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

From MIT News

September 16, 2019
Rob Matheson

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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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.

From Stanford University Engineering: “Quantum technology seeks to control light with unerring precision”

From Stanford University Engineering

August 26, 2019
Tom Abate

The ability to do this could eventually transform how we process large amounts of information.

So long silicon? An experimental diamond chip that harnesses light could lead to a new era of quantum data processing. | ScienceSource/David Parker

For decades, engineers have made computers smaller, faster, and cheaper by improving their fundamental component, the integrated circuit — the generic term that describes the maze of pathways that control the flow of electricity through a silicon chip.

Now, in a new scientific paper [Nature Communications], a team led by Professor Jelena Vuckovic describes how it built an integrated circuit to control the flow of light through a diamond chip, helping pave the way for quantum processors that, in theory, could perform some tasks, such as code-breaking, far faster than the fastest electronic computers today.

“Quantum technology is roughly where electronic technology was in the early 1970s,” said Vuckovic, who led the 13-person research team. “Researchers have figured out how to make very basic integrated circuits, but now they have to be scaled and made much better.”

Building an optical integrated circuit in diamond is a practical step toward making quantum technologies useful. Engineers have long known how to design ordinary electronic circuits and control the electrons that help perform computational tasks. But they are still struggling to build quantum circuits with all the necessary pathways to control photons, the basic particles in light.

To meet this design challenge, Vuckovic’s lab used diamond, a crystal that can have atomic impurities that trap electrons. A laser beam can be pointed at one of these trapped electrons, causing it to spin. These spinning electrons — called qubits, or quantum bits — are the basis for performing quantum calculations just as transistors are the basis for performing electronic calculations. In essence, a quantum processor would have an array of qubits connected by light flowing through an optical integrated circuit, just as an electronic computer has transistors connected by current flowing through wires.

To create their optical integrated circuit, Vuckovic’s team, led by graduate student Constantin Dory, developed algorithms that considered the positions of the impurities that form qubits, and the ways that lasers could manipulate these qubits to perform calculations. The algorithms also took into account the capabilities of the equipment that engineers use to make chips. After considering all these variables together using a process called inverse design, the algorithms generated a schematic that the researchers used to fabricate their optical integrated circuit.

Researchers are developing quantum computers based on light rather than electricity. At Stanford, new materials could be the key to progress in this field. (Image credit: iStock/Pobytov)

To date, the researchers were able to fabricate circuits consisting of six building blocks, potentially enabling interaction of only a few qubits. To build a useful quantum processor, the researchers say they’ll have to design and build a chip with hundreds of interacting qubits, all interconnected with optical pathways, which is extremely challenging, but possible. The Stanford team is also experimenting with other crystals that may prove useful for controlling light and qubits.

Infrared light enters this silicon structure from the left. The cut-out patterns, determined by an algorithm, route two different frequencies of this light into the pathways on the right. This is a greatly magnified image of a working device that is about the size of a speck of dust.

Vuckovic foresees one application of their diamond optical chip in the near term — spy-proofing fiber optic networks. Today, all sorts of sensitive data from bank transfers to government secrets flow as a stream of ordinary light through fiber optic cables. Spies or criminals can tap into this stream without leaving any trace. However, if quantum light, such as a single photon, is used for communication, eavesdropping can be detected because any intrusion would leave behind subtle fingerprints.

Challenges remain. For starters, it is difficult to transmit quantum light over large distances. But Vuckovic is working with several other research teams around the world to build quantum repeaters, in which optical chips with a few qubits each, positioned at regular intervals, would be used to transmit tamper-proof quantum signals over long distances, even across continents. “We think a long-distance quantum network is achievable within a five-year time frame,” she said.

See the full article here .

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Conduct curiosity-driven and problem-driven research that generates new knowledge and produces discoveries that provide the foundations for future engineered systems
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Drive technology transfer to Silicon Valley and beyond with deeply and broadly educated people and transformative ideas that will improve our society and our world.

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The engineering school of the future will look very different from what it looks like today. So, in 2015, we brought together a wide range of stakeholders, including mid-career faculty, students and staff, to address two fundamental questions: In what areas can the School of Engineering make significant world‐changing impact, and how should the school be configured to address the major opportunities and challenges of the future?

One key output of the process is a set of 10 broad, aspirational questions on areas where the School of Engineering would like to have an impact in 20 years. The committee also returned with a series of recommendations that outlined actions across three key areas — research, education and culture — where the school can deploy resources and create the conditions for Stanford Engineering to have significant impact on those challenges.

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From Fermi National Accelerator Lab: “Department of Energy awards Fermilab $3.5 million for quantum science”

FNAL Art Image by Angela Gonzales

From Fermi National Accelerator Lab , an enduring source of strength for the US contribution to scientific research world wide.

August 27, 2019
Edited by Leah Hesla

The U.S. Department of Energy has awarded researchers at its Fermi National Accelerator Laboratory more than $3.5 million to boost research in the fast-emerging field of Quantum Information Science.

