Category Archives: Quantum Computing

In our everyday classical computers, 0s and 1s are associated with switches and electronic circuits turning on and off as part of the computer using a binary number system to calculate possibilities and perform operations. For example, when a computer mouse moves, a sensor tells the computer that an electrical signal has been converted into a binary value or number. Further, this number represents a location that is then represented on the computer screen all of which is embodied by the byte that is the building block of current computers. The sensor message to the computer is also saved to memory. Some calculations have too many possibilities for even a traditional computer to calculate like simulating the weather or calculating scrambled combinations of prime numbers.Quantum is the state of things being unknown at the subatomic level until they can be observed and moves from the byte to the qubit. In a quantum computer, it is said that the values assigned to 0 and 1 can occur at the same time. The reason this impossibility is possible is because of quantums subatomic level where protons and electrons are acting in a wild way beyond the rules of nature as we tend to think of them. Picture The Avengers superhero Antman shrinking into the quantum zone where time did not even move in a linear fashion.In computer terms, once the values of 0 and 1 can happen at the same time, it allows the quantum computer to consider trillions of possibilities or more in the same instant, dwarfing the number of calculations that our traditional computers, stuck in binary counting, can do.This process is called superposition. Superposition ends once a specialized particle, or qubit, slows/is observable, thereby emerging from its quantum state. We stick the qubit in an artificial space vacuum so that it does not get observed or interfered with and remains dynamic. Pictures of quantum computers often show tubes the size of a household refrigerator. But most of the tubing is not the central computer processor as much as the process used to maintain the qubits at the absolute zero quantum state.Since around 1977, RSA has been among the most widely used systems for secure data transmission underlying the Internet, serving as the backbone of the NYSE, most large institutions and most individual online users. What is stopping an average person from hacking anyones elses website is that RSA is easy to build, and being based on two pseudo-random prime numbers, hard to burst for traditional computers limited binary system calculation capacity.

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Quantum Computing 101 -What it is, how is it different and why it matters - The Jerusalem Post

NTT Research has announced a collaboration with Caltech to develop the worlds fastest Coherent Ising Machine (CIM). This relates to a quantum-oriented computing approach that uses special-purpose processors to solve extremely complex combinatorial optimization problems. CIMs are advanced devices that constitute a promising approach to solving optimization problems by mapping them to ground state searches. The primary application of the computing method is drug discovery. Developing new drugs is of importance, including the current fight against COVID-19. Drug discovery is a commonly cited combinatorial optimization problem. The search for effective drugs involves an enormous number of potential matches between medically appropriate molecules and target proteins that are responsible for a specific disease. Conventional computers are used to replicate chemical interactions in the medical space and other areas of life and chemical sciences. To really move forwards, quantum technology is required to take developments beyond trial and error to rapidly tackle the sheer volume of total possible combinations.Other applications of the technology include:LogisticsOne classic problem is that of the traveling salesman (a common logic problem) identifying the shortest possible route that visits each of n number of cities, while returning to the city of origin. This problem and its variants appear in contemporary form in logistical challenges, such as daily automotive traffic patterns. The advantage of using a quantum information system is speed. Machine LearningA CIM is also a good match for some types of machine learning, including image and speech recognition. Artificial neural networks learn by iteratively processing examples containing known inputs and results. CIMs can speed up the training and improve upon the accuracy of existing neural networks.The development of the new computer system has been pioneered by Kazuhiro Gomi, CEO of NTT Research, and Dr. Yoshihisa Yamamoto, Director of NTT Researchs Physics & Informatics (PHI) Lab, who is overseeing this research. This is a step forwards in CIM optimization problems by uniting perspectives from statistics, computer science, statistical physics and quantum optics.

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article image Caltech and NTT developing the world's fastest quantum computer - Digital Journal

Quantum computing offers the promise of solutions to previously unsolvable problems, but in order to deliver on this promise, it will be necessary to preserve and manipulate information that is contained in the most delicate of resources: highly entangled quantum states. One thing that makes this so challenging is that quantum devices must be ensconced in an extreme environment in order to preserve quantum information, but signals must be sent to each qubit in order to manipulate this informationrequiring, in essence, an information superhighway into this extreme environment. Both of these problems must, moreover, be solved at a scale far beyond that of present-day quantum device technology.

Microsofts David Reilly, leading a team of Microsoft and University of Sydney researchers, has developed a novel approach to the latter problem. Rather than employing a rack of room-temperature electronics to generate voltage pulses to control qubits in a special-purpose refrigerator whose base temperature is 20 times colder than interstellar space, they invented a control chip, dubbed Gooseberry, that sits next to the quantum device and operates in the extreme conditions prevalent at the base of the fridge. Theyve also developed a general-purpose cryo-compute core that operates at the slightly warmer temperatures comparable to that of interstellar space, which can be achieved by immersion in liquid Helium. This core performs the classical computations needed to determine the instructions that are sent to Gooseberry which, in turn, feeds voltage pulses to the qubits. These novel classical computing technologies solve the I/O nightmares associated with controlling thousands of qubits.

Quantum computing could impact chemistry, cryptography, and many more fields in game-changing ways. The building blocks of quantum computers are not just zeroes and ones but superpositions of zeroes and ones. These foundational units of quantum computation are known as qubits (short for quantum bits). Combining qubits into complex devices and manipulating them can open the door to solutions that would take lifetimes for even the most powerful classical computers.

Despite the unmatched potential computing power of qubits, they have an Achilles heel: great instability. Since quantum states are easily disturbed by the environment, researchers must go to extraordinary lengths to protect them. This involves cooling them nearly down to absolute zero temperature and isolating them from outside disruptions, like electrical noise. Hence, it is necessary to develop a full system, made up of many components, that maintains a regulated, stable environment. But all of this must be accomplished while enabling communication with the qubits. Until now, this has necessitated a birds nest-like tangle of cables, which could work for limited numbers of qubits (and, perhaps, even at an intermediate scale) but not for large-scale quantum computers.

Microsoft Quantum researchers are playing the long game, using a wholistic approach to aim for quantum computers at the larger scale needed for applications with real impact. Aiming for this bigger goal takes time, forethought, and a commitment to looking toward the future. In that context, the challenge of controlling large numbers of qubits looms large, even though quantum computing devices with thousands of qubits are still years in the future.

