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A new phase of matter previously recognized only in theory has been created by researchers using a quantum processor, which demonstrates the control of an exotic form of particles called non-Abelian anyons.

Neither fermions nor bosons, these exotic anyons fall someplace in between and are believed only to be able to exist in two-dimensional systems. Controlling them allowed the creation of an entirely new phase of matter the researchers now call non-Abelian topological order.

In our everyday world of three dimensions, just two types of particles exist: bosons and fermions. Bosons include light, as well as the subatomic particle known as the Higgs boson, whereas fermions comprise protons, neutrons, and electrons that constitute the matter throughout our universe.

Non-Abelian anyons are identified as quasiparticles, meaning that they are particle-like manifestations of excitation that persist for periods within a specific state of matter. They are of particular interest for their ability to store memory, which may have a variety of technological applications, particularly in quantum computing.

One of the reasons for this is because of the stability non-Abelian anyons possess when compared to qubits, which are currently used in quantum computing platforms. Unlike qubits, which can at times be less than reliable, non-Abelian anyons can store information as they move around one another without the influence of their environment, making them ideal targets for use in computational systems once they can be harnessed at larger scales.

In recent research, Ashvin Vishwanath, the George Vasmer Leverett Professor of Physics at Harvard University, used a quantum processor to test how non-Abelian anyons might be leveraged to perform quantum computation.

One very promising route to stable quantum computing is to use these kinds of exotic states of matter as the effective quantum bits and to do quantum computation with them, said Nat Tantivasadakarn, a former Harvard student now at Caltech, who participated in the research.

To achieve this unique and exotic state of matter, the team devised an experiment that, in principle, was simple: they decided to push the capabilities of Quantinuums newest H2 processor to its limits.

Beginning with 27 trapped ions, the team employed a series of partial measurements designed to follow a sequence in which their complexity increased within the quantum system, which would result in a quantum wave function possessing the characteristics of the particular particles they hoped to generate.

Vishwanath likened their efforts to sculpting a specific state through the process of measurement, a component of the research process that has led physicists in the past to greatand at times perplexingdiscoveries.

Measurement is the most mysterious aspect of quantum mechanics, Vishwanath said, leading to famous paradoxes like Schrdingers cat and numerous philosophical debates.

Employing an adaptive circuit on Quantinuums H2 trapped-ion quantum processor, Vishwanath and his team were successfully able to drive the processor to its limits, allowing them to create and move anyons along what are known as Borromean rings, used in mathematics to describe a trio of closed curves in three-dimensional space that are linked topologically, and are unable to be separated.

Under such conditions, non-Abelian anyons tunneled around a torus created all 22 ground states, as well as an excited state with a single anyona peculiar feature of non-Abelian topological order, the team writes in a newly published study.

This work illustrates the counterintuitive nature of non-Abelions and enables their study in quantum devices, they conclude.

At least for me, it was just amazing that it all works, and that we can do something very concrete, Vishwanath recently told the Harvard Gazette.

It really connects many different aspects of physics over the years, from foundational quantum mechanics to more recent ideas of these new kinds of particles.

Vishwanath, Tantivasadakarn, and their colleague Ruben Verresen were all co-authors on the teams new paper, Non-Abelian topological order and anyons on a trapped-ion processor, which appeared in the journal Nature on February 14, 2024.

Micah Hanks is the Editor-in-Chief and Co-Founder of The Debrief. He can be reached by email atmicah@thedebrief.org. Follow his work atmicahhanks.comand on X:@MicahHanks.

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New Phase of Matter Created During Experiments with Exotic Particles in Quantum Processor - The Debrief

Australias National Supercomputing and Quantum Computing Innovation Hub is set to use Nvidia Grace Hopper Superchips to push the boundaries of quantum computing. In a news release sent to Toms Hardware, Nvidia says that the Pawsey Supercomputing Research Centre in Perth will deploy eight Nvidia Grace Hopper Superchip nodes to power the open-source CUDA Quantum computing platform. It is expected that the new supercomputer will be able to deliver up to 10x higher processing performance than the center has access to now.

