Google's cryostats reach temperatures of 10 millikelvin to run its quantum processors. From aspects of quantum entanglement to chemical reactions with large molecules, many features of the world cannot be described efficiently with conventional computers based on binary logic. The solution, as physicist Richard Feynman realized three decades ago1, is to use quantum processors that adopt a blend of classical states simultaneously, as matter does. Many technical hurdles must be overcome for such quantum machines to be practical, however. These include noise control and improving the fidelity of operations acting on the quantum states that encode the information.
Google has assembled a team of experts trying to craft a quantum computer Financial services, machine learning and other industries could benefit Quantum computing especially useful for complex "optimization" problems It depends on mind-bending physics and ultra-cold temperatures but quantum computing could bring about a new era in processing power that promises to revolutionize everything from artificial intelligence to high finance. The field of quantum computing is still in its infancy but it was given a sizable boost when Google announced in September that it is partnering with experts from the University of California Santa Barbara to develop quantum computing technology as part of its Quantum Artificial Intelligence Lab team. The project also sees Google pairing up with NASA and the Universities Space Research Association to create technology that could become the world's fastest supercomputer. In a traditional computer, circuits are either on or off, and use binary code of ones and zeros for solving problems. A quantum computer uses quantum bits -- called qubits -- and has circuits which exist in all possible states at the same time -- a one, a zero and everything in between.
It's not sci-fi: quantum computing is here and it's changing the way we solve tough problems. Quantum computers make use of the quantum mechanical properties of special materials to perform calculations in ways that are not possible on traditional computing systems. In this talk, we will give a crash course on quantum computing and describe the current state quantum computing technology. We'll focus on a special type of quantum optimization called quantum annealing and its applications in the growing field of machine learning. Joseph "JD" Dulny is a physicist and data scientist with the Booz Allen Strategic Innovation Group (R&D).
When it comes to making bucketloads of cash, any edge is worth pursuing. And for hedge funds, that now means flirting with the idea of using quantum computers in an attempt to give their analysis a speed boost. The Financial Times reports (paywall) that hedge funds including Two Sigma, Renaissance, DE Shaw, and WorldQuant are all experimenting with quantum computing systems. It also quotes the CEO of the (controversial) quantum computing firm D-Wave as saying that the company has had "a lot" of conversations with hedge funds and banks. It's not yet clear what kinds of devices the hedge funds are working with, though.
In the near future, quantum computing could change the world. Download the free report to learn about the the quantum computing industry landscape and how close we are to quantum supremacy. Take climate change for example: Because of the complexity of the climate system, seemingly endless data, and growing limitations on today's computing power, no classical computer (like your desktop) can simulate the earth's climate changes with 100% accuracy. Quantum computers, on the other hand, are supercomputers equipped with advanced processing powers. Taking tons of climate variables into account, they could create data-driven models to help forecast weather patterns and prepare for natural disasters. Beyond climate simulations, these advanced computing systems could make ultra-fast calculations on the biggest and most complex datasets -- and the technology is certainly catching media attention. But how exactly does it work? Quantum computers can process massive and complex datasets more efficiently than classical computers. They use the fundamentals of quantum mechanics to speed up the process of solving complex computations.