Archive for the ‘Quantum Computing’ Category

Take a Diversified Approach to Encryption – DARKReading

Quantum computers may one day break encryption. So might stochastic magnetic tunnel junction machines, also known as spintronics. But we don't need next-generation computing power to break encryption. Its successfully happening right here and now.

Why Does Encryption Fail?There are many factors that contribute to encryption weaknesses and create vulnerabilities ready for exploitation by cybercriminals or state-sponsored actors. Chief among them is poorly implemented cryptography in terms of both the crypto libraries themselves and the way they are used. Bugs such as Heartbleed or the recent implementation error of the Elliptic Curve Digital Signature (ECDS) algorithm in Java versions 15 and above, undermine all programs based on them. The incorrect use of a library, insufficient entropy, or use of weak ciphers is a daily occurrence that impacts specific applications, making bugs even harder to find. Other encryption failings include weak passwords and certificates taken from compromised machines. Combine these techniques with harvest-now-decrypt-later attacks, and encryption technology is no longer what it used to be.

Mathematics, the Cornerstone of Encryption Extremely difficult mathematics underlie our encryption. RSA, the gold standard for public key encryption, is based on the complexity of breaking down a large number into its constituent primes. The forward problem is easy and quick to solve: Take some primes and multiply. But the reverse problem is much harder: Given an integer, which primes were multiplied to make it? Attempts to solve the problem of prime factorization dates back centuries, with Euclid of Alexandria working on specific properties of prime numbers more than 2,000 years ago.

Although no solutions have been found that work on conventional binary computers, that does not mean none exist. After more than 2,000 years of work, most mathematicians agree a prime-factorization algorithm used by a classic computer wont be here anytime soon. Peter Shor proposed an algorithm that could do composite number decomposition in polynomial time on a quantum computer breaking RSA and Diffie-Hellman ciphers but a quantum computer of this kind has not been publicly demonstrated at sufficient scale. Yet.

To prepare for the day when Shors algorithm is in play, the National Institute for Standards and Technology (NIST) has sponsored a post-quantum cryptography (PQC) competition. Now in its sixth year, the competition that began with 82 submissions is expected to announce its four finalists this year.

The remaining candidates are asymmetric-key algorithms (similar in concept to RSA) believed to be capable of withstanding the computational power of a stochastic algorithm that might run on a scalable quantum computer. The mathematical problems upon which these newer algorithms are based are much younger and have not been studied extensively.

In the field of complex mathematics centuries are common time frames. For example, Fermats last theorem took 358 years to be proven. By that logic, its no wonder we have already seen a previously unknown or unforeseen weakness revealed in Rainbow what had been the most peer-reviewed quantum-resistant algorithm now deemed unsuitable for use by NIST. Its only a matter of time, then, before new encryption standards are weakened or outright broken. This is why NIST is encouraging organizations to embrace crypto agility in their post-quantum preparedness planning.

What complicates this matter further is that we don't and won't know which methods are bearing fruit and which techniques are being used, and by whom, to break the encryption we rely on to secure our digital universe. For all we know, large-scale quantum computers are already in use. If you were a nation state or criminal mastermind and had the ability to factor large numbers into their primes, would you tell the world? This is the fundamental problem with modern encryption: We often dont know which, when, or how ciphers are compromised. However, we can say with certainty that encryption is being broken and will be broken.

Look to Wall Street and Diversify To harden IT environments and digital assets in the face of such uncertainty, we can look to Wall Street for strategic advice. To combat the uncertainties and risks associated with loans and stocks go bad, financial institutions embrace diversification. By diversifying investments across multiple asset classes, geographies, and industries, the risks of an entire portfolio imploding are minimized.

This approach can, and should, be applied by enterprise IT and SOC teams when it comes to encryption. Using and mixing/stacking multiple encryption techniques helps to keep data traveling securely even if a flaw is uncovered in one of the encryption layers. We wont always know which part of a crypto stack has been defeated and how, but it wont matter if the cryptography is sufficiently diversified.

As an industry, we need to support the simultaneous use of multiple approaches, anticipating that new crypto methods will come and go. We must mix asymmetric key technology with symmetric key technology, and transmit keys through out-of-band channels. Most importantly, we must develop agreed-on metrics and industrywide benchmarks to measure exactly how diversified our crypto strategy is.

