Category Archives: Quantum Computing

Kate Platonova, Chief Data and Architecture Officer, HSBC

Those organisations who were more invested in cloud tended to fare better at the start of the Coronavirus pandemic in early 2020. One example is HSBC, which uses a range of cloud technology to provide "scalability, resilience and innovation," in the words ofKate Platonova, Chief Data and Architecture Officer at the bank.

She told Computing that the organisation uses as hybrid cloud model.

"We use a hybrid cloud model, so we have strategic partnerships with all three of the major public cloud providers; Google, AWS and Azure. We also consume a range of Software as a Service (SaaS) solutions from a mix of providers. Whichever cloud provider we use, we maintain the same high level of standards for security and resilience."

The choice around which platform to use for each need is made on a case by case basis.

"We select the cloud providers and services based on the best strategic fit for the particular workload. Our priorities are to always ensure we provide a secure environment, protect customer data, maintain service continuity and comply with all relevant policies and regulations globally," said Platonova.

Whilst, like everyone else HSBC was unable to predict the pandemic, it did manage to roll out the tools to enable remote collaboration at a rapid pace.

"At the beginning of 2020, 64 per cent of HSBC's global workforce were able to work remotely - and in a matter weeks our IT teams increased this to 85 per cent. To better support virtual meetings, Zoom was rolled out in 12 weeks - and in January 13 million people attended 4.3 million HSBC meetings on Zoom. 63,000 users in the UK, US and Hong Kong are finding it easier to collaborate using Microsoft Teams and last year over 20,000 laptops were delivered to colleagues at home."

Platinova adds that regular communication has been key to ensuring staff wellbeing, as well as productivity.

"Throughout the pandemic, the wellbeing of our people has been our paramount concern. We have taken steps to enable our front-line colleagues to do their jobs safely and effectively. For all our colleagues, we have maintained a regular flow of communication and listened closely to their needs (including through a specific wellbeing survey to identify priority areas to address), providing the support and flexibility to help them manage their lives during the pandemic."

Another common concern during these times of mass remote working has been security, with potentially compromised personal devices connecting to corporate networks in numbers never seen before. HSBC has used a number of strategies to mitigate these risks, in part sending out secure devices to staff.

"212,000 secure HSBC laptops and desktop PCs are currently being used by colleagues working remotely. And 60,000 colleagues are working using HSBC Virtual Connect - allowing them to securely connect in a number of ways, including from personal Windows and Mac devices. Our BYOD mobile service allows colleagues to securely access their work email, calendar and join Zoom meetings from any supported mobile device."

Stepping away from the pandemic, the organisation continues to invest in the future, with its sights firmly set on exploiting quantum computing.

"We are excited about the potential benefits of quantum computing in banking for solving resource intensive problems and improving customer experience. We think applications could include risk analytics, machine learning and cybersecurity. We're part of the European NEASQC (Next Applications of Quantum Computing) project to explore potential applications for quantum computing within the banking industry."

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Keeping a major bank going during the pandemic: Interview with Kate Platonova, Chief Data and Architecture Officer, HSBC - http://www.computing.co.uk

Scientists and engineers at the University of Sydney and Microsoft Corporation have developed a device that can handle thousands of qubits. To put things in perspective, the current state-of-the-art quantum computer can control only 50 qubits at a time.

Scaled-up quantum computers require control interfaces to manipulate or readout a large number of qubits, which usually operate at temperatures close to absolute zero (1 Kelvin or -273 degrees celsius).

The complementary metal-oxide-semiconductor (CMOS) technology has its limitations due to high thermodynamic dissipation, leading to heating of the fragile quantum bits. Overheating of quantum bits compromises its quantumness, the property of being in two states at the same time (also called superposition).

The current architecture uses multiple connections as every qubit is controlled by external circuitry with a separate electrical connection, generating a lot of heat.

The scientists from the University of Sydney built a CMOS interface between the qubits and the external circuitry, in such a way that the CMOS chip can generate control pulses for multiple qubits, with just four low-bandwidth wires, at 0.1 Kelvin, a temperature 30 times colder than deep space, with ultralow power dissipation.

The interface consists of four low-bandwidth wires at room temperature to provide input signals to the chip, which then configures 32 analogue circuit blocks to control the qubits that use dynamic voltage signals.

Analogue circuit boards use the low leakage of the transistors to generate dynamic voltage signals for manipulating qubits, consuming significantly less power.

