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Initial efforts with San Franciscos Splunk will focus on three key challenges: network security, dynamic logistics and scheduling

Quantum Computing Inc (OTC:QUBT), an advanced technology company developing quantum-ready applications and tools, said Tuesday that it has struck a technology alliance partnership with ().

San Francisco, California-based Splunk creates software for searching, monitoring, and analyzing machine-generated big data via a web-style interface.

Meanwhile, staffed by experts in mathematics, quantum physics, supercomputing, financing and cryptography, Leesburg, Virginia-based Quantum Computing is developing an array of applications to allow companies to exploit the power of quantum computing to their advantage. It is a leader in the development of quantum ready software with deep experience developing applications and tools for early quantum computers.

Splunk brings a leading big-data-analytics platform to the partnership, notably existing capabilities in its Machine/Deep Learning Toolkit in current use by Splunk customers, said the company.

Implementation of quantum computing applications will be significantly accelerated by tools that allow the development and execution of applications independent of any particular quantum computing architecture.

We are excited about this partnership opportunity, said Quantum Computing CEO Robert Liscouski. Splunk is a proven technology leader with over 17,500 customers world-wide, that has the potential to provide great opportunities for QCIs quantum ready software technologies.

Both the companies will partner to do fundamental and applied research and develop analytics that exploit conventional large-data cybersecurity stores and data-analytics workflows, combined with quantum-ready graph and constrained-optimization algorithms.

The company explained that these algorithms will initially be developed using Quantums Mukai software platform, which enables quantum-ready algorithms to execute on classical hardware and also to run without modification on quantum computing hardware when ready.

Once proofs of concept are completed, QCI and Splunk will develop new analytics with these algorithms in the Splunk data-analytics platform, to evaluate quantum analytics readiness on real-world data, noted the company.

The Splunk platform/toolkits help customers address challenging analytical problems via neural nets or custom algorithms, extensible to Deep Learning frameworks through an open source approach that incorporates existing and custom libraries.

The initial efforts of our partnership with Splunk will focus on three key challenges: network security, dynamic logistics and scheduling, said Quantum Computing.

Contact the author Uttara Choudhury at[emailprotected]

Follow her onTwitter:@UttaraProactive

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Quantum Computing strikes technology partnership with Splunk - Proactive Investors USA & Canada

The "Stabilizing Quantum Bits for Computing" report has been added to ResearchAndMarkets.com's offering.

The Report Includes:

Quantum computing entered an era of early commercialization in 2019. Governments subsequently decided to spend billions of dollars to support basic quantum computing research in universities and research institutions. Technology companies such as IBM, Google, Microsoft, D-Wave Systems, Intel, and Zapata developed hardware, software, and solutions that demonstrate the power of quantum computing in solving real-world problems.

Leading players in various industries, such as BASF, Dow, Airbus, and Volkswagen, have stepped into the field of quantum computing, hoping this game-changing technology can help them significantly improve efficiency or quality by simulating or optimizing production, supply chains, and many other areas.

In 2020, government-funded research projects in universities and research institutions will bring approximately $50 million in sales of hardware, software and services to quantum computing companies, which can be segmented into three groups. IBM, Google, Microsoft, and D-Wave Systems are leading companies that provide a full range of solutions from quantum computing hardware to software and services. Alibaba, Honeywell, Rigetti Computing, Xanadu, and several other companies have a similar ambition.

Key Topics Covered:

Chapter 1 Quantum Computing: Emerging Opportunities

Chapter 2 References

List of Tables

Table 1: Global Quantum Computing Market, by End User, Through 2030

Table 2: Quantum Computing Progress, 2019-2020

Table 3: Global Quantum Computing Market for Industrial Users, by Application, Through 2030

Table 4: Global Quantum-Assisted Optimization Market for Industrial Users, by Application, Through 2030

Table 5: Global Quantum Simulation Market for Industrial Users, by Application, Through 2030

List of Figures

Figure 1: Global Quantum Computing Market, by End User, 2020-2030

Figure 2: Global Quantum Computing Market for Industrial Users, by Application, 2025 and 2030

