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Category Archives: Quantum Computing

The 3 Best Quantum Computing Stocks to Buy in February 2024 – InvestorPlace

Much like artificial intelligence (AI), quantum computing will revolutionize just about everything. All thanks to its ability to solve complex problems that are well beyond the ability of non-quantum and classical computers. In fact,according to CBS News, Quantum could give us answers to impossible problems in physics, chemistry, engineering, and medicine. All of which could give a boost to some of the best quantum computing stocks to buy.

It could even be used to discover new drugs, quicker than even imagined. It may even be able to help advance artificial intelligence, machine learning, financial modeling, cybersecurity, batteries, and even help explain the unexplainable parts of our universe. Better,according to Fortune Business Insights, the market valued at $717.3 million in 2022 could be worth well over $6.5 billion by 2030.

Helping, theU.S. government wants to spend billionsto accelerate the development of quantum computing. Right now, many argue the U.S. is falling behind. That being said, investors may want to invest in some of thebest quantum computing stocks to buy including:

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The last time I mentionedD-Wave Quantum(NYSE:QBTS),it traded at about 90 cents on Feb. 1.

At the time, I noted, Itinked a dealwithDeloitteto speed up quantum computing adoption for governments and companies all over Canada. Even better, the company isseeing quarter-over-quarter, and year-over-year growthin revenue, and customer bookings.

Today, QBTS is up to $2.08, and running on news of its new 1,200+Qubit Advantage2 prototype, which it calls the most performant system available to customers today, as noted in a recent press release.

Better, earnings havent been too shabby. In its most recent quarter, QBTS revenue was up 50% quarter over quarter, and 51% year over year. Bookings even jumped 53% year over year to $2.9 million. Plus, this was the companys sixth consecutive quarter of year over year growth in quarterly bookings. The company also reported a $53.3 million cash balance, the highest in the companys history,as noted in its November earnings release. This makes it one of the best quantum computing stocks to buy.

Source: Amin Van / Shutterstock.com

Another one of thebest quantum computing stocks to buy isRigetti Computing(NASDAQ:RGTI), which has been steadily moving higher.

Since the year began, for example, it ran from about 90 cents to a high of $1.53. Now at $1.30. it could push even higher as investors push into quantum computing.

Helping, the company just announced the availability of its Ankaa-2 system, which it says is its highest qubit count quantum processing unit (QPU) available to the public,as noted in a recent press release.

It also inked a five-year deal to provide the Air Force Research Lab Information Directorate to supply researchers with quantum foundry services. This contract allows AFRL to leverage Rigettis fabrication and manufacturing capabilities to build customized quantum systems,as also mentioned in a company press release.

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Or, you could always diversify with an exchange-traded fund (ETF) like theDefiance Quantum ETF(NYSEARCA:QTUM). Since late October, the ETF exploded from a low of about $45 to a recent high of $58.51. Now at $57.53, it could push even higher thanks to holdings such asNvidia(NASDAQ:NVDA),Advanced Micro Devices(NASDAQ:AMD), andMarvell Technology(NASDAQ:MRVL) to name some of the top ones.

With an expense ratio of 0.40%, it also offers exposure to 68 more quantum computing and machine learning stocks. Moving forward, Id like to see the ETF test $70 a share.

On the date of publication, Ian Cooper did not hold (either directly or indirectly) any positions in the securities mentioned. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

Ian Cooper, a contributor to InvestorPlace.com, has been analyzing stocks and options for web-based advisories since 1999.

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3 Quantum Computing Stocks to Tap into the Future in 2024 – InvestorPlace

Invest in quantum leap in 2024, uncovering tech stocks driving the quantum computing industry's explosive growth

As we usher in 2024, quantum computing stocks are not just buzzwords but pivotal players in a technological revolution. Quantum computing, a field brewing for decades, currently stands at the forefront of innovation. Its a realm where the peculiarities of quantum mechanics converge to forge computing power, effectively dwarfing traditional methods.

Moreover, though quantum computing still dances mostly within the experimental stages in commercial settings, its promise remains undeniable. Functional quantum systems are no longer a fragment of science fiction they are a reality. The implications of this technology are vast and varied, stretching from societal advancements to inevitable security challenges. Yet, the promise held within these quantum computing stocks is palpable, a promise of a future where the benefits far surpass the risks.

