Category Archives: Quantum Computing

At Quantum Quest, an all-girls quantum computing camp, 20 teenage female students recently stood on the precipice of a brand new technology: quantum coding.

(Scientists) use quantum computers, program manager Gabbie Meis said. (Quantum computers) actually use quantum mechanics to solve some of the worlds largest problems, like things with lots of data or simulations that our classical computers just dont have enough power to do. Instead of our classical computers, quantum computers are actually an entirely different type of machine that is still being developed today.

This kind of computer requires quantum coding and when programmed could be used to help solve problems like mitigating the impacts of climate change; transportation mapping, such as figuring out how to remap the entire country of Australia with more efficient roadways; or even biomedical research, such as protein folding for vaccine development or drug discovery research.

Back in 2019 Google ran a problem on their quantum computer that they estimated would take the most powerful supercomputer about 10,000 years to solve, Meis said. They said they got their (quantum) computers to solve it in less than two days.

During the camp, students learned the programming language, Qiskit, an open source (free) software development kit. Meis called it a Python-backed library, Python being a programming language. Qiskit allows the students classical computers the kind most of use at home to communicate with quantum computers. Ironically, although the students all had their laptops open, the learning was done on dry erase boards.

Quantum is interdisciplinary so theyre learning the basics in linear algebra, Meis said. Theyre learning computer science and how to code in Python, and theyre learning quantum physics, all wrapped in this single week.

The Coding School, located in Southern California, has a quantum coding initiative called Qubit by Qubit, the most basic unit of information in quantum computing. The initiative seeks to make quantum computing education accessible to students in K-12, because as it stands right now, according to Meis, students dont usually see quantum computing until they are graduate students.

To bring quantum coding to the masses, the school developed the Quantum Quest camp and partners with other organizations to offer it locally. For Tucson, they partnered with the University of Arizonas Office of Societal Impact and the Girl Scouts of Southern Arizona (GSSA).

When this all came about it was the perfect marriage between the Coding School, the U of A and the Girl Scouts in trying to bring accessibility to this more advanced part of STEM, said Colleen McDonald, director of staff supported programs for the GSSA. As Girl Scouts we see ourselves as the connector. We want to make sure that all girls have access to it.

The Coding School has been offering this camp for some time this is its 10th camp but its the first time its been offered in Tucson. Camp topics included everything from foundational concepts that make up the quantum world such as entanglement and qubits, and end with teaching girls how to code real quantum computers.

Its all new science. These students are at the very foundation of quantum coding, according to Meis, and that is part of why it is so important to offer this to young women. One, they are introduced to quantum computing, but two, so they are not alone and do not feel alone in their interest in this field, Meis said.

This is a hard science, right? Meis said. We really want our students to feel that theres a place in this for girls. Were really trying to empower them now while theyre still in high school.

Ive worked with girls for two decades doing STEM with them and one of the biggest things I hear is they think that theyre alone in liking STEM, that they dont realize there are other girls who are also willing to push themselves, Michelle Higgins added. Shes the associate director of the Office of Societal Impact.

The lead instructor for this camp is herself an example to these students. Emily Van Milligen is a doctoral student at the UArizona department of physics. Her field of study is quantum entanglement and routing protocols. She noticed that not one student fell behind; they all listened.

They love it, Van Milligen said. They like the lectures Im giving, which is exciting because that means they enjoy the content. Im not doing anything that special.

One student, 18-year-old Sagan Friskey and future Pima Community College student, spoke enthusiastically about the camp.

I think its super interesting to learn about, especially since were at the very beginning of it becoming a part of something that you can learn about and work with, she said.

Gabriela Malo-Molina, 14, and a student at Catalina Foothills High School, said shes never seen this before but could be interested in looking deeper into it.

I think this is a very special opportunity, and that this field will definitely be more commonly used in the future, she said. And quantum computing in the future will be very helpful for discoveries, especially in the medical field.

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Coding the future | Business | insidetucsonbusiness.com - Inside Tucson Business

Multiverse Collaborating with Bosch to Optimize Quality, Efficiency, and Performance in an Automotive Electronic Components Manufacturing Plant

Multiverse and Bosch will be working to create a quantum computing model of the machinery and process flow in at one of Boschs manufacturing plants in a process known as digital twin. This is a technique where a model of the activities in the facility will be created inside the computer and then enable various simulations and optimizations to be performed which can predict how the plant will perform under different scenarios. The companies will be using both customized quantum and quantum inspired algorithms developed by Multiverse in order to model an automotive electronic components plants located in Madrid, Spain. The companies hope to have first results of this pilot implementation by the end of the year with a goal of finding ways to enhance quality control, improve overall efficiencies, minimize waste, and lower energy usage. Bosch has a total of 240 manufacturing plants that include over 120,000 machines and 250,000 devices which are connected together to provide them with digital control and sensing to optimize performance. So a successful implementation of this digital twin concept could be extended to many more factories and provide Bosch with a significant productivity advantage in the future. A news release from Multiverse about this collaboration can be accessed on their website here.