Figure 3: Global Quantum-Assisted Optimization Market for Industrial Users, by Application, 2025 and 2030

Figure 4: Global Quantum Simulation Market for Industrial Users, by Application, 2025 and 2030

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/d9fd79

View source version on businesswire.com: https://www.businesswire.com/news/home/20200327005220/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Outlook on the Global Stabilizing Quantum Bits for Computing Market to 2030 - ResearchAndMarkets.com - Yahoo Finance

This study explores the rapidly-evolving landscape of privacy and cybersecurity triggered by a rise in the number of connected devices. By 2030, a complex mesh of 91 billion devices around the world will exist, with over 10 connected devices per human.

New York, March 30, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "The Future of Privacy and Cybersecurity, Forecast to 2030" - https://www.reportlinker.com/p05878610/?utm_source=GNW

Every connected device in a smart home or city will be a potential access point to our most sensitive and personal data.This constantly-evolving IoT landscape will expand beyond the traditional network in use today and will result in increasingly complex privacy and cybersecurity challenges.

Readers of the study will gain insight into these challenges in terms of understanding various new endpoints of privacy and cybersecurity, new types of threats looming in the industry, and efforts being made to fight them. The current global regulatory landscape around privacy and the increasing relevance of digital trust and enterprises ability to safeguard it are also discussed.

The study also focuses on evolving global threats such as nuclear hacks, dark web evolution and a state of cyber warfare. Investments and commitments to mitigate this and efforts made to close the gap in the cyber workforce are also outlined in the study. The analyst looks at numerous technology topics such as artificial intelligence (AI), data de-identification, advanced authentication and encryption, biometrics, blockchain, automation and quantum computing and its ability to transform privacy and cybersecurity. For each technology, its significance, impact on privacy and cybersecurity, as well as application potential are discussed. Over 20 innovation examples and emerging business models are provided throughout the study to serve as guideposts for readers. The study also discusses key scenarios in the future based on public interest and level of regulation to allow readers to derive an understanding of the intensity and implications of privacy and cyber threats on our daily lives. While the distinct scenarios are influenced by different positions taken by governments and individuals around the world, the future of privacy and cybersecurity will most likely be a combination of these scenarios. Our analysis of five key industries influenced by the changing landscape of privacy and cybersecurity includes automotive, energy, healthcare, smart cities, banking and financial services. When evaluating industries, we look at cybersecurity opportunity, challenges to implementation, key trends in the value chain, and emerging business models. Innovative companies at the forefront of cybersecurity pertaining to each industry are identified in order to provide strategic direction to readers. Governments, enterprises, and individuals can benefit from the strategic recommendations made in the study meant to provide guidance to mitigate future privacy and cybersecurity challenges through innovative partnerships, regulatory changes, workforce upgradation, technology leverage, and new business models. Finally, we identify three big outcomes and predictions for the future emerging from the evolution of privacy and cybersecurity. Author: Vinay VenkatesanRead the full report: https://www.reportlinker.com/p05878610/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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The Future of Privacy and Cybersecurity, Forecast to 2030 - Yahoo Finance

Benzene: Solving a Mystery in 126 Dimensions

One of the fundamental mysteries of chemistry has been solved by a collaboration between Exciton Science,UNSWandCSIRO and the result may have implications for future designs of solar cells, organic light-emitting diodes and other next gen technologies.

Ever since the 1930s debate has raged inside chemistry circles concerning the fundamental electronic structure of benzene. It is a debate that in recent years has taken on added urgency, because benzene which comprises six carbon atoms matched with six hydrogen atoms is the fundamental building-block of many opto-electronic materials, which are revolutionizing renewable energy and telecommunications tech.

The flat hexagonal ring is also a component of DNA, proteins, wood, and petroleum.

The controversy around the structure of the molecule arises because although it has few atomic components the electrons exist in a state comprising not just four dimensions like our everyday big world but 126.

