This is the first in a series of explainers on quantum technology. The other two are on quantum communication and post-quantum cryptography.

A quantum computer harnesses some of the almost-mystical phenomena of quantum mechanics to deliver huge leaps forward in processing power. Quantum machines promise to outstrip even the most capable of todaysand tomorrowssupercomputers.

They wont wipe out conventional computers, though. Using a classical machine will still be the easiest and most economical solution for tackling most problems. But quantum computers promise to power exciting advances in various fields, from materials science to pharmaceuticals research. Companies are already experimenting with them to develop things like lighter and more powerful batteries for electric cars, and to help create novel drugs.

The secret to a quantum computers power lies in its ability to generate and manipulate quantum bits, or qubits.

Today's computers use bitsa stream of electrical or optical pulses representing1s or0s. Everything from your tweets and e-mails to your iTunes songs and YouTube videos are essentially long strings of these binary digits.

Quantum computers, on the other hand, usequbits, whichare typically subatomic particles such as electrons or photons. Generating and managing qubits is a scientific and engineering challenge. Some companies, such as IBM, Google, and Rigetti Computing, use superconducting circuits cooled to temperatures colder than deep space. Others, like IonQ, trap individual atoms in electromagnetic fields on a silicon chip in ultra-high-vacuum chambers. In both cases, the goal is to isolate the qubits in a controlled quantum state.

Qubits have some quirky quantum properties that mean a connected group of them can provide way more processing power than the same number of binary bits. One of those properties is known as superposition and another is called entanglement.

Qubits can represent numerous possible combinations of 1and 0 at the same time. This ability to simultaneously be in multiple states is called superposition. To put qubits into superposition, researchers manipulate them using precision lasers or microwave beams.

Thanks to this counterintuitive phenomenon, a quantum computer with several qubits in superposition can crunch through a vast number of potential outcomes simultaneously. The final result of a calculation emerges only once the qubits are measured, which immediately causes their quantum state to collapse to either 1or 0.

Researchers can generate pairs of qubits that are entangled, which means the two members of a pair exist in a single quantum state. Changing the state of one of the qubits will instantaneously change the state of the other one in a predictable way. This happens even if they are separated by very long distances.

Nobody really knows quite how or why entanglement works. It even baffled Einstein, who famously described it as spooky action at a distance. But its key to the power of quantum computers. In a conventional computer, doubling the number of bits doubles its processing power. But thanks to entanglement, adding extra qubits to a quantum machine produces an exponential increase in its number-crunching ability.

Quantum computers harness entangled qubits in a kind of quantum daisy chain to work their magic. The machines ability to speed up calculations using specially designed quantum algorithms is why theres so much buzz about their potential.

Thats the good news. The bad news is that quantum machines are way more error-prone than classical computers because of decoherence.

The interaction of qubits with their environment in ways that cause their quantum behavior to decay and ultimately disappear is called decoherence. Their quantum state is extremely fragile. The slightest vibration or change in temperaturedisturbances known as noise in quantum-speakcan cause them to tumble out of superposition before their job has been properly done. Thats why researchers do their best to protect qubits from the outside world in those supercooled fridges and vacuum chambers.

But despite their efforts, noise still causes lots of errors to creep into calculations. Smart quantum algorithmscan compensate for some of these, and adding more qubits also helps. However, it will likely take thousands of standard qubits to create a single, highly reliable one, known as a logical qubit. This will sap a lot of a quantum computers computational capacity.

And theres the rub: so far, researchers havent been able to generate more than 128 standard qubits (see our qubit counter here). So were still many years away from getting quantum computers that will be broadly useful.

That hasnt dented pioneers hopes of being the first to demonstrate quantum supremacy.

Its the point at which a quantum computer can complete a mathematical calculation that is demonstrably beyond the reach of even the most powerful supercomputer.

Its still unclear exactly how many qubits will be needed to achieve this because researchers keep finding new algorithms to boost the performance of classical machines, and supercomputing hardware keeps getting better. But researchers and companies are working hard to claim the title, running testsagainst some of the worlds most powerful supercomputers.

Theres plenty of debate in the research world about just how significant achieving this milestone will be. Rather than wait for supremacy to be declared, companies are already starting to experiment with quantum computers made by companies like IBM, Rigetti, and D-Wave, a Canadian firm. Chinese firms like Alibaba are also offering access to quantum machines. Some businesses are buying quantum computers, while others are using ones made available through cloud computing services.

One of the most promising applications of quantum computers is for simulating the behavior of matterdown to the molecular level. Auto manufacturers like Volkswagen and Daimler are using quantum computers to simulate the chemical composition of electrical-vehicle batteries to help find new ways to improve their performance. And pharmaceutical companies are leveraging them to analyze and compare compounds that could lead to the creation of new drugs.

The machines are also great for optimization problems because they can crunch through vast numbers of potential solutions extremely fast. Airbus, for instance, is using them to help calculate the most fuel-efficient ascent and descent paths for aircraft. And Volkswagen has unveiled a service that calculates the optimal routes for buses and taxis in cities in order to minimize congestion. Some researchers also think the machines could be used to accelerate artificial intelligence.

It could take quite a few years for quantum computers to achieve their full potential. Universities and businesses working on them are facing a shortage of skilled researchersin the fieldand a lack of suppliersof some key components. But if these exotic new computing machines live up to their promise, they could transform entire industries and turbocharge global innovation.

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Explainer: What is a quantum computer? | MIT Technology Review

The use of quantum computers has grown over the past several months as researchers have relied on these systems to make sense of the massive amounts of data related to the COVID-19 virus.

Quantum computers are based on qubits, a unit that can hold more data than classic binary bits, said Heather West, a senior research analyst at IDC.

Besides better understanding of the virus, manufacturers have been using quantum systems to determine supply and demand on certain products -- toilet paper, for example -- so they can make estimates based on trends, such as how much is being sold in particular geographic areas, she said.

"Quantum computers can help better determine demand and supply, and it allows manufacturers to better push out supplies in a more scientific way,'' West said. "If there is that push in demand it can also help optimize the manufacturing process and accelerate it and actually modernize it by identifying breakdowns and bottlenecks."

