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  • richardmitnick 10:12 am on June 2, 2020 Permalink | Reply
    Tags: "Ebb and Flow: Creating Quantum Dots Automatically With AI", A precise control of quantum dots allows researchers to shuttle electrons around and modify their state; and in doing so perform information processing tasks., , , , It is particularly exciting to be involved in a research project aimed at development of fully autonomous tuning software., , , , Qubits, Taking sensitive measurements to make sure that the dots have formed; that the number of electrons is just right; and that the dots can interact with one another., To transform quantum dot devices into functioning qubits in a research lab someone: usually a graduate student or postdoc has to carefully adjust voltages on all those gates .   

    From NIST: “Ebb and Flow: Creating Quantum Dots Automatically With AI” 


    From NIST

    June 2, 2020
    Justyna Zwolak

    1
    Credit: N. Hanacek/J. Zwolak/NIST

    Even though research on artificial intelligence (AI) goes back to the 1960s, it wasn’t until the past decade that AI really became an integral part of our lives. From automatically recognizing faces in our photo library to predicting traffic congestion and finding the fastest routes to our destination, AI is everywhere. It is also revolutionizing how research and science are being done, from data mining to drug discovery.

    What makes AI particularly attractive and at the same time really powerful is that it not only automates many laborious tasks — this in principle could be done with a well-written script — but learns how to do them from data alone, without ever being explicitly programmed to solve the problem at hand. This is known as training the AI.

    Think of tagging pictures: I thought it was really neat when my first “smart” photo album app not only highlighted faces of my friends and family members in pictures, but — after I tagged a couple of pictures with names — started suggesting (surprisingly accurately) when those people were in a new picture, even if their pose and facial expression were quite different from the already tagged pictures. At some point, my app even gave me the option to scan through all my pictures and tag all those people I had already identified. And did so really fast, considering the tens of thousands of pictures I had on my computer at that point! Now, whenever I take new pictures, my photo app matches any people in them to the people I have already tagged. And all I had to do was give the app just a couple of shots of each person to learn from: AI did the rest.

    In my research, I use an AI-powered face-recognition-like approach to classify “faces” of quantum dot devices for use as so-called qubits, the building blocks of a quantum computer’s processor. While in classical computers, information and processes are coded as strings of 0 (no signal in the circuit) and 1 (signal is on), quantum computers use 0, 1 and everything in between. This is achieved by replacing the classical 0-1 bits with quantum bits, aka qubits. There are certain mathematical problems, such as the factorization of numbers, in which quantum computers are expected to outperform classical ones.

    Controlling the Flow

    2
    Credit: N. Hanacek/J. Zwolak/NIST

    Quantum dots are one of the possible realizations of qubits. How do quantum dots work? Let’s conduct the following thought experiment: Suppose there are three locks on the Hudson River. Since the Hudson River can flow in both directions depending on the tide, by carefully adjusting the height of the locks we should be able to — at least in principle — control how much water flows between the reservoirs and chambers, and how much water gets trapped in the two chambers between the locks.

    For example, if all three locks were simultaneously brought up higher than the water level, there would be no water flow and the water levels in the two chambers should be approximately the same. If during the outgoing tide locks A and B were set high, and lock C brought down, we would lower the water level trapped in chamber BC below that in chamber AB. Conversely, if during the incoming tide we would lower lock A, the water levels would be reversed, i.e., the level of water trapped in chamber AB would be lower than in chamber BC. By playing with the heights of the locks we could achieve all possible combinations of the relative depths of chambers AB and BC (ignoring for a moment the actual effect of such locks on the changing tidal currents).

    This is quite like how quantum dots work, except that what flows is electric current, what is being trapped are individual electrons, and what is being raised and lowered is voltage applied to metallic gates imprinted above the electronic channels. A precise control of quantum dots allows researchers to shuttle electrons around and modify their state, and in doing so perform information processing tasks.

    Toward the Quantum Revolution

    Now, to transform quantum dot devices into functioning qubits in a research lab, someone, usually a graduate student or postdoc, has to carefully adjust voltages on all those gates and then take sensitive measurements to make sure that the dots have formed, that the number of electrons is just right, and that the dots can interact with one another. This requires the researcher to measure the current flowing through the device for a set of parameters, recognize what state the device is in from that measurement, change the gate voltages a bit, and then check the current again, repeating the process until the desired state is achieved. And the more dots (and gates) involved, the harder it is to tune all of them to work together properly.

    In fact, full automation of this process is one of the main obstacles to widespread use of semiconductor-based qubits. Even with semi-scripted tuning protocols, a lot of decisions about the proper parameters range are still made by the researcher. At the same time, as one of my colleagues, Jake Taylor, put it well, legions of graduate students applying “trial-and-error” approaches cannot be the ultimate answer for deploying quantum technologies. To enable the quantum revolution, we need to find a way to take the human out of the picture.

    This is the goal of our work. Using the mathematics of pattern recognition and classical optimization, we are developing an auto-tuning protocol that doesn’t require a human to navigate between quantum dot states in real time. The AI in our protocol works like the face recognition app on a phone — whenever a new measurement is taken, it analyzes it and returns a prediction of the most likely state of the device. That information is then fed into an optimization routine that, based on what has been seen so far, suggests how the voltages should be adjusted for the next measurement and— with each iteration — tries to get closer and closer to the desired state, tuning the quantum dot device in the process.

    To train the AI, one of my colleagues, Sandesh Kalantre of the University of Maryland, has developed a model that generates large sets of images of simulated measurements, just like the ones we see in the lab. This was an extremely important step, as a large volume of data is necessary to train the AI.

    In light of the recent advances in building larger quantum dot arrays, it is particularly exciting to be involved in a research project aimed at development of fully autonomous tuning software. However, even though the numerous attempts to automate the various steps of the tuning process — using a combination of image processing, pattern matching, and machine learning — bring us much closer to this goal than ever before, full automation is yet to be achieved. Still, our work is not only paving a path forward for experiments with a larger number of quantum dots, but will also allow us to allocate more precious time — and graduate students — to do more stimulating research.

    See the full article here.

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    NIST Campus, Gaitherberg, MD, USA

    NIST Mission, Vision, Core Competencies, and Core Values

    NIST’s mission

    To promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life.
    NIST’s vision

    NIST will be the world’s leader in creating critical measurement solutions and promoting equitable standards. Our efforts stimulate innovation, foster industrial competitiveness, and improve the quality of life.
    NIST’s core competencies

    Measurement science
    Rigorous traceability
    Development and use of standards

    NIST’s core values

    NIST is an organization with strong values, reflected both in our history and our current work. NIST leadership and staff will uphold these values to ensure a high performing environment that is safe and respectful of all.

    Perseverance: We take the long view, planning the future with scientific knowledge and imagination to ensure continued impact and relevance for our stakeholders.
    Integrity: We are ethical, honest, independent, and provide an objective perspective.
    Inclusivity: We work collaboratively to harness the diversity of people and ideas, both inside and outside of NIST, to attain the best solutions to multidisciplinary challenges.
    Excellence: We apply rigor and critical thinking to achieve world-class results and continuous improvement in everything we do.

     
  • richardmitnick 3:05 pm on February 1, 2020 Permalink | Reply
    Tags: "Quantum computing: What’s the big deal?", , , Qubits   

    From CSIROscope: “Quantum computing: What’s the big deal?” 

    CSIRO bloc

    From CSIROscope

    31 January 2020
    Dominic Banfield
    Dr Cathy Foley
    Saffron Urbaniak

    1
    PhD student Georgina Carson working on a scanning tunnelling microscope which allows her to image materials at an extremely small (atomic) scale. CREDIT: The ARC Centre of Excellence for Quantum Computation and Communication Technology (CQC2T)

    Google claimed ‘quantum supremacy’ last year with their ‘Sycamore’ superconducting quantum computer. At CSIRO, we refer to quantum supremacy as ‘quantum advantage’. So, what is the quantum advantage and, for that matter, quantum technologies? Let us break it down for you.

    What is a quantum computer?

    Quantum physics explains the behaviour of the world at the smallest scale. Most computers already rely on quantum technologies such as semiconductors and laser optics. But, moving forward, a fully-fledged quantum computer will take our understanding of quantum physics to a whole new level.

    Basically, a quantum represents the smallest unit of mass, energy or other physical quantity. Scientists can isolate, control and sense individual quantum particles and their properties. In a quantum computer we use these capabilities to create an entirely new form of computation.

    Quantum computers won’t be that useful for watching cat videos or posting memes. But they have the potential to solve problems that are impossible on current computing systems. Researchers using large-scale quantum computers could spur breakthroughs in new medicines, urban planning, energy-efficient batteries, and even offset the energy consumed by the world’s supercomputers.

    What is the quantum advantage?

    Quantum advantage is the point where a quantum computer can do something that a normal computer can’t in a reasonable amount of time.

