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Quantum algorithms: an overview

#artificialintelligence

A quantum computer is a machine designed to use quantum mechanics to do things which cannot be done by any machine based only on the laws of classical physics. These applications are based on quantum algorithms--algorithms that run on a quantum computer and achieve a speedup, or other efficiency improvement, over any possible classical algorithm. Although large-scale general-purpose quantum computers do not yet exist, the theory of quantum algorithms has been an active area of study for over 20 years. Here we aim to give a broad overview of quantum algorithmics, focusing on algorithms with clear applications and rigorous performance bounds, and including recent progress in the field. Contrary to a rather widespread popular belief that quantum computers have few applications, the field of quantum algorithms has developed into an area of study large enough that a brief survey such as this cannot hope to be remotely comprehensive.


The best of both worlds: How to solve real problems on modern quantum computers

#artificialintelligence

In recent years, quantum devices have become available that enable researchers--for the first time--to use real quantum hardware to begin to solve scientific problems. However, in the near term, the number and quality of qubits (the basic unit of quantum information) for quantum computers are expected to remain limited, making it difficult to use these machines for practical applications. A hybrid quantum and classical approach may be the answer to tackling this problem with existing quantum hardware. Researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory and Los Alamos National Laboratory, along with researchers at Clemson University and Fujitsu Laboratories of America, have developed hybrid algorithms to run on quantum machines and have demonstrated them for practical applications using IBM quantum computers (see below for description of Argonne's role in the IBM Q Hub at Oak Ridge National Laboratory [ORNL]) and a D-Wave quantum computer. "This approach will enable researchers to use near-term quantum computers to solve applications that support the DOE mission. For example, it can be applied to find community structures in metabolic networks or a microbiome," says Yuri Alexeev, principal project specialist, Computational Science division The team's work is presented in an article entitled "A Hybrid Approach for Solving Optimization Problems on Small Quantum Computers" that appears in the June 2019 issue of the Institute of Electrical and Electronics Engineers (IEEE) Computer Magazine.


What It Will Take for Quantum Computers to Turbocharge Machine Learning

#artificialintelligence

Quantum computers could give the machine learning algorithms at the heart of modern artificial intelligence a dramatic speed up, but how far off are we? An international group of researchers has outlined the barriers that still need to be overcome. This year has seen a surge of interest in quantum computing, driven in part by Google's announcement that it will demonstrate "quantum supremacy" by the end of 2017. That means solving a problem beyond the capabilities of normal computers, which the company predicts will take 49 qubits--the quantum computing equivalent of bits. As impressive as such a feat would be, the demonstration is likely to be on an esoteric problem that stacks the odds heavily in the quantum processor's favor, and getting quantum computers to carry out practically useful calculations will take a lot more work.


IBM's latest trick: Turning noisy quantum bits into machine learning magic

#artificialintelligence

IBM's figured out how to ignore noisy qubits and run machine learning algorithms in quantum feature spaces. The age of quantum algorithms is upon us. A team of IBM researchers, alongside scientists from MIT and Oxford, created a pair of quantum classification algorithms and then experimentally implemented them on a hybrid system utilizing a 2-qubit quantum computer and a classical superconductor. Basically, they demonstrated that quantum computers can provide advantages in machine learning that classical computers, alone, cannot. Here we propose and experimentally implement two quantum algorithms on a superconducting processor.


Google claims it has achieved 'quantum supremacy' – but IBM disagrees

The Guardian

For Google it was a historic announcement: a declaration that it had won the race to achieve "quantum supremacy" – the moment that a futuristic quantum computer performed a task that stumped even the most powerful standard computer in the world. But for all the fanfare, which saw Google's CEO Sundar Pichai compare the feat to building the first rocket to reach space, the claim has sparked a bunfight. The tech firm's rival, IBM, was swift to dismiss the excitement. Google has not, it asserts, achieved the highly prized goal of quantum supremacy. Google published its claim in the journal Nature on Wednesday after an earlier report on the work appeared briefly on a Nasa website last month.