“Few pursuits have the revolutionary potential that quantum science presents,” said Fermilab Chief Research Officer Joe Lykken. “Fermilab’s expertise in quantum physics and cryogenic engineering is world-class, and combined with our experience in conventional computing and networks, we can advance quantum science in directions that not many other places can.”

As part of a number of grants to national laboratories and universities offered through its Quantum Information Science-Enabled Discovery (QuantISED) program, DOE’s recent round of funding to Fermilab covers three initiatives related to quantum science. It also funds Fermilab’s participation in a fourth initiative led by Argonne National Laboratory.

The DOE QuantISED grants will fund initiatives related to quantum computing. These include the simulation of advanced quantum devices that will improve quantum computing simulations and the development of novel electronics to work with large arrays of ultracold qubits.

For a half-century, Fermilab researchers have closely studied the quantum realm and provided the computational and engineering capabilties needed to zoom in on nature at its most fundamental level. The projects announced by the Department of Energy will build on those capabilities, pushing quantum science and technology forward and leading to new discoveries that will enhance our picture of the universe at its smallest scale.

“Fermilab is well-versed in engineering, algorithmic development and recruiting massive computational resources to explore quantum-scale phenomena,” said Fermilab Head of Quantum Science Panagiotis Spentzouris. “Now we’re wrangling those competencies and capabilities to advance quantum science in many areas, and in a way that only a leading physics laboratory could.”

_________________________________________________
The Fermilab-led initiatives funded through these DOE QuantISED grants are:

Large Scale Simulations of Quantum Systems on High-Performance Computing with Analytics for High-Energy Physics Algorithms
Lead principal investigator: Adam Lyon, Fermilab

The large-scale simulation of quantum computers has plenty in common with simulations in high-energy physics: Both must sweep over a large number of variables. Both organize their inputs and outputs similarly. And in both cases, the simulation has to be analyzed and consolidated into results. Fermilab scientists, in collaboration with scientists at Argonne National Laboratory, will use tools from high-energy physics to produce and analyze simulations using high-performance computers at the Argonne Leadership Computing Facility. Specifically, they will simulate the operation of a qubit device that uses superconducting cavities (which are also used as components in particle accelerators) to maintain quantum information over a relatively long time. Their results will determine the device’s impact on high-energy physics algorithms using an Argonne-developed quantum simulator.

Partner institution: Argonne National Laboratory

Research Technology for Quantum Information Systems
Lead principal investigator: Gustavo Cancelo, Fermilab

One of the main challenges in quantum information science is designing an architecture that solves problems of massive interconnection, massive data processing and heat load. The electronics must be able to operate and interface with other electronics operating both at 4 kelvins and at near absolute zero. Fermilab scientists and engineers are designing novel electronic circuits as well as massive control and readout electronics to be compatible with quantum devices, such as sensors and quantum qubits. These circuits will enable many applications in the quantum information science field.

Partner institutions: Argonne National Laboratory, Massachusetts Institute of Technology, University of Chicago

MAGIS-100 – co-led by Stanford University and Fermilab
Lead Fermilab principal investigator: Rob Plunkett

Fermilab will host a new experiment to test quantum mechanics on macroscopic scales of space and time. Scientists on the MAGIS-100 experiment will drop clouds of ultracold atoms down a 100-meter-long vacuum pipe on the Fermilab site, and use a stable laser to create an atom interferometer which will look for dark matter made of ultralightweight particles. They will also advance a technique for gravitational-wave detection at relatively low frequencies.

This is a joint venture under the collaboration leadership of Stanford University Professor Jason Hogan, who is funded by grant GBMF7945 from the Gordon and Betty Moore Foundation. Rob Plunkett of Fermilab serves as the project manager.

Other participating institutions: Northern Illinois University, Northwestern University, Stanford University, Johns Hopkins University, University of Liverpool

_________________________________________________

Fermilab was also funded to participate in another initiative led by Argonne National Laboratory:

Quantum Sensors for Wide Band Axion Dark Matter Detection
Lead principal investigator: Peter Barry, Argonne

Researchers are searching high and low for dark matter, the mysterious substance that makes up a quarter of our universe. One theory proposes that it could be made of particles called axions, which would signal their presence by converting into particles of light, called photons. Fermilab researchers are part of a team developing specialized detectors that look for photons in the terahertz range — at frequencies just below the infrared. The development of these detectors will widen the range of frequencies where axions may be discovered. To bring the faint signals to the fore, the team is using supersensitive quantum amplifiers.

Other participating institutions: National Institute of Standards and Technology, University of Colorado

See the full here.

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Fermi National Accelerator Laboratory (Fermilab), located just outside Batavia, Illinois, near Chicago, is a US Department of Energy national laboratory specializing in high-energy particle physics. Fermilab is America’s premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. Thousands of scientists from universities and laboratories around the world
collaborate at Fermilab on experiments at the frontiers of discovery.

