Category Archives: Quantum Computing
The simulator will allow developers to test programs and debug code with their own computers, which is necessary since there really aren’t any quantum computers for them to test their work on yet. Microsoft is also offering a more powerful simulator — one with over 40 logical qubits of computing power — through its Azure cloud computing service. And because the kit is integrated into Microsoft’s Visual Studio developer tool suite, many aspects of the new kit will be familiar.
“What you’re going to see as a developer is the opportunity to tie into tools that you already know well, services you already know well,” Todd Holmdahl, Microsoft’s VP in charge of its quantum effort, said in a statement. “There will be a twist with quantum computing, but it’s our job to make it as easy as possible for the developers who know and love us to be able to use these new tools that could potentially do some things exponentially faster which means going from a billion years on a classical computer to a couple hours on a quantum computer.”
The 20th century gave birth to the Nuclear Age as the power of the atom was harnessed and unleashed. Today, we are on the cusp of an equally momentous and irrevocable breakthrough: the advent of computers that draw their computational capability from quantum mechanics.
US representative Will Hurd (R-Texas) (@HurdOnTheHill) chairs the Information Technology Subcommittee of the Committee on Oversight and Government Reform and serves on the Committee on Homeland Security and the Permanent Select Committee on Intelligence.
The potential benefits of mastering quantum computing, from advances in cancer research to unlocking the mysteries of the universe, are limitless.
But that same computing power can be used to unlock different kinds of secretsfrom your personal financial or health records, to corporate research projects and classified government intelligence.
Its more than just theoretical: An algorithm formulated by mathematician Peter Shor demonstrates that quantum computers are able to factor large numbers more efficiently than classical computers. Large-number factoring is the foundation of todays encryption standards.
The impact of quantum on our national defense will be tremendous. The question is whether the United States and its allies will be ready.
The consequences of mastering quantum computing, while not as visual or visceral as a mushroom cloud, are no less significant than those faced by the scientists who lit up the New Mexico sky with the detonation at the Trinity test site 72 years ago. In the same way that atomic weaponry symbolized power throughout the Cold War, quantum capability is likely to define hegemony in todays increasingly digital, interconnected global economy.
Unlike traditional computers, which process information in binary bits, quantum computers exploit the ability of quantum bits (qubits) to exist in multiple states simultaneously. This allows them to perform incredibly complex calculations at speeds unimaginable today and solve certain classes of problems that are beyond the grasp of todays most advanced super computers.
Today, quantum computers are beginning to move out of research labs in search of broader investment and applications. In October, Google announced that by the end of this year it expects to achieve quantum supremacythe point at which a quantum computer can outperform a classical computer.
Because nations around the world, including China, are investing heavily in research and development, the world is likely less than a decade away from the day when a nation-state could use quantum computers to render many of todays most sophisticated encryption systems useless.
From academics to the National Security Agency, there is widespread agreement that quantum computers will rock current security protocols that protect global financial markets and the inner workings of government.
Already, intelligence agencies around the world are archiving intercepted communications transmitted with encryption that’s currently all but unbreakable, in the hopes that in the future computing advances will turn whats gibberish now into potentially valuable intelligence. Rogue states may also be able to leverage the power of quantum to attack the banking and financial systems at the heart of western capitalism.
Everyone has seen the damage individual hackers can do when they infiltrate a system. Imagine a nation-state intercepting the encrypted financial data that flows across the globe and being able to read it as easily as you are reading this. Quantum computers are so big and expensive thatoutside of global technology companies and well-funded research universitiesmost will be owned and maintained by nation-states. That means the first quantum attacks are likely to be organized by countries hostile to the US and our allies. Rogue states could read military communiques the way the United States and its allies did after cracking the Nazi Enigma codes.
In short, quantum computing presents both an unprecedented opportunity and a serious threat. The United States must lead this transition, in collaboration with its allies around the world. Whether lawmakers want to think of it as a new Manhattan Project or a race to the moon, the US cannot abdicate leadership in scientific discovery or international security.
The window is closing, fast. It took more than five years and nearly half a trillion dollars for companies and governments to prepare for Y2K, which resulted in a non-event for most people. But, the US is not ready for what experts call Y2Q (Years to Quantum), and the time to prepare is now. Even in a pre-quantum era, the need for quantum-safe encryption is real. Banks, government agencies, insurers, hospitals, utilities, and airlines all need to be thinking now about how to implement security and encryption that will withstand a quantum attack.