Quantum computers are at a similar stage that classical computers were in their 40s when machines needed control rooms to function.

However, this chip, according to the scientists, is the most advanced integrated circuit ever built to operate at deep cryogenic temperatures.

The quantum computers that we have now are still lab prototypes and are not commercially relevant yet. Hence, this is definitely a big step towards building practical and commercially relevant quantum computers, said Mr Viraj Kulkarni, But I think that we are still far away from it.

This is because of the Error Correction. Any computing device always has errors in it and no electronic device can be completely perfect. There are various techniques that computers use to correct those errors.

Now the problem with quantum computing is that qubits are very fragile. Even a slight increase in temperature, vibrations, or even cosmic rays can make qubits lose their quantumness, and this introduces errors. So the key question of whether we can really control these errors is still relevant.

Nivedita Dey, research coordinator at Quantum Research and Development Labs, said the qubit noise is still a roadblock in developing quantum computers.

One of the biggest challenges in implementing a quantum circuit in this Noisy Intermediate Scale Quantum (NISQ) era is qubit noise, which causes hindrance in commercial availability of fault-tolerant full-scale quantum computers, said Ms Dey.

This approach can be well suited for practical quantum applications and might reduce the number of error-correcting qubits to be associated with noisy qubits, she added.

If quantum computing does prove to be commercially viable, it will open up completely new avenues.

A plane is not just faster than a car, it can also fly, said Mr Kulkarni, drawing an analogy between quantum computers and conventional computers. The idea is that quantum computers are not just faster, but at the same time will provide us with solutions that are better, especially in AI.

Hence, many applications in AI including complex mathematical equations, drug discovery by enabling chemical simulations, or building financial applications to come up with a better strategy will be solved in a faster and efficient way.

In the end its a tool, so any function a conventional computer can achieve, quantum computers will be able to do it faster and better.

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Microsoft Scientists Build Chip That Can Handle Thousands Of Qubits - Analytics India Magazine

Computer scientists have achieved a quantum computing breakthrough that makes it possible to massively scale up the ultra-powerful machines.

A team of researchers from Microsoft and the University of Sydney invented a chip, dubbed Gooseberry, that can support thousands of qubits the building blocks of quantum computers while operating at temperatures close to absolute zero.

Qubits replace the traditional bits found in current computer systems, which use 1s and 0s to store and transfer data. By acting in a state of superposition, qubits are able to act as both a 1 and a 0 at the same time, allowing quantum computers to achieve processing power that is exponentially more powerful than traditional computers.

To realise the potential of quantum computing, machines will need to operate thousands, if not millions, of qubits, said Professor David Reilly from the University of Sydney, who was chief investigator of the research.

The worlds biggest quantum computers currently operate with just 50 or so qubits. This small scale is partly because of limits to the physical architecture that control the qubits. Our new chip puts an end to those limits.

The research is published in the journal Nature Electronics.

Qubits need to be stored at temperatures that are 40 times colder than deep space in order to function, with current systems relying on cables connected to each individual qubit stored a these extreme temperatures.

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The cryogenic Gooseberry chip disrupts this architectural approach by generating control signals for thousands of qubits in a single place, while requiring only two wires to communicate with the rest of the system.

Current machines create a beautiful array of wires to control the signals; they look like an inverted gilded birds nest or chandelier, Professor Reilly said.

Theyre pretty, but fundamentally impractical. It means we cant scale the machines up to perform useful calculations. There is a real input-output bottleneck.

Building a quantum computer is perhaps the most challenging engineering task of the 21st century Through our partnership with Microsoft, we havent just suggested a theoretical architecture to overcome the input-output bottleneck, weve built it.

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Quantum computing breakthrough uses cryogenics to scale machines to thousands of times their current size - The Independent

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.

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This company is using quantum-inspired algorithms to help create the OLED displays of the future - ZDNet

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

Over the next few years the tech industry has a roadmap to overcome the challenges facing quantum computing. This will pave the way to growth in mainstream quantum computing to solve hard problems.

There are numerous opportunities, from finding a cure for cancer to the development of new, more sustainable materials and tackling climate change. But a recent short film on quantum ethics has highlighted the risks, which may be as profound as the Manhattan Project that led to two atomic bombs being dropped on Hiroshima and Nagasaki in 1945.

