IBM Proves Real Quantum Advantage with 70 Logical Qubits in Just 15 Minutes—What’s Different This Time?

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Quantum Computing: 15 Minutes of Computation Shake Decades of Conventional Wisdom

A computation that is difficult to reproduce within a realistic timeframe—even with the world’s most powerful classical supercomputers and the latest algorithms. Researchers from IBM and the University of Chicago announced that they had performed it in just 15 minutes.

Taken at face value, “15 minutes” sounds brief. But behind that figure lies a problem the quantum computing industry has struggled to solve for years. Quantum computers are theoretically powerful, yet in real-world hardware, even tiny changes in temperature, electromagnetic noise, and control errors can easily undermine the results. The challenge was not simply calculating quickly—it was calculating accurately all the way to the end.

The key to this achievement lies not merely in assembling a large number of qubits. The true protagonists are the 70 logical qubits, designed to withstand errors.

Why Logical Qubits Matter More Than Physical Qubits

Ordinary physical qubits are extremely delicate. Unlike the bits in classical computers, which can maintain a 0 or 1 relatively stably, qubits can have their quantum states disrupted the moment they interact with the outside environment. This is known as decoherence.

For Quantum Computing to move from a possibility in the laboratory to a practical computational resource, systems must be designed with these errors in mind. That is why quantum error correction was developed.

• Physical qubits: Individual qubits that exist in actual hardware
• Logical qubits: Units created by combining multiple physical qubits and detecting and correcting errors so that they operate like a single, stable qubit
• Quantum error correction: A technology that protects quantum information by tracking and correcting errors that occur during computation without directly measuring the information itself

Put simply, if physical qubits are unstable individual musicians, logical qubits are more like an orchestra designed to preserve the entire piece even when some of its members make mistakes. Because carelessly measuring the quantum state itself can alter the information, error correction must be carried out in a far more complex way than in classical computing.

This announcement has drawn attention because the researchers used 70 such protected logical qubits in an actual computation—and also presented statistical reliability, demonstrating that the result was not merely a one-time, chance output.

The Standard for “Quantum Advantage” Is Changing

Earlier quantum advantage experiments mainly focused on demonstrating how quickly quantum devices could perform specific, artificial tasks. They were undoubtedly important technological milestones, but they often struggled to answer the question: “What can they actually be used for?”

The latest result from IBM and the University of Chicago shifts the discussion forward. The key point is not simply that a quantum circuit was executed, but the claim that a computation that the best existing classical approaches would struggle to reproduce in practical terms was performed reliably.

This suggests that Quantum Computing is moving into its next phase:

The competitiveness of quantum computers will depend not on a race to increase the number of qubits, but on how long they can perform computations stably using error-controlled logical qubits.

Of course, having 70 logical qubits does not mean that drug discovery, financial optimization, or codebreaking can immediately be solved routinely. Large-scale industrial problems will require more logical qubits, lower error rates, and more efficient algorithms.

Even so, this 15-minute computation marks an important boundary. It shows that quantum computing is moving beyond being merely a “noisy experimental device” and entering a stage where it can perform computations in a verifiable manner that classical computers cannot easily replicate.

Quantum Computing, the Secret Behind the Number 70: Not Qubits, but Logical Qubits

If a single qubit can represent 0 and 1 simultaneously, why do quantum computers still suffer from so many errors? The answer is simple yet difficult: quantum information is extraordinarily powerful, but at the same time extremely fragile.

The important number in the achievement by researchers from IBM and the University of Chicago is not simply “70.” The key point is that these were not 70 physical qubits, but 70 error-corrected logical qubits. This distinction determines the true significance of this Quantum Computing achievement.

Physical Qubits Are Fast but Easily Disturbed

Physical qubits, the fundamental units of quantum computers, are highly sensitive to their external environment. Even minute changes in temperature, electromagnetic noise, errors in control signals, or interactions with surrounding particles can cause a qubit’s quantum state to collapse.

This is known as decoherence. It is the phenomenon in which the superposition and entanglement states maintained by a qubit become mixed with the environment, causing the information needed for computation to disappear.

