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The race for quantum computing dominance is heating up, creating big opportunities for related quantum computing stocks.

Right now, China and the U.S. appear to be neck and neck. In fact, GlobalData Principal Analyst Isabel Al-Dhahir, said:

In 2024, the two countries stand almost neck-and-neck, albeit with very different strategies. Private companies lead the way in the U.S., while in China, expertise is increasingly concentrated within state institutions.

So far, the U.S. committed about $3 billion in funding for quantum projects. Another $1.2 billion came from the National Quantum Computing Initiative. And even more money is likely to flow in from the Pentagon. Meanwhile, China has committed about $15 billion.

We also have to consider that quantum computing often lands on theU.S. critical and emerging technologies list, which adds technologies that could potentially impact national security with its ability to solve complex problems.

With the race for dominance only set to heat up, here are just a few top quantum computing stocks you may want to invest in today.

Source: Amin Van / Shutterstock.com

After dropping from about $15.50 to less than $10,IonQ(NYSE:IONQ) is starting to bounce.

Last trading at $9.95, Id like to see it initially retest $15.50, and eventually $21.60, as quantum computing stocks start to gain momentum.

While its EPS loss of 20 cents missed by three cents, revenues of $6.1 million were up 60.1% year over year. Analysts were looking for a loss of 17 cents on revenue of $5.76 million. Also, its full-year 2023 revenue of $22 million andbookings of $65.1 million was up 98% and 166%,respectively, year over year.

For 2024, IONQ expects revenue of $37 million to $41 million, which is year-over-year growth of 68.2% and 86.4%, respectively.

Moving forward, the company could do even better with the artificial intelligence boom.By shifting AI workloads to our increasingly powerful quantum computers, IonQ can help address the worlds next great computing challenge, says CEO Peter Chapman.

Source: Boykov / Shutterstock.com

We can also look at quantum computing stocks likeD-Wave Quantum(NYSE:QBTS).

When I first mentioned QBTS on February 1, it traded at around 90 cents. Today, after hitting a high of $2.44, its at $2.01 and still a strong opportunity.

Helping, QBTS and Zapata AI, a generative artificial intelligence software company, announced a collaboration to combine quantum computing and generative AI. And if all works out well, it could create a sizable profit opportunity for all involved.

Dr. Alan Baratz, CEO of D-Wave, said:

Our agreement with Zapata AI marks a significant step toward realizing the potential of combining two of todays most transformative technologies generative AI and quantum computing to help tackle our societys most computationally complex problems Our companies share a common vision to accelerate exploration, adoption and commercial use of emerging technologies to fuel innovation and transformation. Together, we believe D-Wave and Zapata AI will usher in the commercial era of quantum machine learning.

Source: Shutterstock

Or, if youd rather diversify at a low cost, theres theDefiance Quantum ETF(NYSEARCA:QTUM), which has been in a strong uptrend since November. From its current price of $61.38, Id eventually like to see the QTUM ETF race to about $80 a share.

With an expense ratio of 0.40%, the ETF is exposed to companies at the forefront of machine learning, quantum computing, cloud computing and other transformative computing technologies, as noted by DefianceETFs.com. It also tracks the BlueStar Quantum Computing and Machine Learning Index, with about 71 holdings.

Some of its top holdings includeNvidia(NASDAQ:NVDA),Marvell Technology(NASDAQ:MRVL) andAdvanced Micro Devices(NASDAQ:AMD).

Whats nice about this ETF is that we can buy 100 shares of it for about $6,100 at the moment. All while gaining exposure to some of the biggest tech companies in the world. Thats a lot less expensive than buying 100 shares of NVDA for $9,000 a pop, which is just one of the funds top 71 holdings.

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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Hot Stocks: The 3 Best Opportunities for Investing in Quantum Computing - InvestorPlace

In 1940, one genius completed a puzzle in just 20 minutes that shouldve taken him a million years to solve.

His name is Alan Turing.

You may be familiar with Turings story from the 2014 movie The Imitation Game. Benedict Cumberbatch earned a Best Actor nomination for his portrayal of the genius.

If you saw the movie, you know Turing is considered the father of computer science and one of the most important code-breakers of all time.

