Category Archives: Quantum Computing

Dell Technologies have presented what they think about the year 2021 in terms of technologies and the companys view and strategy towards said elements.

For the main discussions, they have shared their insights, analytics, and predictions for the top 4 emerging technologies of 2021, namely quantum computing, silicon chips, 5G, multi-cloud edge solutions.

For starters, the company recognizes the existence and ability of quantum computing but it is not yet practical at least for a couple of years and it should be positioned as an augmentation of conventional computing such as an addition of a new tier towards the highest point of a pyramid hierarchy. They are also impressed by the fact that the cryptography sector has finally met its real challenger in terms of pure brute force speed and have started investing R&D resources to refine modern-day security solutions to match them. Recommendation wise, they are encouraging the development of a simulator and language tailored specifically for quantum computing to train and produce sufficient experts in the future.

Onto semiconductors, they have seen global leaders such as Apple, Intel, and AMD all made their own moves of incorporating their own heterogeneous architectures such as big.LITTLE in their processors one way or another and with NVIDIA purchasing ARM and AMD getting its hands on Xylinx, Dell Technologies are pretty sure future servers are going to follow suit and similar architectures as well, focusing on software modernization, integration platform in conjunction with the silicon chip itself.

The enterprise use of 5G also stemmed the organizations interest as they have predicted that the new standards will really take off during this year as true SA-5G specifications such as mMTC, UR-LLC and MEC provide the groundwork for telecommunications parties to learn, adapt and deploy them in both public and private use cases. Software solutions providers such as Dell Technologies themselves, Microsoft, and more will chime in to continuously refine 5G to be open yet standardized.

Finally, multi-cloud assimilation will solve the issue of edge proliferation which is the excessive independent edge system that currently existed in the ecosystem by clearly classifying resource pools and workload extensions into 2 unique individual categories. In a simpler sense, more workloads and resources targeting public clouds and SaaS edges will involve more logical partitioning compared to the past.

Amit Midha, President of the APAC and Japan region, also added that the entire world is slowly shifting its focus to Asia in terms of business and the technology it carries along and forward into the future. Discussing the companys progress for the social impact aimed for the year 2030 with 9 years to go, they are in the driver seat to achieve a 1:1 ratio of using recycled materials for manufacturing and gender representation for its employees alongside affecting more than 1 billion of lives for a greater good.

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Find out what Dell Technologies has to say about quantum computing, 5G and more for this year - Nasi Lemak Tech

Abu Dhabi Universitys (ADU) Associate Professor of Electrical Engineering in the College of Engineering (CoE), Dr. Montasir Qasymeh, has received a U.S. patent registered under 10,824,048 B2 to develop a first-of-its-kind device that will be capable of connecting superconducting quantum computers over significant distances.

Superconducting quantum computers are the extraordinary computers of the future that will surpass all current ones - and achieve ultrasensitive sensing and unattackable quantum communication networks. Unlike todays conventional computers, quantum computers can process huge amounts of data and perform computations in powerful new ways that were never possible before. Potential applications of quantum computing include accelerating innovations in artificial intelligence and machine learning and tackling future cybersecurity challenges.

Dr. Qasymehs device is composed of graphene; a substance that has been hailed as a miracle material due to its electrical properties and the fact that it is the worlds thinnest and second strongest material. Graphene has already innovated the technology sector and is being applied today to laptops, smartphones and headphones. Dr. Qasymeh has been working with graphene for the past seven years and has numerous publications that have studied this substance. The device converts a quantum microwave signal containing data to a laser beam using properly design graphene layers that are electrically connected and subjected to a laser pump.

Dr. Montasir Qasymeh said: I am humbled and honored to be granted this U.S. patent. This invention will advance the field of quantum computing in the UAE taking us one step further towards the quantum age.

He also added: The coming era is an era of knowledge wealth, that brings with it the opportunity to advance all of humankind. I would like to express my sincerest gratitude to Abu Dhabi University for supporting this project and providing my team with access to its purpose-built academic facilities. I am proud and grateful for Abu Dhabi Universitys continued investment in research.