July 30, 2022

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Multiverse Collaborating with Bosch to Optimize Quality, Efficiency, and Performance in an Automotive Electronic Components Manufacturing Plant -...

Scientists have made a quantum computer that breaks free from the binary system.

Computers as we know them today rely on binary information: they operate in ones and zeroes, storing more complex information in bits that are either off or on. That seemingly simple system is at the heart of every computer we use.

Quantum computers have taken on that same system. They use qubits, which replicate the bits of a classical computer but using quantum technology.

But they are built with more than just those ones and zeroes. Quantum computers are not necessarily restricted to binary, and scientists hope that breaking them are from that system can add extra complexity without using more quantum particles.

Now scientists say they have succeeded in building a quantum computer that works in that way. It can do calculations not with qubits but instead with qudits quantum digits that could allow for vastly more computing power.

Most quantum computers have the access to more quantum states than are actually used when they are doing computation. In the new study, scientists used a computer at the University of Innsbruck that stores information in trapped calcium atoms that can exist in eight different states, for instance but of which generally only two are used.

Researchers were able to show that they could make use of that full potential of the computer, and do so in a way that does not make the computer less reliable, as it does with a traditional computer.

Whats more, scientists typically want to use quantum computers to work on problems that are already naturally expressed in audits. Working with more than zeros and ones is very natural, not only for the quantum computer but also for its applications, allowing us to unlock the true potential of quantum systems, said Martin Ringbauer, an experimental physicist and member of the team from Innsbruck.

The work is reported in a new paper, A universal qudit quantum processor with trapped ions, published in Nature Physics today.

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Scientists create quantum computer that breaks free of binary system - The Independent

Fans of Marvel movies know the word 'quantum' too well.

It's the name of the realm the Avengers used to time travel and fantastical as that is, the concept of quantum mechanics is far from fiction.

Scientists have toyed with the idea since the 1920s in an attempt to explain the mysteries of our universe that can not be explained by traditional physics.

The University of Sydney (USYD) and University of New South Wales Sydney (UNSW) are among Google's new partners, which already included Macquarie University (MQ) and the University of Technology (UTS).

Associate Professor Ivan Kassal, from USYD believes advancements in quantum chemistry could develop life saving medicines and help predict the impact of atmospheric matter on our climate.

"Simulating chemistry is likely to be one of the first applications of quantum computers, and my goal is to develop the quantum algorithms that will allow near-term quantum computers to give us insights into chemical processes that are too complicated to simulate on any classical supercomputer," Kassal said.

Those are very physical problems to solve, but the potential of quantum computers could also speed up solving systems, crack cryptography and enable new applications of machine learning.

Australia's Chief Scientist, Dr Cathy Foley said Google's interest in Australia is "testament to the world class research that has been supported by the Australian Research Council for over two decades".

"I am delighted that Google sees Australia as somewhere to do quantum research. A step in building Australia's quantum industry here," said Dr Foley.

Google is building its quantum research team in Sydney, including its newly-appointed quantum computing scientist, Dr Marika Kieferova.

Professor Michael Bremner of UTS said one of this biggest challenges in quantum computing "is understanding which applications quantum computers can deliver performance that goes beyond classical computing."

"In this project, my team at UTS will work with Google on this problem, examining the mathematical structures that drive quantum algorithms to go beyond classical computing," Professor Michael Bremner, UTS

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Quantum computing and the Australians on the cutting edge - 9News

NEW YORK, July 27, 2022 /PRNewswire/ --IQT Research foresees major commercial opportunities arising to protect blockchain against future quantum computer intrusions and agrees with the White House National Security Memorandum NSM-10, released on May 04, 2022, which indicates the urgency of addressing imminent quantum computing threats and the risks they present to the economy and to national security in our latest report "The Quantum Threat to Blockchain: Emerging Business Opportunities."

Although primarily associated with cryptocurrencies, blockchain has been proposed for a wide range of transactions, including in insurance, real estate, voting, supply chain tracking, gaming, etc. These areas are all vulnerable to quantum threats, which lead to operations disruption, trust damage, and loss of intellectual property, financial assets, and regulated data.

More details on this report can be found at https://www.insidequantumtechnology.com/product/the-quantum-threat-to-blockchain-emerging-business-opportunities/.

For a sample of this report, click on Request Excerpt.

About the Report:

Quantum computers threaten classical public-key cryptography blockchain technologies because they can break the computational security assumptions of elliptic curve cryptography. They also weaken the security of hash function algorithms, which protect blockchain's secrets. This new IQT Research report identifies not only the challenges, but also the opportunities in terms of new products and services that arise from the threat that quantum computers pose to the "blockchain" mechanism. According to a recent study by the consulting firm Deloitte, approximately one-fourth of the blockchain-based cybercurrency Bitcoin in circulation in 2022 is vulnerable to quantum attack.

This report covers both technical and policy issues relating to the quantum vulnerability of blockchain.

From the Report:

About IQT Research:

IQT Research is a division of 3DR Holdings, and the first industry analyst firm dedicated tomeeting the strategic information and analysis needs of the emerging quantum technologysector. In addition to publishing reports on critical business opportunities in the quantumtechnology sector, Inside Quantum Technology produces a daily news website on business-related happenings in the quantum technology field. (https://www.insidequantumtechnology.com/)

3DR Holdings also organizes the Inside Quantum Technology conferences. The next conference is dedicated to quantum cybersecurity and will be held October 25-27 in New York City.

For more details on the report, contact:

Lawrence Gasman[emailprotected]Telephone: 434-825-1311

Press contact:Barry Schwartz[emailprotected]212-677-8700 ext. 118

SOURCE IQT Research

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IQT Research Predicts Blockchain and Quantum Threat Will Quickly Spread Beyond Cybercurrencies; Surge in New Product and Services Opportunities to...

The importance of Data Protection and Privacy can be gauged from the rising coverage and popularity of the World Data Privacy Day. 25 years after the signing of Convention 108 in 1981: the first international treaty to deal with privacy and data protection, it was in 2006, when the Committee of Ministers of the Council of Europe decided that Data Protection Day would be observed on January 28 each year. This is internationally known as World Data Privacy Day outside of Europe. The last few years and especially during the pandemic, have highlighted the importance of Data Security, Privacy and Regulatory Compliances, besides leveraging Data, Analytics, Business Intelligence and Data Sciences for business.

What were the tenets of Data Privacy, Policies and Regulations in the Pre-Pandemic world?

The early days of computerisation were typically based on on-premise computing and data centres. CIOs had the responsibility of data policies, storage, privacy along with design of Information Technology Architecture and its constituent servers, personal computers, software, networking and security systems. Parallel to the rising usage of the Internet, the late 1990s also saw the advent of the EU Data Protection Directive (EU GDPRs predecessor), HIPAA Health and Privacy Act for healthcare establishments, the COPPA Childrens Online Privacy Act, the Gramm Leach Bliley Act for Financial Institutions, the Privacy Officers in Federal Governments and the E-Government Act of 2002 in the US. Cyber Security was evolving as well in the early 2000s with Anti-Virus, Data Leakage Prevention, Database Security, Firewall Management, Web Application Security, Intrusion Detection and Prevention solutions safeguarding against external and internal threats.

The 2nd decade of the 2000s saw the rapid adoption of Cloud with its IaaS, PaaS and SaaS systems coupled with mobility, Bring-Your-Own-Device (BYOD) and IoT device revolution thus causing a paradigm shift in the whole IT landscape impacting data privacy, policies, compliances and cyber security. As workloads and systems shifted out of the Trusted Organisational Network, CISOs were managing privacy and security aspects in the world of cloud, mobility and IoT, handling increasingly sophisticated hackers and insider threats, and managing the more stringent privacy and security guidelines especially related to sensitive data. Data encryption, anonymisation, robust Password management have been some of the fundamental tenets of this evolution in cybersecurity.

Parallelly, from the governance perspective, there has been a rising importance of acts such as Federal Information Security Management Act of 2002, the Department of Defense Strategy for Operating in Cyberspace guidelines of 2011, NIST IT standards, the Homeland Security Act and the Cybersecurity National Security Action Plan (CNAP) of the United States, ENISA, the NIS Directive and the EU GDPR. Cloud Security Frameworks encompassed those covering governance (COBIT), architecture (SABSA), management standards (ISO/IEC 27001) and NIST's Cybersecurity Framework. Rising globalisation also led to dealing with different regulations, compliances and policies across geographies with added nuances of managing intra and intercompany data sharing.

The Pre-pandemic period also saw significant penalties and fines for customer and sensitive data breach especially the cases of Uber, Marriott, Equifax, Home Depot, Capital One, Morgan Stanley, Yahoo, Microsoft, British Airways and several others. This research by Deloitte in 2017 estimated compliance costs to be a significant 10% of a typical banks overall operating costs.

What was the impact of the pandemic on Data Privacy, Policies and Regulations?

The COVID-19 induced digital transformation accelerated the already rising growth in data generation speed, volume and variety. Against the global population of under 8 billion in 2021, the corresponding number of mobile devices and IoT Devices is 15 and 22 billion respectively. As per this research by Statista, the total worldwide data amount rose from 9 Zettabytes (1 Zettabyte = 1 trillion gigabytes) in 2013 to over 27 Zettabytes in 2021, and the prediction is this growing to well over 180 Zettabytes in 2025. Web 3.0 and Metaverse along with 5G and Edge Computing will also contribute their share to this growth along with IoT, Mobility and rise in decentralised and distributed cloud computing.

CISOs and CIOs have now embraced a culture of Cyber Resilience basis Zero Trust Architecture. This is due to the rising breadth and volume of attack surfaces emanating from rapid adoption of cloud, mobility, IoT devices, IT penetration in automotive, consumer durables, telecoms, smart cities, utilities, healthcare and other verticals also covering customers and supply chains, along with the proliferation of 5G and Edge Computing. Moreover, the rise of gig and remote/ hybrid working has also added to the mass of attack surfaces and vulnerabilities.

