Category Archives: Quantum Computing
A game plan for quantum computing | McKinsey
Pharmaceutical companies have an abiding interest in enzymes. These proteins catalyze all kinds of biochemical interactions, often by targeting a single type of molecule with great precision. Harnessing the power of enzymes may help alleviate the major diseases of our time.
Unfortunately, we dont know the exact molecular structure of most enzymes. In principle, chemists could use computers to model these molecules in order to identify how the molecules work, but enzymes are such complex structures that most are impossible for classical computers to model.
A sufficiently powerful quantum computer, however, could accurately predict in a matter of hours the properties, structure, and reactivity of such substancesan advance that could revolutionize drug development and usher in a new era in healthcare. Quantum computers have the potential to resolve problems of this complexity and magnitude across many different industriesand applications, including finance, transportation, chemicals, and cybersecurity.
Solving the impossible in a few hours of computing time, finding answers to problems that have bedeviled science and society for years, unlocking unprecedented capabilities for businesses of all kindsthose are the promises of quantum computing, a fundamentally different approach to computation.
None of this will happen overnight. In fact, many companies and businesses wont be able to reap significant value from quantum computing for a decade or more, although a few will see gains in the next five years. But the potential is so great, and the technological advances are coming so rapidly, that every business leader should have a basic understanding of how the technology works, the kinds of problems it can help solve, and how she or he should prepare to harness its potential.
Quantum computing is a fundamentally different approach to computation compared with the kinds of calculations that we do on todays laptops, workstations, and mainframes. It wont replace these devices, but by leveraging the principles of quantum physics it will solve specific, typically very complex problems of a statistical nature that are difficult for current computers.
Classical computers are programmed with bits as data units (zeros and ones). Quantum computers use so-called qubits, which can represent a combination of both zero and one at the same time, based on a principle called superposition.
Its this difference that gives quantum computers the potential to be exponentially faster than todays mainframes and servers. Quantum computers can do multiple calculations with multiple inputs simultaneously. Todays computers can handle only one set of inputs and one calculation at a time. Working with a certain number of qubitslets say n for our examplea quantum computer can conduct calculations on up to 2n inputs at once.
That sounds crystal clear. But when you dig into the details of how a quantum computer actually works, you start to understand that many existing challenges must be solved before quantum computers deliver on that potential. (For more, see sidebar, Quantum computing versus classical computing.)
Some of these obstacles are technical. Qubits, for example, are volatile. Every bit in todays computers must be in a state of one or zero. A great deal of work goes into ensuring that one bit on a computer chip does not interfere with any other bit on that chip. Qubits, on the other hand, can represent any combination of zero and one. Whats more, they interact with other qubits. In fact, these interactions are what make it possible to conduct multiple calculations at once.
Controlling these interactions, however, is very complicated. The volatility of qubits can cause inputs to be lost or altered, which can throw off the accuracy of results. And creating a computer of meaningful scale would require hundreds of thousands or millions of qubits to be connected coherently. The few quantum computers that exist today can handle nowhere near that number.
Software and hardware companiesranging from start-ups youve never heard of to research institutes to the likes of Google, IBM, and Microsoftare trying to overcome these obstacles. Theyre working on algorithms that bear little resemblance to the ones we use today, hardware that may well wind up looking very different from todays gray boxes, and software to help translate existing data into a qubit-ready format. But they have a long way to go. Although quantum computing as a concept has been around since the early 1980s, the first real proof that quantum computers can handle problems too complicated for classical computers occurred only in late 2019, when Google announced that its quantum computer had solved such a calculation in just 200 seconds. But this was more of a mathematical exercise than anything that could be applied to businessthe problem had no real-world use at all.
Quantum computers will be used for different kinds of problems, incredibly complex ones where eliminating an enormous range of possibilities will save enormous time.
The nature of quantum mechanics also presents obstacles to exponential speed gains. Todays computers operate in a very straightforward fashion: they manipulate a limited set of data with an algorithm and give you an answer. Quantum computers are more complicated. After multiple units of data are input into qubits, the qubits are manipulated to interact with other qubits, allowing for a number of calculations to be done simultaneously. Thats where quantum computers are a lot faster than todays machines. But those gains are mitigated by the fact that quantum computers dont deliver one clear answer. Instead, users get a narrowed range of possible answers. In fact, they may find themselves conducting multiple runs of calculations to narrow the range even more, a process that can significantly lessen the speed gains of doing multiple calculations at once.
Getting a range rather than a single answer makes quantum computers sound less precise than todays computers. Thats true for calculations that are limited in scope, which is one reason quantum computers wont replace todays systems. Instead, quantum computers will be used for different kinds of problems, incredibly complex ones in which eliminating an enormous range of possibilities will save an enormous amount of time.
Quantum computers have four fundamental capabilities that differentiate them from todays classical computers: quantum simulation, in which quantum computers model complex molecules; optimization (that is, solving multivariable problems with unprecedented speed); quantum artificial intelligence (AI), with better algorithms that could transform machine learning across industries as diverse as pharma and automotive; and prime factorization, which could revolutionize encryption.
