Quantum computing will provide breakthroughs in chemistry. How?
It is expected that quantum computing will allow us to solve computational problems that can not be solved by existing classical computing methods. Currently accepted that the very first discipline, which received a boost from quantum advances, this quantum chemistry. In 1982, physicist Richard Feynman, winner of the Nobel Prize noticed that the simulation, and then the analysis of molecules - so complicated case to a digital computer, it is virtually useless for these cases.
The problem was not the fact that the equations governing these simulations, have been difficult, no. In fact, they were relatively simple and straightforward, and knew about them for many years. The problem was that most interest scientists molecules containing hundreds of electrons, and each of these electrons interact with each other electron quantum mechanically - that led to millions of interactions that could not handle even the most powerful computer.
To overcome the quantum nature of these equations, Feynman proposed the creation of quantum computers that will perform calculations based on quantum physics laws as a response. Unfortunately, such a precise manipulation of individual quantum objects was virtually impossible from a technical point of view. Joke, which had a lot to tire in the last 35 years, was the fact that quantum computers "will be in ten years." Over the past couple of years, what was once a distant dream, slowly it becomes a reality. Quantum computers are beginning to emerge, millions of programs work through the cloud, useful applications to take shape.
The power of a quantum computer can roughly estimate the number of qubits, or quantum bits: each qubit may be 1 and 0 at the same time. There are several hardware promising approach to quantum computing, including superconductivity, ion traps and topological transistors. Each of them has advantages and disadvantages, but superconductors ranks first in terms of scalability. Google, IBM and Intel use this approach to create quantum processors in the range from 49 to 72 qubits. qubit quality is constantly improving.
A breakthrough in chemistry
Breakthrough Scientists at the Center for Quantum Computing in Cambridge and their partners from JSR Corp is the ability to simulate multireferensnye states of molecules. Multireferensnye state often necessary to describe the "excited states," which occur when molecules interact.
The reason that such a simulation is of great importance is the fact that the classical digital computers almost can not do anything with multireferensnymi states; in many cases, the classical methods of calculation, not only quantitatively, but also qualitatively unable to describe the electronic structure of molecules. An important issue that was recently solved was to find a way that a quantum computer could perform calculations efficiently and with the desired chemical accuracy for the real world. The program was launched on 20-qubit processor IBM.
Why chemistry came to the attention of such interest? Chemistry - one of the most profitable commercial applications for several reasons. Scientists hope to find more energy-efficient materials that can be used in batteries or solar panels. There are also environmental benefits: about two percent of the world's energy is spent on the production of fertilizers, which are terribly inefficient and can be improved by a complex chemical analysis.
Finally, there are applications in personalized medicine, with the ability to predict how pharmaceutical drugs will affect people based on their genetics. In the long term - the ability to develop a drug for a specific person for the most effective treatment and minimize side effects.
In CQC and JSR Corp had two strategies that have allowed scientists to carry out this breakthrough. First, they used their own CQC compiler for the most efficient conversion of computer program instructions to manipulate the qubit. Such efficiency is particularly important in modern malokubitnyh machine, in which each qubit is important and necessary, and the execution speed is crucial. Second, they used a quantum machine learning, a special subfield of machine learning that uses the amplitude of the vector, not just probability. The method used is a quantum machine learning was developed specifically for malokubitnyh quantum computers, a partial discharge by means of traditional processors.
In the next few years it is expected to significantly improve the quantum of both hardware and software. As soon as the calculations become more accurate, more industries can take advantage of quantum computing applications, including quantum chemistry. Gartner predicts that within four years, 20% of enterprises will budget for quantum computing. In ten years, they will become an integral component technologies.
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