Enter the team of Microsoft and University of Sydney researchers, headed by Dr. David Reilly, who have developed a cryogenic quantum control platform that uses specialized CMOS circuits to take digital inputs and generate many parallel qubit control signalsallowing scaled-up support for thousands of qubitsa leap ahead from previous technology. The chip powering this platform, called Gooseberry, resolves several issues with I/O in quantum computers by operating at 100 milliKelvin (mK) while dissipating sufficiently low power so that it does not exceed the cooling power of a standard commercially-available research refrigerator at these temperatures. This sidesteps the otherwise insurmountable challenge of running thousands of wires into a fridge.

Their work is detailed in a paper published in Nature this month, called A Cryogenic Interface for Controlling Many Qubits. Theyve also extended this research to create the first-of-its-kind general-purpose cryo-compute core, one step up the quantum stack. This operates at around 2 Kelvin (K), a temperature that can be reached by immersing it in liquid Helium. Although this is still very cold, it is 20 times warmer than the temperatures at which Gooseberry operates and, therefore, 400 times as much cooling power is available. With the luxury of dissipating 400 times as much heat, the core is capable of general-purpose computing. Both visionary pieces of hardware are critical advances toward large-scale quantum computer processes and are the result of years of work.

Both chips help manage communication between different parts of a large-scale quantum computerand between the computer and its user. They are the key elements of a complex nervous system of sorts to send and receive information to and from every qubit, but in a way that maintains a stable cold environment, which is a significant challenge for a large-scale commercial system with tens of thousands of qubits or more. The Microsoft team has navigated many hurdles to accomplish this feat.

Quantum computing devices are often measured by how many qubits they contain. However, all qubits are not created equal, so these qubit counts are often apples-to-oranges comparisons. Microsoft Quantum researchers are pioneering the development of topological qubits, which have a high level of error protection built in at the hardware level. This reduces the overhead needed for software-level error correction and enables meaningful computations to be done with fewer physical qubits.

Although this is one of the unique features of Microsofts approach, it is not the only one. In the quantum stack, qubits make up its base. The quantum plane (at the bottom of Figure 1) is made up of a series of topological qubits (themselves made up of semiconductors, superconductors, and dielectrics), gates, wiring, and other packaging that help to process information from raw qubits. The vital processes of communication occur in the next layer higher in the stack (labeled Quantum-Classical Interface in Figure 1 above). The Gooseberry chip and cryo-compute core work together to bookend this communication. The latter sits at the bottom of the Classical Compute portion of the stack, and Gooseberry is unique relative to other control platforms in that it sits right down with the qubits at the same temperature as the quantum planeable to convert classical instructions from the cryo-compute core into voltage signals sent to the qubits.

Why does it matter where the Gooseberry chip sits? It is partly an issue of heat. When the wires that connect the control chip to the qubits are long (as they would have to be if the control chip were at room temperature), significant heat can be generated inside the fridge. Putting a control chip near the qubits avoids this problem. The tradeoff is that the chip is now near the qubits, and the heat generated by the chip could potentially warm up the qubits. Gooseberry navigates these competing effects by putting the control chip near, but not too near, the qubits. By putting Gooseberry in the refrigerator but thermally isolated from the qubits, heat created by the chip is drawn away from the qubits and into the mixing chamber. (See Figure 2 below).

Placing the chip near the qubits at the quantum plane solves one set of problems with temperature but creates another. To operate a chip where the qubits are, it needs to function at the same temperature as the qubits100 mK. Operating standard bulk CMOS chips at this temperature is challenging, so this chip uses fully-depleted silicon-on-insulator (FDSOI) technology, which optimizes the system for operation at cryogenic temperatures. It has a back-gate bias, with transistors having a fourth terminal that can be used to compensate for changes in temperature. This system of transistors and gates allows qubits to be calibrated individually, and the transistors send individualized voltages to each qubit.

Another advantage of Gooseberry is that the chip is designed in such a way that the electrical gates controlling the qubits are charged from a single voltage source that cycles through the gates in a round-robin fashion, charging as necessary. Previous qubit controllers required one-to-one cables from multiple voltage sources at room temperature or 4K, compromising the ability to operate qubits at large scale. The design pioneered by Dr. Reillys team greatly reduces the heat dissipated by such a controller. The cryogenic temperatures also come into play here to make this possiblethe extreme cold allows capacitors to hold their charge longer. This means that the gates need to be charged less frequently and produce less heat and other disruptions to qubit stability.

The Gooseberry chip is made up of both digital and analog blocks. Coupled digital logic circuits perform communication, waveform memory, and autonomous operation of the chip through a finite-state machine (FSM), and the digital part of the chip also includes a master oscillator (see Figure 3). The chip also uses a Serial Peripheral Interface (SPI) for easy communication higher up the quantum stack. The analog component of the chip is a series of cells, called charge-lock fast-gate (CLFG) cells, that perform two functions. First, the charge-lock function is the process for charging gates, as described above. The voltage stored on each gate is tailored to individual qubits. Information is processed in qubits by changing the voltages on the gate, and that happens in the second function, fast-gating. This creates pulses that physically manipulate the qubits, ultimately directing the processing of information in the qubits.

Low power dissipation is a key challenge when it comes to communicating with qubits efficiently via these pulses. There are three variables that impact power dissipation: voltage level, frequency, and capacitance. The voltage needed in this case is set by the qubit, and the frequency is set by both the qubit and clock rate of the quantum plane. This leaves capacitance as the only variable you can adjust to create low power dissipation when charging gates and sending pulseslow capacitance means low dissipation. The capacitors in this system are tiny, spaced close together, and are very near the quantum plane, so they require as little power as possible to shuffle charge between capacitors to communicate with the qubits.

