The compact quantum computer fits into two 19-inch server racks.

Quantum computers still require large, dedicated rooms and complex installations, but now, in a new step towards bringing the technology out of the lab, researchers have designed a prototype quantum computer that is compact enough to fit in ordinary data center racks.

As part of an EU-funded project called AQTION, a group of scientists from the University of Innsbruck in Austria successfully set up a fully functional ion trap quantum computer into two 19-inch server racks, as typically found in data centers around the world. The device only requires a single wall-mounted power plug and is otherwise self-contained.

The prototype is an exciting development in an industry that relies mostly on lab-based implementations, where quantum computers can only be controlled thanks to purpose-built infrastructure. Developing a set-up that is more accessible is therefore key to expanding the reach of the technology.

This is why the EU recently launchedAQTION, a 10 million project that aims to create a compact ion-trap quantum computer that meets industry standards without needing an ultra-stable lab environment for operation.

"Our quantum computing experiments usually fill 30- to 50-square-meter laboratories," says Thomas Monz, AQTION project coordinator. "We were now looking to fit the technologies developed here in Innsbruck into the smallest possible space while meeting standards commonly used in industry."

The new device, said the research team, shows that quantum computers will soon be ready for use in data centers.

The researchers used ions, which are single-charged atoms, as qubits. Quantum information is encoded in the electronic state of ions, and operations are performed with laser pulses that modify and control the state of the particles.

While the approach differs from the well-known superconducting qubits used by IBM and Google in their quantum computers, ion trap devices are gaining attention in the industry. Honeywell, for instance,made its quantum debut last year with trapped-ion technology.

To fit in a couple of 19-inch racks, every individual building block of AQTION's quantum computer had to be downsized, from the ion trap processor to the vacuum chamber. The biggest challenge, therefore, was to ensure that the device did not compromise on performance but the researchers are confident that their prototype is already delivering promising results.

Even outside of the controlled environment that can be achieved in a lab, the device was stable enough to operate without interruption from external disturbances, and the physicists were able to individually control and entangle up to 24 ions. Measurements showed that the system's performance and error rate were on par with lab-based implementations.

"We were able to show that compactness does not have to come at the expense of functionality," said Christian Marciniak, researcher at the University of Innsbruck.

By next year, the team is expecting to create a device with up to 50 individually controllable qubits.

For now, however, the prototype's hardware and software capabilities will be further upgraded before it is made available online. Researchers will access the device over the cloud to test quantum algorithms on a hardware-agnostic quantum computing language.

Here is the original post:
Quantum computers take up a lot of space. Researchers decided to shrink this one down - ZDNet

Elevate your enterprise data technology and strategy at Transform 2021.

The thing that really attracted me to Formula 1 is that its always been about data and technology, says Graeme Hackland, Williams Group IT director and chief information officer of Williams Racing.

Since joining the motorsport racing team in 2014, Hackland has been putting that theory into practice. He is pursuing what he refers to as a data-led digital transformation agenda that helps the organizations designers and engineers create a potential competitive advantage for the teams drivers on race day.

Hackland explains to VentureBeat how Williams F1 is looking to exploit data to make further advances up the grid and how emerging technologies, such as artificial intelligence (AI) and quantum computing, might help in that process.

This interview has been edited for clarity.

VentureBeat: Whats the aim of your data-led transformation process?

Graeme Hackland: Ten years ago, we might have been putting four major package upgrades on the car a year. Were now able to do that much more quickly, and we dont have to wait for big packages of changes. Our digital transformation has been focused on shortening that life cycle. Thats about getting something from a designers brain onto the car as quickly as possible. Test it on a Friday; if its good, it stays. If its not, we refine it, and just keep doing that through the season. And that process has gone really well.

VentureBeat: What kind of data technology are you using to support that process?

Hackland: Some of it is what you would in some industries consider standard data warehousing and business intelligence tools. Some of that is written in-house. At the moment, I dont have a piece of middleware that lies across the whole layer. But thats where we want to head to, so that absolutely everything is feeding into that.

