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