From Science Alert: “This Superconductor Could Be Key to a Whole Different Type of Quantum Computer”

From Science Alert

17 AUG 2019
DAVID NIELD

(c1a1p1c1o1m1/iStock)

For quantum computing to become fully realised, we’re going to have to make a few huge scientific leaps along the way – including finding a superconductor that can act in the same way as silicon does in today’s computing. A team of researchers thinks that search might now be over.

Introducing the compound uranium ditelluride (UTe2), which a new study says could be used to build logic circuits with qubits – those super-powerful quantum bits that can be in two states at once.

One of the major problems quantum physicists are currently coming up against is keeping those qubits operational and stable for long enough to do some actual computing with them. It’s a thorny issue known as quantum decoherence.

What makes UTe2 stand out as a superconductor is its strong resistance to magnetic fields – resistance to the errors that could otherwise creep into quantum calculations.

“This is potentially the silicon of the quantum information age,” says physicist Nick Butch, from the National Institute of Standards and Technology (NIST). “You could use uranium ditelluride to build the qubits of an efficient quantum computer.”

Butch and his colleagues stumbled on the quantum-friendly properties of UTe2 while investigating a variety of uranium-based magnets. The initial thinking was that UTe2 might become magnetic at low temperatures – and while that didn’t happen, the compound did become a superconductor.

Technically, uranium ditelluride is a spin triplet, rather than a spin singlet, like most other superconductors are. This means that its Cooper pairs – electrons bound together at low temperatures – can be orientated differently.

The physics can get very complex very quickly, but the important point is that these properties mean the Cooper pairs can be aligned in parallel rather than in opposition, and that in turn suggests UTe2 should retain its superconductivity in the face of external disturbances (threats to quantum coherence).

“These parallel spin pairs could help the computer remain functional,” says Butch. “It can’t spontaneously crash because of quantum fluctuations.”

One of the reasons why quantum computing can be a head-spinner is that there are several possible approaches to it, and scientists aren’t yet sure which one is going to work best (or at all).

Using UTe2 in this way would take the topological quantum computing approach, an approach that hasn’t been explored as much as other options so far: essentially, it aims to encode qubits in a type of quasiparticle that may not actually exist.

Much of topological quantum computing is still hypothetical, but its big advantage – if indeed it works – is that it wouldn’t require the same level of quantum error correction just to remain coherent and stable.

That could give us logical qubits that work without the need for a lot of other qubits just for error correction. Topological quantum computing has challenges of its own, and we’re still a long way from a general purpose quantum computer, but it’s a step in the right direction – like many other exciting advancements we’re seeing.

And the team thinks uranium ditelluride has a few more secrets to give up yet, both in regards to quantum computing and superconductors in general.

“Exploring it further might give us insight into what stabilises these parallel-spin superconductors,” says Butch.

“A major goal of superconductor research is to be able to understand superconductivity well enough that we know where to look for undiscovered superconductor materials.”

“Right now we can’t do that. What about them is essential? We are hoping this material will tell us more.”

The research has been published in Science.

See the full article here .

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

From University of Illinois Chicago

and

U Hamburg

via

30 JULY 2019
MICHELLE STARR

(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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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.
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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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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.

From Nautilus: “Quantum Supremacy Is Coming: Here’s What You Should Know”

From Nautilus

July 2019
Kevin Hartnett

Graham Carlow

IBM iconic image of Quantum computer

Researchers are getting close to building a quantum computer that can perform tasks a classical computer can’t. Here’s what the milestone will mean.

Quantum computers will never fully replace “classical” ones like the device you’re reading this article on. They won’t run web browsers, help with your taxes, or stream the latest video from Netflix.

Lenovo ThinkPad X1 Yoga (OLED)

What they will do—what’s long been hoped for, at least—will be to offer a fundamentally different way of performing certain calculations. They’ll be able to solve problems that would take a fast classical computer billions of years to perform. They’ll enable the simulation of complex quantum systems such as biological molecules, or offer a way to factor incredibly large numbers, thereby breaking long-standing forms of encryption.

The threshold where quantum computers cross from being interesting research projects to doing things that no classical computer can do is called “quantum supremacy.” Many people believe that Google’s quantum computing project will achieve it later this year. In anticipation of that event, we’ve created this guide for the quantum-computing curious. It provides the information you’ll need to understand what quantum supremacy means, and whether it’s really been achieved.

What is quantum supremacy and why is it important?

To achieve quantum supremacy, a quantum computer would have to perform any calculation that, for all practical purposes, a classical computer can’t.

In one sense, the milestone is artificial. The task that will be used to test quantum supremacy is contrived—more of a parlor trick than a useful advance (more on this shortly). For that reason, not all serious efforts to build a quantum computer specifically target quantum supremacy. “Quantum supremacy, we don’t use [the term] at all,” said Robert Sutor, the executive in charge of IBM’s quantum computing strategy. “We don’t care about it at all.”

