相关论文: Towards a FPGA-controlled deep phase modulation in…
Modern experiments with fundamental quantum systems - like ultracold atoms, trapped ions, single photons - are managed by a control system formed by a number of input/output electronic channels governed by a computer. In hybrid quantum…
Infrared heterodyne interferometry has been proposed as a practical alternative for recombining a large number of telescopes over kilometric baselines in the mid-infrared. However, the current limited correlation capacities impose strong…
In the field of High Performance Computing, communications among processes represent a typical bottleneck for massively parallel scientific applications. Object of this research is the development of a network interface card with specific…
Self-mixing interferometry is a measurement approach in which a laser beam is re-injected into the emitting laser itself after reflection on a target. Information about the position of the target can be obtained from monitoring the voltage…
A novel technique is presented for realising programmable silicon photonic circuits. Once the proposed photonic circuit is programmed, its routing is retained without the need for additional power consumption. This technology enables a…
We have developed a three dimensional (3D) interferometric beamforming technique for imaging lightning flashes using Very-High Frequency (VHF) radio data recorded from several hundreds antennas with baselines up to 100~km as offered by the…
We present a computer-based active interferometer stabilization method that can be set to an arbitrary phase difference and does not rely on modulation of the interfering beams. The scheme utilizes two orthogonal modes propagating through…
Plasmonic interferometry is a rapidly growing area of research with a huge potential for applications in terahertz frequency range. In this Letter, we explore a plasmonic interferometer based on graphene Field Effect Transistor connected to…
To cope with the increasing demand and computational intensity of deep neural networks (DNNs), industry and academia have turned to accelerator technologies. In particular, FPGAs have been shown to provide a good balance between performance…
The LLRF of five of TRIUMF's ISAC-1 accelerator cavities have been replaced by 3 similar FPGA based system with different operating frequencies. These LLRF use internal digital phase locked loops for frequency generation and…
Due to the emergence of embedded applications in image and video processing, communication and cryptography, improvement of pictorial information for better human perception like deblurring, denoising in several fields such as satellite…
Federated edge learning (FEEL) is a framework for training models in a distributed fashion using edge devices and a server that coordinates the learning process. In FEEL, edge devices periodically transmit model parameters to the server,…
We proposes a platform which can generate hardware/software description based on flexible in-struction set architectures (ISAs). The platform takes advantage of the flexibility of field pro-grammable gate array (FPGA) to design many micro…
This letter presents a dual quadrature phasemeter, an implementation of a phase-locked loop designed to track the phase of homodyne and heterodyne inter-satellite laser links. The dual quadrature phasemeters use dual quadrature optical…
Recent efforts for improving the performance of neural network (NN) accelerators that meet today's application requirements have given rise to a new trend of logic-based NN inference relying on fixed function combinational logic. Mapping…
Cold-atom interferometry is a powerful tool for high-precision measurements of the quantum properties of atoms, many-body interactions and gravity. Further enhancement of sensitivity and reduction of complexity of these devices are crucial…
We designed an FPGA fabric to provide phase modulation techniques to lock lasers to optical frequency references. The method incorporates an active residual-amplitude-modulation (RAM) suppression scheme that relies on complex modulation.…
In this work we propose a neuromorphic hardware based signal equalizer by based on the deep learning implementation. The proposed neural equalizer is plasticity trainable equalizer which is different from traditional model designed based…
The deep learning accelerator is one of the methods to accelerate deep learning network computations, which is mainly based on convolutional neural network acceleration. To address the fact that concurrent convolutional neural network…
Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC…