Category Archives: Quantum Computing

Rolls-Royce, Riverlane, and Xanadu Team Up on Grants from the UK and Canadian Governments to Develop Quantum Jet Engine Design – Quantum Computing…

Posted on by

Rolls-Royce, Riverlane, and Xanadu Team Up on Grants from the UK and Canadian Governments to Develop Quantum Jet Engine Design  Quantum Computing Report

Read the rest here:
Rolls-Royce, Riverlane, and Xanadu Team Up on Grants from the UK and Canadian Governments to Develop Quantum Jet Engine Design - Quantum Computing...

Quantum computers in 2023: how they work, what they do, and where they …

Posted on by

In June, an IBM computing executive claimed quantum computers were entering the utility phase, in which high-tech experimental devices become useful. In September, Australias Chief Scientist Cathy Foley went so far as to declare the dawn of the quantum era.

This week, Australian physicist Michelle Simmons won the nations top science award for her work on developing silicon-based quantum computers.

Obviously, quantum computers are having a moment. But to step back a little what exactly are they?

One way to think about computers is in terms of the kinds of numbers they work with.

The digital computers we use every day rely on whole numbers (or integers), representing information as strings of zeroes and ones which they rearrange according to complicated rules. There are also analogue computers, which represent information as continuously varying numbers (or real numbers), manipulated via electrical circuits or spinning rotors or moving fluids.

Read more: There's a way to turn almost any object into a computer and it could cause shockwaves in AI

In the 16th century, the Italian mathematician Girolamo Cardano invented another kind of number called complex numbers to solve seemingly impossible tasks such as finding the square root of a negative number. In the 20th century, with the advent of quantum physics, it turned out complex numbers also naturally describe the fine details of light and matter.

In the 1990s, physics and computer science collided when it was discovered that some problems could be solved much faster with algorithms that work directly with complex numbers as encoded in quantum physics.

The next logical step was to build devices that work with light and matter to do those calculations for us automatically. This was the birth of quantum computing.

We usually think of the things our computers do in terms that mean something to us balance my spreadsheet, transmit my live video, find my ride to the airport. However, all of these are ultimately computational problems, phrased in mathematical language.

As quantum computing is still a nascent field, most of the problems we know quantum computers will solve are phrased in abstract mathematics. Some of these will have real world applications we cant yet foresee, but others will find a more immediate impact.

One early application will be cryptography. Quantum computers will be able to crack todays internet encryption algorithms, so we will need quantum-resistant cryptographic technology. Provably secure cryptography and a fully quantum internet would use quantum computing technology.

In materials science, quantum computers will be able to simulate molecular structures at the atomic scale, making it faster and easier to discover new and interesting materials. This may have significant applications in batteries, pharmaceuticals, fertilisers and other chemistry-based domains.

Quantum computers will also speed up many difficult optimisation problems, where we want to find the best way to do something. This will allow us to tackle larger-scale problems in areas such as logistics, finance, and weather forecasting.

Machine learning is another area where quantum computers may accelerate progress. This could happen indirectly, by speeding up subroutines in digital computers, or directly if quantum computers can be reimagined as learning machines.

In 2023, quantum computing is moving out of the basement laboratories of university physics departments and into industrial research and development facilities. The move is backed by the chequebooks of multinational corporations and venture capitalists.

Contemporary quantum computing prototypes built by IBM, Google, IonQ, Rigetti and others are still some way from perfection.

Read more: Error correcting the things that go wrong at the quantum computing scale

Todays machines are of modest size and susceptible to errors, in what has been called the noisy intermediate-scale quantum phase of development. The delicate nature of tiny quantum systems means they are prone to many sources of error, and correcting these errors is a major technical hurdle.

The holy grail is a large-scale quantum computer which can correct its own errors. A whole ecosystem of research factions and commercial enterprises are pursuing this goal via diverse technological approaches.

The current leading approach uses loops of electric current inside superconducting circuits to store and manipulate information. This is the technology adopted by Google, IBM, Rigetti and others.

Another method, the trapped ion technology, works with groups of electrically charged atomic particles, using the inherent stability of the particles to reduce errors. This approach has been spearheaded by IonQ and Honeywell.

A third route of exploration is to confine electrons within tiny particles of semiconductor material, which could then be melded into the well-established silicon technology of classical computing. Silicon Quantum Computing is pursuing this angle.

Yet another direction is to use individual particles of light (photons), which can be manipulated with high fidelity. A company called PsiQuantum is designing intricate guided light circuits to perform quantum computations.

There is no clear winner yet from among these technologies, and it may well be a hybrid approach that ultimately prevails.

Attempting to forecast the future of quantum computing today is akin to predicting flying cars and ending up with cameras in our phones instead. Nevertheless, there are a few milestones that many researchers would agree are likely to be reached in the next decade.

Better error correction is a big one. We expect to see a transition from the era of noisy devices to small devices that can sustain computation through active error correction.

Another is the advent of post-quantum cryptography. This means the establishment and adoption of cryptographic standards that cant easily be broken by quantum computers.

Read more: Quantum computers threaten our whole cybersecurity infrastructure: here's how scientists can bulletproof it

Commercial spin-offs of technology such as quantum sensing are also on the horizon.

The demonstration of a genuine quantum advantage will also be a likely development. This means a compelling application where a quantum device is unarguably superior to the digital alternative.

And a stretch goal for the coming decade is the creation of a large-scale quantum computer free of errors (with active error correction).

When this has been achieved, we can be confident the 21st century will be the quantum era.

Read the original:
Quantum computers in 2023: how they work, what they do, and where they ...