The stated purpose of the Grace Hopper Superchip nodes in Pawsey is for researchers at the center to run powerful simulation tools and hopefully make breakthroughs in fields like algorithm discovery, device design, quantum machine learning, chemistry simulations, image processing for radio, astronomy, financial analysis, bioinformatics, and more. It is also hoped to advance scientific exploration in Australia and the world.

The Nvidia Grace Hopper Superchips Grace CPU and Hopper GPU architectures are central to the above aspirations and the Nvidia cuQuantum software development kit. This powerful hardware and software melding forms the green teams open-source hybrid quantum computing platform, known more succinctly as the CUDA Quantum platform.

At Pawsey, eight Grace Hopper Superchip nodes based on the Nvidia MGX modular architecture will be deployed, according to the press release we received. It explains that GH200 Superchips eliminates the need for a traditional CPU-to-GPU PCIe connection by combining an Arm-based Nvidia Grace CPU with an Nvidia H100 Tensor Core GPU in the same package, using Nvidia NVLink-C2C chip interconnects MGX modular architecture. A significant benefit of the new interconnects is that the bandwidth between the GPU and CPU is seven times greater than the latest PCIe technology. Moreover, the researchers in Australia are looking forward to a ten-fold increase in application performance when processing data sets measured in terabytes.

We asked Nvidia for some more technical details about the Superchip nodes at Pawsey. It turns out that each node will be using 'just' a single GH200 with Grace CPU and a H100 96GB of HBM3. Thus, the new installation at Pawsey Supercomputing Research Centre in Perth will feature eight nodes each with one GH200 for a total of 8x GH200 (8x Grace CPU and 8x H100 96GB GPU).

One of the other major appealing features of the Nvidia CUDA Quantum platform is that it offers a hybrid solution bridging the worlds of quantum and classical computing. Nvidia claims it is a first-of-its-kind and enables dynamic workflows across disparate system architectures. Researchers can use this platform to integrate and program quantum processing units (QPUs), GPUs, and CPUs in one system. It is also, of course, GPU-accelerated for scalability and performance.

The installation of the new Nvidia Grace Hopper Superchip nodes at Pawsey isnt purely for advancing knowledge or solving some esoteric scientific problems. The Australian government also reckons investments like this make good business sense. According to Australias national science agency, the domestic market opportunity offered by quantum computing is set to be worth $2.5 billion per annum. Additionally, it is estimated that quantum advances could create 10,000 new Australian jobs by 2040.

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Nvidia Grace Hopper Superchip poised to push the boundaries of quantum computing in Australia - Tom's Hardware

Australian quantum computing startup Diraq Pty Ltd. said today it has closed on a $15 million capital raise that will be used to advance its research into a novel concept for building the physical qubits that power quantum computers.

The Series A-2 round was led by Quantonation, a specialist venture capital fund thats focused on quantum computing technologies, and saw participation from Higgins Family Investments and the University of New South Wales, Sydney. The round extends Diraqs original $20 million Series A raise, which closed in May 2022, according to PitchBook data. All told, Diraq has now raised more than $120 million, with the bulk of those funds coming from various Australian and U.S. government funding programs.

The Sydney-based startup is working on the development of quantum processors that rely on electron spins in complementary metal-oxide semiconductor quantum dots. In other words, it claims to be able to make quantum chips using existing chipmaking technologies. The main advantage of using silicon-based qubits the quantum version of the classic binary bit is that this technology could potentially leverage the semiconductor industrys existing infrastructure, meaning they can be manufactured without investing millions of dollars in new quantum chip fabs.

Diraqs silicon-based qubits are very different from the superconducting and ion-trapped counterparts being developed by companies such as IBM Corp. and IonQ Inc., although the research is perhaps not quite as advanced. Although those rivals have already made cloud-based systems available to customers, Diraq is not yet ready to do so. However, the startup insists that its technology remains the only viable way to scale quantum computers to support commercial-scale applications.