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IonQ(NYSE:IONQ) stands out in the quantum computing space as a dedicated player, distinct from the sprawling tech giants which traditionally dominate the sector. This focus gives IonQ an edge, primarily considering its smaller market cap which hints at a robust upside potential for investors. As the first pure-play quantum computing company to go public, IonQ doesnt just participate in the quantum computing conversation; it leads it. With the industry still in its early stages, IonQs role in the sector is critical to the quantum computing narrative.

A significant draw for IonQ is its impressive collaborations with all three major cloud providers. Notably, its Aria quantum computer integrates seamlessly with Amazon (NASDAQ:AMZN), a platform enabling advanced tasks, including testing quantum circuits. This accessibility is a big leap forward for quantum computing applications. Financially, IonQs trajectory has been remarkable. Surpassing its $100 million cumulative bookings target since 2021 and accumulating $58.4 million in bookings in 2023 alone, IonQ demonstrates potent growth. Despite its unprofitability in terms of cash flow, the companys revenue for the third quarter surged by 122% year-over-year (YOY), a clear indicator of its mushrooming potential in a nascent yet rapidly evolving market.

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Nvidia(NASDAQ:NVDA) has established itself as a titan in the tech sphere, particularly in 2023, with its groundbreaking h100 chips leading the charge in artificial intelligence (AI) applications. The anticipation for 2024 is already high as Nvidia gears up to unveil the h200, the successor to the h100. The h200 is poised to elevate Nvidias status even further, reinforcing its position as a frontrunner in the tech world.

Beyond its AI prowess, Nvidia is making significant strides in quantum computing. Its cuQuantum project, aimed at stimulating quantum circuits, has broken new ground in the simulation of ideal and noisy qubits. Nvidias expertise in simulating quantum computing environments is another compelling reason for investors to take note. Moreover, Nvidias projections for a potential quadrupling by 2035 indicate a promising path for long-term investment.

Source: IgorGolovniov / Shutterstock.com

Alphabet(NASDAQ:GOOG, NASDAQ:GOOGL) is emerging as a powerhouse in the quantum computing sphere, achieving a pivotal breakthrough in February by reducing computational errors in its quantum bits. This advancement is a critical step towards making quantum computers not only usable but commercially viable. Alphabets dedication to overcoming one of the major hurdles in quantum computing commercialization highlights its commitment to leading in this innovative field.

Financially, Alphabet is on a strong footing, bolstered by its decision to efficiently reorganize its advertising business, which represents a staggering 80% of its total revenue. This reorganization comes on the heels of a remarkable $54.4 billion in ad sales in the recent quarter. Such strategic shifts could further enhance the companys robust financial performance. Additionally, Alphabets foray into AI with the launch of Gemini, an AI model designed to rival Microsofts OpenAI, showcases its ambition to convert technological prowess into tangible sales growth. The companys impressive top and bottom lines, with sales of $297.13 billion and net income of $66.73 billion, further solidify its position as a robust contender in the tech arena, poised for continued growth and innovation.

On the date of publication, Muslim Farooque did not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

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Beyond Binary: The Convergence of Quantum Computing, DNA Data Storage, and AI – Medium

Exploring the convergence of quantum computing, DNA data storage, and AI how these technologies could revolutionize computing power, memory, and information handling if challenges around implementation and ethics are overcome.

Check out these two books for a deeper dive and to stay ahead of the curve.

Computing technology has advanced in leaps and bounds since the early days of Charles Babbages Analytical Engine in the 1800s. The creation of the first programmable computer in the 1940s ushered in a digital revolution that has profoundly impacted communication, commerce, and scientific research. But the binary logic that underlies modern computing is nearing its limits. Exploring new frontiers in processing power, data storage, and information handling will enable us to tackle increasingly complex challenges.

