Results 111 to 120 of about 189,782 (285)

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

Advanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh, Raiyan Siddique, Sarah S. Sharif, Yaser Mike Banad   +3 more
wiley   +1 more source

Coupled Electron Ion Monte Carlo Calculations of Dense Metallic Hydrogen

, 2004
We present a new Monte Carlo method which couples Path Integral for finite temperature protons with Quantum Monte Carlo for ground state electrons, and we apply it to metallic hydrogen for pressures beyond molecular dissociation.
Carlo Pierleoni, D. J. Stevenson, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, David M. Ceperley, M. Dewing, Markus Holzmann, W. J. Nellis   +8 more
core   +2 more sources

From Monte Carlo to quantum computation [PDF]

Mathematics and Computers in Simulation, 2003
Quantum computing was so far mainly concerned with discrete problems. Recently, E. Novak and the author studied quantum algorithms for high dimensional integration and dealt with the question, which advantages quantum computing can bring over classical deterministic or randomized methods for this type of problem.
openaire   +2 more sources

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Impact of on-site and inter-site Coulomb interactions on the electronic, magnetic and thermomagnetic properties of LaFeO3: Insights from DFT + U and DFT + U + V

Results in Physics
LaFeO3, a widely studied antiferromagnetic perovskite oxide with complex electronic and magnetic interactions, remains a challenging system for accurate theoretical modeling.
Zahra Mosleh, Mahdi TarighiAhmadpour
doaj   +1 more source

Symmetry Enforced Self-Learning Monte Carlo Method Applied to the Holstein Model

, 2018
Self-learning Monte Carlo method (SLMC), using a trained effective model to guide Monte Carlo sampling processes, is a powerful general-purpose numerical method recently introduced to speed up simulations in (quantum) many-body systems.
Batrouni, George, Chen, Chuang, Liu, Junwei, Meng, Zi Yang, Scalettar, Richard, Xu, Xiao Yan   +5 more
core   +3 more sources

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

Low Temperature Properties of Quantum Antiferromagnetic Chains with Alternating Spins S=1 and 1/2

, 1996
We study the low-temperature properties of S=1 and 1/2 alternating spin chains with antiferromagnetic nearest-neighbor exchange couplings using analytical techniques as well as a quantum Monte Carlo method.
, de Vega H J, Fujii M, H-J Mikeska, Haldane F D M, Kahn O, Kolezhuk A K, Lieb E, Mattis D C, S Brehmer, Shoji Yamamoto, Suzuki M   +11 more
core   +1 more source

Real‐Time Sampling‐Based Model Predictive Control Based on Reverse Kullback–Leibler Divergence and Its Adaptive Acceleration

Advanced Intelligent Systems, EarlyView.
This study presents a new sampling‐based model predictive control minimizing reverse Kullback‐Leibler divergence to quickly find a local optimum. In addition, a modified Nesterov's acceleration method is introduced for faster convergence. The method is effective for real‐time simulations and real‐world operability improvement on a force‐driven mobile ...
Taisuke Kobayashi, Kota Fukumoto
wiley   +1 more source

Control Strategies in Guanine Biocrystallization

Angewandte Chemie, EarlyView.
Biological guanine crystals produce spectacular photonic phenomena in animals and hold great promise as new, sustainable optical materials. We review how organisms precisely control the structure, morphologies, and resulting optical properties of these crystals using a set of ingenious ‘design’ strategies, including control of pH, template‐directed ...
Shashanka S. Indri, Avital Wagner, Benjamin A. Palmer   +2 more
wiley   +2 more sources