Caltech Researchers Define Applications for Quantum Computing

July 31, 2017 – Quantum computing hardware continues to evolve. Whether we are talking about D-Wave’s latest machine, Google, IBM or Microsoft, or Chinese efforts, the race to build a commercial quantum computing world has gone hot in the last two years. But what lags behind the hardware, is software.

Researchers tell us that quantum computers will be able to solve complex problems, that they will be faster than the supercomputers we have today, that they will be able to break any existing cryptography while putting in place unbreakable security in all quantum devices.

Quantum computers will analyze the Universe for us in entirely new ways, whether we are studying black holes and supernovas or revealing the latest new particle finds in quantum physics, or unlocking further the mysteries of DNA and RNA. But they can only do this if developers create software that works on quantum computers. Back in January of this year, I wrote about the challenge of developing the programming for quantum computing. D-Wave has developed an open source tool, Qbsolv, to encourage programmers to begin software development. Another developer, Scott Pakin, has created Qmasm, a quantum macro assembler to help with the writing of machine level code. Another company, 1QBit, is also building software for quantum computers, in particular, D-Wave devices.

In the latest Caltech study which was presented at the Institute of Electrical and Electronics Engineers 2017 Symposium on Foundations of Computer Science, researchers provided what they called solutions to “semidefinite programs.”

So what is semidefinite programming?

It is programming designed to solve complex problems where there may be more than one answer, such as solutions that provide minimums and maximums. Think about what kind of software tool would help design a critical component for a rocket to better understand the material constraints under a number of conditions. In conventional computing, this is a complex problem that could tie up a system for hours or even days. In quantum computing with semidefinite programming, the problem can be addressed in minutes providing a range of tolerances and comprehensive risk analysis.

Fernando Brandao and Krysta Svore, are co-authors in the published results of the study. Brandao, a theoretical physicist at Caltech, believes that the quantum algorithm they developed could rapidly describe the quantum states of subatomic matter and its behaviors. Svore manages the Quantum Architectures and Computation Group at Microsoft Research. In their paper which you can access through the Caltech Library Service, it states that the new quantum algorithm they developed achieves an exponential speedup when solving complex linear and quadratic equations.

Real world examples and not theoretical ones where semidefinite programming using quantum computers will prove helpful:

• Minimizing the risk in investment portfolios
• Maximizing inventory and machinery use in production and manufacturing assembly
• Solving complex route scheduling for airlines including flight crew assignments
• Analyzing crime data to reveal previously unseen patterns
• Calculating the optimal conditions for a controlled nuclear fusion reaction
• Studying power grid use to determine load balancing requirements in a generating mix that includes variable renewable energy, storage, and traditional sources

All of these are good candidates for quantum computing but without the programming tools, the value of the advances on the hardware side is moot.