Dr. Hamdi Sheibani, Dean of the College of Engineering at ADU commented: We are extremely proud of yet another accomplishment from Dr. Montasir Qasymeh. This U.S. patent for one of our professors is evidence of ADUs culture of innovation and our continued commitment to the UAE Governments National Agenda to diversify our economy and strengthen our research and innovation sector. The College of Engineering at Abu Dhabi University is committed to supporting educators who serve as role models and mentors to their students and peers by leading with example through their teachings and projects.

The project was developed with the funding of two important grants: the ADEK Award for Research Excellence grant, which was awarded for the research proposal Graphene-Based Modulator for Passive Transmission and White Light Communications from the Ministry of Education; and the Takamul grant from the Department of Economic Development, which was awarded for patent filling.

Dr. Qasymeh received a Ph.D. degree in electrical engineering from Dalhousie University in Halifax, Canada in 2010. From 2010 to 2011, he was Mitacs Elevate Postdoctoral Fellow at the Microwave Photonics Research Laboratory, University of Ottawa, Canada. He joined Abu Dhabi University in 2011, where he continues to teach. With over 10 years of experience in the education and research industry, he has published more than 40 articles in reputed refereed journals and international conferences and has led on 4 U.S. patents (1 Issued and 3 pending). He has attracted a significant amount of research funding (approximately AED 1.8 million) including 2 ADEK awards for research excellence.

During his tenure with Abu Dhabi University, Dr. Qasymeh has taught more than 17 different undergraduate and graduate courses. He is an active member of several national and international scientific committees and is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), the worlds largest technical professional organization dedicated to advancing technology. He is currently working on topics that include novel terahertz waveguides, room temperature quantum devices and ultrafast modulators.

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ADU Professor Receives Us Patent for a First-of-Its-Kind Hybrid Device Set To Advance the Field of Quantum Computing - Al-Bawaba

Fort Collins, Colorado Report on Quantum Computing Market effectively provides key characteristics of the global investment market, population analysis, companies planning mergers and acquisitions, and concerned or new vendors in the review of research institutes reputable global markets. The Quantum Computing Report by QY Research describes the comprehensive market study covering overview, production, manufacturers, dimensions, revenue, price, consumption, growth rate, sales, import, sourcing, export, future plans and technological advancement for the detailed study of the Quantum Computing Market. Although it allows inexpensive reports readily available, tailor-made research by a team of experts. This report primarily focuses on the consumer and retail sectors.

Global Quantum Computing Market was valued at 193.68 million in 2019 and is projected to reach USD1379.67 million by 2027, growing at a CAGR of 30.02% from 2020 to 2027.

The Quantum Computing Market report comprises various chapters listing the participants which are playing a significant role in the global Quantum Computing Market growth. This section of the report displays the statistics of major players in the international market, including company profile, product specification, market share, and production value. The main type of segmentation mentioned in this report is a commercial and residential category. Based on the extensive historical data a well thought out study on the estimated period for the good expansion of Quantum Computing market globally is produced.

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Market Segments and Sub-segments Covered in the Report are as per below:

Quantum Computing Market, By Offering

Consulting solutions Systems

Quantum Computing Market, By Application

Machine Learning Optimization Material Simulation

Quantum Computing Market, By End-User

Automotive Healthcare Space and Defense Banking and Finance Others

It also provides accurate calculations and sales reports of the segments in terms of volume and value. The report introduces the industrial chain analysis, downstream buyers, and raw material sources along with the accurate insights of market dynamics. The report also studies the individual sales, revenue, and market share of every prominent vendor of the Quantum Computing Market. It majorly focuses on manufacturing analysis including the raw materials, cost structure, process, operations, and manufacturing cost strategies. The report delivers detailed data of big companies with information about their revenue margins, sales data, upcoming innovations and development, business models, strategies, investments, and business estimations.

The Quantum Computing Market reports deliver information about the industry competition between vendors through regional segmentation of markets in terms of revenue generation potential, business opportunities, demand & supply comparison taking place in the future. Understanding the Global perspective, the Quantum Computing Market report introduces an aerial view by analyzing historical data and future growth rate.

