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Time crystals. Microwaves. Diamonds. What do these three disparate things have in common?

Quantum computing. Unlike traditional computers that use bits, quantum computers use qubits to encode information as zeros or ones, or both at the same time. Coupled with a cocktail of forces from quantum physics, these refrigerator-sized machines can process a whole lot of information but theyre far from flawless. Just like our regular computers, we need to have the right programming languages to properly compute on quantum computers.

Programming quantum computers requires awareness of something called entanglement, a computational multiplier for qubits of sorts, which translates to a lot of power. When two qubits are entangled, actions on one qubit can change the value of the other, even when they are physically separated, giving rise to Einsteins characterization of spooky action at a distance. But that potency is equal parts a source of weakness. When programming, discarding one qubit without being mindful of its entanglement with another qubit can destroy the data stored in the other, jeopardizing the correctness of the program.

Scientists from MITs Computer Science and Artificial Intelligence (CSAIL) aimed to do some unraveling by creating their own programming language for quantum computing called Twist. Twist can describe and verify which pieces of data are entangled in a quantum program, through a language a classical programmer can understand. The language uses a concept called purity, which enforces the absence of entanglement and results in more intuitive programs, with ideally fewer bugs. For example, a programmer can use Twist to say that the temporary data generated as garbage by a program is not entangled with the programs answer, making it safe to throw away.

While the nascent field can feel a little flashy and futuristic, with images of mammoth wiry gold machines coming to mind, quantum computers have potential for computational breakthroughs in classically unsolvable tasks, like cryptographic and communication protocols, search, and computational physics and chemistry. One of the key challenges in computational sciences is dealing with the complexity of the problem and the amount of computation needed. Whereas a classical digital computer would need a very large exponential number of bits to be able to process such a simulation, a quantum computer could do it, potentially, using a very small number of qubits if the right programs are there.

Our language Twist allows a developer to write safer quantum programs by explicitly stating when a qubit must not be entangled with another, says Charles Yuan, an MIT PhD student in electrical engineering and computer science and the lead author on a new paper about Twist. Because understanding quantum programs requires understanding entanglement, we hope that Twist paves the way to languages that make the unique challenges of quantum computing more accessible to programmers.

Yuan wrote the paper alongside Chris McNally, a PhD student in electrical engineering and computer science who is affiliated with the MIT Research Laboratory of Electronics, as well as MIT Assistant Professor Michael Carbin. They presented the research at last week's 2022 Symposium on Principles of Programming conference in Philadelphia.

Untangling quantum entanglement

Imagine a wooden box that has a thousand cables protruding out from one side. You can pull any cable all the way out of the box, or push it all the way in.

After you do this for a while, the cables form a pattern of bits zeros and ones depending on whether theyre in or out. This box represents the memory of a classical computer. A program for this computer is a sequence of instructions for when and how to pull on the cables.

Now imagine a second, identical-looking box. This time, you tug on a cable, and see that as it emerges, a couple of other cables are pulled back inside. Clearly, inside the box, these cables are somehow entangled with each other.

The second box is an analogy for a quantum computer, and understanding the meaning of a quantum program requires understanding the entanglement present in its data. But detecting entanglement is not straightforward. You cant see into the wooden box, so the best you can do is try pulling on cables and carefully reason about which are entangled. In the same way, quantum programmers today have to reason about entanglement by hand. This is where the design of Twist helps massage some of those interlaced pieces.

The scientists designed Twist to be expressive enough to write out programs for well-known quantum algorithms and identify bugs in their implementations. To evaluate Twist's design, they modified the programs to introduce some kind of bug that would be relatively subtle for a human programmer to detect, and showed that Twist could automatically identify the bugs and reject the programs.

They also measured how well the programs performed in practice in terms of runtime, which had less than 4 percent overhead over existing quantum programming techniques.

For those wary of quantums seedy reputation in its potential to break encryption systems, Yuan says its still not very well known to what extent quantum computers will actually be able to reach their performance promises in practice. There's a lot of research that's going on in post-quantum cryptography, which exists because even quantum computing is not all-powerful. So far, there's a very specific set of applications in which people have developed algorithms and techniques where a quantum computer can outperform classical computers.

An important next step is using Twist to create higher-level quantum programming languages. Most quantum programming languages today still resemble assembly language, stringing together low-level operations, without mindfulness towards things like data types and functions, and whats typical in classical software engineering.

