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Related papers: CNUCTRAN: A program for computing final nuclide co…

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Precision measurements of neutron properties, like its permanent electric dipole moment, rely on understanding complex experimental setups in detail. We show how the properties of stored and transported ultracold neutron ensembles can be…

The Random Phase Approximation theory is used to calculate the total cross sections of electron neutrinos on $^{12}$C nucleus. The role of the excitation of the discrete spectrum is discussed. A comparison with electron scattering and muon…

Nuclear Theory · Physics 2007-05-23 Giampaolo Co'

The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar Information Of Nuclei) machine learning system provides an efficient and accurate route to the prediction of NMR parameters from 3-dimensional chemical structures. Here we…

Nuclear quantum effects such as zero-point energy and hydrogen tunnelling play a central role in many biological and chemical processes. The nuclear-electronic orbital (NEO) approach captures these effects by treating selected nuclei…

Structure determination by chemical-shift-driven NMR crystallography relies on comparing chemical shieldings measured in solid-state NMR experiments with simulations. However, computational cost limits the accuracy of shielding predictions,…

The study and prediction of chemical reactivity is one of the most important application areas of molecular quantum chemistry. Large-scale, fully error-tolerant quantum computers could provide exact or near-exact solutions to the underlying…

Quantum Physics · Physics 2019-09-12 Michael Kühn , Sebastian Zanker , Peter Deglmann , Michael Marthaler , Horst Weiß

This paper presents a comprehensive evaluation of the potential of Quantum Convolutional Neural Networks (QCNNs) in comparison to classical Convolutional Neural Networks (CNNs) and Artificial / Classical Neural Network (ANN) models. With…

Quantum Physics · Physics 2023-07-25 Gowri Namratha Meedinti , Kandukuri Sai Srirekha , Radhakrishnan Delhibabu

We demonstrate quantum simulations of strongly correlated nuclear many-body systems on the RIKEN-Quantinuum Reimei trapped-ion quantum computer, targeting ground states of oxygen, calcium, and nickel isotopes. By combining a hard-core-boson…

Nuclear Theory · Physics 2026-02-10 Sota Yoshida , Takeshi Sato , Takumi Ogata , Masaaki Kimura

At present, many laboratories are performing experiments to simulate theoretical models of strongly correlated systems using cold atoms in optical lattices, a program referred to as "Quantum Simulation". It is hoped that these experiments…

Superconductivity · Physics 2016-11-07 Tin-Lun Ho , Qi Zhou

The latest research of the proportionality of atomic weights of chemical elements made it possible to obtain 3 x 3 matrices for the calculation of information coefficients of proportionality Ip that can be used for 3D modeling of the…

