Category Archives: Quantum Computer
Programming a computer is generally a fairly arduous process, involving hours of coding, not to mention the laborious work of debugging, testing, and documenting to make sure it works properly.
But for a team of physicists from the Harvard-MIT Center for Ultracold Atoms and the California Institute of Technology, things are actually much tougher.
Working in a Harvard Physics Department lab, a team of researchers led by Harvard Professors Mikhail Lukin and Markus Greiner and Massachusetts Institute of Technology Professor Vladan Vuletic developed a special type of quantum computer, known as a quantum simulator, that is programmed by capturing super-cooled rubidium atoms with lasers and arranging them in a specific order, then allowing quantum mechanics to do the necessary calculations.
The system could be used to shed light on a host of complex quantum processes, including the connection between quantum mechanics and material properties, and it could investigate new phases of matter and solve complex real-world optimization problems. The system is described in a Nov. 30 paper published in the journal Nature.
The combination of the systems large size and high degree of quantum coherence make it an important achievement, researchers say. With more than 50 coherent qubits, this is one of the largest quantum systems ever created with individual assembly and measurement.
In the same issue of Nature, a team from the Joint Quantum Institute at the University of Maryland described a similarly sized system of cold charged ions, also controlled with lasers. Taken together, these complimentary advances constitute a major step toward large-scale quantum machines.
Everything happens in a small vacuum chamber where we have a very dilute vapor of atoms which are cooled close to absolute zero, Lukin said. When we focus about 100 laser beams through this cloud, each of them acts like a trap. The beams are so tightly focused, they can either grab one atom or zero; they cant grab two. And thats when the fun starts.
Using a microscope, researchers can take images of the captured atoms in real time, and then arrange them in arbitrary patterns for input.
We assemble them in a way thats very controlled, said Ahmed Omran, a postdoctoral fellow in Lukins lab and a co-author of the paper. Starting with a random pattern, we decide which trap needs to go where to arrange them into desired clusters.
As researchers begin feeding energy into the system, the atoms begin to interact with each other. Those interactions, Lukin said, give the system its quantum nature.
We make the atoms interact, and thats really whats performing the computation, Omran said. In essence, as we excite the system with laser light, it self-organizes. Its not that we say this atom has to be a one or a zero we could do that easily just by throwing light on the atoms but what we do is allow the atoms to perform the computation for us, and then we measure the results.
Those results, Lukin and colleagues said, could shed light on complex quantum mechanical phenomena that are all but impossible to model using conventional computers.
If you have an abstract model where a certain number of particles are interacting with each other in a certain way, the question is why dont we just sit down at a computer and simulate it that way? asked Ph.D. student Alexander Keesling, another co-author. The reason is because these interactions are quantum mechanical in nature. If you try to simulate these systems on a computer, youre restricted to very small system sizes, and the number of parameters are limited.
If you make systems larger and larger, very quickly you will run out of memory and computing power to simulate it on a classical computer, he added. The way around that is to actually build the problem with particles that follow the same rules as the system youre simulating. Thats why we call this a quantum simulator.
Though its possible to use classical computers to model small quantum systems, the simulator developed by Lukin and colleagues uses 51 qubits, making it virtually impossible to replicate using conventional computing techniques.
It is important that we can start by simulating small systems using our machine, he said. So we are able to show those results are correct until we get to the larger systems, because there is no simple comparison we can make.
By Peter Reuell, Harvard Staff Writer | July 3, 2012 | Editor’s Pick
When we start off, all the atoms are in a classical state. And when we read out at the end, we obtain a string of classical bits, zeros, and ones, said Hannes Bernien, another postdoctoral fellow in Lukins lab, and also a co-author. But in order to get from the start to the end, they have to go through the complex quantum mechanical state. If you have a substantial error rate, the quantum mechanical state will collapse.
Its that coherent quantum state, Bernien said, that allows the system to work as a simulator, and also makes the machine a potentially valuable tool for gaining insight into complex quantum phenomena and eventually performing useful calculations. The system already allows researchers to obtain unique insights into transformations between different types of quantum phases, called quantum phase transitions. It may also help shed light on new and exotic forms of matter, Lukin said.
Normally, when you talk about phases of matter, you talk about matter being in equilibrium, he said. But some very interesting new states of matter may occur far away from equilibrium and there are many possibilities for that in the quantum domain. This is a completely new frontier.