On complex, large-scale networks, it can take years to roll out even a relatively straightforward update. Quantum-safe encryption relies on mathematical approaches that even quantum computers have difficulty solving. The challenge is ensuring that every point through which data flows, and even the data itself, is wrapped in quantum-safe security.
Private sector research and development are happening in pockets across North America and among the US’s allies. Google and IBM both have well-publicized programs to build viable quantum computers. At the same time, though, the US and its allies must take practical steps to prepare for the quantum threat. The National Institute of Standards and Technology is working to evaluate quantum-safe cryptographic candidate algorithms. Other organizations like the European Telecommunications Standards Institute and the United Nations International Telecommunications Union are working to ensure our standards for connecting systems continue to evolve to be quantum safe. Companies like ISARA are among a small cadre of cryptographers and programmers building quantum-safe security solutions to help high-risk industries and organizations begin protecting themselves.
Its these kinds of efforts that the US and its allies must collaborate on to align the goals of scientific discovery, technological advancement, and national security. As companies build powerful quantum machines, leaders must simultaneously understand the risks those machines pose and the counter-measures required. Executives in every industry need to understand the implications that quantum computing will have on their legacy systems, and take steps to be ready. At a minimum, that means retrofitting their networks, computers, and applications with encryption that can withstand a quantum attack.
Nowhere is it more vital to begin preparations than with the vast network of governmental systems that do everything from processing Social Security checks to analyzing vast amounts of electronic intelligence.
Whether it was the discovery of fission or the launch of Sputnik, the United States has responded to scientific challenges of the past century with resolve and determination. The US must do the same with quantum computing.
WIRED Opinion publishes pieces written by outside contributors and represents a wide range of viewpoints. Read more opinions here.
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Quantum Computing Is the Next Big Security Risk | WIRED
Quantum computing systems are difficult to understand because they do not behave like the everyday world we live in. But this counterintuitive behavior is what allows them to perform calculations at rate that would not be possible on a typical computer.
Todays computers store information as bits, with each transistor holding either a 1 or a 0. But thanks to something called the superposition principle behavior exhibited by subatomic particles like electrons and photons, the fundamental particles of light a quantum bit, or qubit, can store a 1 and a 0 at the same time. This means two qubits can hold four values at once. As you expand the number of qubits, the machine becomes exponentially more powerful.
Todd Holmdahl, who oversees the quantum project at Microsoft, said he envisioned a quantum computer as something that could instantly find its way through a maze. A typical computer will try one path and get blocked and then try another and another and another, he said. A quantum computer can try all paths at the same time.
The trouble is that storing information in a quantum system for more than a short amount of time is very difficult, and this short coherence time leads to errors in calculations. But over the past two decades, Mr. Schoelkopf and other physicists have worked to solve this problem using what are called superconducting circuits. They have built qubits from materials that exhibit quantum properties when cooled to extremely low temperatures.
With this technique, they have shown that, every three years or so, they can improve coherence times by a factor of 10. This is known as Schoelkopfs Law, a playful ode to Moores Law, the rule that says the number of transistors on computer chips will double every two years.
Schoelkopfs Law started as a joke, but now we use it in many of our research papers, said Isaac Chuang, a professor at the Massachusetts Institute of Technology. No one expected this would be possible, but the improvement has been exponential.
These superconducting circuits have become the primary area of quantum computing research across the industry. One of Mr. Schoelkopfs former students now leads the quantum computing program at IBM. The founder of Rigetti Computing studied with Michel Devoret, one of the other Yale professors behind Quantum Circuits.
In recent months, after grabbing a team of top researchers from the University of California, Santa Barbara, Google indicated it is on the verge of using this method to build a machine that can achieve quantum supremacy when a quantum machine performs a task that would be impossible on your laptop or any other machine that obeys the laws of classical physics.
There are other areas of research that show promise. Microsoft, for example, is betting on particles known as anyons. But superconducting circuits appear likely to be the first systems that will bear real fruit.
The belief is that quantum machines will eventually analyze the interactions between physical molecules with a precision that is not possible today, something that could radically accelerate the development of new medications. Google and others also believe that these systems can significantly accelerate machine learning, the field of teaching computers to learn tasks on their own by analyzing data or experiments with certain behavior.
A quantum computer could also be able to break the encryption algorithms that guard the worlds most sensitive corporate and government data. With so much at stake, it is no surprise that so many companies are betting on this technology, including start-ups like Quantum Circuits.
The deck is stacked against the smaller players, because the big-name companies have so much more money to throw at the problem. But start-ups have their own advantages, even in such a complex and expensive area of research.
