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A new study examines the Global Optical Simulation Software Market, projecting growth through 2029. The research segments the market by key regions and applications, drawing upon current trends and historical data. Leading companies in this sector, as identified in the study, include Zemax, Synopsys Optical Solutions Group, COMSOL, Lumerical, RSoft Design Group, Optis, VirtualLab Fusion, Ansys, LightTrans International, Photon Engineering, Radiant Zemax, Lambda Research Corporation, FRED Optical Engineering Software, Breault Research Organization, TracePro, LucidShape, ASAP-NextGen, CST Studio Suite, OPTIS SPEOS, GratingMOD, VPIphotonics, Goptical, WaveTrain Systems and Simphotek Inc.

The report highlights the increasing application of Optical Simulation Software in Aerospace and Defense, Automotive, Consumer Electronics, Energy, Healthcare, and Industrial Manufacturing. This expansion is driving market digitalization and improving industry efficiency. The study categorizes the software by type, including cloud-based and on-premises solutions.

Geographically, the research extensively covers APAC, Europe, North America, South America, and MEA regions, with detailed breakdowns of countries within each. The research analyzes market strategies employed by key players, such as new product development, joint ventures, and acquisitions, to navigate the current economic landscape. The report aims to provide a comprehensive view of the market, focusing on growth factors, opportunities, and challenges, while profiling key industry participants and their strategies.

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Tamron is developing a groundbreaking 50-200mm f/2.8 lens, a first-of-its-kind optic that promises a significant zoom range without sacrificing light-gathering capability. Patent documents filed in Japan reveal that this fast lens has been under development since at least 2022 and was recently granted this week.

According to the patent application, Tamron is responding to the growing mirrorless camera market’s demand for zoom lenses that offer a large zoom range, maintain a consistent aperture throughout that range, and minimize changes in weight distribution and length during zooming. The company emphasizes the inclusion of advanced corrective optics to minimize visual aberrations, aiming for optical performance comparable to professional 70-200mm f/2.8 lenses but with a wider field of view.

The design intends for minimal lens extension across the 50-200mm range, while maintaining optical quality at all focal lengths. Although the lens is expected to contain a substantial amount of glass, making it not “small,” Tamron aims for a more compact design than might be initially anticipated for such a lens specification.

The complexity of the optical formula is highlighted by comparison to existing Tamron zoom lenses with large ranges, such as the 50-300mm f/4.5-6.3 and the 70-180mm f/2.8, both of which have less intricate optical designs. The new 50-200mm f/2.8 design appears even more complex than Tamron’s praised 35-150mm f/2-2.8 lens, signaling a significant step forward in optical engineering.

This development, alongside Canon’s recent 24-105mm f/2.8 lens, illustrates a trend in the industry towards faster and lighter zoom lenses, enabled by the shift to mirrorless camera systems. The new Tamron lens is poised to further push the boundaries of zoom lens technology, offering photographers an unprecedented combination of versatility and performance.

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Dublin, Ireland – The optical design software market is poised for significant expansion in the coming years, according to a new report from ResearchAndMarkets.com. The market, valued at approximately $862.90 million in 2022, is projected to reach an estimated $1,388.37 million by 2030, growing at a compound annual growth rate of 6.45%.

This growth is largely attributed to the increasing demand for sophisticated optical systems across various sectors. Industries such as aerospace and defense, automotive, medical, and manufacturing are increasingly relying on high-quality modeling and analysis of optical systems, driving the need for advanced software solutions.

The report highlights that software solutions dominated the market in 2022, holding a 72.4% market share, and are expected to continue to lead with the highest CAGR of 6.63%. Within technology segments, 3DIC currently holds the largest market share at 24.5%, while applications in quantum dot technology are predicted to generate substantial revenue, exceeding $100 million by 2026.

Regionally, North America currently leads the market, accounting for 36.6% of the share in 2022, driven by strong technological advancements and diverse industrial applications. However, the Asia Pacific region is expected to experience rapid growth, with a projected CAGR of 7.14%, fueled by increasing technology investments and adoption across various industries.

Key players in the competitive landscape include companies like Ansys, Synopsys, and Lumerical, among others such as 3D Optix, AEH inc, and Zemax. These companies are contributing to innovation and market dynamism within the optical design software sector.

The findings suggest a strong and expanding market for optical design software, driven by the critical need for precise and efficient optical system design and analysis across a broad spectrum of industries globally.

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University of Michigan engineers have unveiled OptoGPT, a novel artificial intelligence tool designed to expedite and enhance the creation of optical materials. Leveraging the transformer neural networks at the core of large language models such as ChatGPT, OptoGPT can逆向工程 optical material recipes, starting from desired optical properties.

This innovative algorithm crafts designs for optical multilayer film structures – stacks of thin material layers – applicable to various technologies. These structures are vital for optimizing light absorption in solar cells, refining reflection in telescopes, improving extreme UV light semiconductor manufacturing, and developing smart windows for energy-efficient buildings.

