Results 71 to 80 of about 12,571,794 (304)

Optimized monte carlo methods [PDF]

, 2008
I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, like Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. I discuss reweighted data analysis and multi-hystogramming. I introduce Simulated Tempering, and as an example its application to the Random Field Ising Model.
openaire   +2 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Monte Carlo Simulation with Asymptotic Method (Published in "Journal of Japan Statistical Society", Vol.35-2, 171-203, 2005. ) [PDF]

We shall propose a new computational scheme with the asymptotic method to achieve variance reduction of Monte Carlo simulation for numerical analysis especially in finance. We not only provide general scheme of our method, but also show its effectiveness
Nakahiro Yoshida, Akihiko Takahashi
core  

When Poor Exciton Dissociation Limits Photocurrents in Organic Solar Cells: Why Low Offset Non‐Fullerene Acceptor Blends Can't Be Efficient

Advanced Materials, EarlyView.
The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
wiley   +1 more source

Fast Simulation Study of Muon Absorption Radiography Based on Energy Loss Calculation

Yuanzineng kexue jishu, 2022
Using natural cosmic ray muon as radiation source, muon absorption radiography can realize nondestructive detection of large-scale geological objects. Simulation analysis is an important step in the application of muon absorption radiography.
DING Wenwan;LIU Yuanyuan;WANG Li;SU Ning;CHENG Jianping;HAN Jianwu;ZHEN Gang
doaj  

Definition of Maintenance Policies in Power Systems Using a Sequential Monte Carlo

U.Porto Journal of Engineering, 2015
This paper reports an application of a simulationmethod called chronological Monte Carlo to evaluate power systems reliability. The Monte Carlo methods are, nowadays, the most widely used method for the estimation of reliability indices.
João Silva
doaj   +1 more source

Resistance to Overdoping Allows Over 2000 S cm−1 Conductivity in P(g3BTTT) With Anion‐Exchange Doping

Advanced Materials, EarlyView.
Anion‐exchange doping of conjugated polymers is an effective way to achieve high conductivities. Here, we report over 2000 S cm−1 electrical conductivity for doped P(g3BTTT). In addition, we show that P(g3BTTT) sustains exceptionally high doping levels without any drop in the charge mobility.
Basil Hunger, Maximilian M. Horn, Eva Röck, Diego Rosas Villalva, Lize Bynens, Jochen Vanderspikken, Christina Kousseff, Silène Gobeil, Olivier Bardagot, Nesibe Akmanşen‐Kalayci, Sarah H. Tolbert, Iain McCulloch, Wouter Maes, Demetra Tsokkou, Natalie Banerji   +14 more
wiley   +1 more source

Monte Carlo simulation for statistical Hauser-Feshbach theory

EPJ Web of Conferences, 2010
Monte Carlo simulations for particle and γ-ray emissions from a compound nucleus based on the Hauser-Feshbach statistical theory are performed. The Monte Carlo method is applied to the neutron induced nuclear reactions on 56Fe, and the results are ...
Watanabe T., Chadwick M.B., Talou P., Kawano T.   +3 more
doaj   +1 more source

Monte Carlo and kinetic Monte Carlo methods

, 2009
This article reviews the basic computational techniques for carrying out multi-scale simulations using statistical methods, with the focus on simulations of epitaxial growth. First, the statistical-physics background behind Monte Carlo simulations is briefly described.
openaire   +2 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source