Quantum computers are error-prone and difficult to program. By introducing and reasoning about the purity of program code, Twist takes a big step towards making quantum programming easier by guaranteeing that the quantum bits in a pure piece of code cannot be altered by bits not in that code, says Fred Chong, the Seymour Goodman Professor of Computer Science at the University of Chicago and chief scientist at Super.tech.

The work was supported, in part, by the MIT-IBM Watson AI Lab, the National Science Foundation, and the Office of Naval Research.

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A new language for quantum computing | MIT News | Massachusetts Institute of Technology - MIT News

Quantum computers made from the same raw materials as standard computer chips hold obvious promise, but so far theyve struggled with high error rates. That seems set to change after new research showed silicon qubits are now accurate enough to run a popular error-correcting code.

The quantum computers that garner all the headlines today tend to be made using superconducting qubits, such as those from Google and IBM, or trapped ions, such as those from IonQ and Honeywell. But despite their impressive feats, they take up entire rooms and have to be painstakingly handcrafted by some of the worlds brightest minds.

Thats why others are keen to piggyback on the miniaturization and fabrication breakthroughs weve made with conventional computer chips by building quantum processors out of silicon. Research has been going on in this area for years, and its unsurprisingly the route that Intel is taking in the quantum race. But despite progress, silicon qubits have been plagued by high error rates that have limited their usefulness.

The delicate nature of quantum states means that errors are a problem for all of these technologies, and error-correction schemes will be required for any of them to reach significant scale. But these schemes will only work if the error rates can be kept sufficiently low; essentially, you need to be able to correct errors faster than they appear.

The most promising family of error-correction schemes today are known as surface codes and they require operations on, or between, qubits to operate with a fidelity above 99 percent. That has long eluded silicon qubits, but in the latest issue of Nature three separate groups report breaking this crucial threshold.

The first two papers from researchers at RIKEN in Japan and QuTech, a collaboration between Delft University of Technology and the Netherlands Organization for Applied Scientific Research, use quantum dots for qubits. These are tiny traps made out of semiconductors that house a single electron. Information can be encoded into the qubits by manipulating the electrons spin, a fundamental property of elementary particles.

The key to both groups breakthroughs was primarily down to careful engineering of the qubits and control systems. But the QuTech group also used a diagnostic tool developed by researchers at Sandia National Laboratories to debug and fine-tune their system, while the RIKEN team discovered that upping the speed of operations boosted fidelity.

A third group from the University of New South Wales took a slightly different approach, using phosphorus atoms embedded into a silicon lattice as their qubits. These atoms can hold their quantum state for extremely long times compared to most other qubits, but the tradeoff is that its hard to get them to interact. The groups solution was to entangle two of these phosphorus atoms with an electron, which enables them to talk to each other.

All three groups were able to achieve fidelities above 99 percent for both single qubit and two-qubit operations, which crosses the error-correction threshold. They even managed to carry out some basic proof-of-principle calculations using their systems. Nonetheless, they are still a long way from making a fault-tolerant quantum processor out of silicon.

Achieving high-fidelity qubit operations is only one of the requirements for effective error correction. The other is having a large number of spare qubits that can be dedicated to this task, while the remaining ones focus on whatever problem the processor has been set.

As an accompanying analysis in Nature notes, adding more qubits to these systems is certain to complicate things, and maintaining the same fidelities in larger systems will be tough. Finding ways to connect qubits across large systems will also be a challenge.

However, the promise of being able to build compact quantum computers using the same tried-and-true technology as existing computers suggests these are problems worth trying to solve.

Image Credit: UNSW/Tony Melov

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Quantum Computing in Silicon Breaks a Crucial Threshold for the First Time - Singularity Hub

Atom Computing

Atom Computing, a quantum computing company headquartered in Berkeley, California, seems to be on the fast track for funding.

This week Atom announced it had secured$60MSeries B round of financing led by Third Point Ventures. The round also included Prime Movers Lab and insiders Innovation Endeavors, Venrock, and Prelude Ventures.

Atom was founded in 2018 with $5M in seed funds by Benjamin Bloom and Jonathan King. Over two years, the duo used those funds to secretly staff and build a quantum computer with a unique technology. What set Atoms computer apart from other quantum machines was that it was the first quantum computer to use nuclear-spin qubits created from optically-trapped neutral atoms.

First-Generation Quantum Computer, Phoenix

In July 2021, Atom Computingreceived an additional $15M in Series A funding from investorsVenrock, Innovation Endeavors, and Prelude Ventures, plus three grants from the National Science Foundation.