When World War II broke out in 1939, Turing was assigned to breaking encrypted messages from the Germans.

This was no easy task, as the Germans held the most sophisticated encryption machine at the time, the Enigma.

Credit: ironypoisoning, via Wikimedia Commons

The Enigmas encryption was far greater than anything before its time.

It became clear cracking the code to the Enigma was going to require an even smarter machine. So Turing built one.

It took Turing and his team nearly a year to build a machine that was powerful enough to decrypt Enigmas messages. It was known as the Bombe, and it helped the Allies crack 84,000 Enigma-coded messages each month.

Decrypting messages went from taking potentially a million years by hand to just 20 minutes.

Heres why were telling you this

Last year, IBM debuted its 1,121-qubit Condor processor. Its the most advanced quantum computer to date.

Quantum computers such as the Condor can perform billions of calculations per second. So they can find patterns in data that are invisible to classic computers. They have the potential to revolutionize everything from medicine to engineering.

Many crypto skeptics believe bitcoins defenses will be broken as quantum computers get more powerful And it will share the same fate as the Enigma.

But theres one key mistake that made the Enigma almost certain to fail. And bitcoin doesnt share that flaw

The reason Enigma failed is because once it was built its creators never improved it.

It was only a matter of time before those looking to crack the Enigma would develop better technology.

While the Enigma stood dead in its tracks, Turing made improvements to his decryption machine every day until it became more powerful than the Enigma.

The lesson here is that you always need to push forward. If you dont, the competition will close the gap.

Its a lesson bitcoin developers took to heart.

The bitcoin network was developed with quantum computing mechanics in mind. To combat this, the difficulty to mine the next bitcoin block increases as more computing power comes online.

Take a look at the chart below. It shows the hash power, or computing power, of the bitcoin mining network.

Every year, the computing power that goes into mining a bitcoin block (in other words, processing a transaction) increases.

As mentioned above, IBM released its 1,121-qubit Condor processor in December 2023.

According to the University of Sussex, youd need a quantum computer with 1.9 billion qubits of processing power to break the bitcoin network.

This means youd need 1.7 million of the most powerful quantum computers built today.

IBM believes it can get to 10,000 qubits by 2026. Even then, itll need nearly 200,000 of these machines to crack the bitcoin network.

How long will it take for companies like IBM to build this many machines? Years? Decades?

Plus, if you want to attack the bitcoin network, you need to control 51% of the networks computing power.

Today, one of the best bitcoin miners, the Bitmain Antminer S19 Pro, will cost you $2,200. This machine can generate 110 terahashes per second (TH/s).

The bitcoin network uses roughly 384.33 million TH/s. That means youd need 1.78 million Antminer S19 Pros to overtake the network. Thats over $3.9 billion.

Youd also need to pay for a storage facility to set up these machines. And youd need to coordinate a massive amount of electricity to the building. These machines consume roughly 3,250 watts per hour.

At an average cost of 23 cents per kilowatt, that would cost about $32 million per day.

But even if you spend nearly $4 billion to take over the bitcoin network, youd never be able to extract all $500 billion of its value. The moment that you overtake the network, its value would race to zero.

Its like pirates buying a $4 billion battleship to commandeer a cargo ship carrying $400 million worth of goods. Its not worth the effort.

And thats why the bitcoin network is considered antifragile. It would cost you more to take over the network than the network would be worth.

Every year that bitcoin exists, it moves further and further out of reach of attackers.

So while you might need 1.9 billion qubits of quantum computing processing power to break the blockchain today Youll likely need 3 billion qubits of processing power next year. And 4 billion the following year and so on.

Thats what separates the fatal flaw of the Enigma from the security of the bitcoin network.

When technology like the Enigma just stands still, competition surpasses you.

Bitcoin, on the other hand, is constantly improving its security. Its never satisfied with where its at. Even if it appears to be unbreakable today, it will still be stronger tomorrow.

So when you see quantum computers gaining ground, know that bitcoin isnt standing still.

Thats why the advances of quantum computers arent a threat to bitcoin for the foreseeable future.

So dont let quantum computing fears stop you from owning a stake in one of the worlds greatest assets.

