Category Archives: Quantum Computing

May 9, 2017 by Tom Abate Researchers are developing quantum computers based on light rather than electricity. At Stanford, new materials could be the key to progress in this field. Credit: iStock/Pobytov

For 60 years computers have become smaller, faster and cheaper. But engineers are approaching the limits of how small they can make silicon transistors and how quickly they can push electricity through devices to create digital ones and zeros.

That limitation is why Stanford electrical engineering Professor Jelena Vuckovic is looking to quantum computing, which is based on light rather than electricity. Quantum computers work by isolating spinning electrons inside a new type of semiconductor material. When a laser strikes the electron, it reveals which way it is spinning by emitting one or more quanta, or particles, of light. Those spin states replace the ones and zeros of traditional computing.

Vuckovic, who is one of the world's leading researchers in the field, said quantum computing is ideal for studying biological systems, doing cryptography or data mining in fact, solving any problem with many variables.

"When people talk about finding a needle in a haystack, that's where quantum computing comes in," she said.

Marina Radulaski, a postdoctoral fellow in Vuckovic's lab, said the problem-solving potential of quantum computers stems from the complexity of the laser-electron interactions at the core of the concept.

"With electronics you have zeros and ones," Radulaski said. "But when the laser hits the electron in a quantum system, it creates many possible spin states, and that greater range of possibilities forms the basis for more complex computing."

Capturing electrons

Harnessing information based on the interactions of light and electrons is easier said than done. Some of the world's leading technology companies are trying to build massive quantum computers that rely on materials super-cooled to near absolute zero, the theoretical temperature at which atoms would cease to move.

In her own studies of nearly 20 years, Vuckovic has focused on one aspect of the challenge: creating new types of quantum computer chips that would become the building blocks of future systems.

"To fully realize the promise of quantum computing we will have to develop technologies that can operate in normal environments," she said. "The materials we are exploring bring us closer toward finding tomorrow's quantum processor."

The challenge for Vuckovic's team is developing materials that can trap a single, isolated electron. Working with collaborators worldwide, they have recently tested three different approaches to the problem, one of which can operate at room temperature a critical step if quantum computing is going to become a practical tool.

In all three cases the group started with semiconductor crystals, material with a regular atomic lattice like the girders of a skyscraper. By slightly altering this lattice, they sought to create a structure in which the atomic forces exerted by the material could confine a spinning electron.

"We are trying to develop the basic working unit of a quantum chip, the equivalent of the transistor on a silicon chip," Vuckovic said.

Quantum dots

One way to create this laser-electron interaction chamber is through a structure known as a quantum dot. Physically, the quantum dot is a small amount of indium arsenide inside a crystal of gallium arsenide. The atomic properties of the two materials are known to trap a spinning electron.

In a recent paper in Nature Physics, Kevin Fischer, a graduate student in the Vuckovic lab, describes how the laser-electron processes can be exploited within such a quantum dot to control the input and output of light. By sending more laser power to the quantum dot, the researchers could force it to emit exactly two photons rather than one. They say the quantum dot has practical advantages over other leading quantum computing platforms but still requires cryogenic cooling, so it may not be useful for general-purpose computing. However, it could have applications in creating tamper-proof communications networks.

Color centers

In two other papers Vuckovic took a different approach to electron capture, by modifying a single crystal to trap light in what is called a color center.

In a recent paper published in Nano Letters, her team focused on color centers in diamond. In nature the crystalline lattice of a diamond consists of carbon atoms. Jingyuan Linda Zhang, a graduate student in Vuckovic's lab, described how a 16-member research team replaced some of those carbon atoms with silicon atoms. This one alteration created color centers that effectively trapped spinning electrons in the diamond lattice.

But like the quantum dot, most diamond color center experiments require cryogenic cooling. Though that is an improvement over other approaches that required even more elaborate cooling, Vuckovic wanted to do better.

So she worked with another global team to experiment with a third material, silicon carbide. Commonly known as carborundum, silicon carbide is a hard, transparent crystal used to make clutch plates, brake pads and bulletproof vests. Prior research had shown that silicon carbide could be modified to create color centers at room temperature. But this potential had not yet been made efficient enough to yield a quantum chip.

Vuckovic's team knocked certain silicon atoms out of the silicon carbide lattice in a way that created highly efficient color centers. They also fabricated nanowire structures around the color centers to improve the extraction of photons. Radulaski was the first author on that experiment, which is described in another NanoLetters paper. She said the net results an efficient color center, operating at room temperature, in a material familiar to industry were huge pluses.

"We think we've demonstrated a practical approach to making a quantum chip," Radulaski said.

But the field is still in its early days and electron tapping is no simple feat. Even the researchers aren't sure which method or methods will win out.

"We don't know yet which approach is best, so we continue to experiment," Vuckovic said.

Explore further: Simultaneous detection of multiple spin states in a single quantum dot

More information: Marina Radulaski et al. Scalable Quantum Photonics with Single Color Centers in Silicon Carbide, Nano Letters (2017). DOI: 10.1021/acs.nanolett.6b05102

Journal reference: Nano Letters

Provided by: Stanford University

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New materials bring quantum computing closer to reality - Phys.org - Phys.Org

Quantum computers finally seem to be coming of age with promises of quantum supremacy by the end of the year. But theres a problemvery few people know how to work them.

