AUREA Technology designs and manufactures a new generation of high-performance and self-contained optical instruments based on the most advanced single photon avalanche photodiodes, ultrafast laser diodes and fast timing electronics. As a worldwide technology leader, AUREA Technology provides ‘world-class’ Geiger-mode single photon counting, picosecond laser source, fast time correlation, and optical fiber sensing instruments.
In addition, AUREA Technology provides best-in-class professional support to more than 200 worldwide customers directly or through its professional distribution channels in North America, Europe, and Asia.
As a result, the AUREA Technology’s market-driven photonics solutions enable the success of its global customers by allowing them to achieve outstanding results, and remain at the forefront of their field. AUREA Technology works closely with its global customers to meet the challenges of today and tomorrow in quantum security, life sciences, nanotechnology, automobile, medical and defense.
AUREA Technology Exhibits its High-performance Optical Building Blocks for Quantum Technologies at SPIE Photonics West 2022
The TheiaVu™ Series is a range of benchtop inspection systems that allow the user to take a wide variety of measurements, and to record repeatable, reliable data to improve processes.
KLA’s Filmetrics F40 allows you to transform your benchtop microscope into an instrument to measure thickness and refractive index.
This product profile describes the properties and applications of the ProMetric® I-SC Solution Imaging Colorimeter.
Dr. David Dung
We spoke with University of Bonn spin-off Midel Photonics, a start-up company whose laser beam shaping technology is hoping to sharpen up the laser industry.
Matthias Sachsenhauser, Ph.D.
Following Laser World of Photonics 2022, we spoke with Matthias Sachsenhauser from Hamamatsu Photonics about the role of laser-driven light sources in the future of the photonics sector.
Dr. Keith Paulsen
AZoOptics speaks to Dr. Keith Paulsen about the importance of breast cancer detection and the introduction of his team's deep-learning algorithm that associates spatial images of tissue optical properties with optical signal patterns measured during an imaging experiment or patient exam.