Palm Beach Research Group

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Why Quantum Computers Will Never Break Bitcoin - Palm Beach Research Group

Enlarge / Quantinuum's H2 "racetrack" quantum processor.

Quantinuum

Today's quantum computing hardware is severely limited in what it can do by errors that are difficult to avoid. There can be problems with everything from setting the initial state of a qubit to reading its output, and qubits will occasionally lose their state while doing nothing. Some of the quantum processors in existence today can't use all of their individual qubits for a single calculation without errors becoming inevitable.

The solution is to combine multiple hardware qubits to form what's termed a logical qubit. This allows a single bit of quantum information to be distributed among multiple hardware qubits, reducing the impact of individual errors. Additional qubits can be used as sensors to detect errors and allow interventions to correct them. Recently, there have been a number of demonstrations that logical qubits work in principle.

On Wednesday, Microsoft and Quantinuum announced that logical qubits work in more than principle. "We've been able to demonstrate what's called active syndrome extraction, or sometimes it's also called repeated error correction," Microsoft's Krysta Svoretold Ars. "And we've been able to do this such that it is better than the underlying physical error rate. So it actually works."

Microsoft has its own quantum computing efforts, and it also acts as a service provider for other companies' hardware. Its Azure Quantum service allows users to write instructions for quantum computers in a hardware-agnostic manner and then run them on the offerings of four different companies, many of them based on radically different hardware qubits. This work, however, was done on one specific hardware platform: a trapped-ion computer from a company called Quantinuum.

We covered the technology behind Quantinuum's computers when the company was an internal project at industrial giant Honeywell. Briefly, trapped ion qubits benefit from a consistent behavior (there's no device-to-device variation in atoms), ease of control, and relative stability. Because the ions can be moved around easily, it's possible to entangle any qubit with any other in the hardware and to perform measurements on them while calculations are in progress. "These are some of the key capabilities: the two-qubit gate fidelities, the fact that you can move and have all the connectivity through movement, and then mid-circuit measurement," Svore told Ars.

Quantinuum's hardware does lag in one dimension: the total number of qubits. While some of its competitors have pushed over 1,000 qubits, Quantinuum's latest hardware is limited to 32 qubits.

That said, a low error rate is valuable for this work. Logical qubits work by combining multiple hardware qubits. If each of those qubits has a high enough error rate, combining them increases the probability that errors will crop up more quickly than they can be corrected. So the error rate has to be below a critical point for error correction to work. And existing qubit technologies seem to be at that pointalbeit barely. Initial work in this area had either barely detected the impact of error correction or had simply registered the errors but not corrected them.

As the draft of a new manuscript describing this work puts it, "To the best our knowledge, none of these experiments have demonstrated logical error rates better than the physical error rates."

Microsoft is also well-positioned to be doing this work. Its role requires it to translate generic quantum code into the commands needed to be performed on Quantinuum's hardwareincluding acting as a compiler provider. And in at least part of this work, it used this knowledge to specifically optimize the code to cut down on the time spent moving ions around.

The work involved three experiments. In the first, the researchers formed a logical qubit with seven information-holding hardware qubits and three ancillary qubits for error detection and correction. The 32 qubits in the hardware allowed two of these to be created; they were then entangled, which required two gate operations. Errors were checked for during the initialization of the qubits and after the entanglement. These operations were performed thousands of times to derive error rates.

On individual hardware qubits, the error rate was 0.50 percent. When error correction was included, this rate dropped to 0.05 percent. But the system could do even better if it identified readings that indicated difficult-to-interpret error states and discarded those calculations. Doing the discarding dropped the error rate to 0.001 percent. These instances were rare enough that the team didn't have to throw out a significant number of operations, but they still made a huge difference in the error rate.

Next, the team switched to what they call a "Carbon code," which requires 30 physical qubits (24 data and six correction/detection), meaning the hardware could only host one. But the code was also optimized for the hardware. "Knowing the two-qubit gate fidelities, knowing how many interaction zones, how much parallelism you can have, we then optimize our error-correction codes for that," Svore said.

The Carbon code also allows the identification of errors that are difficult to correct properly, allowing those results to be discarded. With error correction and discarding of difficult-to-fix errors, the error rate dropped from 0.8 percent to 0.001 percenta factor of 800 difference.