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Take a Diversified Approach to Encryption - DARKReading

Making Quantum Computing a Reality – HBR.org Daily

While quantum computers exist in the lab, general-purpose quantum computers arent yet available for commercial use. How can businesses respond to potential disruptions from this technology before it has actually emerged into the mainstream market? One company that has been investing substantially into quantum computing is Infosys, and so the authors reached out to several researchers and business leaders at the company to learn more about their work. They found that Infosys has taken a hybrid approach, blending elements of classical and quantum computing in order to build a bridge from the reality of today to the disruptive technologies of tomorrow. This has helped the company make headway in leveraging quantum technology in a variety of applications, including optimization problems, machine learning, and cybersecurity. While theres still a long way to go when it comes to developing and applying quantum tech, a hybrid approach is enabling companies to serve customers today, while getting a leg up on the future even if some of the technology involved is still catching up.

Scientists have theorized about the potential of quantum computing that is, a new approach to computation that uses probabilities, rather than binary signals, to make calculations for decades. But in recent years, both private and public sector investment into developing quantum computers has grown significantly, with one report projecting investments of more than $800 million in 2021 alone.

Quantum technology could revolutionize everything from genomic sequencing to transport route optimization, from code-breaking to new materials development. But while quantum computers exist in the lab, general-purpose quantum computers arent yet available for commercial use. How can businesses respond to potential disruptions from this technology before it has actually emerged into the mainstream market?

To explore this question, its helpful to look to historical examples of major technological transitions, such as the shift from analog to digital photography, or from internal combustion to electric engines. In many of these cases, companies leveraged a hybrid approach to integrate new technologies: Rather than attempting to switch over to the new technology all at once, they developed products that combined elements of old and new technologies. For example, the hybrid-electric Prius enabled Toyota to learn about making electric cars while still leveraging its foundation of expertise with traditional gas engines. After launching this initial hybrid model, Toyota moved forward with plug-in hybrid cars and fuel cell electric cars, paving the way for its eventual launch of all-electric cars several years later.

So, what might a similar hybrid approach look like for quantum computing? One organization thats been investing substantially into quantum computing is Infosys, and so we reached out to several researchers and business leaders at the company to learn more about their work. Through a series of in-depth interviews, we found that Infosys has been experimenting with two hybrid approaches to begin commercializing existing innovations and build a bridge to the future of quantum computing:

Infosys has been leveraging these approaches in many different fields, both independently and in partnership with startups. Below, we describe three key applications of quantum computing in which Infosys has begun investing: optimization problems, in which the company has been exploring the potential of quantum-inspired algorithms, and machine learning and cybersecurity solutions, in which Infosys has begun leveraging hybrid models.

While classical algorithms are effective in many domains, they can be prohibitively slow and expensive when it comes to solving certain kinds of optimization problems. For example, in finance, it is difficult to use traditional computers to optimize portfolios, since this necessitates rapid, real-time analysis of the constantly fluctuating risk values associated with investing in each individual stock. To address this challenge, Infosys developed quantum-inspired algorithms to optimize the selection and allocation of assets. This enabled the company to build a diversified portfolio that maximized returns and minimized risks for more than 100 stocks in just one minute, ultimately achieving a 21% improvement in returns compared to conventional (i.e., non-quantum-inspired) asset allocation strategies.

Another area in which traditional computers can struggle to optimize accurately and cost-effectively is in supply chain. To explore the potential for quantum computing in this space, Infosys partnered with QpiAI, a startup developing quantum-inspired solutions for supply chain optimization. While these projects are still in development, the team has already shown that its algorithms enable a 60% cost reduction in vehicle routing optimization.

Machine learning algorithms depend on highly intensive (and expensive) computation power to extract learnings from large datasets. Especially when it comes to analyzing datasets that are highly imbalanced that is, where the cases you care about identifying are extremely rare quantum computing could both dramatically reduce costs and improve these models effectiveness.

