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Global "Quantum Computing Market" Research report is an in-depth study of the market Analysis. Along with the most recent patterns and figures that uncovers a wide examination of the market offer. This report provides exhaustive coverage on geographical segmentation, latest demand scope, growth rate analysis with industry revenue and CAGR status. While emphasizing the key driving and restraining forces for this market, the report also offers a complete study of the future trends and developments of the market.

This report on the Quantum Computing Market study considers important factors such as an analysis of the market, a definition of the market, segmentation, significant trends in the industry, an examination of the competitive landscape, and research methodology. The research provides an idea about various market inhibitors as well as market motivators in both a quantitative and qualitative approach with the purpose of providing users with accurate information.

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What`s New for 2023?

Special coverage on Russia-Ukraine war; global inflation; easing of zero-Covid policy in China and its `bumpy` reopening; supply chain disruptions, global trade tensions; and risk of recession.Global competitiveness and key competitor percentage market sharesMarket presence across multiple geographies - Strong/Active/Niche/TrivialOnline interactive peer-to-peer collaborative bespoke updatesAccess to digital archives and Research PlatformComplimentary updates for one yearThe list of Key Players Profiled in the study includes:-IBM Quantum, Google Quantum Computing, Microsoft Quantum, Honeywell Quantum Solutions, D-Wave Systems, Rigetti Computing, IonQ, Intel Quantum Computing, Alibaba Quantum Computing, and Tencent Quantum Lab.

Cataloging the Competitive Terrain of the Quantum Computing Market:

The report provides an overview of every manufacturers and the products developed by each manufacturer along with the application scope of every product.Data regarding the market share of every company, as well as sales figures concerning each firm, is stated in the report.Details regarding the profit margins and price patterns have been inculcated in the report.IN THE NEWS In 2021, The Azure Quantum Resource Estimator, a tool that Microsoft (US) just released, will help algorithm designers and optimizers create algorithms that will function on next quantum computers.

In 2021, The recently released Intel Quantum SDK from Intel (US) enables programmers to create new quantum algorithms for the future execution of qubits on both virtual and physical quantum hardware.

Quantum Computing Market Dynamics:

This section deals with understanding the market drivers, advantages, opportunities, restraints and challenges. All of this is discussed in detail as below:

Growth Drivers:

1. Potential for solving complex problems and performing advanced simulations.

2. Growing interest from industries such as finance, pharmaceuticals, and logistics.

3. Advancements in quantum hardware and software technologies.

4. Potential for breakthroughs in cryptography and cybersecurity.

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Segmentation Analysis of the Market:

Global Quantum Computing Market forecast report provides a holistic evaluation of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market. Global Quantum Computing Market segments and Market Data Break Down are illuminated By Component: Hardware, Software, Services

By Application: Optimization, Simulation, Cryptography, Machine Learning, Drug Discovery

By Industry Vertical: Aerospace and Defense, Healthcare, Finance, Energy and Utilities, Logistics and Transportation

Regional Coverage:

Rgn-w gmnttn in the Global Quantum Computing Market nlud the claims to split the regional scope of the market, which among these regions has been touted to amass the largest market share over the anticipated duration

North America(USA, Canada and Mexico)Europe(UK, Germany, France and the Rest of Europe)Asia Pacific(China, Japan, India, and the Rest of the Asia Pacific region)South America(Brazil, Argentina and the Rest of South America)Middle East and Africa(GCC and Rest of the Middle East and Africa)

** Note - This report sample includes:

Scope For 2024Brief Introduction to the research report.Table of Contents (Scope covered as a part of the study)Top players in the marketResearch framework (structure of the report)Research methodology adopted by The Market InsightsThe Global Quantum Computing Market Industry Report Covers The Following Data Points:

: This section covers the global Market overview, including the basic market introduction, market analysis by its applications, type, and regions. The major regions of the global Market industry include North America, Europe, Asia-Pacific, and the Middle-East and Africa. Quantum Computing Market industry statistics and outlook are presented in this section. Market dynamics states the opportunities, key driving forces, market risk are studied.

