Occurrence Rates and Heating Effects of Tangential and Rotational Discontinuities as Obtained from Three-dimensional Simulation of Magnetohydrodynamic Turbulence

In solar wind, magnetohydrodynamic (MHD) discontinuities are ubiquitous and often found to be at the origin of turbulence intermittency. They may also play a key role in the turbulence dissipation and heating of the solar wind. The tangential (TD) and rotational (RD) discontinuities are the two most important types of discontinuities. Recently, the connection between turbulence intermittency and proton thermodynamics has been being investigated observationally. Here we present numerical results from three-dimensional MHD simulation with pressure anisotropy and define new methods to identify and to distinguish TDs and RDs. Three statistical results obtained about the relative occurrence rates and heating effects are highlighted: (1) RDs tend to take up the majority of the discontinuities along with time; (2) the thermal states embedding TDs tend to be associated with extreme plasma parameters or instabilities, while RDs do not; (3) TDs have a higher average T as well as perpendicular temperature $T_\perp$. The simulation shows that TDs and RDs evolve and contribute to solar wind heating differently. These results will inspire our understanding of the mechanisms that generate discontinuities and cause plasma heating.Comment: 5 Figures, Submitted to Astrophys. J. Lett., in the process of refereein

Optimizing Shot Assignment in Variational Quantum Eigensolver Measurement

The rapid progress in quantum computing has opened up new possibilities for tackling complex scientific problems. Variational quantum eigensolver (VQE) holds the potential to solve quantum chemistry problems and achieve quantum advantages. However, the measurement step within the VQE framework presents challenges. It can introduce noise and errors while estimating the objective function with a limited measurement budget. Such error can slow down or prevent the convergence of VQE. To reduce measurement error, many repeated measurements are needed to average out the noise in the objective function. By consolidating Hamiltonian terms into cliques, simultaneous measurements can be performed, reducing the overall measurement shot count. However, limited prior knowledge of each clique, such as noise level of measurement, poses a challenge. This work introduces two shot assignment strategies based on estimating the standard deviation of measurements to improve the convergence of VQE and reduce the required number of shots. These strategies specifically target two distinct scenarios: overallocated and underallocated shots. The efficacy of the optimized shot assignment strategy is demonstrated through numerical experiments conducted on a H$_2$ molecule. This research contributes to the advancement of VQE as a practical tool for solving quantum chemistry problems, paving the way for future applications in complex scientific simulations on quantum computers

Formation of Rotational Discontinuities in Compressive three-dimensional MHD Turbulence

Measurements of solar wind turbulence reveal the ubiquity of discontinuities. In this study, we investigate how the discontinuities, especially rotational discontinuities (RDs), are formed in magnetohydrodynamic (MHD) turbulence. In a simulation of the decaying compressive three-dimensional (3-D) MHD turbulence with an imposed uniform background magnetic field, we detect RDs with sharp field rotations and little variations of magnetic field intensity as well as mass density. At the same time, in the de Hoffman-Teller (HT) frame, the plasma velocity is nearly in agreement with the Alfv\'{e}n speed, and is field-aligned on both sides of the discontinuity. We take one of the identified RDs to analyze in details its 3-D structure and temporal evolution. By checking the magnetic field and plasma parameters, we find that the identified RD evolves from the steepening of the Alfv\'{e}n wave with moderate amplitude, and that steepening is caused by the nonuniformity of the Alfv\'{e}n speed in the ambient turbulence.Comment: Five figures enclosed. Submitted to Astrophys. J., Under referrin

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Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88118/1/24749_ftp.pd

SecureBoost Hyperparameter Tuning via Multi-Objective Federated Learning

SecureBoost is a tree-boosting algorithm leveraging homomorphic encryption to protect data privacy in vertical federated learning setting. It is widely used in fields such as finance and healthcare due to its interpretability, effectiveness, and privacy-preserving capability. However, SecureBoost suffers from high computational complexity and risk of label leakage. To harness the full potential of SecureBoost, hyperparameters of SecureBoost should be carefully chosen to strike an optimal balance between utility, efficiency, and privacy. Existing methods either set hyperparameters empirically or heuristically, which are far from optimal. To fill this gap, we propose a Constrained Multi-Objective SecureBoost (CMOSB) algorithm to find Pareto optimal solutions that each solution is a set of hyperparameters achieving optimal tradeoff between utility loss, training cost, and privacy leakage. We design measurements of the three objectives. In particular, the privacy leakage is measured using our proposed instance clustering attack. Experimental results demonstrate that the CMOSB yields not only hyperparameters superior to the baseline but also optimal sets of hyperparameters that can support the flexible requirements of FL participants.Comment: FL-ICAI'2