    Google claims to have run a computation on their quantum processor in 200 seconds that they suggest would take 10,000 years to simulate on a normal computer. This is an amazing breakthrough for the technology, but it comes with some important caveats:

    The computation used to benchmark the performance has no known practical use.
    Quantum computing researchers at IBM claim that instead of 10,000 years, the same task could be simulated in 2.5 days on a classical supercomputer.

    Regardless, the jury is still out on when we will see the first useful applications of quantum computing and what they will be.

    How might we use a ‘supreme’ quantum computer?

    Our Chief Scientist Dr Cathy Foley and our strategic foresight team, CSIRO Futures, are working with Australia’s quantum technology sector to develop a roadmap for the industry. We’ve heard from researchers and start-ups exploring algorithms and applications for quantum computers.

    One opportunity is the development of quantum computer algorithms to speed up machine learning and optimisation processes. Researchers are also looking to simulate the quantum interactions in chemical processes. Google’s CEO suggested simulations run on quantum computers might help identify a more sustainable way to produce ammonia fertiliser, which causes almost 1.5 per cent of global greenhouse gas emissions.

    However, the truth is no one really knows what the possibilities are yet. Imagine you could go back in time before we invented computers. You would have no possible way of understanding what we use them for today.

    3
    Also dubbed the steampunk chandelier, this is IBM’s Q quantum computer. Credit: Lars Plougmann

    What else might this technology achieve?

    Quantum computing will still take years of research and development. But we’re edging closer to harnessing transformational quantum technologies in other applications. We have been working on quantum technologies for more than 30 years making quantum sensors called SQUIDs. Our LANDTEM technology has helped describe and detect over $6 billion worth of ore bodies in Australia and overseas, including the BHP Cannington silver mine.

    About 70 per cent of Australia features barren cover that obscures mineralised rocks and creates challenges for mineral exploration. Australian researchers are developing new high-precision quantum sensors for mineral exploration. This will help us discover new mineral deposits and support one of our key sectors. We could also use the same technology in defence and water resource management.

    Some quantum-enhanced cybersecurity solutions are already on the market. And quantum technologies for secure communications networks are being developed. Researchers are also exploring the possibilities of creating a quantum internet that can warn you if a third party attempts to intercept your messages.

    Next steps

    Late last year we released a discussion paper on quantum technologies (PDF, 2.53KB). This paper considers the potential applications of quantum technologies, challenges and opportunities, and what we need to do to develop our capabilities.

    Dr Foley says we’re looking to harness Australia’s excellence in quantum technology research and pave a way forward to grow the sector.

    “Quantum technology can help create solutions and benefits for industry, develop new export markets and create new job opportunities, as well as help maintain our national and industry security,” she said.

    “We have some of the best quantum research in the world and must continue to invest so we can lead the world.”

    See the full article here .


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    Stem Education Coalition

    SKA/ASKAP radio telescope at the Murchison Radio-astronomy Observatory (MRO) in Mid West region of Western Australia

    So what can we expect these new radio projects to discover? We have no idea, but history tells us that they are almost certain to deliver some major surprises.

    Making these new discoveries may not be so simple. Gone are the days when astronomers could just notice something odd as they browse their tables and graphs.

    Nowadays, astronomers are more likely to be distilling their answers from carefully-posed queries to databases containing petabytes of data. Human brains are just not up to the job of making unexpected discoveries in these circumstances, and instead we will need to develop “learning machines” to help us discover the unexpected.

    With the right tools and careful insight, who knows what we might find.

    CSIRO campus

    CSIRO, the Commonwealth Scientific and Industrial Research Organisation, is Australia’s national science agency and one of the largest and most diverse research agencies in the world.

     
  • richardmitnick 4:45 pm on January 23, 2020 Permalink | Reply
    Tags: Advances in quantum networking and quantum computing, Frequency beam splitter, Frequency tritter which splits a beam of light into three different frequencies instead of two., Off-the-shelf devices can deliver impressive control at the single-photon level., Optics & Photonics News, , Photons travel at the speed of light., Photons: single particles of light that can act as qubits, , Quantum optical frequency combs, Qubits   

    From Oak Ridge National Laboratory: “Quantum experiments explore power of light for communications, computing” 

    i1

    From Oak Ridge National Laboratory

    January 23, 2020

    1
    Researchers in ORNL’s Quantum Information Science group summarized their significant contributions to quantum networking and quantum computing in a special issue of Optics & Photonics News. Credit: Christopher Tison and Michael Fanto/Air Force Research Laboratory.

    A team from the Department of Energy’s Oak Ridge National Laboratory has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.

    ORNL quantum researchers Joseph Lukens, Pavel Lougovski, Brian Williams, and Nicholas Peters—along with collaborators from Purdue University and the Technological University of Pereira in Colombia—summarized results from several of their recent academic papers in a special issue of the Optical Society’s Optics & Photonics News [above], which showcased some of the most significant results from optics-related research in 2019. Their entry was one of 30 selected for publication from a pool of 91.

    Conventional computer “bits” have a value of either 0 or 1, but quantum bits, called “qubits,” can exist in a superposition of quantum states labeled 0 and 1. This ability makes quantum systems promising for transmitting, processing, storing, and encrypting vast amounts of information at unprecedented speeds.

    To study photons—single particles of light that can act as qubits—the researchers employed light sources called quantum optical frequency combs that contain many precisely defined wavelengths. Because they travel at the speed of light and do not interact with their environment, photons are a natural platform for carrying quantum information over long distances.

    Interactions between photons are notoriously difficult to induce and control, but these capabilities are necessary for effective quantum computers and quantum gates, which are quantum circuits that operate on qubits. Nonexistent or unpredictable photonic interactions make two-photon quantum gates much more difficult to develop than standard one-photon gates, but the researchers reached several major milestones in recent studies that addressed these challenges.

    For example, they made adjustments to existing telecommunications equipment used in optics research to optimize them for quantum photonics. Their results revealed new ways to use these resources for both traditional and quantum communication.

    “Using this equipment to manipulate quantum states is the technological underpinning of all these experiments, but we did not expect to be able to move in the other direction and improve classical communication by working on quantum communication,” Lukens said. “These interesting and unanticipated findings have appeared as we delve deeper into this research area.”

    One such tool, a frequency beam splitter, divides a single beam of light into two frequencies, or colors, of light.

    “Imagine you have a beam of light going down an optical fiber that has a particular frequency, say, red,” Lukens said. “Then, after going through the frequency beam splitter, the photon will leave as two frequencies, so it will be both red and blue.”

    The members of this team were the first researchers to successfully design a quantum frequency beam splitter with standard lightwave communications technology. This device takes in red and blue photons simultaneously, then produces energy in either the red or the blue frequency. By using this method to deliberately change the frequencies of photons, the team tricked the stubborn particles into beneficial interactions based on quantum interference, the phenomenon of photons interfering with their own trajectories.

    “It turned out that off-the-shelf devices can deliver impressive control at the single-photon level, which people didn’t know was possible,” Lougovski said.

    Additionally, the researchers completed the first demonstration of a frequency tritter, which splits a beam of light into three different frequencies instead of two. Their results indicated that multiple quantum information processing operations can run at the same time without introducing errors or damaging the data.

    Another key accomplishment was the team’s design and demonstration of a coincidence-basis controlled-NOT gate, which enables one photon to control a frequency shift in another photon. This device completed a universal quantum gate set, meaning any quantum algorithm can be expressed as a sequence within those gates.

    “Quantum computing applications require much more impressive control levels than any sort of classical computing,” Lougovski said.

    The team also encoded quantum information in multiple independent values known as degrees of freedom within a single photon, which allowed them to observe quantum entanglement-like effects without needing two separate particles. Entanglement usually involves two linked particles in which changes made to the state of one particle also apply to the other.

    Finally, the researchers have completed quantum simulations of real-world physics problems. In collaboration with scientists at the Air Force Research Laboratory, they are now developing tiny, specialized silicon chips similar to those common in microelectronics in pursuit of even better photonic performance.

    “In theory, we can get all these operations onto a single photonic chip, and we see a lot of potential for doing similar quantum experiments on this new platform,” Lukens said. “That’s the next step to really move this technology forward.”

    Future quantum computers will allow scientists to simulate incredibly complex scientific problems that would be impossible to study on current systems, even supercomputers. In the meantime, the team’s findings could help researchers embed photonic systems into current high-performance computing resources.

    “We have a very diverse and talented team,” Lougovski said. “The most important thing is we’re getting results.”

    This research was funded by ORNL’s Laboratory Directed Research and Development program.

    See the full article here .


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    ORNL is managed by UT-Battelle for the Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time.