: This section covers Market manufacturers profile based on their business overview, product type, and application. Also, the sales volume, market product price, gross margin analysis, and share of each player is profiled in this report.

: These sections present the market competition based on sales, profits, and market division of each manufacturer. It also covers the industry scenario based on regional conditions.

: These sections provide forecast information related to Quantum Computing Market for each region. The sales channels include direct and indirect Marketing, traders, distributors, and development trends are presented in this report.

: In these sections, Industry key research conclusions and outcome, analysis methodology, and data sources are covered.

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What makes the information worth buying?

A comprehensive and in-depth overview of the global Quantum Computing industry in exchange, use, and geographical area sectors is provided.

This research looks at the industry rewards and constraints that influence industry growth.

Developing business strategies and aspects to aid in an emerging market.

Examining free markets and developing appropriate strategies.

About us:Delivering foresights along with statistical analysis of the operational business industry impacts has been our foremost priority. With the constant developments in the research & development industry, we have always challenged the conventional research methodologies and discovered new research tactics to evolve the growing B2B requirements.

Direct Contact:Jessica Joyal+ 1 (614)602-2897Email: sales@themarketinsights.comWebsite: https://www.themarketinsights.com/

This release was published on openPR.

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Quantum Computing Market Deep Dive into Industry Leaders: Analysis of Top Manufacturers and Their Strategic Ap - openPR

Boise State University is included in three $1 million awards from the U.S. National Science Foundations Regional Innovation Engines, or NSF Engines, program. Boise State researchers will be represented among 40 unique teams to receive the first-ever NSF Engines Development Awards, which aim to help partners collaborate to create economic, societal and technological opportunities for their regions.

The three Engines and their points of contact at Boise State include:

Nancy Glenn, Advancing Autonomous Systems Technologies in the Northern Front (North Dakota, South Dakota, Montana, Idaho)

This project will expand Boise States expertise in autonomous vehicles, including unoccupied aerial systems (UAS) or drones, in both training and applications, in partnership with industry and network members. UAS applications range from infrastructure monitoring to natural resource management, geosciences, and beyond, along with expanding data science.

Lan Li, Advancing Quantum and Supporting Technologies in the Northern Intermountain States (Montana, Wyoming, Idaho)

This project is to establish a network of quantum computing and information systems, called the Quantum Capacity, Operational Resilience and Equity (QCORE) in a three-state region (Montana, Wyoming, and Idaho). Boise State will collaborate with Montana State University, University of Wyoming, and local industry partners to enhance economic development, research innovation, and workforce development in the field of quantum computing and information.

David Estrada, Advancing Semiconductor Technologies in the Northwest (Oregon, Idaho, Washington)

Aligned to the White House Office of Science and Technologys National Strategy for Advanced Manufacturing, this project includes federal, regional and state government bodies, private industry and public learning institutions to develop a regional innovation ecosystem that expands discovery and entrepreneurship for the semiconductor industry. Partnerships with academic institutions and nonprofit organizations will also advance pathways for careers in semiconductor manufacturing.

All three NSF Engines Development projects represent Boise States expertise in critical and emerging technologies, and will build upon existing workforce training programs and use-inspired research, said Vice President for Research and Economic Development Nancy Glenn. Furthermore, the projects will expand our industry and agency partnerships, ultimately providing new opportunities for students to gain workforce skills and attracting and retaining talent.

One of the greatest challenges facing the information and communications technology ecosystem is the amount of energy required to process and store the tremendous amounts of data we produce, said David Estrada, associate professor of materials science and engineering and site director of Boise States NSF Center for Atomically Thin and Multifunctional Coatings. The emerging Pacific Northwest Semiconductor Ecosystem is very well positioned to solve such semiconductor related challenges, and help reap the economic rewards for Idaho, Oregon, and Washington.

