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Quantum Computing 2021: How will this Tech Fare in the Coming Months? – Analytics Insight

Posted: December 16, 2020 at 8:57 pm

This year has been quite tumultuous for businesses as well as provided then with an opportunity to venture into uncertainty with the help of technology. Disruptive technologies like robotics, artificial intelligence, cybersecurity, cloud rose to the occasion to sustain industries amid the crisis. Thus bringing numerous innovations and leapfrogging existing digital age to new heights. In the meantime, quantum computing which was predicted as an emerging trend for 2020 had a fruitful year, thanks to significant advancements that took place during this time.

For instance, in February, quantum computing company, D-Wave Systems Inc., launched Leap-2, which is the first quantum cloud service designed for developers and organizations to easily build and deploy real-world hybrid quantum applications with practical impact. In March, researchers at theU.S. Army Research Laboratorycreated a quantum sensor to detect communications over the entire radio frequency spectrum.

In October, IonQ announced itsnext-generation quantum computer systemwith 32 qubits and an expected quantum volume greater than four million. Quantum volume is a measurement of the overall power of a quantum machine. Later in the same month, theAccredited Standards Committee (ASC X9)issued a new standard for public-key cryptography use of digital signatures.

And most recently, China developed a quantum computing system called Jiuzhang which is reported to be 10 billion times faster than Googles Sycamore.Using, Gaussian boson sampling, Jiuzhang had captured 76 photons and also achieved quantum supremacy. Overall, the latest advancements in quantum computing have been some serious steps towards making it a commercial and scientific reality.

While quantum computing continues to garner billions of dollars of investment across the globe, in the recent coming years, it may be available as a cloud service. Not only that, quantum computing may also become an integral part of data analytics too.

Meanwhile, IDC has predictedthat by 2023, 25% of Fortune 500 companies will gain a competitive advantage from quantum computing. Tech giant IBM plans to deliver a quantum computer with a 1,121-qubit processor (codenamed Condor), inside a 10-foot tall super-fridge that will be online and capable of delivering aQuantum Advantage, by 2023. The Goldeneye fridge is currently in prototype and is designed to be capable of hosting multiple chips. IBM hints that such super-fridges will ultimately be capable of stacking multiple chips providing millions of internally networked qubits.

Quantum advantage is the point where certain information processing tasks can be performed more efficiently or cost-effectively on a quantum computer, in comparison to a traditional system.

Bob Sutor, vice president of IBM Quantum Strategy and Ecosystem says, This year, a number of IBM Q Network organizations collaborated with us to make significant progress in quantum research for industry, including work with Mitsubishi Chemical on applying quantum computing to help develop lithium-oxygen batteries with greater energy density. ExxonMobil to harness quantum computing to develop more accurate chemistry simulation techniques in energy technologies. And Daimler to explore how quantum computing can advance the next generation of EV batteries.Sutor believes that by the following year,over 20,000 will complete online quantum computing technology and coding courses.

Even Steve Gibson, Chief Strategy Officer of Strangeworks, the quantum computing startup company, has announced that Strangeworks will launch its initial offering of the platform in the first quarter of 2021, and the enterprise edition is coming in late 2021.

In terms of key trends that will dominate the quantum computing landscape in the following, it is still early to predict with accuracy. Yet, one can undoubtedly expect major advancements like:

Experts also forecast that in 2021 programmers will concentrate on developing quantum-safe cryptography while cybersecurity will also benefit from quantum computing applications. The latter was also mentioned in CB Insights 2020 Tech Trends report. The report acknowledges howQuantum Key Distribution (QKD)will play as a cybersecurity tool, by securing organizations against quantum-based attacks.

Coming back to cryptography, it is likely that any of the current quantum computing labs or companies may announce that their system has broken the traditional asymmetric key cipher. While Jiuzhangs recent feat fueled rumors about the threat to cryptosystems, fortunately, the quantum computer prototype was unable to solve the factoring problem that is crucial to decoding encrypted information.

Whether, quantum systems will pose a threat or not, to existing blockchain or other cryptography technologies, it is better if companies are prepared for such possibilities. This is because while a traditional computer may take years to crack a weak password string, given the advanced processing capabilities of qubits, it can be a matter of some time, before the world has a public-key of security devices and softwares.

As mentioned earlier, IBM has announced its ambitious plan of building a 1,121-qubit computer (Condor) for 2023. But before that, IBM has projected to launch a 127-qubit computer (codenamed Eagle) in 2021 and a 433-qubit computer(codenamed Osprey) in 2022. These announcements stem from the tech giants target of doubling quantum volume each year.

Meanwhile, Rigetti also plans to seize the qubit count lead with a 4x32Q multichip Aspen module. At the same time, while Googles Sycamore has 53-qubit processing, Google has designed a roadmap of 102Q (logical qubit prototype), 103Q (one logical qubit) in the next coming months.

Therefore, one can expect a narrow heated competition among leading quantum computing companies aiming to attain qubit count lead in 2021.

It is one of the most discussed forecasts that artificial intelligence and quantum computing can benefit each other by enhancing others abilities.

As perFrank Feather, CEO at AI-FUTURE Inc, quantum computing will scale-up rapidly in 2021 and will start to transform Artificial Intelligence into truly Advanced Intelligence. He also adds that, Quantum plus Advanced Intelligence (or QAI) will start to congregate with BioGenetic Sciences to create super-intelligent humanoids (a BioDigi TransHuman Species) in future years.

Simultaneously, applications of artificial intelligence like machine learning, computer vision will be accelerated if run on quantum systems. This will mean faster analysis of data in sectors like fraud detection, drug compound discovery and more. It will also boost Generative AI by expanding the datasets used to train generative or machine, learning models.

For instance, by integrating quantum processing units into the traditional computing framework has the potential to boost the quality of the images generated in say, a facial recognition system. So if we depend upon, the expanded dataset comprising of vast image data (quantitative, qualitative and variety) can significantly improve the detection model.

While IBM and Rigetti employ superconducting qubits, quantum computing systems from Honeywell and IonQ rely on using ion-trap based qubits. With its 6Q H0 and 10Q H1 ((linear trap) processors, Honeywell is also leading the quantum race.

Trapped ion generally offer superior connectivity and higher gate fidelity advantages than its superconducting qubit counterpart. But the major issue with trapped ion systems is that they provide significantly slower gate speeds (typically x100-1000 slower) than superconducting qubits. Experts suggest offsetting this with longer qubit lifetimes and higher fidelities leading to less error correction overhead.

As trapped-ion based quantum computing vendors are accelerating the maturity of their stacks, they also need to address the challenges posed by the trapped ion concept too.

IonQ believes that by pairing Bacon-Shor-13 code with high fidelity physical qubits can be the answer and also help it achieve quantum advantage sooner than others.

Another problem associated with Trapped ion is scaling up. Fortunately, AQT has a solution to this: usage of qubits defined on optical transitions instead of hyperfine transitions which are used by Honeywell and IonQ.

So, in 2021, we can expect AQT joining the ranks of Honeywell and IonQ is trapped ion quantum approach, and at the same time can anticipate more systems based on this concept.

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Quantum Computing 2021: How will this Tech Fare in the Coming Months? - Analytics Insight

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