The bold claim ofachieving "quantum supremacy"came on the back of Google unveiling a new quantum chip design. The hyperbolic phrase essentially means building a quantum device that can perform a calculation impossible for any conventional computer.

In theory, quantum computers can crush conventional ones at important tasks like factoring large numbers. Thats because unlike normal computers, whose bits can either be represented as 0 or 1, a quantum bitor qubitcan be simultaneously 0 and 1 thanks to a phenomenon known as superposition.

Demonstrating this would require thousands of qubits, though, which is well beyond current capabilities. So instead Google plans to compare the computers ability to simulate the behavior of a random arrangement of quantum circuits. They predict it should take 50 qubits to outdo the most powerful supercomputers, a goal they feel they can reach this year.

Clearly the nature of the experiment tips the balance in favor of their chip, but the result would be impressive nonetheless, and could act as a catalyst to spur commercialization of the technology.

This year should also see the first commercial universal quantum computing service go live, with IBM giving customers access to one of its quantum computers over the cloud for a fee. Canadian company D-Wave already provides cloud access to one of its machines, but its quantum computers are not universal, as they can only solve certain optimization problems.

But despite this apparent impetus, the technology has a major challenge to overcome. Programming these devices is much harder than programming conventional computers.

For a start, building algorithms for these machines requires a certain level of understanding about the quantum physics that gives qubits their special properties. While you dont need an advanced physics degree to get your head around it, it is a big departure from traditional computer programming.

Writing in ReadWrite, Dan Rowinski points out, Writing apps that can be translated into some form of qubit-relatable code may require some very different approaches, since among other things, the underlying logic for digital programs may not translate precisely (or at all) to the quantum-computing realm.

And while there are a number of quantum simulators that can run on a laptop for those who want to dip their toes in the water, real quantum computers are likely to behave quite differently. The real challenge is whether you can make your algorithm work on real hardware that has imperfections, Isaac Chuang, an MIT physicist, told Nature.

Convincing programmers to invest the time necessary to learn these skills is going to be tricky until commercial systems are delivering tangible benefits and securing customers, but thats going to be tough if theres no software to run on them.

The companies building these machines recognize this chicken and egg problem, and it is why there is an increasing drive to broaden access to these machines. Before the announcement of the commercial IBMQ service, the company had already released the free Quantum Experience service last year.

Earlier this year, D-Wave open sourced their Qbsolv and Qmasm tools to allow people to start getting to grips with programming its devices, while a pair of Google engineers built a Quantum Computing Playground for people to start investigating the basics of the technology. The company plans to provide access to its devices over the cloud just like IBM.

We dont just want to build these machines, Jerry Chow, the manager of IBMs Experimental Quantum Computing team told Wired. We want to build a framework that allows people to use them.

How easy it will be to translate the skills learned in one of these companies proprietary quantum computing ecosystems to another also remains to be seen, not least because the technology at the heart of them can be dramatically different. This could be a further stumbling block to developing a solid pool of quantum programmers.

Ultimately, the kinds of large-scale quantum computers powerful enough to be usefully put to work on real-world problems are still some years away, so theres no need to panic yet. But as the researchers behind Googles quantum effort note in an article in Nature, this scarcity of programming talent also presents an opportunity for those who move quickly.

If early quantum-computing devices can offer even a modest increase in computing speed or power, early adopters will reap the rewards, they write. Rival companies would face high entry barriers to match the same quality of services and products, because few experts can write quantum algorithms, and businesses need time to tailor new algorithms.

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Quantum Computing Demands a Whole New Kind of Programmer - Singularity Hub

YORKTOWN HEIGHTS, N.Y., May 6, 2017 /PRNewswire/ --While technologies that currently run on classical computers, such as Watson, can help find patterns and insights buried in vast amounts of existing data, quantum computers will deliver solutions to important problems where patterns cannot be seen because the data doesn't exist and the possibilities that you need to explore to get to the answer are too enormous to ever be processed by classical computers.

In March 2017, IBM (NYSE: IBM) announced the industry's first initiative to build commercially available universal quantum computing systems. "IBM Q"quantum systems and services will be delivered via the IBM Cloud platform.

IBM Q systems will be designed to tackle problems that are currently seen as too complex and exponential in nature for classical computing systems to handle. One of the first and most promising applications for quantum computing will be in the area of chemistry. Even for simple molecules like caffeine, the number of quantum states in the molecule can be astoundingly large so large that all the conventional computing memory and processing power scientists could ever build could not handle the problem.

The IBM Q systems promise to solve problems that today's computers cannot tackle, for example:

As part of the IBM Q System, IBM has released a new API (Application Program Interface) for the IBM Quantum Experience that enables developers and programmers to begin building interfaces between its existing five quantum bit (qubit) cloud-based quantum computer and classical computers, without needing a deep background in quantum physics. IBM has also released an upgraded simulator on the IBM Quantum Experience that can model circuits with up to 20 qubits. In the first half of 2017, IBM plans to release a full SDK (Software Development Kit) on the IBM Quantum Experience for users to build simple quantum applications and software programs.

The IBM Quantum Experience enables anyone to connect to IBM's quantum processor via the IBM Cloud, to run algorithms and experiments, work with the individual quantum bits, and explore tutorials and simulations around what might be possible with quantum computing.