Building a robust quantum innovation ecosystem is crucial for economics and national security, said Lan Li, associate professor of materials science and engineering. Quantum computing and information systems open new market opportunities in cybersecurity, artificial intelligence, financial services, and complex manufacturing. Boise State aims to explore a three-fold plan, including economic development, research innovation, and workforce development, which uniquely fits Boise State and its nationally recognized role in molecular and solid-state quantum materials development and characterization in support of quantum information applications as part of a regional quantum ecosystem.

The NSF Engines program is a transformational investment for the nation, ensuring the U.S. remains in the vanguard of competitiveness for decades to come.

These NSF Engines Development Awards lay the foundation for emerging hubs of innovation and potential future NSF Engines, said NSF Director Sethuraman Panchanathan. These awardees are part of the fabric of NSFs vision to create opportunities everywhere and enable innovation anywhere. They will build robust regional partnerships rooted in scientific and technological innovation in every part of our nation. Through these planning awards, NSF is seeding the future for in-place innovation in communities and to grow their regional economies through research and partnerships. This will unleash ideas, talent, pathways and resources to create vibrant innovation ecosystems all across our nation.

The awardees span a broad range of states and regions, reaching geographic areas that have not fully benefited from the technology boom of the past decades. These NSF Engines Development Awards will help organizations create connections and develop their local innovation ecosystems within two years to prepare strong proposals for becoming future NSF Engines, which will each have the opportunity to receive up to $160 million.

Launched by NSFs new Directorate for Technology, Innovation and Partnerships and authorized by the CHIPS and Science Act of 2022, the NSF Engines program uniquely harnesses the nations science and technology research and development enterprise and regional-level resources. NSF Engines aspire to catalyze robust partnerships to positively impact regional economies, accelerate technology development, address societal challenges, advance national competitiveness and create local, high-wage jobs.

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Boise State University wins three NSF Regional Innovation Engines ... - Boise State University

Dear Editor,

Education is set to undergo a major transformation thanks to the rise of artificial intelligence (AI) and quantum computing technologies. These new technologies will revolutionize the way we learn, communicate, and interact with each other, and will open up a whole new world of possibilities for educators and students alike. AI and quantum computing technologies will allow us to create intelligent learning systems that can adapt to the individual needs of each student. By analyzing data on student performance, these systems can identify areas where students need more help and provide personalized recommendations to help them improve. One of the key benefits of AI-powered learning systems is that they can help to reduce educational disparities. With personalized learning systems, students who are struggling can receive the extra help they need, while advanced learners can be challenged with more complex material. This can help to level the playing field and ensure that all students have an equal opportunity to succeed. In addition to personalized learning, AI and quantum computing technologies will also transform the way we interact with each other. Virtual and augmented reality technologies will allow us to create immersive educational experiences that can transport us to different parts of the world and even beyond. For example, students could use virtual reality to explore the Great Barrier Reef, or to experience life in a different time period. These immersive experiences can help to make learning more engaging and exciting, and can help to create a deeper understanding of complex concepts. However, with these new technologies comes a need for educators to stay up-to-date with the latest developments and ensure that students are equipped with the necessary skills to thrive in an AI-powered world. As AI and quantum computing technologies continue to evolve, educators will need to be prepared to adapt their teaching methods and curricula to keep up with the latest advancements. In conclusion, the rise of AI and quantum computing technologies will bring about a transformation in education that has the potential to level the playing field and provide students with personalized learning experiences that meet their individual needs. Educators who are prepared to embrace these new technologies and adapt their teaching methods accordingly will be at the forefront of this transformation, and will help to shape the future of education for generations to come.

The paragraphs above were written for me by ChatGPT with the request Write a newspaper article on how education will be transformed by AI and quantum computing technologies. As an educator, an engineer, and a science enthusiast, the above is remarkable. The question that arises is How should a country transform its current education system for AI and quantum computing technologies? This is what I asked ChatGPT and here is the amazing response. Transforming a countrys education system to incorporate AI and quantum computing technologies can be a complex and challenging process, but it is essential to prepare future generations for the evolving job market and technological landscape. Here are some steps a country can take to transform its current education system:

1. Develop a comprehensive AI and quantum computing education plan: This plan should include the specific skills and knowledge that students will need to be successful in an AI-driven economy, as well as strategies for incorporating new technologies into the classroom.