The researchers tested the Gooseberry chip to see how it would perform by connecting it with a GaAs-based quantum dot (QD) device. Some of the gates in the quantum dot device were connected to a digital-analog converter (DAC) at room temperature to compare these results with standard control approaches. Power leakage from the CLFG cells is measured by a second quantum dot in the device, and measurements of the QD conductance provide a way to monitor the charge-locking process. The temperature of all the components of the chip are measured as the control chip is being powered up, revealing that temperature stays below 100 mK within the necessary range of frequencies or clock speeds (see figure 4). See the paper for more details on the benchmarking process.

Extrapolating these results, the researchers estimated the total system power needed for the Gooseberry control chip as a function of frequency and the number of output gates. These results take into account both the clock speed and temperature needed for topological qubits, and Figure 5 shows that this chip is able to operate within the acceptable limits while communicating with thousands of qubits. This CMOS-based control approach also appears feasible for qubit platforms based on electron spins or gatemons.

The general-purpose cryo-compute core is a recent development that continues the progress made by Gooseberry. This is a general-purpose CPU operating at cryogenic temperatures. At present, the core operates at approximately 2 K, and it handles some triggering manipulation and handling of data. With fewer limitations from temperature, it also deals with branching decision logic, which requires more digital circuit blocks and transistors than Gooseberry has. The core acts as an intermediary between Gooseberry and executable code that can be written by developers, allowing for software-configurable communication between the qubits and the outside world. This technology proves its possible to compile and run many different types of code (written on current tools) in a cryogenic environment, allowing for greater possibilities of what can be accomplished with qubits being controlled by the Gooseberry chip.

Theres no doubt that both Gooseberry and the cryo-compute core represent big steps forward for quantum computing, and having these concepts peer-reviewed and validated by other scientists is another leap ahead. But there are still many more leaps needed by researchers before a meaningful quantum computer can be realized. This is one of the reasons Microsoft has chosen to focus on the long game. While it might be nice to ramp up one aspect of quantum computerssuch as the number of qubitsthere are many concepts to be developed beyond the fundamental building blocks of quantum computers, and researchers at Microsoft Quantum and the University of Sydney arent stopping with these results.

Projects like the Gooseberry chip and cryo-compute core take years to develop, but these researchers arent waiting to put new quantum projects into motion. The idea is to keep scaffolding prior work with new ideas so that all of the components necessary for quantum computing at large scale will be in place, enabling Microsoft to deliver solutions to many of the worlds most challenging problems.

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Full stack ahead: Pioneering quantum hardware allows for controlling up to thousands of qubits at cryogenic temperatures - Microsoft

For most of us, the refrigerator is where we keep our dairy, meat and vegetables. For Ilana Wisby, CEO at Oxford Quantum Circuits (OQC), refrigeration means something else entirely.

Her company, operator of the UKs only commercially available quantum computer, has recently announced a new partnership with Oxford Instruments Nanoscience, a manufacturer of ultra-low temperature refrigerators.

As per the agreement, OQC will be the first to deploy the new Proteox cryo-refrigerator, which reaches temperatures as low as 5-8 millikelvin (circa -273 C/-460 F), significantly colder than outer space.

According to Wisby, the arrival of powerful new refrigerators will allow organizations like hers to take quantum computing to new heights, by improving the "quality" of superconducting quantum bits (qubits).

Quantum effects only happen in really low-energy environments, and energy is temperature. Ultimately, we need to be at incredibly low temperatures, because were working at single-digit electron levels, she explained

A qubit is an electronic circuit made from aluminum, built with a piece of silicon, which we cool down until it becomes superconducting and then further until single electron effects are happening.

The colder the system the less noise and mess there is, she told TechRadar Pro, because all the other junk is frozen out. With the Proteox, then, OQC hopes to be able to scale up the architecture of its quantum machine in a significant way.

The meaning of quantum computing, let alone its significance, can be difficult to grasp without a background in physics. At the end of our conversation, Wisby herself told us she had found it difficult to balance scientific integrity with the need to communicate the concepts.

But, in short, quantum computers approach problem solving in an entirely different way to classical machines, making use of certain symmetries to speed up processing and allow for far greater scale.

Quantum computers exploit a number of principles that define how the world works at an atomic level. Superposition, for example, is a principle whereby something can be in two positions at once, like a coin thats both a head and a tail, said Wisby.

Ultimately, that can happen with information as well. We are therefore no longer limited to just ones and zeros, but can have many versions of numbers in between, superimposed.

Instead of running calculation after calculation in a linear fashion, quantum machines can run them in parallel, optimizing for many more variables - and doing so extremely quickly.

Advances in the field, which is really still only in its nascent stages, are expected to have a major impact on areas such as drug discovery, logistics, finance, cybersecurity and almost any other market that needs to process massive volumes of information.

Quantum computers in operation today, however, can not yet consistently outperform classical supercomputers. There are also very few quantum computing resources available for businesses to utilize; OQC has only a small pool of rivals worldwide in this regard.

The most famous milestone held aloft as a marker of progress is that of quantum supremacy, the point at which quantum computers are able to solve problems that would take classical machines an infeasible amount of time.

In October 2019, Google announced it was the first company to reach this landmark, performing a task with its Sycamore prototype in 200 seconds that would take another machine 10,000 years.

But the claim was very publicly contested by IBM, which dialled up its Summit supercomputer (previously the worlds fastest) to prove it was capable of processing the same workload in roughly two and a half days.

Although the quantum supremacy landmark remains disputed, and quantum computers have not yet been responsible for any major scientific discoveries, Wisby is bullish about the industrys near-term prospects.

Were not there yet, but we will be very soon. Were at a tipping point after which we should start to see discoveries and applications that were fundamentally impossible before, realistically in the next three years.

In pharma, that might mean understanding specific molecules, even better understanding water. We hope to see customers working on new drugs that have been enabled by a quantum computer, at least partially, in the not too distant future.

The challenge facing organizations working to push quantum computing to the next level is balancing quality, scale and control. Currently, as quantum systems are scaled and an appropriate level of control asserted, the quality decreases and information is lost.

Achieving all these things in parallel is whats going to unlock a quantum-enabled future, says Wisby.

There is work to be done, in other words, before quantum fulfils its potential. But steps forward in the ability to fabricate superconducting devices at scale and developments in areas such as refrigeration are setting the stage.