Already, Lukin said, the researchers have seen evidence of such states. In one of the first experiments conducted with the new system, the team discovered a coherent non-equilibrium state that remained stable for a surprisingly long time.
Quantum computers will be used to realize and study such non-equilibrium states of matter in the coming years, he said. Another intriguing direction involves solving complex optimization problems. It turns out one can encode some very complicated problems by programming atom locations and interactions between them. In such systems, some proposed quantum algorithms could potentially outperform classical machines. Its not yet clear whether they will or not, because we just cant test them classically. But we are on the verge of entering the regime where we can test them on the fully quantum machines containing over 100 controlled qubits. Scientifically, this is really exciting.
Other co-authors of the study were visiting scientist Sylvain Schwartz, Harvard graduate students Harry Levine and Soonwon Choi, research associate Alexander S. Zibrov, and Professor Manuel Endres.
This research was supported with funding from the National Science Foundation, the Center for Ultracold Atoms, the Army Research Office, and the Vannevar Bush Faculty Fellowship.
By Arthur Goldhammer, Center for European Studies | November 30, 2017
At the Microsoft Ignite Conference in September, Microsoft let it be known it was going to be a player in the future of quantum computing, and today the company took another step toward that goal when it released a preview of its quantum computing development kit.
The kit includes all of the pieces a developer needs to get started including a Q# language and compiler, a Q# library, a local quantum computing simulator, a quantum trace simulator and a Visual Studio extension.
This is a preview, so its aimed at early adopters who want to understand what it takes to develop programs for quantum computers, which operate very differently from classical ones. Put in simple terms, with a classical computer, a bit can only exist in a binary state of on or off, whereas with quantum programs a qubit (the quantum equivalent of a bit) can exist in multiple states at the same time. This could open the door to programs that simply couldnt have existed before.
This is but one piece in Microsofts big vision for quantum computing that it discussed at Ignite. Microsofts Krysta Svore told TechCrunchs Frederic Lardinois in September that the idea was to offer a comprehensive full-stack solution for controlling the quantum computer and writing applications for it.
We like to talk about co-development, she said. We are developing those [the hardware and software stack] together so that youre really feeding back information between the software and the hardware as we learn, and this means that we can really develop a very optimized solution, she told Lardinois.
Microsoft clearly wants a piece of the quantum computing action, but they are hardly alone. IBM has had a quantum computing service available for programmers since last year, and last month it had a breakthrough with the release of a 20 qubit quantum computer. The company also announced a 50 qubit prototype.
Other companies working on quantum computing research include Google and Intel and a host of other established companies and startups.
We are still in very early days with this technology and it has a long way to go, but the potential is so great that all of these companies, including Microsoft, want to get in as early as possible to capture developer hearts and minds. Todays release is part of that.
See the rest here:
Microsoft releases quantum computing development kit preview …
Intels quantum computing efforts have yielded a new 17-qubit chip, which the company has just delivered to its partner in that field, QuTech in the Netherlands. Its not a major advance in the actual computing power or applications those are still in very early days but its a step towardproduction systems that can be ordered and delivered to spec rather than experimental ones that live in a physics lab somewhere.
Intels celebration of this particular chip is a bit arbitrary; 17 isnt some magic number in the quantum world, nor does this chip do any special tricks other quantum computer systems cant. Intel is just happy that its history and undeniable expertise in designing and fabricating chips and architectures is paying off in a new phase of computing.
I chatted with Intels director of quantum hardware, Jim Clarke, about the new system.
The test chip itself (the gold ports arent the qubits themselves, obviously)
Were relying on our expertise in hardcore engineering, he said. Were working on all parts of the compute stack: the chip, the control electronics, the system architecture, the algorithm.
Its not quite like popping out a new Core processor every year, but theres plenty of overlap.
Our infrastructure allows us to adapt the materials and the package, Clarke said. If you think of a material that might be good for a qubit chip, Intel likely already has a mature process for that material or at least experience with it.
That isnt easy when the field of computing theyre attempting to enter is largely theoretical. Thats why partners like QuTech, a research institute under TU Delft, are essential. Intel isnt short on big brains, but a dedicated facility under a major technical university is likely more fertile ground for this kind of bleeding-edge work.
