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Driven by the government, energy, and transportation verticals, the global market for quantum computing hardware, according to a new report by Research and Markets, is projected to exceed $9.1 billionby 2028. These market segments will use quantum computing for various applications, including simulation, optimization, and sampling.

The research firm forecasts that managed Quantum Computing services will reach $328 million by 2028 with a 47.3% CAGR. Deployment, maintenance, and consulting are critical professional services in the quantum computing market.

Likewise, Quantum computing based on superconducting (cooling) loops technology is forecast to reach $4.5 billion during the same period.

Quantum computing uses the unique capabilities of quantum bits (qubits) to perform computational feats that are orders of magnitude greater than conventional methods. Qubits can exist in multiple states simultaneously due to the principles of quantum physics, enabling greater processing power than the binary representation of data used in classical computing.

Quantum computing is expected to support various capabilities, including:

Ultra-Secure Data and Communications: Quantum teleportation allows encrypted data to follow multiple paths, enhancing security.

Super-Dense Data and Communications: Significantly denser encoding will send more information from point A to point B.

The impact of quantum computing on data processing, communications, digital commerce, security, and the internet is anticipated to be transformative for the ICT sector, wrote the research firm. Quantum computing is also expected to disrupt various industries, from government and defense to logistics and manufacturing.

While Quantum computing is showing potential, the near-term challenge is to maintain qubit stability, as they are affected by molecules' constant motion. Some solutions to these issues involve super-cooling methods like cryogenics, but room-temperature quantum computers using photonic qubits are also being explored.

The research firm said, "Once these challenges are overcome, quantum computing will become more mainstream for solving specific problems.

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The Enchilada Trap, manufactured in Sandia National Laboratories Microsystems Engineering, Science and Applications fabrication facility. Credit: Craig Fritz, Sandia National Laboratories

Sandia National Laboratories has produced its first lot of a new world-class ion trap, a central component for certain quantum computers. This innovative device, termed the Enchilada Trap, enables researchers to construct more powerful machines, propelling the experimental yet groundbreaking realm of quantum computing forward.

In addition to traps operated at Sandia, several traps will be used at Duke University for performing quantum algorithms. Duke and Sandia are research partners through the Quantum Systems Accelerator, one of five U.S. National Quantum Information Science Research Centers funded by the Department of Energys Office of Science.

An ion trap is a type of microchip that holds electrically charged atoms, or ions. With more trapped ions, or qubits, a quantum computer can run more complex algorithms.

Jonathan Sterk points to the section of an ion trap trapped ion qubits travel in a close-up view of the trap inside a vacuum chamber at Sandia National Laboratories. Credit: Craig Fritz, Sandia National Laboratories

With sufficient control hardware, the Enchilada Trap could store and transport up to 200 qubits using a network of five trapping zones inspired by its predecessor, the Roadrunner Trap. Both versions are produced at Sandias Microsystems Engineering, Science, and Applications fabrication facility.

According to Daniel Stick, a Sandia scientist and leading researcher with the Quantum Systems Accelerator, a quantum computer with up to 200 qubits and current error rates will not outperform a conventional computer for solving useful problems. However, it will enable researchers to test an architecture with many qubits that in the future will support more sophisticated quantum algorithms for physics, chemistry, data science, materials science, and other areas.

We are providing the field of quantum computing room to grow and explore larger machines and more complicated programming, Stick said.

Sandia National Laboratories electrical engineer Ray Haltli optimizes parameters before placing gold wire bonds on an ion trap. When ready, the machine runs automatically, placing up to seven wires per second. Credit: Craig Fritz, Sandia National Laboratories

Sandia has researched, built, and tested ion traps for 20 years. To overcome a series of design challenges, the team combined institutional knowledge with new innovations.

For one, they needed space to hold more ions and a way to rearrange them for complex calculations. The solution was a network of electrodes that branches out similar to a family tree or tournament bracket. Each narrow branch serves as a place to store and shuttle ions.

Sandia had experimented with similar junctions in previous traps. The Enchilada Trap uses the same design in a tiled way so it can explore scaling properties of a smaller trap. Stick believes the branching architecture is currently the best solution for rearranging trapped ion qubits and anticipates that future, even larger versions of the trap will feature a similar design.

Another concern was the dissipation of electrical power on the Enchilada Trap, which could generate significant heat, leading to increased outgassing from surfaces, a higher risk of electrical breakdown, and elevated levels of electrical field noise. To address this issue, production specialists designed new microscopic features to reduce the capacitance of certain electrodes.

