Related papers: Advancements in Computing and Simulation Technique…
\texttt{SpaceMath v.2.0} with Machine Learning is an extension of the previous version which we implement observables related with LHC Higgs boson data and their projections for the High Luminosity and High Energy Large Hadron Collider. In…
Near-term quantum computers provide a promising platform for finding ground states of quantum systems, which is an essential task in physics, chemistry, and materials science. Near-term approaches, however, are constrained by the effects of…
We present some recent advances in the computational study of baryon number violation in high energy electroweak collisions. We examine classically allowed processes above the sphaleron barrier and, using a stochastic search procedure, we…
The project, aimed at the theoretical support of experiments at modern and future accelerators -- TEVATRON, LHC, electron Linear Colliders (TESLA, NLC, CLIC) and muon factories, is presented. Within this project a four-level computer system…
The NuMI facility at Fermilab will provide an extremely intense beam of neutrinos for the MINOS neutrino-oscillation experiment. The spacious and fully-outfitted MINOS near detector hall will be the ideal venue for a high-statistics,…
Reservoir Computing is a relatively recent computational framework based on a large Recurrent Neural Network with fixed weights. Many physical implementations of Reservoir Computing have been proposed to improve speed and energy efficiency.…
The Scintillating Bubble Chamber (SBC) collaboration is constructing a 10~kg liquid argon (LAr) bubble chamber at SNOLAB called SBC-SNOLAB having the main objective of detecting dark matter. One of the most novel aspects of SBC-SNOLAB is…
Quantum computers hold great promise for arriving at exact simulations of nuclear dynamical processes (e.g., scattering and reactions) that are paramount to the study of nuclear matter at the limit of stability and to explaining the…
Quantum computing is greatly advanced in recent years and is expected to transform the computation paradigm in the near future. Quantum circuit simulation plays a key role in the toolchain for the development of quantum hardware and…
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is…
Adoption of renewable energy is essential to address the challenge of climate change, but that necessitates energy storage technologies. Lithium-ion batteries, the most ubiquitous solution, are insufficient for large-scale applications, so…
Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics. In this paper, we survey recent approaches for addressing this…
Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision…
A second major upgrade of the LHCb experiment is necessary to allow full exploitation of the High Luminosity LHC for flavour physics. The new experiment will operate in Run 5 of the LHC at a luminosity up to $1.5\times…
Numeric simulations based on the Huygens-Fresnel method allow one to develop intuition about the behavior of coherent light in diffraction and interference experiments. They give an opportunity to numerically observe and appreciate a number…
We present an accurate numerical algorithm, called quantum belief propagation (QBP), for simulation of one-dimensional quantum systems at non-zero temperature. The algorithm exploits the fact that quantum effects are short-range in these…
Examining and controlling the interaction between semiconductor quantum qubits and their environment can boost semiconductor quantum technologies, which have many applications in table-top quantum computing hardware. Electron beams in…
Simulations play a key role for inference in collider physics. We explore various approaches for enhancing the precision of simulations using machine learning, including interventions at the end of the simulation chain (reweighting), at the…
Computational studies of basic models of strongly-correlated electron systems can provide guidance in the search for new materials as well as insight into the physical mechanisms responsible for their properties. Here, we illustrate this by…
The SABRE (Sodium Iodide with Active Background Rejection) experiment will search for an annually modulating signal from dark matter particles in our Galaxy using an array of ultra-pure NaI(Tl) detectors surrounded by an active scintillator…