A group of Chinese academics claims to have made a breakthrough in addressing flaws in popular encryption techniques. They say that their new quantum code-breaking technique has the potential to minimize the size of a realistic quantum computer. Researchers in the United States are skeptical of the assertion.
According to the South China Morning Post, the team, led by Professor Long Guilu of Tsinghua University, claimed in a yet-to-be-published research that their novel algorithm could cut the scale of a practical quantum computer to 372 qubits.
This is even less than the “433 qubits and is nothing close to breaking the codes” of IBM’s Osprey.
The fundamental unit of quantum computing is the qubit. A qubit is the fundamental unit of quantum computing, just as a bit is the fundamental unit of data storage (which can be increased to kilobyte, megabyte, gigabyte, and so on).
In November of last year, IBM of New York introduced a new 433-qubit Quantum processor that has the potential to conduct complicated quantum computations far beyond the capabilities of any ordinary computer.
The ‘IBM Osprey’ processor contains the most qubits of any IBM quantum processor
The ‘IBM Osprey’ processor contains the most qubits of any IBM quantum processor, more than tripling the 127 qubits of the IBM ‘Eagle’ processor announced in 2021.
According to reports citing specialists, the latest assertion by Chinese scientists has disturbed senior security and quantum experts in the United States.
“It may not be correct, but it is not blatantly incorrect. “There’s also the lingering question of why the Chinese government didn’t classify this study,” wrote American cryptographer Bruce Schneier in a blog post.
The failure to clarify the advantage of quantum technology over classical computers, according to Scott Aaronson, director of the University of Texas at Austin’s quantum information center, was a major problem with the Chinese research paper.
“It seems to me that a miracle would be required for the approach here to yield any benefit at all, compared to just running the classical Schnorr’s algorithm on your laptop,” Aaronson wrote in a blog post.