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Quantum Computing Market: By Region

North America Europe The Asia Pacific Latin America The Middle East and Africa

The objectives of the Quantum Computing Global Market Study are:

Split the breakdown data by region, type, manufacturer, and application. Identify trends, drivers, and key influencing factors around the world and in the regions Analysis and study of global Quantum Computing status and future forecast, including production, sales, consumption, history, and forecast. Analysis of the potential and advantage, opportunities and challenges, limitations, and risks of the global market and key regions. Analyze competitive developments such as expansions, agreements, product launches, and acquisitions in the market. Introducing the major Quantum Computing manufacturers, production, sales, market share, and recent developments.

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Quantum Computing Market Size 2021 By Analysis, Manufacturers, Regions, Type and Application, and Forecasts to 2027 - Jumbo News

As fledgling technology goes, quantum computing sounds as science fiction as it gets. Most people have likely not even heard about it, let alone think it can be used for anything immediately useful.

But if IBM fulfills a very bold promise it made in September, crop producers will see the fruits of this technology in a very tangible way within the next five years.

By using quantum computing and artificial intelligence (AI) to speed up the process, IBM researchers are confident they can revolutionize the production of nitrogen fertilizer.

Basically, for every ton of fertilizer produced, we consume one ton of fossil fuel, Teo Laino, manager of IBM Research Zurich, said in an email interview.

We are working to identify and develop materials that will make the conversion of nitrogen into fertilizers happen in a more environmental and sustainable way.

If successful, this could mean lower nutrient costs for producers and given growing concerns about greenhouse gases produce a major PR win for the ag industry, as well.

IBMs goal is to improve the Haber-Bosch process (which turns nitrogen gas into nitrates) in a very fundamental way. This process, created by two German chemists more than a century ago, is both one of the greatest advances in agriculture and one of its biggest challenges.

Fertilizers have helped to sustain two times more people on Earth (than otherwise), said Laino.

(But) this process is consuming nearly two to three per cent of the global energy production on a yearly basis.

The impact of the current process has brought the population to the verge of a sustainability crisis.

This is what prompted the global technology giant to pledge that it would use its quantum computing and AI capability to fundamentally improve the Haber-Bosch process.

We will need to discover new processes that have a greater respect for the environment and the planet, he said. This will also have benefits for the primary producers less impact to the environment means less disaster events related to climate.

This effort to find a much less energy-intensive way to make fertilizer in five years is tremendously exciting, said University of Manitoba soil scientist Mario Tenuta, one of the countrys leading experts on fertilizer use and the senior Canada research chair in 4R nutrient management.

(IBM is) not thinking about making a widget its thinking about making something thats going to change the structure of our industrial processes and get us closer to where we need to go in terms of living and sustaining our presence here, he said.

IBMs specific goal is to find a new catalyst for the Haber-Bosch process a seemingly small thing but one with huge implications. (A catalyst is a substance that makes a chemical reaction proceed much more quickly without being consumed in the reaction.)

Making nitrogen fertilizer requires, not surprisingly, nitrogen. Theres plenty out there (it makes up 78 per cent of the air we breathe), but plants can only use it in its fixed form. In nature, that means it must be harvested from the atmosphere by micro-organisms to form ammonia, nitrites and nitrates which help plants grow.

IBMs bid to greatly reduce the amount of energy needed to make fertilizer would have a huge advance for agriculture, says Mario Tenuta, a University of Manitoba soil scientist and one of the countrys top experts on fertilizer use.photo: Supplied

Legumes can do this, but to do it on an industrial scale with the Haber-Bosch process requires very high temperatures, and hence lots of energy. For decades, researchers have tried to engineer a better catalyst that would reduce the energy needed to produce ammonia through the Haber-Bosch process, but identifying one has been problematic. There are virtually endless combinations of materials to sort through and processing all of them has proven itself beyond the capacity of both humans and traditional computers.

Thats where quantum computing comes in.

Quantum computers are exponentially faster than even the largest mainframe computers. The simplest explanation is instead of encoding information in bits that exist in a binary state of either 1 or 0, they use qubits that exist in states of both 1 and 0 simultaneously. Youd probably need a PhD in quantum physics to understand much more, but it is this state of superposition that makes quantum computing so fast.

IBM researchers plan to extract the materials quantum computers identify as possible catalysts and then with the help of AI construct, test and validate predictive models that could make a more energy-efficient fertilizer production process possible.