For more information on IBM's universal quantum computing efforts, visit http://www.ibm.com/ibmq.

For more information on IBM Systems, visit http://www.ibm.com/systems.

IBM is making the specs for its new Quantum API available on GitHub (https://github.com/IBM/qiskit-api-py) and providing simple scripts (https://github.com/IBM/qiskit-sdk-py) to demonstrate how the API functions.

About IBM Research For more than seven decades, IBM Research has defined the future of information technology with more than 3,000 researchers in 12 labs located across six continents. Scientists from IBM Research have produced six

Nobel Laureates, 10 U.S. National Medals of Technology, five U.S. National Medals of Science, six Turing Awards, 19 inductees in the National Academy of Sciences and 20 inductees into the U.S. National Inventors Hall of Fame.

For more information about IBM Research, visit http://www.ibm.com/research.

CONTACT: Chris Andrews 914-945-1630 candrews@us.bm.com

To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/five-ways-quantum-computing-will-change-the-way-we-think-about-computing-300452712.html

SOURCE IBM

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Five Ways Quantum Computing Will Change the Way We Think ... - PR Newswire (press release)

A team of scientists from eastern China has built the first form of quantum computer that they say is faster than one of the early generation of conventional computers developed in the 1940s.

The researchers at the University of Science and Technology of China at Hefei in Anhui province built the machine as part of efforts to develop and highlight the future use of quantum computers.

The devices make use of the way particles interact at a subatomic level to make calculations rather than conventional computers which use electronic gates, switches and binary code.

China in race to build first code-breaking quantum supercomputer

The Hefei machine predicts the highly complex movement and behaviour of subatomic particles called photons, which make up light.

Normal supercomputers struggle to predict the behaviour of photons because of their huge level of unpredictability and the difficulties in modelling.

Pan Jianwei, the lead scientist on the project, told a press briefing in Shanghai on Wednesday that their device was already 10 to 11 times faster at carrying out the calculations than the first electronic digital computer, ENIAC, would have been capable of. ENIAC was developed in the 1940s.

In a few years time, he said, their machine would eclipse all of the worlds supercomputers in carrying out the calculations.

Quantum teleportation breakthrough earns Pan Jianweis team Chinas top science award

The Chinese team admit that their machine is of no practical use as it only carries out this one highly complex form of calculation, but it highlights the future potential of quantum computing. The teams research was formally published in the scientific journal Nature Photonics on Tuesday.

Scientists estimate that the current faster supercomputers would struggle to estimate the behaviour of 20 photons.

The Hefei researchers quantum device, called a boson sampling machine, can now carry out calculations for five photons, but at a speed 24,000 times faster than previous experiments, they say.

Our architecture is feasible to be scaled up to a larger number of photons and with a higher rate to race against increasingly advanced classical computers, they said in the research paper.

Teleportation, the next generation: Chinese and Canadian scientists closer to a quantum internet

Professor Scott Aaronson, who is based at the University of Texas at Austin and proposed the idea of the boson sampling machine, questioned whether it was useful to compare the latest results with technology developed over 60 years ago, but he said the research had shown exciting experimental progress.

Its a step towards boson sampling with say 30 photons or some number thats large enough that no one will have to squint or argue about whether a quantum advantage has been attained, he said.

'Unhackable' quantum broadband step closer after breakthrough by Chinese scientists

Araronson said one of the main purposes of making boson sampling machines was to prove that quantum devices could be shown to have an advantage in one area of complex calculations over existing types of computer.

Doing so would answer the quantum computing sceptics and help pave the way towards universal quantum computation, he said.

The rest is here:

China hits milestone in developing quantum computer - South China Morning Post

Chinese researchers have built a 10 qubit quantum computer.

China builds ten qubit quantum computer, They will scale to 20 qubits by end of this year and could beat the performance of any regular computer next year with a 30 qubit system.

A chinese research team led by Pan Jianwei is exploring three technical routes to quantum computers: 1. systems based on single photons, 2. ultra-cold atoms and 3. superconducting circuits.

Experimental set-up for multiphoton boson-sampling. The set-up includes four key parts: the single-photon device, demultiplexers, ultra-low-loss photonic circuit and detectors. The single-photon device is a single InAs/GaAs quantum dot coupled to a 2-m-diameter micropillar cavity

Pan Jianwei and his colleagues Lu Chaoyang and Zhu Xiaobo, of the University of Science and Technology of China, and Wang Haohua, of Zhejiang University set two international records in quantum control of the maximal numbers of entangled photonic quantum bits And entangled superconducting quantum bits.

Pan doubling that manipulation of multi-particle entanglement is the core of quantum computing technology and has been the focus of international competition in quantum computing research.

In the photonic system, his team has made the first 5, 6, 8 and 10 entangled photons in the world and is at the forefront of global developments.

Last year, Pan and Lu Chaoyang developed the worlds best single photon source based on semiconductor quantum dots. Now, they are using the high-performance single photon source and electronically programmable photonic circuit to build a multi-photon quantum computing prototype to run the Boson Sampling task.

The Chinese photonic computer is 10 to 100 times faster than the first electronic computer, ENIAC, and the first transistor computer, TRADIC, in running the classical algorithm.