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A fridge thats colder than outer space could take quantum computing to new heights - TechRadar

Deploying the more sustainable and resilient electric grid of the future requiresa sophisticatedusage of data. This begins with sensorsand measurement infrastructurecollecting a wide range of grid-relevant data, butalsoincludes various forms of analytics to usethedata tosolvea wide range ofgrid problems.Many advanced analytics methodsalreadyarebeing used,includingartificial intelligence and machine learning.Now,forward-looking electric utilities are exploringthe next step in enhancing these analytics,by understandinghow emerging computing technologies can be leveraged to provide higher levels of service. Among the mostcompellingexamples of this is the potential use of quantum computing for grid purposes.

This rapid evolution is happening in part toaccommodate additional distributed energy resources (DERs)on the grid, including the solarphotovoltaic (PV)and energy storage that helptoreduce emissions bylimitingthe need for fossil-fuel power plants. High levels of DER penetration not only necessitate reform in traditional grid planning and operation, but also facilitate unprecedented grid modernization to accommodate new types of loads (for example,electric vehicles)andbidirectional power transfer.

Electric utilities like Commonwealth Edison(ComEd)are in a unique position to develop and deploy grid-optimizing technologies to meet the demands of evolving systems and build a scalable model for the grid of the future.Serving over 4 million customers in northern Illinois and Chicago,Illinois, U.S.,ComEd ispartnering with leading academic institutionsincluding the University of Denver and the University of Chicago andleveraging its position as one of the largest electric utilities in theU.S.to explorequantumcomputing applications forgrid purposes.

What Is Quantum Computing?

The major difference between classical and quantum computers is in the way they process information.Whereas classical computing bits are either 0 or 1, quantum bits (qubits) can be both 0 and 1 at the same timethrougha unique quantum property called superposition. For example, an electron can be used as a qubit because it can simultaneously occupy its ground state (0) and its excited state (1).

Moreover, this superposition phenomenon scales exponentially. For example, two qubitscanoccupy four statessimultaneously: 00, 01, 10 and 11. More generally, N qubits can represent an exponential number of states (2N) at once, enabling a quantum computer to process all these states rapidly.This exponential advantageis the salient feature of quantum computers, enabling faster calculations in specific applications,such as factoringlargenumbers and searching datasets.

ComEd cohosted a workshop that brought together a dozen leaders in quantum computing and power systems to help determine the future applications of quantum computing for the grid.

A superconducting quantum computer from Professor David Schuster's laboratory at UChicago that can help drive the field forward. Credit: Yongshan Ding.

The data from these advanced sensors can be leveraged from quantum computing to provide higher levels of grid resiliency and support DER integration.

QuantumComputingApplications

To identify potential applications forquantumcomputing in the grid of the future,ComEdcohosted a workshop on Feb.27, 2020,with researchers from the University of Chicago,the University of Denverand Argonne NationalLaboratory. The purpose of theworkshop was to explore the potential benefitsquantumcomputingcouldbring to power systemsand collaborate on developing technologies that couldbe demonstrated to provide this value.

Recognizing these two fields historicallyhavenot been in close contact, the workshop began with two tutorial sessions, one forpowersystems and another forquantumcomputing, to provide backgroundonthe stateoftheart of the respective fields as well as the emerging challengesof each. Following the tutorial sessions, a technical discussionincludedbrainstormingpotential applications of existingquantumcomputing algorithms on large-scale power system problems requiring heavy computational resources.Followingare severalpotential power systemsapplicationsofquantum computingin deployingthe grid of the future.

Unit Commitment

Optimal system schedulingin particular,unit commitment(UC)is one of the most computationally intensive problems in power systems. UCis a nonlinear, nonconvexoptimizationproblem with a multitude of binary and continuous variables. There have been extensive and continuous efforts to improve the solutiontothis problem, from both optimality and execution time points of view. Recent advances in power systems, such astheintegration of variable renewable energy resources andagrowing number of customer-ownedgeneration units, add another level of difficulty to this problem and make it even harder to solve.

Quantum optimization may solve the UC problem fasterthancurrent models used in classical computers. Thequantumapproximateoptimizationalgorithm(QAOA),analgorithm for quantum computers designed to solve complex combinatorial problems,may be wellsuited for the UC problem. While QAOA was designed for discrete combinatorial optimization, several interesting research directions could relaxthe algorithmto be compatible with mixed-integer programming tasksused inUC.

Contingency Analysis

Another potentialapplicationinvolvescontingency analysis. Traditional power system operators tend to assess system reliability byanalyzingN-1 contingency, to ensure thesystemcan maintainadequatepower flowduringone-at-a-time equipment outages. Systemoperators usually run this study after obtaining a state estimator solution todetermine whethersystem status is still within the acceptable operating condition.

Advanced computing capabilities like quantum computing can support the integration of clean energy generation like this deployment as part of the Bronzeville Community Microgrid.

The high-riskN-k contingencyhas beenintroduced toobtainbetter situational awareness. However, the combinatorial explosion in potential scenarios greatly challenges the existing computing power. Quantum computers could helptoaddress N-k scenarios by enabling access to an exponentially expanded state space.

State Estimation

Quantumcomputingalsohas the potential to enable large-scale distribution systemhybridstate estimation with phasor measurement units (PMUs)and advanced meteringinfrastructure (AMI).Utilitiesalreadyhave deployedthousandsofPMUsand millionsofsmart metersacross the grid that provide data toacentral management system. PMUsprovide time-synchronized three-phase voltage and current measurements at speeds up to 60 samples per second, which allow for linear state estimation at similar speeds.AMI provides voltage and energy measurementsat customer siteswith differenttimeresolutions.

As thesystem becomes more complex, the computationrequiredto usemany measurements estimating the states of apracticalnetwork increasesaccordingly. QAOA provides a promising path for state estimation withPMUsor hybrid state estimation with both PMUsand AMIata speed believed to be unachievable byclassicalcomputers. In addition, QAOA is within the computing capabilities of near-term quantum computers,called noisy intermediate-scale quantum(NISQ),now available.