The best way to understand the business potential of quantum computing is to see how those capabilities could tackle a variety of use cases. Certain industries have specific problems that are particularly well suited to quantum computing. In total, weve reviewed more than 100 nascent use cases and found that they cover a wide range of problems and sectors, including pharmaceuticals, cybersecurity, finance, materials science, and telecommunications. Our research also suggests significant diversity in the development life cycle of these applications, and in the nature of business benefit they could confer. To paint a richer picture of these dynamics at work, lets consider four high-potential applications:
Scientists looking to develop new drugs and substances often need to examine the exact structure of a molecule to determine its properties and understand how it might interact with other molecules. Unfortunately, even relatively small molecules are extremely difficult to model accurately using classical computers, since each atom interacts in complex ways with other atoms. Currently, its almost impossible for todays computers to simulate basic molecules that have relatively few atomsand proteins, to cite just one example, have thousands of them. Thats why todays scientists are forced to actually create the molecules in question (using synthetic chemistry) to physically measure their properties. Often the molecule doesnt work as expected, entailing more synthesis and testing. Each optimization cycle is expensive and time-consuming. This is one reason why developing new drugs and chemicals is such a lengthy process.
Quantum computers are intrinsically well suited to tackle this problem, since the interaction of atoms within a molecule is itself a quantum system. In fact, experts believe that quantum computers will be able to model even the most complex molecules in our bodies. Every bit of progress in this direction will drive faster development of new drugs and other products, and potentially lead to transformative new cures.
Its almost impossible for todays computers to simulate basic molecules that have relatively few atoms. Quantum computers will be able to model even the most complex molecules.
Across every industry, many complex business problems involve a host of variables. Where should I place robots on the factory floor? Whats the shortest route for my delivery truck? Whats the most efficient way to deploy cars, motorcycles, and scooters to create a transportation network that meets user demand? How can I optimize the performance and risk of a financial portfolio? These are just three of the many examples that business leaders confront.
Solving these problems with classical computing is an arduous, hit-and-miss process. To isolate the inputs that drive performance gains or losses, the number of variables that can be shifted in any calculation must be seriously limited. As a result, companies must make one complicated calculation after another, a costly, time-consuming process given the multiplicity of variables. But, since quantum computers work with multiple variables simultaneously, they can be used first to dramatically narrow the range of possible answers in a very short time. Classical computing can then be called in to zero in on one precise answer, and its work will still seem slow compared with that of quantum. But, since quantum has eliminated so many possibilities, this hybrid approach will drastically cut the time it takes to find the best solution.
Quantum computers look radically different from todays gray box laptops, desktops, and servers.
Its possible that quantum computers could speed the arrival of self-driving vehicles. At Ford, GM, Volkswagen, and other car manufacturers, and at a host of start-ups in the new mobility sector, engineers are running hours upon hours of video, image, and lidar data through complex neural networks. Their goal: use AI to teach a car to make crucial driving decisions, such as how to take a turn, where to speed up and slow down, and, crucially, how to avoid other vehicles, not to mention pedestrians. Training an AI algorithm this way requires a set of computationally intensive calculations, which become increasingly difficult as more data and more complex relationships within the variables are added. This training can tax the worlds fastest computers for days or even months. Since quantum computers can perform multiple complex calculations with multiple variables simultaneously, they could exponentially accelerate the training of such AI systems. Its not going to happen anytime soon. Translating classical data sets to quantum ones is arduous work, and early quantum AI algorithms have resulted in only modest gains.
Quantum computing poses a serious threat to the cybersecurity systems relied on by virtually every company. Most of todays online-account passwords and secure transactions and communications are protected through encryption algorithms such as RSA or SSL/TLS. These systems make it easy for businesses to create data that can be shared by authorized users while also being protected from outsiders. Breaking through that encryption requires massive computational power. Its virtually impossible for todays computers to solve the math problem behind well-architected encryption quickly enough to be of practical use. (That math problem is known as prime factorization, since encryption is built around the manipulation of large prime numbers.) When data theft does occur, its often because of poor implementation of cybersecurity protocols.
Since quantum computers can perform multiple calculations simultaneously, they have the potential to break any classical encryption system. In fact, a quantum algorithm to do just that already exists. (Its called Shors algorithm.) Luckily, theres no quantum computer capable of managing the hundreds of thousands to millions of qubits it would take to execute Shors algorithmas we said earlier, todays versions can handle a dozen or so qubits. But somewhere between ten and 20 years from now, that might change, and at that point a new wave of quantum encryption technologies would be required to protect even our most basic online services. Scientistsas well as forward-thinking policy makersare already at work on this quantum cryptography, trying to prepare for this tipping point.
Quantum computing is a complex technology. Its not an app thats going to appear one day and be adopted by millions of people the next. After speaking with dozens of experts in the rapidly growing quantum ecosystem, weve developed a clear estimate of how the technology will progress over the next couple of decades.
Quantum computers will be expensive machines developed and operated by a few key players. Companies such as Google and IBM hope to double the capabilities of quantum computers, in a Moores lawlike fashion, every year. Along with a small but significant cohort of promising start-ups, they will steadily drive up the number of qubits that can be handled by their computers. Since the technology is nascent, their progress may be slow: our estimate is that by 2030 only 2,000 to 5,000 quantum computers will be operational. Since there are many pieces to the quantum-computing puzzle, the hardware and software needed to handle the most complex problems may not exist until 2035 or beyond.
Most businesses wont own a quantum computer. Instead, theyll get quantum services via the cloud.
Nevertheless, quantum will start delivering value to some businesses well before then. Initially, and perhaps in the long term as well, businesses will receive quantum services via the cloud from the same providers they rely on now. Amazon Web Services, Microsoft Azure, and others have already announced quantum offerings. These cloud offerings could quickly expand adoption and demand.
Between 2022 and 2026, we expect many businesses with optimization issues to adopt hybrid approaches, in which parts of the problem would be handled by classical computing and parts by quantum. In that same time frame, quantum computers are likely to become powerful enough to start handling meaningful simulations of molecular structures for chemical, materials, and pharmaceutical companies. The arrival of quantum AI is further off, and we dont expect quantum computers to be powerful enough for prime factorization until the very late 2020s at the earliest.