2. Invest in teacher training: Teachers are the key to transforming education systems, so its important to invest in training programs that will help them learn new technologies and teaching methods.

3. Create partnerships with industry: Collaboration with industry leaders can help to provide educators with the latest technology and insights on how to best prepare students for the workforce.

4. Introduce AI and quantum computing into the curriculum: This can include introducing courses on these topics at all levels of education, from elementary school to university.

5. Encourage creativity and innovation: AI and quantum computing technologies require creativity and innovation, so its important to foster these skills in students through hands-on projects and other experiential learning opportunities.

6. Develop cross-disciplinary programs: AI and quantum computing are multidisciplinary fields, so its important to create programs that incorporate different fields of study, such as computer

science, mathematics, physics, and engineering.

7. Encourage lifelong learning: The rapid pace of technological change means that students will need to continue learning throughout their careers. Education systems should therefore encourage lifelong learning and provide opportunities for upskilling and reskilling.

Transforming an education system for AI and quantum computing technologies is a long-term process that requires collaboration between policymakers, educators, and industry leaders. By investing in the development of AI and quantum computing education programs, training teachers, and encouraging creativity and innovation, countries can prepare their citizens for a future that is increasingly reliant on these emerging technologies.

The writer spent several months researching the two questions posed to ChatGPT and he confesses that ChatGPT responses, in a few seconds, were mind-blowing. Services such as medicine, engineering, law, accounting that involve processes and procedures will undergo paradigm shifts. Indeed, AI and quantum computing technologies will quickly change 21st century living. The policy makers in Guyana should heed the recommendations of ChatGPT and setup a committee to commence the transformation and be among the leaders rather than as a follower.

Sincerely,

Muniram Budhu

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An AI and quantum computing technologies based education ... - Stabroek News

Quantum AI has emerged as a powerful tool in portfolio management, offering unprecedented potential to optimize investment strategies and generate superior returns. By leveraging quantum mechanical principles to process complex data and analyze patterns, quantum AI can unlock hidden value and generate insights that traditional investment techniques simply cant match. In this article, well explore the evolution of quantum AI, its key components, and how it intersects with portfolio management. Well also examine the benefits and challenges it presents for investors, and consider some real-world examples of quantum AI in action.

What is Quantum AI?

At its core, quantum AI is an interdisciplinary field that combines the principles of quantum mechanics and artificial intelligence to solve complex problems. Like traditional AI, quantum AI uses machine learning algorithms to analyze data and identify patterns. However, unlike classical computers, which process information using binary bits, quantum computers use quantum bits (qubits) to represent data. This allows quantum AI to process immense volumes of data simultaneously, making it ideal for applications in finance, healthcare, and other data-intensive fields.

Quantum AI is not just a theoretical concept; it has already been implemented in various industries. For example, in finance, quantum AI is used to identify patterns in financial data, which can help traders make better investment decisions. In healthcare, quantum AI is used to analyze medical images, such as MRIs and CT scans, to detect early signs of diseases.

The Evolution of Quantum Computing

Quantum computing has been an area of research for several decades, but it wasnt until the late 20th century that scientists were able to build functional quantum computers. The first quantum computer was built in 1994 by Peter Shor, a mathematician at MIT, and since then, scientists have made significant strides in developing more powerful quantum processors.

One of the biggest challenges in developing quantum computers is maintaining the delicate quantum state of the qubits. Even the slightest disturbance, such as a stray photon or a vibration, can cause the qubits to lose their quantum state, which can lead to errors in calculations. To overcome this challenge, scientists are developing new materials and technologies, such as superconducting qubits and ion traps, that can better isolate the qubits from their environment.