Despite advances in Cybersecurity measures, cyber-attacks have increased by 3 X in some countries covering Work From Home endpoints, Video Conferencing services, malware, ransomware and the Dark Web as mentioned in this research by Deloitte. Some of the notable high-profile breaches and data leakages were the Sunburst SolarWinds attack, the Estee Lauder customer database leakage, the discovery of Facebook and MGM Resorts confidential data on the Dark Web, the resurgence of WannaCry, Revil and other ransomware attacks, along with the Mozi BotNet. Additionally, there have been widely publicized attacks on critical infrastructures as mentioned in this World Economic Forum Article as well. Ransomware-as-a-Service (RaaS) has also crystallised as a serious ongoing threat. Besides attacks on customers and critical infrastructures, there have been incidents across the digital supply chain, especially leveraging vulnerabilities such as Log4j.

According to a Gartner prediction, by 2025 45% of organisations worldwide will have experienced attacks on their software supply chains, a three-fold increase from 2021. Besides these high-profile external attacks, in 2020, Gartner had reported a close to 50% increase in insider incidents and an 85% more likelihood of employee file and data leakage compared to the pre-COVID era. This point has also been stressed upon in this research by McKinsey which states that 50% of cyber breaches are attributed to accidental and intentional insider threats.

Resilience Frameworks such as FISMA, The Cyber Resilience Review (CRR), the National Institute of Standards and Technology (NIST) FIPS 199, 200 and especially the 800-160 Volume 2 publications treat adverse cyber events as both resiliency and security issues and identify 14 techniques to enhance resilience. These frameworks also encompass Insider Risk Management, as this article by Deloitte highlights. In May 2021, as a response to the SunBurst SolarWinds breach, the Biden Administration in the US issued an executive order mandating strict adherence by the U.S. Federal Agencies to NIST 800-207 as a fundamentally required step for Zero Trust implementation. Another example is of Zoom during the early days of the pandemic in which it had agreed to enhance its security and privacy aspects, on direction from the Federal Trade Commission (FTC)

Artificial Intelligence, Machine Learning, Cyber Data Lakes, Security Information and Event Management (SIEM), Security Orchestration and Response Systems (SOAR), Extended Detection and Response (XDR) and other technologies are playing their part in adhering to the Zero Trust Architecture, Proactive threat hunting and monitoring, minimising false positives and ensuring the already overworked and stressed cyber security teams are handling apt and real incidents and optimising their time.

This article by McKinsey highlights that Data Protection and Privacy and adherence to regulatory compliance enhances organisational reputation, customer trust and builds a solid business advantage. Data Mapping and Classification is the cornerstone of this ethos of proactive customer privacy and data protection steps.

What are the important aspects that companies are considering in 2022?

This research by Gartner states that three fourths of all organizations will restructure risk and security governance for digital transformation in the light of the imploding cyber security threats, insider activity, and increase in attack surfaces and vulnerabilities. This research by EY states that Fortune 500 companies will be together shelling out close to USD 8 billion annually for GDPR compliance.

CISOs, CROs, CDOs, Legal, Risk and Governance Teams have been working together along with business in a cross functional approach to draw up detailed risk categories and assessments across data, people and other ecosystems, estimating cost of breaches and damages, implementing cyber security frameworks and technologies, and crystallising cyber insurance policies. This is even more important for companies who have underage customers such as those in the gaming, retail and entertainment verticals. Technologies such as Artificial Intelligence and blockchain and cybersecurity mesh architecture are being harnessed by companies to have more automated, intelligent and stringent adherence to compliance regulations.

It is of paramount importance for CISOs and leaders to have an in-depth knowledge of country specific data privacy laws, especially for Multinational enterprises and those handling sensitive end customer and employee data. Aspects such as customer/ employee/ stakeholder consent and rights, data storage, retention and transmission policies, clear guidelines in case of infringement, and others must be carefully comprehended. Leaders must keep abreast of all developments across the world, especially across the states in the US, the AI Act, Digital Services and Market Acts of Europe, the new regulations across the Middle East, Japan, Thailand and so on and so forth

Irrespective of company size, it is critical to have a clear privacy policy explaining to users of data across the extended enterprise as to the type of information collected, its usage and purpose, shareability and security. This should also cover agreeing/ blocking/ disabling online cookies. This applies equally in cases organisations are sharing data with each other including those of 3rd party vendors. CIOs and CDOs are working together to balance risk, transparency, customer/ stakeholder satisfaction as well as compliance. Needless to mention, the policies must balance risk, prioritisation, failure/ breach/ damage cost, management commitment and operational and reporting costs. Some companies have appointed Chief Privacy Officers who are custodians and responsible for this important function. Enlisting services of privacy and compliance consultants vis--vis full or partial insourcing are also active and ongoing considerations of management.