Small teams of exceptional people can do exceptional things, said Bill Coughran, who helped oversee the creation of Googles vast internet infrastructure and is now investing in Mr. Schoelkopfs company as a partner at Sequoia. I have yet to see large teams inside big companies doing anything tremendously innovative.
Though Quantum Circuits is using the same quantum method as its bigger competitors, Mr. Schoelkopf argued that his company has an edge because it is tackling the problem differently. Rather than building one large quantum machine, it is constructing a series of tiny machines that can be networked together. He said this will make it easier to correct errors in quantum calculations one of the main difficulties in building one of these complex machines.
But each of the big companies insist that they hold an advantage and each is loudly trumpeting its progress, even if a working machine is still years away.
Mr. Coughran said that he and Sequoia envision Quantum Circuits evolving into a company that can deliver quantum computing to any business or researcher that needs it. Another investor, Canaans Brendan Dickinson, said that if a company like this develops a viable quantum machine, it will become a prime acquisition target.
The promise of a large quantum computer is incredibly powerful, Mr. Dickinson said. It will solve problems we cant even imagine right now.
An earlier version of this article misstated the surname of one of the investors in Quantum Circuits. As correctly noted elsewhere in the article, he is Brendan Dickinson, not Dickson.
Quantum computers work much differently than regular supercomputers, taking advantage of weird quantum physics principals like “superposition.” In theory, they can run specific programs, like encryption-cracking algorithms, many, many times faster than regular computers.
The 50 qubit system (shown below) is a significant leap toward practical quantum computers. “We are really proud of this, it’s a big frickin’ deal,” IBM AI and quantum computer director Dario Gil told MIT Technology Review. Other players in quantum computing including Google, Intel and Rigetti.
IBM’s 50 qubit computer is just a prototype, but it will soon have a working 20 qubit computer that users can try online by the end of 2017, with improvements planned throughout 2018. The company has already made lower-powered machines available for cloud use, and used a 7 qubit model to simulate a molecule, for example. IBM says around 60,000 users have run 1.7 million experiments, resulting in 35 research papers.
Quantum computers haven’t been able to run programs that a regular computer can’t, so the massive speed breakthrough many have hoped for has yet to arrive. Still, Google researchers said last month that a 50 qubit computer they’re working on could surpass current supercomputers, achieving an (excellently-named) milestone called Quantum Supremacy. The technology is tricky, though, so there’s good reason not to get too excited. But, there’s also a good chance that quantum computers will finally break that barrier sometime in the next year or two.
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IBM’s processor pushes quantum computing … – engadget.com
A full stackWith Mundies backing, Freedman set up a lab in Santa Barbara, California, and began recruiting some of the worlds pre-eminent condensed-matter and theoretical physicists, materials scientists, mathematicians and computer scientists to work on building the topological qubit. That team now boasts many leading quantum experts who have joined Microsoft as employees in the past year, including Leo Kouwenhoven, Charles Marcus, David Reilly and Matthias Troyer.
To create the infrastructure for a full computing platform, Microsoft has simultaneously worked on building hardware, software and programming languages for topological quantum computing.
At Ignite on Monday, Microsoft announced the latest milestone in its effort to build a full stack: A new programming language that is designed for developers to create apps to debug on quantum simulators today and run on an actual topological quantum computer in the future.
The same code that youre running today in simulation you can run tomorrow on our quantum computer, Svore said.
Svore said the new tools are designed for developers who are interested in being on the cutting-edge of computer advances the same type of people who were early adopters of machine learning and other artificial intelligence advances.
You dont have to be a quantum physicist to use them. The new programming language is deeply integrated into Visual Studio, and it includes the kinds of tools that developers rely on for classical computing, such as debugging and auto complete.
It shouldnt look too different from the things theyre already doing, Svore said.
The system, which will be available as a free preview by the end of the year, also includes libraries and tutorials so developers can familiarize themselves with quantum computing. Its designed to work at a higher level of abstraction, so that developers without quantum expertise can actually call quantum subroutines, or write sequences of programming instructions, working up to writing a complete quantum program. Developers can sign up to participate today.
The system is designed so that individual users can simulate problems that require up to 30 logical qubits of power on their own personal computers, and select enterprise customers, using Azure, can simulate more than 40 qubits of computational power.
In quantum computing, the power grows exponentially with the number of logical qubits. A logical qubit is the qubit at the level of the algorithm. At that hardware level, each logical qubit is represented in hardware by a number of physical qubits to enable protection of the logical information. Microsofts approach takes fewer topological qubits to develop one logical qubit, making it far easier to scale.