The Hefei reporter quantum device, called a boson sampling machine, can now carry out calculations for five photons, but at a speed 24,000 times than previous experiments.

ENIAC contained 17,468 vacuum tubes, 7200 crystal diodes, 1500 relays, 70,000 resistors, 10,000 capacitors and approximately 5,000,000 hand-soldered joints. It could perform 5000 simple addition or subtraction operations per second. ENIAC could perform 500 floating point operations per second.

The Chinese team led by Pan, Zhu Xiaobo and Wang Haohua have broken that record. They dependent developed a superconducting quantum circuit containing 10 superconducting quantum bits and successfully entangled the 10 quantum bits through a global quantum operation.

Nature Photonics High-efficiency multiphoton boson sampling

They will try to design and manipulate 20 superconducting quantum bits by the end of the year. They also plan to launch a quantum cloud computing platform by the end of this year.

Our architecture is feasible to be scaled up to a larger number of photons and with a higher rate to race against increasingly advanced computers, they said in the research paper.

Professor Scott Aaronson, who is based at the University of Texas at Austin and proposed the idea of the boson sampling machine, questioned whether it was useful to compare the latest results with technology developed over 60 years ago, but he said the research had shown Exciting experimental progress .

Its a step towards boson sampling with say 30 photons or some number thats large enough that no one will have to squint or argue about whether a quantum advantage has been attained, he said.

Araronson said one of the main purposes of making boson sampling machines was to prove that quantum devices could be shown to have an advantage in one area of complex calculations over existing types of computer.

Doing so would answer the quantum computing sceptics and help pave the way towards universal quantum computation, he said.

Abstract

Boson sampling is considered as a strong candidate to demonstrate quantum computational supremacy over classical computers. However, previous proof-of-principle experiments suffered from small photon number and low sampling rates owing to the inefficiencies of the single-photon sources and multiport optical interferometers. Here, we develop two central components for high-performance boson sampling: robust multiphoton interferometers with 99% transmission rate and actively demultiplexed single-photon sources based on a quantum dotmicropillar with simultaneously high efficiency, purity and indistinguishability. We implement and validate three-, four- and five-photon boson sampling, and achieve sampling rates of 4.96kHz, 151Hz and 4Hz, respectively, which are over 24,000 times faster than previous experiments. Our architecture can be scaled up for a larger number of photons and with higher sampling rates to compete with classical computers, and might provide experimental evidence against the extended ChurchTuring thesis.

18 pages of supplemental material

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China builds five qubit quantum computer sampling and will scale to 20 qubits by end of this year and could any beat ... - Next Big Future

Main TERM Q

First proposed in the 1970s, quantum computing relies on quantum physics by taking advantage of certain quantum physics properties of atoms or nuclei that allow them to work together as quantum bits, or qubits, to be the computer's processor and memory. By interacting with each other while being isolated from the external environment, qubits can perform certain calculations exponentially faster than conventional computers.

Qubits do not rely on the traditional binary nature of computing. While traditional computers encode information into bits using binary numbers, either a 0 or 1, and can only do calculations on one set of numbers at once, quantum computers encode information as a series of quantum-mechanical states such as spin directions of electrons or polarization orientations of a photon that might represent a 1 or a 0, might represent a combination of the two or might represent a number expressing that the state of the qubit is somewhere between 1 and 0, or a superposition of many different numbers at once.

A quantum computer can do an arbitrary reversible classical computation on all the numbers simultaneously, which a binary system cannot do, and also has some ability to produce interference between various different numbers. By doing a computation on many different numbers at once, then interfering the results to get a single answer, a quantum computer has the potential to be much more powerful than a classical computer of the same size. In using only a single processing unit, a quantum computer can naturally perform myriad operations in parallel.

Quantum computing is not well suited for tasks such as word processing and email, but it is ideal for tasks such as cryptography and modeling and indexing very large databases.

Microsoft: Quantum Computing 101

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What is Quantum Computing? Webopedia Definition

The quantum computing processor, a physical device enabling the principle of quantum computing, is still rather a theoretical concept than a ready-to-implement engineering solution. Yet this notion has been broken recently by D-Waves announcement of shipping the first commercially available quantum computer model D-Wave 2000Q. IBM is also launching a new quantum computing division IBM Q, a move that might be a turning point in commercialization of quantum computing technology. IBM has pioneered quantum computing in the cloud with API enabling apps mostly for research purposes. We expect vigorous development of the cloud market segment to continue at double digit rate.

The quantum computing market is projected to surpass $5 Billion through 2020.

Despite technology advances the quantum computing market is still fledgling. At the same time this rapidly evolving market is one of the most active R&D fields, attracting substantial government funding that supports research groups at internationally leading academic institutions, national laboratories, and major industrial-research centers. The governments are the major driving force behind investments in quantum computing R&D, fiercely competing for what is perceived as the most promising technology of the 21st century. The worlds largest government IT/Defense contractors follow the government suit.

So, what is the rationale for quantum computing market?

a. National Security Considerations:

b. National Economy Considerations:

The report covers the quantum computing R&D, products, technologies and services as well as government, corporate and venture capital investments in quantum computing.