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  • richardmitnick 10:33 am on September 19, 2019 Permalink | Reply
    Tags: Classical nonseparability can be applied to acoustic waves not just light waves., From Light to Sound, , , , Qubits,   

    From University of Arizona: “Sound of the Future: A New Analog to Quantum Computing” 

    U Arizona bloc

    From University of Arizona

    Sept. 17, 2019
    Emily Dieckman

    University of Arizona engineers are using soundwaves to search through big data with more stability and ease.

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    Pierre Deymier (right) and UA President Robert C. Robbins examine the acoustic system that allowed researchers to create Bell states using phonons. (Photo: Paul Tumarkin/Tech Launch Arizona)

    Human beings create a lot of data in the digital age – whether it’s through everyday items like social media posts, emails and Google searches, or more complex information about health, finances and scientific findings.

    The International Data Corp. reported that the global datasphere contained 33 zettabytes, or 33 trillion gigabytes, in 2018. By 2025, they expect that number to grow to 175 zettabytes. 175 zettabytes of information stored on DVDs would fill enough DVDs to circle Earth 222 times.

    While quantum computing has been touted as a way to intelligently sort through big data, quantum environments are difficult to create and maintain. Entangled quantum bit states, or qubits, usually last less than a second before collapsing. Qubits are also highly sensitive to their surrounding environments and must be stored at cryogenic temperatures.

    In a paper Nature Communications Physics, researchers in the University of Arizona Department of Materials Science and Engineering have demonstrated the possibility for acoustic waves in a classical environment to do the work of quantum information processing without the time limitations and fragility.

    “We could run our system for years,” said Keith Runge, director of research in the Department of Materials Science and Engineering and one of the paper’s authors. “It’s so robust that we could take it outside to a tradeshow without it being perturbed at all – earlier this year, we did.”

    Materials science and engineering research assistant professor Arif Hasan led the research. Other co-authors include MSE research assistant professor Lazaro Calderin; undergraduate student Trevor Lata; Pierre Lucas, professor of MSE and optical sciences; and Pierre Deymier, MSE department head, member of the applied mathematics Graduate Interdisciplinary Program, and member of the BIO5 Institute. The team is working with Tech Launch Arizona, the office of the UA that commercializes inventions stemming from research, to patent their device and is investigating commercial pathways to bring the innovation to the public.

    Quantum Superposition

    In classical computing, information is stored as either 0s or 1s, the same way a coin must land on either heads or tails. In quantum computing, qubits can be stored in both states at the same time – a so-called superposition of states. Think of a coin balanced on its side, spinning so quickly that both heads and tails seem to appear at once.

    When qubits are entangled, anything that happens to one qubit affects the other through a principle called nonseparability. In other words, knock down one spinning coin on a table and another spinning coin on the same table falls down, too. A principle called nonlocality keeps the particles linked even if they’re far apart – knock down one spinning coin, and its entangled counterpart on the other side of the universe falls down, too. The entangled qubits create a Bell state, in which all parts of a collective are affected by one another.

    “This is key, because if you manipulate just one qubit, you are manipulating the entire collection of qubits,” Deymier said. “In a regular computer, you have many bits of info stored as 0s or 1s, and you have to address each one of them.”

    From Light to Sound

    But, like a coin spinning on its edge, quantum mechanics are fragile. The act of measuring a quantum state can cause the link to collapse, or decohere – just like how taking a picture of a spinning coin will mean capturing just one side of the coin. That’s why qubit states can only be maintained for short periods.

    But there’s a way around the use of quantum mechanics for data processing: Optical scientists and electrical and computer engineering researchers have demonstrated the ability to create systems of photons, or units of light, that exhibit nonseparability without nonlocality. Though nonlocality is important for specific applications like cryptography, it’s the nonseparability that matters for applications like quantum computing. And particles that are nonseparable in classical Bell states, rather than entangled in a quantum Bell state, are much more stable.

    The materials science and engineering team has taken this a step further by demonstrating for the first time that that classical nonseparability can be applied to acoustic waves, not just light waves. They use phi-bits, units made up of quasi-particles called phonons that transmit sound and heat waves.

    “Light lasers and single photons are part of the field photonics, but soundwaves fall under the umbrella of phononics, or the study of phonons,” Deymier said. “In addition to being stable, classically entangled acoustic waves are easy to interact with and manipulate.”

    Complex Science, Simple Tools

    The materials to demonstrate such a complex concept were simple, including three aluminum rods, enough epoxy to connect them and some rubber bands for elasticity.

    Researchers sent a wave of sound vibrations down the rods, then monitored two degrees of freedom of the waves: what direction the waves moved down the rods (forward or backward) and how the rods moved in relation to one another (whether they were waving in the same direction and at similar amplitudes). To excite the system into a nonseparable state, they identified a frequency at which these two degrees of freedom were linked and sent the waves at that frequency. The result? A Bell state.

    “So, we have an acoustic system that gives us the possibility creating these Bell states,” Deymier said. “It’s the complete analog to quantum mechanics.”

    Demonstrating that this is possible has opened the door to applying classical nonseparability to the emerging field of phononics. Next, the researchers will work to increase the number of degrees of freedom that can be classically entangled – the more, the better. They also want to develop algorithms that can use these nonseparable states to manipulate information.

    Once the system is refined, they plan to resize it from the tabletop down to the microscale, ready to deploy on computer chips in data centers around the world.

    This work was supported by the W.M. Keck Foundation and the National Science Foundation Emerging Frontiers in Research and Innovation Program.

    See the full article here .


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    U Arizona campus

    The University of Arizona (UA) is a place without limits-where teaching, research, service and innovation merge to improve lives in Arizona and beyond. We aren’t afraid to ask big questions, and find even better answers.

    In 1885, establishing Arizona’s first university in the middle of the Sonoran Desert was a bold move. But our founders were fearless, and we have never lost that spirit. To this day, we’re revolutionizing the fields of space sciences, optics, biosciences, medicine, arts and humanities, business, technology transfer and many others. Since it was founded, the UA has grown to cover more than 380 acres in central Tucson, a rich breeding ground for discovery.

    U Arizona mirror lab-Where else in the world can you find an astronomical observatory mirror lab under a football stadium?

    University of Arizona’s Biosphere 2, located in the Sonoran desert. An entire ecosystem under a glass dome? Visit our campus, just once, and you’ll quickly understand why the UA is a university unlike any other.

     
  • richardmitnick 11:38 am on September 16, 2019 Permalink | Reply
    Tags: , Gaussian noise, , non-Gaussian noise, , Qubits   

    From MIT News and Dartmouth College: “Uncovering the hidden “noise” that can kill qubits” 

    MIT News

    From MIT News

    September 16, 2019
    Rob Matheson

    1
    MIT and Dartmouth College researchers developed a tool that detects new characteristics of non-Gaussian “noise” that can destroy the fragile quantum superposition state of qubits, the fundamental components of quantum computers. Image courtesy of the researchers.

    New detection tool could be used to make quantum computers robust against unwanted environmental disturbances.

    MIT and Dartmouth College researchers have demonstrated, for the first time, a tool that detects new characteristics of environmental “noise” that can destroy the fragile quantum state of qubits, the fundamental components of quantum computers.

    The advance may provide insights into microscopic noise mechanisms to help engineer new ways of protecting qubits.

    Qubits can represent the two states corresponding to the classic binary bits, a 0 or 1. But, they can also maintain a “quantum superposition” of both states simultaneously, enabling quantum computers to solve complex problems that are practically impossible for classical computers.

    But a qubit’s quantum “coherence” — meaning its ability to maintain the superposition state — can fall apart due to noise coming from environment around the qubit. Noise can arise from control electronics, heat, or impurities in the qubit material itself, and can also cause serious computing errors that may be difficult to correct.

    Researchers have developed statistics-based models to estimate the impact of unwanted noise sources surrounding qubits to create new ways to protect them, and to gain insights into the noise mechanisms themselves. But, those tools generally capture simplistic “Gaussian noise,” essentially the collection of random disruptions from a large number of sources. In short, it’s like white noise coming from the murmuring of a large crowd, where there’s no specific disruptive pattern that stands out, so the qubit isn’t particularly affected by any one particular source. In this type of model, the probability distribution of the noise would form a standard symmetrical bell curve, regardless of the statistical significance of individual contributors.

    In a paper published today in the journal Nature Communications, the researchers describe a new tool that, for the first time, measures “non-Gaussian noise” affecting a qubit. This noise features distinctive patterns that generally stem from a few particularly strong noise sources.

    The researchers designed techniques to separate that noise from the background Gaussian noise, and then used signal-processing techniques to reconstruct highly detailed information about those noise signals. Those reconstructions can help researchers build more realistic noise models, which may enable more robust methods to protect qubits from specific noise types. There is now a need for such tools, the researchers say: Qubits are being fabricated with fewer and fewer defects, which could increase the presence of non-Gaussian noise.