A very critical aspect to be considered is organisational culture. Leadership teams must clearly communicate and involve their teams with the goals, privacy policies, operational and compliance aspects, besides deploying technologies and checks. Clear communication, collaboration, gamification, training, rewards and recognitions are some of the tools by which CHROs in Asia and worldwide are assisting the CIOs/ CDOs/ CPOs in this area

What are the trends for 2022 and beyond?

There is little doubt that data focussed and driven enterprises have huge competitive advantages. This research by McKinsey highlights that some organisations which are already seeing contributions of AI to be amounting to 20% of their earnings, are highly likely to have robust data practices. With co-existence of humans and Artificial Intelligence in Super Teams, organisations which imbibe data literacy as well as leverage data and AI driven automation across low risk and daily processes, will have human intelligence focusing on higher risk, value and critical decisions. Focus on Data driven architectures, decisioning, fabrics, lifecycle management, automation driven compliance, and top management focus shall be the keys to unlocking value.

This research by Gartner highlights the 5 top data privacy trends throughout 2024, and anticipates 3/4th of Earths population shall have its personal data covered under a modern privacy and compliance regulation. With hybrid and remote working here to stay, Data Localization and Privacy Enhancing Computational Strategies, Robust AI Governance, and Self-Service UI for Privacy are expecting to be critical for the future. This article by Gartner predicts that by 2024, organisations will spend over USD 15 Billion in Data Protection and Compliance Technology on account on Privacy compliances.

With data, assets, users and entities across on-premise data centres and the hybrid/ multi- cloud across the extended enterprise, the trends of globalisation, decentralised risk and decision making, moving from Compliance and Security functions to Security Behaviour and Culture programs (SBCPs), consolidation and convergence of cyber security solutions and of vendors along with Cybersecurity Mesh Architecture (CSMA) help provide a proactive, uniform and integrated data and security framework and posture.

There shall be continuing threats on account of ransomware and its emerging models along with the increased attack surfaces on account of Metaverse and the Web 3.0. As far as IoT devices go, Governments, Institutions and Enterprises will continue to work on governance frameworks of uniform baseline standards for consumer and industrial IoT devices across users, supply chains and the extended enterprises incorporating shared security principles, certifications and regulations. It is expected that these guidelines shall encompass hardware encryption, software architecture and design and to also be taken into account during supplier compliance and assessment exercises as well.

Although commercial Quantum Computing is some distance away, CISOs are already considering future proofing and working on algorithms that are opaque to Quantum Computers and the threat to public key cryptography by incorporating Confidential computing, quantum safe cryptography, and fully homomorphic encryption. The National Institution of Standards and Technology (NIST) is already working on encryption and other resources and tools to ensure security and cyber resilience in the Quantum Computing era, as this article indicates. Also, the World Economic Forum has recently published the principles of quantum computing governance to minimise data theft, ensure compliance and mitigate risk. Proactively addressing Data Privacy, Policies and Regulations shall most certainly ensure in resilient, competitive and differentiated organisations with great reputations.

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An overview of data in 2022: Privacy, policies, and regulations - ETCIO South East Asia

NYU Langone and Fermilabs Superconducting Quantum Materials and Systems Center have proposed a pilot program to study a new method in MR imaging that combines quantitative MR (qMR) with quantum computing.

The two would develop algorithms that quantum computers could use to accurately and rapidly determine multiple tissue properties from MR scans. While quantum computing would speed up and make scans more accurate, the algorithms would improve qMR for clinical use to allow doctors to confirm interpretations by comparing MR scans based on statistics and machine learning, rather than inconsistencies in image contrast.

We expect to be able to model a large number of properties and the interactions among them to obtain a more comprehensive picture of the underlying structure of the imaged tissues. This will be possible not just because quantum computers enable faster generation of the large models, but also because they are better suited than traditional computers to model the interactions between tissue properties in MR, since they are governed by the laws of quantum mechanics, Dr. Riccardo Lattanzi, an associate radiology professor at NYU Grossman School of Medicine and principal investigator, told HCB News.

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The data is held within the 3D pixels of MR scans, which quantum computers can use to measure properties to assess and monitor patient health across multiple scans. It also can speed up measurements and create more accurate MR simulations to show the underlying properties of the MR data fingerprints.

Having multiple quantitative parameters that reflect the underlying properties of tissues improves detection of lesions and pathologies. Furthermore, by looking at them from different angles (i.e., by having multiple biophysical parameters estimated for the same pixel), we can also better characterize these lesions to help create personalized treatments," said Lattanzi.

He adds that another potential application is being able to generate digital twins to detect and characterize abnormalities.

SQMS Center is made up of 23 institutions studying the use of quantum computing. The partnership is the first one it has undertaken for directly advancing healthcare.

NYU has received DOE Office of Science approval to become a member of the SQMS Center.

The collaboration is pending final approval of a formal agreement between NYU and Fermi Research Alliance, which manages Fermilab.