The report provides detailed year-by-year (2017 2022) forecasts for the following quantum computing (QC) market segments:

Quantum Computing Market Forecast 2017-2022, Tabular Analysis, March 2017, Pages: 23, Figures: 13, Tables: 6, Single User Price: $5,950.00 Reports are delivered in PDF format within 24 hours. Analysis provides quantitative market research information in a concise tabular format. The tables/charts present a focused snapshot of market dynamics.

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Quantum Computing Market Forecast 2017-2022, Tabular Analysis, March 2017, Pages: 23, Figures: 13, Tables: 6, Global Site License: $9,950.00 Reports are delivered in PDF format within 24 hours. Analysis provides quantitative market research information in a concise tabular format. The tables/charts present a focused snapshot of market dynamics.

2CheckOut.com Inc. (Ohio, USA) is an authorized retailer for goods and services provided by Market Research Media Ltd.

Table of Contents

1. Market Report Scope & Methodology 1.1. Scope 1.2. Research Methodology

2. Executive Summary

3. Quantum Computing Market in Figures 2017-2022 3.1. Quantum Computing Market 2017-2022 3.2. Quantum Computing Market 2017-2022 by Technology Segments 3.3. Quantum Computing in the Cloud Market 2017-2022 3.4. Quantum Computing Market 2017-2022 by Country

List of Figures Fig. 1- Quantum Computing Market Forecast 2017-2022, $Mln Fig. 2- Quantum Computing Market: Growth Rates 2017-2022 by Technology Segments, CAGR % Fig. 3- Cumulative Quantum Computing Market 2017-2022, Market Share by Technology Segments, % Fig. 4- Quantum Computing Market 2017-2022 by Technology Segments, $Mln Fig. 5- Quantum Computing Market Dynamics 2017-2022: Market Share by Technology Segments, % Fig. 6- Quantum Computing Market 2017-2022: Quantum Cryptography, $Mln Fig. 7- Quantum Computing Market 2017-2022: Physical QC Device, $Mln Fig. 8- Quantum Computing Market 2017-2022: QC Simulation, $Mln Fig. 9- Quantum Computing Market 2017-2022: QC Programming Infrastructure, $Mln Fig. 10- Quantum Computing in the Cloud Market 2017-2022, $Mln Fig. 11- Cumulative Quantum Market 2017-2022, market share by country, % Fig. 12- Quantum Computing Market 2017-2022 by Country, $Mln Fig. 13- Quantum Computing Market Dynamics 2017-2022: Market Share by Country, %

List of Tables Table 1 The Rationale for Quantum Computing Market Table 2 Quantum Computing Approaches by Physical Principle Table 3 Quantum Computing Market Forecast 2017-2022, $Mln Table 4 Global Quantum Computing Market 2017-2022 by Technology Segments, $Mln Table 5 Quantum Computing in the Cloud Market 2017-2022, $Mln Table 6 Quantum Computing Market 2017-2022 by Top 8 Countries, $Mln

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China already has the world's fastest supercomputer and has now built a crude quantum computer that could outpace today's PCs and servers.

Quantum computers have already been built by companies like IBM and D-Wave, but Chinese researchers have taken a different approach. They are introducing quantum computing using multiple photons, which could provide a superior way to calculate compared to today's computers.

The Chinese quantum computing architecture allows forfive-photonsampling and entanglement. It's an improvement over previous experiments involving single-photon sourcing, up to 24,000 times faster, the researchers claimed.

The Chinese researchers have built components required for Boson sampling, which has been theorized for a long time and is considered an easy way to build a quantum computer. The architecture built by the Chinese can include a large number of photons, which increases the speed and scale of computing.

China is strengthening its technology arsenal in an effort to be self-sufficient. China's homegrown chip powers TaihuLight, the world's fastest computer.

In 2014, China said it would spend US$150 billion on semiconductor development so that PCs and mobile devices would convert to homegrown chips. Afraid that low-cost Chinese chips will flood the market, the U.S. earlier this year accused China of rigging the semiconductor market to its advantage.

It's not clear yet if a quantum computer is on China's national agenda. But China's rapid progress of technology is worrying countries like the U.S. A superfast quantum computer could enhance the country's progress in areas like weapons development, in which high-performance computers are key.

But there's a long way to go before China builds its first full-fledged quantum computer. The prototype quantum computer is good for specific uses but is not designed to be a universal quantum computer that can run any task.

The research behind quantum computers is gaining steam as PCs and servers reach their limit. It's becoming difficult to shrink chips to smaller geometries, which could upset the cycle of reducing costs of computers while boosting speeds.

If they deliver on their promise, quantum computers will drive computing into the future. They are fundamentally different from computers used today.

Bits on todays computers are stored as ones or zeros, while quantum computers rely on qubits, also called quantum bits. Qubits can achieve various states, including holding a one and zero simultaneously, and those states can multiply.

The parallelism allows qubits to do more calculations simultaneously. However, qubits are considered fragile and highly unstable, and can easily breakdown during entanglement, a technical term for when qubits interact. A breakdown could bring instability to a computing process.

The Chinese quantum computer has a photon device based on quantum dots, demultiplexers, photonic circuits, and detectors.

There are multiple ways to build a quantum computer, including via superconducting qubits, which is the building block for D-Wave Systems' systems. Like the Chinese system, D-Wave's quantum annealing method is another easy way to build a quantum computer but is not considered ideal for a universal quantum computer.

