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Consistent with the predictions of Kibble and Zurek, scaling behaviour has been seen in the production of fluxoids during temperature quenches of superconducting rings. However, deviations from the canonical behaviour arise because of…
Microstructural features play an important role for the quality of permanent magnets. The coercivity is greatly influenced by crystallographic defects, which is well known for MnAl-C, for example. In this work we show a direct link of…
Quantum Machine Learning (QML) aims to leverage the principles of quantum mechanics to speed up the process of solving machine learning problems or improve the quality of solutions. Among these principles, entanglement with an auxiliary…
The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle…
This paper presents the latest trends in the powering of particle accelerators. A series of solutions is proposed for responding to the challenges of high performance machines. This paper covers the domains of magnetic field uncertainty,…
The frontier of quantum computing (QC) simulation on classical hardware is quickly reaching the hard scalability limits for computational feasibility. Nonetheless, there is still a need to simulate large quantum systems classically, as the…
New accelerator magnet technology based on Nb3Sn superconductor is being developed at Fermilab since late 90's. Six short dipole models, seven short quadrupole models and numerous individual dipole and quadrupole coils have been built and…
Physics-inspired neural networks (NNs), such as Hamiltonian or Lagrangian NNs, dramatically outperform other learned dynamics models by leveraging strong inductive biases. These models, however, are challenging to apply to many real world…
During testing of the Stress Managed Cosine-Theta dipole mirror magnet SMCTM1, magnet quenches were observed following large voltage spikes in the half-coil voltage taps which preceded normal quench initiation. Following some recent work at…
With the increasing interest in Quantum Machine Learning, Quantum Neural Networks (QNNs) have emerged and gained significant attention. These models have, however, been shown to be notoriously difficult to train, which we hypothesize is…
Changes in magnetic critical behaviour of quenched structurally-disordered magnets are usually exemplified in experiments and in MC simulations by diluted systems consisting of magnetic and non-magnetic components. By our study we aim to…
The information obtained from the operation of a quantum gate on only two complementary sets of input states is sufficient to estimate the quantum process fidelity of the gate. In the case of entangling gates, these conditions can be used…
Reinforcement Learning in domains with sparse rewards is a difficult problem, and a large part of the training process is often spent searching the state space in a more or less random fashion for any learning signals. For control problems,…
Local aspects of magnetism of disordered FePt are investigated by ab initio fully relativistic full potential calculations, employing the supercell approach and the coherent potential approximation (CPA). The focus is on trends of the spin…
Quantifying unknown quantum entanglement experimentally is a difficult task, but also becomes more and more necessary because of the fast development of quantum engineering. Machine learning provides practical solutions to this fundamental…
We present powerful new analysis techniques to constrain effective field theories at the LHC. By leveraging the structure of particle physics processes, we extract extra information from Monte-Carlo simulations, which can be used to train…
We experimentally demonstrate stable trapping of a permanent magnet sphere above a lead superconductor, in vacuum pressures of $4 \times 10^{-8}$~mbar. The levitating magnet behaves as a harmonic oscillator, with frequencies in the 4-31~Hz…
Magnetisation of superconductors are often measured under isothermal and uniform magnetic fields. Magnetisation measurements in an unrestricted thermodynamic state and in non uniform magnetic fields naturally emerge from permanent magnets…
Superconducting materials hold great potential to bring radical changes for electric power and high-field magnet technology , enabling high-efficiency electric power generation, high-capacity lossless electric power transmission, small…
We show that the dynamics resulting from preparing a one-dimensional quantum system in the ground state of two decoupled parts, then joined together and left to evolve unitarily with a translational invariant Hamiltonian (a local quench),…