Svore said one key advantage to having a programming language that works in a simulation environment is that it will help people interested in using quantum computers to solve problems get a better sense of how to harness quantum power for different types of problems. That will accelerate their ability to take advantage of quantum computing when its available.
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Quantum computing – news.microsoft.com
October 11, 2017Timothy Prickett Morgan
Someone is going to commercialize a general purpose, universal quantum computer first, and Intel wants to be the first. So does Google. So does IBM. And D-Wave is pretty sure it already has done this, even if many academics and a slew of upstart competitors dont agree. What we can all agree on is that there is a very long road ahead in the development of quantum computing, and it will be a costly endeavor that could nonetheless help solve some intractable problems.
This week, Intel showed off the handiwork its engineers and those of partner QuTech, a quantum computing spinoff from the Technical University of Delft and Toegepast Natuurwetenschappelijk Onderzoek (TNO), which as the name suggests is an applied science research firm that, among other things, is working with Intel on quantum computing technology.
TNO, which was established in 1988, has a 500 million annual budget and does all kinds of primary research. The Netherlands has become a hotbed of quantum computing technology, along with the United States and Japan, and its government wants to keep it that way and hence the partnership in late 2015 with Intel, which invested $50 million in the QuTech partnership between TU Delft and TNO so it could jumpstart its own quantum computing program after sitting on the sidelines.
With this partnership, Intel is bringing its expertise in materials science, semiconductor manufacturing, interconnects, and digital systems to play to help develop two types of quantum bits, or qubits, which are the basic element of processing in a quantum computer. The QuTech partnership involves the manufacturing of superconducting qubits, but Intel also is working on another technology called spin qubits that makes use of more traditional semiconductor technologies to create what is, in essence, the quantum transistor for this very funky and very parallel style of computing.
The big news this week is that Intel has been able to take a qubit design that its engineers created alongside of those working at QuTech and scale it up to 17 qubits on a single package. A year ago, the Intel-QuTech partnership had only a few qubits on their initial devices, Jim Clarke, director of quantum hardware at Intel, tells The Next Platform, and two years ago it had none. So that is a pretty impressive roadmap in a world where Google is testing a 20 qubit chip and hopes to have one running at 49 qubits before the year is out. Google also has quantum annealing systems from D-Wave, which have much more scale in terms of qubits 1,000 today and 2,000 on the horizon but according to Intel are not a generic enough to be properly commercialized. And if Intel knows anything, it knows how to create a universal computing substrate and scale its manufacturing and its deployment in the datacenters of the world.
Production and cleanroom facilities for the quantum chip made at Intels D1D/D1X plant in Hillsboro, Oregon, in April 2017.
We are trying to build a general purpose, universal quantum computer, says Clarke. This is not a quantum annealer, like the D-Wave machine. There are many different types of qubits, which are the devices for quantum computing, and one of the things that sets Intel apart from the other players is that we are focused on multiple qubit types. The first is a superconducting qubit, which is similar to what Google, IBM, and a startup named Rigetti Computing are working on. But Intel is also working on spin qubits in silicon are very similar to our transistor technologies, and you can expect to hear about that in the next couple of months. These spin qubits build on our expertise in ordinary chip fabrication, and what really sets us apart here is our use of advanced packaging at very low temperatures to improve the performance of the qubit, and with an eye towards scalability.
Just as people are obsessed with the number of transistors or cores on a standard digital processor, people are becoming a bit obsessed with the number of qubits on a quantum chip, and Jim Held, director of emerging technology research at Intel Labs, says that this focus is a bit misplaced. And for those of us who look at systems for a living, this makes perfect sense. Intel is focused on getting the system design right, and then scaling it up on all vectors to build a very powerful quantum machine.
Here is the situation as Held sees it, and breathe in deeply here:
People focus on the number of qubits, but that is just one piece of what is needed. We are really approaching this as engineers, and everything is different about this kind of computer. It is not just the devices, but the control electronics and how the qubits are manipulated with microwave pulses and measured with very sensitive DC instrumentation, and it is more like an analog computer in some respects. Then it has digital electronics that do error correction because quantum devices are very fragile, and they are prone to errors and to the degree that we can correct the errors, we can compute better and longer with them. It also means a new kind of compiler in order to get the potential parallelism in an array of these qubits, and even the programs, the algorithms, written for these devices are an entirely different kind of thing from conventional digital programming. Every aspect of the stack is different. While there is research going on in the academic world at all levels, as an engineering organization we are coming at them all together because we know we have to deliver them all at once as a computer. Moreover, our experience tells us that we want to understand at any given point what our choices at one level are going to mean for the rest of the computer. What we know is that if you have a plate full of these qubits, you do not have a quantum computer, and some of the toughest problems with scaling are in the rest of the stack. Focusing on the number of qubits or the coherence time really does a disservice to the process of getting to something useful.
