Google announced this fall to much fanfare that it had demonstrated quantum supremacy that is, it performed a specific quantum computation far faster than the best classical computers could achieve. IBM promptly critiqued the claim, saying that its own classical supercomputer could perform the computation at nearly the same speed with far greater fidelity and, therefore, the Google announcement should be taken with a large dose of skepticism.

This wasnt the first time someone cast doubt on quantum computing. Last year, Michel Dyakonov, a theoretical physicist at the University of Montpellier in France, offered a slew of technical reasons why practical quantum supercomputers will never be built in an article in IEEE Spectrum, the flagship journal of electrical and computer engineering.

So how can you make sense of what is going on?

As someone who has worked on quantum computing for many years, I believe that due to the inevitability of random errors in the hardware, useful quantum computers are unlikely to ever be built.

Whats a quantum computer?

To understand why, you need to understand how quantum computers work since theyre fundamentally different from classical computers.

A classical computer uses 0s and 1s to store data. These numbers could be voltages on different points in a circuit. But a quantum computer works on quantum bits, also known as qubits. You can picture them as waves that are associated with amplitude and phase.

Qubits have special properties: They can exist in superposition, where they are both 0 and 1 at the same time, and they may be entangled so they share physical properties even though they may be separated by large distances. Its a behavior that does not exist in the world of classical physics. The superposition vanishes when the experimenter interacts with the quantum state.

Due to superposition, a quantum computer with 100 qubits can represent 2100 solutions simultaneously. For certain problems, this exponential parallelism can be harnessed to create a tremendous speed advantage. Some code-breaking problems could be solved exponentially faster on a quantum machine, for example.

There is another, narrower approach to quantum computing called quantum annealing, where qubits are used to speed up optimization problems. D-Wave Systems, based in Canada, has built optimization systems that use qubits for this purpose, but critics also claim that these systems are no better than classical computers.

Regardless, companies and countries are investing massive amounts of money in quantum computing. China has developed a new quantum research facility worth US$10 billion, while the European Union has developed a 1 billion ($1.1 billion) quantum master plan. The United States National Quantum Initiative Act provides $1.2 billion to promote quantum information science over a five-year period.

Breaking encryption algorithms is a powerful motivating factor for many countries if they could do it successfully, it would give them an enormous intelligence advantage. But these investments are also promoting fundamental research in physics.

Many companies are pushing to build quantum computers, including Intel and Microsoft in addition to Google and IBM. These companies are trying to build hardware that replicates the circuit model of classical computers. However, current experimental systems have less than 100 qubits. To achieve useful computational performance, you probably need machines with hundreds of thousands of qubits.

Noise and error correction

The mathematics that underpin quantum algorithms is well established, but there are daunting engineering challenges that remain.

For computers to function properly, they must correct all small random errors. In a quantum computer, such errors arise from the non-ideal circuit elements and the interaction of the qubits with the environment around them. For these reasons the qubits can lose coherency in a fraction of a second and, therefore, the computation must be completed in even less time. If random errors which are inevitable in any physical system are not corrected, the computers results will be worthless.

In classical computers, small noise is corrected by taking advantage of a concept known as thresholding. It works like the rounding of numbers. Thus, in the transmission of integers where it is known that the error is less than 0.5, if what is received is 3.45, the received value can be corrected to 3.

Further errors can be corrected by introducing redundancy. Thus if 0 and 1 are transmitted as 000 and 111, then at most one bit-error during transmission can be corrected easily: A received 001 would be a interpreted as 0, and a received 101 would be interpreted as 1.

Quantum error correction codes are a generalization of the classical ones, but there are crucial differences. For one, the unknown qubits cannot be copied to incorporate redundancy as an error correction technique. Furthermore, errors present within the incoming data before the error-correction coding is introduced cannot be corrected.

Quantum cryptography

While the problem of noise is a serious challenge in the implementation of quantum computers, it isnt so in quantum cryptography, where people are dealing with single qubits, for single qubits can remain isolated from the environment for significant amount of time. Using quantum cryptography, two users can exchange the very large numbers known as keys, which secure data, without anyone able to break the key exchange system. Such key exchange could help secure communications between satellites and naval ships. But the actual encryption algorithm used after the key is exchanged remains classical, and therefore the encryption is theoretically no stronger than classical methods.

Quantum cryptography is being commercially used in a limited sense for high-value banking transactions. But because the two parties must be authenticated using classical protocols, and since a chain is only as strong as its weakest link, its not that different from existing systems. Banks are still using a classical-based authentication process, which itself could be used to exchange keys without loss of overall security.