Our team is always looking ahead, said Sandias Zach Meinelt, the lead integrator on the project. We collaborate with scientists and engineers to learn about the kind of technology, features, and performance improvements they will need in the coming years. We then design and fabricate traps to meet those requirements and constantly seek ways to further improve.

The research was funded by the US Department of Energy.

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The Quantum Leap: Unveiling Quantum computing

Quantum computing, once confined to the realms of theoretical physics, has broken its theoretical shackles to redefine the limits of computation. Traditional computers rely on bits, the binary units of 0s and 1s, to process information. Quantum computers, on the other hand, leverage qubits, which can exist in multiple states simultaneously, thanks to the phenomenon of superposition. This property enables quantum computers to perform complex calculations exponentially faster than classical computers.

While the full potential of quantum computing is yet to be realised, it holds immense promise for revolutionising fields like cryptography, optimisation, and drug discovery. Companies like IBM, Google, and startups like Rigetti are racing to develop practical quantum systems that can tackle real-world problems. Quanticores first core, therefore, resides in the realm of quantum computing, opening doors to previously unattainable possibilities.

Artificial Intelligence (AI), a stalwart of modern technology, is undergoing its own transformation within the Quanticore paradigm. Machine Learning (ML) algorithms have been a driving force behind AIs progress, enabling systems to learn from data and make intelligent decisions. However, Quanticore introduces Quantum Machine Learning (QML), where quantum computers are employed to enhance AIs capabilities.

QML harnesses the power of quantum parallelism to process vast amounts of data more efficiently, leading to breakthroughs in pattern recognition, optimisation, and complex modeling. This convergence of AI and quantum computing empowers us to tackle problems previously deemed intractable, such as simulating molecular behaviour for drug development or optimising complex supply chain networks. Quanticores second core, AI, reinforces its potential to reshape industries across the board.

As Quanticore propels us toward unprecedented technological realms, it also presents formidable challenges. Quantum computing, while immensely powerful, is highly delicate and susceptible to external influences. Maintaining the integrity of qubits poses an ongoing challenge, as even the slightest disturbance can lead to errors in computation. Additionally, the quantum realms innate complexity demands new programming languages, algorithms, and approaches, which the tech community is actively striving to develop.

Ethical considerations also come to the forefront in this age of Quanticore. The potential of AI and quantum computing raises questions about data privacy, algorithmic bias, and the potential for malicious use. Striking a balance between innovation and responsible deployment is paramount, necessitating transparent regulations and cross-disciplinary collaboration.

Quanticores emergence underscores the importance of interdisciplinary collaboration. The fusion of quantum computing, AI, and other technologies necessitates experts from diverse fields to work in tandem. Physicists, computer scientists, mathematicians, and domain specialists must unite to harness the true potential of Quanticore.

Moreover, Quanticores ecosystem extends beyond the realm of academia and research labs. Industries ranging from finance to healthcare are exploring ways to integrate Quanticore technologies into their operations. Financial institutions, for instance, are intrigued by quantums potential to revolutionise cryptography and risk analysis. Healthcare is eyeing the fusion of AI and quantum computing for drug discovery and personalised medicine. The symbiotic relationship between Quanticore and various industries underlines the need for a well-rounded understanding of its nuances.

As we navigate the shifting tech realms, the age of Quanticore beckons us with boundless possibilities. Quantum computing and AI, the core components of Quanticore, are evolving rapidly, offering solutions to problems that have stymied traditional technologies. The journey, however, will be marked by challenges technical, ethical, and philosophical. Its incumbent upon us to approach Quanticore with both curiosity and caution, harnessing its potential while mitigating its risks.

In the Quanticore era, achieving seamless interconnectivity between various technologies is paramount. This is where the concept of Wallet Connect comes into play, acting as a bridge between the world of decentralised finance and the evolving Quanticore landscape. Wallet Connect facilitates secure and private communication between decentralized applications (DApps) and mobile cryptocurrency wallets. As we explore the dynamic interplay of Quanticores core technologies, its essential to recognise the significance of Wallet Connect through its key features:

In the intricate web of Quanticore, Wallet Connect emerges as a vital thread, weaving together the realms of decentralized finance and cutting-edge technologies while upholding the principles of security and user empowerment.