This is analogous to massively parallel machines that dont have enough bandwidth or low latency to talk across cores, sockets, or nodes efficiently and to share work. You can cram as many cores as you want in them, but the jobs wont finish faster.
And thus, Intel is focusing its research on the interconnects that will link qubits together on a device and across multiple devices.
The interconnects are one of the things that concerns us most with quantum computing, says Clarke. From the outset, we have not been focused on a near-term milestone, but rather on what it would take from the interconnect perspective, from the point of view of the design and the control, to deliver a large scale, universal quantum computer.
Interestingly, Clarke says that the on-chip interconnect on commercial quantum chips will be similar to that used on a conventional digital CPU, but it may not be made out of copper wires, but rather superconducting materials.
The one used in the superconducting qubit chip that Intel just fabbed in its Oregon factory and packaged in its Arizona packaging facility is a bit ridiculous looking.
Quantum computing presents a few physical challenges, and superconducting qubits are especially tricky. To keep preserve the quantum states that allow superposition a kind of multiple, concurrent state of the bits that allows for parallel processing at the bit level, to over simplify hugely requires for these analog devices to be kept at extremely cold temperatures and yet still have to interface with the control electronics in the outside world, crammed into a rack.
We are putting these chips in an extremely cold environment 20 millikelvins, and that is much colder than outer space, says Clarke. And first of all, we have to make sure that the chip doesnt fall apart at these temperatures. You have thermal coefficient of expansion. Then you need to worry about package yield and then about the individual qubit yield. Then we worry about wiring them up in a more extensible fashion. These are very high quality radio or microwave frequency chips and we have to make sure we maintain that quality at low temperature once the device is packaged. A lot of the performance and yield that we are getting comes from the packaging.
So for this chip, Intel has wallpapered one side of the chip with standard coaxial ports, like the ones on the back of your home router. Each qubit has two or more coax ports going into it to control its state and to monitor that state. How retro:
We are focused on a commercial machine, so we are much more interested in scaling issues, Held continues along this line of thinking. You have to be careful to not end up in a dead end that only gets you so far. This quantum chip interconnect is not sophisticated like Omni-Path, and it does not scale well, Held adds with a laugh. What we are interested in is improving on that to reduce the massive number of connections. A million qubits turning into millions of coax cables is obviously not going to work. Even at hundreds of qubits, this is not going to work. One way we are going to do this is to move the electronics that is going to control this quantum machine into this very cold environment, not down at the millikelvin level, but a layer or two up at the 4 kelvin temperature of liquid hydrogen. Our partners at QuTech are experts at cryo-CMOS, which means making chips work in this 4 kelvin range. By moving this control circuitry from a rack outside of the quantum computer into the refrigeration unit, it cuts the length of the connections to the qubits.
With qubits, superposition allows a single qubit to represent two different states, and quantum entanglement what Einstein called spooky action at a distance allows for the states to scale linearly as the qubit counts go up. Technically, n quantum bits yield 2 to the n states. (We wrote that out because there is something funky about superscripts in the Alike font we use here at The Next Platform.) The interconnect is not used to maintain the quantum states across the qubits that happens because of physics but to monitor the qubit states and maintain those states and, importantly, to do error correction. Qubits cant be shaken or stirred or they lose their state, and they are extremely fussy. As Google pointed out two years ago at the International Super Computing conference in Germany, a quantum computer could end up being an accelerator for a traditional parallel supercomputer, which is used to do error correction and monitoring of qubits. Intel is also thinking this might happen.
The fussiness of superconducting qubits is probably one of the reasons why Intel is looking to spin qubits and a more standard semiconductor process to create a quantum computer chip whose state is easier to maintain. The other is that Intel is obviously an expert at manufacturing semiconductor devices. So, we think, the work with QuTech is as much about creating a testbed system and a software stack that might be portable as it is investing in this particular superconducting approach. Time will tell.
And time, indeed, it will take. Both Held and Clarke independently think it will take maybe eight to ten years to get a general purpose, universal quantum computer commercialized and operating at a useful scale.