A bit in a classical computer can still be read relatively reliably even if its 0 or 1 fluctuates slightly. A qubit, by contrast, can be affected by the act of measurement itself, and it cannot be copied. Therefore, errors cannot be solved simply by copying values multiple times and backing them up, as in classical computers.

The greatest challenge in quantum computing is not creating qubits, but protecting them well enough to perform accurate computations for a sufficient length of time.

A Logical Qubit Is a Qubit Built for Stability

The technology developed to address this problem is Quantum Error Correction. It involves grouping multiple unstable physical qubits together and making the group function like a single, more stable qubit.

The unit created in this way is called a logical qubit.

A logical qubit is not the same concept as a single physical qubit. It is a computational unit designed to distribute information across multiple physical qubits and detect and correct errors if they occur in some of those qubits.

An easy analogy is as follows:

• Physical qubit: A candle that can easily be extinguished by the wind
• Logical qubit: A stable lighting system created by combining multiple candles with protective devices

Of course, the actual technology is far more complex. During error correction, the system must not directly read the values of the qubits; instead, it measures only auxiliary information indicating whether an error has occurred. Otherwise, the quantum state itself could collapse.

Why Do ‘70 Logical Qubits’ Matter?

Quantum hardware companies have long announced hundreds, and even more than 1,000, physical qubits. But having a large number of physical qubits does not automatically make useful Quantum Computing possible.

As errors accumulate, the reliability of the results rapidly declines as circuits become longer. Complex algorithms, in particular, require many operations and extensive entanglement. Without logical qubits that can be maintained stably, it is difficult to carry out a computation all the way to the end.

This achievement has drawn attention for the following reasons:

• It did not merely possess 70 qubits; it used them as error-corrected logical qubits
• It performed meaningful computations for approximately 15 minutes and presented the statistical reliability of the results
• It targeted computations that would be difficult to reproduce within a realistic timeframe using the latest classical algorithms

In other words, this result answers a question that is more important than the “qubit-count race.” The question is not how many qubits have been created, but how many qubits can be trusted and used for computation.

Still 70, but Already Starting from a Different Line

Seventy logical qubits do not mean that drug development, financial optimization, or codebreaking will immediately be transformed. Large-scale chemical simulations or computations powerful enough to threaten today’s public-key cryptography will likely require far more logical qubits.

Even so, this case is clearly a turning point. It shows that quantum computers are moving beyond noisy experimental equipment and into a stage where they can manage errors and perform reliable computations.

Going forward, the core of the Quantum Computing race will be determined not by the number of physical qubits alone, but by the following three questions:

1. How efficiently can more logical qubits be created?
2. How much can the number of physical qubits required for a single logical qubit be reduced?
3. Can these stable computational resources be connected to real-world industrial problems?

The number 70 may seem small. But in quantum computing, the two words “logical qubits” attached to that number elevate the technology’s potential into an entirely different dimension.

The Quantum Computing War Unfolding at Cryogenic Temperatures: What Quantum Hardware Really Looks Like

This computation did not run on an ordinary server in a data center. It required manipulating invisible quantum states with absolute precision in an environment demanding temperatures near absolute zero and highly precise electronic control.

The reason IBM and the University of Chicago’s demonstration of 70 logical qubits has drawn attention is not simply the algorithm. The key achievement lies in creating a hardware environment capable of running that algorithm reliably in the physical world, where errors occur constantly.

Computers Operating Hundreds of Degrees Below Zero

IBM has long been developing Quantum Computing systems based on superconducting qubits. In the superconducting approach, microscopic circuits made from materials such as aluminum or niobium are placed inside a dilution refrigerator, where the temperature is lowered to a level extremely close to absolute zero.

The reason such extreme cryogenic temperatures are necessary is simple: qubits are extraordinarily sensitive to their surroundings.

• Even a slight increase in thermal energy can disturb a quantum state.
• Electromagnetic noise and vibrations can distort computational results.
• The measurement process itself can affect the state of a qubit.
• Even a minute misalignment in control signals can introduce errors into quantum gate operations.

