks a major step toward practical, chip‑based quantum photonics. Read more: https://lnkd.in/gNQr7Y4g #MonashScience #PhysicsandAstronomy #QuantumTech

Next-generation photonic computing Physicists have developed hybrid light-matter particles that interact strongly enough to perform computation, marking a major step toward next-generation photonic computing. Eighty years after the invention of ENIAC by Penn researchers J. Presper Eckert and John Mauchly, electronic computing still relies heavily on electrons. However, electrons face growing limitations such as heat generation, resistance, and energy loss as modern chips become increasingly complex. To overcome these challenges, researchers led by Bo Zhen at the University of Pennsylvania are exploring photons the massless particles of light as an alternative for future computing technologies. Photons can transmit information rapidly over long distances with minimal energy loss, making them ideal for communication systems. However, because photons interact weakly with matter, they are not naturally suited for signal-switching operations required in computing. The research team addressed this limitation by creating exciton-polaritons, hybrid quasiparticles formed by coupling photons with electrons in an atomically thin semiconductor. These particles combine the speed of light with the strong interaction properties of matter, enabling efficient all-optical signal switching. This breakthrough could significantly impact artificial intelligence and photonic computing. Current photonic AI chips still rely on electronic conversions for nonlinear operations, reducing speed and efficiency. Using exciton-polaritons, the team demonstrated ultra-low-energy all-light switching at approximately 4 quadrillionths of a joule. If successfully scaled, this technology could: • Improve AI hardware efficiency • Reduce power consumption in large AI systems • Enable direct light-based data processing from cameras • Support future quantum computing applications on chips This advancement represents an important milestone in the transition from electronic to photonic computing technologies. Ref: Zhi Wang et al, Strongly Nonlinear Nanocavity Exciton Polaritons in Gate-Tunable Monolayer Semiconductors, Physical Review Letters (2026). DOI: 10.1103/gc15-qsvf #ArtificialIntelligence #AI #Photonics #PhotonicComputing #QuantumComputing #MachineLearning #DeepLearning #DataScience #ComputationalPhysics #Physics #Nanotechnology #Semiconductor #NextGenComputing #Innovation #Research #Science #Technology #FutureTech #OpticalComputing #Bioinformatics #Engineering #STEM #ScientificResearch #UniversityOfPennsylvania #ExcitonPolaritons

The latest paper from my research group is now published: https://lnkd.in/epQvBQnE This work used computational tools to study semiconductor quantum dots and how their properties change with composition. The results showed that even small changes can affect how they perform, which is important for their use in electronics, sensing, and advanced materials. #QuantumDots #Nanotechnology #MaterialsScience #Research #Innovation

According to professor Nakatsuji of the University of Tokyo "This new quantum switch means we can write and store data almost without consuming any active power."

There are billions of possible material combinations. We've explored hundreds. Not because researchers aren't brilliant. Because classical simulation can only see a fraction of the space. Battery materials. Semiconductors. Carbon capture compounds. The candidates that could redefine entire industries are out there. The bottleneck isn't chemistry. It's computation. Quantum simulation doesn't approximate atomic behavior, it models it natively, at the subatomic level where material properties are actually determined. At Qangles: 10,000+ material candidates tested in weeks. Not years. The next generation of materials isn't waiting to be synthesized. It's waiting to be simulated. Read more: https://qangles.ai/ #QuantumComputing ##QuantumComputing #MaterialsScience #MaterialDiscovery #ComputationalScience #QuantumSimulation #DeepTech

Researchers from Monash University have developed a breakthrough nanoscale circuit that can generate, direct, and read light-based information, all on a single chip. https://lnkd.in/etDwg6Q9

Come by for more learning at the IEEE presenation May 21 Seminar: Towards Optical Computing and Quantum Light Generation in Lithium Niobate and 2D Materials Thibault Chervy, Group Leader at NTT Research In-person attendance only. Register: Here     Cost: $4-6 Thurs May 21 11:30 am: Networking & Pizza 12:00 pm: Seminar Location: EAG Laboratories - 810 Kifer Road, Sunnyvale  Attendees will need to provide photo ID, and indicate citizenship Relentless growth in computational demand is eroding the historical divide between signal transmission and signal processing. Nonlinear optics, where strong, deterministic interactions couple optical signals together, has long promised to bridge this divide by performing computation directly in the optical domain. In this talk, I will present recent work from our group toward enabling such technologies on two emerging platforms: thin-film lithium niobate (TFLN) and 2D semiconductors. First, I will present a TFLN vertical-cavity architecture for squeezed-light generation and parallel signal processing. I will then introduce a low-temperature platform based on 2D transition metal dichalcogenides, in which quantum light is generated from a strongly interacting many-body ensemble of excitons. Together, these results illustrate how material development and engineered photonic environments can turn nonlinear and quantum optical phenomena into practical resources for the next generation of computing and communication hardware.    Design and function of a vertical micro-cavity optical parametric oscillator    Ultrafast optical gating in a nonlinear lithium niobate microcavity    Dipolar Interfacial Excitons in Lateral Semiconductor Heterostructures   Thibault Chervy's research lies at the interface between optics and complex materials. He confines photons within such materials to probe emergent optical phenomena, pursuing both fundamental insights and applications. Reciprocally, he investigates how engineering the electromagnetic environment can transform complex phases of matter themselves.

Heat is the bottleneck of modern technology. UVA researchers are helping remove it. A UVA Engineering–led team has published a new Nature Reviews Methods Primers article explaining time-domain thermoreflectance (TDTR)—a laser-based technique that measures temperature changes at picosecond time scales and nanometer length scales. As Patrick Hopkins, UVA’s Whitney Stone Professor of Engineering, puts it: “The limiting factor in all device designs right now is the heat.” From faster computing and generative AI to quantum devices and longer-lasting batteries, understanding how heat moves through materials at the smallest scales is essential. TDTR gives researchers that insight—and this primer will help expand its use across materials science, semiconductor research, and energy storage. The work also reflects the University of Virginia's strength in translating research to impact, including commercialization through Charlottesville-based Laser Thermal.