The basic unit of binary computing is the bit either a 0 or 1. These bits can be manipulated using simple logic gates like AND, OR, and NOT. Combined together, these gates can perform any logical or mathematical operation. This binary code underpins everything from representing the notes in a musical composition to the pixels in a digital photograph. However, maintaining and expanding todays vast computational infrastructure requires massive amounts of energy and resources. And binary systems struggle to efficiently solve exponentially complex problems like modeling protein folding.

In the quest to surpass the boundaries of binary computing, quantum computing emerges as a groundbreaking solution. It leverages the enigmatic and powerful principles of quantum mechanics, fundamentally different from the classical world we experience daily.

Quantum Mechanics: The Core of Quantum Computing

Quantum computing is rooted in quantum mechanics, the physics of the very small. At this scale, particles like electrons and photons behave in ways that can seem almost magical. Two key properties leveraged in quantum computing are superposition and entanglement.

Superposition allows a quantum bit, or qubit, to exist in multiple states (0 and 1) simultaneously, unlike a binary bit which is either 0 or 1. This means a quantum computer can process a vast array of possibilities at once.

Entanglement is a phenomenon where qubits become interlinked in such a way that the state of one (whether its a 0, a 1, or both) can depend on the state of another, regardless of the distance between them. This allows for incredibly fast information processing and transfer.

Exponential Growth in Processing Power

A quantum computer with multiple qubits can perform many calculations at once. For example, 50 qubits can simultaneously exist in over a quadrillion possible states. This exponential growth in processing power could tackle problems that are currently unsolvable by conventional computers, such as simulating large molecules for drug discovery or optimizing complex systems like large-scale logistics.

Revolutionizing Fields: Cryptography and Beyond

Quantum computing holds the potential to revolutionize numerous fields. In cryptography, it could render current encryption methods obsolete, as algorithms like Shors could theoretically break them in mere seconds. This presents both a risk and an opportunity, prompting a new era of quantum-safe cryptography.

Beyond cryptography, quantum computing could advance materials science by accurately simulating molecular structures, aid in climate modeling by analyzing vast environmental data sets, and revolutionize financial modeling through complex optimization.

Key Quantum Algorithms

Research in quantum computing has already produced notable algorithms. Shors algorithm, for instance, can factor large numbers incredibly fast, a task thats time-consuming for classical computers. Grovers algorithm, on the other hand, can rapidly search unsorted databases, demonstrating a quadratic speedup over traditional methods.

The Road Ahead: Challenges and Promises

Despite its potential, quantum computing is still in its infancy. One of the major challenges is maintaining the stability of qubits. Known as quantum decoherence, this instability currently limits the practical use of quantum computers. Keeping qubits stable requires extremely low temperatures and isolated environments.

Additionally, error rates in quantum computations are higher than in classical computations. Quantum error correction, a field of study in its own right, is crucial for reliable quantum computing.

Quantum computing, though still in the developmental stage, stands at the forefront of a computational revolution. It promises to solve complex problems far beyond the reach of traditional computers, potentially reshaping entire industries and aspects of our daily lives. As research and technology advance, we may soon witness the unlocking of quantum computings full potential, heralding a new era of innovation and discovery.

DNA data storage emerges as a paradigm shift, harnessing the building blocks of life to revolutionize how we store information.

Unprecedented Storage Capabilities

DNAs storage density is unparalleled: one gram can store up to 215 petabytes of data. In contrast, traditional flash memory can hold only about 128 gigabytes per gram. This immense capacity could fundamentally change how we manage the worlds exponentially growing data.

Longevity and Reliability

DNA is not only dense but also incredibly durable. It can last thousands of years, far outstripping the lifespan of magnetic tapes and hard drives. Its natural error correction mechanisms, rooted in the double helix structure, ensure data integrity over millennia.

DNA for Computation and Beyond

Beyond storage, DNA holds potential for computation. Researchers are exploring DNA computing, where biological processes manipulate DNA strands to perform calculations. This could lead to breakthroughs in solving complex problems that are infeasible for conventional computers.

Challenges in Practical Implementation

Despite its promise, DNA data storage is not without challenges. Synthesizing and sequencing DNA is currently expensive and time-consuming. Researchers are working on methods to streamline these processes and reduce error rates, which are crucial for making DNA a practical medium for everyday data storage.

