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The ORCA-Quest quantitative CMOS (qCMOS camera) with Photon Number Resolving functionality is the leap in scientific camera evolution that transforms imaging into imagining.
With ultra-quiet, highly-refined electronics, this camera is more than an image capture device; it is a precision instrument that unlocks the ability to investigate new photonic questions because it offers the quality and quantitative performance to detect meaningful data previously lost in the noise.
Four key features of qCMOS
1. Extreme low-noise performance
In order to detect weak light with high signal-to-noise, ORCA-Quest has been designed and optimized to every aspect of the sensor from its structure to its electronics. Not only the camera development but also the custom sensor development has been done with latest CMOS technology, an extremely low noise performance of 0.27 electrons has been achieved.
2. Realization of photon number resolving (PNR) output
Light is a collection of many photons. Photons are converted into electrons on the sensor, and these electrons are called photoelectrons. “Photon number resolving*” is a method of accurately measuring light by counting photoelectrons. In order to count these photoelectrons, camera noise must be sufficiently smaller than the amount of photoelectron signal. Conventional sCMOS cameras achieve a small readout noise, but still larger than photoelectron signal, making it difficult to count photoelectrons. Using advanced camera technology, the ORCA-Quest counts photoelectrons and delivers an ultra-low readout noise of 0.27 electrons rms (@Ultra quiet scan), stability over temperature and time, individual calibration and real-time correction of each pixel value.
* Photon number resolving is unique and quite different from photon counting (More precisely the method resolves the number of photoelectrons. However, since single photon counting instead of single photoelectron counting has been used for a comparable method in this field, we will use the term “photon number resolving”).
3. Back-illuminated structure and high resolution
High QE is essential for high efficiency of detecting photons and achieved by back-illuminated structure. In conventional back-illuminated sensors, crosstalks occur between pixels due to no pixel separation, and resolutions are usually inferior to those of front-illuminated sensors. The ORCA-Quest qCMOS camera’s sensor has back-illuminated structure for achieving high quantum efficiency, and trench structure in one-by-one pixel for reducing crosstalk.
4. Realization of a large number of pixels and high speed readout
Photon counting (PC) level images have typically been acquired using electron multiplication camera such as EM-CCD camera with about 0.3 megapixels. However, the ORCA-Quest qCMOS camera can acquire not only PC level images but also photon number resolving images with 9.4 megapixels. In addition, it is not fair to compare readout speeds of cameras with different pixel number by frame rate. In such a case the pixel rate (number of pixels × frame rate), which is the number of pixels read out per second, is used. Until now, the fastest camera capable of SPC readout was the EM-CCD camera with about 27 megapixel/s, but the ORCA-Quest enables photon number resolving imaging at about 47 megapixel/s, nearly twice as fast.
qCMOS Applications
Quantum technology
Neutral atom, Ion trap
Neutral atoms and ions can be regarded as so-called qubits because they can take on a superposition state in which even a single atom has multiple properties. This property is being actively investigated to realize quantum computing and quantum simulation. By observing the fluorescence of trapped ions and neutral atoms, the state of the qubit can be determined, and a low-noise camera is used to read out the fluorescence.
Simulation image (Rb atom@780 nm/Number of atoms: 5 × 5 array/Atomic emission: 2000 photons/Background: 5 photons/Magnification: 20 × (NA: 0.4)/Distance between each atom: 5 μm)
Astronomy
Lucky imaging
When observing stars from the ground, the image of the star can be blurred due to atmospheric turbulence therefore substantially reducing the ability to capture clear images. However, with short exposures and the right atmospheric conditions, you can sometimes capture clear images. For this reason, lucky imaging is a method of acquiring a large number of images and integrating only the clearest ones while aligning them.
Orion Nebula (Color image with 3 wavelength filters)
Raman spectroscopy
Raman effect is the scattering of light at a wavelength different from that of the incident light, and Raman spectroscopy is a technique for determining the material properties by measuring this wavelength. Raman spectroscopy enables structural analysis at the molecular level, which provides information on chemical bonding, crystallinity, etc.
Delayed fluorescence in plants with qCMOS
Plants release a very small portion of the light energy they absorb for photosynthesis as light over a period of time. This phenomenon is known as delayed fluorescence. By detecting this faint light, it is possible to observe the effects of chemicals, pathogens, the environment, and other stressors on plants.
Delayed fluorescence of ornamental plants (exposure for 10 seconds after 10 seconds of excitation light quenching)
Software Support
Without robust software a camera is an instrument of frustration not exploration. The ORCA-Quest qCMOS camera is fully supported in Hamamatsu’s HCImage and HiPic software. In addition, Hamamatsu provides numerous software tools to help investigators develop software within their own lab environment.
At the core of running all Hamamatsu’s cameras is our DCAM-API. Robust, stable and compatible with all Hamamatsu Cameras and interfaces, this underlying layer of software is needed and freely provided with any front-end, user-interface software that runs Hamamatsu Cameras.
To access controls for developing a custom user interface that integrates with DCAM-API, developers must download the DCAM-API SDK, DCAM-API and DCAM-API SDK are compatible with Windows and Linux.
With the increasing sophistication of imaging experiments, comes an increasing need for customized control of lab hardware. Our software engineers have created useful and user-feedback based toolkits for common development environments including MATLAB, LabVIEW, and Python.
More details and downloads can be found at www.dcam-api.com
For more high performance CCD and CMOS cameras, visit: https://www.axiomoptics.com/scientific-industrial-cameras/#low-light-cameras