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Quantum advances: Three recent innovations with quantum computing

Quantum computers will soon be optimizing financial trading strategies and utilizing quantum chemistry to develop new materials.

IBM Quantum System One in Ehningen, Germany (4 June 2021) Photo: IBM Research (CC BY 2.0)
IBM Quantum System One in Ehningen, Germany (4 June 2021) Photo: IBM Research (CC BY 2.0)

Quantum computing, although some steps away from realizing its true potential, continues to advance. Digital Journal reviews three recent innovations with this advanced stage of computing.

Going forwards we can expect quantum computers to be optimizing financial trading strategies, utilizing quantum chemistry to develop new materials, and applying artificial intelligence technology to natural language processing.

Developing time crystals

Scientists from Stanford University, Google Quantum AI, the Max Planck Institute for Physics of Complex Systems and Oxford University, have outlined the process for creating a time crystal. This was performed using Google’s Sycamore quantum computing hardware.

In terms of what the mysterious sounding ‘time crystal’ is, a time crystal repeats in time infinitely and without any further input of energy. An analogy is a clock that runs forever without any batteries. Scientists consider this to be a separate phase of matter and hitherto it has been a longstanding challenge to experimentally demonstrate the existence of time crystals.

The research has been published in the journal Nature, with the research titled “Time-Crystalline Eigenstate Order on a Quantum Processor.”

Breaking records

Technologists have set a world record for innovation in quantum computing. This is in the form of most accurate entangling gate ever demonstrated without lasers.

An entangling gate takes two qubits (quantum bits) and creates an operation on the secondary qubit that is conditioned on the state of the first qubit. This is important since the universal control of multiple qubits (the ability to entangle qubits and to perform arbitrary individual qubit operation) is essential to building more efficient quantum machines.

Improving financial forecasting

As an example of a new step with application of quantum computers falls within the financial sphere. A new approach has been developed, designed to implement novel credit risk analysis algorithms using quantum computers. This will evolve from a partnership between Classiq, a quantum computing company and NTT DATA. The aim is for a significant advance with financial modelling development to occur.

The outcome will be for Classiq’s platform to help enable NTT DATA to capture, synthesize, analyze and optimize quantum algorithms that scale. This will lead to the implementation of new credit risk analysis algorithms. In financial circles, credit risk analysis exists to determine the creditworthiness of borrowers or vendors to quantify and limit the risk of loss to the lender.

The program behind this will be hardware-independent and not limited by historical approaches to creating quantum algorithms.

These types of algorithms typically require a greater number of qubits. The new platform has been honed to produce intricate quantum circuits without resorting to the process of manual, gate-level programming.

Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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