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Variational Hybrid Quantum Algorithms
Quantum Optimization
Quantum Compilation Routing Architecture
Quantum Machine Learning
Linguistic Predictability and Search Complexity: How Linguistic Redundancy Constraints the Landscape of Classical and Quantum Search
arXiv
Authors: Alessio Di Santo, Gabriella Lanziani
Year
2025
Paper ID
17007
Status
Preprint
Abstract Read
~2 min
Abstract Words
171
Citations
N/A
Abstract
This study examines the quantitative relationship between linguistic regularities and computational search complexity through a hybrid classical-quantum framework applied to Renaissance Italian texts. Using four representative works from the fifteenth and sixteenth centuries-Il Principe (Machiavelli), Il Cortegiano (Castiglione), I Ricordi (Guicciardini), and Orlando Furioso (Ariosto)-we construct character-based n-gram models under both a historically grounded 25-letter orthography and the full modern Italian alphabet. These models provide corpus-derived probabilistic baselines for evaluating substitution-cipher search processes. Combining classical hill climbing and simulated annealing with Grover-style quantum-inspired estimates and a QUBO annealing formulation, we quantify how the probability that a key produces a linguistically plausible decryption (pgood) relates to expected computational effort. Across cipher lengths from 200 to 1000 characters, empirical results confirm the predicted dependence of Grover oracle calls on 1/sqrt(pgood) and show that longer texts yield sharper score distributions and smaller feasible key regions. Overall, the findings establish a link between linguistic redundancy and search-space contraction, providing an empirical framework for comparing classical, quantum-inspired, and idealized quantum search dynamics under unified corpus-driven constraints.
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