This timeline for the development of the technology informs our estimates of when different industries are likely to benefit most from quantum computing. The experts we spoke with expect that pioneers in advanced industries, global energy and materials, finance, and (to a lesser extent) travel and logistics might start generating significant value from quantum by 2025. The big payoff for pharmaceuticals may not come until the following decade, given that solving the most complex medical problems involves mimicking deeply complex molecules. As shown in the exhibit, by the mid-2030s a wide range of industries will have the potential to create significant value from quantum computing.
Exhibit
Obviously, preparing for major technological advances is a key part of any executives portfolio. Thats especially true for quantum, which has the potential to be greatly disruptive. By solving calculations that are impossible with classical computing, quantum could make explicit all kinds of currently implicit knowledge. This wouldnt just revolutionize processes; it could also radically alter the workforces of different industries.
In chemicals and pharmaceuticals, for example, todays synthetic chemists must create actual molecules or solids to test hypotheses about potential new drugs or materials. These substances often dont work as expected, which leads to further cycles of costly and time-consuming synthesis and testing. If quantum computers can model such substances exponentially faster, as expected, companies may well need fewer synthetic chemists. Its not hard to envision such mathematical certainty replacing the expertise and judgment of career professionals in other industries with multivariable problems, such as finance, insurance, transportation, and more.
Even though were unlikely to feel that kind of societal impact for decades, prescient business leaders in almost every industry should develop some kind of quantum strategy now. The kind of preparation depends on whether youre in the first wave of industries that can benefit from the technology, whether your business has use cases that map to the incipient strength of quantum, and whether you believe you might reap transformative or merely incremental gains.
We believe that industries such as finance, travel, logistics, global energy and materials, and advanced industries will start reaping significant value from the hybrid classical/quantum approach in the early 2020s. Business leaders in these first-wave sectors need to develop a quantum strategy quickly or they will be left behind by innovative companies such as Barclays, BASF, BMW, Dow, ExxonMobil, and others that already have taken strategic steps into quantum computing. These leaders should think about how their businesses can tap into the burgeoning quantum infrastructure. Some may want to get into the labor market now and hire quantum developers to build an in-house team to create algorithms that target pressing systemic problems. Quantum talent is in short supply right now, and its unlikely that research universities will be able to turn out enough top quantum engineers to keep up with the rapidly expanding demand.
Other first-wave companies may find it useful to partner directly with the technology companies developing quantum. We are in the early stages of a long process of adapting quantum to the needs of business, so companies still have the potential to influence that development in ways that serve their particular needs.
If you have business and trade secrets that you would want to keep secret for ten to 50 years, then you need to start worrying now.
Besides companies in these first-wave industries, theres another cohort that should actively monitor the progress of quantum. According to Louisiana State University professor Jonathan Dowling, If you have business and trade secrets that you would want to keep secret for ten to 50 years, then you need to start worrying now. Companies whose business depends on decades of data must be on high alert about the cybersecurity issues that quantum computing raises. At the very least, the topic should be at the top of the chief information officers agenda, and business leaders need to be confident that their companies have a plan for making a safe transition from current cryptography to quantum cryptography.
Even if your business doesnt fall into one of these two groups, quantum computing is a technology that your key technology experts should be monitoring. Quantum is not just an iterative technology that enables marginal improvements. It has the potential to be both transformative and disruptive. Technologies this potent can emerge at unpredictable speed and cause unpredictable impact. Business leaders who dont want to be caught unaware should start getting ready for quantum computing now.
Read more:
A game plan for quantum computing | McKinsey
Quantum computing use cases–what you need to know | McKinsey
Accelerating advances in quantum computingare serving as powerful reminders that the technology is rapidly advancing toward commercial viability. In just the past few months, for example, a research center in Japan announced a breakthrough in entangling qubits (the basic unit of information in quantum, akin to bits in conventional computers) that could improve error correction in quantum systems and potentially make large-scale quantum computers possible. And one company in Australia has developed software that has shown in experiments to improve the performance of any quantum-computing hardware.
As breakthroughs accelerate, investment dollars are pouring in, and quantum-computing start-ups are proliferating. Major technology companies continue to develop their quantum capabilities as well: companies such as Alibaba, Amazon, IBM, Google, and Microsoft have already launched commercial quantum-computing cloud services.
Of course, all this activity does not necessarily translate into commercial results. While quantum computing promises to help businesses solve problems that are beyond the reach and speed of conventional high-performance computers, use cases are largely experimental and hypothetical at this early stage. Indeed, experts are still debating the most foundational topics for the field (for more on these open questions, see sidebar, Debates in quantum computing).
Still, the activity suggests that chief information officers and other leaders who have been keeping an eye out for quantum-computing news can no longer be mere bystanders. Leaders should start to formulate their quantum-computing strategies, especially in industries, such as pharmaceuticals, that may reap the early benefits of commercial quantum computing. Change may come as early as 2030, as several companies predict they will launch usable quantum systems by that time.
To help leaders start planning, we conducted extensive research and interviewed 47 experts around the globe about quantum hardware, software, and applications; the emerging quantum-computing ecosystem; possible business use cases; and the most important drivers of the quantum-computing market. In the report Quantum computing: An emerging ecosystem and industry use cases, we discuss the evolution of the quantum-computing industry and dive into the technologys possible commercial uses in pharmaceuticals, chemicals, automotive, and financefields that may derive significant value from quantum computing in the near term. We then outline a path forward and how industry decision makers can start their efforts in quantum computing.
