Category Archives: Quantum Computing
Cambridge named as world-leading centre of quantum computing research – Varsity Online
The Centre for Quantum Information and Foundations is based at the Department of Applied Mathematics and Theoretical PhysicsLouis Ashworth
The University of Cambridge has been chosen as one of the worlds top ten universities and research institutions by The Quantum Daily, a leading online publication in the field of quantum computing.
It describes Cambridge as being at the apex of the countrys pioneering quantum movement.
Several quantum computing startups have spun out of the University, while many other quantum organizations made their homes near Cambridge because of the ready access to world-leading talent and brainpower, the publication continues.
Professor Adrian Kent, a quantum physicist at the Universitys Department of Applied Mathematics and Theoretical Physics, told Varsity: Recognition is always pleasing, of course, but were really focussed on enjoying work in this amazing field and doing the best science we can.
The Quantum Daily describes the Centre for Quantum Information and Foundations (CQIF), based at the Department of Applied Mathematics and Theoretical Physics, as an example of the Universitys ability to combine research, teaching and service to encourage the growth of this ecosystem.
Conventional (classical) computers use the bit (binary digit) as a unit of information, which can exist in one of two states represented by the digits 0 and 1. Quantum computers, on the other hand, operate on quantum bits, or qubits.
Qubits are governed by the laws of quantum mechanics, so can exist in both states at once. This phenomenon, known as entanglement, may in future allow quantum computers to perform calculations inaccessible to their classical counterparts.
Research at the CQIF currently focuses on theoretical and practical quantum cryptography and relativistic quantum cryptography a field invented at the CQIF, Kent and his colleagues told Varsity.
Quantum cryptography research is driven by the fact that the state of quantum systems is sensitive to measurement and observation, in principle making them ideal for secure communications.
The CQIF is a member of the UK Quantum Communications Hub, which Kent and the other researchers describe as a collaboration between many UK research groups, one of whose projects is building a secure quantum cryptographic network that will link nodes in Cambridge to Ipswich, London, Bristol and beyond.
Other research at the Centre investigates foundational questions probing the basic principles of quantum theory itself and its relationship to classical physics and gravity, as well as the overlap between quantum computing and classical computer science.
CQIF is also examining quantum advantage, or why quantum computers are faster than classical computers, the researchers explained. A better understanding of key differences between behaviours of classical and quantum systems will help answer questions about how to build efficient quantum computers and design software to run on them.
Quantum information theory, the study of information transmission and manipulation in quantum systems, is another focus of research at the CQIF. In particular, Kent and his colleagues are interested in removing the traditionally considered assumptions to understand information transmission in more realistic conditions.
One such assumption is that quantum systems are memoryless, meaning the probability of an event occurring does not depend on how much time has elapsed since the last event, they explained.
The researchers toldVarsity of their enjoyment of the depth and breadth of research in the CQIF, and the diverse backgrounds and expertise of those working at the centre.
It often leads to useful discussions between the different members of CQIF, resulting in cross-fertilization of ideas from different areas, useful insights and, ultimately, exciting results, they continued.
This recognition will hopefully contribute to more talented young scientists aspiring to work in this inspiring place.
In addition to Cambridge, TheQuantum Dailys list includes other organisations from around the world. The Chinese Academy of Science, the Max Planck Society and Harvard University were among those chosen.
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Cambridge named as world-leading centre of quantum computing research - Varsity Online
IBM’s new roadmap for quantum computing promises 100x speedups and then some – Neowin
One of the pioneers of quantum computing, IBM, revealed its Quantum Development Roadmap for the future of quantum computers today. It builds on the firm's previous roadmap from September 2020, in which it laid out the pathway towards achieving quantum computing ecosystems comprised of thousands of noise-resilient and stable qubits by 2023. This "inflection point", as IBM puts it, is crucial for the full-scale, commercial realization of quantum computers. Since then, the firm has made significant inroads towards achieving this goal, which has been highlighted in the update unveiled today.
