Related papers: Development of an FPGA-based realtime DAQ system f…
In this article we present the Dark-photons$\&$Axion-Like particles Interferometer (DALI), a novel experiment designed for the detection of photon-mixing cold dark matter in the microwave band between 6 and 60 GHz. DALI is a haloscope for…
Quantum sensing is a rapidly growing field of research which is already improving sensitivity in fundamental physics experiments. The ability to control quantum devices to measure physical quantities received a major boost from…
Dark acoustic oscillations (DAOs) in the matter power spectrum can arise in many different dark sector models, and can imprint on a variety of cosmological observables. In this work we use measurements of the galactic UV luminosity function…
In this paper, we present a complete Data Acquisition System (DAQ) together with the readout mechanisms for the J-PET tomography scanner. In general detector readout chain is constructed out of Front-End Electronics (FEE), measurement…
A front-end waveform digitization data acquisition system prototype for pulsed magnetic field generator in inertial confinement fusion is described. The pulse magnetic field is created by discharging a high-voltage capacitor through a small…
The axion is a light pseudoscalar particle which suppresses CP-violating effects in strong interactions and also happens to be an excellent dark matter candidate. Axions constituting the dark matter halo of our galaxy may be detected by…
Quantum annealing (QA) is a hardware-based heuristic optimization and sampling method applicable to discrete undirected graphical models. While similar to simulated annealing, QA relies on quantum, rather than thermal, effects to explore…
Feedback-based adaptive quantum optimization (FALQON) is a promising approach for solving combinatorial problems on noisy intermediate-scale quantum (NISQ) devices, requiring only single circuit evaluations per layer. However, standard…
The axion was first introduced as a consequence of the Peccei-Quinn mechanism to solve the CP problem in strong interactions of particle physics and is a well motivated cold dark matter candidate. This particle is expected to interact…
The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an…
This paper introduces a high-performance Soft-Core Processor based data acquisition system designed for handling Resistive Plate Chambers (RPCs). The DAQ consist of FPGA-based hardware equipped with Soft-Core Processor and embedded…
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…
The axion is a well-motivated cold dark matter (CDM) candidate first postulated to explain the absence of $CP$ violation in the strong interactions. CDM axions may be detected via their resonant conversion into photons in a "haloscope"…
The Compressed Baryonic Matter (CBM) experiment is designed to handle interaction rates of up to 10 MHz and up to 1 TB/s of raw data generated. With triggerless streaming data acquisition in the experiment and beam intensity fluctuations,…
Performing Data Assimilation (DA) at a low cost is of prime concern in Earth system modeling, particularly at the time of big data where huge quantities of observations are available. Capitalizing on the ability of Neural Networks…
The CAST (CERN Axion Solar Telescope) experiment is searching for solar axions by their conversion into photons inside the magnet pipe of an LHC dipole. The analysis of the data recorded during the first phase of the experiment with vacuum…
Exploring the mysterious dark matter is a key quest in modern physics. Currently, detecting axions, a hypothetical particle proposed as a primary component of dark matter, remains a significant challenge due to their weakly interacting…
We propose using variational quantum algorithms (VQAs) to simulate established quantum algorithms under realistic noise conditions, aiming to surpass the fidelity of theoretical circuits in noisy environments. Focusing on the Quantum…
Designing parameterized quantum circuits (PQCs) that are expressive, trainable, and robust to hardware noise is a central challenge for quantum machine learning (QML) on noisy intermediate-scale quantum (NISQ) devices. We present a…
Fast imaging localises celestial transients using source finders in the image domain. The need for high computational throughput in this process is driven by next-generation telescopes such as Square Kilometre Array (SKA), which, upon…