Solving 'barren plateaus' is the key to quantum machine learning

Many machine learning algorithms on quantum computers suffer from the dreaded "barren plateau" of unsolvability, where they run into dead ends on optimization problems. This challenge had been relatively unstudied—until ...

Machine learning speeds up quantum chemistry calculations

Quantum chemistry, the study of chemical properties and processes at the quantum scale, has opened many paths to research and discovery in modern chemistry. Without ever handling a beaker or a test tube, chemists can make ...

Calculating the benefits of exascale and quantum computers

A quintillion calculations a second. That's one with 18 zeros after it. It's the speed at which an exascale supercomputer will process information. The Department of Energy (DOE) is preparing for the first exascale computer ...

Quantum machines learn 'quantum data'

Skoltech scientists have shown that quantum enhanced machine learning can be used on quantum (as opposed to classical) data, overcoming a significant slowdown common to these applications and opening a "fertile ground to ...

Quantum autoencoders to denoise quantum measurements

Many research groups worldwide are currently trying to develop instruments to collect high-precision measurements, such as atomic clocks or gravimeters. Some of these researchers have tried to achieve this using entangled ...

Machine learning to scale up the quantum computer

,,Quantum computers are expected to offer tremendous computational power for complex problems –currently intractable even on supercomputers—in the areas of drug design, data science, astronomy and materials chemistry ...

Machine learning implemented for quantum optics

As machine learning continues to surpass human performance in a growing number of tasks, scientists at Skoltech have applied deep learning to reconstruct quantum properties of optical systems.

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