Transistors in classical computers can operate while tolerating a certain amount of noise. Qubits in quantum computers, by contrast, are exceptionally delicate. As a result, the area surrounding a quantum processor becomes a complex network of cooling equipment, shielding structures, high-frequency control lines, signal amplifiers, and measurement instruments.

Why ‘Logical Qubits’ Matter More Than Physical Qubits

A hardware system’s true competitiveness is difficult to judge by its qubit count alone. Even a large number of physical qubits is of limited use for lengthy computations if their error rates are too high.

That is why researchers combine multiple physical qubits to create a single logical qubit. This approach is designed to detect and correct errors in some of the physical qubits, allowing the group as a whole to operate like one stable qubit.

Put simply:

If physical qubits are unstable individual performers, a logical qubit is more like an orchestra that detects mistakes and compensates for them.

This process comes at a significant cost. Creating one stable logical qubit requires numerous physical qubits, sophisticated error-correction codes, and fast control and measurement systems. Therefore, securing 70 error-corrected logical qubits represents a far more complex achievement than simply building a “70-qubit chip.”

Precision Engineering for Controlling Invisible States

Quantum Computing hardware is not merely a matter of semiconductor chips. A real-world system must bring the following components together and make them work in harmony:

• Quantum processor: The core chip that implements the qubits and their connectivity
• Cryogenic cooling system: Equipment that suppresses thermal noise and maintains the superconducting state
• Microwave control equipment: Electronics that send precise operational signals to the qubits
• High-speed measurement and readout system: A system that reads computational results and error information
• Error-correction software: A layer that interprets measured error signals and protects the logical state

Error correction, in particular, blurs the boundary between hardware and software. Higher-quality physical qubits reduce the burden on error correction, faster control electronics make it possible to detect errors in time, and more efficient algorithms allow meaningful computations to run with a limited number of logical qubits.

A Challenge More Difficult Than ‘More Qubits’

In the quantum industry, qubit counts often make the headlines. But the real competition ahead will not be a simple race for bigger numbers. It will depend on how many reliable logical qubits can be maintained, and for how long.

What this achievement demonstrates is not merely the ability to pack more qubits into cryogenic equipment. It demonstrates the ability to manage errors in an environment where noise is unavoidable, perform extended computations, and ultimately prove the reliability of the results.

In the end, the battle over quantum hardware is not fought on the chip alone. Only when cooling technology, control electronics, error-correction mathematics, and software are completed together do quantum states truly become a computational resource.

Quantum Computing: From Quantum Supremacy to Quantum Utility—The Real Test Begins

Simply saying that a quantum computer has beaten a classical computer is not enough. If it has merely solved an artificial problem that no one would ever use in practice, it may be an impressive technology demonstration—but it is difficult to call it a tool capable of transforming an industry.

This is where Quantum Supremacy and Quantum Utility must be clearly distinguished.

• Quantum Supremacy means that quantum hardware has outperformed classical computers computationally on a specific task.
• Quantum Utility means that the computation can create real value in science, industry, or business.

Past quantum supremacy experiments focused primarily on problems such as sampling the output distributions of random quantum circuits. These tasks were well suited to demonstrating the performance of quantum hardware, but had limited practical applicability. They could prove that the task was “extremely difficult for classical computers,” but they struggled to provide a clear answer to the question, “So what can it actually be used for?”

This is precisely why the demonstration involving 70 error-corrected logical qubits by researchers from IBM and the University of Chicago has drawn attention. The researchers not only performed, in about 15 minutes, a computation that would be difficult for classical algorithms to reproduce within a realistic timeframe, but also sought to verify the statistical reliability of the results. They were not simply running a complex circuit once; they were trying to show that error-corrected logical qubits can function as a reliable computational resource.

Of course, this does not mean that they have immediately solved drug development, logistics optimization, or financial analysis. Quantum Computing is still likely to show an advantage only on a very limited range of problems. In particular, it remains necessary to verify whether quantum algorithms are clearly superior to classical methods and whether they are economically viable even after accounting for data input and output, as well as the cost of error correction.