Most experts agree that quantum computers will need millions, if not billions of qubits to obtain an advantage over classical computers. But at present, most existing quantum machines can only support thousands of qubits.

Diraq says its approach will allow it to build a full-stack quantum computer that can move the nascent industry toward truly fault-tolerant computing. Already, it claims to have demonstrated superior qubit control with enough fidelity to allow for scalable error correction. This is necessary because in existing systems, the qubits are inherently unstable, introducing errors into quantum calculations that get worse as those systems scale.

The startup claims to have patents covering a detailed CMOS-based architecture for billions of qubits, capable of full error correction, together with advanced methods for qubit control, quantum memory, as well as innovative CMOS device designs.

Diraq co-founder and Chief Executive Andrew Dzurak (pictured, center) said that billions of qubits will be required to see useful quantum computing deployed cost-efficiently in a commercial timeframe. We are working closely with our foundry partners to drive qubit development based on tried and tested CMOS techniques coupled with our proprietary designs, he explained. We are focused on delivering energy-efficient processors with billions of qubits on one chip contained in one refrigerator, rather than thousands of chips and refrigerators requiring hundreds of square meters of space in a warehouse.

Analyst Holger Mueller of Constellation Research Inc. said Diraqs confidence in its approach to quantum computing makes it a promising proposition. It would be a major breakthrough in quantum computing if Diraq is able to use existing CMOS infrastructure to build those incredibly unstable qubits, Mueller said. Its too early to tell if the approach will be successful, but the funding will certainly help, and those who have a stake in the quantum revolution would do well to keep an eye out for whatever Diraq comes up with next.

Quantonation partner Will Zeng said the startups main focus going forward will be to develop a working quantum device using a standard semiconductor foundry. This milestone will serve as a proof point, solidifying the viability of Diraqs technology and propelling the companys ambitious scale-up program aimed at constructing the most powerful quantum computers in the world, he added.

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Quantum computing startup Diraq raises $15M to build qubits using traditional silicon chips - SiliconANGLE News

In a thought experiment that would be inadvisable to put into practice, Erwin Schrdinger argued that if a cat were placed in a sealed box with a mechanism that may or may not trigger the release of poison to kill the animal, it would be both dead and alive at the same time. Besides inadvertently raising the blood pressure of cat lovers a demographic thatshouldn't be messed with he was trying to demonstrate the idea of quantum superposition, the theory behind qubits and quantum computing.

Conventional computers as well as phones, tablets and everything else with a computing element rely on bits, the smallest possible units of information. Each of them can only hold a single value at a time traditionally represented as a one or zero. Anything stored or processed in a computer is, deep under the surface, converted by programming languages to ones and zeros the lowercase letter "a," for example goes by "1100001." A single GB of data, about the volume of streaming Netflix for an hour, represents over 8.5 billion bits, meaning ones or zeros. Printed out, that would be almost 3 million pages (don't try this at home.)

That slightly abstract piece of information gets much more complicated when it comes to quantum computing. Quantum bits, or qubits, can flicker between the two states a little like a tossed coin except with differing probabilities. Crucially, qubits can also be entangled to always land on the same result, which means a single string can store multiple pieces of information simultaneously.

Quantum in the cloud

As a result, quantum computers are said to have the potential to store and process more information than even the most advanced supercomputers relying on conventional bits. Scientists expect they will lend themselves particularly well to tasks that require the analysis of different combinations of factors, such as discovering new materials, battery chemistries orplanning traffic.

Still, these use cases are not here yet. The quantum computers available today cannot do anything conventional computers can't and there are some significant quirks that still need to be overcome. Crucially,the number of qubitsinside a quantum computer will need to increase, and the technology's susceptibility toerrors caused by environmental noisehas yet to be fully resolved.