Firstly, this year, IBM is planning on releasing Qiskit runtimean execution environment that speeds up the execution of quantum circuits by as much as 100x. Qiskit runtime achieves this substantial speedup by reducing the latency in the communication between classical and quantum computers. By cutting this latency, workloads that take months to run today can be cut down to a matter of a few hours.
The Qiskit runtime rethinks the classical-quantum workload so that programs will be uploaded and executed on classical hardware located beside quantum hardware, slashing latencies emerging from communication between the users computer and the quantum processor.
One of the primary use cases of quantum computers is the simulation of quantum systems, which is an arduous task for classical computers since the computational complexity required to model a system grows exponentially with respect to its size. Today, a simulation of Lithium hydride (LiH) can take up to 100 days. But with the 100X speedup, this task can be done in one day.
Moreover, Qiskit runtime will be sizing up the capacity to run a greater variety of quantum circuits, allowing developers to run programs developed by others as a service in their own workloads and eventually tackling previously inaccessible problems with quantum computers. With help from the firm's OpenQASM3 assembly language, technologies designed on OpenShift, by 2023, IBM plans on debuting circuit libraries and advanced control systems for manipulating large qubit fabrics.
Cumulatively, IBM boldly claims that come 2023, its quantum systems will be powerful enough to explore major problems with a clear demonstratable advantage over classical computers.
Come 2025, IBM is confident that it will achieve "frictionless quantum computing", a turning point at which the barrier to entry into quantum development will be greatly tamed.
By then, we envision that developers across all levels of the quantum computing stack will rely upon on our advanced hardware with a cloud-based API, working seamlessly with high performance computing resources to push the limits of computation overalland include quantum computation as a natural component of their existing computation pipelines.
And a decade from now, in the 2030s, IBM hopes that our hardware and software prowess will reach the extent that we will be able to run billions and trillions of quantum circuits without even realizing that we are doing so. That would be the era of practical, full-scale commercial quantum computers.
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IBM's new roadmap for quantum computing promises 100x speedups and then some - Neowin
This company is using quantum-inspired algorithms to help create the OLED displays of the future – ZDNet
OTI is using quantum simulations, machine learning and real-world testing in pilot production.
It was about four years ago, in the back of an Uber driving him back from a conference, that the idea of using quantum computing to design OLED displays for smartphones and TVs started germinating in the mind of Michael Helander, the CEO and co-founder of materials design company OTI Lumionics.
Helander was sharing his ride with a particle physicist who doubled as a VC, and who was then an early investor in leading quantum computing company D-Wave. As you do in such circumstances, the pair were discussing quantum computing solutions capable of simulating the properties of atoms coming together to form molecules and solids and what that might mean for Helander's field of expertise, computational chemistry.
"That conversation got me asking myself: is this even feasible?" Helander tells ZDNet. Now a few years later, it would seem so. OTI has successfully developed a new electrode material that is ready for mass production and started shipping worldwide at the end of 2020. The material will be used to manufacture first-of-their-kind transparent OLED displays.
Most OLED displays require several layers made up of different materials to function, including a cathode, through which electrical current flows in. Because standard cathodes are not transparent, front-facing cameras and sensors for technologies like facial recognition have to sit on top of the display, which is why most smartphones still come with a punch-hole at the top.
SEE: Tableau business analytics platform: A cheat sheet (free PDF download) (TechRepublic)
For our devices' bulky cutouts to disappear, cameras would have to be integrated under the display meaning that the display needs to be transparent. OTI's team replaced standard cathodes with a new material patterned with small holes that act as microscopic transparent windows, effectively letting light go through the display.
With front-facing cameras and 3D facial recognition sensors moved under the display, not only can the screen be larger and smoother, but transparent displays also come with higher brightness and longer battery life. Helander hopes this will bring about new designs for phones, and also laptops, tablets and foldable devices, as well as AR and VR hardware.
"OLED displays are a massive and growing market," says Helander. "There is a lot of excitement about the technology expanding into laptops and monitors. We see it as an opportunity to innovate when it comes to the convergence of display and sensors."