In conclusion, Quanticore represents an amalgamation of technologies that are poised to redefine our world. The quantum leap of quantum computing and the cognitive prowess of AI converge to open doors we never thought possible. However, as we embark on this journey, its crucial to remember that the true power of Quanticore lies not just in its technological might, but in our ability to navigate its complexities responsibly, ethically, and collaboratively. The age of Quanticore is upon us are we ready to shape it for the better?

Ivy Carter is an ardent tech enthusiast with a deep passion for innovation. As a woman in the world of technology, she finds great joy in connecting with like-minded individuals, united by a shared fascination for pushing boundaries.

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Quanticore: Navigating the shifting tech realms - Maddyness

Bengaluru: Marc Carrel-Billiard, who recently visited India, serves as a senior managing director at Accenture. He heads Accenture Technology Innovation, the R&D Labs, Accenture Strategic Growth Initiatives, Accenture Studios and Accenture Ventures. In his 25-year tenure at the company, he has pioneered technology, particularly in voice recognition, knowledge-based systems, and neural networks. In an interview, Carrel-Billiard shared his views on how business leaders can harness scientific advancements and technologies such as artificial intelligence (AI), generative AI, quantum computing, blockchain, metaverse, and digital twins, and Indias role in these domains. Edited excerpts:

Bengaluru: Marc Carrel-Billiard, who recently visited India, serves as a senior managing director at Accenture. He heads Accenture Technology Innovation, the R&D Labs, Accenture Strategic Growth Initiatives, Accenture Studios and Accenture Ventures. In his 25-year tenure at the company, he has pioneered technology, particularly in voice recognition, knowledge-based systems, and neural networks. In an interview, Carrel-Billiard shared his views on how business leaders can harness scientific advancements and technologies such as artificial intelligence (AI), generative AI, quantum computing, blockchain, metaverse, and digital twins, and Indias role in these domains. Edited excerpts:

As we spelt out in our Technology Vision 2023 report, theres a revolution at every level. While companies already have a technology strategy to manage their information (IT) and operational technology (OT, which is about physical or hardware systems), the strategy needs to encompass science tech (ST), too, if enterprises want to leverage the new reality over the next 5-10 years.

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As we spelt out in our Technology Vision 2023 report, theres a revolution at every level. While companies already have a technology strategy to manage their information (IT) and operational technology (OT, which is about physical or hardware systems), the strategy needs to encompass science tech (ST), too, if enterprises want to leverage the new reality over the next 5-10 years.

Many companies are using tools such as RPA (robotic process automation) for automation work and claiming to do AI. But next generation of AI is about generalizing AI, which explores how a new category of AI, spurred on by foundation models and large language models (LLMs), is used by companies. We are also looking at multi-sensorial next-generation metaverse that is not just about vision and audio, but also haptics. One key focus area of the metaverse, will be industrial digital twins (digital replicas of physical systems).

Our technology vision report has a different theme every year. This year it is: When Atoms meet Bits: The foundations of our new reality. That is, while we may live in a physical world, we parallelly live in a digital world, too. We are going to see convergence of those two worlds in digital twins: everything you do will basically be replicated by a computer. For instance, instead of going to a doctor to get your heart (or any organ) examined, you will get an alert because of predictive monitoring of your digital twin whether you are on a plane, in a car, or anywhere. Besides, the value of the metaverse is not only to buy a house next to a big star, rather, it is a continuum of digitally-enhanced worlds, realities, and business models. Our life will be powered by digital twins, whether building digital twins of refineries or airplanes using 3D scanning to anticipate failures or monitoring. People at times do not appreciate the complex system modelling that goes into building a digital twinthey see only the user interface of a digital twin like the 3D model, or AR-VR (augmented and virtual reality) experiences. However, we need a very smart AI engine to simulate that stuff. At Accenture, we have made strategic investments in this complex system modelling to simulate organs, planes, refineries, and even climate change.

We have set up a generative AI and LLM Centre of Excellence (CoE) with 1,600 employees globally, a significant part of which is in India. We are working with Indian Institute of Science on collaborative research projects and developing intellectual properties in next generation computing technologies that enable AI at the edge, including cloud, edge, quantum, and neuromorphic computing and sustainable software engineering. People working at our Bengaluru lab also contribute to the lab in Dublin, which specializes in life sciences.

There are different types of clientsthose that are very innovative. They have the culture and mindset for innovation. There are the followers who had been innovating, but didnt know that they had the capacity to reinvent themselves. The third comprises laggards who are not much into digital transformation, and have migrated their services on the cloud to survive. We deliver our tech vision to clients by explaining our agenda and actions.