VentureBeat: What would that piece of middleware look like?

Hackland: We originally thought of three main domains: design, manufacturing, and race engineering. And you would have these three bubbles that would all talk to each other. But what weve realized is trying to create data lakes just hasnt worked. It hasnt given us the actual intelligence that we wanted, so we often refer to data puddles. Its much better to have many of these puddles that are well-structured and the data is well understood. And then, through a middleware layer, we can get to the graphical user interfaces.

VentureBeat: What does that layer of information mean for the Williams F1 teams engineers?

Hackland: Were covering everything, from what they look at through to the data structure. And the data structure has been one of our biggest challenges. We relied heavily on Microsoft Excel, and pulling data from all these other sources into Excel was very manual it took too long. So thats the piece of work that weve been doing. Weve not made it public who were working with in that area. Talking publicly about some of the stuff were doing around data and computation, were just not ready yet.

VentureBeat: How do you work out the build vs. buy question?

Hackland: When I got to Williams, we were largely buy-only. We built an in-house capability across three groups: manufacturing, aerodynamics, and race engineering. So they have embedded development groups, and I think thats really important. We considered whether we were going to create a centralized development function. But actually, we feel having them in those three groups is really important. And then as you build those groups, the pendulum swings from buy-only because youve got the capability in-house. The default now is that we will always develop our own if we can. Where theres a genuine competitive advantage, wed develop it ourselves.

VentureBeat: Where might you choose to buy data technologies?

Hackland: Some of the tools that we use trackside are off-the-shelf. Its not all in-house-written, because it doesnt make sense to write your own in some areas. But if you dont write your own applications, youre also accepting that these applications are used by multiple teams. If its a race-engineering application, its probably used across Formula 1 and maybe in other formulas as well. So then you cant customize it and you cant get competitive advantage out of it because everyone else has access to it too. So sometimes well use those as maybe a front end and then well be doing other things in the background. When you start to combine that data with other information, thats when theres a real competitive advantage, and thats where weve put our internal resources.

VentureBeat: What about AI? Is that a technology youre investigating?

Hackland: None of the teams are talking about AI except in passing; theyre just mentioning that AI is being used. None of us want to talk about it yet, and where were applying it. But what weve said publicly is that there are some really interesting challenges that AI can logically be applied to and you get benefits straightaway. So pit stops, the rulebook there are roles that AI can play.

VentureBeat: Can you give me a sense of how AI might be applied in F1?

Hackland: Initially, to augment humans to give engineers more accurate data to work with, or to shortcut their decision-making process so that they can make the right decision more frequently. I felt, even five years ago, that it would be possible that AI could make a pit stop decision without any human intervention. So that is possible, but I dont believe any of the teams will be doing it this year, and we wont. The engineers are not ready, and the humans are not ready to be replaced by AI. So that might take a little bit of time to show them that we can. I think theres still that reluctance to completely hand over the decision-making process, and I can understand that.

VentureBeat: What about other areas of emerging technology?

Hackland: From my perspective, quantum computing is a really exciting opportunity to take computation to a whole new level. And if we can get in there early before the other teams, I think well have a real advantage. There are interesting things happening with some [racing] organizations around that. Once again, were not talking about it publicly, but quantum is completely awesome. I think quantum will take a while. I dont want to be sitting here saying that in the next two years that were going to be developing, designing, and running the car and doing the race analytics on a quantum computer. But a hybrid computer that has quantum elements to it? Absolutely, and within a couple of years. Im really excited about what were doing already.

Read more from the original source:
Williams F1 drives digital transformation in racing with AI, quantum - VentureBeat

June 2, 2021• Physics 14, s72

Merging ideas from neuroscience, machine learning, and quantum technology, researchers propose a new information-storage device.

