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Quantum mechanics describes how nature works at a fundamental level. Using those principles to build a quantum computer doesn’t just mean working at the nanoscale level; it also means keeping everything cold enough to see quantum effects. That’s why D-Wave runs its Orion system at a temperature 250 times colder than interstellar space.

Last year the company had a 16-qubit quantum computer that founder and CTO Geordie Rose claimed was the most powerful quantum computer ever built and the first ever to run commercially-relevant applications. This year it has 28 qubits, it can recognise photos of famous landmarks – and you might soon be able to use it over the Web.

That’s far ahead of most other quantum computing developments and D-Wave has managed it by using semiconductor manufacturing techniques and existing chip fabs instead of optical circuits, quantum dots, laser containment or other approaches requiring exotic manufacturing techniques. D-Wave is also working on the other half of the problem; the programming tools for writing applications that take advantage of what quantum computing promises to deliver.

Rose defines a quantum computer as “a machine that harnesses the language of nature at the most fundamental level to gain, in some cases, extremely impressive performance gains over conventional computers. Computers are constrained by the laws of physics; what you can do with information is no more than the laws of physics, when you operate at classical level. On a quantum computer, information processing is done on devices that obey the laws of quantum mechanics. These things can be very small and very cold, and they can be built out of exotic materials.”

The exotic material in D-Wave’s quantum chip is niobiumhttp://en.wikipedia.org/wiki/Niobium ; cool it enough and it becomes a superconductor. When ordinary metal conducts electricity, the electronshttp://en.wikipedia.org/wiki/Electron carrying the electric current collide with the imperfections in the metal and you get resistance. When you cool superconducting metal like niobium, the metal’s electrons form Cooper pairs where the motion of one electron is matched by an equal and opposite motion of the paired electron, which stops the electrons hitting the imperfections and generating resistance, which means the electrons flow freely without you needing to pump in extra current. When the Cooper pairs enter the Josephson junctions in the chip – made up of two segments of superconducting niobium linked by a weak insulating barrier – they break up, creating electron-like quasi-particles that can tunnel through the insulator in the junction, effectively conducting the current through the junction.

The niobium is arranged in rings through which the current can flow clockwise, anti-clockwise or in a mixture of both directions – corresponding, according to Rose, to the 0, 1 or superposition of the two values in the quantum bit of information (qubit) that quantum computing is based on. “The chip is a series of metal traces on a silicon substrate; the substrate is the same as you’d use for any semiconductor process but on top are layers of metal interrupted by insulators. This is an entirely metal based magnetic thing where all the information is stored in the direction of the current flows around the metal loop and interruptions.”

The direction of the current converts into a value for the qubit based on whether that qubit has a bias towards one direction (0 or 1), whether neighbouring qubits are running the in same or opposite directions and the energy barrier between the different qubit states. The current chip, Leda, has 28 rings, giving 28 qubits, but they’re not all interconnected to each other, only to a number of ‘neighbours’. The Cooper pair in the niobium are technically bosons so they all exist in the same quantum state, Rose claims, which gives the entire superconductor quantum properties even without interconnecting every qubit. Reducing the number of interconnections simplifies manufacturing and has enabled D-wave to go from 2 qubits in 2002 to 16 in 2007, 28 today – and 512 and 1024 over the next year, if things go well.

Many believe that true quantum computing will enable computations that supercomputers would take hundreds of years to process, enabling real-time weather prediction, custom drug design and cracking encryption. Geordie Rose isn’t promising those kinds of universal applications, at least not immediately.

“The breadth of applications is actually quite narrow. The machine can be thought of most profitably as an analogue computer. It’s not exactly an analogue computer, it’s something novel that has never existed before but conceptually you can think of it as a special purpose chip designed to do one thing well. Ultimately, quantum computers will turn into a lot more than that but when you do the first iteration of a technology, it helps to focus what it does. This particular chip, all it does is problems related to pattern matching. Other applications such as code breaking; this chip is disabled in a way that makes those things not possible to run on it. It is possible that in future we might expand – if this particular project succeeds financially – to include other type of processors that are able to harness nature in way that allows you to do these things. But those are long term things and certainly not our focus right now.”

At the Future in Review conference this year Rose showed an image matching program developed with Google image matching expert, Dr Hartmut Neven, that can distinguish photos of, say, the Taj Mahalhttp://en.wikipedia.org/wiki/Taj_Mahal from photos of Big Ben by comparing the image to a group of images already labelled as the Taj Mahal. The software looks for matching points of interest in the photos, which means solving hard maths problems that Orion is very good at, according to Rose. “Similarity matching between images is a very hard artificial intelligence problem and it turns out, with quantum computers, that their sweet spot is in the technical math that underlies certain hard vision problems and certain hard machine learning problems.”