IBM already has a 5-qubit quantum computer that is available via the cloud. It is now chasing a universal quantum computer using superconducting qubitsbut has a different gating model to stabilize systems. Microsoft is trying to chase a new quantum computer based on a new topography and a yet-undiscovered particle called non-abelian anyons.

In a bid to build computers of the future, China has also built a neuromorphic chip called Darwin.

Excerpt from:

China adds a quantum computer to high-performance computing arsenal - PCWorld

by Chris Woodford. Last updated: February 18, 2017.

How can you get more and more out of less and less? The smaller computers get, the more powerful they seem to become: there's more number-crunching ability in a 21st-century cellphone than you'd have found in a room-sized, military computer 50 years ago. Yet, despite such amazing advances, there are still plenty of complex problems that are beyond the reach of even the world's most powerful computersand there's no guarantee we'll ever be able to tackle them. One problem is that the basic switching and memory units of computers, known as transistors, are now approaching the point where they'll soon be as small as individual atoms. If we want computers that are smaller and more powerful than today's, we'll soon need to do our computing in a radically different way. Entering the realm of atoms opens up powerful new possibilities in the shape of quantum computing, with processors that could work millions of times faster than the ones we use today. Sounds amazing, but the trouble is that quantum computing is hugely more complex than traditional computing and operates in the Alice in Wonderland world of quantum physics, where the "classical," sensible, everyday laws of physics no longer apply. What is quantum computing and how does it work? Let's take a closer look!

Photo: Quantum computing means storing and processing information using individual atoms, ions, electrons, or photons. On the plus side, this opens up the possibility of faster computers, but the drawback is the greater complexity of designing computers that can operate in the weird world of quantum physics. Photo courtesy of US Department of Energy.

You probably think of a computer as a neat little gadget that sits on your lap and lets you send emails, shop online, chat to your friends, or play gamesbut it's much more and much less than that. It's more, because it's a completely general-purpose machine: you can make it do virtually anything you like. It's less, because inside it's little more than an extremely basic calculator, following a prearranged set of instructions called a program. Like the Wizard of Oz, the amazing things you see in front of you conceal some pretty mundane stuff under the covers.

Photo: This is what one transistor from a typical radio circuit board looks like. In computers, the transistors are much smaller than this and millions of them are packaged together onto microchips.

Conventional computers have two tricks that they do really well: they can store numbers in memory and they can process stored numbers with simple mathematical operations (like add and subtract). They can do more complex things by stringing together the simple operations into a series called an algorithm (multiplying can be done as a series of additions, for example). Both of a computer's key tricksstorage and processingare accomplished using switches called transistors, which are like microscopic versions of the switches you have on your wall for turning on and off the lights. A transistor can either be on or off, just as a light can either be lit or unlit. If it's on, we can use a transistor to store a number one (1); if it's off, it stores a number zero (0). Long strings of ones and zeros can be used to store any number, letter, or symbol using a code based on binary (so computers store an upper-case letter A as 1000001 and a lower-case one as 01100001). Each of the zeros or ones is called a binary digit (or bit) and, with a string of eight bits, you can store 255 different characters (such as A-Z, a-z, 0-9, and most common symbols). Computers calculate by using circuits called logic gates, which are made from a number of transistors connected together. Logic gates compare patterns of bits, stored in temporary memories called registers, and then turn them into new patterns of bitsand that's the computer equivalent of what our human brains would call addition, subtraction, or multiplication. In physical terms, the algorithm that performs a particular calculation takes the form of an electronic circuit made from a number of logic gates, with the output from one gate feeding in as the input to the next.

The trouble with conventional computers is that they depend on conventional transistors. This might not sound like a problem if you go by the amazing progress made in electronics over the last few decades. When the transistor was invented, back in 1947, the switch it replaced (which was called the vacuum tube) was about as big as one of your thumbs. Now, a state-of-the-art microprocessor (single-chip computer) packs hundreds of millions (and up to two billion) transistors onto a chip of silicon the size of your fingernail! Chips like these, which are called integrated circuits, are an incredible feat of miniaturization. Back in the 1960s, Intel co-founder Gordon Moore realized that the power of computers doubles roughly 18 monthsand it's been doing so ever since. This apparently unshakeable trend is known as Moore's Law.

Photo: This memory chip from a typical USB stick contains an integrated circuit that can store 512 megabytes of data. That's roughly 500 million characters (536,870,912 to be exact), each of which needs eight binary digitsso we're talking about 4 billion (4,000 million) transistors in all (4,294,967,296 if you're being picky) packed into an area the size of a postage stamp!

It sounds amazing, and it is, but it misses the point. The more information you need to store, the more binary ones and zerosand transistorsyou need to do it. Since most conventional computers can only do one thing at a time, the more complex the problem you want them to solve, the more steps they'll need to take and the longer they'll need to do it. Some computing problems are so complex that they need more computing power and time than any modern machine could reasonably supply; computer scientists call those intractable problems.

As Moore's Law advances, so the number of intractable problems diminishes: computers get more powerful and we can do more with them. The trouble is, transistors are just about as small as we can make them: we're getting to the point where the laws of physics seem likely to put a stop to Moore's Law. Unfortunately, there are still hugely difficult computing problems we can't tackle because even the most powerful computers find them intractable. That's one of the reasons why people are now getting interested in quantum computing.