None of this has prevented companies, including many telcos, from hopping aboard the bandwagon. For example, Deutsche Telekom's T-Systems, which providesdigital and IT solutions to businesses, already offers cloud access to quantum computers.

It has teamed up with several companies producing quantum computers, giving customers access to different types of the technology, with each company creating qubits in a different way. For now, the platform includes computers from market heavyweight IBM, alongside IQM and AQT.

T-Systems has also partnered with European platform PlanQK, which is developing a quantum computing ecosystem. As a result, customers have access to ready-made quantum algorithms andapplications. While these do not currently outperform conventional computers,PlanQKsays the idea behind the project is to allow developers to gain knowledge about specific hardware platforms and build the skills required.

In future, more telcos could venture in a similar direction. Andrew Lord, the senior manager of optical networks and quantum research atBT, told Light Reading during an interview that the company would consider selling access to cloud computers in future, perhaps as part of a broader computing platform.

The issue, Lord says, is that quantum computers alone will not be able to solve many of the problems put to them. The goal, then, is to provide a more generic service with quantum as one of the elements included.

"The challenge is, how can you orchestrate between that? So how do you take a problem from a customer and say, the best way of solving this problem is in this combination of compute, whether it's high performance computing, quantum computing, other types, and how do you orchestrate between all of that." The result would be a holistic computing and networking environment, where a customer only pays for the computing time they need. "So that that then becomes a resource scheduling kind of problem, which we're good at," said Lord.

Quantum radio

Yet another area of quantum relevant to telcos is quantum sensing. It uses quantum physics to create what Lord calls ridiculously sensitive sensors that can "pinpoint the location of something down to millimeters," pick up on the vibration of a fiber to deduce that a car has driven on a road above it, or provide alerts about leaking pipes.

Such functionalities could help telcos, which often run extensive fiber optic networks, to better utilize those assets. Because of quantum sensors' higher sensitivity, which can increase communication ranges, the technology could also yield better radios. In the long run, quantum radio could improve mapping and cell phone communications indoors, underwater, underground and in urban canyons.

In 2022, BT trialled quantum antenna technology that relies on excited atomic states, increasing sensitivity compared with traditional technologies. Its atomic radio frequency receiver can pick up weaker signals, and it could be placed inside passive optical receivers in hard-to-reach areas to improve mobile coverage. According to the company, the technology is still in its early stages, but it could eventually make smart cities, IoT and smart agriculture cheaper to implement.

The demonstration used digital modulation within one of EE's main commercial 5G frequency ranges. And earlier this year, the company used a quantum optical radio receiver to make a three-way Microsoft Teams call between three UK locations using EE's 4G spectrum. While a lot of quantum technology might still be far from deployment, BT reckons this particular technology could be deployed in three to five years' time, reportedTelcoTitans.

Although quantum computing and sensing have clearly caught the eye of the telecom industry, it's impossible to tell when these technologies may be ready for prime time, especially in the case of quantum computing. But unlike Schrdinger's unlucky cat, we at least know they are alive and kicking.

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Telcos jostle for position ahead of quantum leap - Light Reading

Where we are currently, and where we are headed

Quantum computing is a technology that exploits the laws of quantum mechanics to solve problems too complex for classical computers. The first significant contribution to the development of quantum computing occurred in 1982, when Richard Feynman postulated that to simulate the evolution of quantum systems in an efficient way, we would need to build quantum computers (computational machines that use quantum effects). Nevertheless, it was not until 1994 that the view on quantum computing changed. Peter Shor developed a polynomial time quantum algorithm allowing quantum computers to efficiently factorize large integers exponentially quicker than the best classical algorithm on traditional machines, turning a problem which is computationally intractable into one that can be solved in just a few hours by a large enough quantum computer. So, once practical quantum computers are a reality, it will be possible to crack cryptographic algorithms based on integer factorization, such as RSA, which are fundamental for the operation of internet protocols.

But what do we mean by a large enough quantum computer? How far are we from building it?