Quantum has gained momentum this year because it has moved from the academic realm to "more commercially evolving ecosystems,'' West said.

In late 2019, Google claimed that it had reached quantum supremacy, observed Carmen Fontana, an IEEE member and a cloud and emerging tech practice lead at Centric Consulting. "While there was pushback on this announcement by other leaders in tech, one thing was certain -- it garnered many headlines."

Echoing West, Fontana said that until then, "quantum computing had felt to many as largely an academic exercise with far-off implications. After the announcement, sentiment seemed to shift to 'Quantum computing is real and happening sooner than later'."

In 2020, there have been more tangible timelines and applications for quantum computing, indicating that the space is rapidly advancing and maturing, Fontana said.

"For instance, IBM announced plans to go from their present 65-qubit computer to a 1,000-qubit computer over the next three years," he said. "Google conducted a large-scale chemical simulation on a quantum computer, demonstrating the practicality of the technology in solving real-world problems."

Improved artificial intelligence (AI) capabilities, accelerated business intelligence, and increased productivity and efficiency were the top expectations cited by organizations currently investing in cloud-based quantum computing technologies, according to an IDC surveyearlier this year.

"Initial survey findings indicate that while cloud-based quantum computing is a young market, and allocated funds for quantum computing initiatives are limited (0-2% of IT budgets), end users are optimistic that early investment will result in a competitive advantage,'' IDC said.

Manufacturing, financial services, and security industries are currently leading the way by experimenting with more potential use cases, developing advanced prototypes, and being further along in their implementation status, according to IDC.

Quantum is not without its challenges, though. The biggest one West sees is decoherence, which happens when qubits are exposed to "environmental factors" or too many try to work together at once. Because they are "very, very sensitive," they can lose their power and ability to function, and as result, cause errors in a calculation, she said.

"Right now, that is what many of the vendors are looking to solve with their qubit solutions,'' West said.

Another issue preventing quantum from becoming more of a mainstream technology right now is the ability to manage the quantum systems. "In order to keep qubits stable, they have to be kept at very cold, subzero temps, and that makes it really difficult for a lot of people to work with them,'' West said.

Nevertheless, With the time horizon of accessible quantum computing now shrinking to a decade or less, Fontana believes we can expect to see "an explosion of start-ups looking to be first movers in the quantum applications space. These companies will seek to apply quantum's powerful compute power to solve existing problems in novel ways."

Here are eight companies that are already focused on quantum computing.

Atom Computing is a quantum computing hardware company specializing in neutral atom quantum computers. While it is currently prototyping its first offerings, Atom Computing said it will provide cloud access "to large numbers of very coherent qubits by optically trapping and addressing individual atoms," said Ben Bloom, founder and CEO.

The company also builds and creates "complicated hardware control systems for use in the academic community,'' Bloom said.

Xanadu is a Canadian quantum technology company with the mission to build quantum computers that are useful and available to people everywhere. Founded in 2016, Xanadu is building toward a universal quantum computer using silicon photonic hardware, according to Sepehr Taghavi, corporate development manager.

The company also provides users access to near-term quantum devices through its Xanadu Quantum Cloud (XQC) service. The company also leads the development of PennyLane, an open-source software library for quantum machine learning and application development, Taghavi said.

In 2016, IBM was the first company to put a quantum computer on the cloud. The company has since built up an active community of more than 260,000 registered users, who run more than one billion every day on real hardware and simulators.

In 2017, IBM was the first company to offer universal quantum computing systems via theIBM Q Network. The network now includes more than 125 organizations, including Fortune 500s, startups, research labs, and education institutions. Partners include Daimler AG,JPMorgan Chase, andExxonMobil. All use IBM's most advanced quantum computers to simulate new materials for batteries, model portfolios and financial risk, and simulate chemistry for new energy technologies, the company said.

By2023, IBM scientists will deliver a quantum computer with a 1,121-qubit processor, inside a 10-foot tall "super-fridge" that will be online and capable of delivering a Quantum Advantage-- the point where certain information processing tasks can be performed more efficiently or cost effectively on a quantum computer, versus a classical one, according to the company.

ColdQuanta commercializes quantum atomics, which it said is "the next wave of the information age." The company's Quantum Core technology is based on ultra-cold atoms cooled to a temperature of nearly absolute zero; lasers manipulate and control the atoms with extreme precision.

The company manufactures components, instruments, and turnkey systems that address a broad spectrum of applications: quantum computing, timekeeping, navigation, radiofrequency sensors, and quantum communications. It also develops interface software.

ColdQuanta's global customers include major commercial and defense companies; all branches of the US Department of Defense; national labs operated by the Department of Energy; NASA; NIST; and major universities, the company said.

In April 2020, ColdQuanta was selected by the Defense Advanced Research Projects Agency (DARPA) to develop a scalable, cold-atom-based quantum computing hardware and software platform that can demonstrate quantum advantage on real-world problems.

Zapata Computing empowers enterprise teams to accelerate quantum solutions and capabilities. It introduced Orquestra, an end-to-end, workflow-based toolset for quantum computing. In addition to previously available backends that include a full range of simulators and classical resources, Orquestra now integrates with Qiskit and IBM Quantum's open quantum systems, Honeywell's System Model H, and Amazon Braket, the company said.

The Orquestra workflow platform provides access to Honeywell's H, and was designed to enable teams to compose, run, and analyze complex, quantum-enabled workflows and challenging computational solutions at scale, Zapata said. Orquestra is purpose-built for quantum machine learning, optimization, and simulation problems across industries.

Recently introduced Azure Quantum provides a "one-stop-shop" to create a path to scalable quantum computing, Microsoft said. It is available in preview to select customers and partners through Azure.

For developers, Azure Quantum offers:

Founded in 1999, D-Wave claims to be the first company to sell a commercial quantum computer, in 2011, and the first to give developers real-time cloud access to quantum processors with Leap, its quantum cloud service.