The basic relationship is that Intel makes the chips, and QuTech tests them with the latest algorithms, models, and instruments. They turn around and say something like that was great, but well need at least 14 qubits to do this next thing, and we saw a lot of interference under such and such conditions. Intel jots it down and a few months later (theres no set timeline), out comes a new one, and the cycle repeats.
Im simplifying, of course, because I dont know the details of all this quantum tomfoolery (who can, really?), but thats a powerful cycle to nurture.
The results so far let Intel boast of a chip that, thanks to the companys manufacturing prowess and the work by QuTech, has considerably improved in reliability and performance over the last two years, while the architecture, system infrastructure (such as interconnects and testing methods) and so on have evolved alongside.
Of course, these amazing quantum computers still dont really do anything yet and they have to operate at around 20 thousandths of a degree above absolute zero. But the first problem is more exciting than limiting (the potential of these machines, theoretically, is enormous), and the second one, to my surprise, isnt really a big deal any more.
Turns out (perhaps you knew, but I didnt) that you can package a multi-qubit quantum computing system, cooled to the millikelvin level, in an enclosure the size of an oil drum.
Theres a long way to go in the quantum computing world, but its a no-brainer for companies like Intel to bet on the concept; its billions of dollars in infrastructure serve excellently for collateral.
Here is the original post:
Intel moves towards production quantum computing with new 17 …
It looks like a prop from Doctor Who or Hollywood’s idea of a mad professor’s crazy invention.
But the glittering lump of steel sprouting foil-wrapped pipes balanced on a stack of books and magazines represents a revolution in computing that could change the world.
The 60cm tall machine housed in a cramped laboratory at the University of Sussex is a prototype ion qubit quantum computer.
Still a work in progress, it is designed to demonstrate technology that marks a leap forward in attempts to build unimaginably powerful computers based on the weird principles of quantum physics.
Scientists hope that in as little as 10 years they will be able to scale up the device to produce the first commercially available universal quantum computer capable of solving myriad different problems.
Quantum computers are the ultimate multi-taskers, carrying out many operations at once to work millions of times faster than conventional computers.
They could theoretically unravel incredibly complex problems in days that would take a modern supercomputer billions of years to solve, and transform fields such as finance, drug discovery, biochemistry, materials science and encryption.
A conventional computer stores “bits” of information as binary code sequences of zeroes and ones, but a quantum computer “qubit” can be a zero, a one, both a zero and a one, or an infinite number of values in between.
That is due to the strange ability of subatomic particles to be in more than one state at the same time, until they are observed or interfered with. Only then does one or other value materialise. In a similar way, a spinning coin hides its identity until a hand stops it to reveal a face that is heads or tails.
Speaking at the British Science Festival in Brighton, Professor Winfried Hensinger, who heads the university’s quantum technology lab, says even Albert Einstein was “freaked out” by quantum effects and called them “spooky”.
Then 10 to 20 years ago physicists started asked themselves whether it might be possible to build a quantum device that could perform certain computations “unbelievably fast”.
“What does unbelievably fast mean?” said Hensinger “Unbelievably fast means that it could calculate something that even the fastest supercomputer in the world would take billions of years to calculate in minutes, days or weeks.
“It means quantum computers can solve problems you couldn’t even dream about solving before.”
Originally posted here:
Quantum computer a possibility in 10 years – News.com.au – NEWS.com.au
Launch of the University of Sydney partnership with Microsoft.Front row: Ph.D. candidate Alice Mahoney with Microsoft’s David Pritchard. Back row (R-L): Station Q Sydney director Professor David Reilly; Microsoft’s Douglas Carmean; Station Q Sydney senior research scientist Dr. Maja Cassidy; University of Sydney Chancellor Belinda Hutchinson, postdoctoral researcher Dr. John Hornibrook and University of Sydney Vice-Chancellor Dr. Michael Spence. Credit: Jayne Ion/University of Sydney
Scientists at the University of Sydney are entering a new phase of development to scale up the next generation of quantum-engineered devices.
These devices will form the heart of the first practical topological quantum computers.
A study released today in Nature Communications confirms one of the prerequisites for building these devices.
An author of that paper, Dr Maja Cassidy, said: “Here at Station Q Sydney we are building the next generation of devices that will use quasiparticles known as Majorana fermions as the basis for quantum computers.”
Dr Cassidy said the $150 million Sydney Nanoscience Hub provides a world-class environment in which to build the next generation of devices.