One interviewee featured in the film, Ilana Wisby, CEO, Oxford Quantum Circuits said: We wont fully understand the impact of what we have until we have got the systems, but it will be revolutionising and will be lucrative for some.

The experts discussed the need for a debate across society to assess and appreciate the risk quantum computing will pose. Ilyas Khan, CEO Cambridge Quantum Computing said: We may be able to shift the boundaries of what can and cannot be done with machines.

Faye Wattleton, co-found EeroQ Quantum urged the innovators and policy makers to take a step back to consider the implications and its impact on humanity. If we can do in a few minutes what it would take 10,000 years to do with current technology then that requires careful consideration. From a societal perspective, what does this kind of power mean?

Just because a quantum computer makes it possible to solve an insoluble problem, does not mean it should be solved.

In the past, there was oversight and governance of technological breakthroughs like the printing press, which paved the way to mass media and the railways, which led to mass transit. But IT has become arrogant. Its proponents say that it moves far too quickly to be restrained by a regulatory framework. As an expert at a recent House of Lords Select Committee meeting warned, policy-makers are not very good at looking ahead at the long term impact of a new technological development. In the 1990s, who would have considered that the growth of the internet, social media and mobile phones would be a stimulant for fake news and a catalyst for rogue states to influence elections in other countries.

Khan describes the lack of controls on the internet like being asleep at the wheel. What are the implications of a quantum computing society? Perhaps, as Khan, says, society need to anticipate these issues, instead of being asleep at the wheel again.

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The risk of giving in to quantum progress - ComputerWeekly.com

CHICAGO, Feb. 2, 2021 /PRNewswire/ -- According to the new market research report "Quantum Computing Marketwith COVID-19 impact by Offering (Systems and Services), Deployment (On Premises and Cloud Based), Application, Technology, End-use Industry and Region - Global Forecast to 2026", published by MarketsandMarkets, the market is expected to grow from USD 472 million in 2021 to USD 1,765 million by 2026, at a CAGR of 30.2%. The early adoption of quantum computing in the banking and finance sector is expected to fuel the growth of the market globally. Other key factors contributing to the growth of the quantum computing market include rising investments by governments of different countries to carry out research and development activities related to quantum computing technology. Several companies are focusing on the adoption of QCaaS post-COVID-19. This, in turn, is expected to contribute to the growth of the quantum computing market. However, stability and error correction issues is expected to restrain the growth of the market.

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Services segment is attributed to hold the largest share of the Quantum Computing market

The growth of services segment can be attributed to the increasing number of startups across the world that are investing in research and development activities related to quantum computing technology. This technology is used in optimization, simulation, and machine learning applications, thereby leading to optimum utilization costs and highly efficient operations in various end-use industries.

Cloud based deployment to witness the highest growth in Quantum Computing market in coming years

With the development of highly powerful systems, the demand for cloud-based deployment of quantum computing systems and services is expected to increase. This, in turn, is expected to result in a significant revenue source for service providers, with users paying for access to noisy intermediate-scale quantum (NISQ) systems that can solve real-world problems. The limited lifespan of rapidly advancing quantum computing systems also favors cloud service providers. The flexibility of access offered to users is another factor fueling the adoption of cloud-based deployment of quantum computing systems and services. For the foreseeable future, quantum computers are expected not to be portable. Cloud can provide users with access to different devices and simulators from their laptops.

Optimization accounted for a major share of the overall Quantum Computing market

Optimization is the largest application for quantum computing and accounted for a major share of the overall Quantum Computing market. Companies such as D-Wave Systems, Cambridge Quantum Computing, QC Ware, and 1QB Information Technologies are developing quantum computing systems for optimization applications. Networked Quantum Information Technologies Hub (NQIT) is expanding to incorporate optimization solutions for resolving problems faced by the practical applications of quantum computing technology.

Trapped ions segment to witness highest CAGR of Quantum Computing market during the forecast period

The trapped ions segment of the market is projected to grow at the highest CAGR during the forecast period as quantum computing systems based on trapped ions offer more stability and better connectivity than quantum computing systems based on other technologies. IonQ, Alpine Quantum Technologies, and Honeywell are a few companies that use trapped ions technology in their quantum computing systems.