But in other ways, quantum supremacy would be a watershed moment in the history of computing. At the most basic level, it could lead to quantum computers that are, in fact, useful for certain practical problems.

There is historical justification for this view. In the 1990s, the first quantum algorithms solved problems nobody really cared about. But the computer scientists who designed them learned things that they could apply to the development of subsequent algorithms (such as Shor’s algorithm for factoring large numbers) that have enormous practical consequences.

“I don’t think those algorithms would have existed if the community hadn’t first worked on the question ‘What in principle are quantum computers good at?’ without worrying about use value right away,” said Bill Fefferman, a quantum information scientist at the University of Chicago.

The quantum computing world hopes that the process will repeat itself now. By building a quantum computer that beats classical computers—even at solving a single useless problem—researchers could learn things that will allow them to build a more broadly useful quantum computer later on.

“Before supremacy, there is simply zero chance that a quantum computer can do anything interesting,” said Fernando Brandão, a theoretical physicist at the California Institute of Technology and a research fellow at Google. “Supremacy is a necessary milestone.”

In addition, quantum supremacy would be an earthquake in the field of theoretical computer science. For decades, the field has operated under an assumption called the “extended Church-Turing thesis,” which says that a classical computer can efficiently perform any calculation that any other kind of computer can perform efficiently. Quantum supremacy would be the first experimental violation of that principle and so would usher computer science into a whole new world. “Quantum supremacy would be a fundamental breakthrough in the way we view computation,” said Adam Bouland, a quantum information scientist at the University of California, Berkeley.

How do you demonstrate quantum supremacy?

By solving a problem on a quantum computer that a classical computer cannot solve efficiently. The problem could be whatever you want, though it’s generally expected that the first demonstration of quantum supremacy will involve a particular problem known as “random circuit sampling.”

A simple example of a random sampling problem is a program that simulates the roll of a fair die. Such a program runs correctly when it properly samples from the possible outcomes, producing each of the six numbers on the die one-sixth of the time as you run the program repeatedly.

In place of a die, this candidate problem for quantum supremacy asks a computer to correctly sample from the possible outputs of a random quantum circuit, which is like a series of actions that can be performed on a set of quantum bits, or qubits. Let’s consider a circuit that acts on 50 qubits. As the qubits go through the circuit, the states of the qubits become intertwined, or entangled, in what’s called a quantum superposition. As a result, at the end of the circuit, the 50 qubits are in a superposition of 250 possible states. If you measure the qubits, the sea of 250 possibilities collapses into a single string of 50 bits. This is like rolling a die, except instead of six possibilities you have 250, or 1 quadrillion, and not all of the possibilities are equally likely to occur.

Quantum computers, which can exploit purely quantum features such as superpositions and entanglement, should be able to efficiently produce a series of samples from this random circuit that follow the correct distribution. For classical computers, however, there’s no known fast algorithm for generating these samples—so as the range of possible samples increases, classical computers quickly get overwhelmed by the task.

What’s the holdup?

As long as quantum circuits remain small, classical computers can keep pace. So to demonstrate quantum supremacy via the random circuit sampling problem, engineers need to be able to build quantum circuits of at least a certain minimum size—and so far, they can’t.

Circuit size is determined by the number of qubits you start with, combined with the number of times you manipulate those qubits. Manipulations in a quantum computer are performed using “gates,” just as they are in a classical computer. Different kinds of gates transform qubits in different ways—some flip the value of a single qubit, while others combine two qubits in different ways. If you run your qubits through 10 gates, you’d say your circuit has “depth” 10.

To achieve quantum supremacy, computer scientists estimate a quantum computer would need to solve the random circuit sampling problem for a circuit in the ballpark of 70 to 100 qubits with a depth of around 10. If the circuit is much smaller than that, a classical computer could probably still manage to simulate it — and classical simulation techniques are improving all the time.

Yet the problem quantum engineers now face is that as the number of qubits and gates increases, so does the error rate. And if the error rate is too high, quantum computers lose their advantage over classical ones.

There are many sources of error in a quantum circuit.

At the moment, the best two-qubit quantum gates have an error rate of around 0.5%, meaning that there’s about one error for every 200 operations. This is astronomically higher than the error rate in a standard classical circuit, where there’s about one error every 1017operations. To demonstrate quantum supremacy, engineers are going to have to bring the error rate for two-qubit gates down to around 0.1%.

How will we know for sure that quantum supremacy has been demonstrated?

Some milestones are unequivocal. Quantum supremacy is not one of them. “It’s not like a rocket launch or a nuclear explosion, where you just watch and immediately know whether it succeeded,” said Scott Aaronson, a computer scientist at the University of Texas, Austin.

To verify quantum supremacy, you have to show two things: that a quantum computer performed a calculation fast, and that a classical computer could not efficiently perform the same calculation.