Behind OTI's innovative product is a so-called "materials discovery platform" and powering that platform, equally as innovative techniques. "At OTI Lumionics we are developing advanced materials by design using quantum simulations, machine learning and real-world testing in pilot production," proudlystates the company's pitch.
There is a good reason that Helander's interest in quantum was piqued four years ago: the technology, although still in its infancy, is expected to break new ground in the field of molecular simulation. For the CEO of a company that describes itself as a designer of advanced materials for the electronics sector, that is enough to justify digging deeper.
From early on, Helander's strategy has consisted of using a computer-based approach to electronic material design. As a small company, OTI was never equipped with armies of chemists ready to test and trial thousands of different molecular designs in the lab until a winning combination was found. "The way we develop materials has been heavily based on the use of computational techniques in chemical and material design," explains Helander.
"But it turns out that even state-of-the-art classical computational chemistry, for a lot of these difficult problems, is inadequate," he continues. "Either they can't reach a high enough level of accuracy, or, if the theory is accurate enough, it becomes an intractable problem that requires a supercomputer to solve."
Quantum computing, and its ability to leverage the odd behavior of qubits to solve many calculations at once, seemed at first glance an ideal match. Qubits could be used to predict how the complex alignment of many different compounds could result in particular properties for a given electronic material, as well as how this material would interact with other molecules in a device and they could, in principle, do this faster and more accurately than any existing classical methods.
Around the same time, long-established quantum champion IBM published the results of an experiment showing that simple molecules like hydrogencould be simulatedby a universal gate-based quantum system. The stars were aligned; the odds were in favor of quantum-based molecular simulation; and OTI's chemists started getting excited about the implications for computational chemistry.
They quickly found themselves facing a limiting factor. With less than a hundred qubits currently sitting in most quantum computers, there wasn't much that could actually be done. "To solve an industrial-sized problem, you need more qubits than will be scientifically feasible in the next ten to 20 years," says Helander. "But as a small company, we don't have the resources to invest in a long R&D program of that kind."
SEE: Less is more: IBM achieves quantum computing simulation for new materials with fewer qubits
Like any CEO, Helander's interest lies in short-to-near-term business value; and so, he decided to tackle the problem with an entirely new perspective. If the number of qubits available couldn't match the size of the problem, then the problem had to be re-made to match the number of qubits at hand.
"That's actually a gap in theory," says Helander. "So I started with a group of theoreticians. I told them to forget everything they knew about computational chemistry, and imagine a new set of computational chemistry representation to map to a qubit space. What would that look like?"
There is a long-standing problem in the quantum space, argues Helander: instead of developing brand-new programs that are tailored for quantum hardware, scientists apply classical models to qubits. As it turns out, however, the way problems are represented in the classical world doesn't always sit well with small-scale, hardware-constrained quantum computers.
Take the unitary coupled cluster that is, chemists' jargon to describe the technique used to represent chemical systems. According to Helander, that particular classical representation is highly inefficient when mapped onto a quantum computer, and requires large numbers of qubits and gate operations. Instead, OTI's researchersdeveloped a brand-new "qubit coupled cluster method,"adapted specially for quantum systems.
For Helander, if the number of qubits available couldn't match the size of the problem, then the problem had to be re-made to match the number of qubits at hand.
"In order to see value with limited hardware, you have to develop native code and write low-level stuff," says Helander. "We developed that first native representation of the problem we wanted to solve, for quantum computers."
Theory was promptly built into software and, equipped with a bunch of new quantum-ready algorithms, OTI's team tested the technology in cloud-based quantum computers. The researchers, however, couldn't let go of an ongoing feeling of frustration at the nevertheless limited hardware, at the lack of error correction, at the stubborn levels of noise, and often at all three at the same time.
This is when Helander started looking closer at quantum-inspired techniques, a branch of the field that looks at ways to apply quantum-optimized algorithms to classical hardware. With a new set of custom-built, highly efficient quantum algorithms, wondered the CEO, why not try and run the software on regular CPUs and GPUs?