Microsoft’s Station Q will move scientific equipment into the Nanoscience Hub’s clean rooms – controlled environments with low levels of pollutants and steady temperatures – over the next few months as it increases capacity to develop quantum machines.
Dr Cassidy said that building these quantum devices is a “bit like going on a detective hunt”.
“When Majorana fermions were first shown to exist in 2012, there were many who said there could be other explanations for the findings,” she said.
A challenge to show the findings were caused by Majoranas was put to the research team led by Professor Leo Kouwenhoven, who now leads Microsoft’s Station Q in the Netherlands.
The paper published today meets an essential part of that challenge.
In essence, it proves that electrons on a one-dimensional semiconducting nanowire will have a quantum spin opposite to its momentum in a finite magnetic field.
“This information is consistent with previous reports observing Majorana fermions in these nanowires,” Dr Cassidy said.
She said the findings are not just applicable to quantum computers but will be useful in spintronic systems, where the quantum spin and not the charge is used for information in classical systems.
Dr Cassidy conducted the research while at the Technical University Delft in the Netherlands, where she held a post-doctorate position. She has since returned to Australia and is based at the University of Sydney Station Q partnership with Microsoft.
University of Sydney Professor David Reilly is the director of Station Q Sydney.
“This is practical science at the cutting-edge,” Professor Reilly said. “We have hired Dr Cassidy because her ability to fabricate next-generation quantum devices is second to none.”
He said Dr Cassidy was one of many great minds attracted to work at Station Q Sydney already this year. “And there are more people joining us soon at Sydney as we build our capacity.”
Professor Reilly last week won the Australian Financial Review award for Emerging Leadership in Higher Education.
Explore further: Majorana highway on a chip
More information: J. Kammhuber et al, Conductance through a helical state in an Indium antimonide nanowire, Nature Communications (2017). DOI: 10.1038/s41467-017-00315-y
There are weeks where it seems like every piece of physics news mentions quantum computingbut we are nowhere near a quantum iPhone. You probably remember that computers can consist of billions of nanometer-scale transistors etched into silicon. Those chips used to be enormous, room-sized setups where instead of transistors, there were tubes the size of light bulbs. Physicists in the quantum computing world are still trying to pick out the best vacuum tubes.
Headlines emerged today mentioning a new kind of qubit that could make quantum computers more easily. But it would help to first understand where quantum computing is overall.
Heres a quick quantum computing recap. Regular computer bits store information with a binary yes-no system, like a wire with or without a current. A quantum bit, or qubit, instead relies on the probabilistic nature of quantum mechanics: instead of yes and no, theres a pair of options with an associated probability for each. There are algorithms in science and artificial intelligence that could run more quickly or efficiently with such a computing system. There are some mechanical systems that store qubits, but theyve proven expensive, bulky, or difficult to keep in that fragile quantum state without collapsing into a classical bitwith a probability of 100 percent yes or no.
A team of researchers at the University of New South Wales in Australia and Purdue University in the US now have a blueprint for a new kind of qubit and therefore a new kind of quantum computing system, one built into silicon just like the parts of a regular computer. Such a system could potentially be important as a scaleable, space-saving qubit that stays quantum. But whether it will work remains to be seen; someone actually needs to build a computer based on it.
This design provides a realizable blueprint for scalable spin-based quantum computers in silicon, the authors write in the paper, published today in the journal Nature Communications.
The paper builds on Bruce Kanes well-known 1998 quantum computer proposal in Nature, where qubits are stored as properties of atoms, and performing computer operations is done by applying an electric field. The team proposes what they call flip-flop qubits, where a phosphorous atom sits in a silicon semiconductor. The electron and the nucleus both contain intrinsic properties called spin that can assume values called up and down (spin is a property built into particles like magnetism is built into fridge magnets). The flip-flop qubits ones and zeroes become stored when an electric field causes the electron and nucleus spins to snap into opposite states, one up and the other down, or vice versa.
These qubits would have a few benefits, say the researchers: Theyd have very low error rates, for example. Qubits are fragile things, so any real-world quantum computer must still work regardless of whether some of its qubits fall apart, and errors should be as infrequent as possible. These qubits are also built into silicon and controlled by electric fields, meaning they could potentially be integrated into silicon chips. The qubits can interact with one another over large distances, which leaves room for other non-quantum pieces of the quantum computer. But the authors point out that some challenges do exist, including the handling of noise and phonons (tiny vibrations).