We use an entire ecosystem of technologies, from AI to tackle sustainable goal challenges to quantum computing, which isan important part of accelerating the scientific discovery process, said Laino. We currently use quantum computing to address several important chemical challenges in these processes.

Meanwhile, we study how to solve more holistic problems while making progress on a road map that is bringing us closer to running bigger solutions on larger quantum computing hardware.

If all is successful, the next step would be to scale the process.

The company foresees the use of fuel cells that would work like a reverse battery. Basically, instead of storing energy, fuel cells would use energy from renewable sources to combine nitrogen from the atmosphere and hydrogen from water to produce ammonia. The catalytic molecules identified by the technology would be used to lower the amount of energy needed to sustain the nitrogen fixation process.

While this would be a good thing overall, what would it actually mean for crop farmers trying to keep their input costs down?

Basic economics dictate that a less energy-intensive process for making fertilizer should mean savings for fertilizer companies (less energy equals less cost), with those savings theoretically passed on to the producer.

However, there are still some unknown factors at play, particularly when it comes to the kind of energy that will fuel fertilizer production, said Tenuta.

With IBMs focus on using renewables such as solar and hydro as fuel for the production process, how much farmers would wind up paying for the end product is anyones guess, he said.

I am personally expecting that by 2050 our reliance on fossil fuels as an energy source is going to be in the minoritycompared to renewables, he said. You just dont know what the cost of those renewables is going to be down the road.

That said, Tenuta believes the fact that IBM is looking for this catalyst using in-reach technology is itself remarkable.

And who knows where that might lead, he said, adding it might even allow fertilizer to be made on farms.

Maybe a really good catalyst will ensure there is no difference between a factory and a farmers yard, said Tenuta. You would still think that (production) would be more efficient in a big factory than making it at a small scale, but who knows?

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A fertilizer revolution is on the horizon - Alberta Express

Quantum computing is emerging as a subfield of quantum information science. This technology has already started attracting interest from researchers and technology companies with almost feverish excitement and activity. Companies have even begun racing to achieve quantum supremacy. In 2019, Google officially announced that it achieved quantum supremacy. Quantum computing promises great potential in diverse areas, including medical research, financial modeling, traffic optimization, artificial intelligence, weather forecasting, and more.

Quantum computing can be a ground-breaking technology for cybersecurity, enabling companies to improve their cybersecurity strategies. It will help detect and deflect quantum computing-based attacks before they cause harm to groups and individuals.

Quantum cybersecurity is the field of study of all aspects affecting the security and privacy of communications and computations owing to the development of quantum technologies. Quantum computers are likely to solve problems that cannot be done by traditional computers, such as solving the algorithms behind encryption keys that safeguard data and the internets infrastructure. Moreover, as most of todays encryption relies heavily on mathematical formulas that would take impractically much time to decode using todays computers, a quantum computer can easily factor those formulas and break the code.

Over 20 years ago, Peter Shor, an MIT professor of applied mathematics, developed a quantum algorithm that could easily factor large numbers far more quickly than a conventional computer. Since then, scientists have been working on developing quantum computers that can break asymmetric encryption.

The development of large quantum computers could have calamitous consequences for cybersecurity. In this context, thinking quantum cybersecurity solutions will be an advantageous edge. Quantum cybersecurity can pave more robust and compelling opportunities for the security of critical and personal data. It will particularly be useful in quantum machine learning and quantum random number generation, as noted byIBM.

The pace of quantum research undoubtedly continues to accelerate in the years ahead. But it will also pose challenges and vulnerabilities to mission-critical information needed to retain its secrecy. Adapting to advanced cryptography to address these threats could be an obvious solution. The quantum cryptography approach is based on creating algorithms that are hard to break even for quantum computers. This approach can also work with conventional computers.

Another security approach against quantum computing attacks is lattice-based cryptography. Conventional cryptographic algorithms can be replaced with lattice-based algorithms that are designed with proven security. These new algorithms can conceal data inside complex math problems called lattices. Google already has begun testing post-quantum cryptography methods that integrate lattice-based algorithms. According to IBM researcher Cecilia Boschini, lattice-based cryptography will prevent future quantum computing-based attacks and form a basis for Fully Homomorphic Encryption (FHE) that makes it possible for users to perform calculations on a file without seeing the data or revealing it to hackers. The NSA, NIST, and other governmental agencies are also starting to invest in this developing method.