D-Wave's approach to quantum computing, known as quantum annealing, is best suited to optimization tasks in fields such as AI, logistics, cybersecurity, financial modeling, fault detection, materials sciences, and more. More than 250 early quantum applications have been built to-date using D-Wave's technology, the company said.

The company has seen a lot of momentum in 2020. In February, D-Wave announced the launch of Leap 2, which introduced new tools and features designed to make it easier for developers to build bigger applications. In July, the company expanded access to Leap to India and Australia. In March, D-Wave opened free access to Leap for researchers working on responses to the COVID-19 pandemic. In September, the company launched Advantage, a quantum system designed for business. Advantage has more than 5,000 qubits, 15-way qubit connectivity, and an expanded hybrid solver service to run problems with up to one million variables, D-Wave said. Advantage is accessible through Leap.

Strangeworks, a startup based in Austin, Texas, claims to be lowering the barrier to entry into quantum computing by providing tools for development on all quantum hardware and software platforms. Strangeworks launched in March 2018, and one year later, deployed a beta version of its software platform to users from more than 140 different organizations. Strangeworks will open its initial offering of the platform in Q1 2021, and the enterprise edition is coming in late 2021, according to Steve Gibson, chief strategy officer.

The Strangeworks Quantum Computing platform provides tools to access and program quantum computing devices. The Strangeworks IDE is platform-agnostic, and integrates all hardware, software frameworks, and supporting languages, the company said. To facilitate this goal, Strangeworks manages assembly, integrations, and product updates. Users can share their work privately with collaborators, or publicly. Users' work belongs to them and open sourcing is not required to utilize the Strangeworks platform.

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Eight leading quantum computing companies in 2020 | ZDNet

Dec 19th 2020

THE FINANCE industry has had a long and profitable relationship with computing. It was an early adopter of everything from mainframe computers to artificial intelligence (see timeline). For most of the past decade more trades have been done at high frequency by complex algorithms than by humans. Now big banks have their eyes on quantum computing, another cutting-edge technology.

This is the idea, developed by physicists in the 1980s, that the counter-intuitive properties of quantum mechanics might allow for the construction of computers that could perform mathematical feats that no non-quantum machine would ever be capable of. The promise is now starting to be realised. Computing giants like Google and IBM, as well as a flock of smaller competitors, are building and refining quantum hardware.

Quantum computers will not beat their classical counterparts at everything. But much of the maths at which they will excel is of interest to bankers. At a conference on December 10th William Zeng, head of quantum research at Goldman Sachs told the audience that quantum computing could have a revolutionary impact on the bank, and on finance more broadly.

Many financial calculations boil down to optimisation problems, a known strength of quantum computers, says Marco Pistoia, the head of a research unit at JPMorgan Chase, who spent many years at IBM before that. Quantum quants hope their machines will boost profits by speeding up asset pricing, digging up better-performing portfolios and making machine-learning algorithms more accurate. A study by BBVA, a Spanish bank, concluded in July that quantum computers could boost credit-scoring, spot arbitrage opportunities and accelerate so-called Monte Carlo simulations, which are commonly used in finance to try to model the likely behaviour of markets.

Finance is not the only industry looking for a way to profit from even the small, unstable quantum computers that mark the current state of the art; sectors from aerospace to pharmaceuticals are also hunting for a quantum advantage. But there are reasons to think finance may be among the first to find it. Mike Biercuk of Q-CTRL, a startup that makes control software for quantum computers, points out that a new financial algorithm can be deployed faster than a new industrial process. The size of financial markets means that even a small advance would be worth a lot of money.

Banks are also buying in expertise. Firms including BBVA, Citigroup, JPMorgan and Standard Chartered have set up research teams and signed deals with computing firms. The Boston Consulting Group reckons that, as of June, banks and insurers in America and Europe had hired more than 115 expertsa big number for what remains, even in academia, a small specialism. We have more physics and maths PhDs than some big universities, jokes Alexei Kondratyev, head of data analytics at Standard Chartered.

Startups are exploring possibilities too. Enrique Lizaso of Multiverse Computing reckons his firms quantum-enhanced algorithms can spot fraud more effectively, and around a hundred times faster, than existing ones. The firm has also experimented with portfolio optimisation, in which analysts seek well-performing investment strategies. Multiverse re-ran decisions made by real traders at a bank. The job was to choose, over the course of a year, the most profitable mix from a group of 50 assets, subject to restrictions, such as how often trades could be made.

The result was a problem with around 101,300 possible solutions, a number that far outstrips the number of atoms in the visible universe. In reality, the banks traders, assisted by models running on classical computers, managed an annual return of 19%. Depending on the amount of volatility investors were prepared to put up with, Multiverses algorithm generated returns of 20-80%though it stops short of claiming a definitive quantum advantage.

Not all potential uses are so glamorous. Monte Carlo simulations are often used in regulatory stress tests. Christopher Savoie of Zapata, a quantum-computing firm based in Boston, recalls one bank executive telling him: Dont bring me trading algorithms, bring me a solution to CCAR [an American stress-test regulation]. That stuff eats up half my computing budget.

All this is promising. But quantum financiers acknowledge that, for now, hardware is a limitation. Were not yet able to perform these calculations at a scale where a quantum machine offers a real-world advantage over a classical one, says Mr Biercuk. One rough way to measure a quantum computers capability is its number of qubits, the analogue of classical computings 1-or-0 bits. For many problems a quantum computer with thousands of stable qubits is provably far faster than any non-quantum machine that could ever be builtit just does not exist yet.

For now, the field must make do with small, unstable devices, which can perform calculations for only tiny fractions of a second before their delicate quantum states break down. John Preskill of the California Institute of Technology has dubbed these NISQsNoisy, Intermediate-Scale Quantum computers.

Bankers are working on ways to conduct computations on such machines. Mr Zeng of Goldman pointed out that the computational resources needed to run quantum algorithms have fallen as programmers have tweaked their methods. Mr Pistoia points to papers his team has written exploring ways to scale useful financial calculations into even small machines.