Many recent computing advances derive their inspiration from models of the human brain. For example, researchers have created a machine-learning model that mimics the brains ability to recognize new patterns by recalling previously encountered ones. So far, implementations of associative memory have largely involved conventional silicon-chip-based computers. Now, Benjamin Lev of Stanford University and colleagues propose a way of implementing associative memory with multiple Bose-Einstein condensates (BECs) and an optical cavity. The researchers say that their method should be better at learning and recognizing patterns than the standard associative memory design.

A computer with associative memory stores information in a mathematical function that looks like a potential energy landscape with many local minima. Each local minimum corresponds to a separate piece of information. To retrieve that information, the device is initialized in some state close to the relevant minimum, and it then finds that minimum. This process effectively reconstructs data from imprecise versions of that data. While everyday technologies typically dont use associative memory techniques, researchers are interested in them because of their speed and their robustness to user mistakes.

The researchers proposed device stores information in the energy landscape of multiple, separated BECs contained within the same optical cavity. The spin of each BEC interacts with that of the others by scattering photons in the cavity. They can engineer the energy landscape of the system by manipulating the position of each BEC. To retrieve information, the BECs are collectively initialized in a particular spin state, which relaxes into an energy minimum that is imaged using light emitted from the cavity. The researchers think they can build this device in the near term, as they have already demonstrated all the elements in the design.

Sophia Chen

Sophia Chen is a freelance science writer based in Columbus, Ohio.

See the article here:
A Computer Memory Based on Cold Atoms and Light - Physics

The company said it contracted the expert under a one-year agreement to research tangible and disruptive optimisations that can be made within Bitcoin mining which could result in faster execution and energy savings

Quantum Blockchain PLC () said it signed a service agreement with a UK-based international cryptography expert specialising in cryptocurrency mining blockchain optimisations as part of a research & development (R&D) strategy for Bitcoin mining.

The AIM-listed company saidthere are tangible and disruptive optimisations that can be made within the Bitcoin mining process that could result in faster execution and energy savings. The first set of optimisations is expected to be ready for testing in the coming weeks.

Quantum also said the aim of the work is to improve the efficiency of Bitcoin mining by targeting a material reduction in energy usage and faster hash processing. Thiswill increase the probability of successful mining operations. The firmintends to apply for patents over any relevant intellectual property generated during the process.

Meanwhile, the group said existing and imminent mining optimisations are expected to be made available on commercial cores within the next three months, on field-programmable gate array (FPGA) computer chips within six months and ultimately on application-specific integrated circuit (ASIC) chips in the second half of 2022.

Quantum said this line of R&D represents one of its out-of-the-box solutions to achieve highly competitive Bitcoin mining results, adding it willexplore other proof-of-work cryptos and their competitive mining advantages alongside the cryptography expert.

As part of the service agreement, the firm said it has awarded the consultant options over 10mln new shares in the company exercisable at 5p each between February 15, 2022, and August 15, 2022.

Securing the services of an international expert, who already has significant experience and know-how in Bitcoin mining optimisations, is one of the first concrete moves by the company to challenge the substantial Bitcoin market, Quantums chief executive and chairman Francesco Gardin said in a statement.

The company is addressing, in parallel, other cutting-edge approaches to Bitcoin mining, including, among others, the use of quantum computing. More detailed announcements will be made in due course. We believe that this out-of-the-box approach gives us the potential to play a disruptive role in the Bitcoin mining industry, the CEO added.

Here is the original post:
Quantum Blockchain inks deal with cryptography expert to optimise Bitcoin mining operations - Proactive Investors UK

The CEOs of Americas biggest banks and financial institutionsBank of America BAC , Citigroup C , J.P. Morgan, Goldman Sachs GS , Morgan Stanley MS , and Wells Fargo WFC are getting a grilling today up on Capitol Hill.Theyll be asked about why theyve made so much money during COVID; and why they arent loaning out more money to help us recover from COVID; as well as getting the usual questions powerful bankers draw from our politicians, both Republicans and Democrats.

