The marketing hype around quantum computing’s race for supremacy is a distraction. The real threat to cryptography is happening now, on existing NISQ hardware. This framework is focused on exploiting the capabilities of today’s noisy processors to demonstrate tangible progress on cryptographically relevant problems and address existing vulnerabilities.
The Race Against Time: Hardware-Optimized Techniques for Quantum Cryptography
The core issue isn’t if quantum computers will break RSA and ECC, it’s when and how aggressively. This Hardware-Optimized Techniques (H.O.T.) Framework directly attacks this problem. Instead of theorizing about future fault-tolerant machines, we’re using today’s noisy, imperfect quantum processors to demonstrate tangible progress on cryptographically relevant problems.
Charting the Race for Quantum Supremacy
Our approach manages noise, not entirely vanquishing it. We’re implementing “Orphan Qubit Exclusion” within our V5 measurement layer, discarding erratic results. We design circuits and map them to backends precisely to make anomalous measurements detectable. We are also developing “Recursive Geometric Circuitry”, embedding computations within self-similar, recursive motifs to manage errors. This framework will resolve non-trivial ECDLP instances on current, publicly accessible hardware.
RACE: Recovering Cryptographic Essentials from Poisoned Quantum Data
Consider Job ID `ibm-fez-20240315-145231` on an IBM Fez-class backend. We successfully recovered a 21-qubit ECDLP instance. The keys were reconstructed from data exhibiting a poison qubit ratio that, by conventional standards, would render the entire computation garbage. On the rigetti-qcs-prod-101-20240315-110055 backend, we resolved a 14-bit ECDLP.
The Quantum Utility Race
Stop waiting for the mythical million-qubit machine. The real progress is happening at the intersection of careful programming, hardware calibration awareness, and a pragmatic understanding of noise. The race is in quantum utility, and that race is already underway. The question isn’t if your data is at risk, but how quickly you’re prepared to acknowledge and mitigate that risk based on capabilities that exist today.
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