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NYU Langone, Fermilab to enhance, speed up quantitative MR with quantum computing - DOTmed HealthCare Business News

New Jersey, United States This Quantum Computing Market research works as the best evaluation tool to track the progress of the industry and keep an eye on the competitors growth strategies. It further helps to keep you ahead of your business competitors. This report depicts a few potential problems and gives solutions to them by doing comprehensive research on the market scenario. Valuable information is provided here about a particular market segment according to product type, application, region type, and end user. By referring to this comprehensive Quantum Computing market analysis report, it becomes possible for organizations to monitor the efficiency of sales, determine the quality of services offered by competitors, estimate the competition level in the market and understand the communication channels followed by competitors in the market.

This Quantum Computing Market research report covers career outlooks, regional marketplaces, and an overview of the expectations of a number of end-use sectors. With the help of relevant market data, key organizations are able to obtain a competitive benefit over the competitors in the market and attain the best results for business growth. Furthermore, this Quantum Computing market analysis report emphasizes doing a comparison between several various geographical markets in key regions such as North America, Europe, Middle East, Africa, Latin America, and Asia Pacific. It aims at covering complex structures to classifications to an easy-to-follow overview of different business sectors.

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Key Players Mentioned in the Quantum Computing Market Research Report:

Qxbranch QC Ware Corp., International Business Machines Corporation (IBM), D-Wave Systems Inc., 1qb Information Technologies Inc., Cambridge Quantum Computing Ltd, Station Q Microsoft Corporation, River Lane Research, Rigetti Computing, Research at Google Google Inc

A massive amount of information presented in this Quantum Computing Market report helps business players to make beneficial decisions. Some of the major key aspects covered in this market analysis are key performance indicators, customer acquisition, and manufacturers list. Performance results of the marketing plan are also covered in this market analysis report. This market study report enables to bring the improvements required in the business. It further talks about how COVID-19 caused huge trauma in several major sectors. Key marketing channels, market growth opportunities, core marketing strategy, and current scope of the business are some of the major factors discussed in this report. It further briefs on the current position of the market. It depicts the effect of metrics on market trends, revenue, and leads.

Quantum ComputingMarket Segmentation:

Quantum Computing Market, By Offering

Consulting solutions Systems

Quantum Computing Market, By Application

Optimization Machine Learning Material Simulation

Quantum Computing Market, By End User

Space and Defense Automotive Healthcare Banking and Finance Chemicals Energy & Power

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For Prepare TOC Our Analyst deep Researched the Following Things:

Report Overview:It includes major players of the Quantum Computing market covered in the research study, research scope, market segments by type, market segments by application, years considered for the research study, and objectives of the report.

Global Growth Trends:This section focuses on industry trends where market drivers and top market trends are shed light upon. It also provides growth rates of key producers operating in the Quantum Computing market. Furthermore, it offers production and capacity analysis where marketing pricing trends, capacity, production, and production value of the Quantum Computing market are discussed.

Market Share by Manufacturers:Here, the report provides details about revenue by manufacturers, production and capacity by manufacturers, price by manufacturers, expansion plans, mergers and acquisitions, and products, market entry dates, distribution, and market areas of key manufacturers.

Market Size by Type:This section concentrates on product type segments where production value market share, price, and production market share by product type are discussed.

Market Size by Application:Besides an overview of the Quantum Computing market by application, it gives a study on the consumption in the Quantum Computing market by application.

Production by Region:Here, the production value growth rate, production growth rate, import and export, and key players of each regional market are provided.

Consumption by Region:This section provides information on the consumption in each regional market studied in the report. The consumption is discussed on the basis of country, application, and product type.

Company Profiles:Almost all leading players of the Quantum Computing market are profiled in this section. The analysts have provided information about their recent developments in the Quantum Computing market, products, revenue, production, business, and company.

Market Forecast by Production:The production and production value forecasts included in this section are for the Quantum Computing market as well as for key regional markets.

Market Forecast by Consumption:The consumption and consumption value forecasts included in this section are for the Quantum Computing market as well as for key regional markets.

Value Chain and Sales Analysis:It deeply analyzes customers, distributors, sales channels, and value chain of the Quantum Computing market.

Key Findings:This section gives a quick look at the important findings of the research study.

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Quantum Computing Market Size, Scope, Growth Opportunities, Trends by Manufacturers And Forecast to 2029 - This Is Ardee

Artificial intelligence (AI) is emerging as one of the key industry trends after decades of just being a researchers dream. From conversations with Alexa and Siri to Waymo (Google) and Teslas vehicles driving themselves, OpenAIs GPT-3 writing prose like a human, and DeepMind (Google)s AlphaZero beating human chess grandmasters, it is becoming clear that AI is now mature enough to resolve real-life problems and is often faster and better at it than humans.

Elsewhere in the tech industry, several visionaries are working towards developing quantum computers, which seek to leverage the properties of quantum physics to perform calculations much faster than todays computers.

At this point, you cannot be blamed for wondering: what exactly has quantum computing got to do with AI?

Algorithmic complexity is a somewhat obscure mathematical concept that connects the work being done by AI researchers and quantum computing pioneers.