AccurateForecasting

When it comes to system operation, forecasting is another issuequantumcomputing could address.The high volatility ofDERs, such assolar andwind, may disturb normal system operation and underminethesystems reliability. Accurate forecastingof variable generationwouldenablesystem operators to act proactively to avoid potential system frequency disturbances and stability concerns.

Quantumcomputing couldmake it possible to consider abroaderrange of data for forecasting (such as detailed weather projections and trends) and achieve a much more accurate forecast.The workshop identified Boltzmannas a potentially effective method to tackle this problem. In particular, thequantum Boltzmannmachine (QBM) is a model that has significantly greater representational power than traditional Boltzmannmachines. QBMsalreadyhavebeen experimentally realized on currently availablequantum computers.

AddressingUncertainties

An inherent part of modern power gridsistheuncertaintystemmingfrom various sources (such asvariable generation, component failures, customer behavior, extreme weatherandnatural disasters). Uncertainties cannot be controlled by grid operators, so the common practice is to define potential scenarios and plan for themaccordingly.However, these scenarioscanbe significantin some cases, making it extremely challenging to devise a viable plan for grid operation and asset management.

Quantum computers capabilityto solve numerous scenarios simultaneouslycould beuseful in addressing uncertainty in power systems. Quantum algorithms under development by financial firmsalsomaybe directly translatable to addressing uncertainties in power grids.

StudyingThese Applications

As part of thebroader collaboration,the University of Denver teamhas beenawarded a grant to study some of theapplicationsof quantum computing in power grids.Awarded by theColorado Office of Economic Development & International Trade,the grantaimstoexplorequantum computing-enhanced security and sustainability for next-generation smart grids. In particular, the team will investigate the quantum solution of the power flow problem as the most fundamentalcomputationalanalysis in power systems.

The workshop also identified that practical applications of quantum computing may soon be possible thanks to the development of quantum hardware.In 2019,Googleconducted aquantum supremacy experimentby running asimple program on a small quantum computer in secondsthatwould have taken days on the worlds largest supercomputer. IBM recently released a technology roadmapin whichmachineswilldoublein sizeoverthe next few years, with a target of over 1000 quantum bitsby2023whichlikelywould belarge enough for many of thepotentialpower gridapplications.

A Quantum Leap

The 2020 workshopthat ComEd,theUniversity of Chicago andtheUniversity of Denver engaged inhas only scratched the surface ofquantumcomputingas a new paradigm to solve complex energy system issues. However, this first step presents a path toward understanding the capabilities ofquantumcomputing and the role it can play in optimizing energy systems.That path toward understanding is best taken together, as academics and engineers,government and institutions,andutilitiescollaborate to share knowledge to build theelectricgrid of the future.

ComEdand the two universities have sustained a bimonthlycollaboration since the workshopto explorepower systems applications of quantum computing.Some preliminary results on quantum computing approaches to theUCproblem were presentedbytheUniversity of Chicago in the IEEE 2020 Quantum Week.As this collaboration develops, it becomes increasingly likely the next generation of grid technologies will engage the quantum possibilities of ones, zeros and everything in between.

Honghao Zheng(honghao.zheng@comed.com)isaprincipalquantitativeengineer insmart grid emerging technology atCommonwealthEdison(ComEd),where he supportsnew technology ideation, industrialresearch and development,and complex project execution. Prior to ComEd,heworkedasatechnical leadof Spectrum PowerOperator Training Simulator and TransmissionNetwork Applicationsmodulesfor Siemens DG SWS.ZhengreceivedhisPh.D. inelectricalengineering fromtheUniversity ofWisconsin-Madison in 2015.

Ryan Burg(ryan.s.burg@comed.com)is aprincipalbusinessanalyst insmartgridprograms at ComEd,where he supports academic partnerships. He previously taught sustainable management and business ethics at Bucknell, HSE and Georgetown Universities.Burgholds a joint Ph.D.in sociology and business ethics from the Wharton School of Businessof the University of Pennsylvania.

AleksiPaaso(esa.paaso@comed.com)is director ofdistributionplanning,smartgridandinnovation at ComEd, where he is responsible for distribution planning activities, distributed energy resource (DER) interconnection, andsmart grid strategy and project execution. He is a senior member ofthe IEEE and technical co-chair for the 2020 IEEE PES Transmission & Distribution Conference and Exposition. He holds a Ph.D.in electrical engineering from the University of Kentucky.

RozhinEskandarpour(Rozhin.Eskandarpour@du.edu)is aseniorresearchassociateintheelectrical andcomputerengineeringdepartment at the University of Denver. Her expertise spans the areas ofquantumcomputing andartificialintelligenceapplications in enhancingpowersystemresilience.Shealsois the CEO and founder of Resilient Entanglement LLC, a Colorado-based R&D company focusing on quantumgrid.She is a senior member of the IEEE society. Rozhin holds a Ph.D. degree inelectrical and computer engineering from the University of Denver.

AminKhodaei(Amin.Khodaei@du.edu)isa professor ofelectrical andcomputerengineering at the University of Denver andthe founder of PLUG LLC, an energy consulting firm. He holds a Ph.D.degree inelectricalengineering from the Illinois Institute of Technology. Dr.Khodaeihas authored more than 170 technical articles on various topics in power systems, including the design of the grid of the future in the era of distributed resources.

Pranav Gokhale(pranavgokhale@uchicago.edu)iscofounder and CEO ofSuper.tech, a quantum software start-up. He recently defended his Ph.D.in computer science fromtheUniversity ofChicago(UChicago), where he focused on bridging the gap from near-term quantum hardware to practical applications.Gokhales Ph.D.research led to over a dozen publications, three best paper awards and two patent applications. Prior toUChicago,hestudied computer science and physics at Princeton University.

Frederic T.Chong(chong@cs.uchicago.edu)is the Seymour Goodman Professor in thedepartment ofcomputerscience at the University of Chicago. Healsoisleadprincipalinvestigator for the Enabling Practical-scale Quantum Computing(EPiQC) project, a National Science Foundation (NSF)Expedition in Computing. Chong received his Ph.D. from MIT in 1996. He is a recipient of the NSF CAREER award, the Intel Outstanding Researcher Award andninebest paper awards.