While quantum computing offers exponential speedups on specialized problems, its broader applicability and scalability remain uncertain. And both quantum and DNA computing currently require extremely low operating temperatures only possible with expensive equipment. They also consume large amounts of energy, though less than traditional data centers. However, both offer inherent data security advantages. Quantum computations cannot be copied, while DNA data storage is dense and hard to access. We may see hybrid deployments that apply these technologies to niche applications. For generalized workloads, traditional binary computing will likely dominate for the foreseeable future.

The integration of AI with quantum computing and DNA data storage represents a leap forward in computational capability.

AI and Quantum Computing: A Synergy for Complex Problems

AI algorithms can leverage the immense processing power of quantum computers to analyze large datasets more efficiently than ever before. This synergy could lead to breakthroughs in fields like drug discovery, where AI can analyze quantum-computed molecular simulations.

AI and DNA Data Storage: Managing Massive Databases

With DNAs vast storage capacity, AI becomes essential in managing and interpreting this wealth of information. AI algorithms can be designed to efficiently encode and decode DNA-stored data, making it accessible for practical use.

Ethical and Societal Implications

As highlighted in The Coming Wave by Mustafa Suleyman, the intersection of these technologies raises significant ethical questions. The use of genetic data in AI models, for instance, necessitates stringent privacy protections and considerations of genetic discrimination.

Looking Ahead: AI as the Conductor

The future sees AI not just as a tool but as a conductor, orchestrating the interplay between quantum computing and DNA data storage. This involves developing new algorithms tailored to the unique properties of quantum and DNA-based systems.

Google AI recently demonstrated a program that can autonomously detect and correct errors on a quantum processor, a major milestone. On the DNA computing front, researchers successfully stored a movie file and 100 books using DNA sequences. Ongoing studies also show promise in using DNA to manufacture nanoscale electronics for faster, denser computing. Quantum computing is enabling models of complex chemical reactions and biological processes. As costs decline, we could see exponential growth in synthesizing custom DNA and practical quantum computers.

Despite promising strides, there are still obstacles to realizing commercially viable DNA and quantum computing. Stability of quantum bits remains limited to milliseconds, far too short for practical applications. And while DNA sequencing costs have dropped, synthesis and assembly costs remain prohibitively high. There are also ethical pitfalls if without careful oversight, like insurers obtaining genetic data, or AI algorithms exhibiting biases. Job losses due to increasing automation present another societal challenge. Investments in retraining and social programs will be necessary to ensure shared prosperity.

Hybridized quantum-DNA computing could transform our relationship with information and usher in an era of highly personalized medicine and hyper-accurate simulations. It may even require overhauling information theory and rethinking how humans interact with advanced AI. But we must thoughtfully navigate disruptions to industries like finance and cryptography. Avoiding misuse will also require international cooperation to enact governance frameworks and design systems mindful of ethical dilemmas. With wise stewardship, hybrid computing could positively benefit humanity.

The convergence of quantum computing, DNA data storage, and AI represents an unprecedented phase change for processing power, memory, and information handling. To fully realize the potential, while mitigating risks, we must aggressively fund research and development at the intersection of these fields. The technical hurdles are surmountable through collaboration between the public and private sectors. But establishing governance and ethical frameworks ultimately requires a broad, multidisciplinary approach. If society rises to meet this challenge, we could enter an age of scientific wonders beyond our current imagination.

Check out these two books for a deeper dive:

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Breaking the Cold Barrier: The Cutting-Edge of Quantum Entanglement – SciTechDaily

Two groundbreaking studies have developed a method for controlling quantum entanglement in molecules, specifically calcium fluoride (CaF), using an optical tweezer array to create highly entangled Bell states. This advancement opens new avenues in quantum computing and sensing technologies.

Advancements in quantum entanglement with calcium fluoride molecules pave the way for new developments in quantum computing and sensing, utilizing controlled Bell state creation.

Quantum entanglement with molecules has long been a complex challenge in quantum science. However, recent advancements have emerged from two new studies. These studies showcase a method to tailor the quantum states of individual molecules, achieving quantum entanglement on demand. This development offers a promising platform for advancing quantum technologies, including computation and sensing. Quantum entanglement, a fundamental aspect of quantum mechanics, is vital for various quantum applications.