    “It’s like being in a crowded room. If everyone speaks with the same volume, there is a lot of background noise, but I can still maintain my own conversation. However, if a few people are talking particularly loudly, I can’t help but lock on to their conversation. It can be very distracting,” says William Oliver, an associate professor of electrical engineering and computer science, professor of the practice of physics, MIT Lincoln Laboratory Fellow, and associate director of the Research Laboratory for Electronics (RLE). “For qubits with many defects, there is noise that decoheres, but we generally know how to handle that type of aggregate, usually Gaussian noise. However, as qubits improve and there are fewer defects, the individuals start to stand out, and the noise may no longer be simply of a Gaussian nature. We can find ways to handle that, too, but we first need to know the specific type of non-Gaussian noise and its statistics.”

    “It is not common for theoretical physicists to be able to conceive of an idea and also find an experimental platform and experimental colleagues willing to invest in seeing it through,” says co-author Lorenza Viola, a professor of physics at Dartmouth. “It was great to be able to come to such an important result with the MIT team.”

    Joining Oliver and Viola on the paper are: first author Youngkyu Sung, Fei Yan, Jack Y. Qiu, Uwe von Lüpke, Terry P. Orlando, and Simon Gustavsson, all of RLE; David K. Kim and Jonilyn L. Yoder of the Lincoln Laboratory; and Félix Beaudoin and Leigh M. Norris of Dartmouth.

    Pulse filters

    For their work, the researchers leveraged the fact that superconducting qubits are good sensors for detecting their own noise. Specifically, they use a “flux” qubit, which consists of a superconducting loop that is capable of detecting a particular type of disruptive noise, called magnetic flux, from its surrounding environment.

    In the experiments, they induced non-Gaussian “dephasing” noise by injecting engineered flux noise that disturbs the qubit and makes it lose coherence, which in turn is then used as a measuring tool. “Usually, we want to avoid decoherence, but in this case, how the qubit decoheres tells us something about the noise in its environment,” Oliver says.

    Specifically, they shot 110 “pi-pulses” — which are used to flip the states of qubits — in specific sequences over tens of microseconds. Each pulse sequence effectively created a narrow frequency “filter” which masks out much of the noise, except in a particular band of frequency. By measuring the response of a qubit sensor to the bandpass-filtered noise, they extracted the noise power in that frequency band.

    By modifying the pulse sequences, they could move filters up and down to sample the noise at different frequencies. Notably, in doing so, they tracked how the non-Gaussian noise distinctly causes the qubit to decohere, which provided a high-dimensional spectrum of the non-Gaussian noise.

    Error suppression and correction

    The key innovation behind the work is carefully engineering the pulses to act as specific filters that extract properties of the “bispectrum,” a two-dimension representation that gives information about distinctive time correlations of non-Gaussian noise.

    Essentially, by reconstructing the bispectrum, they could find properties of non-Gaussian noise signals impinging on the qubit over time — ones that don’t exist in Gaussian noise signals. The general idea is that, for Gaussian noise, there will be only correlation between two points in time, which is referred to as a “second-order time correlation.” But, for non-Gaussian noise, the properties at one point in time will directly correlate to properties at multiple future points. Such “higher-order” correlations are the hallmark of non-Gaussian noise. In this work, the authors were able to extract noise with correlations between three points in time.

    This information can help programmers validate and tailor dynamical error suppression and error-correcting codes for qubits, which fixes noise-induced errors and ensures accurate computation.

    Such protocols use information from the noise model to make implementations that are more efficient for practical quantum computers. But, because the details of noise aren’t yet well-understood, today’s error-correcting codes are designed with that standard bell curve in mind. With the researchers’ tool, programmers can either gauge how their code will work effectively in realistic scenarios or start to zero in on non-Gaussian noise.

    Keeping with the crowded-room analogy, Oliver says: “If you know there’s only one loud person in the room, then you’ll design a code that effectively muffles that one person, rather than trying to address every possible scenario.”

    See the full article here .


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    MIT Seal

    The mission of MIT is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the twenty-first century. We seek to develop in each member of the MIT community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

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  • richardmitnick 8:59 am on July 30, 2019 Permalink | Reply
    Tags: A team of physicists at University of Illinois at Chicago and the University of Hamburg have taken a different approach., Entangled Majorana quasiparticles produced by splitting an electron into two halves are surprisingly stable., , , Majorana quasiparticles, , , , Qubits, , , They remember how they've been moved around a property that could be exploited for storing information., They've started with a rhenium superconductor a material that conducts electricity with zero resistance when supercooled to around 6 Kelvin (–267°C; 449°F)., , U Hamburg,   

    From University of Illinois and U Hamburg, via Science Alert: “An Elusive Particle That Acts as Its Own Antiparticle Has Just Been Imaged” 

    U Illinois bloc

    From University of Illinois Chicago

    and

    2
    U Hamburg

    via

    30 JULY 2019
    MICHELLE STARR

    3
    (Palacio-Morales et al. Science Advances, 2019)

    New images of the Majorana fermion have brought physicists a step closer to harnessing the mysterious objects for quantum computing.

    These strange objects – particles that acts as their own antiparticles – have a vast as-yet untapped potential to act as qubits, the quantum bits that are the basic units of information in a quantum computer.

    IBM iconic image of Quantum computer

    They’re equivalent to binary bits in a traditional computer. But, where regular bits can represent a 1 or a 0, qubits can be either 1, 0 or both at the same time, a state known as quantum superposition. Quantum superposition is actually pretty hard to maintain, although we’re getting better at it.

    This is where Majorana quasiparticles come in. These are excitations in the collective behaviour of electrons that act like Majorana fermions, and they have a number of properties that make them an attractive candidate for qubits.

    Normally, a particle and an antiparticle will annihilate each other, but entangled Majorana quasiparticles produced by splitting an electron into two halves are surprisingly stable. In addition, they remember how they’ve been moved around, a property that could be exploited for storing information.

    But the quasiparticles have to remain separated by a sufficient distance. This can be done with a special nanowire, but a team of physicists at the University of Illinois at Chicago and the University of Hamburg in Germany have taken a different approach.

    They’ve started with a rhenium superconductor, a material that conducts electricity with zero resistance when supercooled to around 6 Kelvin (–267°C; 449°F).

    On top of these superconductors, the researchers deposited nanoscale islands of single layers of magnetic iron atoms. This creates what is known as a topological superconductor – that is, a superconductor that contains a topological knot.

    “This topological knot is similar to the hole in a donut,” explained physicist Dirk Morr of the University of Illinois at Chicago.

    “You can deform the donut into a coffee mug without losing the hole, but if you want to destroy the hole, you have to do something pretty dramatic, such as eating the donut.”

    When electrons flow through the superconductor, the team predicted that Majorana fermions would appear in a one-dimensional mode at the edges of the iron islands – around the so-called donut hole. And that by using a scanning tunneling microscope – an instrument used for imaging surfaces at the atomic level – they would see this visualised as a bright line.

    Sure enough, a bright line showed up.

    It’s not the first time Majorana fermions have been imaged, but it does represent a step forward. And just last month, a different team of researchers revealed that they had been able to turn Majorana quasiparticles on and off.

    But being able to visualise these particles, the researchers said, brings us closer to using them as qubits.

    “The next step will be to figure out how we can quantum engineer these Majorana qubits on quantum chips and manipulate them to obtain an exponential increase in our computing power,” Morr said.

    The research has been published in Science Advances.

    See the full article here .

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    4

    The University

    Universität Hamburg is the largest institution for research and education in northern Germany. As one of the country’s largest universities, we offer a diverse range of degree programs and excellent research opportunities. The University boasts numerous interdisciplinary projects in a broad range of fields and an extensive partner network of leading regional, national, and international higher education and research institutions.
    Sustainable science and scholarship

    Universität Hamburg is committed to sustainability. All our faculties have taken great strides towards sustainability in both research and teaching.
    Excellent research

    As part of the Excellence Strategy of the Federal and State Governments, Universität Hamburg has been granted clusters of excellence for 4 core research areas: Advanced Imaging of Matter (photon and nanosciences), Climate, Climatic Change, and Society (CliCCS) (climate research), Understanding Written Artefacts (manuscript research) and Quantum Universe (mathematics, particle physics, astrophysics, and cosmology).

    An equally important core research area is Infection Research, in which researchers investigate the structure, dynamics, and mechanisms of infection processes to promote the development of new treatment methods and therapies.
    Outstanding variety: over 170 degree programs

    Universität Hamburg offers approximately 170 degree programs within its eight faculties:

    Faculty of Law
    Faculty of Business, Economics and Social Sciences
    Faculty of Medicine
    Faculty of Education
    Faculty of Mathematics, Informatics and Natural Sciences
    Faculty of Psychology and Human Movement Science
    Faculty of Business Administration (Hamburg Business School).