And at some point those programmers will meet hardware-makers coming the other way. In 2019 Google was the first to demonstrate quantum supremacy, using a 53-qubit NISQ machine to perform in minutes a calculation that would have taken the worlds fastest supercomputer more than 10,000 years. IBM, which has invested heavily in quantum computing, reckons it can build a 1,000-qubit machine by 2023. Both it and Google have talked of a million qubits by the end of the decade.

When might the financial revolution come? Mr Savoie thinks simple algorithms could be in use within 18 months, with credit-scoring a plausible early application. Mr Kondratyev says three to five years is more realistic. But the crucial point, says one observer, is that no one wants to be late to the party. One common worry is that whoever makes a breakthrough first may choose to reap the rewards in obscurity, rather than broadcast the fact to the world. After all, says Mr Biercuk, that is how high-frequency trading got started.

This article appeared in the Finance & economics section of the print edition under the headline "Quantum for quants"

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Wall Streets latest shiny new thing: quantum computing - The Economist

Spinning atoms in a magnetic field notoriously behave in ways that scientists are yet to understand entirely. New research from MIT has now shed some light on the obscure laws that govern the smallest of particles, which could pave the way for further developments in the design of quantum devices that rely on atomic spin.

The team exposed spinning lithium atoms to magnetic forces of different strengths to observe how the quantum particles reacted both individually and as a group. They were faced in each scenario with a surprising choreography of atoms, revealing unexpected diversity of behavior in a well-known and studied magnetic material.

Spin, like mass or charge, is an intrinsic property of atoms: the particles rotate around an axis in either a clockwise manner (often described as "down") or anticlockwise ("up"). Based on their spin, atoms can react to magnetic fields in different ways, for example by aligning themselves with other atoms in a specific pattern.

The spin of many atoms together in a magnetic material that is exposed to a magnetic field can reach an equilibrium state, where all the atom spins are aligned; or the atoms can adopt dynamic behavior, where the spins across many atoms create a wave-like pattern.

MIT's research team focused on the way that atoms evolve from dynamic behavior back into an equilibrium state and found that the magnetic force that the atoms are exposed to plays a key part in determining the particles' behavior. Some magnets triggered a so-called "ballistic" behavior, where the atomic spins shot quickly back into an equilibrium state, while others revealed "diffusive behavior", with the particles spinning back to equilibrium in a much slower fashion.

"Studying one of the simplest magnetic materials, we have advanced the understanding of magnetism," said Wolfgang Ketterle, professor of physics at MIT and the leader of the research team. "When you find new phenomena in one of the simplest models in physics for magnetism, then you have a chance to fully describe and understand it. This is what gets me out of bed in the morning, and gets me excited."

To study the phenomenon, Ketterle's team brought the lithium atoms down to temperatures more than ten times colder than interstellar space, which freezes the particles to a near standstill and enables easier observation. Using lasers as a type of tweezer, the scientists then grabbed the atoms and arranged them into strings of beads. With 1,000 strings, each comprising 40 atoms, the team created an ultra-cold 40,000-strong atom lattice.

Pulsed magnetic forces of different strengths were then applied to the lattice, causing each atom along the string to tilt its spin in a wavelike manner. The researchers were able to image those wave patterns on a detector, and watched how the atoms gradually evolved from dynamic behavior to equilibrium, depending on the nature of the magnetic field that they were exposed to.

The process, explained Ketterle, is similar to plucking a guitar's strings: playing the strings brings them out of their equilibrium condition, and allows the scientists to watch what happens before they return to their original state.

"What we're doing here is, we're kind of plucking the string of spins. We're putting in this helix pattern, and then observing how this pattern behaves as a function of time," Ketterle said. "This allows us to see the effect of different magnetic forces between the spins."

Although some of this behavior had been theoretically predicted in the past, detailed observation of patterns of atomic spins had never been observed in detail until now. These patterns, however, were found to fit an existing mathematical model called the Heisenberg model, which is commonly used to predict magnetic behavior.

Together with a team of scientists at Harvard, MIT's researchers were able to calculate the spin's dynamics. The results, therefore, aren't only useful to advance the knowledge of magnetism at a fundamental level; but they could also be used as a blueprint for a device that could predict the properties and behaviors of new materials at the quantum level.

"With all of the current excitement about the promise of quantum information science to solve practical problems in the future, it is great to see work like this actually coming to fruition today," said John Gillaspy, program officer in the Division of Physics at the National Science Foundation, and a funder of the research.

A higher-level understanding of quantum particles could also lead to the design of new technologies, such as spintronic devices, according to the researchers. Unlike electronics, which leverage the flow of electrons, spintronics tap the spin of quantum particles to transmit, process and store information. They hold promise, therefore, for quantum computing, where the spin of particles would constitute a bit of quantum information.

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Quantum computing: Strings of ultracold atoms reveal the surprising behavior of quantum particles - ZDNet

Anyon Systems's Quantum Computer

Anyon System's superconducting quantum processor.

MONTREAL, Dec. 15, 2020 (GLOBE NEWSWIRE) -- Anyon Systems Inc. (Anyon), a quantum computing company based in Montreal, Canada, announced today that it is to deliver Canadas first gate-based quantum computer for the Department of National Defenses Defence Research and Development Canada (DRDC). The quantum computer will feature Anyons Yukon generation superconducting quantum processor. Named after Canadas westernmost territory, the quantum computer will enable DRDC researchers to explore quantum computing to solve problems of interest to their mission.

Quantum computing is expected to be a disruptive technology and is of strategic importance to many industries and government agencies. Anyon is focused on delivering large-scale, fault-tolerant quantum computers to a wide group of early adopters including government agencies, high performance computing centers and universities in the near term, said Dr. Alireza Yazdi, founder and CEO of Anyon.

Founded in 2014, Anyon Systems is the first Canadian company manufacturing gate-based quantum computing platform for universal quantum computation. Anyon Systems delivers turnkey gate-based quantum computers. The company is headquartered in Montreal, Quebec.

