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Showing posts with label fault-tolerant quantum computing. Show all posts

Quantum Error Correction Moves From Theory to Practical Breakthroughs

Quantum computing’s biggest roadblock has always been fragility: qubits lose information at the slightest disturbance, and protecting them requires linking many unstable physical qubits into a single logical qubit that can detect and repair errors. That redundancy works in principle, but the repeated checks and recovery cycles have historically imposed such heavy overhead that error correction remained mainly academic. Over the last year, however, a string of complementary advances suggests quantum error correction is transitioning from theory into engineering practice. 

Algorithmic improvements are cutting correction overheads by treating errors as correlated events rather than isolated failures. Techniques that combine transversal operations with smarter decoders reduce the number of measurement-and-repair rounds needed, shortening runtimes dramatically for certain hardware families. Platforms built from neutral atoms benefit especially from these methods because their qubits can be rearranged and operated on in parallel, enabling fewer, faster correction cycles without sacrificing accuracy.

On the hardware side, researchers have started to demonstrate logical qubits that outperform the raw physical qubits that compose them. Showing a logical qubit with lower effective error rates on real devices is a milestone: it proves that fault tolerance can deliver practical gains, not just theoretical resilience. Teams have even executed scaled-down versions of canonical quantum algorithms on error-protected hardware, moving the community from “can this work?” to “how do we make it useful?” 

Software and tooling are maturing to support these hardware and algorithmic wins. Open-source toolkits now let engineers simulate error-correction strategies before hardware commits, while real-time decoders and orchestration layers bridge quantum operations with the classical compute that must act on error signals. Training materials and developer platforms are emerging to close the skills gap, helping teams build, test, and operate QEC stacks more rapidly. 

That progress does not negate the engineering challenges ahead. Error correction still multiplies resource needs and demands significant classical processing for decoding in real time. Different qubit technologies present distinct wiring, control, and scaling trade-offs, and growing system size will expose new bottlenecks. Experts caution that advances are steady rather than explosive: integrating algorithms, hardware, and orchestration remains the hard part. 

Still, the arc is unmistakable. Faster algorithms, demonstrable logical qubits, and a growing ecosystem of software and training make quantum error correction an engineering discipline now, not a distant dream. The field has shifted from proving concepts to building repeatable systems, and while fault-tolerant, cryptographically relevant quantum machines are not yet here, the path toward reliable quantum computation is clearer than it has ever been.

IBM’s 120-Qubit Quantum Breakthrough Edges Closer to Cracking Bitcoin Encryption

 

IBM has announced a major leap in quantum computing, moving the tech world a step closer to what many in crypto fear most—a machine capable of breaking Bitcoin’s encryption.

Earlier this month, IBM researchers revealed the creation of a 120-qubit entangled quantum state, marking the most advanced and stable demonstration of its kind so far.

Detailed in a paper titled “Big Cats: Entanglement in 120 Qubits and Beyond,” the study showcases genuine multipartite entanglement across all 120 qubits. This milestone is critical in the journey toward fault-tolerant quantum computers—machines powerful enough to run algorithms that could potentially outpace and even defeat modern cryptography.

“We seek to create a large entangled resource state on a quantum computer using a circuit whose noise is suppressed,” the researchers wrote. “We use techniques from graph theory, stabilizer groups, and circuit uncomputation to achieve this goal.”

This achievement comes amid fierce global competition in the quantum computing race. IBM’s progress surpasses Google Quantum AI’s 105-qubit Willow chip, which recently demonstrated a physics algorithm faster than any classical computer could simulate.

In the experiment, IBM scientists utilized Greenberger–Horne–Zeilinger (GHZ) states, also known as “cat states,” a nod to Schrödinger’s iconic thought experiment. In these states, every qubit exists simultaneously in superposition—both zero and one—and if one changes, all others follow, a phenomenon impossible in classical physics.

“Besides their practical utility, GHZ states have historically been used as a benchmark in various quantum platforms such as ions, superconductors, neutral atoms, and photons,” the researchers noted. “This arises from the fact that these states are extremely sensitive to imperfections in the experiment—indeed, they can be used to achieve quantum sensing at the Heisenberg limit.”

To reach the 120-qubit benchmark, IBM leveraged superconducting circuits and an adaptive compiler that directed operations to the least noisy regions of the chip. They also introduced a method called temporary uncomputation, where qubits that had completed their tasks were briefly disentangled to stabilize before being reconnected.

The performance was evaluated using fidelity, which measures how closely a quantum state matches its theoretical ideal. While a fidelity of 1.0 represents perfect accuracy and 0.5 marks confirmed full entanglement, IBM’s experiment achieved a score of 0.56, verifying that all qubits were coherently connected in one unified system.

Direct testing of such a vast quantum state is computationally unfeasible—it would take longer than the age of the universe to analyze every configuration. Instead, IBM used parity oscillation tests and Direct Fidelity Estimation, statistical techniques that sample subsets of the system to verify synchronization among qubits.

Although IBM’s current system does not yet threaten existing encryption, this progress pushes the boundary closer to a reality where quantum computers could challenge digital security, including Bitcoin’s defenses.

According to Project 11, a quantum research group, roughly 6.6 million BTC—worth about $767 billion—could be at risk from future quantum attacks. This includes coins believed to belong to Bitcoin’s creator, Satoshi Nakamoto.

“This is one of Bitcoin’s biggest controversies: what to do with Satoshi’s coins. You can’t move them, and Satoshi is presumably gone,” Project 11 founder Alex Pruden told Decrypt. “So what happens to that Bitcoin? It’s a significant portion of the supply. Do you burn it, redistribute it, or let a quantum computer get it? Those are the only options.”

Once a Bitcoin address’s public key becomes visible, a sufficiently powerful quantum system could, in theory, reconstruct it and take control of the funds before a transaction is confirmed. While IBM’s 120-qubit experiment cannot yet do this, it signals steady advancement toward that level of capability.

With IBM aiming for fault-tolerant quantum systems by 2030, and rivals like Google and Quantinuum pursuing the same goal, the quantum threat to digital assets is no longer a distant speculation—it’s a growing reality.