According to a statement on Atom's press release by Rob Hays, Atom Computing's president and CEO, there was no shortage of investment interest. "We've seen a tremendous amount ofinvestor interest in what many are starting to believe is a more promising way to scale quantum computers neutral atoms, he said. Our technology advancements and this investment give us the runway to continue our focus on delivering the most scalable and reliable quantum computers."

Whats different about its technology

Most of todays quantum computers use two types of qubits, either superconducting (IBM & Google) or trapped-ion (Quantinum or IonQ). Amazon doesnt yet have a quantum computer, but it plans to build one using superconducting hardware. In contrast, Psi Quantum and Xanadu use photons of light that act as qubits.

Atom computing chose to use a different technology -nuclear-spin qubits made from neutral atoms.Phoenix, the name of Atoms first-generation, gate-based quantum computer platform, uses 100 optically trapped qubits.

These qubits are created from an isotope of Strontium, a naturally occurring element considered to be a neutral atom. Goingdeeper, neutral atoms have equal numbers of protons and electrons. However, isotopes of Strontium have varying numbers of neutrons. These differences in neutrons produce different energy levels in the atom that allow spin qubits to be created. Atom Computing uses the isotope Strontium-87 and takes advantage of its unique energy levels to create spin qubits.

It is important for qubits to remain in a quantum state long enough to complete running the quantum circuits. The time that a qubit retains its quantum state is called its coherence time. Neutral atom qubits have a longer coherence time than most other qubit technologies.

Lasers instead of wires are used for precision control of the strontium-87 qubits. Lasers eliminates wiring, which can create radiation and noise that negatively affects coherence.

There are many other technical reasons for using neutral atom spin qubits but beyond the scope of this article.

Second generation plans

Artist rendering of Atom Computings second-generation quantum

With its latest $60M Series B funding, Atom Computing plans to build a larger, second-generation neutral-atom quantum computer. Many additional qubits will give the system increased computational ability. Atom Computing is currently likely to have undisclosed customer trials and use cases in progress. However, we expect new and more significant use cases to be publicly announced once the new quantum system is operational.

Patrick Moorhead, president and chief analyst of Moor Insights and Strategy, said, Qubit coherence, fidelity, and scalability are essential factors for achieving quantum advantage. Atom Computing has already demonstrated that Phoenix, its first-generation 100+ nuclear-spin qubit quantum processor, has the potential to check all those boxes. With the additional $60M Series B funding, I believe Atom could build a large qubit, second-generation quantum system that either brings it to the edge of quantum advantage or possibly even achieves it.

Analyst notes:

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, or speaking sponsorships. The company has had or currently has paid business relationships with 88,A10 Networks,Advanced Micro Devices, Amazon,Ambient Scientific,AnutaNetworks,Applied Micro,Apstra,Arm, Aruba Networks (now HPE), AT&T, AWS, A-10 Strategies,Bitfusion, Blaize, Box, Broadcom, Calix, Cisco Systems, Clear Software, Cloudera,Clumio, Cognitive Systems, CompuCom,CyberArk,Dell, Dell EMC, Dell Technologies, Diablo Technologies,Dialogue Group,Digital Optics,DreamiumLabs, Echelon, Ericsson, Extreme Networks, Flex, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud,Graphcore,Groq,Hiregenics,HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM,IonVR,Inseego, Infosys,Infiot,Intel, Interdigital, Jabil Circuit, Konica Minolta, Lattice Semiconductor, Lenovo,Linux Foundation,Luminar,MapBox, Marvell Technology,Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco),Mesophere, Microsoft, Mojo Networks, National Instruments, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek,Novumind, NVIDIA,Nutanix,Nuvia (now Qualcomm), ON Semiconductor, ONUG, OpenStack Foundation, Oracle, Panasas,Peraso, Pexip, Pixelworks, Plume Design, Poly (formerly Plantronics),Portworx, Pure Storage, Qualcomm, Rackspace, Rambus,RayvoltE-Bikes, Red Hat,Residio, Samsung Electronics, SAP, SAS, Scale Computing, Schneider Electric, Silver Peak (now Aruba-HPE), SONY Optical Storage,Springpath(now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, TE Connectivity,TensTorrent,TobiiTechnology, T-Mobile, Twitter, Unity Technologies, UiPath, Verizon Communications,Vidyo, VMware, Wave Computing,Wellsmith, Xilinx,Zayo,Zebra,Zededa, Zoho, andZscaler.Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is a personal investor in technology companiesdMYTechnology Group Inc. VI andDreamiumLabs.