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Anyon Systems to Deliver a Quantum Computer to the Canadian Department of National Defense - GlobeNewswire

This week in future tech, a Chinese quantum computer can reportedly solve a problem in 200 seconds, compared to the 2.5bn years a supercomputer needs.

A quantum computer developed at the University of Science and Technology in Hefei, China, has caught the worlds attention due to what appears to be a performance vastly exceeding others that exist today.

According to findings in published in Scienceand reported by Nature, researchers claim they demonstrated a quantum advantage, using laser beams to perform a computation that is not mathematically possible using traditional binary computers.

We have shown that we can use photons, the fundamental unit of light, to demonstrate quantum computational power well beyond the classical counterpart, said researcher Jian-Wei Pan.

Tasked with solving the so-called boson sampling problem, the researchers found solutions in as little as 200 seconds. By comparison, it could take Chinas TaihuLight supercomputer about 2.5bn years to do the same.

However, Christian Weedbrook, chief executive of quantum-computing start-up Xanadu, said that unlike Googles Sycamore quantum computer announced last year, the Chinese quantum computer is not programmable. This means that, so far, it cannot be used for solving practical problems.

Scientists from the University of Washington have unveiled a drone that smells, using the power of a moth. Writing in IOP Bioinspiration and Biomimetics, they revealed their Smellicopter design.

The autonomous drone uses a live antenna from a moth to navigate toward smells, while also having the ability to sense and avoid obstacles. A moth uses its antennae to sense chemicals in its environment and navigate toward sources of food or potential mates.

In this case, the researchers used antennae from the Manduca sexta hawkmoth for Smellicopter. The moths were placed in a fridge to anaesthetise them before removing their antennae. Once separated, the live moth antennae could stay chemically active for four hours.

By adding tiny wires into either end of the antenna, the researchers were able to connect it to an electrical circuit and measure the average signal from all of the cells in the antenna. They said Smellicopter could be used to detect things such as gas leaks, explosives and disaster survivors.

From a robotics perspective, this is genius, said Sawyer Fuller of the University of Washington. The classic approach in robotics is to add more sensors, and maybe build a fancy algorithm or use machine learning to estimate wind direction. It turns out, all you need is to add a fin.

German air taxi firm Volocopter said it plans to make regular services a reality in Singapore within the next three years. In October 2019, Volocopter completed the its first air taxi demonstration flight over the Marina Bay area of Singapore and the company is now looking to obtain the necessary regulatory approvals for regular service, including those from Civil Aviation Authority of Singapore and the European Union Aviation Safety.

The first route is expected to be a touristic route over the southern waters, offering views of the Marina Bay skyline, and future routes may include cross-border flights. The company is expected to hire over 200 full-time employees in Singapore to manage a network of routes by 2026.

The citys research institutes conducting R&D play an integral part in this, said Florian Reuter, CEO of Volocopter. Topics like route validation for autonomous operations, material science and research regarding battery technology are very important for our long-term business success.

The Global Mobile Suppliers Association (GSA) has reported that the number of announced 5G devices has surpassed 500 for the first time. By the end of November this year, there were 519 announced 5G devices, of which 303 were commercially available.

In the last three months, the number of announced 5G devices has grown by 29.4pc, while there has been a 59.5pc increase in the number of commercially available 5G devices over the same period.

This year weve seen more and more symbolically important milestones being passed over 500 announced 5G devices, more than 100 vendors, over 250 different phones, and 100 fixed wireless access CPE devices, said Joe Barrett, president of the GSA.

And it doesnt stop there; we expect more 5G devices to become commercially available, surpassing the 330 mark before the year is out. The device vendor community has stepped up and delivered in the face of unprecedented challenges. As an industry, we can be excited about the opportunities 2021 will bring.

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Chinese quantum computer may be the most powerful ever seen - Siliconrepublic.com

Electrons inhabit a strange and topsy-turvy world. These infinitesimally small particles have never ceased to amaze and mystify despite the more than a century that scientists have studied them. Now, in an even more amazing twist, physicists have discovered that, under certain conditions, interacting electrons can create what are called topological quantum states. This finding, which was recently published in the journal Nature,holds great potential for revolutionizing electrical engineering, materials science and especially computer science.

Topological states of matter are particularly intriguing classes of quantum phenomena. Their study combines quantum physics with topology, which is the branch of theoretical mathematics that studies geometric properties that can be deformed but not intrinsically changed. Topological quantum states first came to the publics attention in 2016 when three scientists Princetons Duncan Haldane, who is Princetons Thomas D. Jones Professor of Mathematical Physics and Sherman Fairchild University Professor of Physics, together with David Thouless and Michael Kosterlitz were awarded the Nobel Prize for their work in uncovering the role of topology in electronic materials.

A Princeton-led team of physicists have discovered that, under certain conditions, interacting electrons can create what are called topological quantum states, which,has implications for many technological fields of study, especially information technology. To get the desired quantum effect, the researchersplaced two sheets of graphene on top of each other with the top layer twisted at the "magic" angle of 1.1 degrees, whichcreates a moir pattern. This diagram shows a scanning tunneling microscopeimaging the magic-angle twisted bilayer graphene.

Image courtesy of Kevin Nuckolls

The last decade has seen quite a lot of excitement about new topological quantum states of electrons, said Ali Yazdani, the Class of 1909 Professor of Physics at Princeton and the senior author of the study. Most of what we have uncovered in the last decade has been focused on how electrons get these topological properties, without thinking about them interacting with one another.

But by using a material known as magic-angle twisted bilayer graphene, Yazdani and his team were able to explore how interacting electrons can give rise to surprising phases of matter.

The remarkable properties of graphene were discovered two years ago when Pablo Jarillo-Herrero and his team at the Massachusetts Institute of Technology (MIT) used it to induce superconductivity a state in which electrons flow freely without any resistance. The discovery was immediately recognized as a new material platform for exploring unusual quantum phenomena.

Yazdani and his fellow researchers were intrigued by this discovery and set out to further explore the intricacies of superconductivity.

But what they discovered led them down a different and untrodden path.