    Universität Hamburg is also home to several museums and collections, such as the Zoological Museum, the Herbarium Hamburgense, the Geological-Paleontological Museum, the Loki Schmidt Garden, and the Hamburg Observatory.
    History

    Universität Hamburg was founded in 1919 by local citizens. Important founding figures include Senator Werner von Melle and the merchant Edmund Siemers. Nobel Prize winners such as the physicists Otto Stern, Wolfgang Pauli, and Isidor Rabi taught and researched at the University. Many other distinguished scholars, such as Ernst Cassirer, Erwin Panofsky, Aby Warburg, William Stern, Agathe Lasch, Magdalene Schoch, Emil Artin, Ralf Dahrendorf, and Carl Friedrich von Weizsäcker, also worked here.
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    U Illinois campus

    The University of Illinois at Urbana-Champaign community of students, scholars, and alumni is changing the world.

    With our land-grant heritage as a foundation, we pioneer innovative research that tackles global problems and expands the human experience. Our transformative learning experiences, in and out of the classroom, are designed to produce alumni who desire to make a significant, societal impact.

    The University of Illinois at Chicago (UIC) is a public research university in Chicago, Illinois. Its campus is in the Near West Side community area, adjacent to the Chicago Loop. The second campus established under the University of Illinois system, UIC is also the largest university in the Chicago area, having approximately 30,000 students[9] enrolled in 15 colleges.

    UIC operates the largest medical school in the United States with research expenditures exceeding $412 million and consistently ranks in the top 50 U.S. institutions for research expenditures.[10][11][12] In the 2019 U.S. News & World Report’s ranking of colleges and universities, UIC ranked as the 129th best in the “national universities” category.[13] The 2015 Times Higher Education World University Rankings ranked UIC as the 18th best in the world among universities less than 50 years old.[14]

    UIC competes in NCAA Division I Horizon League as the UIC Flames in sports. The Credit Union 1 Arena (formerly UIC Pavilion) is the Flames’ venue for home games.

     
  • richardmitnick 8:30 am on July 26, 2019 Permalink | Reply
    Tags: "Stanford physicists count sound particles with quantum microphone", , , Qubits,   

    From Stanford University: “Stanford physicists count sound particles with quantum microphone” 

    Stanford University Name
    From Stanford University

    July 24, 2019
    Ker Than

    A device that eavesdrops on the quantum whispers of atoms could form the basis of a new type of quantum computer.

    1
    Artist’s impression of an array of nanomechanical resonators designed to generate and trap sound particles, or phonons. The mechanical motions of the trapped phonons are sensed by a qubit detector, which shifts its frequency depending on the number of phonons in a resonator. Different phonon numbers are visible as distinct peaks in the qubit spectrum, which are shown schematically behind the resonators. (Image credit: Wentao Jiang)

    Stanford physicists have developed a “quantum microphone” so sensitive that it can measure individual particles of sound, called phonons.

    The device, which is detailed July 24 in the journal Nature, could eventually lead to smaller, more efficient quantum computers that operate by manipulating sound rather than light.

    “We expect this device to allow new types of quantum sensors, transducers and storage devices for future quantum machines,” said study leader Amir Safavi-Naeini, an assistant professor of applied physics at Stanford’s School of Humanities and Sciences.

    Quantum of motion

    First proposed by Albert Einstein in 1907, phonons are packets of vibrational energy emitted by jittery atoms. These indivisible packets, or quanta, of motion manifest as sound or heat, depending on their frequencies.

    Like photons, which are the quantum carriers of light, phonons are quantized, meaning their vibrational energies are restricted to discrete values – similar to how a staircase is composed of distinct steps.

    “Sound has this granularity that we don’t normally experience,” Safavi-Naeini said. “Sound, at the quantum level, crackles.”

    The energy of a mechanical system can be represented as different “Fock” states – 0, 1, 2, and so on – based on the number of phonons it generates. For example, a “1 Fock state” consist of one phonon of a particular energy, a “2 Fock state” consists of two phonons with the same energy, and so on. Higher phonon states correspond to louder sounds.

    Until now, scientists have been unable to measure phonon states in engineered structures directly because the energy differences between states – in the staircase analogy, the spacing between steps – is vanishingly small. “One phonon corresponds to an energy ten trillion trillion times smaller than the energy required to keep a lightbulb on for one second,” said graduate student Patricio Arrangoiz-Arriola, a co-first author of the study.

    To address this issue, the Stanford team engineered the world’s most sensitive microphone – one that exploits quantum principles to eavesdrop on the whispers of atoms.

    In an ordinary microphone, incoming sound waves jiggle an internal membrane, and this physical displacement is converted into a measurable voltage. This approach doesn’t work for detecting individual phonons because, according to the Heisenberg uncertainty principle, a quantum object’s position can’t be precisely known without changing it.

    “If you tried to measure the number of phonons with a regular microphone, the act of measurement injects energy into the system that masks the very energy that you’re trying to measure,” Safavi-Naeini said.

    Instead, the physicists devised a way to measure Fock states – and thus, the number of phonons – in sound waves directly. “Quantum mechanics tells us that position and momentum can’t be known precisely – but it says no such thing about energy,” Safavi-Naeini said. “Energy can be known with infinite precision.”

    Singing qubits

    The quantum microphone the group developed consists of a series of supercooled nanomechanical resonators, so small that they are visible only through an electron microscope. The resonators are coupled to a superconducting circuit that contains electron pairs that move around without resistance. The circuit forms a quantum bit, or qubit, that can exist in two states at once and has a natural frequency, which can be read electronically. When the mechanical resonators vibrate like a drumhead, they generate phonons in different states.

    “The resonators are formed from periodic structures that act like mirrors for sound. By introducing a defect into these artificial lattices, we can trap the phonons in the middle of the structures,” Arrangoiz-Arriola said.

    Like unruly inmates, the trapped phonons rattle the walls of their prisons, and these mechanical motions are conveyed to the qubit by ultra-thin wires. “The qubit’s sensitivity to displacement is especially strong when the frequencies of the qubit and the resonators are nearly the same,” said joint first-author Alex Wollack, also a graduate student at Stanford.

    However, by detuning the system so that the qubit and the resonators vibrate at very different frequencies, the researchers weakened this mechanical connection and triggered a type of quantum interaction, known as a dispersive interaction, that directly links the qubit to the phonons.

    This bond causes the frequency of the qubit to shift in proportion to the number of phonons in the resonators. By measuring the qubit’s changes in tune, the researchers could determine the quantized energy levels of the vibrating resonators – effectively resolving the phonons themselves.

    “Different phonon energy levels appear as distinct peaks in the qubit spectrum,” Safavi-Naeini said. “These peaks correspond to Fock states of 0, 1, 2 and so on. These multiple peaks had never been seen before.”

    Mechanical quantum mechanical

    Mastering the ability to precisely generate and detect phonons could help pave the way for new kinds of quantum devices that are able to store and retrieve information encoded as particles of sound or that can convert seamlessly between optical and mechanical signals.

    Such devices could conceivably be made more compact and efficient than quantum machines that use photons, since phonons are easier to manipulate and have wavelengths that are thousands of times smaller than light particles.

    “Right now, people are using photons to encode these states. We want to use phonons, which brings with it a lot of advantages,” Safavi-Naeini said. “Our device is an important step toward making a ‘mechanical quantum mechanical’ computer.”

    Other Stanford co-authors include graduate students Zhaoyou Wang, Wentao Jiang, Timothy McKenna and Jeremy Witmer, and postdoctoral researchers Marek Pechal and Raphël Van Laer.

    The research was funded by the David and Lucile Packard Fellowship, the Stanford University Terman Fellowship and the U.S. Office of Naval Research.

    See the full article here .


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    Stanford University campus. No image credit

    Stanford University

    Leland and Jane Stanford founded the University to “promote the public welfare by exercising an influence on behalf of humanity and civilization.” Stanford opened its doors in 1891, and more than a century later, it remains dedicated to finding solutions to the great challenges of the day and to preparing our students for leadership in today’s complex world. Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto. Since 1952, more than 54 Stanford faculty, staff, and alumni have won the Nobel Prize, including 19 current faculty members

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  • richardmitnick 1:10 pm on March 10, 2019 Permalink | Reply
    Tags: A quantum computer would greatly speed up analysis of the collisions hopefully finding evidence of supersymmetry much sooner—or at least allowing us to ditch the theory and move on., And they’ve been waiting for decades. Google is in the race as are IBM Microsoft Intel and a clutch of startups academic groups and the Chinese government., , At the moment researchers spend weeks and months sifting through the debris from proton-proton collisions in the LCH trying to find exotic heavy sister-particles to all our known particles of matter., “This is a marathon” says David Reilly who leads Microsoft’s quantum lab at the University of Sydney Australia. “And it's only 10 minutes into the marathon.”, , , , For CERN the quantum promise could for instance help its scientists find evidence of supersymmetry or SUSY which so far has proven elusive., , IBM has steadily been boosting the number of qubits on its quantum computers starting with a meagre 5-qubit computer then 16- and 20-qubit machines and just recently showing off its 50-qubit processor, In a bid to make sense of the impending data deluge some at CERN are turning to the emerging field of quantum computing., In a quantum computer each circuit can have one of two values—either one (on) or zero (off) in binary code; the computer turns the voltage in a circuit on or off to make it work., In theory a quantum computer would process all the states a qubit can have at once and with every qubit added to its memory size its computational power should increase exponentially., Last year physicists from the California Institute of Technology in Pasadena and the University of Southern California managed to replicate the discovery of the Higgs boson found at the LHC in 2012, None of the competing teams have come close to reaching even the first milestone., , , Qubits, The quest has now lasted decades and a number of physicists are questioning if the theory behind SUSY is really valid., Traditional computers—be it an Apple Watch or the most powerful supercomputer—rely on tiny silicon transistors that work like on-off switches to encode bits of data., Venture capitalists invested some $250 million in various companies researching quantum computing in 2018 alone.,   

    From WIRED: “Inside the High-Stakes Race to Make Quantum Computers Work” 

    Wired logo

    From WIRED

    03.08.19
    Katia Moskvitch

    1
    View Pictures/Getty Images

    Deep beneath the Franco-Swiss border, the Large Hadron Collider is sleeping.