It’s the second part that’s trickiest. Classical computers often turn out to be better at solving certain kinds of problems than computer scientists expected. Until you’ve proved a classical computer can’t possibly do something efficiently, there’s always the chance that a better, more efficient classical algorithm exists. Proving that such an algorithm doesn’t exist is probably more than most people will need in order to believe a claim of quantum supremacy, but such a claim could still take some time to be accepted.

How close is anyone to achieving it?

By many accounts Google is knocking on the door of quantum supremacy and could demonstrate it before the end of the year. (Of course, the same was said in 2017.) But a number of other groups have the potential to achieve quantum supremacy soon, including those at IBM, IonQ, Rigetti and Harvard University.

These groups are using several distinct approaches to building a quantum computer. Google, IBM and Rigetti perform quantum calculations using superconducting circuits. IonQ uses trapped ions. The Harvard initiative, led by Mikhail Lukin, uses rubidium atoms. Microsoft’s approach, which involves “topological qubits,” seems like more of a long shot.

Each approach has its pros and cons.

Superconducting quantum circuits have the advantage of being made out of a solid-state material. They can be built with existing fabrication techniques, and they perform very fast gate operations. In addition, the qubits don’t move around, which can be a problem with other technologies. But they also have to be cooled to extremely low temperatures, and each qubit in a superconducting chip has to be individually calibrated, which makes it hard to scale the technology to the thousands of qubits (or more) that will be needed in a really useful quantum computer.

Ion traps have a contrasting set of strengths and weaknesses. The individual ions are identical, which helps with fabrication, and ion traps give you more time to perform a calculation before the qubits become overwhelmed with noise from the environment. But the gates used to operate on the ions are very slow (thousands of times slower than superconducting gates) and the individual ions can move around when you don’t want them to.

At the moment, superconducting quantum circuits seem to be advancing fastest. But there are serious engineering barriers facing all of the different approaches. A major new technological advance will be needed before it’s possible to build the kind of quantum computers people dream of. “I’ve heard it said that quantum computing might need an invention analogous to the transistor—a breakthrough technology that performs nearly flawlessly and which is easily scalable,” Bouland said. “While recent experimental progress has been impressive, my inclination is that this hasn’t been found yet.”

Say quantum supremacy has been demonstrated. Now what?

If a quantum computer achieves supremacy for a contrived task like random circuit sampling, the obvious next question is: OK, so when will it will do something useful?

The usefulness milestone is sometimes referred to as quantum advantage. “Quantum advantage is this idea of saying: For a real use case—like financial services, AI, chemistry—when will you be able to see, and how will you be able to see, that a quantum computer is doing something significantly better than any known classical benchmark?” said Sutor of IBM, which has a number of corporate clients like JPMorgan Chase and Mercedes-Benz who have started exploring applications of IBM’s quantum chips.

A second milestone would be the creation of fault-tolerant quantum computers. These computers would be able to correct errors within a computation in real time, in principle allowing for error-free quantum calculations. But the leading proposal for creating fault-tolerant quantum computers, known as “surface code,” requires a massive overhead of thousands of error-correcting qubits for each “logical” qubit that the computer uses to actually perform a computation. This puts fault tolerance far beyond the current state of the art in quantum computing. It’s an open question whether quantum computers will need to be fault tolerant before they can really do anything useful. “There are many ideas,” Brandão said, “but nothing is for sure.”

See the full article here .

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Welcome to Nautilus. We are delighted you joined us. We are here to tell you about science and its endless connections to our lives. Each month we choose a single topic. And each Thursday we publish a new chapter on that topic online. Each issue combines the sciences, culture and philosophy into a single story told by the world’s leading thinkers and writers. We follow the story wherever it leads us. Read our essays, investigative reports, and blogs. Fiction, too. Take in our games, videos, and graphic stories. Stop in for a minute, or an hour. Nautilus lets science spill over its usual borders. We are science, connected.

From University of New South Wales: “200 times faster than ever before: the speediest quantum operation yet”

From University of New South Wales

18 Jul 2019
Isabelle Dubach

A group of physicists at UNSW Sydney have built a super-fast version of the central building block of a quantum computer. The research is the milestone result of a vision first outlined by scientists 20 years ago.

From left to right: Professor Michelle Simmons, Dr. Sam Gorman, Postdoc Research Associate, Dr. Yu He, Postdoc Research Associate, Ludwik Kranz, PhD student, Dr. Joris Keizer, Senior Research Fellow, Daniel Keith, PhD student

A group of scientists led by 2018 Australian of the Year Professor Michelle Simmons have achieved the first two-qubit gate between atom qubits in silicon – a major milestone on the team’s quest to build an atom-scale quantum computer. The pivotal piece of research was published today in world-renowned journal Nature.

A two-qubit gate is the central building block of any quantum computer – and the UNSW team’s version of it is the fastest that’s ever been demonstrated in silicon, completing an operation in 0.8 nanoseconds, which is ~200 times faster than other existing spin-based two-qubit gates.