Ultracold molecules, with their intricate internal structure and long-lived rotational states, are ideal candidates for qubits in quantum computing and quantum simulations. Despite success in creating entanglement in atomic, photonic, and superconducting systems, achieving controlled entanglement between molecules has been a challenge. Now, Yicheng Bao and colleagues, along with Conner Holland and colleagues, have developed a method for the controlled quantum entanglement of calcium fluoride (CaF) molecules.

These studies utilized the long-range dipolar interaction between laser-cooled CaF molecules in a reconfigurable optical tweezer array. They successfully demonstrated the creation of a Bell state, a key class of entangled quantum state characterized by maximum entanglement between two qubits. The Bell state is crucial for many quantum technologies.

Both studies show that two CaF molecules located in neighboring optical tweezers and placed close enough to sense their respective long-range electric dipolar interaction led to an interaction between tweezer pairs, which dynamically created a Bell state out of the two previously uncorrelated molecules.

The demonstrated manipulation and characterization of entanglement of individually tailored molecules by Baoet al.and Hollandet al.paves the way for developing new versatile platforms for quantum technologies, writes Augusto Smerzi in a related Perspective.

References:

Dipolar spin-exchange and entanglement between molecules in an optical tweezer array by Yicheng Bao, Scarlett S. Yu, Loc Anderegg, Eunmi Chae, Wolfgang Ketterle, Kang-Kuen Ni and John M. Doyle, 7 December 2023, Science. DOI: 10.1126/science.adf8999

Entanglement with tweezed molecules by Augusto Smerzi, 7 December 2023, Science. DOI: 10.1126/science.adl4179

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Where AI and quantum computing meet – TechTarget

To a lot of IT leaders, quantum computers sound closer to science fiction than something that can be implemented in their data centers. But it's on the way; IBM last month introduced System Two, the first quantum computer that connects three processors to work together.

Last year's small steps on the quantum roadmap are turning into this year's bigger leaps. IBM charged Scott Crowder, vice president of quantum adoption, with the task of helping customers discover new uses for quantum computing, as well as the development of the software to accomplish those tasks. We asked Crowder to give CIOs a progress report on where quantum computing technology has advanced, and what it will take to get it into the enterprise.

For those who have heard of quantum computing but don't quite grok it, how does it differ from the classical computing that powers our laptops, phones and desktops?

Scott Crowder: It fundamentally uses a different information science. It's not like classical in the sense that we were doing classical information science before we invented digital computers. This is different in the way it does computation. Therefore, it's better at certain kinds of math than the computers of today are bad at and vice versa.

You could theoretically run anything on a universal quantum computer, but you wouldn't want to. You only want to run through quantum the things that classical computers aren't great at and what quantum computers have been proven to be good at. They leverage quantum mechanics, so it is like sci-fi come to life. It can do certain kinds of computation that we might never ever, ever be able to do using a classroom.

When will we see more mainstream adoption of quantum computers, and what will that look like?

Crowder: Before this year, you could argue that anything you could do with a quantum computer could be simulated classically. There was no point of doing the computation on a computer other than learning about its information science. But that's changed. This year, for the first time, you actually could run something on a quantum computer that you can't run on a classical simulator. It doesn't mean you can run anything on a quantum computer. It's the first couple of kinds of computations that you can actually get value out of a quantum computer as opposed to trying to simulate it.

Over the next couple of years, the usefulness or utility will continue to expand. Right now, there are limitations of how big a problem we can run because of the quality of the systems. But we're past the point where there's value in running a quantum computer. It doesn't mean there's business value yet, because problems tend to get bigger, they need to be integrated into your workflows, etc. But we don't think it's going to take until 2033 for other people to get business value.

In the 1940s, we weren't carrying around classical computers in our pocket and doing whatever it is we're doing on our phones. They were the initial use cases in scheduling. I think that's going to be true this decade [for quantum computers]. In the next decade when the systems get bigger and bigger and bigger -- and better and better and better -- you're going to see more and more use cases.

What will be the first use cases?