    LHC

    CERN map


    CERN LHC Tunnel

    CERN LHC particles

    But it won’t be quiet for long. Over the coming years, the world’s largest particle accelerator will be supercharged, increasing the number of proton collisions per second by a factor of two and a half.

    Once the work is complete in 2026, researchers hope to unlock some of the most fundamental questions in the universe. But with the increased power will come a deluge of data the likes of which high-energy physics has never seen before. And, right now, humanity has no way of knowing what the collider might find.

    To understand the scale of the problem, consider this: When it shut down in December 2018, the LHC generated about 300 gigabytes of data every second, adding up to 25 petabytes (PB) annually. For comparison, you’d have to spend 50,000 years listening to music to go through 25 PB of MP3 songs, while the human brain can store memories equivalent to just 2.5 PB of binary data. To make sense of all that information, the LHC data was pumped out to 170 computing centers in 42 countries [http://greybook.cern.ch/]. It was this global collaboration that helped discover the elusive Higgs boson, part of the Higgs field believed to give mass to elementary particles of matter.

    CERN CMS Higgs Event


    CERN ATLAS Higgs Event

    To process the looming data torrent, scientists at the European Organization for Nuclear Research, or CERN, will need 50 to 100 times more computing power than they have at their disposal today. A proposed Future Circular Collider, four times the size of the LHC and 10 times as powerful, would create an impossibly large quantity of data, at least twice as much as the LHC.

    CERN FCC Future Circular Collider map

    In a bid to make sense of the impending data deluge, some at CERN are turning to the emerging field of quantum computing. Powered by the very laws of nature the LHC is probing, such a machine could potentially crunch the expected volume of data in no time at all. What’s more, it would speak the same language as the LHC. While numerous labs around the world are trying to harness the power of quantum computing, it is the future work at CERN that makes it particularly exciting research. There’s just one problem: Right now, there are only prototypes; nobody knows whether it’s actually possible to build a reliable quantum device.

    Traditional computers—be it an Apple Watch or the most powerful supercomputer—rely on tiny silicon transistors that work like on-off switches to encode bits of data.

    ORNL IBM AC922 SUMMIT supercomputer, No.1 on the TOP500. Credit: Carlos Jones, Oak Ridge National Laboratory/U.S. Dept. of Energy

    Each circuit can have one of two values—either one (on) or zero (off) in binary code; the computer turns the voltage in a circuit on or off to make it work.

    A quantum computer is not limited to this “either/or” way of thinking. Its memory is made up of quantum bits, or qubits—tiny particles of matter like atoms or electrons. And qubits can do “both/and,” meaning that they can be in a superposition of all possible combinations of zeros and ones; they can be all of those states simultaneously.

    For CERN, the quantum promise could, for instance, help its scientists find evidence of supersymmetry, or SUSY, which so far has proven elusive.

    Standard Model of Supersymmetry via DESY

    At the moment, researchers spend weeks and months sifting through the debris from proton-proton collisions in the LCH, trying to find exotic, heavy sister-particles to all our known particles of matter. The quest has now lasted decades, and a number of physicists are questioning if the theory behind SUSY is really valid. A quantum computer would greatly speed up analysis of the collisions, hopefully finding evidence of supersymmetry much sooner—or at least allowing us to ditch the theory and move on.

    A quantum device might also help scientists understand the evolution of the early universe, the first few minutes after the Big Bang. Physicists are pretty confident that back then, our universe was nothing but a strange soup of subatomic particles called quarks and gluons. To understand how this quark-gluon plasma has evolved into the universe we have today, researchers simulate the conditions of the infant universe and then test their models at the LHC, with multiple collisions. Performing a simulation on a quantum computer, governed by the same laws that govern the very particles that the LHC is smashing together, could lead to a much more accurate model to test.

    Beyond pure science, banks, pharmaceutical companies, and governments are also waiting to get their hands on computing power that could be tens or even hundreds of times greater than that of any traditional computer.

    And they’ve been waiting for decades. Google is in the race, as are IBM, Microsoft, Intel and a clutch of startups, academic groups, and the Chinese government. The stakes are incredibly high. Last October, the European Union pledged to give $1 billion to over 5,000 European quantum technology researchers over the next decade, while venture capitalists invested some $250 million in various companies researching quantum computing in 2018 alone. “This is a marathon,” says David Reilly, who leads Microsoft’s quantum lab at the University of Sydney, Australia. “And it’s only 10 minutes into the marathon.”

    Despite the hype surrounding quantum computing and the media frenzy triggered by every announcement of a new qubit record, none of the competing teams have come close to reaching even the first milestone, fancily called quantum supremacy—the moment when a quantum computer performs at least one specific task better than a standard computer. Any kind of task, even if it is totally artificial and pointless. There are plenty of rumors in the quantum community that Google may be close, although if true, it would give the company bragging rights at best, says Michael Biercuk, a physicist at the University of Sydney and founder of quantum startup Q-CTRL. “It would be a bit of a gimmick—an artificial goal,” says Reilly “It’s like concocting some mathematical problem that really doesn’t have an obvious impact on the world just to say that a quantum computer can solve it.”

    That’s because the first real checkpoint in this race is much further away. Called quantum advantage, it would see a quantum computer outperform normal computers on a truly useful task. (Some researchers use the terms quantum supremacy and quantum advantage interchangeably.) And then there is the finish line, the creation of a universal quantum computer. The hope is that it would deliver a computational nirvana with the ability to perform a broad range of incredibly complex tasks. At stake is the design of new molecules for life-saving drugs, helping banks to adjust the riskiness of their investment portfolios, a way to break all current cryptography and develop new, stronger systems, and for scientists at CERN, a way to glimpse the universe as it was just moments after the Big Bang.

    Slowly but surely, work is already underway. Federico Carminati, a physicist at CERN, admits that today’s quantum computers wouldn’t give researchers anything more than classical machines, but, undeterred, he’s started tinkering with IBM’s prototype quantum device via the cloud while waiting for the technology to mature. It’s the latest baby step in the quantum marathon. The deal between CERN and IBM was struck in November last year at an industry workshop organized by the research organization.

    Set up to exchange ideas and discuss potential collab­orations, the event had CERN’s spacious auditorium packed to the brim with researchers from Google, IBM, Intel, D-Wave, Rigetti, and Microsoft. Google detailed its tests of Bristlecone, a 72-qubit machine. Rigetti was touting its work on a 128-qubit system. Intel showed that it was in close pursuit with 49 qubits. For IBM, physicist Ivano Tavernelli took to the stage to explain the company’s progress.

    IBM has steadily been boosting the number of qubits on its quantum computers, starting with a meagre 5-qubit computer, then 16- and 20-qubit machines, and just recently showing off its 50-qubit processor.

    IBM iconic image of Quantum computer

    Carminati listened to Tavernelli, intrigued, and during a much needed coffee break approached him for a chat. A few minutes later, CERN had added a quantum computer to its impressive technology arsenal. CERN researchers are now starting to develop entirely new algorithms and computing models, aiming to grow together with the device. “A fundamental part of this process is to build a solid relationship with the technology providers,” says Carminati. “These are our first steps in quantum computing, but even if we are coming relatively late into the game, we are bringing unique expertise in many fields. We are experts in quantum mechanics, which is at the base of quantum computing.”

    The attraction of quantum devices is obvious. Take standard computers. The prediction by former Intel CEO Gordon Moore in 1965 that the number of components in an integrated circuit would double roughly every two years has held true for more than half a century. But many believe that Moore’s law is about to hit the limits of physics. Since the 1980s, however, researchers have been pondering an alternative. The idea was popularized by Richard Feynman, an American physicist at Caltech in Pasadena. During a lecture in 1981, he lamented that computers could not really simulate what was happening at a subatomic level, with tricky particles like electrons and photons that behave like waves but also dare to exist in two states at once, a phenomenon known as quantum superposition.

