Diffuse correlation spectroscopy (DCS) is a promising noninvasive technique for monitoring cerebral blood flow and measuring cortex functional activation tasks. Taking multiple parallel measurements has been shown to increase sensitivity, but is not easily scalable with discrete optical detectors. Here we show that with a large 500 × 500 SPAD array and an advanced FPGA design, we achieve an SNR gain of almost 500 over single-pixel mDCS performance. The system can also be reconfigured to sacrifice SNR to decrease correlation bin width, with 400 ns resolution being demonstrated over 8000 pixels.

In this article, we report on SwissSPAD3 (SS3), a 500 × 500 pixel single-photon avalanche diode (SPAD) array, fabricated in 0.18-µm CMOS technology. In this sensor, we introduce a novel dual-gate architecture with two contiguous temporal windows, or gates, guaranteed by the circuit architecture to be nonoverlapping and covering the totality of the sensor's exposure period. The gates can be adjusted with a temporal resolution of 17.9 ps, and the minimum measured gate width is 0.99 ns; to our knowledge, the shortest reported to date among large-format SPAD imagers. In the dual-channel mode, the burst frame rate is 49.8 and 97.7 kframes/s in the single-channel mode. A 2690-MB/s PCI express (PCIe) interface has been added to the data acquisition framework, enabling continuous operation at approximately 44 and 88 kframes/s. Due to optimizations of the gate-signal tree, we achieved a significant reduction to gate skew and gate width variation, which is negligible with respect to the SPAD temporal jitter. These improvements, along with sub-10-cps dark count rate (DCR) per pixel and 50% maximum photon detection probability (PDP), result in a sensor particularly well suited for fast acquisition fluorescence lifetime imaging microscopy (FLIM) experiments, for which we demonstrate reduced dispersion versus a single-gated sensor.

Single-photon avalanche diode (SPAD) arrays can be used for single-molecule localization microscopy (SMLM) because of their high frame rate and lack of readout noise. SPAD arrays have a binary frame output, which means photon arrivals should be described as a binomial process rather than a Poissonian process. Consequentially, the theoretical minimum uncertainty of the localizations is not accurately predicted by the Poissonian Cramér-Rao lower bound (CRLB). Here, we derive a binomial CRLB and benchmark it using simulated and experimental data. We show that if the expected photon count is larger than one for all pixels within one standard deviation of a Gaussian point spread function, the binomial CRLB gives a 46% higher theoretical uncertainty than the Poissonian CRLB. For typical SMLM photon fluxes, where no saturation occurs, the binomial CRLB predicts the same uncertainty as the Poissonian CRLB. Therefore, the binomial CRLB can be used to predict and benchmark localization uncertainty for SMLM with SPAD arrays for all practical emitter intensities.

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum–position entanglement and photon–number correlations to provide the typical refocusing and ultra-fast, scanning-free, 3D imaging capability of plenoptic devices, along with dramatically enhanced performances, unattainable in standard plenoptic cameras: diffraction-limited resolution, large depth of focus, and ultra-low noise. To further increase the volumetric resolution beyond the Rayleigh diffraction limit, and achieve the quantum limit, we are also developing dedicated protocols based on quantum Fisher information. However, for the quantum advantages of the proposed devices to be effective and appealing to end-users, two main challenges need to be tackled. First, due to the large number of frames required for correlation measurements to provide an acceptable signal-to-noise ratio, quantum plenoptic imaging (QPI) would require, if implemented with commercially available high-resolution cameras, acquisition times ranging from tens of seconds to a few minutes. Second, the elaboration of this large amount of data, in order to retrieve 3D images or refocusing 2D images, requires high-performance and time-consuming computation. To address these challenges, we are developing high-resolution single-photon avalanche photodiode (SPAD) arrays and high-performance low-level programming of ultra-fast electronics, combined with compressive sensing and quantum tomography algorithms, with the aim to reduce both the acquisition and the elaboration time by two orders of magnitude. Routes toward exploitation of the QPI devices will also be discussed.