Posts Tagged ‘material science’

IBM Moves Quantum Computing Toward Commercial Systems

September 20, 2017

IBM seem determined to advance quantum computing. Just this week IBM announced its researchers developed a new approach to simulate molecules on a quantum computer that may one day help revolutionize chemistry and materials science. In this case, the researchers implemented a novel algorithm that is efficient with respect to the number of quantum operations required for the simulation. This involved a 7-qubit processor.

7-cubit processor

In the diagram above IBM scientists successfully used six qubits on a purpose-built seven-qubit quantum device to address the molecular structure problem for beryllium hydride (BeH2) – the largest molecule simulated on a quantum computer to date.

Back in May IBM announced an even bigger quantum device. It prototyped the first commercial processor with 17 qubits and leverages significant materials, device, and architecture improvements to make it the most powerful quantum processor created to date by IBM. This week’s announcement certainly didn’t surpass it in size. IBM engineered the 17-qubit system to be at least twice as powerful as what is available today to the public on the IBM Cloud and it will be the basis for the first IBM Q early-access commercial systems.

It has become apparent to the scientists and researchers who try to work with complex mathematical problems and simulations that the most powerful conventional commercial computers are not up to the task. Even the z14 with its 10-core CPU and hundreds of additional processors dedicated to I/O cannot do the job.

As IBM puts it: Even today’s most powerful supercomputers cannot exactly simulate the interacting behavior of all the electrons contained in a simple chemical compound such as caffeine. The ability of quantum computers to analyze molecules and chemical reactions could help accelerate research and lead to the creation of novel materials, development of more personalized drugs, or discovery of more efficient and sustainable energy sources.

The interplay of atoms and molecules is responsible for all matter that surrounds us in the world. Now “we have the potential to use quantum computers to boost our knowledge of natural phenomena in the world,” said Dario Gil, vice president of AI research and IBM Q, IBM Research. “Over the next few years, we anticipate IBM Q systems’ capabilities to surpass what today’s conventional computers can do, and start becoming a tool for experts in areas such as chemistry, biology, healthcare and materials science.”

So commercial quantum systems are coming.  Are you ready to bring a quantum system into you data center? Actually you can try one today for free here  or through GitHub, which offers a Python software development kit for writing quantum computing experiments, programs, and applications. Although DancingDinosaur will gladly stumble through conventional coding, quantum computing probably exceeds his frustration level even with a Python development kit.

However, if your organization is involved in these industries—materials science, chemistry, and the like or is wrestling with a problem you cannot do on a conventional computer—it probably is worth a try, especially for free. You can try an easy demo card game that compares quantum computing with conventional computing.

But as reassuringly as IBM makes quantum computing sound, don’t kid yourself; it is very complicated.  Deploying even a small qubit machine is not going to be like buying your first PC. Quantum bits, reportedly, are very fragile or transitory. Labs will keep them very cold just to better stabilize the system and keep them from switching their states before they should.  Just think how you’d feel about your PC if the bit states of 0 and 1 suddenly and inextricably changed.

That’s not the only possible headache. You only have limited time to work on cubits given their current volatility when not super cooled. Also, work still is progressing on advancing the quantum frameworks and mapping out ecosystem enablement.

Even IBM researchers admit that some problems may not be better on quantum computers. Still, until you pass certain threshold, like qubit volume, your workload might not perform better on a quantum computer. The IBM quantum team suggests it will take until 2021 to consistently solve a problem that has commercial relevance using quantum computing.

Until then, and even after, IBM is talking about a hybrid approach in which parts of a problem are solved with a quantum computer and the rest with a conventional system. So don’t plan on replacing your Z with a few dozen or even hundreds of qubits anytime soon.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.


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