It is research, so we are only coming to timing based on how we think we are going to solve a number of problems, says Held. There will be a milestone where a machine will be able to tackle interesting but small problems, and then there will be a full scale machine that is mature enough to be a general purpose, widely useful accelerator in the supercomputer environment or in the cloud. These will not be free-standing computers because they dont do a lot of things that a classical digital computer does really well. They could do them, because in theory any quantum computer can do anything a digital computer can do, but they dont do it well. It is going to take on the order of eight to ten years to solve these problems we are solving now. They are all engineering problems; the physicists have done an excellent job of finding feasible solutions out of the lab and scaling them out.
Clarke adds a note of caution, pointing out that there are a lot of physics problems that need to be solved for the packaging aspects of a quantum computer. But I think to solve the next level of physics problems, we need a healthy dose of engineering and process control, Clarke says. I think eight to ten years is probably fair. We are currently at mile one of a marathon. Intel is already in the lead pack. But when we think of a commercially relevant quantum computer, we think of one that is relevant to the general population, and moreover, one that would show up on Intels bottom line. They key is that we are building a system, and at first, that system is going to be pretty small but it is going to educate us about all aspects of the quantum computing stack. At the same time, we are designing that system for extensibility, both at the hardware level and at the architecture control level to get to many more qubits. We want to make the system better, and larger, and it is probably a bit premature to start assigning numbers to that other than to say that we are thinking about the longer term.
It seems we might need a quantum computer to figure out when we might get a quantum computer.
Categories: Cloud, Compute, HPC, Hyperscale
Tags: Delft, Intel, quantum, qubit, QuTech, spin qubit, Superconducting, TNO
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Intel Takes First Steps To Universal Quantum Computing
According to Intel, the building blocks of quantum computing, qubits, are very fragile. They can only operate at extremely low temperatures (250 times colder than deep space) and must be packaged carefully to prevent data loss. Intel’s research groups in Oregon and Arizona have found a way to manufacture 17-quibit chips with an architecture that makes them more reliable at higher temperatures and reduced RF interference between each qubit. The chip can send and receive 10 to 100 times more signal than comparable wire-bonded chips and has an advanced design that allows for the techniques to be applied to larger quantum integrated circuits, which are much bigger than typical silicon chips.
“Our quantum research has progressed to the point where our partner QuTech is simulating quantum algorithm workloads, and Intel is fabricating new qubit test chips on a regular basis in our leading-edge manufacturing facilities,” said Intel Labs’ Dr. Michael Mayberry. “Intel’s expertise in fabrication, control electronics and architecture sets us apart and will serve us well as we venture into new computing paradigms, from neuromorphic to quantum computing.”
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quantum computing – engadget.com
Instead of creating quantum computers based on qubits that can each adopt only two possible options, scientists have now developed a microchip that can generate qudits that can each assume 10 or more states, potentially opening up a new way to creating incredibly powerful quantum computers, a new study finds.
Classical computers switch transistors either on or off to symbolize data as ones and zeroes. In contrast, quantum computers use quantum bits, or qubitsthat, because of the bizarre nature of quantum physics, can be in a state ofsuperpositionwhere they simultaneously act as both 1 and 0.
The superpositions that qubits can adopt let them each help perform two calculations at once. If two qubitsare quantum-mechanically linked, orentangled,they can help perform four calculations simultaneously; three qubits, eight calculations; and so on. As a result, aquantum computer with 300 qubits could perform more calculations in an instant than there are atoms in the known universe, solving certain problems much faster than classical computers. However, superpositions are extraordinarily fragile, making it difficult to work with multiple qubits.
Most attempts at building practical quantum computers rely on particles that serve as qubits. However, scientists have long known that they could in principle use quditswith more than two states simultaneously. In principle, a quantum computer with two 32-state qudits, for example, would be able to perform as many operations as 10 qubits while skipping the challenges inherent with working with 10 qubits together.
Researchers used the setup pictured above to create, manipulate, and detect qudits. The experiment starts when a laser fires pulses of light into a micro-ring resonator, which in turn emits entangled pairs of photons.Because the ring has multiple resonances, the photons have optical spectrumswitha set of evenly spaced frequencies(red and blue peaks), a process known as spontaneous four-wave mixing (SFWM).The researchers were able to use each of thefrequencies to encode information, which means the photons act asqudits.Each quditis in a superposition of 10 possible states, extending the usual binary alphabet (0 and 1) of quantum bits.The researchers also showed they could perform basic gate operations on the qudits using optical filters and modulators, and then detect the results using single-photon counters.