Moreover, according to aForbes article, quantum computing can transform cybersecurity in four areas: quantum random number generation is fundamental to cryptography; quantum-secure communications, specifically quantum key distribution (QKD); post-quantum cryptography, and quantum machine learning.

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The Promise and Impact of Quantum Computing on Cybersecurity - Analytics Insight

Scientists at the Freie Universitt Berlin have come up with an AI-based solution for calculating the ground state of the Schrdinger equation in quantum chemistry.

The Schrdingers equation is primarily used to predict the chemical and physical properties of a molecule based on the arrangement of its atoms. The equation helps determine where the electrons and nuclei of a molecule are and under a given set of conditions what their energies are.

The equation has the same central importance as Newtons law motion, which can predict an objects position at a particular moment, but in quantum mechanics that is in atoms or subatomic particles.

The article describes how the neural network developed by the scientists at the Freie Universitt Berlin brings more accuracy in solving the Schrdingers equation and what does this mean for the future.

In principle, the Schrdingers equation can be solved to predict the exact location of atoms or subatomic particles in a molecule, but in practice, this is extremely difficult since it involves a lot of approximation.

Central to the equation is a mathematical object, a wave function that specifies electrons behaviour in a molecule. But the high dimensionality of the wave function makes it extremely difficult to find out how electrons affect each other. Thus the most you get from the mathematical representations is a probabilistic account of it and not exact answers.

This limits the accuracy with which we can find properties of a molecule like the configuration, conformation, size, and shape, which can help define the wave function. The process becomes so complex that it becomes impossible to implement the equation beyond a few atoms.

Replacing the mathematical building blocks, the scientists at Freie Universitt Berlin came up with a deep neural network that is capable of learning the complex patterns of how electrons are located around the nuclei.

The scientists developed a Deep Neural Networks (DNN) model, PauliNet, that has several advantages over conventional methods to study quantum systems like the Quantum Monte Carlo or other classical quantum chemistry methods.

The DNN model developed by these scientists is highly flexible and allows for a variational approach that can aid accurate calculation of electronic properties beyond the electronic energies.

Secondly, it also helps the easy calculation of many-body and more-complex correlation with fewer determinants, reducing the need for higher computation power. The model mainly helped solve a major tradeoff issue between accuracy and computational cost, often faced while solving the Schrodinger equation.

The model can also calculate the local energy of heavy nuclei like heavy metals without using pseudo-potentials or approximations.

Lastly, the model developed in the study has anti-symmetry functions and other principles crucial to electronic wave functions integrated into the DNN model, rather than let the model learn. Thus, building fundamental physics in the model has helped it make meaningful and accurate predictions.

In recent years, artificial intelligence has helped solve many scientific problems that otherwise seemed impossible using traditional methods.

AI has become instrumental in anticipating the results of experiments or simulations of quantum systems, especially due to its sciences complex nature. In 2018, reinforcement learning was used to design new quantum experiments in automated laboratories autonomously.

Recent efforts by the University of Warwick and another IBM and DeepMind have also tried to solve the Schrdingers equation. However, PauliNet, with its greater accuracy of solving the equation now, presents us with a potential to use it in many real-life applications.

Understanding molecules composition can help accelerate drug-discovery, which earlier was difficult due to the approximations to understand its properties.

Similarly, it could also help discover several other elements or metamaterials like new catalysts, industrial chemical applications, new pesticides, among others. It can be used in characterising molecules that are synthesised in laboratories.

Several academic and commercial software use Schrdingers equation at the core but are based on applications. The accuracy of this software will improve. Quantum computing in itself is based on quantum phenomena of superposition and is made up of qubits that take advantage of the principle. Quantum computing performance will improve as qubits will be able to be measured faster.

While the current study has come up with a faster, cheaper, and accurate solution, there are many challenges to overcome before it is industry-ready.

However, once it is ready, the world will witness many applications as a result of greater accuracy in solving Schrdingers equation.

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AI Helps Solve Schrdinger's Equation What Does The Future Hold? - Analytics India Magazine