相关论文: Effect of CLIQ on training of HL-LHC quadrupole ma…

Low-dimensional quantum magnets are a versatile materials platform for studying the emergent many-body physics and collective excitations that can arise even in systems with only short-range interactions. Understanding their low-temperature…

During its Run 2 (2015-2018), the Large Hadron Collider (LHC) operated at almost twice higher energy, and provided Pb-Pb collisions with an order of magnitude higher luminosity, than in the previous Run 1. In consequence, the power of the…

A single aperture Canted-Cosine-Theta (CCT) quadrupole magnet, made of NbTi superconductors, has been developed for the final focus region of the FCC-ee study. The conductor layout is optimised to mitigate edge effects on one of the two…

Possible layouts of superconducting dipoles for the main injector of High Energy LHC (HE-LHC) are proposed on the basis of the experience matured with ongoing R&D activities at the Italian National Institute of Nuclear Physics (INFN),…

Errors in the current generation of quantum processors pose a significant challenge towards practical-scale implementations of quantum machine learning (QML) as they lead to trainability issues arising from noise-induced barren plateaus, as…

The theoretical framework of the neutrino electron excitation at low energies including the screening effect in semiconductor detectors is developed for the first time, both in the Standard Model and in the presence of the neutrino magnetic…

Nb3Sn conductors are important candidates for high-field magnets for particle accelerators, and they continue to be widely used for many laboratory and NMR magnets. However, the critical current density, Jc, of present Nb3Sn conductors…

A wealth of physics results have already been obtained from the LHC, due to the excellent performance of the collider and its experiments. Even more results are expected to be achievable in the phase of the high-luminosity LHC (HL-LHC). It…

The Large Hadron Collider (LHC) at CERN is a 7 TeV proton synchrotron, with a design stored energy of 362 MJ per beam. The high-luminosity (HL-LHC) upgrade will increase this to 675 MJ per beam. In order to protect the superconducting…

Quantum Machine Learning (QML) is an accelerating field of study that leverages the principles of quantum computing to enhance and innovate within machine learning methodologies. However, Noisy Intermediate-Scale Quantum (NISQ) computers…

In this contribution to the Quark Matter 2012 conference, we study whether energy loss models established for RHIC energies to describe the quenching of heavy quarks can be applied at LHC with the same success. We also benefit from the…

The purpose of this document is to define the specifications for the structure fabrication and assembly of MQXFA series magnets to be used by the US High-Luminosity LHC Accelerator Upgrade Project (AUP). Magnets fabricated according to…

Investigating the potential benefits of the use of magnetic fields in Inertial Confinement Fusion (ICF) experiments has given rise to new experimental platforms like the Magnetized Liner Inertial Fusion (MagLIF) approach at the Z-machine…

The operating conditions defining the current data taking campaign at the Large Hadron Collider, known as Run 3, present unparalleled challenges for the real-time data acquisition workflow of the LHCb experiment at CERN. To address the…

Superconducting accelerator magnets have a nonlinear dependence of field on current due to the magnetization associated with the iron or with persistent currents in the superconducting filaments. This also gives rise to hysteresis phenomena…

Using unimproved and non-perturbatively O(a) improved Wilson fermions, results are given for the three lowest moments of unpolarised nucleon structure functions. Renormalisation, chiral extrapolation and the continuum limit of the matrix…

The magnetic Gilbert damping and spin-orbital to charge interconversion phenomenon play vital role in controlling the modern spintronics device performances. Though the ferromagnets (FMs) and heavy metals (HMs) are considered to be the key…

Machine learning force fields (MLFFs), which employ neural networks to map atomic structures to system energies, effectively combine the high accuracy of first-principles calculation with the computational efficiency of empirical force…

Superconducting qubits are among the most promising candidates for building quantum information processors. Yet, they are often limited by slow and error-prone qubit readout -- a critical factor in achieving high-fidelity operations. While…

We present the results from a series of lattice simulations of the charmonium system using a highly-improved NRQCD action, both in the quenched approximation, and with n_f = 2 light dynamical quarks. The spectra show some evidence for…