In the Simmons’ group approach, a two-qubit gate is an operation between two electron spins – comparable to the role that classical logic gates play in conventional electronics. For the first time, the team was able to build a two-qubit gate by placing two atom qubits closer together than ever before, and then – in real-time – controllably observing and measuring their spin states.

The team’s unique approach to quantum computing requires not only the placement of individual atom qubits in silicon but all the associated circuitry to initialise, control and read-out the qubits at the nanoscale – a concept that requires such exquisite precision it was long thought to be impossible. But with this major milestone, the team is now positioned to translate their technology into scalable processors.

Professor Simmons, Director of the Centre of Excellence for Quantum Computation and Communication Technology (CQC2T) and founder of Silicon Quantum Computing Pty Ltd., says the past decade of previous results perfectly set the team up to shift the boundaries of what’s thought to be “humanly possible”.

“Atom qubits hold the world record for the longest coherence times of a qubit in silicon with the highest fidelities,” she says. “Using our unique fabrication technologies, we have already demonstrated the ability to read and initialise single electron spins on atom qubits in silicon with very high accuracy. We’ve also demonstrated that our atomic-scale circuitry has the lowest electrical noise of any system yet devised to connect to a semiconductor qubit.

“Optimising every aspect of the device design with atomic precision has now allowed us to build a really fast, highly accurate two-qubit gate, which is the fundamental building block of a scalable, silicon-based quantum computer.

“We’ve really shown that it is possible to control the world at the atomic scale – and that the benefits of the approach are transformational, including the remarkable speed at which our system operates.”

UNSW Science Dean, Professor Emma Johnston AO, says this key paper further shows just how ground-breaking Professor Simmons’ research is.

“This was one of Michelle’s team’s final milestones to demonstrate that they can actually make a quantum computer using atom qubits. Their next major goal is building a 10-qubit quantum integrated circuit – and we hope they reach that within 3-4 years.”

Getting up and close with qubits – engineering with a precision of just thousand-millionths of a metre

Using a scanning tunnelling microscope to precision-place and encapsulate phosphorus atoms in silicon, the team first had to work out the optimal distance between two qubits to enable the crucial operation.

“Our fabrication technique allows us to place the qubits exactly where we want them. This allows us to engineer our two-qubit gate to be as fast as possible,” says study lead co-author Sam Gorman from CQC2T.

“Not only have we brought the qubits closer together since our last breakthrough, but we have learnt to control every aspect of the device design with sub-nanometer precision to maintain the high fidelities.”

See the full article here .

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Welcome to UNSW Australia (The University of New South Wales), one of Australia’s leading research and teaching universities. At UNSW, we take pride in the broad range and high quality of our teaching programs. Our teaching gains strength and currency from our research activities, strong industry links and our international nature; UNSW has a strong regional and global engagement.

In developing new ideas and promoting lasting knowledge we are creating an academic environment where outstanding students and scholars from around the world can be inspired to excel in their programs of study and research. Partnerships with both local and global communities allow UNSW to share knowledge, debate and research outcomes. UNSW’s public events include concert performances, open days and public forums on issues such as the environment, healthcare and global politics. We encourage you to explore the UNSW website so you can find out more about what we do.

From Iowa State University via Futurity: “Quantum control with light paves way for ultra-fast computers”

From Iowa State University

via

Futurity

July 16th, 2019
Mike Krapfl-Iowa State

Terahertz light can control some of the essential quantum properties of superconducting states, report researchers.

Jigang Wang patiently explains his latest discovery in quantum control that could lead to superfast computing based on quantum mechanics: He mentions light-induced superconductivity without energy gap. He brings up forbidden supercurrent quantum beats. And he mentions terahertz-speed symmetry breaking.

Then he backs up and clarified all that. After all, the quantum world of matter and energy at terahertz and nanometer scales—trillions of cycles per second and billionths of meters—is still a mystery to most of us.

“I like to study quantum control of superconductivity exceeding the gigahertz, or billions of cycles per second, bottleneck in current state-of-the-art quantum computation applications,” says Wang, a professor of physics and astronomy at Iowa State University. “We’re using terahertz light as a control knob to accelerate supercurrents.”

A bit more explanation

Superconductivity is the movement of electricity through certain materials without resistance. It typically occurs at very, very cold temperatures. Think -400 Fahrenheit for “high-temperature” superconductors.

Terahertz light is light at very, very high frequencies. Think trillions of cycles per second. It’s essentially extremely strong and powerful microwave bursts firing at very short time frames.

It all sounds esoteric and strange. But the new method could have very practical applications.

“Light-induced supercurrents chart a path forward for electromagnetic design of emergent materials properties and collective coherent oscillations for quantum engineering applications,” Wang and his coauthors write in a paper in Nature Photonics.