An ecosystem that can sustain a quantum-computing industry has begun to unfold. Our research indicates that the value at stake for quantum-computing players is nearly $80 billion (not to be confused with the value that quantum-computing use cases could generate).
Because quantum computing is still a young field, the majority of funding for basic research in the area still comes from public sources (Exhibit 1).
Exhibit 1
However, private funding is increasing rapidly. In 2021 alone, announced investments in quantum-computing start-ups have surpassed $1.7 billion, more than double the amount raised in 2020 (Exhibit 2). We expect private funding to continue increasing significantly as quantum-computing commercialization gains traction.
Exhibit 2
Hardware is a significant bottleneck in the ecosystem. The challenge is both technical and structural. First, there is the matter of scaling the number of qubits in a quantum computer while achieving a sufficient level of qubit quality. Hardware also has a high barrier to entry because it requires a rare combination of capital, experience in experimental and theoretical quantum physics, and deep knowledgeespecially domain knowledge of the relevant options for implementation.
Multiple quantum-computing hardware platforms are under development. The most important milestone will be the achievement of fully error-corrected, fault-tolerant quantum computing, without which a quantum computer cannot provide exact, mathematically accurate results (Exhibit 3).
Exhibit 3
Experts disagree on whether quantum computers can create significant business value before they are fully fault tolerant. However, many say that imperfect fault tolerance does not necessarily make quantum-computing systems unusable.
When might we reach fault tolerance? Most hardware players are hesitant to reveal their development road maps, but a few have publicly shared their plans. Five manufacturers have announced plans to have fault-tolerant quantum-computing hardware by 2030. If this timeline holds, the industry will likely establish a clear quantum advantage for many use cases by then.
The number of software-focused start-ups is increasing faster than any other segment of the quantum-computing value chain. In software, industry participants currently offer customized services and aim to develop turnkey services when the industry is more mature. As quantum-computing software continues to develop, organizations will be able to upgrade their software tools and eventually use fully quantum tools. In the meantime, quantum computing requires a new programming paradigmand software stack. To build communities of developers around their offerings, the larger industry participants often provide their software-development kits free of charge.
In the end, cloud-based quantum-computing services may become the most valuable part of the ecosystem and can create outsize rewards to those who control them. Most providers of cloud-computing services now offer access to quantum computers on their platforms, which allows potential users to experiment with the technology. Since personal or mobile quantum computing is unlikely this decade, the cloud may be the main way for early users to experience the technology until the larger ecosystem matures.
Most known use cases fit into four archetypes: quantum simulation, quantum linear algebra for AI and machine learning, quantum optimization and search, and quantum factorization. We describe these fully in the report, as well as outline questions leaders should consider as they evaluate potential use cases.
We focus on potential use cases in a few industries that research suggests could reap the greatest short-term benefits from the technology: pharmaceuticals, chemicals, automotive, and finance. Collectively (and conservatively), the value at stake for these industries could be between roughly $300 billion and $700 billion (Exhibit 4).
Exhibit 4
Quantum computing has the potential to revolutionize the research and development of molecular structures in the biopharmaceuticals industry as well as provide value in production and further down the value chain. In R&D, for example, new drugs take an average of $2 billion and more than ten years to reach the market after discovery. Quantum computing could make R&D dramatically faster and more targeted and precise by making target identification, drug design, and toxicity testing less dependent on trial and error and therefore more efficient. A faster R&D timeline could get products to the right patients more quickly and more efficientlyin short, it would improve more patients quality of life. Production, logistics, and supply chain could also benefit from quantum computing. While it is difficult to estimate how much revenue or patient impact such advances could create, in a $1.5 trillion industry with average margins in earnings before interest and taxes (EBIT) of 16 percent (by our calculations), even a 1 to 5 percent revenue increase would result in $15 billion to $75 billion of additional revenues and $2 billion to $12 billion in EBIT.
Quantum computing can improve R&D, production, and supply-chain optimization in chemicals. Consider that quantum computing can be used in production to improve catalyst designs. New and improved catalysts, for example, could enable energy savings on existing production processesa single catalyst can produce up to 15 percent in efficiency gainsand innovative catalysts may enable the replacement of petrochemicals by more sustainable feedstock or the breakdown of carbon for CO2 usage. In the context of the chemicals industry, which spends $800 billion on production every year (half of which relies on catalysis), a realistic 5 to 10 percent efficiency gain would mean a gain of $20 billion to $40 billion in value.
The automotive industry can benefit from quantum computing in its R&D, product design, supply-chain management, production, and mobility and traffic management. The technology could, for example, be applied to decrease manufacturing processrelated costs and shorten cycle times by optimizing elements such as path planning in complex multirobot processes (the path a robot follows to complete a task) including welding, gluing, and painting. Even a 2 to 5 percent productivity gainin the context of an industry that spends $500 billion per year on manufacturing costswould create $10 billion to $25 billion of value per year.
Finally, quantum-computing use cases in finance are a bit further in the future, and the advantages of possible short-term uses are speculative. However, we believe that the most promising use cases of quantum computing in finance are in portfolio and risk management. For example, efficiently quantum-optimized loan portfolios that focus on collateral could allow lenders to improve their offerings, possibly lowering interest rates and freeing up capital. It is earlyand complicatedto estimate the value potential of quantum computingenhanced collateral management, but as of 2021, the global lending market stands at $6.9 trillion, which suggests significant potential impact from quantum optimization.
In the meantime, business leaders in every sector should prepare for the maturation of quantum computing.