This is just one of several ideas researchers have for qubits. Companies are already plowing ahead building quantum computersyou may have heard of the controversial D-Wave computer with two thousand qubits (this is far less powerful than scientists would want, and theres debate over whether it can outperform any classical computers). The D-Wave relies on superconductors to create its qubits, materials with no electronic resistance that show quantum mechanical effects on macroscopic scales. There are also existing ion traps, where atoms on some surface are trapped by electric fields, and optics solutions where qubit information gets stored on light particles or photons.
As far as this latest idea goes, its potentially a big advance, Na Young Kim, Associate Professor at the University of Waterloos Institute for Quantum Computing told Gizmodo in an email. At the moment, ion traps and superconducting systems seem to stand in the front line, but there are big hurdles to overcome. Silicon systems may have a great potential to scale up if a robust design is solidified, and translated to present silicon technologies, she said. In that sense, this work certainly pushes silicon systems closer to the next phase of quantum computing development.
Its important to stay realistic with all of this though. Martin LaForest, senior manager of scientific outreach also at the Institute for Quantum Computing at the University of Waterloo recently told me that were now at the junction where physical quantum computer blueprints are beginning to meet theoretical demand required to reap quantum computings benefits. But were still a ways off from a computer that scientists actually use. Chris Wilson (again from the IQC) recently told me that a quantum computer that works the way you think when you hear computer would require possibly a hundred thousand physical qubits. Youre talking about a machine that looks like a modern supercomputer, something that fills a warehouse, he said.
Ultimately, this latest advance is a blueprint for what could potentially be some important quantum computer hardware. Even still, dont expect to see a quantum computer in your office any time soon (you know, unless you work at IBM or Google).
Go here to read the rest:
Scientists Propose a New Kind of Quantum Computer, But What … – Gizmodo
Twitter’s hashtag just turned 10, and wouldn’t you know it, scientists just worked out a far better use for it – at the nanoscale.
See, it turns out that a criss-cross pattern of semiconducting nanowires is the perfect structure to help manipulate a particular type of quasiparticle into quantum bits.
This nano-hashtag structure at scales of a billionth of a metre should help the quasiparticles, known as Majorana fermions, be more easily formed into a qubit: the building blocks for quantum computers.
Majorana fermions are shown to be far more robust than existing qubit technology, and scientists developing this technology reckon it will lead to a new generation of quantum architecture that will end with a scalable, fault-tolerant universal quantum computer.
This kind of architecture is what Microsoft’s Station Q is looking for, and recently announced a multi-year partnership at the University of Sydney. One of the researchers involved with this new research is Dr Maja Cassidy, a senior researcher at Station Q Sydney, which is based at the University of Sydney Nanoscience Hub.
“Networks of nanowires are crucial to demonstrate how Majorana fermions interact through braiding,” said Dr Cassidy. “These will be a fundamental building block for topological quantum computation.”
Dr Cassidy worked on the research team while she was at TU Delft in the Netherlands.
Continue reading here:
Scientists Just Found A Use For The Hashtag In Quantum Computing – Gizmodo Australia
Image credit: TriStar Pictures
Over the course of the hour, the discussion ranged from quantum computing and robotics to hacking and the ethics of creating sentient AI. Here are some of the highlights from the talk!
The Beginnings of AI: Early AI and Symbolic Reasoning
Joe Haldeman started off the discussion by talking about his experience with AI and symbolic reasoning courses during his college education, which covered philosophy, mathematics, and computer science. “I was studying AI before you guys were even born,” he joked.
He described writing out truth tables and learning quasi-algebraic logic, which allowed him to represent the “thought processes” of early computers. “I have faith in symbolic logic that I don’t have in natural language,” he said. “I won’t say it doesn’t lie, but when it lies, you can piece the truth out of it.”There’s something very elemental about writing out basic true-false equations for Haldeman: “I do know how to sit with a quasi-algebraic system and tease the truth out itit’s a feeling of power.”
Sentient AI and Quantum Computing
What gives a quantum computer its incredible, limit-breaking power is the qubit, which is analogous to the usual bits found in all computers, except that instead of a 1 and 0 state, a qubit can exist in a state that’s simultaneously 1 and 2 or neither.
This extra dimension allows for computational power that transcends current limits, opening the possibility for an artificial intelligence to grasp higher functions like self-awareness.
