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Meta-optics and nano-optics are rapidly advancing, promising to revolutionize photonics systems and commercial applications, surpassing the limits of traditional optics. These materials, especially metasurfaces, are able to manipulate light in unique ways, leading to smaller, more versatile optical devices. Companies like Apple, Google, and Samsung are investing heavily in this field, aiming to integrate metaoptics into consumer electronics for improved imaging, authentication, and telecommunications.

The excitement around metaoptics stems from their potential to offer unprecedented control over light, enabling compact and versatile optical devices applicable across various sectors. Collaboration between physics, materials science, electrical engineering, and optics researchers is driving innovation in this area. Furthermore, the need to assess and validate the quality of metaoptics and metasurfaces presents opportunities for companies specializing in metrology.

While research groups have achieved significant progress and functional prototypes, the focus is shifting to mass production. Metaoptics, being compatible with CMOS fabrication techniques used for chip manufacturing through deep-ultraviolet lithography, are attracting major chip foundries. Companies like Metalenz, Moxtek, and NIL Technology are already producing metalenses with applications in polarization imaging, microscopy, and biosensing.

Researchers are actively developing innovative applications. For instance, polarization-sensitive cameras using metasurfaces, pioneered by Federico Capasso’s team at Harvard University, are being utilized in NASA projects and have led to Metalenz’s Polar ID for secure facial authentication. These cameras are more compact and efficient than traditional polarization cameras.

The unique properties of metaoptics, such as structural birefringence, are key to these advancements, allowing for polarization control without traditional birefringent materials. Semiconductor firms like STMicroelectronics are partnering with metaoptics companies for applications like facial recognition lidar in smartphones, and companies like Tunoptix are developing metalens designs for various camera applications.

Moxtek, a company with 25 years of experience in nano- and micro-optics, is mass-producing 1D periodic nanostructured metaoptic gratings using nanoimprint replication, highlighting the increasing manufacturability of these components. They are expanding production to meet the demand for emerging metaoptic designs.

Critical to the success of metaoptics is metrology, not only for final validation but throughout the design and manufacturing process. However, metrology for metaoptics presents challenges due to the nanoscale features. Traditional methods may not be sufficient to accurately assess these materials’ complex functionalities.

Metrology tool developers are responding to this need, creating tools specifically for metaoptics characterization. While research-grade tools are becoming available, enhancing test speed is crucial for high-volume production. Automated, in-situ, and real-time quality control is necessary to detect defects efficiently during mass production.

Key advancements in metrology include enhanced resolution, real-time in-situ monitoring suited for production environments, and scalability to handle large surface areas and volumes. Companies like Moxtek are upgrading to higher-volume measurement tools from TRIOPTICS.

Metaoptics are also contributing to advancements in metrology itself. Their unique characteristics require specialized metrology approaches, such as measuring focusing efficiency and higher-order focal spot information. Techniques using spectrally filtered light and scattering screens are being employed to characterize metalenses and other meta-elements.

Metasurfaces are also finding use in interferometry, where differences in diffraction patterns reveal phase changes induced by the metasurface. PHASICS Corp. offers interferometric systems designed for in-situ metaoptics measurements, suitable for use near manufacturing lines.

The increasing demand for compact and precise optical components is driving the integration of nanophotonics and metaoptics into industrial metrology. Polarization-based optical metrology could benefit from improved metasurface-based polarization components. Moreover, the semiconductor industry, already utilizing diffraction gratings for precise overlay metrology, is a natural fit for adopting metasurfaces as metrology targets due to material compatibility and potential for enhanced accuracy and smaller feature sizes.

Experts emphasize the need for greater industry awareness of the potential of metasurfaces and nanophotonics in advanced optical metrology. They also highlight the importance of national metrology institutes in supporting this development. Collaboration between academia and industry is crucial to tailor metasurfaces for specific metrology applications.