Quantum cryptography technology must shift its focus to quantum transmission of information if its going to become significantly more secure than existing cryptography techniques.

Commercial-scale quantum computing challenges

While quantum cryptography holds some promise if the problems of quantum transmission can be solved, I doubt the same holds true for generalized quantum computing. Error-correction, which is fundamental to a multi-purpose computer, is such a significant challenge in quantum computers that I dont believe theyll ever be built at a commercial scale.

[ Youre smart and curious about the world. So are The Conversations authors and editors. You can get our highlights each weekend. ]

Subhash Kak, Regents Professor of Electrical and Computer Engineering, Oklahoma State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image: Reuters

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Quantum Computers Are the Ultimate Paper Tiger - The National Interest Online

Making fast and powerful quantum computing available through the cloud can enable tasks to be processed millions of times faster, and could shape lives and businesses as we know it. For example, applications using quantum computing could reduce or prevent traffic congestion, cybercrimes, and cancer. However, reaching the quantum supremacy landmark doesnt mean that Google can take its foot off the gas. Rather, the company has thrown down the gauntlet and the race to commercialize quantum computing is on. Delivering this killer technology is still an uphill battle to harness the power of highly fickle machines and move around quantum bits of information, which is inherently error-prone.

To deliver quantum cloud services, whether for commercial or academic research, Google must tie together units of quantum information (qubits) and wire data, which is part of every action and transaction across the entire IT infrastructure. If quantum cloud services get to the big league, it will still rely on traffic flows based on wire data to deliver value to users. This raises a conundrum for IT and security professionals who must assure services and deliver a flawless user experience. On one hand, the quantum cloud service solves a million computations in parallel and in real time. On the other hand, the results are delivered through wire data across a cloud, SD-WAN, or 5G network. It does not matter if a quantum computer today or tomorrow can crank out an answer 100 million times faster than a regular computer chip if an application that depends on it experiences performance problems or a threat actor is lurking in your on-premises data centre or penetrated the IT infrastructure first and last lines of defence.

No matter what the quantum computing world will look like in the future, IT teams such as NetOps and SecOps will still need to use wire data to gain end-to-end visibility into their on-premises data centres and cloud environment. Wire data is used to fill the visibility gap and see what others cant; to gain actionable intelligence to detect cyber-attacks or quickly solve service degradations. Quantum computing may increase speed, but it also adds a new dimension of infrastructure complexity and the potential for something breaking anywhere along the service delivery path. With that said, reducing risk therefore requires removing service delivery blind spots. A proven way to do that is by turning wire data into smart data to cut through infrastructure complexity and gain visibility without borders. When that happens, the IT organization will fully understand with precise accuracy the issues impacting service performance and security.

In the rush to embrace quantum computing, wire data therefore cannot, and should not, be ignored. Wire data can be turned into contextually, useful smart data. With a smart data platform, the IT organization can help make quantum computing a success by protecting user experience across different industries including automotive, manufacturing and healthcare. Therefore, while Google is striving for high quality qubits and blazing new quantum supremacy trails, success ultimately relies on using smart data for service assurance and security in an age of infinite devices, cloud applications and exponential scalability.

Ron Lifton, Senior Enterprise Solutions Manager, NETSCOUT

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Quantum supremacy is here, but smart data will have the biggest impact - Quantaneo, the Quantum Computing Source

Scientists are closer to taming the most powerful light in the Universe. A physicist at the University of California has figured out how to make stable positronium atoms, which may lead to the creation of gamma ray lasers.

Gamma rays are the product of electromagnetic radiation that is caused by the radioactive decay of atomic nuclei. Harnessing these extremely bright (and usually very brief) lights, which have the highest photon energy, could lead to next-generation technologies. The highly penetrating gamma rays are shorter in wavelength than x-rays, and can be utilized for spacecraft propulsion, advanced medical imaging and treating cancers.

Creating a gamma ray laser requires manipulating positronium, a hydrogen-like atom that is a mixture of matter and antimatter in particular, of electrons and their antiparticles known as positrons. The collision of a positron with an electron results in the production of gamma ray photons.

To make gamma-ray laser beams, the positronium atoms need to be in the same quantum state, called a Bose-Einstein condensate. The new study from professor Allen Mills of the UC Riverside Department of Physics and Astronomy, shows that hollow spherical bubbles filled with a positronium atom gas can be kept stable in liquid helium.

"My calculations show that a bubble in liquid helium containing a million atoms of positronium would have a number density six times that of ordinary air and would exist as a matter-antimatter Bose-Einstein condensate," said Mills.

