Quantum Factorization Records Surpassed by Canine Named Scribble - Our Attempt to Follow Suit
In a surprising turn of events, a team of scientists, led by cryptology experts Peter Gutmann and Stephan Neuhaus, have shaken up the world of quantum computing with their unconventional approach to factorization.
The team's method, which they refer to as a "sleight of hand," revolves around the process of factorization - where prime numbers are multiplied together to get a specific number. This process is crucial in the field of cryptology, particularly in the security of digital communications.
In their study, available via the Cryptology ePrint Archive, the team employs an unusual cast of characters: a dog named Scribble, an abacus, and old computers. Scribble, who is also known as a canine computer, was instrumental in the factorization process, barking three times to find the number of factors for both 15 and 21. Llywelyn 'Clue' Orpheus Carpineti, another dog in the team, was able to factorize the number 187 by barking 11 times.
However, the team didn't stop at simple numbers. They attempted to factorize the RSA-2048 number, a large number used in cryptography, which has 617 decimal digits. While they claim to have succeeded, they point out that there was "sleight of hand" involved, suggesting hidden assumptions or unrealistic conditions that may have exaggerated the performance claims of quantum factoring experiments.
The team's paper challenges quantum factorization records, but they also highlight the potential challenges in overcoming major obstacles before quantum computing will be at a useful level. The researchers suggest algorithms that can be used to have barky dogs solve even enormous numbers without the need for a large number of barks.
Interestingly, the team used a computer from 1981 and an algorithm from 1945 in their experiments. An abacus was also used to demonstrate factorization, showcasing the versatility of their approach.
The team's work raises important questions about the current state of quantum factoring and the need for transparency in quantum computing experiments. They argue that the factors should be unknown to the experimenter to ensure fair and accurate results.
While quantum computers could potentially solve factorization problems exponentially faster than regular computers, they have yet to do so effectively. The team's innovative study serves as a reminder that traditional methods, combined with a touch of ingenuity, can still make significant contributions to the field.