While challenges remain in scaling up production and adapting metrology techniques to industrial volumes, researchers believe that existing metrology methods can be enhanced to meet the needs of metaoptics characterization. Harnessing the unique capabilities of metasurfaces themselves can further improve metrology accuracy beyond traditional optics.

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Deepnight, a startup founded by former Google software engineers Lucas Young and Thomas Li, is tackling the challenge of digital night vision technology for the U.S. military. Traditional night vision goggles, which rely on analog technology using optical lenses and chemical processes, can cost between $13,000 to $30,000 per unit from defense contractors. The U.S. Army has been striving to digitize night vision for years, with initiatives like the multi-billion dollar Integrated Visual Augmentation System (IVAS) project.

Young, specializing in computational photography, and Li, with expertise in AI and computer vision, realized a software-based approach could revolutionize night vision. Inspired by a 2018 research paper on AI for low-light imaging, Young recognized that advancements in AI chips on System on Chips (SoCs) now made real-time, 90 frames per second AI-powered night vision feasible.

Leaving their positions at Google, Young and Li established Deepnight and joined the Y Combinator program. To demonstrate their concept’s viability to the U.S. Army, they developed a night vision smartphone application and showcased it using a VR headset. This initial demonstration and a white paper outlining their software-centric approach led to a $100,000 contract from the Army in February 2024, just a month into Y Combinator.

Following further successful demonstrations in Washington D.C., Deepnight secured additional contracts. Within a year of its launch, the startup has accumulated approximately $4.6 million in contracts from federal entities, including the U.S. Army and Air Force, as well as companies such as Sionyx and SRI International.

Deepnight’s innovative approach has also attracted significant investor interest. After completing Y Combinator, the company raised $5.5 million in a funding round led by Initialized Capital, with participation from angel investors including Vladlen Koltun, the scientist whose research paper inspired Deepnight’s technology.

Deepnight’s technology is software-based and designed to integrate with various hardware platforms, from goggles to helmets. By utilizing readily available and inexpensive smartphone camera technology, Deepnight aims to make advanced night vision accessible across diverse sectors including automotive, security, drones, and maritime applications.

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Cimbria, a leader in industrial processing solutions, has launched BRAIN, a new software control system for its optical sorters. This advanced system, powered by artificial intelligence, is designed to streamline the creation of complex sorting recipes and boost efficiency in optical sorting processes by up to 18%. BRAIN simplifies the operation of Cimbria’s optical sorters by leveraging AI to combine human input with machine learning. This synergy enhances the precision of raw material sorting, leading to more effective results. According to Michela Pelliconi, head of sales for optical sorting at Cimbria, BRAIN revolutionizes the operation of their top-tier optical sorters. She emphasized that the software incorporates years of Cimbria’s experience and knowledge to automatically optimize settings for superior sorting outcomes, reducing manual adjustments. The sophisticated algorithm within BRAIN software allows the SEA.IQ PLUS optical sorter to more accurately identify and differentiate elements based on color, shape, size, and defects, resulting in time savings and reduced manual workload. Technical staff will find machine operation simplified with AI-generated recipes, minimizing the need for subjective interpretation, leading to faster and simpler workflows. This enhanced system also enables operators to manage multiple machines and sites more effectively. Cimbria highlights its position as a global leader in industrial processing, handling, and storage solutions for cereals, seeds, animal feed, food, and other bulk materials. The company states that BRAIN is built upon its extensive market expertise and long-term experience in optimal sorting processes, ensuring high-quality end products. Pelliconi noted that AI is becoming essential in global business in 2024, and Cimbria is proud to be the first in their industry to introduce AI’s benefits. She added that the launch of BRAIN is considered a first step into the vast potential of AI, with a primary focus on enhancing efficiency and quality for their customers.

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Photonic integrated circuits (PICs) are emerging as a transformative technology for computation and data transmission, offering enhanced scalability and efficiency over traditional electronic circuits. These PICs are particularly vital for next-generation data centers grappling with the exponential surge in data demands driven by advancements in artificial intelligence, 5G, and high-performance computing which are straining current copper interconnects and energy consumption. Optical interconnects, particularly co-packaged optics (CPO), are viewed as a solution, integrating electronic and photonic components to boost bandwidth density and reduce power usage. Ansys, a company with existing electronic and semiconductor design tools, is expanding its capabilities to better integrate with photonic simulation, aiming to streamline CPO system design.