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A Quantum Leap Is Coming: Ones, Zeros And Everything In Between - Transmission & Distribution World

Issued on: 25/01/2021 - 13:19Modified: 25/01/2021 - 14:18

The first quantum revolution gave way to lasers and transistors while the secondushered in MRIs and GPS. But the technology still holds much more promisefor the future. We tell you why quantum computing is becomingsuch a strategic sector.

Quantum physics constitutes a huge change in how one understands the world and conceives reality. There is a shift from the intuitive, straightforward classical paradigmto the quantum world that describesmuch more complex, counterintuitive and amazing phenomena. In this edition, we attempt to explain the fundamental mechanism of quantum physics, a demonstration of how little we actually know about our world.

We dig deeper into the prospect of quantum computers with Eleni Diamanti, a senior researcher at LIP6 Sorbonne. She tells us how much this technology is set to revolutionise certain sectors like communications, medtech and theInternet of Things, plus how nations and companies are now engaged in an arms race for quantum supremacy.

And in Test 24, wetake a look at the French startup Vaonis' latest deviceVespera, a perfect hybrid between a smart telescope and a camera that picked up the best innovation award at this year's CES trade show.

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Tech 24 - Welcome to the quantum era - FRANCE 24

BOSTON, Jan. 27, 2021 /PRNewswire/ --Aliro Quantum, the leading quantum networking company, announces today that it has joined the Center for Quantum Networks (CQN) Industry Advisory Board. Aliro will help guide CQN on its mission to build the first long-range quantum network enabled by quantum repeaters, making Entanglement as a Servicethe fundamental building block for a 100% secure networka reality for government and business use. CQN, centered at the University of Arizona, was founded in 2020 with a $26 million grant from the National Science Foundation (NSF).

"The Center for Quantum Networks is at the forefront of establishing national leadership in quantum networking technology," said Jim Ricotta, Aliro CEO. "Aliro will provide valuable industry perspective to support CQN's groundbreaking work. I've led companies into nascent networking markets before, and the signs are unmistakable: The quantum internet will spur a new remarkable computing revolution."

CQN will develop the first quantum network enabling fully error-corrected quantum connectivity at 10 M qubits/s over 100-km simultaneously between multiple user groups, enabled by quantum repeaters. Prineha Narang, Professor at Harvard and Aliro CTO, serves as a Thrust Co-Lead at CQN, with a focus on quantum materials, devices, and fundamentals.

"The Quantum Internet will surpass the capabilities of today's internet because of the unique applications afforded by distributed entanglement," said Saikat Guha, Director, CQN.

CQN was founded in 2020 as an NSF Engineering Research Center (ERC). The NSF ERC program supports convergent research, education, and technology translation at U.S. universities that will lead to strong societal impacts.

To learn more about Aliro and its quantum networking solutions, visit aliroquantum.com.

About Aliro Quantum

Aliro Quantum is a quantum networking platform company that spun out of NarangLab at Harvard University. Aliro is leading the charge on quantum network market creation by offering the foundational technologies needed for organizations around the world to build powerful quantum systems. An Air Force Research grant recipient, Aliro is designing quantum network simulation and emulation tools while partnering with national labs and hardware vendors including Air Force Research Labs, IBM Q Network, Rigetti, Honeywell Quantum Solutions, and Hyperion Research to make scalable quantum computing accessible. To learn more, visit https://aliroquantum.com.

About Center for Quantum Networks

The Center for Quantum Networks(CQN) is taking on one of the great engineering challenges of the 21st century: to lay the technical and social foundations of the quantum internet. CQN will lay the foundations for a socially responsible quantum internet which will spur new technology industries and a competitive marketplace of quantum service providers and application developers. CQN aims to develop a quantum network enabling error-corrected quantum connectivity at mega qubits per second over metropolitan-scale distances, simultaneously for multiple user pairs, supported on a network backbone of quantum repeaters and switches. To learn more, visit https://cqn-erc.org.

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Aliro Joins the Center for Quantum Networks (CQN) Industry Advisory Board to Lay the Foundations for a Commercially-Available Quantum Internet -...

The globalquantum computing marketis valued at $667.3 million by 2027, surging from $88.2 million in 2019 at a noteworthy CAGR of 30.0%.

Impact Analysis of COVID-19 on the Quantum Computing Market

The global market for quantum computing services is projected to experience considerable impact due to the emergence of the Coronavirus disease (COVID-19). In the fight against COVID-19, quantum computing platform has joined the force of disruptive technologies at the service to better control the global outbreak. The current coronavirus crisis provides a valuable stage for zooming in the real potential applications of quantum computing in highly-impacted and complex situations. The esteemed companies operating in global quantum computing market are trying their best to provide integrated platform amidst the shutdown. For instance, in September 2020, IBM, an American multinational technology and consulting company, announced to conduct IBM Quantum Summit 2020 to discover chemical compounds that could contribute to the fight against COVID-19 pandemic.

On the other hand, quantum computing is very helpful in the discovery of lot of drugs which is a computationally-intensive task. Quantum computing can analyze the the interaction between biomolecules, and this can be helpful in tackling infectious agents such as coronavirus and others. There can be no other better way than to model the problem on a computer and conduct extensive research on the same. For instance in March, D-Wave announced that they are offering quantum computers free to anyone working on the coronavirus crisis for research and other work related to covid19. Therefore, there are many companies expirenced upsurge in growth, throughout the pandemic period. These type of factors may lead lucrative opportunities for the investors in the forecast period.

Quantum Computing Market Analysis:

The enormous growth of the global quantum computing market is mainly attributed to the increasing integration of quantum computing platforms in healthcare. Companies such as 1QB Information Technologies Inc., QxBranch, LLC, D-Wave Systems Inc. are working in the field of material simulation to enhance the accessibility, availability, and usability of quantum computers in material simulation applications. In addition, these players are following strategic collaborations, business expansion and technological innovations to acquire the largest share in the global industry. For instance, in October 2020, Cambridge Quantum Computing announced that they are opening Ph.D. internships with multinational pharmaceutical companies for drug designing through quantum algorithms. These key factors may lead to a surge in the demand for quantum computing services in the global market.

