Factoring integers with sublinear resources on a superconducting quantum processor

your compute requirements by ~2x to recover the prime factors (specifically it's actually a logarithm so it's < 2x more compute is needed). The algorithm for doing this is known as Shor's algorithm [0] and because of how complexity works in computer science, it turns out that this algorithm can be applied to many many problems mechanically and these problems are the underpinnings of RSA, DSA, ECDH key exchanges. These quantum-resistant algorithms are based on mathematical problems believed to be exponentially difficult even for a theoretical quantum computer - when you double the size of the problem, it again takes exponentially more time even for a theoretical quantum computer. These are of course unproven beliefs but that's true of classical algorithms too. So no, it doesn't matter where you run the cryptographic algorithm; it remains computationally difficult to solve the problem without knowing the secret. The quantum computer is critically important though for your ability to crack classical problems though - without it, all of this post-quantum cryptography is unnecessary. [0] https://en.wikipedia.org/wiki/Shor%27s_algorithm [1] https://arxiv.org/pdf/2212.12372

sensitive data. Create a Scalable Complexity Factor incorporating 18-month cycles to increase the complexity of temcrypt and a custom clock that advances and adds one hour every 6 months. The dependency to decrypt the data is based on a unique key, the time it was encrypted, and the processing power of your machine. If you don't apply the exact key at the exact time (hour and minute) in later days, decrypting the information becomes “impossible”. You can read more in the following repository paths: ▪ Readme: https://github.com/jofpin/temcrypt/blob/main/README.md ▪ Knowledge: https://github.com/jofpin/temcrypt/blob/main/KNOWLEDGE.md With temcrypt, you can have many use cases. Some I can mention include protection for your seed phrases (cryptocurrency wallets), business data, military data, medical data, and much more. I hope you enjoy temcrypt and share it with your friends, coworkers, developers, lawyers, journalists, and people around the world who deserve to protect their most sensitive data. This is a big step for a new era of new ways to encrypt and protect data. Follow me on: https://twitter.com/jofpin

this rare therefore it is fine". Essentially the only real problem not addressed by the paper was that it required arbitrarily good qubits... so he went and invented quantum error correction [2]. The paper being discussed here [3] does not strike me as meticulous. It strikes me as sloppy. They are getting good numbers by hoping potential problems are not problems. Instead of addressing the biggest potential showstoppers, they have throwaway sentences like "It should be pointed out that the quantum speedup of the algorithm is unclear due to the ambiguous convergence of QAOA". How many shots are needed for each sample point fed into the classical optimization algorithm? How many steps does the optimization algorithm need? How do these scale as the problem size is increased? How big are they for the largest classically simulable size (RSA128 with 37 qubits according to their table)? These are absolutely critical questions!... and the paper doesn't satisfyingly address them. Is there somewhere where I can bet money that this doesn't amount to anything? 1: https://arxiv.org/abs/quant-ph/9508027 2: https://journals.aps.org/pra/abstract/10.1103/PhysRevA.52.R2... 3: https://arxiv.org/abs/2212.12372