Analyzing a system that complex has until now proved impossible, meaning that the precise behavior of benzene electrons could not be discovered. And that represented a problem, because without that information, the stability of the molecule in tech applications could never be wholly understood.

Now, however, scientists led byTimothy Schmidt from the ARC Centre of Excellence in Exciton Science and UNSW Sydney have succeeded in unraveling the mystery and the results came as a surprise. They have now been published in the journalNature Communications.

Professor Schmidt, with colleagues from UNSW andCSIROs Data61, applied a complex algorithm-based method called dynamic Voronoi Metropolis sampling (DVMS) to benzene molecules in order to map their wavefunctions across all 126 dimensions.

Key to unraveling the complex problem was a new mathematical algorithm developed by co-author Dr. Phil Kilby from CSIROs Data61. The algorithm allows the scientist to partition the dimensional space into equivalent tiles, each corresponding to a permutation of electron positions.

Of particular interest to the scientists was understanding the spin of the electrons. All electrons have spin it is the property that produces magnetism, among other fundamental forces but how they interact with each other is at the base of a wide range of technologies, from light-emitting diodes to quantum computing.

What we found was very surprising, said Professor Schmidt. The electrons with whats known as up-spin double-bonded, where those with down-spin single-bonded, and vice versa.

That isnt how chemists think about benzene. Essentiallyit reduces the energy of the molecule, making it more stable, by getting electrons, which repel each other, out of each others way.

Co-author Phil Kilby from Data61 added: Although developed for this chemistry context, the algorithm we developed, for matching with constraints can also be applied to a wide variety of areas, from staff rostering to kidney exchange programs.

Reference: The electronic structure of benzene from a tiling of the correlated 126-dimensional wavefunction by Yu Liu, Phil Kilby, Terry J. Frankcombe and Timothy W. Schmidt, 5 March 2020, Nature Communications.DOI: 10.1038/s41467-020-15039-9

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After 90 Years, Scientists Solve One of the Fundamental Mysteries of Chemistry - SciTechDaily

Quantum circuits are collections of quantum gates interconnected by quantum wires. They are building blocks of computers that use mechanical effects to perform tasks.

However, no quantum circuit is entirely error-free. Scientists around the globe are keen to optimize the efficiency of quantum circuits.

In a new study, scientists at the Indian Institute of Science (IISc) used mathematical analog and devised an algorithm to address this problem. The algorithm counts the number of computing resources necessary and optimizes them to obtain maximum efficiency.

Aninda Sinha, Associate Professor at the Centre for High Energy Physics, IISc, and corresponding author of the study said,We were able to [theoretically] build the most efficient circuit and bring down the number of resources needed by a huge factor.

Pratik Nandy, Sinhas Ph.D. student and a co-author of the paper, said, Analogously, there are universal quantum gates for making quantum circuits. In reality, the gates are not 100 percent efficient; there is always an error associated with the output of each gate. And that error cannot be removed; it merely keeps on adding for every gate used in the circuit.

The most efficient circuit does not minimize the error in the output; rather, it minimizes the resources required for obtaining that same output. So the question boils down to given net error tolerance, what is the minimum number of gates needed to build a quantum circuit?

In 2006, a study by the University of Queensland had suggested that the counting the number of gates to achieve maximum efficiency is equivalent to finding the path with the shortest distance between two points in some mathematical space with volume V. A separate 2016 study argued that this number should vary directly with V.

Scientists in this study went back to Queenslands original study and found that the total counting number of gates wont result in variation with V, somewhat it varies with V2.

By generalizing the studys assumptions and later introducing a few modifications, scientists found that the minimum number of gates indeed varies directly with the volume.

Surprisingly, the results of the study appear to link the efficiency optimization problem with string theory, a famous idea that tries to combine gravity and quantum physics to explain how the universe works.

According to scientists, this link can prove to be instrumental in helping scientists interpret theories that involve gravity. They also aim to develop methods that describe a collection of quantum circuits to calculate specific experimental quantities that cannot be theoretically simulated using existing methods.

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Maximizing the efficiency of a quantum circuit - Tech Explorist