Finally, the researchers performed repeated rounds of gate operations followed by error detection and correction on a logical qubit using the Carbon code. These again showed a major improvement thanks to error correction (about an order of magnitude) after one round. By the second round, however, error correction had only cut the error rate in half, and any effect was statistically insignificant by round three.

So while the results tell us that error correction works, they also indicate that our current hardware isn't yet sufficient to allow for the extended operations that useful calculations will require. Still, Svore said, "I think this marks a critical milestone on the path to more elaborate computations that are fault tolerant and reliable" and emphasized that it was done on production commercial hardware rather than a one-of-a-kind academic machine.

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Quantum error correction used to actually correct errors - Ars Technica

Researchers from the Institute of Industrial Science, The University of Tokyo have solved a foundational problem in transmitting quantum information, which could dramatically enhance the utility of integrated circuits and quantum computing. Credit: Institute of Industrial Science, The University of Tokyo

Quantum electronics represents a significant departure from conventional electronics. In traditional systems, memory is stored in binary digits. In contrast, quantum electronics utilizes qubits for storage, which can assume various forms, including electrons trapped in nanostructures known as quantum dots. Nonetheless, the ability to transmit information beyond the adjacent quantum dot poses a substantial challenge, thereby limiting the design possibilities for qubits.

Now, in a study recently published in Physical Review Letters, researchers from the Institute of Industrial Science at the University of Tokyo are solving this problem: they developed a new technology for transmitting quantum information over perhaps tens to a hundred micrometers. This advance could improve the functionality of upcoming quantum electronics.

How can researchers transmit quantum information, from one quantum dot to another, on the same quantum computer chip? One way might be to convert electron (matter) information into light (electromagnetic wave) information: by generating lightmatter hybrid states. Previous work has been incompatible with the one-electron needs of quantum information processing. Improving on high-speed quantum information transmission in a way that is more flexible in design and is compatible with the semiconductor fabrication tools that are currently available was the goal of the research teams study.

In our work, we couple a few electrons in the quantum dot to an electrical circuit known as a terahertz split-ring resonator, explains Kazuyuki Kuroyama, lead author of the study. The design is simple and suitable for large-scale integration.

Previous work has been based on coupling the resonator with an ensemble of thousands to tens of thousands of electrons. In fact, the coupling strength is based on the large size of this ensemble. In contrast, the present system confines only a few electrons, which is suitable for quantum information processing. Nevertheless, both electrons and terahertz electromagnetic waves are confined to an ultra-small area. Therefore, the coupling strength is comparable in strength to that of many-electron systems.

Were excited because we use structures that are widespread in advanced nanotechnology and are commonly integrated into semiconductor manufacturing to help solve a practical quantum information transmission problem, says Kazuhiko Hirakawa, senior author. We also look forward to applying our findings to understanding the fundamental physics of lightelectron coupled states.

This work is an important step forward in solving a previously vexing problem in transmitting quantum information that has limited applications of laboratory findings. In addition, such lightmatter interconversion is regarded as one of the essential architectures for large-scale quantum computers based on semiconductor quantum dots. Because the researchers results are based on materials and procedures that are common in semiconductor manufacturing, practical implementation should be straightforward.

Reference: Coherent Interaction of a Few-Electron Quantum Dot with a Terahertz Optical Resonator by Kazuyuki Kuroyama, Jinkwan Kwoen, Yasuhiko Arakawa and Kazuhiko Hirakawa, 9 February 2024, Physical Review Letters. DOI: 10.1103/PhysRevLett.132.066901

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Redefining Quantum Communication: Researchers Have Solved a Foundational Problem in Transmitting Quantum ... - SciTechDaily

In a significant advancement for quantum computing, Microsoft and Quantinuum have announced a major milestone which might represent the most stable quantum capabilities observed so far. Microsofts approach allows a quantum computer to self-correct, achieving an unprecedented level of reliability with no errors across thousands of tests.

The essence of quantum computing comes from its basic unit, the qubit, which offers the potential to handle complex calculations at speeds incomprehensible to traditional computers. However, qubits are also prone to errors due to environmental factors. To address this, error-correction techniques are essential, and Microsoft and Quantinuum have made headway in this domain.