Hacking the Internet (of Things)
Paired with the introduction of hundreds of new, networked “smart” devices, from refrigerators to wearables to personal robots, the potential for hackers to take over a given device has grown exponentially in recent years.
Kelly cites the recent shutdown of a Facebook chatbot AIas an example of what happens when we lose control of AI: after trying to learn to communicate in English, the AI behind Facebook’s chat program decided that it would create its own, more efficient language, which was unintelligible to humans. When researchers realized what it was doing, they quickly shut it down.
The Promise of Sci-Fi and AI
As for the question of how close we are to realizing the kind of AI found in sci-fi and how safe we are from our darkest fears of robotic domination, Haldeman summed it up nicely: “This whole question shimmers between the uncomputable and the fictional. It’s a great place to start stories. These are existential stories-what is man? What are his computational limits?”
Stay tuned for more stories from Escape Velocity 2017!
The 4th International Conference on Quantum Technologies held in Moscow last month was supposed to put the spotlight on Google, who were preparing to give a lecture on a 49-qubit quantum computer they have in the works.
A morning talk presented by Harvard University’s Mikhail Lukin, however, upstaged that evening’s event with a small announcement of his own his team of American and Russian researchers had successfully tested a 51-qubit device, setting a landmark in the race for quantum supremacy.
Quantum computers are considered to be part of the next generation in revolutionary technology; devices that make use of the odd ‘in-between’ states of quantum particles to accelerate the processing power of digital machines.
The truth is both fascinating and disappointing. It’s unlikely we’ll be playing Grand Theft Auto VR8K-3000 on a quantum-souped Playstation 7 any time soon. Sorry, folks.
Quantum computing isn’t all about swapping one kind of chip for a faster one.
What it does do is give us a third kind of bit where typical computers have only two. In quantum computing, we apply quantum superposition that odd cloud of ‘maybes’ that a particle occupies before we observe its existence cemented as one of two different states to solving highly complex computational problems.
While those kinds of problems are a long, tedious process that tax even our best supercomputers, a quantum computer’s “qubit” mix of 1s, 0s, and that extra space in between can make exercises such as simulating quantum systems in molecules or factorising prime numbers vastly easier to crunch.
That’s not to say quantum computing could never be a useful addition for your home desktop. But to even begin dreaming of the possibilities, there are a whole number of problems to solve first.
One of them is to ramp up a measly handful of qubits from less than 20 to something that can begin to rival our best classical supercomputers on those trickier tasks.
That number? About 50-odd, a figure that’s often referred to in rather rapturous terms as quantum supremacy.
The Harvard device was based on an array of super-cooled atoms of rubidium held in a trap of magnets and laser ‘tweezers’ that were then excited in a fashion that allowed their quantum states to be used as a single system.
The researchers were able to control 51 of these trapped atoms in such a way that they could model some pretty complex quantum mechanics, something well out of reach of your everyday desktop computer.
While the modelling was mostly used to test the limits of this kind of set-up, the researchers gained useful insights into the quantum dynamics associated with what’s called many-body phenomena.
Fortunately they were still able to test their relatively simpler discoveries using classical computers, finding their technique was right on the money.
The research is currently on the pre-publish website arXiv.com, awaiting peer review. But the announcement certainly has the quantum computing community talking about the possibilities and consequences of achieving such limits.
The magical number of 50 qubits is more like a relative horizon than a true landmark. Not much has changed in the world of quantum computing with the Harvard announcement, and we still have a long way to go before this kind of technology will be useful in making any significant discoveries.
Google’s own plan for a 49-qubit device uses a completely different process to Lukin’s, relying on multiple-qubit quantum chips that employ a solid-state superconducting structure called a Josephson junction.
They’ve proven their technology with a simpler 9-qubit version, and plan to gradually step up to their goal.
Without going into detail, each of the technologies has its pros and cons when it comes to scaling and reliability.
A significant problem with quantum computing will be how to make the system as reliable and error-free as possible. While classical computing can duplicate processes to reduce the risk of mistakes, the probabilistic nature of qubits makes this impossible for quantum calculations.
There’s also the question on how to connect a number of units together to form ever larger processors.
Which methods will address these concerns best in the long run is anybody’s guess.
“There are several platforms that are very promising, and they are all entering the regime where it is getting interesting, you know, system sizes you cannot simulate with classical computers,” Lukin said to Himanshu Goenka from International Business Times.