SEE: BMW explores quantum computing to boost supply chain efficiencies
A partnership with Microsoft soon followed, and OTI's team started using the Redmond giant'sAzure Quantum platform, which is designed to run quantum-inspired algorithms on classical Azure hardware. In principle, by using sophisticated optimization techniques, Azure Quantum enables users to reap the rewards of quantum computing approaches while using classical devices.
Last year, in a blog post, Microsoft announced that the project was showing signs of success: OTI had effectivelydemonstrated meaningful resultson commercially relevant sized problems. Specifically, the company had completed the simulation of a green light-emitting OLED material known as Alq3 a problem that would have required 42 error-corrected qubits on gate-based quantum hardware.
For Helander, the experiment showed the promise of much nearer-term value to be drawn from quantum-inspired algorithms, and their potential to start drawing benefits from quantum computers without needing to use them directly.
The company completed the simulation of a green light-emitting OLED material known as Alq3, which would have required 42 error-corrected qubits on gate-based quantum hardware.
That is not to say that OTI has ruled out using pure quantum hardware. Quite the opposite: the company is working with D-Wave, which provides a cloud-based quantum annealer that is much easier to control than the gate-based quantum computers operated by companies like IBM or Rigetti. This means that D-Wave can offer a technology that is already several thousands of qubits-strong, and that can reach the industrial relevance that Helander and his team are looking for, without error.
Helander and his team, therefore, share their time between classical techniques, quantum-inspired approaches and purely quantum-based experiments.
"At the moment, our quantum techniques focus a lot on theory development and optimization," says Helander. "For our current product, for example, we applied a combination of all the different tools that we had classical simulations, quantum systems and quantum-inspired algorithms."
SEE: Microsoft's quantum cloud computing plans take another big step forward
"We still heavily combine our quantum methods with classical techniques," he continues. "Even though the amount of value we are driving is only a small subset of our everyday work, from this point forward we're looking at increasing that over time until more of our workflow is adopting quantum and quantum-inspired methods."
While the company, for now, is focusing on high-value OLED displays, Helander is positive that the discoveries led by OTI's research team will generate an avalanche of innovations in many other fields such as battery design and drug development. The technology could effectively replace processes that were until now based on trial-and-error, with highly sophisticated computer models that would rapidly build designs for new molecules from the ground up.
The potential of quantum computing to phenomenally disrupt industries that are hunting for new and improved materials is well-known, but it will be at least a decade before quantum's value translates into real-world results. For those too impatient to wait, however, quantum-inspired methods might provide an early sneak peak of better things to come.
Quantum Computing 101 -What it is, how is it different and why it matters – The Jerusalem Post
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
A Quantum Leap Is Coming: Ones, Zeros And Everything In Between – Transmission & Distribution World
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
University of Glasgow partners with Oxford Instruments NanoScience on quantum computing – SelectScience
The University of Glasgow, one of thepioneering institutions at the leading edge of quantum technology development and home of the Quantum Circuits Group, has announced its using Oxford Instruments next-generation Cryofree refrigerator, Proteox, as part of its research to accelerate the commercialization of quantum computing in the UK.
Were excited to be using Proteox, the latest in cryogen-free refrigeration technology, and to have the system up and running in our lab, comments Professor Martin Weides, Head of the Quantum Circuits Group. Oxford Instruments is a long-term strategic partner and todays announcement highlights the importance of our close collaboration to the future of quantum computing development. Proteox is designed with quantum scale-up in mind, and through the use of its Secondary Insert technology, were able to easily characterize and develop integrated chips and components for quantum computing applications.
The University of Glasgow, its subsidiary and commercialization partner, Kelvin Nanotechnology, and Oxford Instruments NanoScience are part of a larger consortium supported by funding from Innovate UK, the UKs innovation agency, granted in April 2020. The consortium partners will boost quantum technology development by the design, manufacture, and test of superconducting quantum devices.