Microsoft has developed an innovative algorithm capable of correcting qubit-generated errors in Quantinuums system, resulting in a dramatically reduced error rate. By converting 30 qubits into four highly reliable logical qubits, not only did they demonstrate a notable decline in error occurrence, but the logical qubits even had the resilience to correct any arising issues without being compromised.

This advancement, while impressive, is only a stepping stone, as the real-world applications of quantum computing will require over a hundred logical qubits. The outcomes of this experiment are yet to be scrutinized by the larger scientific community, but they inject optimism into quantum research, indicating that practical quantum computing is drawing closer.

This collaboration between Microsoft and Quantinuum is pushing the boundaries of the quantum ecosystem and may soon revolutionize fields from scientific research to energy security, embodying a landmark in the evolution of computing technology.

Quantum Computing: Industry Insights and Market Forecasts

Quantum computing represents a transformative leap in computational capabilities, offering the promise of solving complex problems far beyond the reach of current supercomputers. This emerging industry is characterized by its potential to revolutionize various fields, including cryptography, materials science, pharmaceuticals, and finance, by performing calculations at unprecedented speeds.

Market forecasts suggest that the quantum computing industry is on a trajectory of rapid expansion. According to recent research, the global quantum computing market is expected to grow substantially over the next decade, attributed to increased investments from both private and public sectors, advancements in quantum algorithms and error correction, and a growing demand for solving complex computational problems. The financial investment in quantum computing research and development is significant, with tech giants and startups alike racing to achieve breakthroughs that could grant them an edge in this potentially lucrative market.

Overcoming Industry Challenges

Despite the significant advancements made by Microsoft and Quantinuum, the quantum computing industry faces multiple challenges. One of the most prominent is achieving scalable error correction, which is necessary to build practical and reliable quantum computers. The successful error-correcting algorithm developed by Microsoft addresses one part of this complex puzzle, yet scaling up to a large number of logical qubits without incurring prohibitive costs or excessive complexity remains a technical hurdle.

Temperature control is another issue, as quantum processors need to be kept at extremely low temperatures to minimize environmental disturbances. Additionally, the coherence time, or the duration for which qubits maintain their quantum state, is a key factor that needs to be extended to allow for more complex and extended computations.

Protecting quantum information against decoherence and maintaining robustness against errors are critical focus areas for researchers. As the technology matures, the industry will also have to tackle broader issues such as standardization, establishing quantum-safe security protocols, and developing a skilled workforce capable of pushing the boundaries of quantum computer science.

Revolutionizing Fields and Future Potential

The potential applications of quantum computing are vast, and the improvements in error correction shown by Microsoft and Quantinuum are significant steps towards unlocking this potential. In healthcare, for example, quantum computing could enable the design of more effective drugs by accurately simulating complex molecules. In finance, quantum algorithms could optimize portfolios by evaluating countless scenarios simultaneously. For climate and energy, quantum computers may model new materials for better solar cells or more efficient batteries, contributing to sustainable energy solutions.

With industry leaders like Microsoft and their partners demonstrating a more stable quantum future, the practical application within these fields becomes increasingly feasible, ushering in a new era of innovation and discovery. The benefits of quantum computing will only be fully realized once the technology becomes widely accessible, leading to a paradigm shift in the way we approach and solve the worlds most challenging problems.

For further reading and staying updated on the progress of the quantum computing industry, you may wish to visit the websites of leading tech companies and research institutions. Links to a few of them are provided below:

IBM Google Intel Honeywell

Please keep in mind when exploring these resources that the quantum computing landscape is rapidly evolving, and new advancements or collaborations could emerge at any point.

Leokadia Gogulska is an emerging figure in the field of environmental technology, known for her groundbreaking work in developing sustainable urban infrastructure solutions. Her research focuses on integrating green technologies in urban planning, aiming to reduce environmental impact while enhancing livability in cities. Gogulskas innovative approaches to renewable energy usage, waste management, and eco-friendly transportation systems have garnered attention for their practicality and effectiveness. Her contributions are increasingly influential in shaping policies and practices towards more sustainable and resilient urban environments.

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Quantum Computing Leaps Forward with Groundbreaking Error Correction - yTech