In other words, the discovery could help physicists “create crazy-fast quantum computers by nudging supercurrents,” Wang writes in a summary of the research team’s findings.

Controlling quantum physics

Finding ways to control, access, and manipulate the special characteristics of the quantum world and connect them to real-world problems is a major scientific push these days. The National Science Foundation has included the “Quantum Leap” in its “10 big ideas” for future research and development.

“By exploiting interactions of these quantum systems, next-generation technologies for sensing, computing, modeling, and communicating will be more accurate and efficient,” says a summary of the science foundation’s support of quantum studies. “To reach these capabilities, researchers need understanding of quantum mechanics to observe, manipulate, and control the behavior of particles and energy at dimensions at least a million times smaller than the width of a human hair.”

The researchers are advancing the quantum frontier by finding new macroscopic supercurrent flowing states and developing quantum controls for switching and modulating them.

A summary of the research team’s study says experimental data they obtained from a terahertz spectroscopy instrument indicates terahertz light-wave tuning of supercurrents is a universal tool “and is key for pushing quantum functionalities to reach their ultimate limits in many cross-cutting disciplines” such as those mentioned by the science foundation.

And so, the researchers write, “We believe that it is fair to say that the present study opens a new arena of light-wave superconducting electronics via terahertz quantum control for many years to come.”

The Army Research Office supports Wang’s research. Additional researchers from Iowa State, the University of Wisconsin-Madison, and the University of Alabama at Birmingham contributed to the work.

See the full article here .

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Iowa State University is a public, land-grant university, where students get a great academic start in learning communities and stay active in 800-plus student organizations, undergrad research, internships and study abroad. They learn from world-class scholars who are tackling some of the world’s biggest challenges — feeding the hungry, finding alternative fuels and advancing manufacturing.

Iowa Agricultural College and Model Farm (now Iowa State University) was officially established on March 22, 1858, by the legislature of the State of Iowa. Story County was selected as a site on June 21, 1859, and the original farm of 648 acres was purchased for a cost of $5,379. The Farm House, the first building on the Iowa State campus, was completed in 1861, and in 1862, the Iowa legislature voted to accept the provision of the Morrill Act, which was awarded to the agricultural college in 1864.

Iowa State University Knapp-Wilson Farm House. Photo between 1911-1926

Iowa Agricultural College (Iowa State College of Agricultural and Mechanic Arts as of 1898), as a land grant institution, focused on the ideals that higher education should be accessible to all and that the university should teach liberal and practical subjects. These ideals are integral to the land-grant university.

The first official class entered at Ames in 1869, and the first class (24 men and 2 women) graduated in 1872. Iowa State was and is a leader in agriculture, engineering, extension, home economics, and created the nation’s first state veterinary medicine school in 1879.

In 1959, the college was officially renamed Iowa State University of Science and Technology. The focus on technology has led directly to many research patents and inventions including the first binary computer (the ABC), Maytag blue cheese, the round hay baler, and many more.

Beginning with a small number of students and Old Main, Iowa State University now has approximately 27,000 students and over 100 buildings with world class programs in agriculture, technology, science, and art.

Iowa State University is a very special place, full of history. But what truly makes it unique is a rare combination of campus beauty, the opportunity to be a part of the land-grant experiment, and to create a progressive and inventive spirit that we call the Cyclone experience. Appreciate what we have here, for it is indeed, one of a kind.

From University of Oxford: “Oxford to lead quantum computing hub as part of UK’s research and innovation drive”

From University of Oxford

11 Jul 2019

Oxford to lead quantum computing hub as part of UK’s research and innovation drive.

Science Minister Chris Skidmore has today announced £94 million of funding for the UK’s Quantum Technologies Research Hubs – including a quantum computing and simulation hub led by Oxford University.

Hubs centred at Oxford, Birmingham, Glasgow and York will revolutionise computing, sensing and timing, imaging, and communications respectively. The collaborations will involve 26 universities, 138 investigators and over 100 partners.

Among the developments in quantum research already taking place in the UK are technologies that will allow fire crews to see through smoke and dust, computers to solve previously unsolvable computational problems, construction projects to image unmapped voids like old mine workings, and cameras that will let vehicles ‘see’ around corners.

The National Quantum Technologies Programme, which began in 2013, has now entered its second phase of funding, part of which will involve the newly announced £94 million investment in four research hubs by the UK government, via UK Research and Innovation’s (UKRI) Engineering and Physical Sciences Research Council (EPSRC).

Through these hubs, the UK’s world-leading quantum technologies research base will continue to drive the development of new technologies through its network of academic and business partnerships.

Science Minister Chris Skidmore said: “Harnessing the full potential of emerging technologies is vital as we strive to meet our Industrial Strategy ambition to be the most innovative economy in the world.

“Our world-leading universities are pioneering ways to apply quantum technologies that could have serious commercial benefits for UK businesses. That’s why I am delighted to be announcing further investment in quantum technology hubs that will bring academics and innovators together and make this once futuristic technology applicable to our everyday lives.”