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Atom Computing Plans To Build A Bigger And Better High-Tech Quantum Computer With Its Latest $60 Million Series B Funding - Forbes

Johannes Oberreuter, Quantum Computing practice lead and data scientist at Reply, spoke to Information Age about how quantum computing is helping businesses to meet objectives

Quantum is emerging as a new vehicle for business problem solving.

Quantum computing is an evolving technology that promises to enhance an array of business operations. Based on quantum mechanics that focus on the smallest dimensions of nature molecules, atoms and subatomic particles quantum computers are set to provide faster solutions to complex business problems, through testing multiple possible solutions for a problem simultaneously.

The basis for quantum computing is a unit of information known as a qubit; unlike bits, which can only have the values zero or one, can come in the form of anything in between, which allows for this new approach to become possible, and is called a superposition. Combined, multiple qubits can produce many outcomes at the same time. Every extra qubit doubles the search space, which therefore grows exponentially.

Many companies are looking into how quantum can bolster industries and provide new use cases for businesses. One organisation thats exploring this space is Reply, which has been developing solutions for optimisation in logistics, portfolio management and fault detection, among other areas.

Discussing how Reply is helping to provide possible use cases to its clients, quantum computing expert Johannes Oberreuter said: We work on a level which translates the problem into a quantum language that is as universal as possible, and doesnt go too deep into the hardware.

The first thing weve found thats delivering value now is the domain of optimisation problems. An example is the travelling salesman problem, which has lots of applications in logistics, where complexities and constraints also need to be accounted for, like during the pandemic.

Very often, problems, which are found too complex to be optimised on common hardware, are tackled by some heuristics. Usually, theres a team or a person with experience in the domain, who can help with this, but they dont know yet that there are better solutions out there now. Quantum computing allows for problems being presented in a structured way similar to a wish list, containing all business complexities. They are all encoded into a so-called objective function, which can then be solved in a structured way.

Companies have used all sorts of algorithms and brain power to try to solve optimisation problems. Finding the optimum with an objective function is still a difficult problem to solve, but here a quantum computer can come to the rescue.

Pushing parameters

According to Oberreuter, once a quantum computer becomes involved in the problem solving process, the optimal solution can really be found, allowing businesses to find the best arrangements for the problem. While current quantum computers, which are suitable for this kind of problems, called quantum annealers now have over 5,000 qubits, many companies that enlist Replys services often find that problems they have require more than 16,000-20,000 variables, which calls for more progress to be made in the space.

You can solve this by making approximations, commented the Reply data scientist. Weve been writing a program that is determining an approximate solution of this objective function, and we have tested it beyond the usual number of qubits needed.

The system is set up in a way that prevents running time from increasing exponentially, which results in a business-friendly running time of a couple of seconds. This reduces the quality of the solution, but we get a 10-15% better result than what business heuristics are typically providing.

Through proofs-of-concepts, Reply has been able to help clients to overcome the challenge of a lack of expertise in quantum. By utilising and building up experience in the field, a shoulder-to-shoulder approach helps to clarify how solutions can be developed more efficiently.

Machine learning has risen in prominence over the last few years to aid automation of business processes with data, and help organisations meet goals faster. However, machine learning projects can sometimes suffer from lack of data and computational expense. To combat this, Reply has been looking to the problem solving capabilities brought by quantum computing.

Oberreuter explained: What weve discovered with quantum machine learning is you can find better solutions, even with the limited hardware thats accessible currently. While there will probably never be an end-to-end quantum machine learning workflow, integration of quantum computing into the current machine learning workflow is useful.

Some cloud vendors now offer quantum processing units (QPUs). In a deep learning setup for complex tasks, you could easily rent it from the cloud providers by individual calls to experiment, if it improves your current model.

What weve found interesting from our contribution towards the quantum challenge undertaken by BMW and AWS, is the marriage of classical machine learning models with quantum models. The former is really good at extracting attributes from unstructured data such as images, which are then joined by a quantum representation which provides an advantage for classification.