Until about 2030, we believe that quantum-computing use cases will have a hybrid operating model that is a cross between quantum and conventional high-performance computing. For example, conventional high-performance computers may benefit from quantum-inspired algorithms.
Beyond 2030, intense ongoing research by private companies and public institutions will remain vital to improve quantum hardware and enable moreand more complexuse cases. Six key factorsfunding, accessibility, standardization, industry consortia, talent, and digital infrastructurewill determine the technologys path to commercialization.
Leaders outside the quantum-computing industry can take five concrete steps to prepare for the maturation of quantum computing:
Leaders in every industry have an uncommon opportunity to stay alert to a generation-defining technology. Strategic insights and soaring business value could be the prize.
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Quantum computing use cases--what you need to know | McKinsey
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Classical computing is reaching its limit. Thus, there is a need to revolutionize the current form of computing. Towards this end, quantum computing is one of the promising computing paradigms. However, programming quantum computers differ significantly from classical computing due to novel features of quantum computing, such as superposition and entanglement. Thus, the Art, Science, and Engineering of Quantum Programming differ from classical programming.
Monday, April 17, 2023 to Wednesday, April 19, 2023
We are proud to be hosting the next Quantum Computing Theory in Practice (QCTIP) conference at Jesus College in Cambridge on 17-19 April 2023.
The conference will take place over 3 days, and together with our keynote speakers, poster sessions and invited talks, we will take stock of the newest developments in the field and map out the future of quantum computing. More details and further updates can be found at https://registration.qctip.com/qctip-2023
Thursday, December 15, 2022
Wednesday, December 14, 2022
We invite you to attend (online-only) Episode XLVI of the Warsaw Quantum Computing Group meetup!
On 15.12 at 18:00 UTC+1, Piotr Gawron will give a lecture on "Kernels, tensors, matrices and reservoirs the wild world of (Quantum) Machine Learning".
If you are interested, sign up by 14.12 (EOD UTC+1):https://docs.google.com/forms/d/e/1FAIpQLSdQfT2IK6twbiZJ8TIRYuQfyvUc2dHq...
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IBM Quantum roadmap to build quantum-centric supercomputers | IBM …
Two years ago, we issued our first draft of that map to take our first steps: our ambitious three-year plan to develop quantum computing technology, called our development roadmap. Since then, our exploration has revealed new discoveries, gaining us insights that have allowed us to refine that map and travel even further than wed planned. Today, were excited to present to you an update to that map: our plan to weave quantum processors, CPUs, and GPUs into a compute fabric capable of solving problems beyond the scope of classical resources alone.
Our goal is to build quantum-centric supercomputers. The quantum-centric supercomputer will incorporate quantum processors, classical processors, quantum communication networks, and classical networks, all working together to completely transform how we compute. In order to do so, we need to solve the challenge of scaling quantum processors, develop a runtime environment for providing quantum calculations with increased speed and quality, and introduce a serverless programming model to allow quantum and classical processors to work together frictionlessly.
But first: where did this journey begin? We put the first quantum computer on the cloud in 2016, and in 2017, we introduced an open source software development kit for programming these quantum computers, called Qiskit. We debuted the first integrated quantum computer system, called the IBM Quantum System One, in 2019, then in 2020 we released our development roadmap showing how we planned to mature quantum computers into a commercial technology.
As part of that roadmap, in 2021 we released our IBM Quantum broke the 100qubit processor barrier in 2021. Read more about Eagle.127-qubit IBM Quantum Eagle processor and launched Qiskit Runtime, a runtime environment of co-located classical systems and quantum systems built to support containerized execution of quantum circuits at speed and scale. The first version gave a In 2021, we demonstrated a 120x speedup in simulating molecules thanks to a host of improvements, including the ability to run quantum programs entirely on the cloud with Qiskit Runtime.120x speedup on a research-grade quantum workload. Earlier this year, we launched the Qiskit Runtime Services with primitives: pre-built programs that allow algorithm developers easy access to the outputs of quantum computations without requiring intricate understanding of the hardware.
Now, our updated map will show us the way forward.
In order to benefit from our world-leading hardware, we need to develop the software and infrastructure so that our users can take advantage of it. Different users have different needs and experiences, and we need to build tools for each persona: kernel developers, algorithm developers, and model developers.
For our kernel developers those who focus on making faster and better quantum circuits on real hardware well be delivering and maturing Qiskit Runtime. First, we will add dynamic circuits, which allow for feedback and feedforward of quantum measurements to change or steer the course of future operations. Dynamic circuits extend what the hardware can do by reducing circuit depth, by allowing for alternative models of constructing circuits, and by enabling parity checks of the fundamental operations at the heart of quantum error correction.
To continue to increase the speed of quantum programs in 2023, we plan to bring threads to the Qiskit Runtime, allowing us to operate parallelized quantum processors, including automatically distributing work that is trivially parallelizable. In 2024 and 2025, well introduce error mitigation and suppression techniques into Qiskit Runtime so that users can focus on improving the quality of the results obtained from quantum hardware. These techniques will help lay the groundwork for quantum error correction in the future.
However, we have work to do if we want quantum will find broader use, such as among our algorithm developers those who use quantum circuits within classical routines in order to make applications that demonstrate quantum advantage.
For our algorithm developers, well be maturing the Qiskit Runtime Services primitives. The unique power of quantum computers is their ability to generate non-classical probability distributions at their outputs. Consequently, much of quantum algorithm development is related to sampling from, or estimating properties of these distributions. The primitives are a collection of core functions to easily and efficiently work with these distributions.