Key Components of Quantum AI

Quantum AI is built on several key components, including quantum processors, quantum algorithms, and classical computers. Quantum processors are the heart of any quantum computer, and they are responsible for manipulating the qubits that represent data. Quantum algorithms, on the other hand, are the software programs that run on quantum processors, and they are designed to perform specific tasks, such as optimization or pattern recognition.

Classical computers are used to control and monitor quantum processors, as well as to process the output data generated by quantum algorithms. However, because quantum and classical computers operate on different principles, it can be challenging to integrate them seamlessly. To address this issue, researchers are developing new software tools and programming languages that can bridge the gap between quantum and classical computing.

Overall, quantum AI has enormous potential to revolutionize many fields, from finance and healthcare to energy and transportation. As quantum computers become more powerful and more widely available, we can expect to see even more exciting applications of quantum AI in the years to come.

Traditional Portfolio Management Techniques

Portfolio management is the process of constructing and managing a portfolio of assets to achieve a specific financial goal, such as maximizing returns or minimizing risk. Traditional portfolio management techniques rely on a combination of fundamental analysis, technical analysis, and market data to select investments and optimize allocation. While these techniques have been successful in generating modest returns, they are limited by their reliance on historical data and predetermined models.

How Quantum AI Enhances Portfolio Management

QuantumAItrading.net offers several benefits for portfolio management, including enhanced risk assessment and mitigation, optimized asset allocation and diversification, and increased efficiency and cost savings. By leveraging quantum algorithms to analyze complex market data, quantum AI can identify patterns and generate insights that traditional techniques cant match. Additionally, quantum AIs ability to process massive amounts of data simultaneously allows investors to perform real-time risk assessment, adjust portfolios to changing market conditions, and optimize asset allocation to achieve specific financial goals.

Real-World Examples of Quantum AI in Finance

Several financial institutions have already started to incorporate quantum AI into their investment strategies. For example, JPMorgan Chase launched a quantum AI platform in 2019 that uses quantum algorithms to optimize asset trading and portfolio management. Similarly, Goldman Sachs has partnered with QC Ware, a quantum computing startup, to explore the potential of quantum AI in finance. Other companies, such as Cambridge Quantum Computing, are developing quantum algorithms specifically designed for asset pricing and portfolio optimization.

Benefits of Quantum AI in Portfolio Management

Improved Risk Assessment and Mitigation

One of the key benefits of quantum AI in portfolio management is its ability to perform real-time risk assessment and mitigation. By analyzing complex market data in real-time, quantum AI can identify patterns and correlations that traditional techniques cannot, allowing investors to adjust their portfolios to changing market conditions and minimize risk.

Enhanced Decision-Making Capabilities

Quantum AIs ability to process massive amounts of data simultaneously also means that investors can make more informed and accurate investment decisions. By analyzing vast datasets with unparalleled speed and accuracy, quantum AI can generate insights that traditional techniques simply cant match, helping investors make better-informed investment decisions.

Optimized Asset Allocation and Diversification

Quantum AI also offers significant potential for optimizing asset allocation and diversification. By analyzing vast quantities of market data, quantum AI can identify correlations and relationships between assets that traditional techniques cannot. This allows investors to construct portfolios that are optimized for specific financial goals, such as maximizing returns or minimizing risk.

Increased Efficiency and Cost Savings

Finally, quantum AI presents significant potential for increasing efficiency and reducing costs in portfolio management. By automating many of the tasks traditionally performed by humans, such as data analysis and portfolio optimization, quantum AI can reduce the workload of portfolio managers and free them up to focus on higher-level tasks. This can lead to significant cost savings for investors, as well as increased efficiency and productivity.

Challenges and Limitations of Quantum AI in Portfolio Management

Technological Barriers and Scalability

While quantum AI presents significant potential for portfolio management, there are also several significant challenges and limitations that must be addressed. One of the primary challenges is technological, as quantum computers are still in the experimental phase and are not yet powerful enough to handle many of the complex tasks required in portfolio management. Additionally, scalability remains a significant challenge, as quantum algorithms and hardware are still in their infancy.

