相关论文: FSUDAQ -- A general purpose GUI data acquisition p…

Edge AI computing boxes are a new class of computing devices that are aimed to revolutionize the AI industry. These compact and robust hardware units bring the power of AI processing directly to the source of data--on the edge of the…

Digital-analog quantum computing (DAQC) is an alternative paradigm for universal quantum computation combining digital single-qubit gates with global analog operations acting on a register of interacting qubits. Currently, no available…

We report a mixed-signal data acquisition (DAQ) system for optically detected magnetic resonance (ODMR) of solid-state spins. This system is designed and implemented based on a Field-Programmable-Gate-Array (FPGA) chip assisted with…

There is currently a lot of activity in R\&D for future collider experiments. Multiple detector prototypes are being tested, each one with slightly different requirements regarding the format of the data to be analysed. This has generated a…

Distributed functional scalar quantization (DFSQ) theory provides optimality conditions and predicts performance of data acquisition systems in which a computation on acquired data is desired. We address two limitations of previous works:…

In the traditional approach to controlling superconducting qubits using microwave pulses, the field of pulse shaping has emerged in order to assist in the removal of leakage and increase gate fidelity. However, the challenge of scaling…

The SeaQuest experiment (Fermilab E906) detects pairs of energetic {\mu}+ and {\mu}- produced in 120 GeV/c proton-nucleon interactions in a high rate environment. The trigger system consists of several arrays of scintillator hodoscopes and…

A new $\mu$TCA DAQ system was introduced in CANDLES experiment with SpaceWire-to-GigabitEthernet (SpaceWire-GigabitEthernet) network for data readout and Flash Analog-to-Digital Converters (FADCs). With SpaceWire-GigabitEthernet, we can…

Federated learning is a distributed machine learning framework to collaboratively train a global model without uploading privacy-sensitive data onto a centralized server. Usually, this framework is applied to edge devices such as…

Quantum computers have rapidly improved in scale and fidelity, yet access to large systems remains limited for most researchers. This makes accurate and scalable noisy quantum simulation essential. While density matrix simulation provides…

A large number of data need to be transmitted in high-speed between Field Programmable Gate Array (FPGA) and Advanced RISC Machines 11 micro-controller (ARM11) when we design a small data acquisition (DAQ) system for nuclear experiments.…

DDSCAT 7.2 is a freely available open-source Fortran-90 software package applying the discrete dipole approximation (DDA) to calculate scattering and absorption of electromagnetic waves by targets with arbitrary geometries and complex…

We describe a modular multi-channel data acquisition system based on the 5-15 Gigasample-per-second waveform-recording PSEC4 chip. The system architecture incorporates two levels of hardware with FPGA-embedded system control and in-line…

A new data acquisition program for personal computers with Windows operating system has been built at Charles University van de Graaff laboratory. It allows fast data acquisition from CAMAC and other PC interface cards using interrupt or…

This work presents AEQUAM (Area Efficient QUAntum eMulation), a toolchain that enables faster and more accessible quantum circuit verification. It consists of a compiler that translates OpenQASM 2.0 into RISC-like instructions, Cython…

We present a large-scale facial UV-texture dataset that contains over 50,000 high-quality texture UV-maps with even illuminations, neutral expressions, and cleaned facial regions, which are desired characteristics for rendering realistic 3D…

We introduce new parallel algorithms for efficiently simulating stabilizer (Clifford) circuits on GPUs, with a focus on data-parallel tableau evolution and scalable handling of projective measurements. Our approach reformulates key…

The retinal fundus images are utilized extensively in the diagnosis, and their quality can directly affect the diagnosis results. However, due to the insufficient dataset and algorithm application, current fundus image quality assessment…

Deep learning-based image compression (LIC) has achieved state-of-the-art rate-distortion (RD) performance, yet deploying these models on resource-constrained FPGAs remains a major challenge. This work presents a complete, multi-stage…

Caribou is a flexible open-source DAQ system developed and used within several collaborative frameworks (CERN EP R&D, RD50, AIDAinnova) for laboratory and high-rate beam tests and easy integration of new silicon-pixel detector prototypes.…