Computational complexity theory, a field sitting across mathematics and computer science, focuses on classifying computational problems according to their resource usages, such as space (memory) and time. In essence, a computational problem is a task that can be solved by a computer mechanically following the mathematical steps defined in an algorithm.

For instance, consider the problem of sorting the numbers in a list. One possible algorithm, called Selection Sort, consists of repeatedly finding the minimum element (in ascending order) from the unsorted part of the list (initially, all of it) and putting it at the beginning. This algorithm effectively maintains two sub-lists within the original list as it works its way through: the already sorted part and the remaining unsorted part. After several passes of this process, the outcome is a sorted list from smaller to larger. In terms of time complexity, this is expressed by the complexity of N2, where N means the size or number of elements in the list. Mathematicians have come up with more efficient, albeit more complex sorting algorithms, such as Cube Sort or Tim Sort, both of which have an N x log(N) complexity. Sorting a list of 100 elements is a simple task for todays computers but sorting a list of a billion records might be less so. Therefore, the time complexity (or the number of steps in the algorithm in relation to the size of the input problem) is very important.

To solve a problem faster, one can either use a faster computer or find a more efficient algorithm that requires fewer operations, which is what lower time complexity means. However, it is clear that in the case of problems of exponential complexity (for instance, N2 or 2N), the math works against you, and with larger problem sizes it is not realistic to just use faster computers. And this is precisely the case in the field of artificial intelligence.

First, we will look at the computational complexity of the artificial neural networks used by todays artificial intelligence (AI) systems. These mathematical models are inspired by the biological neural networks that constitute animal brains. They learn to identify or categorize input data, by seeing many examples. They are a collection of interconnected nodes or neurons, combined with an activation function that determines the output based on the data presented in the input layer and the weights in the interconnections.

To adjust the weights in the interconnections so that the output is useful or correct, the network can be trained by exposure to many data examples and backpropagating the output loss.

For a neural network with N inputs, M hidden layers, where the i-th hidden layer contains mi hidden neurons, and k output neurons, the algorithm that adjusts the weights of all neurons (called a backpropagating algorithm) will have a time complexity of:

To put things in context, the popular OpenAIs GPT-3 model, which is already capable of writing original prose with fluency equivalent to that of a human, has 175 billion parameters (or neurons). With an M in the billions, this AI model currently takes months to train, even using powerful server computers in large cloud data centers. Furthermore, AI models are going to continue growing in size, so the situation will get worse over time.

Quantum computers are machines that use the properties of quantum physics, specifically superposition and entanglement, to store data and perform computations. The expectation is that they can execute billions of simultaneous operations, therefore providing a very material speedup for highly complex problems, including AI.

While classical computers transmit information in bits (short for binary digits), quantum computers use qubits (short for quantum bits). Like classical bits, qubits do eventually have to transmit information as a one or zero but are special in that they can represent both a one and a zero at the same time. A qubit is considered to have a probability distribution, e.g., it is 70% likely to be a one and 30% likely to be a zero. This is what makes quantum computers special.

There are two essential properties in quantum mechanics that quantum computers take advantage of: superposition and entanglement.

When a qubit is both a one and a zero at the same time, it is said to be in a superposition. Superposition is the general name for the condition when a system is in multiple states at once and only assumes a single state when it is measured. If we pretend that a coin is a quantum object, a superposition can be imposed when the coin is flipped: there is only a probability of the coin being either heads or tails. Once the coin has landed, we have made a measurement, and we know whether the coin is heads or tails. Likewise, only when we measure the spin of an electron (similar to the coin landing) do we know what state the electron is in and whether it is a one or a zero.

Quantum particles in superposition are only useful if we have more than one of them. This brings us to our second fundamental principle of quantum mechanics: entanglement. Two (or more) particles that are entangled cannot be individually described, and their properties depend completely on one another. So, entangled qubits can affect each other. The probability distribution of a qubit (being a one or zero) depends on the probability distribution of all other qubits in the system.

Because of that, the addition of each new qubit to a system has the effect of doubling the number of states that the computer can analyze. This exponential increase in computer power contrasts with classical computing, which only scales linearly with each new bit.

Entangled qubits can, theoretically, execute billions of simultaneous operations. It is obvious that this capability would provide a dramatic speedup to any algorithm with complexities in the range of N2, 2N, or NN.

Because of the impressive potential of quantum computing, while hardware teams continue to work on making these systems a reality (the largest to date is IBMs 127-Qubit Eagle system), software researchers are already working on new algorithms that could leverage this simultaneous computation capability, in fields such as cryptography, chemistry, materials science, systems optimization, and machine learning/AI. It is believed that Shors factorization quantum algorithm will provide an exponential speedup over classical computers, which poses a risk to current cryptographic algorithms.