Now scientists have for the first time created a microchip that can generate two entangled qudits each with 10 states, for 100 dimensions total, more than what six entangled qubits could generate. We have now achieved the compact and easy generation of high-dimensional quantum states, says study co-lead author Michael Kues, a quantum optics researcher at Canadas National Institute of Scientific Research, or INRS,its French acronym,in Varennes, Quebec.
The researchers developed a photonic chip fabricated using techniques similar to ones used for integrated circuits. A laser fires pulses of light into a micro-ring resonator, a 270-micrometer-diameter circle etched onto silica glass, which in turn emits entangled pairs of photons. Each photon is in a superposition of 10 possible wavelengths or colors.
For example, a high-dimensional photon can be red and yellow and green and blue, although the photons used here were in the infrared wavelength range, Kues says. Specifically, one photon from each pair spanned wavelengths from 1534 to 1550 nanometers, while the other spanned from 1550 to 1566 nanometers.
Using commercial off-the-shelf telecommunications components, the researchers showed they could manipulate these entangled photons. The basic capabilities they show are really what you need to do universal quantum computation, says quantum optics researcher Joseph Lukens at Oak Ridge National Laboratory, in Tennessee, who did not take part in this research. Its pretty exciting stuff.
In addition, by sending the entangled photons through a 24.2-kilometer-long optical fiber telecommunications system, the researchers showed that entanglement was preserved over large distances. This could prove useful for nigh-unhackable quantum communications applications, the researchers say.
What I think is amazing about our system is that it can be created using components that are out on the market, whereas other quantum computer technologies need state-of-the-art cryogenics, state-of-the-art superconductors, state-of-the-art magnets, saysstudy co-senior authorRoberto Morandotti, a physicistatINRSin Varennes. The fact that we use basic telecommunications components to access and control these states means that a lot of researchers could explore this area as well.
The scientists noted that current state-of-the-art components could conceivably generate entangled pairs of 96-state qudits, corresponding to more dimensions than 13 qubits. Conceptually, in principle, I dont see a limit to the number of states of qudits right now, Lukens, from Oak Ridge,says. I do think a 96-by-96-dimensional system is fairly reasonable, and achievable in the near future.
But he adds that several components of the experiment were not on the microchips, such as the programmable filters and phase modulators, which led to photon loss. Kues says that integrating such components with the rest of the chips and optimizing their micro-ring resonator would help reduce such losses to make their system more practical for use.
The next big challenge we will have to solve is to use our system for quantum computation and quantum communications applications, Kues says. While this will take some additional years, it is the final step required to achieve systems that can outperform classical computers and communications.
The scientists detailed their findings in the latest issue of the journal Nature.
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Qudits: The Real Future of Quantum Computing? – IEEE Spectrum
Quantum computing is an exciting new computing paradigm with unique problems to be solved and new physics to be discovered. Quantum computing, in essence, is the ultimate in parallel computing, with the potential to tackle problems conventional computers cant handle. For example, quantum computers may simulate nature to advance research in chemistry, materials science and molecular modeling.
In 2015, Intel established a collaborative relationship with QuTech to accelerate advancements in quantum computing. The collaboration spans the entire quantum system or stack from qubit devices to the hardware and software architecture required to control these devices as well as quantum applications. All of these elements are essential to advancing quantum computing from research to reality.
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Intels director of quantum hardware, Jim Clarke, holds the new 17-qubit superconducting test chip. (Credit: Intel Corporation)
Intels 17-qubit superconducting test chip for quantum computing has unique features for improved connectivity and better electrical and thermo-mechanical performance. (Credit: Intel Corporation)
Researchers work in the quantum computing lab at QuTech, Intels quantum research partner in the Netherlands. Intel in October 2017 provided QuTech a 17-qubit superconducting test chip for quantum computing. (Credit: QuTech)
Professor Leo DiCarlo poses in the quantum computing lab at QuTech, Intels quantum research partner in the Netherlands. Intel in October 2017 provided QuTech a 17-qubit superconducting test chip for quantum computing. (Credit: QuTech)
Intel is collaborating with QuTech in the Netherlands to advance quantum computing research. Intel in October 2017 provided QuTech a 17-qubit superconducting test chip for quantum computing. (Credit: Intel Corporation)
Intels new 17-qubit superconducting test chip packaged for delivery to research partners at QuTech, Intels quantum research partner in the Netherlands. Intel in October 2017 provided QuTech with the 17-qubit superconducting test chip for quantum computing. (Credit: Intel Corporation)
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Quantum Computing | Intel Newsroom
With a tip of the hat to our Big on Data bro George Anadiotis, this week, we’re breaking from our usual routine of the here and now to look at what’s coming next. Mention the words quantum computing, and your first impression is that we’re probably going to be spouting science fiction.