    Feynman proposed to build a machine that could. “I’m not happy with all the analyses that go with just the classical theory, because nature isn’t classical, dammit,” he told the audience back in 1981. “And if you want to make a simulation of nature, you’d better make it quantum mechanical, and by golly it’s a wonderful problem, because it doesn’t look so easy.”

    And so the quantum race began. Qubits can be made in different ways, but the rule is that two qubits can be both in state A, both in state B, one in state A and one in state B, or vice versa, so there are four probabilities in total. And you won’t know what state a qubit is at until you measure it and the qubit is yanked out of its quantum world of probabilities into our mundane physical reality.

    In theory, a quantum computer would process all the states a qubit can have at once, and with every qubit added to its memory size, its computational power should increase exponentially. So, for three qubits, there are eight states to work with simultaneously, for four, 16; for 10, 1,024; and for 20, a whopping 1,048,576 states. You don’t need a lot of qubits to quickly surpass the memory banks of the world’s most powerful modern supercomputers—meaning that for specific tasks, a quantum computer could find a solution much faster than any regular computer ever would. Add to this another crucial concept of quantum mechanics: entanglement. It means that qubits can be linked into a single quantum system, where operating on one affects the rest of the system. This way, the computer can harness the processing power of both simultaneously, massively increasing its computational ability.

    While a number of companies and labs are competing in the quantum marathon, many are running their own races, taking different approaches. One device has even been used by a team of researchers to analyze CERN data, albeit not at CERN. Last year, physicists from the California Institute of Technology in Pasadena and the University of Southern California managed to replicate the discovery of the Higgs boson, found at the LHC in 2012, by sifting through the collider’s troves of data using a quantum computer manufactured by D-Wave, a Canadian firm based in Burnaby, British Columbia. The findings didn’t arrive any quicker than on a traditional computer, but, crucially, the research showed a quantum machine could do the work.

    One of the oldest runners in the quantum race, D-Wave announced back in 2007 that it had built a fully functioning, commercially available 16-qubit quantum computer prototype—a claim that’s controversial to this day. D-Wave focuses on a technology called quantum annealing, based on the natural tendency of real-world quantum systems to find low-energy states (a bit like a spinning top that inevitably will fall over). A D-Wave quantum computer imagines the possible solutions of a problem as a landscape of peaks and valleys; each coordinate represents a possible solution and its elevation represents its energy. Annealing allows you to set up the problem, and then let the system fall into the answer—in about 20 milliseconds. As it does so, it can tunnel through the peaks as it searches for the lowest valleys. It finds the lowest point in the vast landscape of solutions, which corresponds to the best possible outcome—although it does not attempt to fully correct for any errors, inevitable in quantum computation. D-Wave is now working on a prototype of a universal annealing quantum computer, says Alan Baratz, the company’s chief product officer.

    Apart from D-Wave’s quantum annealing, there are three other main approaches to try and bend the quantum world to our whim: integrated circuits, topological qubits and ions trapped with lasers. CERN is placing high hopes on the first method but is closely watching other efforts too.

    IBM, whose computer Carminati has just started using, as well as Google and Intel, all make quantum chips with integrated circuits—quantum gates—that are superconducting, a state when certain metals conduct electricity with zero resistance. Each quantum gate holds a pair of very fragile qubits. Any noise will disrupt them and introduce errors—and in the quantum world, noise is anything from temperature fluctuations to electromagnetic and sound waves to physical vibrations.

    To isolate the chip from the outside world as much as possible and get the circuits to exhibit quantum mechanical effects, it needs to be supercooled to extremely low temperatures. At the IBM quantum lab in Zurich, the chip is housed in a white tank—a cryostat—suspended from the ceiling. The temperature inside the tank is a steady 10 millikelvin or –273 degrees Celsius, a fraction above absolute zero and colder than outer space. But even this isn’t enough.

    Just working with the quantum chip, when scientists manipulate the qubits, causes noise. “The outside world is continually interacting with our quantum hardware, damaging the information we are trying to process,” says physicist John Preskill at the California Institute of Technology, who in 2012 coined the term quantum supremacy. It’s impossible to get rid of the noise completely, so researchers are trying to suppress it as much as possible, hence the ultracold temperatures to achieve at least some stability and allow more time for quantum computations.

    “My job is to extend the lifetime of qubits, and we’ve got four of them to play with,” says Matthias Mergenthaler, an Oxford University postdoc student working at IBM’s Zurich lab. That doesn’t sound like a lot, but, he explains, it’s not so much the number of qubits that counts but their quality, meaning qubits with as low a noise level as possible, to ensure they last as long as possible in superposition and allow the machine to compute. And it’s here, in the fiddly world of noise reduction, that quantum computing hits up against one of its biggest challenges. Right now, the device you’re reading this on probably performs at a level similar to that of a quantum computer with 30 noisy qubits. But if you can reduce the noise, then the quantum computer is many times more powerful.

    Once the noise is reduced, researchers try to correct any remaining errors with the help of special error-correcting algorithms, run on a classical computer. The problem is, such error correction works qubit by qubit, so the more qubits there are, the more errors the system has to cope with. Say a computer makes an error once every 1,000 computational steps; it doesn’t sound like much, but after 1,000 or so operations, the program will output incorrect results. To be able to achieve meaningful computations and surpass standard computers, a quantum machine has to have about 1,000 qubits that are relatively low noise and with error rates as corrected as possible. When you put them all together, these 1,000 qubits will make up what researchers call a logical qubit. None yet exist—so far, the best that prototype quantum devices have achieved is error correction for up to 10 qubits. That’s why these prototypes are called noisy intermediate-scale quantum computers (NISQ), a term also coined by Preskill in 2017.

    For Carminati, it’s clear the technology isn’t ready yet. But that isn’t really an issue. At CERN the challenge is to be ready to unlock the power of quantum computers when and if the hardware becomes available. “One exciting possibility will be to perform very, very accurate simulations of quantum systems with a quantum computer—which in itself is a quantum system,” he says. “Other groundbreaking opportunities will come from the blend of quantum computing and artificial intelligence to analyze big data, a very ambitious proposition at the moment, but central to our needs.”

    But some physicists think NISQ machines will stay just that—noisy—forever. Gil Kalai, a professor at Yale University, says that error correcting and noise suppression will never be good enough to allow any kind of useful quantum computation. And it’s not even due to technology, he says, but to the fundamentals of quantum mechanics. Interacting systems have a tendency for errors to be connected, or correlated, he says, meaning errors will affect many qubits simultaneously. Because of that, it simply won’t be possible to create error-correcting codes that keep noise levels low enough for a quantum computer with the required large number of qubits.

    “My analysis shows that noisy quantum computers with a few dozen qubits deliver such primitive computational power that it will simply not be possible to use them as the building blocks we need to build quantum computers on a wider scale,” he says. Among scientists, such skepticism is hotly debated. The blogs of Kalai and fellow quantum skeptics are forums for lively discussion, as was a recent much-shared article titled “The Case Against Quantum Computing”—followed by its rebuttal, “The Case Against the Case Against Quantum Computing.

    For now, the quantum critics are in a minority. “Provided the qubits we can already correct keep their form and size as we scale, we should be okay,” says Ray Laflamme, a physicist at the University of Waterloo in Ontario, Canada. The crucial thing to watch out for right now is not whether scientists can reach 50, 72, or 128 qubits, but whether scaling quantum computers to this size significantly increases the overall rate of error.

    3
    The Quantum Nano Centre in Canada is one of numerous big-budget research and development labs focussed on quantum computing. James Brittain/Getty Images

    Others believe that the best way to suppress noise and create logical qubits is by making qubits in a different way. At Microsoft, researchers are developing topological qubits—although its array of quantum labs around the world has yet to create a single one. If it succeeds, these qubits would be much more stable than those made with integrated circuits. Microsoft’s idea is to split a particle—for example an electron—in two, creating Majorana fermion quasi-particles. They were theorized back in 1937, and in 2012 researchers at Delft University of Technology in the Netherlands, working at Microsoft’s condensed matter physics lab, obtained the first experimental evidence of their existence.

    “You will only need one of our qubits for every 1,000 of the other qubits on the market today,” says Chetan Nayak, general manager of quantum hardware at Microsoft. In other words, every single topological qubit would be a logical one from the start. Reilly believes that researching these elusive qubits is worth the effort, despite years with little progress, because if one is created, scaling such a device to thousands of logical qubits would be much easier than with a NISQ machine. “It will be extremely important for us to try out our code and algorithms on different quantum simulators and hardware solutions,” says Carminati. “Sure, no machine is ready for prime time quantum production, but neither are we.”

