Use of Monte Carlo simulation: an empirical study of German, Austrian and Swiss controlling departments

2015 ◽  
Vol 26 (2-3) ◽  
pp. 249-273 ◽  
Author(s):  
Cathérine Grisar ◽  
Matthias Meyer
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Empirical Study

scholarly journals Iterative quantum amplitude estimation

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Dmitry Grinko ◽  
Julien Gacon ◽  
Christa Zoufal ◽  
Stefan Woerner
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Empirical Study ◽  
Estimation Accuracy ◽  
Phase Estimation ◽  
Rigorous Analysis ◽  
Logarithmic Factor ◽  
Small Constant ◽  
Amplitude Estimation ◽  
Quantum Amplitude

AbstractWe introduce a variant of Quantum Amplitude Estimation (QAE), called Iterative QAE (IQAE), which does not rely on Quantum Phase Estimation (QPE) but is only based on Grover’s Algorithm, which reduces the required number of qubits and gates. We provide a rigorous analysis of IQAE and prove that it achieves a quadratic speedup up to a double-logarithmic factor compared to classical Monte Carlo simulation with provably small constant overhead. Furthermore, we show with an empirical study that our algorithm outperforms other known QAE variants without QPE, some even by orders of magnitude, i.e., our algorithm requires significantly fewer samples to achieve the same estimation accuracy and confidence level.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

A Monte Carlo simulation study of associated liquid crystals

1999 ◽  
Vol 97 (11) ◽  
pp. 1173-1184 ◽  
Author(s):  
R. Berardi, M. Fehervari, C. Zannoni
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Liquid Crystals ◽  
Simulation Study ◽  
Monte Carlo Simulation Study

Applying Meta-Analysis to Adverse Impact Assessment: A Monte Carlo Simulation

2006 ◽  
Author(s):  
John F. Skinner ◽  
Scott B. Morris
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Impact Assessment ◽  
Meta Analysis ◽  
Adverse Impact

Monte Carlo simulation for reference tissue-based linear analysis of [11C]MP4A AND [11C]MP4P: Assessment of optimal regions and optimization for precise measurement of brain AChE activity

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S644-S644
Author(s):  
Koichi Sato ◽  
Kiyoshi Fukushi ◽  
Hitoshi Shinotoh ◽  
Shin-ichiro Nagatsuka ◽  
Noriko Tanaka ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ache Activity ◽  
Precise Measurement ◽  
Linear Analysis ◽  
Reference Tissue ◽  
Brain Ache ◽  
Brain Ache Activity
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