But theres one question they should be asked, but wont be: what are they doing to protect their assets and Americas financial industry against future quantum attack?Because getting the big banks to lead the charge in getting America quantum ready is as much a matter of social responsibility as promoting racial equity; and as fundamental to our national security as it is a matter of their bottom lines.

The Colonial Pipeline debacle has revealed how vulnerable our infrastructure is to cyberattack, including a future quantum computer attack.My last column revealed how important it is to use quantum and post-quantum solutions to protect our cyber vulnerabilities, now and in the future.This is even more true of our financial infrastructure, including our leading financial markets, our global payments system, and the Federal Reserve system itself.

NEW YORK, NEW YORK - MAY 11: The New York Stock Exchange stands in lower Manhattan after global ... [+] stocks fell as concerns mount that rising inflation will prompt central banks to tighten monetary policy on May 11, 2021 in New York City. By mid afternoon the tech-heavy Nasdaq Composite had lost 0.6% after falling 2.2% at its session low. (Photo by Spencer Platt/Getty Images)

Our preliminary econometric research at the Hudson Institutes Quantum Alliance Initiative indicates that the cost of a quantum computer attack on our financial system would be catastrophicfar more than a successful conventional cyberattack.In February authors Welburn and Strong of the RAND Corporation applied a standard Input-Output (I-O) model to conclude that cyber-attack disrupting JP Morgan Chases business operations for a single day would result in over $3.5 Billion in total losses for the American economy.

Unfortunately, that model ignored the network contagion effects within the financial sector.We estimate that a single quantum attack on one of the five largest financial institutions in the U.S. that disrupts their access to the Fedwire Funds Service payment system would cause a cascading financial failure costing anywhere from $730 Billion to $1.95 Trillion.Indeed, a quantum computer attack could impair nearly 60% of total assets in the banking system due to bank runs and endogenous liquidity traps.

We know from conversations with Treasury Department officials that banks and the Fed work closely with the federal government and Treasury on cybersecurity issues.But despite warnings from the last Office of Financial Research report on the quantum risk to financial stability, theres still a big hole when it comes to confronting the quantum threat.In fact, the big banks interest in quantum computers tends to revolve around how those computers amazing capabilities will be to serve customers and analyze market trends and risks.Thus far only J.P. Morgan and VISA V seem to be thinking about the day when a powerful quantum computer can break the most widespread cryptographic methods currently used in cybersecurity. The fact is, the leadership of all the big banks will be crucial for protecting our economy from a quantum-induced financial meltdown, or worse.

Therefore, its time to propose that the banks join together to create a Quantum Task Force made up of the countrys largest financial institutions, to promote quantum and post-quantum solutions to cyberattacks not just for themselves but throughout the financial system. Recent research from the New York Fed reveals that a cyberattack just one vulnerable mid-sized bank (less than $10 billion in assets, or less than five percent the size of Goldman Sachs) can bring down the whole system. Our preliminary study here at the Hudson Institutes Quantum Alliance Initiative indicates that the result would be catastrophic.

Offsetting a risk of this magnitude should be a national, as well as industry, imperative.Its a problem that wont wait until 2024 when NIST is expected to begin the roll out of its post-quantum cryptography standards. The array of tools currently available, from quantum-resistant algorithms and double encryption to quantum key distribution for the most vital corporate communications, can protect institutions today and tomorrow, against a quantum attack or the conventional threats that are already lurking out there.

It will no longer suffice to claim that the quantum threat is far off out on the horizonten years or morethat we dont have to worry about it before the next shareholders meeting. As my next column will show, the threat may be coming sooner than the experts have predicted.

Fortunately, our biggest financial institutions have the know-how, the resources, and the self-interest to lead us all into the post-quantum era.It is no exaggeration to say that none of us will be truly safe, until they are.

Read more from the original source:
Getting The Big Banks To Confront The Quantum Challenge - Forbes