Data Privacy and Security Concerns

Another significant challenge is data privacy and security. As quantum AI algorithms become more sophisticated, they may be able to crack many of the encryption techniques currently used to protect sensitive financial data. This presents significant risks for investors, as well as regulatory and ethical concerns around data privacy and security.

Ethical Considerations and Bias in AI

Finally, there are ethical considerations around the use of AI in finance, particularly around bias and discrimination. As AI algorithms become more sophisticated, they may inadvertently introduce biases that perpetuate existing inequalities in the financial system. Additionally, the lack of transparency in AI algorithms presents challenges for regulators and investors alike, as it can be difficult to audit AI decision-making and ensure that it is fair and unbiased.

Conclusion

Despite these challenges, quantum AI presents significant potential for portfolio management, offering enhanced risk assessment and mitigation, optimized asset allocation and diversification, and increased efficiency and cost savings. As quantum computing technology continues to evolve and become more powerful, we can expect to see increased adoption of quantum AI in finance and other data-intensive fields. However, addressing the challenges and limitations of quantum AI will be critical to ensuring that it is used ethically and responsibly, and that it benefits investors and society as a whole.

Link:
Unlocking the Potential of Quantum AI in Portfolio Management ... - NNN NEWS NIGERIA

The proposed technique is expected to enable quantum sampling algorithms to scale to high precision, paving the way for quantum advantage on practical problems

COLLEGE PARK, Md., May 04, 2023--(BUSINESS WIRE)--IonQ (NYSE: IONQ), an industry leader in quantum computing, in collaboration with the Fidelity Center for Applied Technology (FCAT), today announced an efficient and reliable design as a critical first step in the application of quantum computing to Monte Carlo methods. The first-of-its-kind state preparation technique is scalable and has been demonstrated on IonQ hardware for up to 20 qubits. The achievement may not only benefit financial institutions in tasks like portfolio management, but also other industries including science and engineering, where Monte Carlo algorithms are used. A research paper outlining the new technique is available here for viewing.

State preparation is a necessary component of many quantum algorithms and is fundamental in expediting Monte Carlo methods, which use randomness to simulate outcomes of complex problems. Financial institutions use Monte Carlo algorithms to understand the relationship between an outcome and multiple variables in complex systems, but their precision is frequently limited by the length of time needed to run the same algorithm repeatedly with different values of the variables. IonQ and FCAT believe that when run on large and accurate quantum computers, this state preparation technique will help these institutions achieve faster results.

"The Fidelity Center for Applied Technology team were early believers in the power of quantum to reshape the field of finance, and we are pleased to announce the development of a first-of-its-kind state preparation technique with them," said Peter Chapman, CEO, IonQ. "In finance, accuracy and speed can mean the difference between profit or loss. We believe this technique can provide financial institutions a tool they need to integrate quantum into their workflow and explore novel ways to inform portfolio engineering, retirement planning, and risk management in even the most complex of scenarios."

Story continues

Todays announcement is an extension of IonQs project with the FCAT team, during which the two groups issued a paper describing how certain generative quantum machine learning algorithms may provide an advantage over their classical counterparts. Additional information about IonQs work with FCAT will be presented at the American Physical Society (APS) Annual Meeting 2023, taking place March 5-10, 2023, in Las Vegas, Nevada.

"The Monte Carlo protocol is an integral component of financial planning, as it helps us understand how several correlated variables interact with each other when one element is changed," said Adam Schouela, Head of Emerging Technology, Fidelity Center for Applied Technology. "However, current state preparation techniques are either theoretical or have some type of deficiency when scaling. Today, were proud to announce alongside IonQ a state preparation algorithm that we believe is scalable and executable on NISQ hardware."