Mills thinks helium would work as the stabilizing container because at extremely low temperatures, the gas would turn to liquid and actually repel positronium. This results from its negative affinity fo positronium and would cause bubbles to be created, which would be the source of the necessary Bose-Einstein condensates.

Testing these ideas and actually configuring an antimatter beam to produce such bubbles in liquid helium is the next goal for the Positron laboratory at UC Riverside that Mills directs.

"Near term results of our experiments could be the observation of positronium tunneling through a graphene sheet, which is impervious to all ordinary matter atoms, including helium, as well as the formation of a positronium atom laser beam with possible quantum computing applications," explained the physicist.

Check out the new study in Physical Review A.

Professor Allen Mills of the UC Riverside Department of Physics and Astronomy.

Credit: I. Pittalwala, UC Riverside.

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Original post:

Breakthrough in creation of gamma ray lasers that use antimatter - Big Think

Key Takeaways

Looking back, 2019 saw some significant announcements in Quantum computing. In May, IBM published a paper in Nature that suggested they may have found a path to dealing with decoherence in current quantum computers. Writing for InfoQ Sergio De Simone pointed out:

"The main issue with decoherence is the fast decay of a wave function, which has the undesirable effect of generating noise and errors after a very short time period. The paper proposes two approaches, one called probabilistic error correction and the other zero noise extrapolation, to keep decoherence under control."

In September, Google announced, also via a paper in Nature, it had built a machine that achieved quantum supremacy - the point at which a quantum computer can solve problems which classical computers practically cannot. The claim was disputed by IBM, and the practical application of Googles achievement is still limited, but both these announcements demonstrate real progress in the field.

Also significant - the news that Microsoft open-sourced Q#, its Language for Quantum Computing.

A surprise this year was the decline of interest in Virtual Reality, at least in the context of Smart-phone-based VR. Sergio notes:

"Google's decision to stop supporting its Daydream VR headset seemingly marks the end of phone-based virtual reality, a vision that attempted to combine the use of smartphones with 'dumb' VR headsets to bring VR experiences to the masses. Google's decision is accompanied by the BBC disbanding its VR content team after two years of successful experimentation."

JavaScript, Java, and C# remain the most popular languages we cover, but were also seeing strong interest in Rust, Swift, and Go, and our podcast with Bryan Cantrill on "Rust and Why He Feels Its The Biggest Change In Systems Development in His Career" is one of the top-performing podcasts weve published this year. Weve also seen a growing interest in Python this year, probably fuelled by its popularity for machine learning tasks.

After a rather turbulent 2018, Java seems to be settling into its bi-annual release cycle. According to our most-recent reader survey Java is the most used language amongst InfoQ readers, and there continues to be a huge amount of interest in the newer language features and how the language is evolving. We also continue to see strong and growing interest in Kotlin.

It has been interesting to see Microsofts growing involvement in Java, joining the OpenJDK, acquiring JClarity, and hiring other well known figures including Monica Beckwith.

Our podcast with Rod Johnson in which he chats about the early days of the Spring Framework, Languages Post-Java, & Rethinking CI/CD was another of our top-performing podcasts this year.

Matt Raibles JHipster book, now in its 5th version, was one of our most-downloaded books of the year.

In the Java programming language trends report, we noted increased adoption of non-HotSpot JVMs, and we believe OpenJ9 is now within the early-adopter stage. As the time we noted that:

"We believe that the increasing adoption of cloud technologies within all types of organisation is driving the requirements for JREs that embrace associated "cloud-native" principles such as fast start-up times and a low memory footprint. Graal in itself may not be overly interesting, but the ability to compile Java application to native binaries, in combination with the support of polyglot languages, is ensuring that we keep a close watch on this project."

Since the report came out, we feel that the GraalVM has demonstrated significant potential, and will continue to watch its progress with interest.

Our top performing content for Java this year included:

Although it didnt quite make it in the top five list, an honourable mention should go to Brian Goetzs fantastic "Java Feature Spotlight" article "Local Variable Type Inference."

The release of .NET Core 3 in September generated a huge buzz on InfoQ and produced some of our most-popular .NET content of the year. WebAssembly has been another area of intense interest, and we saw a corresponding surge in interest for Blazor, a new framework in ASP.NET Core that allows developers to create interactive web applications using C# and HTML. Blazor comes in multiple editions, including Blazor WebAssembly which allows single-page applications to run in the client's web browser using a WebAssembly-based .NET runtime.

According to our most-recent reader survey, C# is the second-most widely used language among InfoQ readers after Java, and interest in C#8 in particular was also strong.