Furthermore, the article highlights the growing importance of system miniaturization and the role of metalenses or metasurfaces. These nanopatterned, flat lenses can combine functionalities and overcome limitations of traditional lens curvature, attracting interest from companies like Lumotive, which is developing liquid-crystal metasurfaces for LiDAR applications.

Optical design software development is also concentrating on improving user experience and efficiency. Ansys is reportedly leveraging GPUs and cloud computing to accelerate simulations, citing examples of up to 60x reduction in simulation time using GPUs versus standard CPUs. The need to bridge the gap between idealized models and real-world optical devices is also addressed. Ansys emphasizes design for manufacturing, introducing features like “composite surface” to account for fabrication variations and surface imperfections. They are also incorporating the impact of external factors such as vibrations and temperature through integration with tools like Ansys Mechanical and OpticStudio, enabling simulation of real-world scenarios like gravitational effects on satellite optical components. The future of optical design software development, according to the article, is driven by customer feedback and anticipating future industry needs to facilitate the creation of next-generation optical products.

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Fingerprint scanners are now a widely adopted security feature, integrated into devices ranging from smartphones to tablets. These biometric sensors have evolved significantly, becoming more sophisticated in capturing and verifying fingerprints for device unlocking and authentication.

One prevalent type is the optical fingerprint scanner, the earliest form of this technology used in smartphones. Optical scanners function by taking a digital photograph of the fingerprint. The sensor illuminates the finger and captures the reflected light, creating an image that algorithms then analyze to identify unique patterns like ridges and lines. However, due to their 2D image capture, optical scanners have been identified as less secure and susceptible to being fooled by high-quality images or prosthetics. To enhance security, hybrid solutions combining optical and capacitive technologies have become more common.

Capacitive fingerprint scanners offer enhanced security and are frequently found in contemporary devices. These scanners employ arrays of miniature capacitor circuits. Instead of capturing an image, they map the fingerprint by measuring the changes in electrical charge when a finger is placed on the sensor’s conductive plates. Ridges in a fingerprint create capacitance changes, while air gaps do not, allowing for a detailed digital representation to be created. This method offers improved security over optical scanners as it’s harder to replicate through images or prosthetics, although hardware or software hacking remains a potential vulnerability.

Ultrasonic fingerprint scanners represent the latest advancement in fingerprint scanning technology for smartphones. Utilizing ultrasonic waves, these scanners transmit a pulse against the finger. A portion of the pulse is absorbed, while the rest is reflected back to the sensor. By measuring the intensity of the returning pulses, the sensor constructs a detailed 3D map of the fingerprint, capturing ridges, pores, and unique fingerprint characteristics. This 3D mapping makes ultrasonic scanners the most secure type currently available. Despite offering superior security, ultrasonic scanners were initially perceived as slightly slower compared to other types, though advancements are being made to improve their speed.

In-display fingerprint scanners, which are integrated beneath the device screen, can utilize both optical-capacitive and ultrasonic technologies. Optical-capacitive in-display scanners function by detecting light reflected from the fingerprint through the gaps in OLED displays. Ultrasonic in-display scanners, on the other hand, transmit ultrasonic waves through the display to read the fingerprint. While both are used for in-display implementations, ultrasonic scanners are typically found in premium devices, while optical-capacitive scanners are more common in a wider range of smartphones, including mid-range models.

Beyond the sensor technology, the security and performance of fingerprint scanners also depend on associated components and software. A dedicated integrated circuit (IC) processes the raw data from the scanner and transmits it to the phone’s main processor. Manufacturers employ unique algorithms to analyze fingerprint data, focusing on identifying distinctive features known as minutiae, such as ridge endings and bifurcations. This approach enhances matching speed and accuracy while also allowing for successful recognition even with partial or smudged prints.