OptoGPT achieves design generation in a remarkably swift 0.1 seconds. Moreover, its designs are streamlined, averaging six fewer layers than those from previous methods, simplifying manufacturing processes.

According to L. Jay Guo, University of Michigan professor of electrical and computer engineering, the traditional design of these structures demands significant expertise to pinpoint the optimal material combinations and layer thicknesses. OptoGPT automates this intricate process, utilizing a transformer architecture, similar to ChatGPT, but adapted for material design.

The algorithm treats materials and their thicknesses as linguistic elements, identifying correlations to predict design solutions that meet specific optical property targets, such as high reflection.

Validation testing against 1,000 known designs demonstrated OptoGPT’s accuracy, with a mere 2.58% difference. Fine-tuning further refines accuracy to 1.92%. Researchers emphasize OptoGPT’s broad applicability, offering a flexible solution for diverse optical design challenges across fields.

Statistical analysis of OptoGPT’s neural network reveals material clustering based on type, such as metals and dielectrics, validating the model’s optical logic. This inverse design algorithm provides a more adaptable approach compared to task-specific predecessors, empowering researchers and engineers to innovate across a wide spectrum of optical applications.

The project is partly funded by the National Science Foundation.

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University of Michigan engineers have created a new algorithm called OptoGPT, designed to develop optical multilayer film structures for various applications, including solar cells. OptoGPT leverages the same computer architecture as the popular ChatGPT and works in reverse, determining the material structure necessary to achieve specific optical properties. This innovative algorithm can produce designs for multilayer film structures in just 0.1 seconds. These structures, composed of stacked thin layers of different materials, are crucial for maximizing light absorption in solar cells and optimizing other optical components, such as those used in telescopes. The developers of OptoGPT highlight that their designs typically require six fewer layers compared to those generated by older models, making them simpler to manufacture. L. Jay Guo, a professor of electrical and computer engineering at the University of Michigan, explained that traditional design processes are complex and require significant expertise to identify the optimal combination of materials and layer thicknesses. OptoGPT treats materials of specific thicknesses as "words" and their optical properties as inputs. By identifying correlations between these "words," the algorithm predicts the next "word" to construct a "phrase" that fulfills the desired optical property. Professor Guo, the lead author of a paper published in Opto-Electronic Advances titled “OptoGPT: A foundation model for inverse design in optical multilayer thin film structures,” stated that they essentially created artificial sentences to fit the existing ChatGPT model framework. The research paper emphasizes OptoGPT’s ability to handle the complex inverse design problem in multilayer structures and its versatility across different input targets, structure types, and fabrication processes. Although the algorithm was trained using a dataset of 10 million samples, the researchers acknowledge that this dataset represents only a fraction of the vast design possibilities for optical multilayer thin film structures. This limitation means OptoGPT may not identify designs outside of its training data. The researchers concluded that broader collaboration among research groups is necessary to develop more comprehensive models for photonic inverse design capable of handling more complex structures.

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Canon has recently filed patents for several new camera lenses, sparking excitement among photographers. The Japanese tech giant secured patents in Japan for two wide-angle zoom lenses, a 15-28mm f/2.8 and a 17-30mm f/2.8, and three telephoto zoom lenses, a 70-300mm f/4, a 300-600mm f/2.8-4.5, and a 400-600mm f/2.8-4. These patents were officially published in late July, following submissions in January 2023 for the wide-angle designs, and a day earlier for the telephoto lenses.

The wide-angle patents describe compact zoom lenses with a constant fast aperture of f/2.8. This development suggests Canon might be aiming to bridge the gap between its existing RF 14-35mm f/4 and RF 15-35mm f/2.8 lenses, potentially offering a lighter and more affordable f/2.8 wide-angle zoom option, albeit with a slightly reduced zoom range.

The telephoto lens patents include a more conventional 70-300mm f/4, but also more innovative designs like the 300-600mm f/2.8-4.5 and 400-600mm f/2.8-4. Canon’s patents highlight a growing demand for telephoto zooms that combine bright apertures and high optical performance with a compact size. These designs hint at Canon’s continued push for innovation in telephoto optics, similar to their recent release of the unique RF 100-300mm f/2.8 lens.

The emergence of these patents follows recent comments from a Canon executive about developing RF lenses that are currently “unimaginable,” adding fuel to speculation about Canon’s future lens roadmap. If the 300-600mm and 400-600mm patents were to materialize into actual lenses, they could provide comprehensive telephoto coverage for photographers, particularly in sports and wildlife photography.

It is important to note that patents do not guarantee product releases. Many patented technologies and designs never make it to market. However, these filings offer a glimpse into Canon’s research and development directions and indicate the company’s focus on expanding its RF lens lineup with both versatile wide-angle and cutting-edge telephoto zoom options to compete in the evolving mirrorless camera market, where competitors like Nikon are also actively launching new telephoto lenses. Camera enthusiasts will be watching closely to see if these patented lens designs will eventually become available for Canon EOS R system users.

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