Our top performing .NET content included:

Jonathan Allens piece in the list is part of an excellent series of articles and news posts that Jonathan Allen wrote for InfoQ during 2019. Others included:

Unsurprisingly, the majority of InfoQ readers write at least some JavaScript - around 70% according to the most recent reader survey - making it the most widely used language among our readers. The dominant JavaScript frameworks for InfoQ readers seem to currently be Vue and React. We also saw interest in using Javascript for machine learning via TensorFlow.js. Away from JavaScript, we saw strong interest in some of the transpiler options. In addition to Blazor, mentioned above, we saw strong interest in Web Assembly, Typescript, Elm and Svelte.

Top-performing content included:

Its unsurprising that distributed computing, and in particular the microservices architecture style, remains a huge part of our news and feature content. We see strong interest in related topics, with our original Domain Driven Design Quickly book, and our more-recent eMag "Domain-Driven Design in Practice" continuing to perform particularly well, and interest in topics like observability and distributed tracing. We also saw interest in methods of testing distributed systems, including a strong performance from our Chaos Engineering eMag, and a resurgence in reader interest in some for the core architectural topics such as API design, diagrams, patterns, and models.

Our top performing architecture content was:

Our podcast with Grady Booch on todays Artificial Intelligence reality and what it means for developers was one of our most popular podcasts of the year, and revealed strong interest in the topic from InfoQ readers.

Key AI stories in 2019 were MIT introducing GEN, a Julia-basd language for artificial intelligence, Googles ongoing work on ML Kit, and discussions around conversational interfaces, as well as more established topics such as streaming.

Its slightly orthogonal to the rest of the pieces listed here, but we should also mention "Postgres Handles More Than You Think" by Jason Skowronski which performed amazingly well.

Our top-performing content for AI and ML was:

If there was an overarching theme to our culture and methods coverage this year it might best be summed up as "agile done wrong" and many of our items focused on issues with agile, and/or going back to the principles outlined in the Agile Manifesto.

We also saw continued in interest in some of the big agile methodologies, notably Scrum, with both "Scrum and XP from the Trenches", and "Kanban and Scrum - Making the Most of Both" performing well in our books department.

We also saw strong reader interest in remote working with Judy Rees eMag on "Mastering Remote Meetings", and her corresponding podcast, performing well, alongside my own talk on "Working Remotely and Managing Remote Teams" from Aginext this year.

Our most popular published content for Culture and Methods was:

Our top performing culture podcasts were:

In our DevOps and Cloud trends report, we noted that Kubernetes has effectively cornered the market for container orchestration, and is arguably becoming the cloud-agnostic compute abstraction. The next "hot topics" in this space appear to be "service meshes" and developer experience/workflow tooling. We continue to see strong interest in all of thee among InfoQs readers.

A trend were also starting to note is a number of languages which are either infrastructure or cloud-orientated. In our Programming Languages trends report, we noted increased interest and innovation related to infrastructure-aware or cloud-specific languages, DSLs, and SDKs like Ballerina and Pulumi. In this context we should also mention Dark, a new language currently still in private beta, but already attracting a lot of interest. Somewhat related, we should also mention the Ecstasy language, co-created by Tangosol founders Cameron Purdy and Gene Gleyzer. Chris Swan, CTO for the Global Delivery at DXC Technology, spoke to Cameron Purdy about the language and the problems its designed to solve.

In the eMags department "Kubernetes: Past, Present and Future", and "DevSecOps in Practice" were among our top performers:

Making predictions in software in notoriously hard to do, but we expect to see enterprise development teams consolidate their cloud-platform choices as Kubernetes adoption continues. Mostly this will be focussed on the "big five" cloud providers - Amazon, Google, IBM (plus Red Hat), Microsoft, and VMware (plus Pivotal). We think that, outside China, Alibaba will struggle to gain traction, as will Oracle, Salesforce, and SAP.

In the platform/operations space were expecting that service meshes will become more integrated with the underlying orchestration frameworks (e.g. Kubernetes). Were also hopeful that the developer workflow for interacting with service meshes becomes more integrated with current workflows, technologies, and pipelines.

Ultimately developers should be able to control deploy, release, and debugging via the same continuous/progressive delivery pipeline. For example, using a "GitOps" style pipeline to deploy a service by configuring k8s YAML (or some higher-level abstraction), controlling the release of the new functionality using techniques like canarying or shadowing via the configuration of some traffic management k8s custom resource definition (CRD) YAML, and enabling additional logging or debug tooling via some additional CRD config.