Quantum theory is the branch of physics that deals with the world of atoms and the smaller (subatomic) particles inside them. You might think atoms behave the same way as everything else in the world, in their own tiny little waybut that's not true: on the atomic scale, the rules change and the "classical" laws of physics we take for granted in our everyday world no longer automatically apply. As Richard P. Feynman, one of the greatest physicists of the 20th century, once put it: "Things on a very small scale behave like nothing you have any direct experience about... or like anything that you have ever seen." (Six Easy Pieces, p116.)

If you've studied light, you may already know a bit about quantum theory. You might know that a beam of light sometimes behaves as though it's made up of particles (like a steady stream of cannonballs), and sometimes as though it's waves of energy rippling through space (a bit like waves on the sea). That's called wave-particle duality and it's one of the ideas that comes to us from quantum theory. It's hard to grasp that something can be two things at oncea particle and a wavebecause it's totally alien to our everyday experience: a car is not simultaneously a bicycle and a bus. In quantum theory, however, that's just the kind of crazy thing that can happen. The most striking example of this is the baffling riddle known as Schrdinger's cat. Briefly, in the weird world of quantum theory, we can imagine a situation where something like a cat could be alive and dead at the same time!

What does all this have to do with computers? Suppose we keep on pushing Moore's Lawkeep on making transistors smaller until they get to the point where they obey not the ordinary laws of physics (like old-style transistors) but the more bizarre laws of quantum mechanics. The question is whether computers designed this way can do things our conventional computers can't. If we can predict mathematically that they might be able to, can we actually make them work like that in practice?

People have been asking those questions for several decades. Among the first were IBM research physicists Rolf Landauer and Charles H. Bennett. Landauer opened the door for quantum computing in the 1960s when he proposed that information is a physical entity that could be manipulated according to the laws of physics. One important consequence of this is that computers waste energy manipulating the bits inside them (which is partly why computers use so much energy and get so hot, even though they appear to be doing not very much at all). In the 1970s, building on Landauer's work, Bennett showed how a computer could circumvent this problem by working in a "reversible" way, implying that a quantum computer could carry out massively complex computations without using massive amounts of energy. In 1981, physicist Paul Benioff from Argonne National Laboratory tried to envisage a basic machine that would work in a similar way to an ordinary computer but according to the principles of quantum physics. The following year, Richard Feynman sketched out roughly how a machine using quantum principles could carry out basic computations. A few years later, Oxford University's David Deutsch (one of the leading lights in quantum computing) outlined the theoretical basis of a quantum computer in more detail. How did these great scientists imagine that quantum computers might work?

The key features of an ordinary computerbits, registers, logic gates, algorithms, and so onhave analogous features in a quantum computer. Instead of bits, a quantum computer has quantum bits or qubits, which work in a particularly intriguing way. Where a bit can store either a zero or a 1, a qubit can store a zero, a one, both zero and one, or an infinite number of values in betweenand be in multiple states (store multiple values) at the same time! If that sounds confusing, think back to light being a particle and a wave at the same time, Schrdinger's cat being alive and dead, or a car being a bicycle and a bus. A gentler way to think of the numbers qubits store is through the physics concept of superposition (where two waves add to make a third one that contains both of the originals). If you blow on something like a flute, the pipe fills up with a standing wave: a wave made up of a fundamental frequency (the basic note you're playing) and lots of overtones or harmonics (higher-frequency multiples of the fundamental). The wave inside the pipe contains all these waves simultaneously: they're added together to make a combined wave that includes them all. Qubits use superposition to represent multiple states (multiple numeric values) simultaneously in a similar way.

Just as a quantum computer can store multiple numbers at once, so it can process them simultaneously. Instead of working in serial (doing a series of things one at a time in a sequence), it can work in parallel (doing multiple things at the same time). Only when you try to find out what state it's actually in at any given moment (by measuring it, in other words) does it "collapse" into one of its possible statesand that gives you the answer to your problem. Estimates suggest a quantum computer's ability to work in parallel would make it millions of times faster than any conventional computer... if only we could build it! So how would we do that?

In reality, qubits would have to be stored by atoms, ions (atoms with too many or too few electrons) or even smaller things such as electrons and photons (energy packets), so a quantum computer would be almost like a table-top version of the kind of particle physics experiments they do at Fermilab or CERN! Now you wouldn't be racing particles round giant loops and smashing them together, but you would need mechanisms for containing atoms, ions, or subatomic particles, for putting them into certain states (so you can store information), knocking them into other states (so you can make them process information), and figuring out what their states are after particular operations have been performed.

Photo: A single atom can be trapped in an optical cavitythe space between mirrorsand controlled by precise pulses from laser beams.