Browsein-depth TOC on"Quantum Computing Market"

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Banking and finance is attributed to hold major share of Quantum Computing market during the forecast period

In the banking and finance end-use industry, quantum computing is used for risk modeling and trading applications. It is also used to detect the market instabilities by identifying stock market risks and optimize the trading trajectories, portfolios, and asset pricing and hedging. As the financial sector is difficult to understand; the quantum computing approach is expected to help users understand the complexities of the banking and finance end-use industry. Moreover, it can help traders by suggesting them solutions to overcome financial challenges.

APAC to witness highest growth of Quantum Computing market during the forecast period

APAC region is a leading hub for several industries, including healthcare and pharmaceuticals, banking and finance, and chemicals. Countries such as China, Japan, and South Korea are the leading manufacturers of consumer electronics, including smartphones, laptops, and gaming consoles, in APAC. There is a requirement to resolve complications in optimization, simulation, and machine learning applications across these industries. The large-scale development witnessed by emerging economies of APAC and the increased use of advanced technologies in the manufacturing sector are contributing to the development of large and medium enterprises in the region. This, in turn, is fueling the demand for quantum computing services and systems in APAC.

In APAC, the investments look promising, as most countries such as China, Japan, and South Korea have successfully contained the virus compared with the US and European countries. China is easing the restrictions placed on factory lockdowns and worker movement. Despite being the epicenter of COVID-19, China has maintained its dominant position as a global network leader.

The Quantum Computing market was dominated by International Business Machines (US), D-Wave Systems (Canada), Microsoft (US), Amazon (US), and Rigetti Computing (US).

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Quantum Computing Market worth $1,765 million by 2026 - Exclusive Report by MarketsandMarkets - PRNewswire

BMW is starting to embrace quantum computing to optimize its supply chains. The automaker has started testing Honeywell systems to help it determine the best components to buy at the right time without disrupting production. While one supplier might be able to deliver components faster, similar parts might be cheaper from another supplier at the same time, as CNET notes. The new Honeywell H1 machine can determine the most optimal selections from the available choices.

Tracking the availability and pricing of components from a variety of suppliers can be a complex task, especially for traditional computers, so BMW is hoping that the quantum approach can help it to improve its manufacturing processes. It's not the first automaker to test quantum computing. Volkswagen has tried using the technology to develop better traffic management systems.

Elsewhere, BMW has announced entry-level plug-in hybrid versions of the 3 Series and 5 Series. After the 320e and 530e become available in March, the automaker will have 15 BMW models and one Mini with plug-in hybrid drive in its lineup.

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BMW tries to get ahead of its supply curve using quantum computing - Engadget

CONNIE ZHOU

It's fitting that one of the coolest quantum computing projects going has an equally cool name.Goldeneyeis IBM's internal codename for the world's largest dilution refrigerator, which will house a future 1,000,000 qubit quantum processor.

In September 2020, IBM debuted a detailed roadmap about how it will scale its quantum technology in the next three years to reach the true quantum industry inflection point of Quantum Advantage -- the point at which quantum systems will be more powerful than today's conventional computing.

But there's a catch: You can't do anything in quantum without incredibly low temperatures.

To reach this 'moon landing' moment, the IBM team developed the largest dilution refrigerator, which will house a future 1,000,000 qubit system. Work is underway to reach the goal of quantum computer capable of surpassing conventional machines by 2023, and this 10-foot-tall and 6-foot-wide "super-fridge" is a key ingredient, capable of reaching temperatures of 15 millikelvin, which is colder than outer space. The fridge gets so cold it takes between 5 and 14 days to cool down.

I caught up withJerry Chow, Director of Quantum Hardware System Development for IBM, to learn about the Herculean project and to find out what's next for IBM's quantum computing ambitions.

Let's start with the basics: Why is a super-fridge necessary for useful quantum computing and what advances in the last decade or so have aided that effort?

Superconducting qubits need to be cooled down to between 10-15 millikelvin for their quantum behavior to emerge. They need to be kept that cold to ensure that their performance is high. Dilution refrigeration technology, which has been around for a really long time, is an enabling technology specifically for superconducting qubits for quantum computing. Whereas a different type of qubit might require its own unique set of hardware and infrastructure.

Around 2010, cryogen-free dilution refrigerators became en vogue. These didn't require transferring and refilling liquid cryogenic helium every other day to keep these refrigerators cold. In fact, my PhD at Yale was completed entirely at the time when we were still experimenting on what we call "wet" dilution refrigerators. However, around 2010, the whole world started switching over to these reliable cryogen-free "dry" dilution refrigerators which suddenly allowed for experiments with superconducting qubits to be done for a lot longer periods of time with no interruption.