Multiverse and Single Quantum Receive a $1.4 Million Contract from the German Aerospace Center (DLR) for Quantum Materials Science Research – Quantum…

Posted on by

Multiverse and Single Quantum Receive a $1.4 Million Contract from the German Aerospace Center (DLR) for Quantum Materials Science Research  Quantum Computing Report

Originally posted here:
Multiverse and Single Quantum Receive a $1.4 Million Contract from the German Aerospace Center (DLR) for Quantum Materials Science Research - Quantum...

What Is Quantum Computing? The Complete WIRED Guide | WIRED

Posted on by

You may have heard that a qubit in superposition isboth 0 and 1 at the same time. Thats not quite true and also not quite false. The qubit in superposition has someprobability of being 1 or 0, but it represents neither state, just like our quarter flipping into the air is neither heads nor tails, but some probability of both. In the simplified and, dare we say, perfect world of this explainer, the important thing to know is that the math of a superposition describes the probability of discovering either a 0 or 1 when a qubit is read out. The operation of reading a qubits value crashes it out of a mix of probabilities into a single clear-cut state, analogous to the quarter landing on the table with one side definitively up. A quantum computer can use a collection of qubits in superpositions to play with different possible paths through a calculation. If done correctly, the pointers to incorrect paths cancel out, leaving the correct answer when the qubits are read out as 0s and 1s.

For some problems that are very time-consuming for conventional computers, this allows a quantum computer to find a solution in far fewer steps than a conventional computer would need. Grovers algorithm, a famous quantum search algorithm, could find you in a phone book of 100 million names with just 10,000 operations. If a classical search algorithm just spooled through all the listings to find you, it would require 50 million operations, on average. For Grovers and some other quantum algorithms, the bigger the initial problemor phone bookthe further behind a conventional computer is left in the digital dust.

The reason we dont have useful quantum computers today is that qubits are extremely finicky. The quantum effects they must control are very delicate, and stray heat or noise can flip 0s and 1s or wipe out a crucial superposition. Qubits have to be carefully shielded, and operated at very cold temperaturessometimes only fractions of a degree above absolute zero. A major area of research involves developing algorithms for a quantum computer to correct its own errors, caused by glitching qubits. So far, it has been difficult to implement these algorithms because they require so much of the quantum processors power that little or nothing is left to crunch problems. Some researchers, most notably at Microsoft, hope to sidestep this challenge by developing a type of qubit out of clusters of electrons known asa topological qubit. Physicists predict topological qubits to be more robust to environmental noise and thus less error-prone, but so far theyve struggled to make even one. After announcing a hardware breakthrough in 2018, Microsoft researchersretracted their work in 2021 after other scientists uncovered experimental errors.

Still, companies have demonstrated promising capability with their limited machines. In 2019, Google useda 53-qubit quantum computer to generate numbers that follow a specific mathematical pattern faster than a supercomputer could. The demonstration kicked off a series of so-called quantum advantage experiments, which saw an academic group in Chinaannouncing their own demonstration in 2020 and Canadian startup Xanaduannouncing theirs in 2022. (Although long known as quantum supremacy experiments, many researchers have opted tochange the name to avoid echoing white supremacy.) Researchers have been challenging each quantum advantage claim by developing better classical algorithms that allow conventional computers to work on problems more quickly,in a race that propels both quantum and classical computing forward.

Meanwhile, researchers havesuccessfully simulatedsmall molecules using a few qubits. These simulations dont yet do anything beyond the reach of classical computers, but they might if they were scaled up, potentially helping the discovery of new chemicals and materials. While none of these demonstrations directly offer commercial value yet, they have bolstered confidence and investment in quantum computing. After having tantalized computer scientists for 30 years, practical quantum computing may not exactly be close, but it has begun to feel a lot closer.

What the Future Holds for Quantum Computing

Error-prone but better than supercomputers at a cherry-picked task, quantum computers have entered their adolescence. Its not clear how long this awkward phase will last, and like human puberty it can sometimes feel like it will go on forever. Researchers in the field broadly describe todays technology as Noisy Intermediate-Scale Quantum computers, putting the field in the NISQ era (if you want to be popular at parties, know that its pronounced nisk). Existing quantum computers are too small and unreliable to execute the fields dream algorithms, such as Shors algorithm for factoring numbers.

The question remains whether researchers can wrangle their gawky teenage NISQ machines into doing something useful. Teams in both the public and private sector are betting so, as Google, IBM, Intel, and Microsoft have all expanded their teams working on the technology, with a growing swarm of startups such as Xanadu and QuEra in hot pursuit. The US, China, and the European Union each have new programs measured in the billions of dollars to stimulate quantum R&D. Some startups, such as Rigetti and IonQ, have even begun trading publicly on the stock market bymerging with a so-calledspecial-purpose acquisition company, or SPACa trick to quickly gain access to cash. Their values havesince plummeted, in some cases by much more than the pandemic correction seen more broadly across tech companies. Its not quite clear what the first killer apps of quantum computing will be, or when they will appear. But theres a sense that whichever company is first to make these machines useful will gain big economic and national security advantages.

More here:
What Is Quantum Computing? The Complete WIRED Guide | WIRED

Baidu Ends Its Quantum Computing Research and Donates Lab and Equipment to the Beijing Academy of Quantum Information Sciences – Quantum Computing…

Posted on by

Baidu Ends Its Quantum Computing Research and Donates Lab and Equipment to the Beijing Academy of Quantum Information Sciences  Quantum Computing Report

Continue reading here:
Baidu Ends Its Quantum Computing Research and Donates Lab and Equipment to the Beijing Academy of Quantum Information Sciences - Quantum Computing...