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University of Calcutta

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Representative Papers

Capability-Adaptive Cryptanalysis with Reduced-Space Quantum Verification

Aug 12, 2026

This work addresses the fundamental challenge of efficiently integrating classical cryptanalytic evidence with quantum verification in hybrid cryptanalysis. We propose a capability-adaptive unified framework that synergistically combines linear, differential, and side-channel analyses. By constructing a mathematical model for candidate space reduction, the framework establishes a theoretical linkage between spatial compression and the complexity of quantum verification, while incorporating a Hamiltonian formulation to ensure physical realizability. Experimental results demonstrate that the initial key hypothesis space of 4,096 candidates is reduced to just 13 (a compression rate of 99.683%), and the number of Grover iterations required for verification drops from 50 to 2—yielding an approximate 25-fold efficiency gain—with a target state success probability of 94.53%.

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Latest Papers

Capability-Adaptive Cryptanalysis with Reduced-Space Quantum Verification

Aug 12, 2026

This work addresses the fundamental challenge of efficiently integrating classical cryptanalytic evidence with quantum verification in hybrid cryptanalysis. We propose a capability-adaptive unified framework that synergistically combines linear, differential, and side-channel analyses. By constructing a mathematical model for candidate space reduction, the framework establishes a theoretical linkage between spatial compression and the complexity of quantum verification, while incorporating a Hamiltonian formulation to ensure physical realizability. Experimental results demonstrate that the initial key hypothesis space of 4,096 candidates is reduced to just 13 (a compression rate of 99.683%), and the number of Grover iterations required for verification drops from 50 to 2—yielding an approximate 25-fold efficiency gain—with a target state success probability of 94.53%.

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