UKRI’s chief executive, Professor Sir Mark Walport, said: “The UK is leading the field in developing quantum technologies, and this new investment will help us make the next leap forward in the drive to link discoveries to innovative applications. UKRI is committed to ensuring the best research and researchers are supported in this area.”

Oxford will lead the UKRI EPSRC Hub in Quantum Computing and Simulation, which will enable the UK to be internationally leading in quantum computing and simulation. It will drive progress towards practical quantum computers and usher in the era where they will have revolutionary impact on real-world challenges in a range of multidisciplinary themes, from the discovery of novel drugs and new materials through to quantum-enhanced machine learning, information security and even carbon reduction through optimised resource usage.

The hub will bring together leading quantum research teams across 17 universities into a collaboration with more than 25 national and international commercial, governmental and academic entities. It will address critical research challenges and work with partners to accelerate the development of quantum computing in the UK. Hub research will focus on the hardware and software that will be needed for future quantum computers and simulators.

Professor David Lucas of Oxford’s Department of Physics, principal investigator for the new hub, said: “The quantum computing and simulation hub will drive forward the UK’s progress in developing future quantum computing technology. It will build on the successes of the Oxford-led ‘Phase 1’ NQIT hub, which has delivered world-leading performance in quantum logic and quantum networking, as well as a number of spinout companies to take quantum research out of the lab into the commercial arena.”

See the full article here.

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Oxford is a collegiate university, consisting of the central University and colleges. The central University is composed of academic departments and research centres, administrative departments, libraries and museums. The 38 colleges are self-governing and financially independent institutions, which are related to the central University in a federal system. There are also six permanent private halls, which were founded by different Christian denominations and which still retain their Christian character.

The different roles of the colleges and the University have evolved over time.

From COSMOS Magazine: “Thanks to AI, we know we can teleport qubits in the real world”

From COSMOS Magazine

26 June 2019
Gabriella Bernardi

Deep learning shows its worth in the word of quantum computing.

We’re coming to terms with quantum computing, (qu)bit by (qu)bit.
MEHAU KULYK/GETTY IMAGES

Italian researchers have shown that it is possible to teleport a quantum bit (or qubit) in what might be called a real-world situation.

And they did it by letting artificial intelligence do much of the thinking.

The phenomenon of qubit transfer is not new, but this work, which was led by Enrico Prati of the Institute of Photonics and Nanotechnologies in Milan, is the first to do it in a situation where the system deviates from ideal conditions.

Moreover, it is the first time that a class of machine-learning algorithms known as deep reinforcement learning has been applied to a quantum computing problem.

The findings are published in a paper in the journal Communications Physics.

One of the basic problems in quantum computing is finding a fast and reliable method to move the qubit – the basic piece of quantum information – in the machine. This piece of information is coded by a single electron that has to be moved between two positions without passing through any of the space in between.

In the so-called “adiabatic”, or thermodynamic, quantum computing approach, this can be achieved by applying a specific sequence of laser pulses to a chain of an odd number of quantum dots – identical sites in which the electron can be placed.

It is a purely quantum process and a solution to the problem was invented by Nikolay Vitanov of the Helsinki Institute of Physics in 1999. Given its nature, rather distant from the intuition of common sense, this solution is called a “counterintuitive” sequence.

However, the method applies only in ideal conditions, when the electron state suffers no disturbances or perturbations.

Thus, Prati and colleagues Riccardo Porotti and Dario Tamaschelli of the University of Milan and Marcello Restelli of the Milan Polytechnic, took a different approach.

“We decided to test the deep learning’s artificial intelligence, which has already been much talked about for having defeated the world champion at the game Go, and for more serious applications such as the recognition of breast cancer, applying it to the field of quantum computers,” Prati says.

Deep learning techniques are based on artificial neural networks arranged in different layers, each of which calculates the values for the next one so that the information is processed more and more completely.

Usually, a set of known answers to the problem is used to “train” the network, but when these are not known, another technique called “reinforcement learning” can be used.

In this approach two neural networks are used: an “actor” has the task of finding new solutions, and a “critic” must assess the quality of these solution. Provided a reliable way to judge the respective results can be given by the researchers, these two networks can examine the problem independently.

The researchers, then, set up this artificial intelligence method, assigning it the task of discovering alone how to control the qubit.

“So, we let artificial intelligence find its own solution, without giving it preconceptions or examples,” Prati says. “It found another solution that is faster than the original one, and furthermore it adapts when there are disturbances.”

In other words, he adds, artificial intelligence “has understood the phenomenon and generalised the result better than us”.

“It is as if artificial intelligence was able to discover by itself how to teleport qubits regardless of the disturbance in place, even in cases where we do not already have any solution,” he explains.

“With this work we have shown that the design and control of quantum computers can benefit from the using of artificial intelligence.”

See the full article here .

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