In financial fraud detection, for example, the number of fraudulent transactions is tiny compared to the number of normal transactions. This makes it hard to develop classical machine learning algorithms that can identify fraud sufficiently quickly and accurately. But Infosys took a hybrid approach, building out a hybrid neural network algorithm in which most network layers used classical computing, while some layers incorporated input from a quantum computer. With this system, Infosys was able to achieve a 1.66% improvement in the accuracy of its fraud detection tool a difference that may seem small, but has the potential to translate to significant savings given the massive scale of the global financial system.

Current cybersecurity protocols typically use pseudo-random numbers to encrypt sensitive information such as passwords, personal data, or even blockchains. The problem is, quantum computers can easily crack the methods traditional computers use to generate random numbers, potentially posing a huge threat to any organization using these standard encryption tools. Yet, alongside this new threat, quantum technology also holds new possibilities: Quantum systems can produce a large, reliable stream of true random numbers that cannot be decrypted with either classical or quantum systems.

Infosys partnered with quantum cybersecurity firm Quintessence Labs to develop a hybrid solution that first generates true random keys with a quantum random number generator, and then funnels those keys into classical cryptographic algorithms and encryption systems. This approach makes it possible to generate truly random, unpredictable numbers for use in a wide variety of existing commercial applications, enabling a new level of cybersecurity for any organization that works with large quantities of sensitive data.

. . .

These applications might sound like science fiction, but they are very real. While quantum computers still have a long way to go before theyre ready for prime time, businesses are already leveraging quantum technologies in hybrid solutions, blending the old with the new to build a bridge between the reality of today and the potential of tomorrow. Investing in this hybrid strategy now is the best way for companies to develop the expertise in quantum principles and software development that will become critical as these technologies reach maturity. It also means that regardless of how exactly quantum hardware develops and which platforms ultimately emerge as industry standards, the algorithms being developed today will be able to operate on almost any type of quantum hardware (rather than being limited to just one system). Ultimately, taking a hybrid approach enables companies to serve customers today, while getting a leg up on the future even if some of the technology involved is still catching up.

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10 Universities Unleashing the Best Quantum Computing Research – Analytics Insight

Advancements in quantum computing have made it a popular career choice in 2022

Quantum computing has been on the slug for quite a long period of time. But recently, the technology has been buzzing with advanced innovations that are changing the modern tech industry. Quantum computing has become a game-changer in fields like cryptography, chemistry, material science, agriculture, and pharmaceuticals. As technology advances, the problems of global crises become even more complex. During the Covid pandemic, quantum research unraveled several creative tools and innovations that enhanced the confidence of researchers in quantum computing. Emerging as one of the trendiest technologies in the industry, there are several universities and colleges that are encouraging quantum research initiatives and programs for their students. These quantum computing universities possess the best faculty, laboratories, and tools that can help the students to develop their own creations. In this article, we have listed such top quantum computing universities that provide world-class infrastructure for tech aspirants to excel in the quantum computing domain through quantum research and other initiatives.

The University of Waterloo is offering quantum computing courses and advanced research programs for quantum students. It has published over 1500 research papers since its inception. This institute has the potential to combine academic excellence with entrepreneurial innovation to bring out the best of what technology and intellect have to offer.

The university was the first to work on the pure state NMR quantum computing which was demonstrated at Oxford and the University of York. The universitys quantum research department is among the top. It arranges research initiatives that aim to utilize the vast potential of quantum tech. The faculty aims to produce pioneers in the technology who will be responsible to innovate for the benefit of society.

Harvard claims that the Harvard Quantum Initiative in Science and Engineering involves a community of researchers with an intense interest in advancing the science and engineering of quantum systems and applications. The group of quantum researchers at Harvard is trying to build the second quantum revolution and accelerate advances in this domain.

MIT is known to be a research giant. Its branches extend to artificial intelligence and quantum computing. The universitys strength in theoretical physics is now leveraged into quantum information and computing. MIT researchers wish to explore quantum algorithms and complexity, quantum information theory, measurement, control, and connections.

The Berkeley Center for Quantum Computation and Information includes analysts from the domains of engineering, chemistry, and physical sciences. These researchers and analysts work on central issues in quantum gadgets, cryptography, quantum data hypothesis, calculations, and others for the introduction of advanced quantum PCs.

The Joint Quantum Institute includes quantum researchers from the Department of National Institute of Standards and Technology and the Department of Physics of the University of Maryland. Each of these institutes contributes to major hypothetical and exploratory examination programs with a focus on control and sending the quantum framework.