In regards to architecture, next year will hopefully be the year of "managing complexity". Architectural patterns such microservices and functions(as-a-service) have enabled developers to better separate concerns, implement variable rates of change via independent isolated deployments, and ultimately work more effectively at scale. However, our ability to comprehend the complex distributed systems we are now building -- along with the availability of related tooling -- has not kept pace with these developments. Were looking forward to seeing what the open source community and vendors are working on in the understandability, observability, and debuggability space.

We expect to see more developers experimenting with "low code" platforms. This is partly fueled by a renewed push from Microsoft for its PowerApps, Flow, Power BI, and Power Platform products.

In the .NET ecosystem, we believe that Blazor will keep gaining momentum among web developers. .NET 5 should also bring significant changes to the ecosystem with the promised interoperability with Java, Objective-C, and Swift. Although it is early to say, Microsoft's recent efforts on IoT and AI (with ML.NET) should also help to raise the interest in .NET development. Related we expect to see the interest in Web Assembly continue and hope that the tooling hear will start to mature.

Despite the negative news around VR this year, we still think that something in the AR/VR space, or some other form of alternative computer/human interaction, is likely to come on the market in the next few years and gain significant traction, though it does seem that the form factor for this hasnt really arrived.

Charles Humble took over as editor-in-chief at InfoQ.com in March 2014, guiding our content creation including news, articles, books, video presentations and interviews. Prior to taking on the full-time role at InfoQ, Charles led our Java coverage, and was CTO for PRPi Consulting, a remuneration research firm that was acquired by PwC in July 2012. For PRPi he had overall responsibility for the development of all the custom software used within the company. He has worked in enterprise software for around 20 years as a developer, architect and development manager. In his spare time he writes music as 1/3 of London-based ambient techno group Twofish, whose debut album came out in February 2014 after 14 years of messing about with expensive toys, and spends as much time as he can with his wife and young family.Erik Costlow is a software security expert with extensive Java experience. He manages developer relations for Contrast Security and public Community Edition. Contrast weaves sensors into applications, giving them the ability to detect security threats based on how the application uses its data. Erik was the principal product manager in Oracle focused on security of Java 8, joining at the height of hacks and departing after a two-year absence of zero-day vulnerabilities. During that time, he learned the details of Java at both a corporate/commercial and community level. He also assisted Turbonomic's product management team to achieve $100M annual revenue in data center/cloud performance automation. Erik also lead product management for Fortify static code analyzer, a tool that helps developers find and fix vulnerabilities in custom source code. Erik has also published several developer courses through Packt Publishing on data analysis, statistics, and cryptography.

Arthur Casals is a Computer Science researcher working in the area of Artificial Intelligence / Multi-agent Systems. He has been developing software for 20+ years, in different markets/industries. Arthur has also assumed different roles in the past: startup founder, CTO, tech manager, software engineer. He holds a B.Sc. degree in Computer Engineering and an MBA degree.

Daniel Bryant works as an Independent Technical Consultant and Product Architect at Datawire. His technical expertise focuses on 'DevOps' tooling, cloud/container platforms, and microservice implementations. Daniel is a Java Champion, and contributes to several open source projects. He also writes for InfoQ, O'Reilly, and TheNewStack, and regularly presents at international conferences such as OSCON, QCon and JavaOne. In his copious amounts of free time he enjoys running, reading and traveling.

Bruno Couriol holds a Msc in Telecommunications, a BsC in Mathematics and a MBA by INSEAD. Most of his career has been spent as a business consultant, helping large companies addressing their critical strategical, organizational and technical issues. In the last few years, he developed a focus on the intersection of business, technology and entrepreneurship.

Ben Linders is an Independent Consultant in Agile, Lean, Quality and Continuous Improvement, based in The Netherlands. Author of Getting Value out of Agile Retrospectives, Waardevolle Agile Retrospectives, What Drives Quality, The Agile Self-assessment Game and Continuous Improvement. As an adviser, coach and trainer he helps organizations by deploying effective software development and management practices. He focuses on continuous improvement, collaboration and communication, and professional development, to deliver business value to customers. Ben is an active member of networks on Agile, Lean and Quality, and a frequent speaker and writer. He shares his experience in a bilingual blog (Dutch and English) and as an editor for Agile at InfoQ. Follow him on Twitter: @BenLinders.

Shane Hastie is the Director of Community Development for ICAgile, a global accreditation and certification body dedicated to improving the state of agile learning. Since first using XP in 2000 Shane's been passionate about helping organizations and teams adopt sustainable, humanistic ways of working irrespective of the brand or label they go by. Shane was a Director of the Agile Alliance from 2011 until 2016. Shane leads the Culture and Methods editorial team for InfoQ.com

Read more from the original source:

InfoQ's 2019, and Software Predictions for 2020 - InfoQ.com