Samuel Burri

2papers

2 Papers

QUANT-PHFeb 11, 2021
A High Speed Integrated Quantum Random Number Generator with on-Chip Real-Time Randomness Extraction

Francesco Regazzoni, Emna Amri, Samuel Burri et al.

The security of electronic devices has become a key requisite for the rapidly-expanding pervasive and hyper-connected world. Robust security protocols ensuring secure communication, device's resilience to attacks, authentication control and users privacy need to be implemented. Random Number Generators (RNGs) are the fundamental primitive in most secure protocols but, often, also the weakest one. Establishing security in billions of devices requires high quality random data generated at a sufficiently high throughput. On the other hand, the RNG should exhibit a high integration level with on-chip extraction to remove, in real time, potential imperfections. We present the first integrated Quantum RNG (QRNG) in a standard CMOS technology node. The QRNG is based on a parallel array of independent Single-Photon Avalanche Diodes (SPADs), homogeneously illuminated by a DC-biased LED, and co-integrated logic circuits for postprocessing. We describe the randomness generation process and we prove the quantum origin of entropy. We show that co-integration of combinational logic, even of high complexity, does not affect the quality of randomness. Our CMOS QRNG can reach up to 400 Mbit/s throughput with low power consumption. Thanks to the use of standard CMOS technology and a modular architecture, our QRNG is suitable for a highly scalable solution.

CVNov 6, 2018
A Bit Too Much? High Speed Imaging from Sparse Photon Counts

Paramanand Chandramouli, Samuel Burri, Claudio Bruschini et al.

Recent advances in photographic sensing technologies have made it possible to achieve light detection in terms of a single photon. Photon counting sensors are being increasingly used in many diverse applications. We address the problem of jointly recovering spatial and temporal scene radiance from very few photon counts. Our ConvNet-based scheme effectively combines spatial and temporal information present in measurements to reduce noise. We demonstrate that using our method one can acquire videos at a high frame rate and still achieve good quality signal-to-noise ratio. Experiments show that the proposed scheme performs quite well in different challenging scenarios while the existing approaches are unable to handle them.