Therefore, two approaches are proposed which exploit quantum computing to solve diagnosis problems: The first method employs Grover's algorithm, and the second is based on the Quantum Approximate Optimization Algorithm. To show the industrial application, we present an integrated approach to learn the...
Quantum computers are best-suited for solving problems with a limited volume of output, and—ideally—those with a limited amount of input. These restrictions might lead you to assume that the scope of what quantum computers can do is narrow, but the exact opposite is true. Quantum compu...
Computing is often about decisions with yes or no answers. By analogy, amedical test(type of problem) checks if a patient's specimen (an instance of the problem) has a certain disease indicator (yes or no answer). The instance, represented in a Turing machine in digital form, is the in...
The MoFe protein, left, and the FeMoco, right, would be able to be analyzed by quantum computing to help reveal the complex chemical system behind nitrogen fixation by the enzyme nitorgense. With rapid recent advances in quantum technology, we have drawn ever closer to the threshold of quantu...
“You have made friends and contacts that will stay with you for the rest of your career, and I hope it is just the start of your engagement with quantum computing and the NQCC.” The success of the event paves the way for future hackathons, most likely focused on specific industry ...
There are many difficult challenges for realizing quantum computers. Long-term, extensive R&D is required. Through open innovation with influential research institutes around the world, Fujitsu Laboratories has started R&D of quantum computing in all fields, ranging from hardware to software, and from ...
that the new chip helps figure out how to correct errors — like flipping a binary code from a 1 to a 0 — that occasionally pop up when working with quantum computing queries. If quantum computing errors are mitigated, it could pave the way for more usable quantum compu...
Quantum Approximate Optimization algorithm (QAOA) aims to search for approximate solutions to discrete optimization problems with near-term quantum computers. As there are no algorithmic guarantee possible for QAOA to outperform classical computers, with
for photonic realization and scalable to large problem sizes with the advances in high-dimensional quantum information manipulation and large scale linear-optical systems. Our results open an essentially new route toward quantum advantages and extend the computational capability of optical quantum computing...
But quantum computing is still in its early days, and there is much progress to be made. One point for improvement is error correction. Classic computers have built-in error-correction code with alpha particles that are flipping bits into their memory all of the time. ...