Most interestingly, it is believed quantum linear algebra will provide a polynomial speed-up, which will enormously improve the performance of our artificial neural networks. Google has launched TensorFlow Quantum, a software framework for quantum machine learning, which allows rapid prototyping of hybrid quantum-classical ML models. IBM, also a leader in quantum computing, recently announced that it has found mathematical proof of a quantum advantage for quantum machine learning. However, while the likes of IBM and Google are vertically integrated (thus developing both the hardware systems and the software algorithms) there is also a very interesting group of quantum software startups including Zapata, Riverlane, 1Qbit, and, to a certain degree, Quantinuum (since Cambridge Quantum Computing merged with Honeywell and rebranded, it is not a pure software company anymore), to name just a few.

As quantum hardware becomes more powerful and quantum machine learning algorithms are perfected, quantum computing is likely to take a significant share of the AI chips market. For a more detailed discussion on AI chips and quantum computing, please take a look at our thematic reports on AI, AI chips, and quantum computing.

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What has quantum computing got to do with AI? - Verdict

Quantum computers hold the promise of revolutionising information technology by utilising the whacky physics of quantum mechanics. But playing with strange, new machinery often throws up even more interesting and novel physics. This is precisely what has happened to quantum computing researchers in the US.

Reported in Nature, physicists who were shining a pulsing laser at atoms inside a quantum computer observed a completely new phase of matter. The new state exhibits two time dimensions despite there still being only a singular time flow.

The researchers believe the new phase of matter could be used to develop quantum computers in which stored information is far more protected against errors than other architectures.

See, what makes quantum computers great is also what makes them exceedingly tricky.

Unlike in classical computers, a quantum computers transistor is on the quantum scale, like a single atom. This allows information to be encoded not just using zeroes and ones, but also a mixture, or superposition, of zero and one.

Hence, quantum bits (or qubits) can store multidimensional data and quantum computers would be thousands, even millions of times faster than classical computers, and perform far more efficiently.

But this same mixture of 0 and 1 states in qubits is also what makes them extremely prone to error. So a lot of quantum computing research revolves around making machines with reduced flaws in their calculations.

Read more: Australian researchers develop a coherent quantum simulator

The mind-bending property discovered by the authors of the Nature paper was produced by pulsing a laser shone on the atoms inside the quantum computer in a sequence inspired by the Fibonacci numbers.

Using an extra time dimension is a completely different way of thinking about phases of matter, says lead author Philipp Dumitrescu, a research fellow at the Flatiron Institutes Centre for Computational Quantum Physics in New York City, US. Ive been working on these theory ideas for over five years and seeing them realised in experiments is exciting.

The teams quantum computer is built on ten atomic ions of ytterbium which are manipulated by laser pulses.

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Quantum mechanics tells us that superpositions will break down when qubits are influenced (intentionally or not), leading the quantum transistor to pick to be either in the 0 or 1 state. This collapse is probabilistic and cannot be determined with certainty beforehand.

Even if you keep all the atoms under tight control, they can lose their quantumness by talking to their environment, heating up, or interacting with things in ways you didnt plan, Dumitrescu says. In practice, experimental devices have many sources of error that can degrade coherence after just a few laser pulses.

So, quantum computing engineers try to make qubits more resistant to outside effects.

One way of doing this is to exploit what physicists call symmetries which preserve properties despite certain changes. For example, a snowflake has rotational symmetry it looks the same when rotated a certain angle.

Time symmetry can be added using rhythmic laser pulses, but Dumitrescus team added two time symmetries by using ordered but non-repeating laser pulses.

Other ordered but non-repeating structures include quasicrystals. Unlike typical crystals which have repeating structure (like honeycombs), quasicrystals have order, but no repeating pattern (like Penrose tiling). Quasicrystals are actually the squished down versions, or projections, of higher-dimensional objects. For example, a two-dimensional Penrose tiling is a projection of a five-dimensional lattice.

Could quasicrystals be emulated in time, rather than space? Thats what Dumitrescus team was able to do.

Whereas a periodic laser pulse alternates (A, B, A, B, A, B, etc), the parts of the quasi-periodic laser-pulse based on the Fibonacci sequence are the sum of the two previous parts (A, AB, ABA, ABAAB, ABAABABA, etc.). Like a quasicrystal, this is a two-dimensional pattern jammed into a single dimension. Hence, theres an extra time symmetry as a boon from this time-based quasicrystal.

The team fired the Fibonacci-based laser pulse sequence at the qubits at either end of the ten-atom arrangement.

Using a strictly periodic laser pulse, these edge qubits remained in their superposition for 1.5 seconds an impressive feat in itself given the strong interactions between qubits. But, with the quasi-periodic pulses, the qubits stayed quantum for the entire length of the experiment around 5.5 seconds.

With this quasi-periodic sequence, theres a complicated evolution that cancels out all the errors that live on the edge, Dumitrescu explains. Because of that, the edge stays quantum-mechanically coherent much, much longer than youd expect. Though the findings bear much promise, the new phase of matter still needs to be integrated into a working quantum computer. We have this direct, tantalising application, but we need to find a way to hook it into the calculations, Dumitrescu says. Thats an open problem were working on.

Read more:

New phase of matter with 2D time created in quantum computer - Cosmos