There are three kinds of math that quantum computers are getting better at.

One of them is around simulating nature. Materials, properties, physics, chemistry -- think of all the industrial as well as healthcare and life sciences chemistry-related things.

The second kind of math that quantum computers will be better at is a certain kind of complex structure in the data. The most famous algorithm, Shor's algorithm -- which all the nation-states are interested in -- is that kind of math. It does factoring: A times B equals C. A times B; regular old computers are good at giving you C. But given C, your computer is not good at figuring out what A and B were. Classical computers are not good at that kind of math, which is a good thing. If we don't have cryptography, we don't have a digital economy.

This is part of the discussion about quantum. If it falls into the hands of bad actors, we are in deep trouble. But this kind of math is also used in machine learning -- things like classification. It can help find fraud, better trial sites for clinical trials and better treatments when it's given a patient's health record data. There's a lot of interest in the industry of leveraging quantum computers in the near term for those kinds of problems.

The last kind of math, which is also interesting -- but for the second phase of the journey late this decade or in the next decade -- is around optimization. What takes me N tries on a regular old computer will take the square root of N tries on a quantum computer. So N equals 100, squared equals a factor of 10. There might be breakthroughs in that space as well. Examples might be portfolio optimization in financial services, risk management and logistics -- a whole bunch of things that people struggle with using regular computers to document today.

Quantum computers run somewhere down near zero degrees Kelvin. How are we going to solve the freezer problem? Put them in space?

Crowder: Unfortunately, space isn't cold enough.

We need to isolate the computing part of it from the rest of the universe because you're programmatically entangling these qubits with each other in a specific way. It can't be perfectly isolated (at absolute zero) because if it is perfectly isolated, we can't get them to do anything. It needs to be just connected enough to the rest of the universe so you can program it, but the rest of the universe can't muck with it. That's why either you need to keep it very, very, very, very cold -- like we do with our technology -- or you need to shoot laser beams at it [using a light-based approach] to take the entropy out. It's complicated, and it's not room temperature, no matter how you do it.

The good news is that there are commercial refrigeration techniques that are stable. They're low cost, and they're low energy compared to regular old computers -- like compared to a rack of electronics. These things seem extremely efficient. The refrigeration action is not that big of a problem. There are other problems in scaling them and getting the cost down, but the underlying technology is there.

Do you think that quantum computers will ever make it into the average enterprise data center? Or will it be reserved for specialized use only large enterprises will be able to afford?

Crowder: The infrastructure around quantum computers, I know, seems weird and different right now. But we've deployed them at Cleveland Clinic; we've deployed them in Germany, Japan and Canada. We have large data centers. I think in the near-term, like the next several years, the technology is so rapidly advancing that it probably doesn't make sense plopping them in enterprise data centers, because you're going to want the latest technology.

Cloud delivery has definite advantages because the software stack is evolving quickly and allows us to get new capabilities out to everybody at the same time and because the underlying hardware improves year by year by year. You're going to have quantum computers in enterprise data centers, whether that be [via] cloud provider or on premises. It's going to happen. It just doesn't make sense in the next several years.

Explain how quantum computing will intersect with AI. We have heard that quantum is not a match for generative AI.

Crowder: It's a mix. People usually use the word AI to mean the latest trend in AI.

Thinking of AI in a broader sense [than just generative AI], yes, there is a direct connection in terms of finding data patterns and complex structure problems, through machine learning or other means. Quantum will automatically do a better job of classification, as an example. That's not generative AI.

Generative AI is the latest stage in AI, and that is now the definition of AI for the next year or two until we come up with something else -- the next definition of AI. Generative AI has just a tenuous connection to quantum computing. There are people who are doing research and looking at leveraging quantum on neural networks as opposed to deep neural networks. I don't think anything has proven that quantum is going to be better in that space. But some researchers think that it might. Over the next couple of years, we'll find out the answer. But at this point I haven't seen any data that says definitively "yes." But I haven't seen any data that says definitively "no" either.

Don Fluckinger covers digital experience management, end-user computing, CPUs and assorted other topics for TechTarget Editorial. Got a tip? Email him here.

