Superconducting qubits are among the most promising platforms for quantum computing and quantum sensing, requiring advanced electronic systems for their control and readout. These systems must generate high-fidelity microwave pulses, ensure low-noise amplification, and enable fast, high-precision measurements. The control system relies on arbitrary waveform generators (AWGs) and microwave...
Superconducting quantum bits, or qubits, are among the most promising technologies for the realization of fully-functioning quantum computers, and their possible applications, ranging from quantum simulations to quantum sensing and particle detection, make these devices a potentially interesting tool also for particle physics experiments.
A fundamental step in the research on this field has...
Quantum imaging is an emerging field that leverages the principles of quantum mechanics to achieve imaging capabilities beyond classical limits. By exploiting entangled photon, quantum imaging techniques enable enhanced resolution, improved sensitivity, and novel imaging modalities such as super-resolution, ghost imaging, sub-shot-noise imaging. These approaches hold significant promise for...
Random Power is an innovation project turned into a start-up company, developing a platform of random bit streamers based on quantum tunneling in Silicon Devices. The patent protected principle has been implemented in a series of boards and in an ASIC, currently in its final assessment phase. The basic building blocks to make it compliant to the FIPS-140-3 certification protocol, together with...
Future gravitational wave detectors will require increasingly sophisticated control systems to enhance sensitivity and expand operational range. A key challenge is optimizing the entire data acquisition and processing loop, from ADC conversion to real-time elaboration and DAC actuation, where low, deterministic latency is essential for improving overall system performance and extending control...
Memristors, first theorized by Leon Chua in 1971 as the fourth fundamental circuit element, were experimentally realized in 2008 by researchers at HP Labs. Since then, significant progress has been made in the development of memristive devices, unlocking new opportunities for energy-efficient computing and high-density memory storage. While companies such as Knowm focus on research-driven...
Keywords: Neuromorphic-Computing, spiking neural network, computational neuroscience, HPC, Edge Computing
Brain-inspired Spiking Neural Networks represent a promising frontier in computational models, offering potential advantages over traditional computing paradigms in terms of energy efficiency, temporal information processing, and adaptability to dynamic data. This can benefit numerous...