This was a wonderful detour that came out of nowhere, said Kevin Nuckolls, the lead author of the paper and a graduate student in physics. It was totally unexpected, and something we noticed that was going to be important.

Following the example of Jarillo-Herrero and his team, Yazdani, Nuckolls and the other researchers focused their investigation on twisted bilayer graphene.

Its really a miracle material, Nuckolls said. Its a two-dimensional lattice of carbon atoms thats a great electrical conductor and is one of the strongest crystals known.

Graphene is produced in a deceptively simple but painstaking manner: a bulk crystal of graphite, the same pure graphite in pencils, is exfoliated using sticky tape to remove the top layers until finally reaching a single-atom-thin layer of carbon, with atoms arranged in a flat honeycomb lattice pattern.

To get the desired quantum effect, the Princeton researchers, following the work of Jarillo-Herrero, placed two sheets of graphene on top of each other with the top layer angled slightly. This twisting creates a moir pattern, which resembles and is named after a common French textile design. The important point, however, is the angle at which the top layer of graphene is positioned: precisely 1.1 degrees, the magic angle that produces the quantum effect.

Its such a weird glitch in nature, Nuckolls said, that it is exactly this one angle that needs to be achieved. Angling the top layer of graphene at 1.2 degrees, for example, produces no effect.

The researchers generated extremely low temperatures and created a slight magnetic field. They then used a machine called a scanning tunneling microscope, which relies on a technique called quantum tunneling rather than light to view the atomic and subatomic world. They directed the microscopes conductive metal tip on the surface of the magic-angle twisted graphene and were able to detect the energy levels of the electrons.

They found that the magic-angle graphene changed how electrons moved on the graphene sheet. It creates a condition which forces the electrons to be at the same energy, said Yazdani. We call this a flat band.

When electrons have the same energy are in a flat band material they interact with each other very strongly. This interplay can make electrons do many exotic things, Yazdani said.

One of these exotic things, the researchers discovered, was the creation of unexpected and spontaneous topological states.

This twisting of the graphene creates the right conditions to create a very strong interaction between electrons, Yazdani explained. And this interaction unexpectedly favors electrons to organize themselves into a series of topological quantum states.

The researchers discovered that the interaction between electrons creates topological insulators:unique devices that whose interiors do not conduct electricity but whose edges allow the continuous and unimpeded movement ofelectrons. This diagram depicts thedifferent insulating states of the magic-angle graphene, each characterized by an integer called its Chern number, which distinguishes between different topological phases.

Image courtesy of Kevin Nuckolls

Specifically, they discovered that the interaction between electrons creates what are called topological insulators. These are unique devices that act as insulators in their interiors, which means that the electrons inside are not free to move around and therefore do not conduct electricity. However, the electrons on the edges are free to move around, meaning they are conductive. Moreover, because of the special properties of topology, the electrons flowing along the edges are not hampered by any defects or deformations. They flow continuously and effectively circumvent the constraints such as minute imperfections in a materials surface that typically impede the movement of electrons.

During the course of the work, Yazdanis experimental group teamed up two other Princetonians Andrei Bernevig, professor of physics, and Biao Lian, assistant professor of physics to understand the underlying physical mechanism for their findings.

Our theory shows that two important ingredients interactions and topology which in nature mostly appear decoupled from each other, combine in this system, Bernevig said. This coupling creates the topological insulator states that were observed experimentally.

Although the field of quantum topology is relatively new, itcouldtransform computer science. People talk a lot about its relevance to quantum computing, where you can use these topological quantum states to make better types of quantum bits, Yazdani said. The motivation for what were trying to do is to understand how quantum information can be encoded inside a topological phase. Research in this area is producing exciting new science and can have potential impact in advancing quantum information technologies.

Yazdani and his team will continue their research into understanding how the interactions of electrons give rise to different topological states.

The interplay between the topology and superconductivity in this material system is quite fascinating and is something we will try to understand next, Yazdani said.

In addition to Yazdani, Nuckolls, Bernevig and Lian, contributors to the study included co-first authors Myungchul Oh and Dillon Wong, postdoctoral research associates, as well as Kenji Watanabe and Takashi Taniguchi of the National Institute for Material Science in Japan.

Strongly Correlated Chern Insulators in Magic-Angle Twisted Bilayer Graphene, by Kevin P. Nuckolls, Myungchul Oh, Dillon Wong, Biao Lian, Kenji Watanabe, Takashi Taniguchi, B. Andrei Bernevig and Ali Yazdani, was published Dec. 14 in the journal Nature (DOI:10.1038/s41586-020-3028-8). This work was primarily supported by the Gordon and Betty Moore Foundations EPiQS initiative (GBMF4530, GBMF9469) and the Department of Energy (DE-FG02-07ER46419 and DE-SC0016239). Other support for the experimental work was provided by the National Science Foundation (Materials Research Science and Engineering Centers through the Princeton Center for Complex Materials (NSF-DMR-1420541, NSF-DMR-1904442) and EAGER DMR-1643312), ExxonMobil through the Andlinger Center for Energy and the Environment at Princeton, the Princeton Catalysis Initiative, the Elemental Strategy Initiative conducted by Japans Ministry of Education, Culture, Sports, Science and Technology (JPMXP0112101001, JSPS KAKENHI grant JP20H0035, and CREST JPMJCR15F3), the Princeton Center for Theoretical Science at Princeton University, the Simons Foundation, the Packard Foundation, the Schmidt Fund for Innovative Research, BSF Israel US foundation (2018226), the Office of Naval Research (N00014-20-1-2303) and the Princeton Global Network Funds.

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'Magic' angle graphene and the creation of unexpected topological quantum states - Princeton University

There are three kinds of light, says Carmen Palacios-Berraquero, the CEO and co-founder of Nu Quantum a quantum photonics company based in Cambridge. Chaotic light is the stuff we encounter on a daily basis street lamps and light bulbs. Coherent light covers things with structure, like lasers which were first built in 1960, and have had a revolutionary impact on everything from surgery to home entertainment.