The University of Sydney focuses on the challenging problems of quantum computing and applying these insights to construct new technologies. The scientific research initiatives undertaken by this university mainly focus on deep industrial and entrepreneurial activities.

The Chicago Quantum Exchange showcases a distinct fascination for modern endeavors and propelling scholastics in the designing and study of quantum data and computing. Their goal is to advance the id and investigation of quantum data and computing advances and furthermore the improvement of new applications.

The Universitys division of quantum physics and information specializes in the domain of quantum optics. The division lists the primary foundation for foundations, which are filter-based quantum communication, quantum memory and quantum repeater, and other distinct paradigms.

Researchers at the University of Innsbrucks Quantum Information and Computation department study models for quantum information processing and fundamental aspects of quantum information theory. The focus of their research is the theory of measurement-based quantum computation, which will result in a new and more thorough understanding of multi-body entanglement as a resource.

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Quantum computing ecosystem expands in all directions – TechRepublic

Maybells Icebox Dilution Refrigerator condenses a room-sized cryogenic setup into a system slightly larger than your kitchen fridge to cool quantum devices to the necessary temperatures. Image: Maybell Quantum

Its hard to keep up with all the news coming out of the quantum computing industry these days. The quantum ecosystem is growing in all directions from academic to corporate boardrooms and producing new hardware, software and partnerships.

Denis Mandich, CTO of quantum entropy startup Qrypt, said that the race to make qubits at scale is a winner-take-all competition.

If you make that scalable quantum computer, your advantage is so great that youll leave everyone else in the dust, he said. Thats why so much money is pouring into this sector and why companies are hiring at an unbelievable pace.

Qrypt is a member of the Quantum Consortium that tracks open positions among member organizations including corporations, academic institutions, national labs and government agencies. There are more than 600 listings in the QED-C directory as of early April.

Its a knife fight to get people at this point, he said.

Mandich said every country has outspent the U.S. when it comes to quantum investments because leaders recognize that this is a national race as well.

Whoever is there first has immediate business interest because people will pay for this tomorrow if it scales, he said.

This roundup of quantum news ranging from advancements in hardware, benchmarking work or strategic investments shows why there are so many jobs and why its a challenge to fill them.

The Good Chemistry Company got a vote of confidence via a strategic investment from Accenture Ventures, the consulting companys corporate venture capital arm. The companys QEMIST Cloud is an integrated platform designed for developers. Computational chemistry developers can use the platform to build chemical simulation applications and workflows with emerging algorithms in quantum chemistry, machine learning and quantum computing.

Carl Dukatz, Accentures global quantum computing lead, said in a press release that a new class of scalable cloud-based technology is emerging to support the next generation of chemistry, material science and structural design. Accenture Ventures did not disclose the terms of the investment.

Siemens Digital Industries Software is funding a research project with Pasqal to advance quantum computational multi-physics simulation. The company will use its proprietary quantum methods to solve complex nonlinear differential equations and enhance Siemens product design and testing software. Pasqal specializes in neutral atom-based quantum computing.

Georges-Olivier Reymond, CEO and founder of Pasqal, said the work will focus on creating more accurate digital twins for automotive, electronics, energy and aerospace customers. Pasqals quantum technology controls atoms with an equal number of electrons and protons with optical tweezers and laser light to engineer full-stack processors with high scalability and long coherence times, according to the company. The companys software agnostic processing units operate at room temperature with lower energy.

In March, the French company announced a partnership with Microsoft to offer access to its technology via Azure Quantum. Dr. Krysta Svore, a distinguished engineer and VP of quantum software at Microsoft, said Pasqals services will provide Azure Quantum users with new computational possibilities. The Pasqal system will be available later this year.

Zapata and IonQ announced at the end of March a Defense Advanced Research Projects Agency multi-million dollar award for quantum benchmarking. The funds will support the creation of software tools to make hardware-specific resource estimates for quantum computers. The collaboration includes teams from:

Yudong Cao, CTO and founder of Zapata Computing, said the program will focus on hardware-specific resource estimation.

