Вход на сайт

Просмотр новости

Найдите то, что Вас интересует

Neural networks unlock larger quantum simulations with lower computational costs

Дата публикации: 22-07-2026 20:40:07

In recent years, research using artificial intelligence to predict material properties has advanced rapidly. Neural network quantum Monte Carlo methods have attracted attention as highly accurate simulation techniques. However, their extremely high computational cost has limited their application to small molecular systems. This study introduces a new computational method that overcomes this limitation.

Основное содержимое страницы с новостью.

🛡️

Just a quick check

We’re checking your connection to prevent automated abuse

Схожие новости

#Наименование новостиТональностьИнформативностьДата публикации
1Quantum neural networks get their first hardware test05.1727-07-2026
2Nvidia Brings The Power Of Open Source AI Models To Quantum Computing01014-04-2026
3An ordinary laptop solved a problem thought to require a quantum computer06.3620-07-2026
4Teaching machines to quiet the noise in quantum computers07.0702-02-2026
5Разработан протокол для квантовых вычислений, ускоряющий поиск решений0024-09-2025
6Quantum advantage reassessed: More realistic benchmarks for quantum algorithms06.8712-08-2026
7Quantum Zeno effect could freeze computations as qubit systems scale up08.7124-07-2026
8Создана ускоряющая работу квантовых вычислительных цепочек нейросеть0020-03-2025
9Faster quantum computers can learn from their own mistakes06.0515-07-2026
10New multiplexing scheme accelerates long-distance quantum communication07.5222-07-2026

Классификация: Наука. Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 7.62. Источник: phys.org.