2026-05-08 –, Main Stage
What do Niccolò Machiavelli and Grover's Algorithm have in common? More than you think. While one mastered the art of political manipulation in the 1500s, the other promises a quadratic speedup for quantum key search. But when these two worlds collide, something unexpected happens: The quantum oracle misfires.
In this talk, we build Grover search oracles directly from Renaissance Italian texts —
Il Principe, Orlando Furioso, Il Cortegiano, I Ricordi — and measure exactly how much
linguistic redundancy contracts the cipher key space. We then simulate those oracles on a real quantum statevector and watch the standard iteration formula get it catastrophically wrong.
We will dive into:
- The Corpus-Driven Oracle: How character-level n-gram redundancy defines the fraction of "good" keys p_good — the sole parameter governing both classical exhaustive search and Grover oracle call count.
- The Discrete Resonance Failure: At one statistical threshold, the textbook formula predicts 2 optimal iterations. The real quantum simulation needs 24 — making quantum search four times slower than classical at that point. We dissect why.
- The L=600 Transition Zone: An empirical anomaly where stylistic variance in 16th-century prose (Latin citations, proper-noun lists) creates a chaotic instability band that separates statistical noise from structural reality.
- QUBO vs. Grover: Why compressing a 23-letter alphabet to 7 letters breaks the annealer but leaves the quantum oracle unaffected — and what that tells us about attack-surface geometry.
Join us for a journey where orthography meets qubits, proving that whether you hold a quill or a
quantum processor, redundancy is the enemy of secrecy — but discrete arithmetic is the enemy
of quantum speedup.
Cryptanalysis has always been a game of exploiting patterns. This session takes that principle
into quantum territory by pitting the rigid orthography of Renaissance Italian against the
probabilistic mechanics of Grover amplitude amplification — and catching the algorithm in a
failure mode the textbook formula cannot predict.
The Setup
We introduce a two-phase experimental framework built around a custom Python toolkit that
normalizes and models four 16th-century Italian corpora using character n-gram language models.
Every candidate decryption key is scored against the corpus; the fraction of keys that score above
a statistical plausibility threshold — p_good — becomes the marked fraction fed to the Grover
oracle. This transforms a linguistics measurement into a quantum complexity parameter.
Phase 1 sweeps the full 23-letter alphabet across multiple cipher lengths and plausibility
thresholds, producing analytical Grover oracle estimates and classical exhaustive-search baselines.
Phase 2 reduces the alphabet to 7 letters — making all 5 040 keys enumerable — and runs a
direct statevector simulation of Grover amplitude amplification. No analytical approximations.
Real quantum circuit behavior on a controlled key space.
The Discovery: Discrete Resonance Failure
The headline finding is a failure mode the standard Boyer formula cannot anticipate. At one
threshold, p_good produces an angle θ for which no small integer iteration count satisfies the
resonance condition. The formula confidently recommends stopping at iteration 2. The real
probability curve keeps oscillating and only peaks at iteration 24 — requiring 49 oracle calls
against a classical expectation of 12.5 trials. Quantum loses by a factor of four.
We walk through the forensic geometry of this collapse: why the sinusoidal Grover envelope
creates near-equal local maxima that fool the continuous approximation, and how to detect
near-resonant p_good values before deploying the algorithm.
The L=600 Anomaly
A separate empirical anomaly surfaces at cipher length L=600, where p_good persistently
exceeds both shorter and longer ciphers across five of six tested thresholds. A targeted stability
analysis — sampling 20 distinct text segments at each length — identifies this as a transition
zone of maximal within-length variance: at L=600, local stylistic features of Renaissance prose
(Latin citations, enumerations, proper-noun clusters) produce segment-level fluctuations wide
enough to push p_good above its expected trend. We show how to isolate structural data effects
from algorithmic noise.
QUBO and the Landscape-Warping Effect
Parallel Quadratic Unconstrained Binary Optimization (QUBO) annealing experiments reveal a
complementary insight: compressing a 23-letter alphabet to 7 letters cuts the trigram parameter
space by a factor of ~36, collapsing statistically distinct character patterns onto the same
symbols and creating false energy attractors — suboptimal keys surrounded by uphill barriers
the annealer cannot cross. The QUBO failure pattern inverts relative to the 23-letter case.
The Grover oracle, which only needs a binary marked/unmarked verdict, is structurally immune to
this distortion. The two attack paradigms probe entirely different properties of the key-score
landscape.
What Attendees Will Take Away
- How to construct a corpus-derived Grover oracle and measure p_good empirically rather than
assuming it. - How to detect discrete resonance conditions that cause the standard iteration formula to fail —
and by how much. - Why reducing model complexity (smaller alphabet, lower-order n-grams) can help a quantum
oracle while simultaneously breaking an annealing attack. - A reusable stability analysis method for distinguishing structural data features from
algorithmic artefacts in any combinatorial search benchmark.
This talk is for anyone at the intersection of classical cryptanalysis, optimization heuristics,
and quantum security — no prior quantum computing background required.
Alessio Di Santo received a Bachelor's degree in Information Engineering in 2020 from the Università degli Studi dell'Aquila, with a thesis focused on fairness and cryptography. In 2022, he completed a Master's degree at the same institution, presenting a thesis on forensic acquisition techniques for Windows IT/OT assets. Currently, he is pursuing a Ph.D. at the Università degli Studi dell'Aquila under the supervision of Professor Dajana Cassioli, with co-tutor Walter Tiberti. Since 2020, he has been employed in the cybersecurity sector, working as a Cyber Threat Intelligence Analyst, Incident Responder, Purple Teamer and Malware Analyst. Nowadays, he works as a Senior Cyber Security Specialist at Deutsche Boerse.
Gabriella Lanziani received her Bachelor Degree in Literature and her Master Degree in History. Her academic interests lie primarily in linguistics, with a particular focus on the structural and semantic properties of language and their potential applications in information theory and cryptography. Her research explores how linguistic analysis - especially syntax, semantics, and pattern recognition - can contribute to the understanding of code systems, cryptographic communication, and natural language processing in cybersecurity contexts.