How did the Goldeneye project first took shape? And what were the biggest perceived technical challenges early on?

The very first thought of building something at that scale came from my colleaguePat Gumannwhile brainstorming long-term, 'crazy' ideas in my office in November of 2018. At that time, our team was tasked with deploying our first 53-qubit quantum computer in the IBM Quantum Computation Center in Poughkeepsie, NY, a challenge which pushed a few limits in what we could place into a single cryogenic refrigerator at the time. While working on it, it also really made us start thinking beyond, and almost instantly that we will need much larger cryogenic support system to ever cool down between 1,000 to 1 million qubits. This was simply due to the sheer volume required to host, not only all the qubits, but also all of the auxiliary, cryogenic, microwave electronics cables, filters, attenuators, isolators, amplifiers, etc.

It became very apparent that a new way of thinking in terms of the design would be needed and we started coming up with different form factors for how to effectively construct and cool down a behemoth such as the super-fridge. Some of the challenges we had were purely infrastructural such as how were we going to find a space in the building big enough to start this project and where would we find the capabilities to work with really large pieces of metal.

And as the rubber started to meet the road what have turned out to be the biggest hurdles to creating a useful quantum computer, and what does that say about the trajectory of the technology?

Some of the most challenging hurdles to overcome includes improving the quality of the underlying qubits, which includes improving the underlying coherence times (the amount of time that qubits stay in a superposition state), the achievable two-qubit gate fidelities, and reducing crosstalk between qubits as we scale up.

For that matter, most of these improvements feed into an overall quality measure for the performance of a quantum computer which we have defined called the Quantum Volume. Having a measure such as Quantum Volume allows us to really show progression along a roadmap of improvements, and we have been demonstrating this scaling of Quantum Volume year over year as we make new systems better and better.

The higher the Quantum Volume, the more real-world, complex problems quantum computers can potentially solve. A variety of factors determine Quantum Volume, including the number of qubits, connectivity, and coherence time, plus accounting for gate and measurement errors, device cross talk, and circuit software compiler efficiency.

Where is IBM right now with regards to Goldeneye? What can we expect in the near future?

Our "Goldeneye" super-fridge is very much an ongoing project, which is on target for completion in 2023. It is just one critical part of our long-term roadmap for scaling quantum technology. As we continue to execute on the roadmap we announced in September, we're pleased to share that we achieved aQuantum Volume of 128in November and we're working towards improving the quality of our underlying systems in order to debut our127-qubit IBM Quantum Eagle processorlater this year.

In the near future, we're poised to make exciting developments with our entire technology stack, including software and control systems. At IBM, we're working toward a complete set of broad innovations and breakthroughs.

What will quantum computing mean for the world in the long run? How will be a game changer?

Quantum computing will vastly broaden the types of problems we will address, and the technology offers a new form of computation that we expect to work in a frictionless fashion with today's classical computers. From the chemistry of new materials, and the optimization of everything from vehicle routing to financial portfolios, to improving machine learning, quantum will be an integral part of the future of computing and we're proud to be laying the foundation for a future of discovery.

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IBM's Goldeneye: Behind the scenes at the world's largest dilution refrigerator - ZDNet

