Singapore unveils new projects to boost quantum computing initiatives

Singapore has launched two new national quantum programmes to bolster developments in the field of quantum computing.

The first programme – National Quantum Computing Hub (NQCH) – will focus on accelerating talent development and allow researchers to explore the different ways in which quantum computing can foster financial and chemical sectors.

On the other hand, the second programme, National Quantum Fabless Foundry (NQFF), will facilitate micro and nanofabrication of quantum devices.

Speaking at Asia Tech x Singapore Summit, Heng Swee Keat, Deputy Prime Minister and Coordinating Minister for Economic Policies of Singapore stated that the country’s investment in quantum computing not only helps brace for the future but also proactively shape the future.

The newly launched programmes fall under the umbrella of the Quantum Engineering Programme (QEP) 2.0, which is designed to solve real-world challenges using quantum technology and eventually scale up Singapore’s quantum engineering capabilities.

For the unversed, quantum computing channelizes the laws of quantum mechanics to address complex problem-solving for classical computers at enhanced speed and efficiency by building multidimensional spaces allowing patterns linking individual data points to appear.

As it caters to a broad spectrum of industries, quantum computing offers limitless scope for different means of applications.

Dr. Si-Hui Tan, Chief Science Officer at Horizon Quantum Computing, emphasized on the potential of quantum technology during the Summit saying that the expanse of problems that can be solved with quantum computing is limited only due to lack of imagination.

Meanwhile, Dr. Scott Crowder, Vice President of IBM Quantum shed light on the real-world application of quantum computing in drug discovery – with capabilities such as simulating behaviors of chemicals and drug interactions - during the panel discussion.

In addition to this, quantum technology has greater potential to boost machine learning as it is capable of drawing complex patterns from data, subsequently benefitting financial institutions in optimising portfolio or detecting/predicting fraud.

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