Todays announcement follows recent news that IonQ has acquired quantum software compiler Entangled Networks, with the goal of building large-scale quantum computers by enabling computation across multiple distributed quantum processors. Additionally, in 2022 IonQ entered into a multi-million-dollar contract with the U.S. Air Force Research Lab, as well as partnerships with companies like Dell Technologies, Hyundai Motors, Airbus, and GE Research, among others. For more information, visit investors.ionq.com/news.

About IonQ

IonQ, Inc. is a leader in quantum computing, with a proven track record of innovation and deployment. IonQ Aria is the latest in a line of cutting-edge commercial quantum systems, boasting industry-leading 25 algorithmic qubits. Along with record performance, IonQ has defined what it believes is the best path forward to scale.

IonQ is the only company with its quantum systems available through the cloud on Amazon Braket, Microsoft Azure, and Google Cloud, as well as through direct API access. IonQ was founded in 2015 by Dr. Christopher Monroe and Dr. Jungsang Kim based on 25 years of pioneering research. To learn more, visit http://www.ionq.com.

About the Fidelity Center for Applied Technology

Since 1999, the Fidelity Center for Applied Technology has served as an innovative technology resource for Fidelity Investments. FCAT research and development teams evaluate and track important trends in technology, identifying those that will matter most to Fidelity over the next five years. FCAT is a catalyst for breakthrough achievements, developing and bringing new capabilities and products to scale and building effective tools and systems that support millions of individual and institutional customers. Every day, FCAT teams lay the foundation for Fidelitys future, one experiment at a time.IONQ and Fidelity Investments are not affiliated.

IonQ Forward-Looking Statements

This press release contains certain forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Some of the forward-looking statements can be identified by the use of forward-looking words. Statements that are not historical in nature, including the words "anticipate," "expect," "suggests," "plan," "believe," "intend," "estimates," "targets," "projects," "should," "could," "would," "may," "will," "forecast" and other similar expressions are intended to identify forward-looking statements. These statements include those related to the application of quantum computing to Monte Carlo methods and its benefit to financial institutions and other industries where the Monte Carlo method is used; the ability of the state preparation technique to help institutions achieve faster results with Monte Carlo algorithms; the power of quantum computing to reshape the field of finance; the ability of financial institutions to integrate quantum computing into their workflow; and IonQs ability to build large-scale quantum computers by enabling computation across multiple distributed quantum processors. Forward-looking statements are predictions, projections and other statements about future events that are based on current expectations and assumptions and, as a result, are subject to risks and uncertainties. Many factors could cause actual future events to differ materially from the forward-looking statements in this press release, including but not limited to: market adoption of quantum computing solutions and IonQs products, services and solutions; the ability of IonQ to protect its intellectual property; changes in the competitive industries in which IonQ operates; changes in laws and regulations affecting IonQs business; IonQs ability to implement its business plans, forecasts and other expectations, and identify and realize additional partnerships and opportunities; and the risk of downturns in the market and the technology industry. The foregoing list of factors is not exhaustive. You should carefully consider the foregoing factors and the other risks and uncertainties described in the "Risk Factors" section of IonQs Quarterly Report on Form 10-Q for the quarter ended September 30, 2022 and other documents filed by IonQ from time to time with the Securities and Exchange Commission. These filings identify and address other important risks and uncertainties that could cause actual events and results to differ materially from those contained in the forward-looking statements. Forward-looking statements speak only as of the date they are made. Readers are cautioned not to put undue reliance on forward-looking statements, and IonQ assumes no obligation and does not intend to update or revise these forward-looking statements, whether as a result of new information, future events, or otherwise. IonQ does not give any assurance that it will achieve its expectations.

View source version on businesswire.com: https://www.businesswire.com/news/home/20230504005416/en/

Contacts

IonQ Media contact:Tyler Ogoshipress@ionq.com

IonQ Investor Contact:investors@ionq.com

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IonQ and Fidelity Center for Applied Technology Announce Development of Scalable Quantum State Preparation for Monte Carlo Algorithms - Yahoo Finance