Yes. Thats one reason why we advise our leaders to think about the six pillars when considering generative AI, or any new tech tool. First, we advise them to dive in with a business-driven mindset, where you just need to think about the power of a technology and rethink how it can reinvent part of the business (not the company) so that you dont have to take a big risk. Basically to have your employees and, eventually, customers to experience it. For example, car makers put the whole document of a car in a book, or online with videos. Soon, it will be delivered with the help of Generative AI, using natural language processing or speech recognition, wherein you get to talk to the car or phone to get answers. The second is people-first approach. You need to demystify technology for employees, change their mindset to make them realize that these tools will make them powerful, rather than having their activities (jobs) taken away.

The third is getting your proprietary data ready, and connect it with a mesh-like technology. Four, choose the best green platform to run your system. Five, use Responsible AI to explain how your systems work. And last, but not the least, you need to figure out what youre doing with this data. Nothing can stop Generative AI. We must adopt it, understand it, and try to leverage it in the best possible way.

Generative AI is not new. Google was already working on transformers in 2017. So, weve been leveraging Generative AI for many years, its just that we didnt talk about it. For me, its just another tool like the cloud, etc. But (with ChatGPT), consumers lapped this up, which explains this (Generative AI) revolution.

As for our clients, we explain how they can leverage Generative AI the way we explain our approach to quantum computing. One thing we found is that Gen AI has the potential to transform 40% of all working hours. This doesnt mean that 40% of jobs will go away but it simply means that there will be a shift in the way we work. Basically, a specific task in any given job may become fully automated while some will be assisted by AI like a co-pilot. Other jobs will not be affected.

At Accenture, we are using Gen AI in our labs to deliver assets and solutions. And we announced a $3 billion investment over three years in its Data and AI practice this June to show the world that we are doubling down our efforts in this space. The important consideration for enterprises is how they will customise the system. The easiest stuff to do is what we call prompt engineering, but even this will be done by AI itself in the next 1-2 years.

While technology has accelerated scientific discovery, enterprises were largely content to leave science tech in the hands of researchers and specific industries like pharma or chemicals. Thats starting to change. More enterprises are widening their innovation efforts and discovering just how disruptive the intersection of science and technology can be.

When we launched our quantum computing practice six years ago, we wanted to talk to our industry leaders to understand what type of business or classification of problems were appropriate for quantum computers. We surveyed about 49 industries, and out of these, we found more than 150 use cases that we could use in sectors like manufacturing, finance, and pharma.

As an example, we started to engage with Biogen. One of the processes they wanted to change was to be able to compute the level of stability of medical compounds but classical computers, which allow drug companies to run hundreds of millions of comparisons, are limited only to molecules of up to a certain size. Quantum computers allow pharma companies to compare molecules that are much larger. Accenture Labs worked with D-Wave 1QBit (1QB Information Technologies, Inc.) to significantly improve the companys discovery process and eventually improve patient outcomes.

Another example is BBVA. Weve been working with them in three areas -- currency, credit scoring and optimization of trading trajectories (Accenture worked with D-Wave Systems and Spain-headquartered Banco Bilbao Vizcaya Argentaria (BBVA) to use quantum algorithms to address the opportunities in these areas).

A lot of people are cyborgs. They just dont know it. Youre a cyborg, for instance, if you have a pacemaker (sends electrical pulses to help your heart beat at a normal rate and rhythm) in you because it is powered by electronics. Theres are very smart AI algorithms that measure everything, which are making pacemakers more intelligent. Accenture also has a US patent for developing an algorithm to find the optimal donor-patient matches in a kidney exchange network using quantum computing, which can be used by hospital networks and government agencies nationwide.

For me, blockchain is the technology to power Web 3, but we need to rethink blockchains like making it greener. Accenture is one of the prominent players when it comes to making blockchain adoption in the world -- were all talking about making your identity card, driving permit, and everything into your E-wallet, powered by blockchain.

When I think sentient, for me its about two worlds. The first is emotional, and the second is, responsible. In our Dublin lab, we are also looking at how we can make these intelligent systems more emotional, so that they can interact with people better. On the emotional front, we have developed a tool which allows clients to change the recipe using suggested ingredients from generative AI, which comprises three categories: expected, surprising and novel. This is not something you would expect from a machine. And weve been testing the tool in partnership with a Michelin 3-Star restaurant. As for AI becoming sentient at any given point in time, I believe we will have to create machines we can connect with you. Thats going to be important in the future of adoption of these systems.

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Everything you do will be replicated by a computer | Mint - Mint