Today'sannouncement demonstrates the major contribution Oxford Instruments is making towards pioneering quantum technology work in the UK, states Stuart Woods, Managing Director of Oxford Instruments NanoScience. With our 60 years of experience of in-house component production and global service support, we are accelerating the commercialization of quantum to discover whats next supporting our customers across the world.
Proteox is a next-generation Cryofree system that provides a step change in modularity and adaptability for ultra-low temperature experiments in condensed-matter physics and quantum computing industrialization. The Proteox platform has been developed to provide a single, interchangeable modular solution that can support multiple users and a variety of set-ups or experiments. It also includes remote management software which is integral to the system design, enabling, for example, the system to be managed from anywhere in the world.
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University of Glasgow partners with Oxford Instruments NanoScience on quantum computing - SelectScience
Caltech and NTT developing the world’s fastest quantum computer – Digital Journal
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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Caltech and NTT developing the world's fastest quantum computer - Digital Journal
Aliro Joins the Center for Quantum Networks (CQN) Industry Advisory Board to Lay the Foundations for a Commercially-Available Quantum Internet -…
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 -...
Major Quantum Computing Projects And Innovations Of 2020 – Analytics India Magazine
Quantum computing has opened multiple doors of possibilities for quick and accurate computation for complex problems, something which traditional methods fail at doing. The pace of experimentation in quantum computing has very naturally increased in recent years. 2020 too saw its share of such breakthroughs, which lays the groundwork for future innovations. We list some of the significant quantum computing projects and experiments of 2020.
IT services company Atos devised Q-Score for measuring quantum performance. As per the company, this is the first universal quantum metric that applies to all programmable quantum processors. The company said that in comparison to qubits, the standard figure of merit for performance assessment, Q-Score provides explicit, reliable, objective, and comparable results when solving real-world optimisation problems.
The Q-Score is calculated against three parameters: application-driven, ease of use, and objectiveness and reliability.
Googles AI Quantum team performed the largest chemical simulation, to date, on a quantum computer. Explaining the experiment in a paper titled, Hartree-Fock on a superconducting qubit quantum computer, the team said it used variational quantum eigensolver (VQE) to simulate chemical mechanisms using quantum algorithms.
It was found that the calculations performed in this experiment were two times larger than the previous similar experiments and contained about ten times the number of quantum gate operations.
The University of Sydney developed an algorithm for characterising noise in large scale quantum computers. Noise is one of the major obstacles in building quantum computers. With this newly developed algorithm, they have tried to tame the noise by reducing interference and instability.
A new method was introduced to return an estimate of the effective noise with relative precision. The method could also detect all correlated errors, enabling the discovery of long-range two-qubit correlations in the 14 qubit device. In comparison, the previous methods would render infeasible for device size above 10 qubits.
The tool is highly scalable, and it has been tested successfully on the IBM Quantum Experience device. The team believes that with this, the efficiency of quantum computers in solving computing problems will be addressed.
Canadian quantum computing D-Wave Systems announced the general availability of its next-generation quantum computing platform. This platform offers new hardware, software, and tools for accelerating the delivery of quantum computing applications. The platform is now available in the Leap quantum cloud service and has additions such as Advantage quantum system with 5000 qubits and 15-way qubit connectivity.
It also has an expanded solver service that can perform calculations of up to one million variables. With these capabilities, the platform is expected to assist businesses that are running real-time quantum applications for the first time.
Physicists at MIT reported evidence of Majorana fermions on the surface of gold. Majorana fermions are particles that are theoretically their own antiparticle; it is the first time these have been observed on metal as common as gold. With this discovery, physicists believe that this could prove to be a breakthrough for stable and error-free qubits for quantum computing.
The future innovation in this direction would be based on the idea that combinations of Majorana fermions pairs can build qubit in such a way that if noise error affects one of them, the other would still remain unaffected, thereby preserving the integrity of the computations.