“But I think it is way premature to pick a winner among them. Moreover, if we are thinking about truly large scales, hundreds of thousands of qubits, systems which will be needed for some algorithms, to be honest, I don’t think anyone knows how to go there.”
It’s a small step on the road to a hundred thousand qubits, but it doesn’t make passing this milestone any less significant.
Happy 51, Harvard!
See the article here:
We’re About to Cross The ‘Quantum Supremacy’ Limit in Computing – ScienceAlert
Explaining the Most Recent Record for Quantum Computing: A 51-Qubit Quantum Computer Array – All About Circuits
Last month, a team of Russian and American scientists unveiled a quantum computer array with 51 qubits at the International Conference on Quantum Technologies in Moscow. Here’s a look at how they accomplished this new milestone with the use of cold atoms and lasers.
If you’re already familiar with quantum computing, I recommend skipping to the next section. If you’re not familiar with quantum computing, it is aptly named for its quantum properties. In quantum physics, particles do not have a defined location until they are observed. In classical computing, digital data is read in bits, which are 1s and 0s, or ON and OFF states, which we know as binary, which can be manipulated into different arrangements using various logic gates.
Quantum computing combines concepts from classical computing and quantum mechanics to make qubits (a shortened nickname for “quantum bits”). Unlike classical bits, qubits can be a 1 or 0 at the same time, much like Schrodinger’s cat, which is in a state of flux until observed. So,four bits have 16 possible combinations (24), whereas four qubits can be in every possible combination at the same time until they are observed. This allows a quantum computer to perform every possible calculation at the same time. A quantum algorithm reduces the time required for large calculations by the square root of the number of entries being searched.
Quantum computers are not practical for most tasks handled by personal computers, but they excel at large-scale calculations such as searching databases, running simulations, and even breaking encryptions. The video below is the simplest explanation of quantum computing I have seen so far.
It seems like every few months, quantum computing reaches a new milestone. Last month, at the International Conference on Quantum Technologies in Moscow, attendees and reporters gathered in mass for Professor John Martinis’ presentation of a chip embedded with 49 qubits. Instead, in a fashion that reminds me of Steve Harvey announcing the Miss Universe pageant, Mikhail Lukin, a Harvard professor and co-founder of the Russian Quantum Centermade his own announcement and stole the show.
Lukin’s team had successfully created the world’s most powerful, functional quantum computer to date, which runs on 51 qubits. The device was tested successfully at Harvard, where it solved physics problems that silicon chip-based supercomputers were struggling with.
Most quantum computers have been designed using superconductors and even semiconductors. Martinis’ 49-qubit chip was constructed in this fashion. Since traditional semiconductor materials are reaching their limits, Lukin’s team took a different approach.
The 51-qubit machine uses “cold atoms” in place of qubits that are locked onto laser cells. Cold atom physics is the discipline of studying atoms at incredibly low temperatures (.0000001 degrees Kelvin) in order to recreate quantum conditions. Cooling atoms to temperatures near absolute zero slows their movement down and makes them easier to observe. The video below gives an introduction to cold atom physics (starting at 1:35). After that, we’ll get into the biggest question I had about all of this:
How the heck do super-cooled atoms with lasers shining through them make a computer?
Lukin’s team wrote a research paper (PDF) explaining the experiment they set up. After sifting through the equations, I arrived at the data-reading mechanism. The setup consists of a linear array101 evenly spaced “optical tweezers”, which are generated by feeding a multi-tone RF signal into an into an acousto-optic deflector.
In simpler terms, they shine a laser beam through a vacuum tube and take fluorescence images(a type of laser scanning microscopy) of the atoms as they change betweenpositions. The “traps” that control the position of the atoms are programmable, which allows this super cooledvacuum tube with a laser shooting through it to function like a quantum computer.
As computing devices become ever smaller, engineers have been teaming up with scientists from other disciplines like physics and biology to make some outside-the box computing devices. Although it’s unlikely that any of these will end up in personal devices anytime soon (or ever), it always reminds me that a computer is just a device that calculates problems, and what our concept of a “computer” will look like in 100 years might just be beyond our current levels of comprehension.
If you’d like to learn more about quantum computing, I’ve compiled some resources below along with some of my favorite outlandish non-silicon computers!
Featured image used courtesy of Kurzgesagt