Lack of knowledge and skills may create a negative impact on global quantum computing services throughout the analysis timeframe. This type of factors may hamper the quantum computing market growth during the analysis period.

The global quantum computing industry is growing extensively across various fields, but fastest growing adoption of quantum computing is in agriculture. Quantum computing offers software solutions for agriculture in large businesses and startups all over the world to develop innovative solutions in agriculture. For instance Quantum, a software and data science company launched a software named AgriTech, ths software helps farmers to monitor crops, agricultural fields and it will respond quickly to all the issues related to agriculture. These factors may provide lucrative opportunities for the global quantum computing market, in the coming years.

The consulting solutions sub-segment of the quantum computing market will have the fastest growth and it is projected to surpass $354.0 million by 2027, with an increase from $37.1 million in 2019. This is mainly attributed to its application in blind quantum computing and quantum cryptography playing a major role to secure cloud computing services. Moreover, the consulting solutions segment for quantum computing technologies covers broad range of end-user industries including automotive, space & defense, chemicals, healthcare, and energy & power, and others.

Moreover systems offering sub-segment type will have a significant market share and is projected to grow at a CAGR of 26.7% by registering a revenue of $313.3 million by 2027. This growth is mainly attributed to many government authorities across the developed as well as developing economies that are heavily investing into quantum computing technologies. For instance, in February 2020, the Indian government announces that they are going to invest $1120 million in quantum computing research. This type of government support and scheme is expected to flourish the research for technology under the National Mission of Quantum Technology and Application project. Such government support may bolster the segmental growth, in the analysis period.

Machine learning sub-segment for the quantum computing industry shall have rapid growth and it is anticipated to generate a revenue of $236.9 million by 2027, during the forecast period. This growth is mainly attributed to higher applications of quantum computing in the broad range of areas such as drug discovery, multi-omics data integration, and many among others. These factors may offer lucrative opportunities for the segment, during the forecast timeframe.

The banking and finance sub-segment will be the fastest-growing segment and it is expected to register a revenue of $159.2 million by 2027, throughout the analysis timeframe. The enormously growing quantum computing in the finance sector across the globe has advanced with developments in smartphone technology and computer processing. In addition, the quantum computing platform helps speed up the transactional activities in cost-effective ways. Hence, the quantum computing platform is extensively attracting the interest of BFSI firms that are seeking to boost their data speed, trade, and transactions. Such factors are projected to upsurge the growth of the segment, during the projected timeframe.

The quantum computing market for the Asia-Pacific region will be a rapidly-growing market and it has generated a revenue of $18.1 million in 2019 and is further projected to reach up to $150.3 million by 2027. The demand for quantum computing services is surging in the Asia pacific region, specifically because of the strategic collaboration and development. For instance, in December 2019, D-Wave Systems came in a partnership with Japans NEC for building of quantum apps and hybrid HPC for exploring the capabilities NECs high-performance computers and D-Waves quantum systems. Such partnerships may further surge the growth of market, during the analysis timeframe.

The Europe quantum computing market shall have a dominating market share and is anticipated to reach up to $ 221.2 million by the end of 2027 due to its higher application in fields such as development and discovery of new drugs, cryptography, cyber security, defense sector, among others. In addition, the use of quantum computing will also have positive consequences in development of AI as well as in machine learning. For instance, in July 2019, Utimaco GmbH, software & hardware provider came in partnership with ISARA to utilize post quantum cryptography; this partnership will help their users to have secured and encrypted communication that cannot be decrypted by other computers. These initiatives may create a positive impact on the Asia-pacific quantum computing market, during the forecast period.

Key Market Players

Porters Five Forces Analysis for Quantum Computing Market:

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Analysis: Opportunities and Restraint of the Quantum Computing Market KSU | The Sentinel Newspaper - KSU | The Sentinel Newspaper

BEIJING, Jan. 27, 2021 The preliminary results for the 2020-2021 ASC Student Supercomputer Challenge (ASC20-21) have now been released. After two months of intense competition, 28 teams from over 300 participating universities from around the world have stood out and advanced to the finals. Beihang University, Jinan University, Shanghai Jiaotong University, the Chinese University of Hong Kong, Universidad EAFIT, University of Warsaw, and Ural Federal University are just some of the finalists.

Because the COVID-19 pandemic is still rampant in many countries around the world, the ASC20-21 Student Supercomputer Challenge finals will be organized to include both on-site and virtual participations. The Top21 teams from the Chinese mainland will join the finals on-site, and the Top7 teams outside of Chinese mainland will remotely participate in the finals virtually.

Among the teams advancing to the ASC20-21 finals are three champions from the prior Student Cluster Competitions: Tsinghua University champion of SC19 & SC20, University of Science and Technology of China champion of ISC20, and National Tsing Hua University champion of ASC19. It will be the first time in the history of the student supercomputing competition that three world champions will directly compete, which has created massive interest and enthusiasm for this round of the ASC20-21 finals.

There is also much excitement about the debuting teams from Monash University, Hunan University and Lanzhou University for making their first ASC finals appearance this year. Five teams, including the team of Peking University, are repeat finalists after advancing to their first finals at ASC19. This ASC20-21 final is full of traditional powerhouses and remarkable new contenders, which will make the competition intense till the last moments, when various awards will be presented including the Champion, Silver Prize, Highest LINPACK, and e Prize.

The ASC20-21 preliminaries included computational tasks from ACS20 like quantum computing simulation and language examination, but also included a new cutting-edge task in astronomy searching for pulsars. Many of the participating teams performed very well in the preliminaries and demonstrated an outstanding ability to learn and innovate freely.

The pulsar search task required teams to use the open-source software PRESTO to search for potential pulsars based on the observational data from the Five-hundred-meter Aperture Spherical radio Telescope (FAST), also known as China Sky Eye. The research of pulsars is so valuable because it can help solve major physics conundrums, such as gravitational wave detection and spacecraft navigation. The Universidad EAFIT team optimized the software compilation parameters, used a variety of Python tools for algorithm hotspot analysis, and adopted a multi-process solution to parallelize the entire search process.