    Another company Carminati is watching closely is IonQ, a US startup that spun out of the University of Maryland. It uses the third main approach to quantum computing: trapping ions. They are naturally quantum, having superposition effects right from the start and at room temperature, meaning that they don’t have to be supercooled like the integrated circuits of NISQ machines. Each ion is a singular qubit, and researchers trap them with special tiny silicon ion traps and then use lasers to run algorithms by varying the times and intensities at which each tiny laser beam hits the qubits. The beams encode data to the ions and read it out from them by getting each ion to change its electronic states.

    In December, IonQ unveiled its commercial device, capable of hosting 160 ion qubits and performing simple quantum operations on a string of 79 qubits. Still, right now, ion qubits are just as noisy as those made by Google, IBM, and Intel, and neither IonQ nor any other labs around the world experimenting with ions have achieved quantum supremacy.

    As the noise and hype surrounding quantum computers rumbles on, at CERN, the clock is ticking. The collider will wake up in just five years, ever mightier, and all that data will have to be analyzed. A non-noisy, error-corrected quantum computer will then come in quite handy.

    See the full article here .

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  • richardmitnick 11:49 am on March 1, 2019 Permalink | Reply
    Tags: "Yale researchers create a ‘universal entangler’ for new quantum tech", Potential uses in quantum computing and cryptography and quantum communications, , Qubits, The entangling mechanism is called an exponential-SWAP gate,   

    From Yale University: “Yale researchers create a ‘universal entangler’ for new quantum tech” 

    Yale University bloc

    From Yale University

    February 27, 2019
    Jim Shelton

    One of the key concepts in quantum physics is entanglement, in which two or more quantum systems become so inextricably linked that their collective state can’t be determined by observing each element individually. Now Yale researchers have developed a “universal entangler” that can link a variety of encoded particles on demand.

    The discovery represents a powerful new mechanism with potential uses in quantum computing, cryptography, and quantum communications. The research is led by the Yale laboratory of Robert Schoelkopf and appears in the journal Nature.

    Quantum calculations are accomplished with delicate bits of data called qubits, which are prone to errors. To implement faithful quantum computation, scientists say, they need “logical” qubits whose errors can be detected and rectified using quantum error correction codes.

    “We’ve shown a new way of creating gates between logically-encoded qubits that can eventually be error-corrected,” said Schoelkopf, the Sterling Professor of Applied Physics and Physics at Yale and director of the Yale Quantum Institute. “It’s a much more sophisticated operation than what has been performed previously.”

    The entangling mechanism is called an exponential-SWAP gate. In the study, researchers demonstrated the new technology by deterministically entangling encoded states in any chosen configurations or codes, each housed in two otherwise isolated, 3D superconducting microwave cavities.

    1
    Yale researchers have created a way to entangle a variety of encoded particles on demand.

    “This universal entangler is critical for robust quantum computation,” said Yvonne Gao, co-first author of the study. “Scientists have invented a wealth of hardware-efficient, quantum error correction codes — each one cleverly designed with unique characteristics that can be exploited for different applications. However, each of them requires wiring up a new set of tailored operations, introducing a significant hardware overhead and reduced versatility.”

    The universal entangler mitigates this limitation by providing a gate between any desired input states. “We can now choose any desired codes or even change them on the fly without having to re-wire the operation,” said co-first author Brian Lester.

    The discovery is just the latest step in Yale’s quantum research work. Yale scientists are at the forefront of efforts to develop the first fully useful quantum computers and have done pioneering work in quantum computing with superconducting circuits.

    Additional authors of the study are Kevin Chou, Luigi Frunzio, Michel Devoret, Liang Jiang, and Steven Girvin. The research was supported by the U.S. Army Research Office.

    See the full article here .

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    Yale University Campus

    Yale University comprises three major academic components: Yale College (the undergraduate program), the Graduate School of Arts and Sciences, and the professional schools. In addition, Yale encompasses a wide array of centers and programs, libraries, museums, and administrative support offices. Approximately 11,250 students attend Yale.

     
  • richardmitnick 10:22 am on February 23, 2019 Permalink | Reply
    Tags: , , , , , Qubits, Semiconductor quantum dots,   

    From University of Cambridge: “Physicists get thousands of semiconductor nuclei to do ‘quantum dances’ in unison” 

    U Cambridge bloc

    From University of Cambridge

    22 Feb 2019
    Communications office

    1
    Theoretical ESR spectrum buildup as a function of two-photon detuning δ and drive time τ, for a Rabi frequency of Ω = 3.3 MHz on the central transition. Credit: University of Cambridge.

    A team of Cambridge researchers have found a way to control the sea of nuclei in semiconductor quantum dots so they can operate as a quantum memory device.

    Quantum dots are crystals made up of thousands of atoms, and each of these atoms interacts magnetically with the trapped electron. If left alone to its own devices, this interaction of the electron with the nuclear spins, limits the usefulness of the electron as a quantum bit – a qubit.

    Led by Professor Mete Atatüre from Cambridge’s Cavendish Laboratory, the researchers are exploiting the laws of quantum physics and optics to investigate computing, sensing or communication applications.

    “Quantum dots offer an ideal interface, as mediated by light, to a system where the dynamics of individual interacting spins could be controlled and exploited,” said Atatüre, who is a Fellow of St John’s College. “Because the nuclei randomly ‘steal’ information from the electron they have traditionally been an annoyance, but we have shown we can harness them as a resource.”

    The Cambridge team found a way to exploit the interaction between the electron and the thousands of nuclei using lasers to ‘cool’ the nuclei to less than 1 milliKelvin, or a thousandth of a degree above the absolute zero temperature. They then showed they can control and manipulate the thousands of nuclei as if they form a single body in unison, like a second qubit. This proves the nuclei in the quantum dot can exchange information with the electron qubit and can be used to store quantum information as a memory device. The results are reported in the journal Science.

    Quantum computing aims to harness fundamental concepts of quantum physics, such as entanglement and superposition principle, to outperform current approaches to computing and could revolutionise technology, business and research. Just like classical computers, quantum computers need a processor, memory, and a bus to transport the information backwards and forwards. The processor is a qubit which can be an electron trapped in a quantum dot, the bus is a single photon that these quantum dots generate and are ideal for exchanging information. But the missing link for quantum dots is quantum memory.

    Atatüre said: “Instead of talking to individual nuclear spins, we worked on accessing collective spin waves by lasers. This is like a stadium where you don’t need to worry about who raises their hands in the Mexican wave going round, as long as there is one collective wave because they all dance in unison.

    “We then went on to show that these spin waves have quantum coherence. This was the missing piece of the jigsaw and we now have everything needed to build a dedicated quantum memory for every qubit.”

    In quantum technologies, the photon, the qubit and the memory need to interact with each other in a controlled way. This is mostly realised by interfacing different physical systems to form a single hybrid unit which can be inefficient. The researchers have been able to show that in quantum dots, the memory element is automatically there with every single qubit.

    Dr Dorian Gangloff, one of the first authors of the paper [Science] and a Fellow at St John’s, said the discovery will renew interest in these types of semiconductor quantum dots. Dr Gangloff explained: “This is a Holy Grail breakthrough for quantum dot research – both for quantum memory and fundamental research; we now have the tools to study dynamics of complex systems in the spirit of quantum simulation.”

    The long term opportunities of this work could be seen in the field of quantum computing. Last month, IBM launched the world’s first commercial quantum computer, and the Chief Executive of Microsoft has said quantum computing has the potential to ‘radically reshape the world’.

    Gangloff said: “The impact of the qubit could be half a century away but the power of disruptive technology is that it is hard to conceive of the problems we might open up – you can try to think of it as known unknowns but at some point you get into new territory. We don’t yet know the kind of problems it will help to solve which is very exciting.”

    See the full article here .

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    Please help promote STEM in your local schools.

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    U Cambridge Campus

    The University of Cambridge (abbreviated as Cantab in post-nominal letters) is a collegiate public research university in Cambridge, England. Founded in 1209, Cambridge is the second-oldest university in the English-speaking world and the world’s fourth-oldest surviving university. It grew out of an association of scholars who left the University of Oxford after a dispute with townsfolk. The two ancient universities share many common features and are often jointly referred to as “Oxbridge”.

    Cambridge is formed from a variety of institutions which include 31 constituent colleges and over 100 academic departments organised into six schools. The university occupies buildings throughout the town, many of which are of historical importance. The colleges are self-governing institutions founded as integral parts of the university. In the year ended 31 July 2014, the university had a total income of £1.51 billion, of which £371 million was from research grants and contracts. The central university and colleges have a combined endowment of around £4.9 billion, the largest of any university outside the United States. Cambridge is a member of many associations and forms part of the “golden triangle” of leading English universities and Cambridge University Health Partners, an academic health science centre. The university is closely linked with the development of the high-tech business cluster known as “Silicon Fen”.

     
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