How organisations can drive value from AI on the edge

Mike Ellerton, partner at Go Reply, spoke to Information Age about Replys recent research conducted into edge AI, and how organisations can drive value from the technology. Read here

Additionally, quantum technologies are being explored for cyber security, with the view that soon quantum computers can solve problems that are currently insurmountable for todays technologies. A particular algorithm thats been cited by Reply, that could be solved by quantum computing, is the one used for RSA key cryptography, which while trusted to be secure now, is estimated to need 6000 error-free qubits to be cracked in the space of two weeks.

Quantum technology for cyber security is now on the shelf, and were offering this to our clients to defend against this threat, said Oberreuter. Quantum mechanics have a so-called no-cloning theorem, which prevents users from copying messages sent across a communication channel. The crux is that in order for this to work, you need a specialised quantum channel.

We have experts who specialise in cyber security, that have been leading the effort to craft an offering for this.

Reply is a network of highly specialised industry companies, that helps clients across an array of sectors to optimise and integrate processes, applications and devices using the latest technologies. Established in 1996, the organisation offers services for capabilities including quantum, artificial intelligence (AI), big data, cloud and the Internet of Things (IoT). More information on the services that Reply provides can be found here.

This article was written as part of a paid-for content campaign with Reply

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How quantum computing is helping businesses to meet objectives - Information Age

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The last time we covered Arqit Quantum (NASDAQ:ARQQ) was when it was still Centricus Acquisition Corp, the SPAC that we invested a small, speculative exposure in. The thesis remains mostly unchanged. Using symmetric keys is secure, given trust can be established between the parties sharing the key, and that this is basically the only tenable solution against quantum computing, which can break any encryption based on mathematics. The commercial value of the product is being backed up by early adopters who are signing up for long-term commitments with Arqit and have mission-critical data needs. Arqit will have gone from pre to post-revenue as of the end of 2021, and we believe that as an end of the world hedge, unlike crypto which could by the way be universally dismantled by quantum computing in a few instants, Arqit fits the bill perfectly.

The whole space of cybersecurity tends to be wholly underinvested. Not until a data breach occurs do most companies ever really think about their cybersecurity needs. Indeed, it's a segment that still has quite the room to grow.

Arqit Quantum

Companies that do understand the importance of cybersecurity are the ones that make up Arqit's already developing pipeline.

Arqit Quantum

The UK government, major Japanese conglomerates, IoT, telco and defense companies all make up the current pipeline. Companies like Babcock (OTCPK:BCKIF) and Northrop Grumman (NYSE:NOC) already have signed agreements with Arqit to both use and collaborate in developing as many use cases for Arqit's courier-like model for symmetric keys. The companies share a common need to protect data communications for mission-critical uses. In particular the defense companies are a vote of confidence for the use-cases and necessity of symmetric key courier infrastructure for data communication.

One of the key selling points of Arqit is also the fact that as opposed to dramatic infrastructure shifts or an arms race of encryption algorithms that might have otherwise been required to defend against the quantum threat, Arqit uses immutable and unbeatable properties of photon transmission in conjunction with encryption algorithms that have been used in the past by banks and governments, with literal couriers transporting them. Arqit is just an outsourced courier-like service that for now uses just the cloud and terrestrial data centers run its platform, but will eventually launch satellites with small, but exceptionally powerful computers that will be able to root keys that will be generated between recipients and senders of data using random numbers and a proprietary protocol. The addressable market is therefore every networked device between which safe transmission of data is desirable, and the system makes symmetric keys, which traditionally required high-levels of interparty trust in exchange for security, a totally trustless system.

The revenue and EBITDA projections, which are based on these recurring revenue contracts with the customers in the pipeline, amount to the following and imply the following multiples on forward earnings.

The Value Lab

While revenues and profits are only getting started in FY 2022, 2023 is when we start to see more meaningful EBITDA. With the addressable market including all interconnected devices where privacy is important, even at the 2025 forecast levels, we are of course still at a very nascent stage for this market.

The quantum threat is still a while away. People are not close to working a quantum computer yet, but the point is that it's inevitable, and if you aren't prepared the moment a quantum computer comes online, perhaps in the hands of a quite hostile government or entity, then it will be an instant before that quantum computer decrypts all your data for whatever purposes they might have had for it. With the core market of mission-critical use-cases already forming a nice revenue base for a recurring model with strong theoretical economics, and the further commercialization possible into the broader addressable market, the current valuation, while already acknowledging the uniqueness and timeliness of the Arqit offer, is probably a long way off from where it could be in the next 10-15 years when all networks are threatened by quantum attacks.

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Arqit Quantum Is Terrestrial For Now, But Will Go To Space - Seeking Alpha