Upgrading the quantum computer

October 23, 2015, University of Innsbruck

Theoretical physicists have proposed a scalable quantum computer architecture. The new model, developed by Wolfgang Lechner, Philipp Hauke and Peter Zoller, overcomes fundamental limitations of programmability in current approaches that aim at solving real-world general optimization problems by exploiting quantum mechanics.

Within the last several years, considerable progress has been made in developing a quantum computer, which holds the promise of solving problems a lot more efficiently than a classical computer. Physicists are now able to realize the basic building blocks, the quantum bits (qubits) in a laboratory, control them and use them for simple computations. For practical application, a particular class of quantum computers, the so-called adiabatic quantum computer, has recently generated a lot of interest among researchers and industry. It is designed to solve real-world optimization problems conventional computers are not able to tackle. All current approaches for adiabatic quantum computation face the same challenge: The problem is encoded in the interaction between qubits; to encode a generic problem, an all-to-all connectivity is necessary, but the locality of the physical quantum bits limits the available interactions.

"The programming language of these systems is the individual interaction between each physical qubit. The possible input is determined by the hardware. This means that all these approaches face a fundamental challenge when trying to build a fully programmable quantum computer," explains Wolfgang Lechner from the Institute for Quantum Optics and Quantum Information (IQOQI) at the Austrian Academy of Sciences in Innsbruck.

Fully programmable quantum computer

Theoretical physicists Wolfang Lechner, Philipp Hauke and Peter Zoller have now proposed a completely new approach. The trio, working at the University of Innsbruck and the IQOQI, suggest overcoming the challenges by detaching the logical qubit from the physical implementation. Each physical qubit corresponds to one pair of logical qubits and can be tuned by local fields. These could be electrical fields when dealing with atoms and ions or magnetic fields in superconducting qubits. "Any generic optimization problem can be fully programmed via the fields," explains co-author Philipp Hauke from the Institute for Theoretical Physics at the University of Innsbruck, Austria. "By using this approach we are not only avoiding the limitations posed by the hardware but we also make the technological implementation scalable."

Integrated fault-tolerance

Because of the increased number of degrees of freedom, which could also lead to non-physical solutions, the physicists arrange the qubits in a way that four physical qubits interact locally.

"In this way we guarantee that only physical solutions are possible," explains Wolfgang Lechner. The solution of the problem is encoded redundantly in the . "With this redundancy our model has also a high fault-tolerance," says Lechner. The new architecture can be realized on various platforms ranging from superconducting circuits to ultracold gases in optical lattices. "Our approach allows for the application of technologies that have not been suitable for adiabatic quantum optimization until now," says the physicist. Lechner, Hauke and Zoller have introduced this in the journal Science Advances. The scientific community has also expressed great interest in the new model.

Peter Zoller is convinced: "The step from mechanical calculators to fully programmable computers started the information technology age 80 years ago. Today we are approaching the age of quantum information."

A patent for the new quantum computer architecture has been submitted this year. The scientists are financially supported by the Austrian Science Fund (FWF) and the European Research Council (ERC) among others.

Explore further: Simulation of chiral edge states in a quantum system

More information: A quantum annealing architecture with all-to-all connectivity from local interactions. W. Lechner, P. Hauke, P. Zoller. Sci. Adv. 1, e1500838 (2015). DOI: 10.1126/sciadv.1500838

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Spaced out Engineer
1 / 5 (2) Oct 24, 2015
Too cool. I'm not sure what to hope for. If electrical fields, magnetic fields, and electromagnet fields are to be taken substrate independantly in their representation of reality, this is really promising.

The stacking and fracturing of symmetry and asymetry still could have higher dimensional representations that are currently not preceivable and might not exist as imaginable processes. Meaning the determination between local minima/maxima, non-halting (do to no maxima/minima), and global minima/maxima could still not be applicable to some types of problems.

We need more math to determine if our axiomatic seeking of truth can find valid isomorphism for the contexts we find ourselves within. Maybe photonic machine learning can help, but the syntactic evolution of the system, even with valid training data, might quickly exceed our human abilities. How can you trust, use, or sort data you can not translate, transcribe, or that may not have the same kind of intepretation?
Oct 24, 2015
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3 / 5 (2) Oct 24, 2015
Docile, quantum channel capacity is a very different issue then what kind of computability class a machine implements. What you content is that the complexity class BQP of problems that a quantum computer can efficiently solve is the same as BPP the one that a probabilistic Turing machine can tackle.

While this question hasn't been theoretically settled, it is about as unlikely as NP=P.
Oct 24, 2015
This comment has been removed by a moderator.
3 / 5 (2) Oct 24, 2015
Docile, the quantum channel paper that underlies the article you link to considers a a thermal noise channel. In a sense it shows more rigorously what has been suspected all along, that entanglement as a an information resource won't get you far as soon as you add some non-negligible noise. Hence a quantum chip like the one from D-Wave has to be kept very close to absolute zero, and the performance degrades rapidly when the temperature increases: http://wp.me/p2lHU6-5k/#update

As to the speed benefit achieved by cooling, this is because at this temperature regime entanglement (as well as other quantum probabilities) are no longer dominated by thermal ones that will otherwise quickly randomize the density matrix that describes the system.

As far as we know classical systems cannot efficiently simulate a many-body quantum evolution.
3 / 5 (2) Oct 24, 2015
Just to be clear, don't mean to put down memristors, very cool technology, will breath new life into classical computing, but the "parallelism" of qubits is at a much more fundamental level.

This is something that becomes very tangible when you try to emulate a quantum computer. The more parallel, the better. Spark is currently my platform of choice, but no matter how much hardware you throw at it, it's very hard to go beyond the emulation of some dozens of qubits i.e. hundreds are out of the question.

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