In practice, there are lots of possible ways of containing atoms and changing their states using laser beams, electromagnetic fields, radio waves, and an assortment of other techniques. One method is to make qubits using quantum dots, which are nanoscopically tiny particles of semiconductors inside which individual charge carriers, electrons and holes (missing electrons), can be controlled. Another method makes qubits from what are called ion traps: you add or take away electrons from an atom to make an ion, hold it steady in a kind of laser spotlight (so it's locked in place like a nanoscopic rabbit dancing in a very bright headlight), and then flip it into different states with laser pulses. In another technique, the qubits are photons inside optical cavities (spaces between extremely tiny mirrors). Don't worry if you don't understand; not many people do! Since the entire field of quantum computing is still largely abstract and theoretical, the only thing we really need to know is that qubits are stored by atoms or other quantum-scale particles that can exist in different states and be switched between them.

Although people often assume that quantum computers must automatically be better than conventional ones, that's by no means certain. So far, just about the only thing we know for certain that a quantum computer could do better than a normal one is factorisation: finding two unknown prime numbers that, when multiplied together, give a third, known number. In 1994, while working at Bell Laboratories, mathematician Peter Shor demonstrated an algorithm that a quantum computer could follow to find the "prime factors" of a large number, which would speed up the problem enormously. Shor's algorithm really excited interest in quantum computing because virtually every modern computer (and every secure, online shopping and banking website) uses public-key encryption technology based on the virtual impossibility of finding prime factors quickly (it is, in other words, essentially an "intractable" computer problem). If quantum computers could indeed factor large numbers quickly, today's online security could be rendered obsolete at a stroke.

Does that mean quantum computers are better than conventional ones? Not exactly. Apart from Shor's algorithm, and a search method called Grover's algorithm, hardly any other algorithms have been discovered that would be better performed by quantum methods. Given enough time and computing power, conventional computers should still be able to solve any problem that quantum computers could solve, eventually. In other words, it remains to be proven that quantum computers are generally superior to conventional ones, especially given the difficulties of actually building them. Who knows how conventional computers might advance in the next 50 years, potentially making the idea of quantum computers irrelevantand even absurd.

Photo: Quantum dots are probably best known as colorful nanoscale crystals, but they can also be used as qubits in quantum computers). Photo courtesy of Argonne National Laboratory.

Three decades after they were first proposed, quantum computers remain largely theoretical. Even so, there's been some encouraging progress toward realizing a quantum machine. There were two impressive breakthroughs in 2000. First, Isaac Chuang (now an MIT professor, but then working at IBM's Almaden Research Center) used five fluorine atoms to make a crude, five-qubit quantum computer. The same year, researchers at Los Alamos National Laboratory figured out how to make a seven-qubit machine using a drop of liquid. Five years later, researchers at the University of Innsbruck added an extra qubit and produced the first quantum computer that could manipulate a qubyte (eight qubits).

These were tentative but important first steps. Over the next few years, researchers announced more ambitious experiments, adding progressively greater numbers of qubits. By 2011, a pioneering Canadian company called D-Wave Systems announced in Nature that it had produced a 128-qubit machine. Thee years later, Google announced that it was hiring a team of academics (including University of California at Santa Barbara physicist John Martinis) to develop its own quantum computers based on D-Wave's approach. In March 2015, the Google team announced they were "a step closer to quantum computation," having developed a new way for qubits to detect and protect against errors. In 2016, MIT's Isaac Chang and scientists from the University of Innsbruck unveiled a five-qubit, ion-trap quantum computer that could calculate the factors of 15; one day, a scaled-up version of this machine might evolve into the long-promised, fully fledged encryption buster! There's no doubt that these are hugely important advances. Even so, it's very early days for the whole fieldand most researchers agree that we're unlikely to see practical quantum computers appearing for many yearsperhaps even decades.

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Quantum computing: A simple introduction - Explain that Stuff

Quantum computing (QC) is another wave thats soon to be impacting information technology (IT) in various companies across the world. Luckily IT managers wont need to take any action for at least another three years or so from now, but they should start thinking about QC in a different light now as to prepare.

After several years of up and downs, scientists now conclude that quantum mechanics is more natural than what we call normal physics. Quantum mechanics deals with the very small and lives within its own world. However, everything we know in this world owes its existence to quantum mechanics.

So why is this important to an IT manager you may wonder? Well, the answer lies in the qubit and an explanation of Heisenbergs Uncertainty Principle, entanglement, superposition and so on and so forth. The IBM Quantum Experience has been offering a 5-qubit system since May 2016. Similar to early 1950s computers this system is unable to support any practical applications as 5-bits can only represent one of 32 unique states; 5-qubits, on the other hand, can represent all 32 states at the same time.

To understand this concept further, consider that fifty people flip a coin in the air thats numbered ad unfairly bias to either heads or tails. On a count of three everyone flips their coin in the air and lets it drop to the floor. For just that one moment in time, the spinning of all 50 coins is affected by each other via currents or collisions like QC entanglement. While theyre spinning asking whether a certain coin is heads or tails makes sense and is like QC uncertainty.Also, the coins spin so fast that its a blend of states between heads and tails which is like QC superposition. And finally, when they all fall to the floor, the entanglement ends which is like QC coherence.

However, in the coin toss, two may interact with one another Two coins interacting will represent one of 4 states while spinning and 3 coins will represent one of 8 states, 4 coins represent one of 16 states and so on. The point is that the n-coin system equals n bits of information, but the n-qubit system represents so much more. When n is small, there is hardly any difference between the two systems, but when n is large, the n-qubit system gets a little more complicated.

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Quantum Computing and What All Good IT Managers Should Know - TrendinTech