Even so, the direction is clear. The industry’s question is shifting from “Can quantum computers become faster than classical computers?” to “On which real-world problems, how reliably, and with how much cost reduction and performance improvement can they deliver?”

The real test is not the number of logical qubits itself. It is whether those qubits can solve real problems that are difficult for classical computers in a repeatable and verifiable manner. If quantum supremacy was the starting line, quantum utility is now the most important finish line Quantum Computing must cross.

Quantum Computing: The Real Contest Begins After the Milestone

Seventy error-corrected logical qubits are undoubtedly a historic milestone. The fact that IBM and researchers at the University of Chicago performed a computation in roughly 15 minutes that would be practically difficult to reproduce using classical algorithms demonstrates that quantum computers may be capable of moving beyond the realm of mere experimental devices.

But this number does not mean that drug design, RSA decryption, or power-grid optimization can now be solved immediately. The real competition in Quantum Computing is only just beginning.

What Matters More Than the Number of Logical Qubits

A logical qubit is a more stable computational unit created by combining multiple physical qubits to monitor and correct errors. In other words, “70 logical qubits” does not simply mean possessing 70 qubits. It represents the achievement of preserving quantum states that are vulnerable to noise while making computational results reliable.

However, real-world industrial problems require a far greater scale.

• Drug and materials simulation requires the precise handling of the electronic structures of complex molecules. As molecular size and accuracy requirements increase, more logical qubits and longer computation times become necessary.
• Cryptanalysis requires, most notably, Shor’s algorithm for factoring large integers. This remains a goal considerably beyond the current level of several dozen logical qubits.
• Power-grid and logistics optimization cannot be solved automatically simply by increasing the number of qubits. The problems must first be reformulated to suit quantum algorithms, while the roles of classical and quantum computers must also be allocated efficiently.

Ultimately, the key question is not whether “70 have been built,” but whether this system can be scaled to hundreds or thousands of logical qubits.

The Greatest Challenge: The Scalability of Error Correction

In quantum computing, error correction is not an optional feature for improving performance; it is an essential requirement. Physical qubits can easily lose their states due to heat, electromagnetic interference, and minute errors in control signals. As a result, creating a single stable logical qubit requires numerous physical qubits, along with complex error-detection and correction procedures.

This process comes with substantial costs.

1. Improving physical qubit quality
   The error rate of each qubit must be reduced so that fewer resources are required for error correction.

2. Making error-correction codes more efficient
   The same level of reliability must be achieved with fewer physical qubits.

3. Enhancing the precision of control systems
   The electronics, cooling systems, and software required to control and measure vast numbers of qubits simultaneously must all advance together.

4. Validating useful algorithms
   Algorithms with genuine industrial value must demonstrate that they outperform classical methods on error-corrected quantum hardware.

For this reason, the competition ahead is unlikely to be a simple race to increase the number of physical qubits. Instead, it will likely center on a combination of error rates, the number of logical qubits, computational depth, and verifiability.

A Major Technical Deal, but a Long Game for the Market

This achievement is a major technological event. It is especially significant because the discussion around quantum advantage is moving away from artificial sampling tasks and toward reliable, error-corrected computation.

From a market perspective, however, it should be interpreted with caution. In the near future, Quantum Computing is more likely to prove its value first in limited fields—such as chemical simulation, specialized optimization, and cryptography research—rather than becoming a general-purpose platform immediately adopted by every company, as cloud computing and AI have been.

What companies should focus on now is not exaggerated expectation, but the following questions:

• Does our industry have difficult problems that are worth solving with quantum computing?
• Would classical supercomputing or a hybrid approach be sufficient?
• When should we begin preparing for security risks such as the transition to post-quantum cryptography?
• Do we have the data and specialized talent needed to take advantage of quantum technology when it matures?

Seventy logical qubits are not the finish line. They are closer to a starting signal—proof that quantum computers can begin moving toward real-world problems. Technologically, this is a giant leap forward. But the contest in the market will unfold on a much longer timeline.