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Sunday, December 03, 2017

1MP Photon-number-resolving Sensor

OSA Optica publishes a paper "Photon-number-resolving megapixel image sensor at room temperature without avalanche gain" by Jiaju Ma, Saleh Masoodian, Dakota Starkey, and Eric Fossum, Dartmouth College, NH, USA. From the abstrac t:

"Termed a quanta image sensor, the device is implemented in a commercial stacked (3D) backside-illuminated CMOS image sensor process. Without the use of avalanche multiplication, the 1.1 μm pixel-pitch device achieves 0.21e−  rms average read noise with average dark count rate per pixel less than 0.2e−/s, and 1040 fps readout rate. This novel platform technology fits the needs of high-speed, high-resolution, and accurate photon-counting imaging for scientific, space, security, and low-light imaging as well as a broader range of other applications."

9 comments:

  1. A remarkable work! Do you have some demo images to share please?

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    1. Thanks for the comment. One 1Mjot binary single-photon image can be found in the paper. BTW, the paper is open-access.

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  2. Impressive! one question here: was the 0.21 e- rms avg read noise measured at 1040fps in full resolution?

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    1. The measurement is made with the analog output array that operates at a much slower speed than the digital one. Since the noise seems dominated by SF 1/f noise, slow is not an advantage and also the CDS time is faster (shorter) for the digital array. The jot and SF are the same for both devices. The log D log H curve tells us about the noise for the higher speed single-bit output but determining input-referred e- noise from the on-chip single bit quantizer output alone is complicated.

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  3. What's the unit of "probability density"? Why it is not added up to 1?

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    1. It should integrate to unity and it looks like that to me. Which figure are you concerned about?

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    2. the y axis of the Fig 5(b). Also in the (a), if simply counting the data dots, it seems less than 1.

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    3. Still looks at least roughly right to me. The green curve should have an area underneath it equal to unity, which is the same area as a rectangle 20 high (full scale of the graph) by 0.05 wide. But, perhaps JJ wants to comment further.

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    4. I guess the confusion here is that one needs to do the integration with the corresponding x-axis scale. As Eric commented, the area of the curve equals to 1. The varied spreads of the data over x-axis make the y-axis scale look quite different in several plots. For example, the x-axis span for CG plots is ~60 and is ~0.2 for read noise plots (Fig. 5). As you normalize the area to 1, you get quite different y-axis scales.

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