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PAC

Information Center for Mathematical Science

PAC

A single-photon sampling architecture for solid-state imaging sensors
Author Emmanuel Candes (Stanford University)
Homepage Url http://www-stat.stanford.edu/~candes/publications.html
Coauthors Ewout van den Berg, Garry Chinn, Craig Levin, Peter Olcott, Carlos Sing-Long
Abstract Advances in solid-state technology have enabled the development of silicon photomultiplier sensor arrays capable of sensing individual photons. Combined with high-frequency time-todigital converters (TDCs), this technology opens up the prospect of sensors capable of recording with high accuracy both the time and location of each detected photon. Such a capability could lead to signi cant improvements in imaging accuracy, especially for applications operating with low photon uxes such as LiDAR and positron emission tomography. The demands placed on on-chip readout circuitry imposes stringent trade-o s between ll factor and spatio-temporal resolution, causing many contemporary designs to severely underutilize the technology's full potential. Concentrating on the low photon ux setting, this paper leverages results from group testing and proposes an architecture for a highly ecient readout of pixels using only a small number of TDCs, thereby also reducing both cost and power consumption. The design relies on a multiplexing technique based on binary interconnection matrices. We provide optimized instances of these matrices for various sensor parameters and give explicit upper and lower bounds on the number of TDCs required to uniquely decode a given maximum number of simultaneous photon arrivals. To illustrate the strength of the proposed architecture, we note a typical digitization result of a 120  120 photodiode sensor on a 30 m  30 m pitch with a 40 ps time resolution and an estimated ll factor of approximately 70%, using only 161 TDCs. The design guarantees registration and recovery of up to s = 4 simultaneous photon arrivals. A fast decoding algorithm is available, which decodes successfully with probability 1
Abstract Url http://www-stat.stanford.edu/~candes/papers/GroupTesting.pdf