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

Multimodal Large Language Models (MLLM) are increasingly deployed in domains where both reliability and efficiency are critical. However, current models remain overconfident, producing highly certain but incorrect answers. At the same time,…

Parameterized Quantum Circuits (PQCs) with fixed structures severely degrade the performance of Quantum Machine Learning (QML). To address this, a Hybrid Quantum-Classical Classifier (HQCC) is proposed. It opens a practical way to advance…

It is expected that the LHC accelerator and experiments will undergo a luminosity upgrade which will commence after several years of running. This part of the LHC operations is referred to as Super-LHC (SLHC) and is expected to provide…

The High-Luminosity LHC will provide the unique opportunity to explore the nature of physics beyond the Standard Model of strong and electroweak interactions. Highly selective first level triggers are essential for the physics programme of…

NH4CuCl3 has two magnetization plateaus at one-quarter and three-quarters of the saturation magnetization, irrespective of the external field direction. Magnetic excitations in NH4CuCl3 have been investigated by means of neutron inelastic…

Despite remarkable successes in solving various complex decision-making tasks, training an imitation learning (IL) algorithm with deep neural networks (DNNs) suffers from the high computation burden. In this work, we propose quantum…

We present significant advances in Laser Wakefield Acceleration (LWFA) operating at a 1 kHz repetition rate, employing a sub-TW, few-femtosecond laser and a continuously flowing hydrogen gas target. We conducted the first comprehensive…

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…

For Run 3 (from 2021), the LHC will undergo a significant increase in instantaneous luminosity to 1.5 times its current value which will lead to larger collected statistics and an enhanced sensitivity to new physics. The Phase-1 upgrade of…

Heisenberg exchange coupling (HC) and biquadratic exchange coupling (BQC) are known to occur in magnetic tunnel junctions (MTJ) and nanoscale spintronics structures. MTJ-based molecular spintronics devices (MTJMSD) provide a platform to…

We report on suppression of long-range wakefields in CLIC accelerating structures. Strong detuning and moderate damping is employed. In these initial design studies we focus on the CLIC_G structure and enforce a moderate Q of 300 and 500.…

A new CLIC Test Facility (CTF3) at CERN will serve to study the drive beam generation for the Compact Linear Collider (CLIC). CTF3 has to accelerate a 3.5 A electron beam in almost fully-loaded structures. The pulse contains more than 2000…

The Large Hadron Collider (LHC) at CERN has been instrumental in recent advances in experimental high energy physics by colliding beams of protons and heavier nuclei at unprecedented energies. The present heavy-ion programme is based mainly…

Recent fabrication of atomic precision nanodevices for spintronics greatly boosted their performance and also revealed new interesting features, as oscillating magnetoresistance with number of atomic layers in a multilayered structure. This…

Vacuum of Quantum Chromodynamics in very strong (hadron-scale) magnetic fields exhibits many interesting nonperturbative effects. Some of these effects can be studied with the help of lattice simulations in quenched QCD. We review our…

Multi-head latent attention (MLA) is designed to optimize KV cache memory through low-rank key-value joint compression. Rather than caching keys and values separately, MLA stores their compressed latent representations, reducing memory…

We propose a noise-mitigation quantum simulation strategy for near-term quantum devices based on Quantum Circuit Learning (QCL), which is in particular effective for integrable quantum spin chains. The method trains a shallow variational…

For many machine learning applications in science, data acquisition, not training, is the bottleneck even when avoiding experiments and relying on computation and simulation. Correspondingly, and in order to reduce cost and carbon…

The effect of quenched disorder on the multiphase competition has been investigated by examining the pressure phase diagram of half doped manganite Ln0.5B0.5MnO3 (Ln = Sm and Nd) with A-site disorders. Sm0.5Ba0.5MnO3, a spin glass insulator…

Quantum machine learning is an approach that aims to improve the performance of machine learning methods by leveraging the properties of quantum computers. In quantum circuit learning (QCL), a supervised learning method that can be…