Palacios-Berraquero hopes that the third category, single-photon sources, could have an equally transformative effect. At Nu Quantum, she is working on technologies that can emit and detect single photons the smallest possible units of light. Photonic quantum technologies are about manipulating information processing, communicating and securing information encoded in single particles of light, she says. That allows you to do different things more powerful calculations, or better security.

Single photons cant be eavesdropped on or tampered with without the sender and recipient finding out. And they can be used to take advantage of quantum properties such as entanglement to enable more powerful computing and cryptography.

But building them is a really difficult technical challenge. There are only a handful of companies around the world no more than six, says Palacios-Berraquero that can reliably and controllably either emit or detect single photons. Nu Quantum is hoping to do both.

The company was spun out of research at Cambridge Universitys Cavendish Lab. Palacios-Berraquero had studied physics as an undergraduate and been drawn to the beauty of the interactions between light and matter. During her PhD, she developed a new technique for producing single-photon emitters and adapted it to work on ultra-thin crystals of hexagonal boron nitride a tiny defect in the crystal traps an electron, which then gives off photons.

She began the process of patenting it, and feeling disillusioned with academia started exploring potential commercialisation opportunities for her single-photon emitters. At around the same time, she was introduced to Matthew Applegate, another Cavendish researcher who had developed a way of detecting single photons. What was already a solid business idea with some investment became a portfolio approach, in which I had invented a single photon source, and Matthew had invented a single-photon detector, she says.

Nu Quantum has won 3.6m in government grants, and has just started working with BT, Airbus and other partners to test potential uses for its components. In September 2020 it closed a 2.1m seed round which will help fuel rapid growth and a move into a state of the art photonics lab in Cambridge.

The first product set for launch in 2022 will be a quantum random number generator, which will take advantage of the quantum nature of single photons to generate truly random numbers, based on an algorithm developed by Applegate, Nu Quantum co-founder and CTO. There are potential applications for video games, gambling, cloud security and communication where random numbers are used to generate the keys that scramble encrypted messages. The technology could also play a role in distributing those keys Nu Quantum is working with BT on a pilot that will generate, emit and detect quantum keys and make telecoms more secure. We are aspiring to be much more than the sum of the parts, says Palacios-Berraquero. The aspiration is something much bigger.

Amit Katwala is WIRED's culture editor. He tweets from @amitkatwala

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BEIJING--(BUSINESS WIRE)--The preliminary round of the 2020-2021 ASC Student Supercomputer Challenge (ASC20-21) officially kicked off on November 16, 2020. More than 300 university teams from five continents registered to participate in this competition. Over the next two months, they will be challenged in several cutting-edge applications of Supercomputing and AI. The 20 teams that eventually make out of the preliminaries will participate in the finals from May 8 to 12, 2021 at Southern University of Science and Technology in Shenzhen, China. During the finals, they will compete for various awards including the Champion, Silver Prize, Highest LINPACK, and e- Prize.

Among the registered participants for ASC20-21 are three prior champion teams: the SC19/SC20 champion team of Tsinghua University, the ISC20 champion team of University of Science and Technology of China, and the ASC19 champion of National Tsing Hua University. Other power competitors include teams from University of Washington (USA), University of Warsaw (Poland), Ural Federal University (Russia), Monash University (Australia), EAFIT University (Columbia) and so much more.

For the tasks of this preliminary round of merged ASC20 and ASC21, the organizing committee has retained the quantum computing simulation and language exam tasks from the ASC20, and added a new fascinating, cutting-edge task in astronomy -- searching for pulsars.

Pulsars are fast-spinning neutron stars, and remnants of collapsed super stars. Pulsars feature a high density and strong magnetic field. By observing and studying the extreme physic of pulsars, the scientists can delve into the mysterious space around black holes and detect the gravitational waves triggered from the intense merge of super massive black holes in distant galaxies. Because of the unique nature of pulsars, the Nobel Prize in physics has been awarded twice for pulsar-related discoveries. Using radio telescopes over the previous decades, astronomers have discovered nearly 3,000 pulsars with 700 being discovered by PRESTO, the open-source pulsar search and analysis software. In ASC20-21, the participants are asked to use PRESTO from its official website, and the observational data from Five-hundred-meter Aperture Spherical radio Telescope (FAST), the worlds largest single-dish radio telescope located in Guizhou, China, operated by National Astronomical Observatories, Chinese Academy of Sciences. Participating teams should achieve the applications maximum parallel acceleration, while searching for a pulsar in the FAST observational data loaded in the computer cluster they build. Practically the teams will need to understand the pulsar search process, complete the search task, analyze the code, and optimize the PRESTO application execution, by minimizing the computing time and resources.

The quantum computing simulation task will require each participating team to use the QuEST (Quantum Exact Simulation Toolkit) running on computer cluster to simulate 30 qubits in two cases: quantum random circuits (random.c), and quantum fast Fourier transform circuits (GHZ_QFT.c). Quantum simulations provides a reliable platform for studying of quantum algorithms, which are particularly important because quantum computers are not practically available yet in the industry.

The Language Exam task will require all participating teams to train AI models on an English Cloze Test dataset, striving to achieve the highest "test scores". The dataset covers multiple levels of English language tests used in China.

This years ASC training camp will be held on November 30 to help the participating teams from all around the world prepare for the competition. HPC and AI experts from Chinese Academy of Sciences, Peng Cheng Laboratory, State Key Laboratory of High-end Server & Storage Technology will introduce in details the competition rules, computer cluster build and optimization, and provide guidance.

About ASC

The ASC Student Supercomputer Challenge is the worlds largest student supercomputer competition, sponsored and organized by Asia Supercomputer Community in China and supported by Asian, European, and American experts and institutions. The main objectives of ASC are to encourage exchange and training of young supercomputing talent from different countries, improve supercomputing applications and R&D capacity, boost the development of supercomputing, and promote technical and industrial innovation. The first ASC Student Supercomputer Challenge was held in 2012 and since has attracted nearly 10,000 undergraduates from all over the world. Learn more ASC at https://www.asc-events.org/.