You can match images and look for patterns on conventional computers, but it takes a lot of time it train the system, says Rose. “The requirement to do very fast search on a large number of images requires that you sacrifice quality. Often what happens in image search is that you can do very well on finding certain types of objects in images by spending a lot of time up front. You can detect faces in photos very quickly if you spend a year using an enormous amount of computing cycles to do that.”

Using Orion won’t necessarily speed up the time it takes to search, but he believes it will produce much better matches to what you’re looking for, and he’s not worried by performance that’s actually slower than conventional computing today. “This is not a demonstration of performance; this is a demonstration that we can do this end to end. We will be able to get a quality of matching on large data sets you simply can’t get with conventional computing, no matter how good your algorithms are. When you are searching for something complicated or unique it’s sometimes hard to describe. This is the first step of a system where you can query not with text but with images; it’s the sweet spot of the next generation of search and what these computers do very well.”

Pattern matching covers a wide range of applications. D-wave has previously demonstrated searching a database of molecules, creating a seating plan with many constraints on who can sit together and solving Sudoku puzzles and commercial applications are the next step. Rose talks about improving the logistics of how jet fuel is distributed and stored, cataloguing stars in images of space, modelling protein folding and counting the number of rocks in a possible landing area on Mars but also solving complex business problems: “What is the ideal business unit in my company to work on this project? I need three people who know C++ and earn less than such and such…”

But Orion isn’t anywhere near ready to go in your data center. It’s going to be staying in D-wave’s headquarters in Burnaby, Canada for the immediate future, because of what Rose calls the “extraordinary” cooling requirements. The Josephson junctions are only microns across; the chip they’re on is 5 millimetres square. But Orion itself is roughly the size of a large domestic refrigerator, and most of the system is taken up by the refrigeration equipment.

“This thing sits inside a shielded room, a big metal room which is almost a magnetic vacuum for certain frequencies of EM radiation. Inside is an insert which is half fridge and half filtering. We run this thing at ten milliKelvin, just 0.01 degrees above absolute zero – and just for a point of reference the temperature of interstellar space is about 2.7 Kelvin. The chip needs to sit in a magnetic vacuum. A lot of the gadgetry inside this is very, very robust filters that filter out every bit of noise you can with current technology, to get the signals on the lines coming in and the ambient magnetic field to very low levels – one nanotesla in three dimensions across the whole chip, which is at or beyond the state of the art for magnetic vacuum technology.”

Rather than moving Orion, D-Wave is developing remote access software. Writing quantum annealing algorithms for solving binary quadratic programs on Orion is very different from classical programming. You can work directly in the system’s machine language, directly choosing the current flowing on the input lines on the chip, but Rose expects that will only appeal to scientists studying the way quantum computing itself behave. Demos like the image matching system are written as problems in what he calls ‘industry standard ways to state combinatorial optimization problems’. A conventional computer converts that for Orion so that a solution corresponds to a pattern of current in the qubits that takes up the minimum amount of energy – the annealing.

“It’s like trying to find the lowest point in a valley when you have a ball and you let the ball go; it can find the lowest point by finding its natural state,” Rose explains. “It’s really easy to learn to use the system at this level, but figuring out how to recast the problem you really care about – say image matching – to use this new capability is very hard. Typically the folks who “get it” at this level have PhD-level discrete math backgrounds applied in an industry setting.”

Rose wants more people than that using Orion; “I’m a big fan of opening things up as much as possible to anyone wants to use them and making them easy to use even if people don’t understand quantum computation.” For the rest of us, D-Wave has produced a compiler that means programmers can state problems in SQL using a new FIND command. “This level of access allows anyone who is an expert database programmer to begin using the system within about 30 minutes,” claims Rose, “most of which is in learning the syntax of the FIND command, which is very similar to SELECT.” Developers who want to prototype applications or get familiar with the interface can try the programming model out with D-Wave’s Web service solver, although this currently runs a software emulation rather than sending commands to real hardware.

D-Wave’s demonstrations have generated plenty of controversy, partly because the company hasn’t published the kind of information that comes out of less commercial concerns in peer-reviewed journals. Critics suggest that what D-wave has is an analog computer that won’t achieve quantum performance; Geordie Rose believes time will show it’s a true quantum computer. “It’s known that there are several universal models of quantum computation, just like there are several universal classical models. The one we picked, adiabatic quantum computing, has significant advantage in that it’s easy to implement with large qubits.”

Using semiconductor manufacturing techniques means D-Wave can create a new version of the processor every month and keep tweaking it to fix any problems. And he’s confident there’s enough demand that we’ll see a usable quantum computer within years, not the decades some predict. “There’s a huge push from business and technology and that push is not going to go away any time. This is not like super high temperature conductors or fusion; this is something that’s going to be pushed until it works.”

Source:

http://www.tomshardware.com/reviews/super-cooled-quantum-computing,1976.html

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