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Predicting the State-of-Health (SoH) of lithium-ion batteries is a fundamental task of battery management systems on electric vehicles. It aims at estimating future SoH based on historical aging data. Most existing deep learning methods…
We describe the concept and procedure of drifted-charge extraction developed in the MicroBooNE experiment, a single-phase liquid argon time projection chamber (LArTPC). This technique converts the raw digitized TPC waveform to the number of…
Searches for charged lepton flavor violation (CLFV) offer deep probes for a range of new physics scenarios, such as super-symmetric models, theories involving scalar leptoquarks or additional Higgs doublets, and models explaining the…
The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for…
The milliQan Collaboration has proposed to search for millicharged particles by looking for very weakly ionizing tracks in a detector installed in a cavern near the CMS experiment at the LHC. We note that another form of exotica can also…
The reconstruction of the positron trajectory in the MEG-II experiment searching for the $\mu^+ \to e^+ \gamma$ decay uses a cylindrical drift chamber operated with a helium-isobutane gas mixture. A stable performance of the detector in…
This thesis reports the various phases of the life cycle of a cylindrical GEM detector, developed within the context of the CGEM-IT project. This represents the Italian proposal for the upgrade of the BESIII inner tracker, which has been…
We evaluate the phase-coherent transport of electrons along linear structures of varying length, which are made from two types of potential wells set in either a periodic or a Fibonacci quasi-periodic sequence. The array is described by a…
After a short introduction to the SM picture of CP violation, we discuss recent work on how to use SU(3) flavor symmetry, along with some dynamical approximations, to extract the CKM weak phases and the strong rescattering phases from…
The COMET experiment aims to search for the neutrinoless muon to electron transition process with new sensitivity levels. The online trigger system is an integral part of achieving the sensitivity levels required and will be subject to an…
Jet flavour tagging is crucial in experimental high-energy physics. A tagging algorithm, DeepJetTransformer, is presented, which exploits a transformer-based neural network that is substantially faster to train than state-of-the-art graph…
Quantum information processing requires overcoming decoherence---the loss of "quantumness" due to the inevitable interaction between the quantum system and its environment. One approach towards a solution is quantum dynamical decoupling---a…
In this study, deep learning is used to estimate kinetic parameters for modeling itaconic acid production based on real batch experiments conducted at different agitation speeds and reactor scales. Two deep learning strategies, namely…
The Collider Detector at Fermilab (CDF) is a general-purpose experimental apparatus with an inner tracking detector for measuring charged particles, surrounded by a calorimeter for measurements of electromagnetic and hadronic showers, and a…
The paper considers the electrodisintegration of the deuteron for kinematic conditions of the JLab experiment E-94-019. The calculations have been performed within the covariant Bethe-Salpeter approach with a separable kernel of…
Deep learning model trained by imbalanced data may not work satisfactorily since it could be determined by major classes and thus may ignore the classes with small amount of data. In this paper, we apply deep learning based imbalanced data…
Beam Drift Chamber (BDC) is designed to reconstruct the trajectories of incident rare isotope beams provided by RAON (Rare isotope Accelerator complex for ON-line experiments) into the experimental target of LAMPS (Large Acceptance…
In the attempt to fully profile a $Z'$ boson accessible at the Large Hadron Collider (LHC), we study the sensitivity of di-lepton (for the electron, muon and tauon cases) and di-quark (for the case of the heavy flavours, $t$ and, possibly,…
The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims at improving the performance of practical DL implementations in terms of cloud bandwidth consumption, response latency, and data privacy preservation. Focusing on…
We develop a mathematically rigorous theory for the quantum transfer processes in degenerate donor-acceptor dimers in contact with a thermal environment. We calculate explicitly the transfer rates and the acceptor population efficiency. The…