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ASC20-21 Student Supercomputer Challenge Kickoff: Quantum Computing Simulations, AI Language Exam and Pulsar Searching with FAST - Business Wire

Jordi Tura

November 23, 2020• Physics 13, 183

Classical computers can efficiently simulate the behavior of quantum computers if the quantum computer is imperfect enough.

With a few quantum bits, an ideal quantum computer can process vast amounts of information in a coordinated way, making it significantly more powerful than a classical counterpart. This predicted power increase will be great for users but is bad for physicists trying to simulate on a classical computer how an ideal quantum computer will behave. Now, a trio of researchers has shown that they can substantially reduce the resources needed to do these simulations if the quantum computer is imperfect [1]. The arXiv version of the trios paper is one of the most Scited papers of 2020 and the result generated quite a stir when it first appeared back in FebruaryI overheard it being enthusiastically discussed at the Quantum Optics Conference in Obergurgl, Austria, at the end of that month, back when we could still attend conferences in person.

In 2019, Google claimed to have achieved the quantum computing milestone known as quantum advantage, publishing results showing that their quantum computer Sycamore had performed a calculation that was essentially impossible for a classical one [2]. More specifically, Google claimed that they had completed a three-minute quantum computationwhich involved generating random numbers with Sycamores 53 qubitsthat would take thousands of years on a state-of-the-art classical supercomputer, such as IBMs Summit. IBM quickly countered the claim, arguing that more efficient memory storage would reduce the task time on a classical computer to a couple of days [3]. The claims and counterclaims sparked an industry clash and an intense debate among supporters in the two camps.

Resolving the disparity between these estimates is one of the goals of the new work by Yiqing Zhou, of the University of Illinois at UrbanaChampaign, and her two colleagues [1]. In their study, they focused on algorithms for classically replicating imperfect quantum computers, which are also known as NISQ (noisy intermediate-scale quantum) devices [4]. Todays state-of-the-art quantum computersincluding Sycamoreare NISQ devices. The algorithms the team used are based on so-called tensor network methods, specifically matrix product states (MPS), which are good for simulating noise and so are naturally suited for studying NISQ devices. MPS methods approximate low-entangled quantum states with simpler structures, so they provide a data-compression-like protocol that can make it less computationally expensive to classically simulate imperfect quantum computers (see Viewpoint: Pushing Tensor Networks to the Limit).

Zhou and colleagues first consider a random 1D quantum circuit made of neighboring, interleaved two-qubit gates and single-qubit random unitary operations. The two-qubit gates are either Controlled-NOT gates or Controlled-Z (CZ) gates, which create entanglement. They ran their algorithm for NISQ circuits containing different numbers of qubits, N, and different depths, Da parameter that relates to the number of gates the circuit executes (Fig. 1). They also varied a parameter in the MPS algorithm. is the so-called bond dimension of the MPS and essentially controls how well the MPS capture entanglement between qubits.

The trio demonstrate that they can exactly simulate any imperfect quantum circuit if D and N are small enough and is set to a value within reach of a classical computer. They can do that because shallow quantum circuits can only create a small amount of entanglement, which is fully captured by a moderate . However, as D increases, the team finds that cannot capture all the entanglement. That means that they cannot exactly simulate the system, and errors start to accumulate. The team describes this mismatch between the quantum circuit and their classical simulations using a parameter that they call the two-qubit gate fidelity fn. They find that the fidelity of their simulations slowly drops, bottoming out at an asymptotic value f as D increases. This qualitative behavior persists for different values of N and . Also, while their algorithm does not explicitly account for all the error and decoherence mechanisms in real quantum computers, they show that it does produce quantum states of the same quality (perfection) as the experimental ones.

In light of Googles quantum advantage claims, Zhou and colleagues also apply their algorithm to 2D quantum systemsSycamore is built on a 2D chip. MPS are specifically designed for use in 1D systems, but the team uses well-known techniques to extend their algorithm to small 2D ones. They use their algorithm to simulate an N=54, D=20 circuit, roughly matching the parameters of Sycamore (Sycamore has 54 qubits but one is unusable because of a defect). They replace Googles more entangling iSWAP gates with less entangling CZ gates, which allow them to classically simulate the system up to the same fidelity as reported in Ref. [2] with a single laptop. The simulation cost should increase quadratically for iSWAP-gate circuits, and although the team proposes a method for performing such simulations, they have not yet carried them out because of the large computational cost it entails.

How do these results relate to the quantum advantage claims by Google? As they stand, they do not weaken or refute claimswith just a few more qubits, and an increase in D or f, the next generation of NISQ devices will certainly be much harder to simulate. The results also indicate that the teams algorithm only works if the quantum computer is sufficiently imperfectif it is almost perfect, their algorithm provides no speed up advantage. Finally, the results provide numerical insight into the values of N, D, f, and for which random quantum circuits are confined to a tiny corner of the exponentially large Hilbert space. These values give insight into how to quantify the capabilities of a quantum computer to generate entanglement as a function of f, for example.

So, whats next? One natural question is, Can the approach here be transferred to efficiently simulate other aspects of quantum computing, such as quantum error correction? The circuits the trio considered are essentially random, whereas quantum error correction circuits are more ordered by design [5]. That means that updates to the new algorithm are needed to study such systems. Despite this limitation, the future looks promising for the efficient simulation of imperfect quantum devices [6, 7].

Jordi Tura is an assistant professor at the Lorentz Institute of the University of Leiden, Netherlands. He also leads the institutes Applied Quantum Algorithms group. Tura obtained his B.Sc. degrees in mathematics and telecommunications and his M.Sc. in applied mathematics from the Polytechnic University of Catalonia, Spain. His Ph.D. was awarded by the Institute of Photonic Sciences, Spain. During his postdoctoral stay at the Max Planck Institute of Quantum Optics in Germany, Tura started working in the field of quantum information processing for near-term quantum devices.

A nanopatterned magnetic structure features an unprecedently strong coupling between lattice vibrations and quantized spin waves, which could lead to novel ways of manipulating quantum information. Read More

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Imperfections Lower the Simulation Cost of Quantum Computers - Physics