General Physics · Physics 2012-07-20 Mikhail M. Labushev

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming…

Quantum Physics · Physics 2024-09-20 Yuri Alexeev , Maximilian Amsler , Paul Baity , Marco Antonio Barroca , Sanzio Bassini , Torey Battelle , Daan Camps , David Casanova , Young Jai Choi , Frederic T. Chong , Charles Chung , Chris Codella , Antonio D. Corcoles , James Cruise , Alberto Di Meglio , Jonathan Dubois , Ivan Duran , Thomas Eckl , Sophia Economou , Stephan Eidenbenz , Bruce Elmegreen , Clyde Fare , Ismael Faro , Cristina Sanz Fernández , Rodrigo Neumann Barros Ferreira , Keisuke Fuji , Bryce Fuller , Laura Gagliardi , Giulia Galli , Jennifer R. Glick , Isacco Gobbi , Pranav Gokhale , Salvador de la Puente Gonzalez , Johannes Greiner , Bill Gropp , Michele Grossi , Emanuel Gull , Burns Healy , Benchen Huang , Travis S. Humble , Nobuyasu Ito , Artur F. Izmaylov , Ali Javadi-Abhari , Douglas Jennewein , Shantenu Jha , Liang Jiang , Barbara Jones , Wibe Albert de Jong , Petar Jurcevic , William Kirby , Stefan Kister , Masahiro Kitagawa , Joel Klassen , Katherine Klymko , Kwangwon Koh , Masaaki Kondo , Doga Murat Kurkcuoglu , Krzysztof Kurowski , Teodoro Laino , Ryan Landfield , Matt Leininger , Vicente Leyton-Ortega , Ang Li , Meifeng Lin , Junyu Liu , Nicolas Lorente , Andre Luckow , Simon Martiel , Francisco Martin-Fernandez , Margaret Martonosi , Claire Marvinney , Arcesio Castaneda Medina , Dirk Merten , Antonio Mezzacapo , Kristel Michielsen , Abhishek Mitra , Tushar Mittal , Kyungsun Moon , Joel Moore , Mario Motta , Young-Hye Na , Yunseong Nam , Prineha Narang , Yu-ya Ohnishi , Daniele Ottaviani , Matthew Otten , Scott Pakin , Vincent R. Pascuzzi , Ed Penault , Tomasz Piontek , Jed Pitera , Patrick Rall , Gokul Subramanian Ravi , Niall Robertson , Matteo Rossi , Piotr Rydlichowski , Hoon Ryu , Georgy Samsonidze , Mitsuhisa Sato , Nishant Saurabh , Vidushi Sharma , Kunal Sharma , Soyoung Shin , George Slessman , Mathias Steiner , Iskandar Sitdikov , In-Saeng Suh , Eric Switzer , Wei Tang , Joel Thompson , Synge Todo , Minh Tran , Dimitar Trenev , Christian Trott , Huan-Hsin Tseng , Esin Tureci , David García Valinas , Sofia Vallecorsa , Christopher Wever , Konrad Wojciechowski , Xiaodi Wu , Shinjae Yoo , Nobuyuki Yoshioka , Victor Wen-zhe Yu , Seiji Yunoki , Sergiy Zhuk , Dmitry Zubarev

Crystallization is a key step in macromolecular structure determination by crystallography. While a robust theoretical treatment of the process is available, due to the complexity of the system, the experimental process is still largely one…

Biomolecules · Quantitative Biology 2016-08-02 Irem Altan , Patrick Charbonneau , Edward H. Snell

Binarized neural networks, or BNNs, show great promise in edge-side applications with resource limited hardware, but raise the concerns of reduced accuracy. Motivated by the complex neural networks, in this paper we introduce complex…

Neural and Evolutionary Computing · Computer Science 2021-04-21 Yanfei Li , Tong Geng , Ang Li , Huimin Yu

Simulating quantum physical processes has been one of the major motivations for quantum information science. Quantum channels, which are completely positive and trace preserving processes, are the standard mathematical language to describe…

Quantum Physics · Physics 2024-02-01 Hang Li , Kai Wang , Shijie Wei , Fan Yang , Xinyu Chen , Barry C. Sanders , Dong-Sheng Wang , Gui-Lu Long

A simple Monte Carlo procedure is described for simulating the multiple scattering and absorption of electrons with the incident energy in the range 1-50 keV moving through a slab of uniformly distributed material of given atomic number,…

Materials Science · Physics 2007-05-23 Nima Ghal-eh , Mohammad Farhad Rahimi , Mehrnoush Manouchehri

Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

We present here a detailed description of the model of ran-driven nuclear transduction in living cells to be published elswere. The mathematical model presented is the first to account for the active transport of molecules along the…

Numerical Analysis · Mathematics 2009-07-07 A. Cangiani

Grid decarbonization for climate change requires dispatchable carbon-free energy like nuclear fusion. The tokamak concept offers a promising path for fusion, but one of the foremost challenges in implementation is the occurrence of…

Machine Learning · Computer Science 2023-12-05 William F Arnold , Lucas Spangher , Christina Rea

Simulating the nonequilibrium dynamics of thermal states is a fundamental problem across scales from high energy to condensed matter physics. Quantum computers may provide a way to solve this problem efficiently. Preparing a thermal state…

Quantum Physics · Physics 2023-11-03 Jason Saroni , Henry Lamm , Peter P. Orth , Thomas Iadecola

Motivation: A Chemical Reaction Network (CRN) is a set of chemical reactions, which can be very complex and difficult to analyze. Indeed, dynamical properties of CRNs can be described by a set of non-linear differential equations that…

Computational Engineering, Finance, and Science · Computer Science 2021-07-02 Lucia Nasti , Roberta Gori , Paolo Milazzo , Federico Poloni
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