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The 3 Hottest Quantum Computing Stocks to Watch in 2024 – InvestorPlace

With the technology machinery running at full speed, forward-looking investors should consider the hottest quantum computing stocks for the prospect of robust profitability. To be sure, the pure-play ecosystem presents high risks. At the same time, the potential paradigm shift involved in quantum computers makes the bullish case incredibly enticing.

Essentially, the innovation empowers simultaneous multi-tiered data transmissions at a level that classical computers could never hope to achieve. Thats because the latter category is effectively a binary proposition. To solve a multi-tiered problem, it must first tackle the earlier iteration before resolving the subsequent challenges.

Quantum computers? They can address multiple problem sets, in part because the underlying qubit can exist in two physical states owing to the straight-up weird phenomenon of quantum mechanics at one time. Bottom line, it opens doors previously considered permanently closed, thus undergirding hot quantum stocks.

For full disclosure, the sector is very much young and there will almost certainly be growing pains. So, dont play in this sandbox if you cant handle volatility. Still, if you can accept the risk-reward profile, these hottest quantum computing stocks deserve a closer look.

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While internet and tech innovation juggernaut Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) may be a mature and thus boring idea, GOOG should help you on the road to the hottest quantum computing stocks that are proven viable. Analysts agree, rating shares a consensus strong buy with a $155.60 average price target. The high-side target lands at $160.

Through its Google Quantum AI team, Alphabet represents a major player in the research and development of superconducting quantum processors and software tools. So far, the company has achieved significant milestones in demonstrating its quantum supremacy. Enticingly, the quantum computing market could be worth $6.5 billion by 2028, representing a CAGR of 48.1% from 2023.

Although GOOG is unquestionably one of the hot quantum computing stocks, the main difference between parent Alphabet and the competition centers on the primary focus. Alphabet is more research oriented and it can afford to do so thanks to its robust financials.

In other words, its not one of the hottest quantum computing stocks based on upward mobility potential. However, you can trust Alphabet to be around in the next hundred years.

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Based in Canada, D-Wave Quantum (NYSE:QBTS) claims to be the worlds first company to sell computers that exploit quantum effects in their operation. It carries serious clout, with D-Waves early customers stemming from esteemed names like Alphabets Google and the University of Southern California. Analysts anticipate great things from QBTS, pegging it a unanimous strong buy with a $2.17 price target. That makes it one of the hottest quantum computing stocks based on implied growth.

Fundamentally, D-Wave is relevant to the discussion thanks to its specialty in building annealing quantum computers. These devices are specifically designed for solving so-called optimization problems, such as logistics, scheduling and financial modeling. Further, D-Waves processors are based on superconducting qubits arranged in a chimera topology. This distinct profile enables the company to tackle specific challenges at a much faster clip than classical computers.

Financially, the risk for QBTS is that its largely a narrative play. For example, shares trade at a trailing-year revenue multiple of 12.62X. Needless to say, thats sky high. However, with the projected growth of the underlying field, QBTS might be an opportunity based on where it might go.

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Headquartered in Berkeley, California, Rigetti Computing (NASDAQ:RGTI) develops quantum integrated circuits (ICs). An IC is basically a canvas of semiconductor wafers with millions of tiny resistors, capacitors and other components. Rigetti also develops a cloud platform called Forest that enables programmers to write with quantum algorithms. Analysts love RGTI, rating shares a unanimous strong buy with a $3. That also makes it one of the hottest quantum computing stocks based on implied shareholder profit.

As mentioned above, Rigetti lays a stake in the quantum field through its software platform. Beyond providing tools for algorithm design, Forest enables quantum circuit development and error correction. Therefore, it caters to both researchers and developers who may be working on different quantum applications. Further, the company aims to introduce practical applications in areas like materials science, chemistry and even financial modeling.

According to investment data aggregator Gurufocus, Rigettis projected future three-to-five-year revenue growth rate clocks in at 45.29%. That would be impressive if it comes true. However, investors should realize that right now, RGTI trades at 7.93X trailing-year sales, which is significantly overpriced. Still, if you anticipate a bright future, Rigetti could be one of the hot quantum computing stocks to consider.

On the date of publication, Josh Enomoto did not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

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