Typically, algorithm developers require breaking problems into a series of smaller quantum and classical programs, with an orchestration layer to stitch the data streams together into an overall workflow. We call the infrastructure responsible for this stitching To bring value to our users, we need our programing model to fit seamlessly into their workflows, where they can focus on their code and not have to worry about the deployment and infrastructure. We need a serverless architecture.Quantum Serverless. Quantum Serverless centers around enabling flexible quantum-classical resource combinations without requiring developers to be hardware and infrastructure experts, while allocating just those computing resources a developer needs when they need them. In 2023, we plan to integrate Quantum Serverless into our core software stack in order to enable core functionality such as circuit knitting.
What is circuit knitting? Circuit knitting techniques break larger circuits into smaller pieces to run on a quantum computer, and then knit the results back together using a classical computer.
Earlier this year, we demonstrated a circuit knitting method called entanglement forging to double the size of the quantum systems we could address with the same number of qubits. However, circuit knitting requires that we can run lots of circuits split across quantum resources and orchestrated with classical resources. We think that parallelized quantum processors with classical communication will be able to bring about quantum advantage even sooner, and a recent paper suggests a path forward.
With all of these pieces in place, well soon have quantum computing ready for our model developers those who develop quantum applications to find solutions to complex problems in their specific domains. We think by next year, well begin prototyping quantum software applications for specific use cases. Well begin to define these services with our first test case machine learning working with partners to accelerate the path toward useful quantum software applications. By 2025, we think model developers will be able to explore quantum applications in machine learning, optimization, natural sciences, and beyond.
Of course, we know that central to quantum computing is the hardware that makes running quantum programs possible. We also know that a quantum computer capable of reaching its full potential could require hundreds of thousands, maybe millions of high-quality qubits, so we must figure out how to scale these processors up. With the 433-qubit Osprey processor and the 1,121-qubit Condor processors slated for release in 2022 and 2023, respectively we will test the limits of single-chip processors and controlling large-scale quantum systems integrated into the IBM Quantum System Two. But we dont plan to realize large-scale quantum computers on a giant chip. Instead, were developing ways to link processors together into a modular system capable of scaling without physics limitations.
To tackle scale, we are going to introduce three distinct approaches. First, in 2023, we are introducing Heron: a 133-qubit processor with control hardware that allows for real-time classical communication between separate processors, enabling the knitting techniques described above. The second approach is to extend the size of quantum processors by enabling multi-chip processors. Crossbill, a 408 qubit processor, will be made from three chips connected by chip-to-chip couplers that allow for a continuous realization of the heavy-hex lattices across multiple chips. The goal of this architecture is to make users feel as if theyre just using just one, larger processor.
Along with scaling through modular connection of multi-chip processors, in 2024, we also plan to introduce our third approach: quantum communication between processors to support quantum parallelization. We will introduce the 462-qubit Flamingo processor with a built-in quantum communication link, and then release a demonstration of this architecture by linking together at least three Flamingo processors into a 1,386-qubit system. We expect that this link will result in slower and lower-fidelity gates across processors. Our software needs to be aware of this architecture consideration in order for our users to best take advantage of this system.
Our learning about scale will bring all of these advances together in order to realize their full potential. So, in 2025, well introduce the Kookaburra processor. Kookaburra will be a 1,386 qubit multi-chip processor with a quantum communication link. As a demonstration, we will connect three Kookaburra chips into a 4,158-qubit system connected by quantum communication for our users.
The combination of these technologies classical parallelization, multi-chip quantum processors, and quantum parallelization gives us all the ingredients we need to scale our computers to wherever our roadmap takes. By 2025, we will have effectively removed the main boundaries in the way of scaling quantum processors up with modular quantum hardware and the accompanying control electronics and cryogenic infrastructure. Pushing modularity in both our software and our hardware will be key to achieving scales well ahead of our competitors, and were excited to deliver it to you.
Our updated roadmap takes us as far as 2025 but development wont stop there. By then, we will have removed some of the biggest roadblocks in the way of scaling quantum hardware, while developing the tools and techniques capable of integrating quantum into computing workflows. This sea change will be the equivalent of replacing paper maps with GPS satellites as we navigate into the quantum future.
This sea change will be the equivalent of replacing paper maps with GPS satellites.
We arent just thinking about quantum computers, though. Were trying to induce a paradigm shift in computing overall. For many years, CPU-centric supercomputers were societys processing workhorse, with IBM serving as a key developer of these systems. In the last few years, weve seen the emergence of AI-centric supercomputers, where CPUs and GPUs work together in giant systems to tackle AI-heavy workloads.
Now, IBM is ushering in the age of the quantum-centric supercomputer, where quantum resources QPUs will be woven together with CPUs and GPUs into a compute fabric. We think that the quantum-centric supercomputer will serve as an essential technology for those solving the toughest problems, those doing the most ground-breaking research, and those developing the most cutting-edge technology.
We may be on track, but exploring uncharted territory isnt easy. Were attempting to rewrite the rules of computing in just a few years. Following our roadmap will require us to solve some incredibly tough engineering and physics problems.
But were feeling pretty confident weve gotten this far, after all, with the new help of our world-leading team of researchers, the IBM Quantum Network, the Qiskit open source community, and our growing community of kernel, algorithm, and model developers. Were glad to have you all along for the ride as we continue onward.
Quantum Chemistry: Few fields will get value from quantum computing as quickly as chemistry. Even todays supercomputers struggle to model a single molecule in its full complexity. We study algorithms designed to do what those machines cant.
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IBM Quantum roadmap to build quantum-centric supercomputers | IBM ...
