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Photomultiplier tubes (PMTs) are widely used in particle and nuclear physics experiments. The reconstruction of PMT waveforms is a fundamental task in these experiments, where accurate extraction of photoelectron (PE) multiplicities and…
Multi-timestep simulation of brain-inspired Spiking Neural Networks (SNNs) boost memory requirements during training and increase inference energy cost. Current training methods cannot simultaneously solve both training and inference…
Excited states in $^{58,60,62}$Ni were populated via inelastic proton scattering at the Australian National University as well as via inelastic neutron scattering at the University of Kentucky Accelerator Laboratory. The Super-e electron…
This paper describes simulation analyses on beam and laser (X-ray)-driven accelerations in effective nanotube models obtained from Vsim and EPOCH codes. Experimental setups to detect wakefields are also outlined with accelerator facilities…
If accepted, the paper will be available at http://pubs.acs.org/journals/jpcbfh/
We deploy a combination of reinforcement learning-based approaches and more traditional optimization techniques to identify optimal protocols for population transfer in a multi-level system. We constraint our strategy to the case of fixed…
Spiking Neural Networks (SNNs) offer superior energy efficiency over Artificial Neural Networks (ANNs). However, they encounter significant deficiencies in training and inference metrics when applied to Spiking Vision Transformers (S-ViTs).…
Real-time biosignal processing on wearable devices has attracted worldwide attention for its potential in healthcare applications. However, the requirement of low-area, low-power and high adaptability to different patients challenge…
This paper studies the transmit energy beamforming in a multi-antenna wireless power transfer (WPT) system, in which an access point (AP) equipped with a uniform linear array (ULA) sends radio signals to wirelessly charge multiple…
The Transformer architecture has shown to be a powerful tool for a wide range of tasks. It is based on the self-attention mechanism, which is an inherently computationally expensive operation with quadratic computational complexity: memory…
Spiking neural network (SNN) is interesting both theoretically and practically because of its strong bio-inspiration nature and potentially outstanding energy efficiency. Unfortunately, its development has fallen far behind the conventional…
In this paper, the phase shifting transformer (PST) is introduced in the Transmission Expansion Planning (TEP) problem considering significant wind power integration. The proposed planning model is formulated as a bilevel program which…
In this article, a feasible switchyard design is proposed for the Shanghai soft x-ray free electron laser facility. In the proposed scheme, a switchyard is used to transport the electron beam to different undulator lines. Three-dimensional…
Spiking neural networks (SNNs) that mimic information transmission in the brain can energy-efficiently process spatio-temporal information through discrete and sparse spikes, thereby receiving considerable attention. To improve accuracy and…
This paper presents a spatial-temporal single harmonic switching (STHS) transmitter array architecture with enhanced efficiency in the power back-off (PBO) region. STHS is an electromagnetic and circuit co-designed and jointly optimized…
Efficient routing in IoT sensor networks is critical for minimizing energy consumption and latency. Traditional centralized algorithms, such as Dijkstra's, are computationally intensive and ill-suited for dynamic, distributed IoT…
Recently, brain-inspired spiking neuron networks (SNNs) have attracted widespread research interest because of their event-driven and energy-efficient characteristics. Still, it is difficult to efficiently train deep SNNs due to the…
Longitudinal coupling offers a compelling pathway for quantum nondemolition (QND) readout, but pulse design is constrained by hardware limitations such as the coupling strength and the photon number required to stay within the linear…
The Advanced Superconducting Test Accelerator (ASTA) currently under commissioning at Fermilab will enable a broad range of beam-based experiments to study fundamental limitations to beam intensity and to develop transformative approaches…
We present an efficient and cost-effective way to train operators of complex systems with limited accessibility, such as sub-detectors of big experiments at the CERN Large Hadron Collider (LHC). Our coaching station was developed to train…