The key priority is building and integrating software tools across a broad range of the quantum stack from abstract program description, compiler toolchains, error correction and mitigation, to low-level physical control of quantum hardware systems, Cao said. For Zapata specifically, this program will also be an opportunity to test and develop our Orquestra platform for large-scale numerical experiments needed for creating the quantum benchmarks.

The research team started work in March and expects the project to last three years.

At the GTC conference in March, NVIDIA shared an update on its quantum work. The companys cuQuantum is now in general release, while its cuQuantum DGX Appliance is in beta. CEO Jensen Huang announced a new quantum compiler: nvq++, which targets the Quantum Intermediate Representation, a specification of a low-level machine language that quantum and classical computers can use to communicate. Researchers at Oak Ridge National Laboratory will be among the first to use this software.

These projects position NVIDIA strategically at classical and quantum inflection points, where classical advantage gives way to quantum value, according to Gartner Analyst Chirag Dekate.

Maybell Quantum exited stealth mode in March with the Icebox, a new design for quantum hardware. The founders have shrunk the cooling system required to run the specialized hardware down the size of a kitchen refrigerator. The Colorado company has more than a dozen patent-pending innovations, including Flexlines. These quantum wires offer industry-leading performance and density, while transmitting a fraction of the heat and vibration of traditional cabling, according to the company. There are 4,500 of these wires in a single Icebox, which represents three items more qubits in one-tenth of the space, said Maybells CTO Dr. Kyle Thompson.

Quantum Brilliance is planning a joint research and development hub with La Trobe University and RMIT University to develop high-performance, scalable diamond-based quantum microprocessors. The Research Hub for Diamond Quantum Materials will develop fabrication techniques.

Dr. Marcus Doherty is the co-founder and chief scientific officer of Quantum Brilliance, the head of the Diamond Quantum Science and Technology Laboratory at the Australian National University and the leader of the Australian Armys quantum technology roadmap.

Professor Chris Pakes, acting deputy vice chancellor for research and industry engagement at La Trobe University, said the partnership will use both universities expertise in diamond growth, surface imaging and engineering, and combine it with Quantum Brilliances industry experience and manufacturing capabilities. Quantum Brilliance uses impurities within synthetic diamonds, and a carbon atom is swapped out for a nitrogen atom in the lattice of the crystal, to generate qubits.

Q-CTRL is also supporting expanded quantum research through a partnership with The Paul Scherrer Institute. Dr. Cornelius Hempel, group lead for ion trap quantum computing at the university, said that efficient and automated tuneup and calibration procedures will be an essential aspect of day-to-day operations as quantum computers get larger and larger.

Q-CTRLs hardware agnostic, yet hardware-aware tools will be very valuable in finding optimal control solutions that ensure uniform performance across larger qubit arrays, he said.

Both teams have experience in quantum computing based on trapped ions, including specialized approaches in error correction. The Institute has an existing research partnership with ETH Zurich via a quantum computing hub that opened in May 2021.

SaaS startup Agnostiq has submitted a new research paper that recommends a more practical approach to measuring the progress of quantum computing: use benchmarks that match the application in question. Agnostiq conducted its research with a portfolio optimization task to determine whether quantum computers have actually improved over time for specific use cases.The findings include:

One of the most significant findings was that high-quality portfolios were produced using quantum circuits requiring larger numbers of gates than previously demonstrated. This shows the quality of hardware for performing combinatorial optimization has improved because increasing the number of gates produces more noise, according to the researchers. Other findings include:

The peak solution quality was observed at higher depth (p=4) on 3 qubits on an IonQ trapped ion machine.An IBM machine with the lowest qubit quality (quantum volume = 8) performed best of all the IBM machines tested.Variability should be considered with all benchmarking numbers because quantum computers presently give variable results (as high as 29%) depending on the time the machines were accessed.

Agnostiqs Head of R&D Santosh Kumar Radha said the research was motivated by the fact that every quantum hardware paradigm has its own set of performance metrics and each team is improving across different dimensions.

We recognized a need to better understand how these non-trivial improvements translate to real-world applications. Radha said.

Agnostiq develops software tools that make quantum and high performance computing resources more accessible to enterprises and developers. Its open source workflow orchestration platform Covalent is designed to manage and execute tasks on heterogeneous compute resources.

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