How quantum computing could change the world | McKinsey & Company
June 25, 2022Quantum computing, an emerging technology that uses the laws of quantum mechanics to produce exponentially higher performance for certain types of calculations, offers the possibility of major breakthroughs across sectors. Investors also see these possibilities: Funding of start-ups focused on quantum technologies more than doubled to $1.4 billion in 2021 from 2020. Quantum computing now has the potential to capture nearly $700 billion in value as early as 2035, with that market estimated to exceed $90 billion annually by 2040. That said, quantum computings more powerful computers could also one day pose a cybersecurity risk. To learn more, dive deeper into these topics:
Quantum computing funding remains strong, but talent gap raises concern
Quantum computing use cases are getting realwhat you need to know
Quantum computing just might save the planet
How quantum computing can help tackle global warming
How quantum computing could change financial services
Pharmas digital Rx: Quantum computing in drug research and development
Will quantum computing drive the automotive future?
A quantum wake-up call for European CEOs
Whenand howto prepare for post-quantum cryptography
Leading the way in quantum computing
Redefine your career at QuantumBlack
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How quantum computing could change the world | McKinsey & Company
One of the First Quantum Computers Produced in Europe To Be Launched in Poland – HPCwire
The new systems based on European technology will be available for R&D purposes to a wide range of European users, the scientific communities, industry and the public sector. The selected proposals ensure diversity in the quantum technologies and architectures to give European users an opportunity to test several different practical implementations of quantum computing systems connected with classical supercomputers and provided by dark fibers owned by PIONIER Polish Optical Internet.
Pozna Supercomputing and Networking Center (PSNC) affiliated to theInstitute of Bioorganic Chemistry, Polish Academy of Sciences (PAS)in Pozna, is the coordinator and initiator of the Polish project as well as the installation site. The project consortium also includes the Center for Theoretical Physics PAS and a Polish company:Creotech Instruments S.A.
The major factor that determined our decision to apply in the EuroQCS call was the fact that we would be able to install a quantum computer whose key components are provided by a Polish company: Creotech Instruments S.A. Our talks with dedicated radio astronomers and physicists resulted in a quick and unanimous decision that Poland has a chance to take an active position on the quantum map of Europe, explains Cezary Mazurek, PhD Eng., Director of PSNC.
The leading Polish provider of specialized electronics for the quantum market, Creotech Instruments has been selected as one of the organizations to develop a quantum computer in Poland. Parallel to this project, the Creotech team also is currently involved in the development of the first large quantum computer for the European Commission. The implementation of this project is proceeding according to plan. A few days ago, the company concluded a 4-year framework agreement with the European Commission giving it access to financing tools to achieve the latter projects goals.
I am proud to see that once again the expertise of our Creotech experts has been recognized by the international community, setting us apart from other companies from the domestic Deep Tech market. Our team will be tasked with delivering specialized control and measurement electronics in the infrastructure of the Polish quantum computer integrated with the infrastructure of the PSNC supercomputer located in Pozna, Poland. There are many important computing tasks that classical supercomputers have been struggling with for years in scientific communities. Quantum computers, including those developed as part of the current project, will address this very issue. The infrastructures deployment in Poland will translate into the long-term industrial, scientific and even social development of our country, says Grzegorz Brona, PhD, President of the Management Board of Creotech Instruments S.A.
The key partner in the project is theCenter for Theoretical Physics which brings together researchers from various fields that are essential for the development and application of quantum computations, including experts in theoretical physics, astrophysics and natural sciences: classical and quantum field theory, quantum optics, basics of quantum mechanics and quantum information theory. Quantum technologies are also a significant area of R&D work performed by theUniversity of Latviawhich boasts several highly ranked research groups in quantum physics. International expert teams in collaboration with PSNC will be responsible for developing hybrid classical-quantum algorithms and mechanisms to allow users throughout Europe to access and use the resources of the new quantum computer.
Quantum computations leveraging the support of PSNCs supercomputing infrastructure and HPC technology will facilitate a range of scientific research and open up new opportunities for industrial innovation. It is worth noting that the selection of the six European sites to host a quantum computer coincided with the announcement of the winners of this years Nobel Prize in Physics, Alain Aspect, John F. Clauser and Anton Zeilinger for their work in quantum mechanics and quantum information science.
Choosing Poland and our center as one of the six European locations for this breakthrough classical-quantum supercomputer architecture shows that we have met all the entry criteria and have the relevant experience to build such a hybrid. For many years, PSNC has been Polands representative in the PRACE (Partnership in Advanced Computing in Europe) initiative and has been implementing strategic projects from the Polish Roadmap for Research Infrastructures, including the PRACE-LABandPRACE-LAB2national supercomputing systems. We are very pleased to have managed to not only build a strong project consortium in partnership with the Polish scientific community and our business partner, Creotech Instruments, but also to involve experts specializing in quantum technologies from the Central and Eastern Europe region, including Latvia, Lithuania, Slovenia, Hungary and Austria, says Krzysztof Kurowski, PhD Eng. from PSNC.
It is also important to mention that another project submitted as part of the EuroHPC call to develop a quantum computer LUMI-Q in Czechia features other two Polish entities:Academic Computer Centre Cyfronet AGHandNicolaus Copernicus Astronomical Center PAS, making it a total of five Polish institutions engaged in EuroQCS.
At the moment, the realization and financing plans regarding all six projects are being formally discussed. A total of 17 UE states will contribute to the quantum initiative.
Source: PSNC
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One of the First Quantum Computers Produced in Europe To Be Launched in Poland - HPCwire
There’s a New Quantum Computing Record: Control of a 6-Qubit Processor in Silicon – ScienceAlert
Another record has been broken on the way to fully operational and capable quantum computers: the complete control of a 6-qubit quantum processor in silicon.