To ensure data protection, fingerprint information is typically stored securely within the device’s hardware. ARM processors utilize TrustZone technology, creating a Trusted Execution Environment (TEE) to isolate sensitive biometric data. Some devices, like Google Pixel phones, incorporate dedicated security chips such as the Titan M2, further bolstering hardware security. This secure enclave principle, also known as Secure Enclave by Apple and Secure Processing Unit (SPU) by Qualcomm, prevents unauthorized access to fingerprint data by apps or the main operating system.

The FIDO Alliance has developed protocols leveraging these secure hardware environments to enable secure, password-less authentication. Using FIDO protocols, users can authenticate online services using their fingerprint without transmitting actual biometric data. Instead, secure digital keys are exchanged for authentication.

Fingerprint scanners have become a critical component of modern device security. Their continued evolution towards increased speed, enhanced security, and seamless integration into device designs suggests they will remain an essential security feature for the foreseeable future, particularly with the growth of secure mobile payments and the ongoing need for robust user authentication methods.

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Researchers have successfully demonstrated the behavior of simulated analog opto-electronic neuromorphic devices, utilizing tools previously developed for modeling these systems. The devices, modeled using VerilogA and compatible with SPICE models and Spectre simulators, are crucial for simultaneously simulating photonic and electronic effects, essential due to the fundamentally opto-electronic nonlinearity at play.

Simulations show that the timing and intensity of input pulses significantly alter the output response of the resonator neuron within the device. Specifically, the device reacts differently to single or double pulses depending on the spacing between the pulses in relation to the resonant period. Two pulses spaced half a resonant period apart can cancel each other out, preventing the system from reaching its threshold. Conversely, pulses spaced a full resonant period apart amplify the output signal, pushing the system past the threshold. This timing sensitivity allows the neurons to encode temporal information from inputs, potentially beneficial for tasks requiring coincidence detection and timing-based learning mechanisms.

The neuron’s behavior also varies with pump power. At lower pump power, the neuron is monostable, returning to a resting state after excitation. However, at higher pump power, the neuron exhibits bistability, maintaining a spiking state even without input. Returning to a resting state in this bistable regime necessitates a precisely timed pulse.

Further experiments revealed that the neuron can be excited by strong inhibitory signals due to the nature of its threshold as an unstable limit cycle. This is significant because the device outputs negative spikes relative to its DC operating point.

The research also explored the neuron’s response to constant excitation. Under sufficient constant input power, the neuron enters a self-pulsating state. Varying the input power demonstrated that the device operates as a Class 2 excitable system. This classification is characterized by an abrupt shift in spike rate from zero to a substantial value as the threshold is crossed, indicating a subcritical Hopf bifurcation. The system also displays bistability within a specific input power range.

Furthermore, the study explicitly demonstrated the neuron’s frequency preference. The device shows resonant spiking behavior, with output amplitude significantly enhanced when the input frequency matches the neuron’s natural spiking rate. The resonance peak broadens with higher input amplitudes, suggesting that sufficiently strong off-resonance signals can still trigger spiking.

Crucially, the researchers demonstrated the cascadability of these neurons, a critical requirement for building neural networks. On-resonance signals experience regenerative gain, allowing them to propagate through multiple layers of neurons. Off-resonance signals, representing noise or unwanted signals, diminish as they pass through successive layers. The researchers successfully cascaded ten spiking neurons, showing that the output of one neuron can effectively drive the next, proving the potential for building complex neural networks with these devices.

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Azthena, a content platform, has issued a notice to its users regarding the nature of its answers and data handling practices. While Azthena states that it utilizes edited and approved content, the platform cautions users that responses may occasionally be inaccurate and recommends verifying information with relevant suppliers or authors. Specifically addressing health-related queries, Azthena explicitly clarifies that it does not offer medical advice and urges users to seek counsel from qualified medical professionals for any health concerns. In terms of data privacy, user questions, excluding email addresses, will be shared with OpenAI and retained for a period of 30 days, according to OpenAI’s privacy policies. Azthena also advises users against submitting questions that involve sensitive or confidential details. For comprehensive details, users are directed to the full Terms & Conditions document available via a provided link.

