collaborators

5 papers

quant-ph2026

Effective Transition from Weak to Essential Non-Markovianity Induced by Coarse-Graining

Gabriel M. Arantes, Barbara Amaral, Nadja K. Bernardes

Quantum channels generally reduce the distinguishability of quantum states, thereby constraining information transmission and processing in open quantum systems. While it is known…

cs.AI2026

Impact of Data-Oriented and Object-Oriented Design on Performance and Cache Utilization with Artificial Intelligence Algorithms in Multi-Threaded CPUs

Gabriel M. Arantes, Giancarlo Lucca, Eduardo N. Borges +3

The growing performance gap between multi-core CPUs and main memory necessitates hardware-aware software design paradigms. This study provides a comprehensive performance analysis…

cs.AI2025

SpellForger: Prompting Custom Spell Properties In-Game using BERT supervised-trained model

Emanuel C. Silva, Emily S. M. Salum, Gabriel M. Arantes +3

Introduction: The application of Artificial Intelligence in games has evolved significantly, allowing for dynamic content generation. However, its use as a core gameplay co-creatio…

q-fin.CP2025

Machine Learning vs. Randomness: Challenges in Predicting Binary Options Movements

Gabriel M. Arantes, Richard F. Pinto, Bruno L. Dalmazo +5

Binary options trading is often marketed as a field where predictive models can generate consistent profits. However, the inherent randomness and stochastic nature of binary option…

quant-ph2025

k-Uniform complete hypergraph states stabilizers in terms of local operators

Gabriel M. Arantes, Vinícius Salem, Danilo Cius +1

In this work, we present a novel method to express the stabilizer of a k-uniform complete hypergraph state as a linear combination of local operators. Quantum hypergraph states gen…