The Language Exam task required 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. The team of the Chinese University of Hong Kong carefully analyzed the intention and objectives of this task. Using a large amount of research literature, they ran experiments to compare the performance of different models, incorporated pre & post processing algorithms, and selected the best model. This boosted them to reach their remarkably high score.

The quantum computing simulation task required each participating team to use the QuEST (Quantum Exact Simulation Toolkit) running on a 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 quantum algorithms, which are particularly important because quantum computers are not practically available yet in the industry. National Tsing Hua University made considerable effort in finding the algorithms hotspots and provided a detailed performance analysis of QuEST. They tried several methods for the GPU version of QuEST and made crucial optimizations to achieve much better performance of the toolkit. In addition, they delivered a detailed plan to further optimize QuEST in the future.

The selection process for both on-site and virtual participation has presented a tough challenge for the Evaluation Committee. After a long and careful evaluation, the ASC20-21 Student Supercomputer Challenge Committee selected the following teams to qualify for the ASC20-21 Finals:

Finalist On-site Participation

Beihang University

Jinan University

Qinghai University

Zhejiang University

Taiyuan University of Technology

Sun Yat-sen University

National University of Defense Technology

Peking University

Shandong University

Fuzhou University

Shanxi University

Southern University of Science and Technology

University of Electronic Science and Technology of China

Huazhong University of Science & Technology

Hunan University

Tsinghua University

Lanzhou University

Southeast University

Shanghai Jiaotong University

University of Science and Technology of China

Northwestern Polytechnical University

Finalist Virtual Participation

National Tsing Hua University

The Chinese University of Hong Kong

Universidad EAFIT

Kasetsart University

University of Warsaw

Monash University

Ural Federal University named after the first President of Russia B.N.Yeltsin

Note: The finalists are listed by competition ranking.

About ASC

The ASC Student Supercomputer Challenge is the worlds largest student supercomputer competition, sponsored and organized by Asia Supercomputer Community 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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28 University Teams from Around the World Advance to the Finals of the ASC20-21 Student Supercomputer Challenge - HPCwire

Schematic of light-induced formation of Weyl points in a Dirac material of ZrTe5. Jigang Wang and collaborators report how coherently twisted lattice motion by laser pulses, i.e., a phononic switch, can control the crystal inversion symmetry and photogenerate giant low dissipation current with an exceptional ballistic transport protected by induced Weyl band topology. Credit: U.S. Department of Energy, Ames Laboratory

Scientists at the U.S. Department of Energys Ames Laboratory and collaborators at Brookhaven National Laboratory and the University of Alabama at Birmingham have discovered a new light-induced switch that twists the crystal lattice of the material, switching on a giant electron current that appears to be nearly dissipationless. The discovery was made in a category of topological materials that holds great promise for spintronics, topological effect transistors, and quantum computing.

Weyl and Dirac semimetals can host exotic, nearly dissipationless, electron conduction properties that take advantage of the unique state in the crystal lattice and electronic structure of the material that protects the electrons from doing so. These anomalous electron transport channels, protected by symmetry and topology, dont normally occur in conventional metals such as copper. After decades of being described only in the context of theoretical physics, there is growing interest in fabricating, exploring, refining, and controlling their topologically protected electronic properties for device applications. For example, wide-scale adoption of quantum computing requires building devices in which fragile quantum states are protected from impurities and noisy environments. One approach to achieve this is through the development of topological quantum computation, in which qubits are based on symmetry-protected dissipationless electric currents that are immune to noise.

Light-induced lattice twisting, or a phononic switch, can control the crystal inversion symmetry and photogenerate giant electric current with very small resistance, said Jigang Wang, senior scientist at Ames Laboratory and professor of physics at Iowa State University. This new control principle does not require static electric or magnetic fields, and has much faster speeds and lower energy cost.

This finding could be extended to a newquantum computing principle based on the chiral physics and dissipationlessenergy transport, which may run much faster speeds, lower energy cost and high operation temperature. said Liang Luo, a scientist at Ames Laboratory and first author of the paper.

Wang, Luo, and their colleagues accomplished just that, using terahertz (one trillion cycles per second) laser light spectroscopy to examine and nudge these materials into revealing the symmetry switching mechanisms of their properties.

In this experiment, the team altered the symmetry of the electronic structure of the material, using laser pulses to twist the lattice arrangement of the crystal. This light switch enables Weyl points in the material, causing electrons to behave as massless particles that can carry the protected, low dissipation current that is sought after.

We achieved this giant dissipationless current by driving periodic motions of atoms around their equilibrium position in order to break crystal inversion symmetry, says Ilias Perakis, professor of physics and chair at the University of Alabama at Birmingham. This light-induced Weyl semimetal transport and topology control principle appears to be universal and will be very useful in the development of future quantum computing and electronics with high speed and low energy consumption.

What weve lacked until now is a low energy and fast switch to induce and control symmetry of these materials, said Qiang Li, Group leader of the Brookhaven National Laboratorys Advanced Energy Materials Group. Our discovery of a light symmetry switch opens a fascinating opportunity to carry dissipationless electron current, a topologically protected state that doesnt weaken or slow down when it bumps into imperfections and impurities in the material.

Reference: A light-induced phononic symmetry switch and giant dissipationless topological photocurrent in ZrTe5 by Liang Luo, Di Cheng, Boqun Song, Lin-Lin Wang, Chirag Vaswani, P. M. Lozano, G. Gu, Chuankun Huang, Richard H. J. Kim, Zhaoyu Liu, Joong-Mok Park, Yongxin Yao, Kaiming Ho, Ilias E. Perakis, Qiang Li and Jigang Wang, 18 January 2021, Nature Materials.DOI: 10.1038/s41563-020-00882-4

Terahertz photocurrent and laser spectroscopy experiments and model building were performed at Ames Laboratory. Sample development and magneto-transport measurements were conducted by Brookhaven National Laboratory. Data analysis was conducted by the University of Alabama at Birmingham. First-principles calculations and topological analysis were conducted by the Center for the Advancement of Topological Semimetals, an Energy Frontier Research Center funded by the DOE Office of Science.

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Light-Induced Twisting of Weyl Nodes Switches on Giant Electron Current Useful for Spintronics and Quantum Computing - SciTechDaily