Researchers are calling it "a major stepping stone" for the technology.
Qubits (or quantum bits) are the quantum equivalents of classical computing bits, only they can potentially process much more information. Thanks to quantum physics, they can be in two states at once, rather than just a single 1 or 0.
The difficulty is in getting a lot of qubits to behave as we need them to, which is why this jump to six is important. Being able to operate them in silicon the same material used in today's electronic devices makes the technology potentially more viable.
"The quantum computing challenge today consists of two parts," says quantum computing researcher Stephan Philips from the Delft University of Technology in the Netherlands. "Developing qubits that are of good enough quality, and developing an architecture that allows one to build large systems of qubits."
"Our work fits into both categories. And since the overall goal of building a quantum computer is an enormous effort, I think it is fair to say we have made a contribution in the right direction."
The qubits are made from individual electrons fixed in a row, 90 nanometers apart (a human hair is around 75,000 nanometers in diameter). This line of 'quantum dots' is placed in silicon, using a structure similar to the transistors used in standard processors.
By making careful improvements to the way the electrons were prepared, managed, and monitored, the team was able to successfully control their spin the quantum mechanical property that enables the qubit state.
The researchers were also able to create logic gates and entangle systems of two or three electrons, on demand, with low error rates.
Researchers used microwave radiation, magnetic fields, and electric potentials to control and read electron spin, operating them as qubits, and getting them to interact with each other as required.
"In this research, we push the envelope of the number of qubits in silicon, and achieve high initialization fidelities, high readout fidelities, high single-qubit gate fidelities, and high two-qubit state fidelities," says electrical engineer Lieven Vandersypen, also from the Delft University of Technology.
"What really stands out though is that we demonstrate all these characteristics together in one single experiment on a record number of qubits."
Up until this point, only 3-qubit processors have been successfully built in silicon and controlled up to the necessary level of quality so we're talking about a major step forward in terms of what's possible in this type of qubit.
There are different ways of building qubits including on superconductors, where many more qubits have been operated together and scientists are still figuring out the method that might be the best way forward.
The advantage of silicon is that the manufacturing and supply chains are all already in place, meaning the transition from a scientific laboratory to an actual machine should be more straightforward. Work continues to keep pushing the qubit record even higher.
"With careful engineering, it is possible to increase the silicon spin qubit count while keeping the same precision as for single qubits," says electrical engineer Mateusz Madzik from the Delft University of Technology.
"The key building block developed in this research could be used to add even more qubits in the next iterations of study."
The research has been published in Nature.
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There's a New Quantum Computing Record: Control of a 6-Qubit Processor in Silicon - ScienceAlert
Nobel Prize in Physics goes to scientists who paved the way for quantum computing – Space.com
Three scientists who laid the groundwork for the understanding of the odd "entangling" behavior of quantum particles have received the 2022 Nobel Prize in Physics.
French physicist Alain Aspect, Austria's Anton Zeilinger and American John Clauser were honored for their experiments exploring the nature of entangled quantum particles.
Defying the logic of our everyday reality, such particles behave like a single unit even when they are far away from each other. Engineers are currently working on harnessing this odd behavior in a range of revolutionary technologies, including quantum computing and quantum cryptography, a supposedly unbreakable technique of secure information coding.
The beginning of quantum theory dates back to the great physicists of the early 20th century, including Albert Einstein and Niels Bohr. But the generation represented by the three new Nobel Prize laureates bridged the gap between theory and practical experiments and applications.
Related: 10 mind-boggling things you should know about quantum physics
"Quantum information science is a vibrant and rapidly developing field. It has a broad range of potential implications in areas such as secure information transfer, quantum computing and sensing technology," Eva Olsson, a member of the Nobel Committee for Physics, said in a news conference on Tuesday(Oct.4). "This year's Nobel Prize in Physics honors the groundbreaking work and science of the central figures who took up the challenges and tackled them in laboratories."
One of the most mature applications of quantum technology is quantum cryptography, which takes advantage of the fact that changes made to one particle in an entangled system affect the other. Encryption keys to secret messages can therefore be encoded into the quantum states of such particles. These keys can be exchanged between the parties in the communication process securely, because any interception of the secret keys by a third party would inherently change the particles' quantum state and render the keys invalid.
Quantum key distribution via satellites was first demonstrated by China in 2016 as part of its Quantum Experiments at Space Scale project. Countries all over the world have since begun developing similar technologies.
Perhaps the most high-profile application of entangled quantum particles is in the nascent field of quantum computing. Quantum computers encode information into the quantum states of particles, which can lead to giant leaps in the speed of information processing.
Scientists believe that, once up and running, quantum computers will accelerate drug research, material science and lead to improvements in climate change modeling and weather forecasting, among other benefits.
"It has become increasingly clear that a new kind of quantum technology is emerging," Anders Irbck, chair of the Nobel Committee for Physics, said in a statement. "We can see that the laureates' work with entangled states is of great importance, even beyond the fundamental questions about the interpretation of quantum mechanics."
"This prize demonstrates the fundamental beauty of physics," Penelope Lewis, the chief publishing officer of the American Institute of Physics' publishing department, commented in a statement. "With their pioneering experiments in quantum entanglement, Aspect, Clauser, and Zeilinger brought quantum mechanics out of its philosophical beginnings dating back nearly a century and into the present day. Their experiments laid the groundwork for incredible advances in quantum computing and cryptography, technologies with the potential to transform the modern world."
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Nobel Prize in Physics goes to scientists who paved the way for quantum computing - Space.com