So what is quantum computing? It harnesses the physics of subatomic particles to provide a different way to store data and solve problems compared to conventional computers. Specifically, it totally turns the world of conventional binary computing on its side because quantum computing bits, or qubits, can represent multiple states at once, rather than just 0 or 1. The result is that quantum computers could solve certain HPC-like problems more efficiently.
Oh and by the way, did we mention that quantum computers must run at 4 degrees Kelvin? That’s 4 degrees above absolute zero, far colder than interstellar space.
It’s tempting to dismiss quantum computers as the computing equivalent of Warp Speed out of Star Trek. Then again, it was barely a few months ago where we saw SAS founder James Goodnight talking to Alexa to gin up a SAS analytics run in much the same way that Captain James T. Kirk spoke to his computers.
So why are we having this conversation?
Our attention was piqued by a chain of events over the past month. IBM first convened an analyst call around an upcoming article in the scientific journal Nature showing how a quantum computing modeling problem for complex molecular behavior would be documented in a Jupyter notebook. (If you want to get technical, it was about how to derive the lowest energy state of a molecule of beryllium hydride.)
Then Satya Nadella assembled a panel of Microsoft researchers to conclude his Ignite conference keynote with a session on pure theoretical physics that sailed straight over the heads of the business analyst and developer audience. Fortunately, the IBM call was way more plain spoken, addressing how quantum computers could be applied to common business problems, and where the technology stands today.
Turns out, quantum computers represent advances that would look familiar to veterans of big data analytics where you could query all of the data, not just a sample. It would also look familiar to those working with graph computing where you could factor the complexity of many-to-many relationships that would otherwise require endless joins with relational data models.
Quantum computing lends itself to any optimization problem where the combination of what-ifs, and all the permutations associated with them, would simply overwhelm a conventional binary computer. That lends itself to a large trove of mundane business and operational problems that are surprisingly familiar.
For instance, if you try to optimize a supply chain, chances are, you are narrowing down the problem to tackle the dozen most likely scenarios. With the resources of quantum computing, you could widen and deepen the analysis to virtually all possible scenarios. The same goes with tangible business challenges like managing financial risk when you have a complex tangle of interlocking trading systems across the globe. Or imagine, during drug testing, that a clinical research team could model all the potential interactions of a new drug with virtually the entire basket of medications that a specific patient cohort would be likely also be taking? And from there, could true personalized medicine be far behind?
But quantum computing development is still embryonic. A small Canadian startup, D Wave Systems, is selling units on a limited basis today. IBM is offering machines from of a half dozen 5 – 17 qubits in the cloud while Google is developing architectures that could scale up to 49. So it’s not surprising that quantum still hits the wall with classes of problems that require complex, iterative processing (which, by the way, is what Spark excels at).
A good example of the type of problem that for now is just out of reach is encryption/decryption. As the algorithms grow more complex, it means factoring larger and larger prime numbers. Turns out, the interactions between qubits (which is called quantum entanglement) could short-cut such problems by taking the square root of the number of entries, and reducing the number of steps accordingly. The bottleneck is memory; such computations would require storing of state or interim results, much like a Spark or MapReduce problem. The problem is that, while development of compute chips is underway, nobody yet knows what true quantum memory would look like.
That would imply that for some problems, a division of labor where quantum factors the permutations while conventional scale-out systems handle the iterative processing might be an interim (or long-term) step.
There are a surprisingly sizable number of organizations currently pursuing quantum computing. Right now, most of the action is basic government-funded R&D, although some reports estimate VC investment over the past three years amounting to roughly $150 million. On one hand, it would be easy to get overly optimistic on near-term prospects for development given the rate at which technologies as varied as smart mobile devices, Internet of things, big data analytics, and cloud computing have blossomed from practically nothing a decade ago.
But the barriers to adoption of quantum are both physical and intellectual.
There is the physical need to super-cool machines that, in eras past, would have posed huge obstacles. But the cloud will likely do for quantum machines what they are already starting to do for GPUs: provide the economics for scale-out.
That leaves several more formidable hurdles. The physics of scale out still require basic rather than applied research – we still need to figure out how to scale such a large, fragile system. But the toughest challenge is likely to be intellectual, as it will likely require a different way of thinking to conceptualize a quantum computing problem. That suggests that the onramp to quantum will likely prove more gradual compared to the breakout technologies of the last decade.
See the article here:
What will you actually use quantum computing for? | ZDNet