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We are entering a new paradigm for the oil and gas industry, one far removed from the Trump Presidencys pro-drilling policies. The Biden Admin is likely to cut back on oil and gas production in the US, in favor of promoting renewable energy sources and carbon pollution reduction. In the short run, his policies are likely to push oil and gas prices up and that may turn out to help the hydrocarbon sector, at least at the bottom line, over the coming year. But for the oil companies, the lessons of 2020 appear in the balance sheets. The massive spike down in prices last May, followed by a quick recovery, only to finish the year at roughly the same price as it began all of this has the producers looking to cut back on spending, consolidate or reduce debt, and maintain free cash flow. In the words of Raymond James oil industry analyst John Freeman: [We] enter 4Q20 earnings and 2021 capital budget season with WTI trading, ironically, in essentially the same low $50s range as we did this time last year. While crude is largely in the same spot, the industry has definitely undergone a strategic shift with balance sheet health and returning capital to shareholders by far the highest priorities. In addition to noting the general trend of the industry after a difficult year, Freeman has also been updating his stance on individual oil and gas stocks. Two in particular have gotten Freemans attention. He sees at least 50% upside potential for each of them. We ran the two through TipRanks' database to see what other Wall Street's analysts have to say about them. Apache Corporation (APA) With headquarters in Houston, Texas, Apache is an important operator in the North American oil industry. The companys US hydrocarbon exploration and production activities are located in the Permian Basin, along the Gulf Coast, and in the Gulf Mexico. Apache also has operations in the UK (in the North Sea), in Egypt (in the Western Desert), and in Suriname (offshore). The companys Permian holdings include 665.8 million barrels of oil equivalent, 66% of its proven reserves. The company beat the quarterly revenue expectations in the third quarter, with $1.12 billion at the top line. Since reporting the Q3 revenue, Apaches stock has gained 71%. The company reported 445,000 barrels of oil equivalent per day in Q3 production. Covering the stock for Raymond James, analyst John Freeman writes: We continue to like Apache's diversified portfolio of U.S. onshore and international assets (Egypt, the North Sea, and Suriname), and given Apache's considerable commodity exposure (only hedged Waha basis in 2021), the company is ideally situated to capitalize on our projected resurgence in commodity prices in the 2021/2022 timeframe. Adding to this, the operator has an extremely robust FCF profile [and] proven commitment to capital discipline In line with these comments, the analyst gives APA a Strong Buy rating and a $24 price target that implies a 60% upside potential over the coming 12 months. (To watch Freemans track record, click here) Freeman leads the Bulls on Apache. The stock has a Moderate Buy from the analyst consensus, based on 12 reviews that include 6 Buys, 5 Holds, and 1 Sell. The shares are selling for $14.94, and their $19.30 average price target suggests room for 29% upside growth this year. (See APA stock analysis on TipRanks) Diamondback Energy (FANG) Also based in Texas, Diamondback Energy is another player in the Permian Basin energy boom. The company boasts an $8.9 billion market cap and saw revenues hit $720 million in the third quarter of 2020. Production in the quarter averaged 287.8 thousand barrels of oil equivalent per day. Diamondbacks reserves total more than 1.12 billion barrels of oil equivalent, of which 63% are oil and 37% are natural gas and related liquids. Diamondback is expanding its operations through M&A activity. In December of last year, the company announced that it will be acquiring QEP Resources, a natural gas driller in the Midland Basin of the Permian formation along with operations in North Dakotas Williston formation. The acquisition is an all-stock deal, worth an estimated $2.2 billion. QEP brings 49,000 acres in the Midland for potential development, an average production of 48,300 thousand BOE per day, and 48 drilled but uncompleted wells. These assets are accretive to Diamondbacks portfolio. In a related piece of news, Diamondback has announced that it will also be acquiring Guidon, another rival Texas oil producer. Guidon brings additional Permian assets to Diamondback, and the acquisition is significant, valued at $862 million in both cash and stock. Casting his eye on Diamondback, Freeman sees the company in a strong position to meet the challenges of both the energy environment and the Biden Administrations regulatory policies. Going forward with the addition of QEP and Guidon acreage we anticipate the Midland accounts for ~75% of pro forma activity. Note that even after the QEP/Guidon acquisitions, FANG still has no federal acreage exposure - a significant positive given regulatory uncertainty will likely persist following the expiration of the 60-day leasing moratorium We believe FANG offers considerable upside potential over the long-term and are confident in the company's ability to weather near-term commodity uncertainties, Freeman opined. Unsurprisingly, Freeman rates FANG as a Strong Buy, along with a $91 price target. This figure indicates confidence in ~51% growth over the next 12 months. (To watch Freemans track record, click here) Theres broad agreement on Wall Street with Freemans position here. FANG stock holds a Strong Buy rating from the analyst consensus, based on 13 recent Buy reviews against just 3 Holds. The average price target is $67.37, which implies ~12% upside from the current trading price of $67.37. (See FANG stock analysis on TipRanks) To find good ideas for oil stocks trading at attractive valuations, visit TipRanks Best Stocks to Buy, a newly launched tool that unites all of TipRanks equity insights. Disclaimer: The opinions expressed in this article are solely those of the featured analyst. The content is intended to be used for informational purposes only. It is very important to do your own analysis before making any investment.

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BMW tries to get ahead of its supply curve using quantum computing - Yahoo Tech