Регистрация и место проведения
Мероприятие проводится совместно Открытым Университетом Сколково и Microsoft в Политехническом музее (г. Москва).
Дата и время: 10 апреля 2012 г., 18.30-20:00
Место проведения: Политехнический музей, Новая площадь ¾, подъезд 9, малая аудитория
Прямая трансляция: sk.ru/live
If science were a dating app, quantum physics and machine learning probably wouldn’t be a match. They’re from completely different fields and often require completely different backgrounds and skills. But, throw in a little quantum computing and, suddenly, that science-matchmaking app becomes Tinder and the attraction between the two is palpable.
Even though the extent of change that quantum computing will unleash on AI is up for debate, many experts now more than suspect that quantum computing will definitely alter AI at some level. Analysts from bank holding company BBVA, for example, point toward the natural synergy between quantum computing and AI as reasons why quantum machine learning will eventually best classical machine learning.
“Quantum machine learning can be more efficient than classic machine learning, at least for certain models that are intrinsically hard to learn using conventional computers,” says Samuel Fernández Lorenzo, a quantum algorithm researcher who collaborates with BBVA’s New Digital Businesses area. “We still have to find out to what extent do these models appear in practical applications.”
This shows the Bacon–Shor subsystem code implemented on a 15-ion chain.
Multiple heads are better than one in real world calculations. Now, a team of University of Maryland-led quantum engineers report that multiple qubits may be better than one when it comes to error-corrections.
In what’s been described as a foundational step toward using quantum computers to tackle practical problems, the team combined nine qubits — a quantum bit — to make a single, improved logical qubit. A logical qubit can be used to probe for mistakes that extremely sensitive quantum computers are subject to, according to the researchers.
In the paper, which was just published in Nature, the team write that “Although fault-tolerant design works in principle, it has not previously been demonstrated in an error-corrected physical system with native noise characteristics. Here we experimentally demonstrate fault-tolerant circuits for the preparation, measurement, rotation and stabilizer measurement of a Bacon–Shor logical qubit using 13 trapped ion qubits.”
Nine of the qubits were termed data qubits and the four remaining are referred to as ancilla — or extra — qubits. The logical qubit was based on a quantum error correction code to easily detect and correct errors and made it to be fault-tolerant, or minimize the negative effects of errors.
“Qubits composed of identical atomic ions are natively very clean by themselves,” said Christopher Monroe, who is a Fellow of the Joint Center for Quantum Information and Computer Science and a College Park Professor in the Department of Physics at the University of Maryland in a university news release. “However, at some point, when many qubits and operations are required, errors must be reduced further, and it is simpler to add more qubits and encode information differently. The beauty of error correction codes for atomic ions is they can be very efficient and can be flexibly switched on through software controls.”
Всем привет! В этой статье мы рассмотрим пример работы с объемным аудио в Unity для консольных и ПК проектов. На данном примере будет описан пайплайн работы с аудио на крупном проекте с множеством источников звука, HRTF и др.