Large technology companies have been working for years with the objective of building a large-scale quantum device. As published by the Quantum Insider, the leading players in this field are Google, IBM, Microsoft and AWS (Amazon), although IBM has the longest computing history.

Apart from them, there are other promising companies which are also invested in fabricating quantum hardware and developing software. Some examples are D-Wave, Rigetti Computing, IonQ, PsiQuantum, Quantiuum or Oxford Ionics. It is worth noting that not all of them are working on the same type of quantum computers. Differences among these computers depend on the nature of qubits and how they can be controlled and manipulated. The main types of quantum computers are superconducting, photonic, neutral atoms-based, trapped ions, quantum dots and gate-based quantum computers, the first being the most mature and popular type.

In 2016, IBM put the first quantum computer on the cloud for anyone to run experiments (the IBM Quantum Experience). One year later, they introduced Qiskit, the open-source python-based toolkit for programming these quantum computers (the version 1.0 will be released this year). Then, in subsequent years, the company developed Falcon, a 27-qubit quantum computer (2018) and the 65-qubit Hummingbird (2020). Also, in 2020, IBM released their development roadmap, which had a major update in 2022 and provides a detailed plan to build an error-corrected quantum computer before the end of the decade. According to this roadmap, IBM was planning to build in 2021 the first quantum processor with more than 100 qubits, the 127 qubit Eagle; in 2022, the 433-qubit Osprey; and finally, in 2023, the 1121-qubit Condor processor. All objectives were successfully achieved. Nevertheless, as Jay Gambetta, VP of IBM Quantum, mentioned in his article, we must figure out how to scale up quantum processors since a quantum computer capable of reaching its full potential could require hundreds of thousands, maybe millions of high-quality qubits. For this reason, in the following years and with the ambition of solving the scaling problem, the company is proposing three different approaches for developing ways to link processors together into a modular system capable of scaling without physics limitations.

Scalability refers to the ability to increase the number of qubits in a quantum system, allowing to solve more complex problems.

Another tech giant working on quantum computing is Google, which has the Quantum AI Campus. This company announced in 2018 a 72-qubit quantum processor called Bristlecone and in 2019 presented a 53-qubit quantum computer, Sycamore, and claimed quantum supremacy for the first time, which generated a lot of debate in the community. Lastly, the Quantum AI researchers announced significant advances in quantum error correction by achieving for the first time the experimental milestone of scaling a logical qubit. Quantum error correction is essential for scaling up quantum computers and achieving error rates low enough for useful calculations.

Quantum supremacy describes the ability of a quantum computer for solving a problem that the most powerful conventional computer cannot process in a practical amount of time.

Microsoft decided to focus on quantum computing in the late 1990s and currently is offering Azure Quantum, a cloud quantum computing service which provides an environment to develop quantum algorithms which can be run in simulators of quantum computers. Due to the companys approach of working with partners and academic institutions, Azure Quantum allows us to choose from different quantum hardware solutions created by industry leaders such as Quantinuum, Ionq, Quantum Circuits, Inc., Rigetti or Pasqal.

Microsoft is taking a different approach on the design of quantum computers they are relying on a new type of qubit, a topological qubit. As they explicitly say, Our approach to building a scaled quantum machine is the more challenging path in the near term, but its the most promising one long term. In this regard, in 2022, Microsoft reported an important achievement on the development topological qubit hardware, and later that year they share more data from their experiments.

Although Amazon has not announced that it is developing quantum hardware and/or software, they launched in 2019 Amazon Braket, a quantum computing service which makes it possible to build quantum algorithms, test them in a simulator, run them on different quantum computers and analyze the results. Customers can access hardware from leaders such as Rigetti, Ion-Q and D-Wave Systems, which means that they can experiment with systems based on three different qubit technologies.

In addition, Amazon also launched the Amazon Quantum Solutions Lab which helps companies to be ready for quantum computing by offering them the possibility to work with leading experts in quantum computing, machine learning, optimization, and high-performance computing.

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The State of the Art in Quantum Computing - Medium