In December, Intel introduced Horse Ridge II. It is the second generation of its cryogenic control chip, considered a milestone towards developing scalable quantum computers. Based on its predecessor, Horse Ridge I, it supports a higher level of integration for the quantum systems control. It can read qubit states and control several gates simultaneously to entangle multiple qubits. One of its key features is the Qubit readout that provides the ability to read the current qubit state.
With this feature, Horse Ridge II allows for faster on-chip, low latency qubit state detection. Its multigate pulsing helps in controlling the potential of qubit gates. This ability allows for the scalability of quantum computers.
I am a journalist with a postgraduate degree in computer network engineering. When not reading or writing, one can find me doodling away to my hearts content.
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Major Quantum Computing Projects And Innovations Of 2020 - Analytics India Magazine
A little better all the time in 2021 – Science Magazine
A famous story about the Beatles tells of the collaboration between Paul McCartney and John Lennon on the song Getting Better for their legendary Sgt. Pepper's Lonely Hearts Club Band album. After McCartney wrote the lines I've got to admit, it's getting better; a little better all the time, Lennon wryly added, It can't get no worse. This story could serve as an epigraph as the calendar turns from the year 2020, which could hardly have gotten much worse, to 2021, when we hope life will indeed get a little better all the time. Better from COVID-19 because of the vaccines, better from misinformation spread by outgoing president Donald Trump and his allies, and better, we can hope, when it comes to the production and distribution of scientific knowledge.
There's plenty of exciting science to be optimistic about in 2021 (see News on p. 6). At the end of 2020, the DeepMind group in the United Kingdom announced a major advance in long-standing challenges in protein folding, predicting three-dimensional (3D) structures of proteins from their amino acid sequence. The next year portends even more exciting advances in protein structure and design.
On the cosmic front, there are many efforts underway to bring samples from the Solar System back to this planet. The Hayabusa2 mission that traveled to the asteroid 162173 Ryugu retrieved what could be a treasure trove of material revealing details about the ancient delivery of water and organic molecules to Earth. Similarly, the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer) mission has collected samples from the asteroid Bennu that, when they arrive, could reveal important aspects of the formation of the Solar System. The new Mars rover Perseverance will land in February and, in addition to transmitting important data from the red planet, will begin the process of collecting samples that may eventually be studied in terrestrial laboratories.
In biology, the COVID-19 pandemic led to major advances in the development and application of messenger RNA (mRNA) vaccines. It is stunning that science not only came up with a vaccine to a new pathogen so quickly but also advanced a brand new vaccine technology, albeit one that was already in development for several years. The application of mRNA therapies to other problems in infectious diseases and throughout medicine will be exciting to follow.
Quantum computing remains an important area to watch. This year, Science published a paper that describes the application of a quantum computer to an important problem in theoretical chemistry. In the coming months, it's likely that there will be progress in addressing the problem of quantum error correction, pushing quantum computing a little closer to routine application.
Additive manufacturing and 3D printing continue to become more practical. In particular, the ability to apply these techniques to new types of materials will make it more likely that advanced manufacturing can benefit from the science behind these processes.
On the policy front, the continued development of the UK Research and Innovation (UKRI) organizationas described in a recent editorial by Ottoline Leyserwill be of keen interest as the Brexit process continues. Despite choppy politics, the scientific vision of UKRI is strong and could lead to advances in British science.
In the United States, although the Biden White House will certainly be friendlier to science, the science denial that fueled the Trump administration will linger in the American population and among some conservative politicians. The battles ahead are not to be underestimated. Continued denial of climate change and COVID-19 is sadly inevitable, and it will take everything U.S. science and the Biden administration can muster to stay strong. Still, as new leaders are named and confirmed in health and science policy, U.S. science should be able to at least catch its breath and feel optimistic about a new era.
Although 2020 will certainly go down as a year that couldn't get much worse, there is plenty to be proud of and reason to hope that things will be getting better. The virus was confronted. Epidemiologists and other scientists became household names. And the scientific community found a much stronger voice, one that will serve us all well in 2021 and beyond.
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A little better all the time in 2021 - Science Magazine