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Richard Gale Optics Clavius lens sets are now available for shipping. The lens sets, which include 28mm, 38mm, 58mm, and 88mm focal lengths, all feature a matched 58/2 MMZ optical block dating back to approximately 1971. Each lens in the set is T2 and equipped with a stainless PL mount, compatible with PL-EOS adapters.

Key features of the Clavius lenses include full frame coverage, historic optical elements with single layer MgF2 coatings, classical lower contrast rendering, and a high responsiveness to flaring. They also boast interchangeable aperture disks allowing for effects like ovals, soft focus, defocus distortion, and apodisation, along with unorthodox optical designs and a consistent f/2.0 aperture across the range.

Recent improvements have been made to the Clavius lenses, now featuring internal focusing, a relocated focus ring for better camera body clearance, and a geared aperture ring. While maintaining the same optical design as previous versions, the updated sets include a greater selection of waterstop aperture disks. Richard Gale Optics also announced they are developing a 138mm/2 lens and a wide angle attachment for the 28mm/2 lens, with details to be confirmed.

The lenses utilize optical elements from the Minsk plant of the 1970s, known for single-layer MgF2 anti-reflective coatings and refined optical processing, aiming to deliver vintage characteristics with good optical performance. The lenses are designed to create organic, characterful images free from unwanted color aberrations, appealing to users seeking historic glass aesthetics in their workflow.

According to Richard Gale Optics, the lenses utilize proprietary front-mounted spherical lens cells to achieve the different focal lengths, all while preserving the rendering, bokeh, and flare characteristics from the central 58/2 optical block. The Clavius lens sets are listed on the Richard Gale Optics website and are available for worldwide shipping, potentially as early as Monday this week, with a retail price of £15,250.00.

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Eindhoven-based Morphotonics, a nanoimprinting technology solutions company, has announced the initial closing of its Series B financing round, securing over $10 million, equivalent to approximately €9 million. This funding marks the company’s 10th anniversary, with a second closing anticipated before the year’s end. The funding round saw participation from new investors 3M and BOM (Brabant Development Agency), alongside existing investor Innovation Industries, with BOM and Innovation Industries jointly leading the investment.

Morphotonics specializes in large-area nanoimprint technology, notably its Roll-to-Plate (R2P) technology, designed to revolutionize display technology and enhance visual experiences. The company’s technology aims to advance 3D displays, improve the accessibility of Augmented Reality (AR) smart glasses, and contribute to more energy-efficient solutions for mobile devices. Morphotonics’ technology facilitates the creation of advanced products such as high-performance mobile screens, outdoor-readable smartphones, and immersive AR smart glasses by enabling the precise addition of intricate structures to surfaces like glass and foils at scale.

The company states its technology is currently used by major customers across Europe, the US, and Asia. Prior to this funding round, Morphotonics was awarded a European Innovation Council (EIC) Accelerator Grant in June 2023. The newly acquired capital is intended to facilitate the company’s operational scaling, expand its international customer base, particularly in Asia, and establish its large-area nanoimprinting technology as a standard within display optics production.

Company CEO and co-founder, Jan Matthijs ter Meulen, highlighted the impending growth in applications such as glasses-free 3D displays and Smart AR Glasses, emphasizing that the funding will strengthen the company’s market and technical leadership and broaden its impact across both consumer electronics and display markets.

Investors include 3M Ventures, the corporate venturing arm of 3M Company; BOM (Brabant Development Agency), an agency focused on regional innovation and development in Brabant and backed by the Province of Brabant and the Ministry of Economic Affairs; and Innovation Industries, a European deep tech venture capital firm managing over €850 million, which invests in deep tech companies addressing global challenges.

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