Q-NERVE – Plataforma de Chiplets AI+Quantum para Biossensores de Próxima Geração

Published by Rāmānujan Institute for the Development of Prodigious Young Mathematicians on

Abstract

Este whitepaper apresenta o Q-NERVE™, uma plataforma avançada baseada em arquitetura de chiplets que integra inteligência artificial embarcada, fotônica integrada, dispositivos MOEMS e elementos de computação quântica para o desenvolvimento de biossensores de próxima geração.

A proposta central é superar as limitações atuais da bioinstrumentação tradicional, criando dispositivos vestíveis e modulares capazes de operar com resolução subcelular e processamento em edge computing, eliminando a dependência de infraestrutura em nuvem.

O sistema combina aquisição de sinais fisiológicos complexos (como EEG, MEG, PPG e GSR), manipulação óptica de alta precisão e inferência local por aceleradores neurais, permitindo diagnósticos em tempo real e aplicações avançadas em neurointerfaces, medicina preditiva e bioengenharia.

Adicionalmente, a plataforma incorpora módulos de coerência quântica baseados em ion traps, ampliando a sensibilidade e estabilidade dos sensores em ambientes biológicos complexos.

Ao integrar computação quântica, IA e fotônica em uma arquitetura modular, o Q-NERVE posiciona-se como uma infraestrutura tecnológica estratégica para o futuro da medicina, das interfaces homem-máquina e da bioinstrumentação de alta precisão.

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Rāmānujan Institute for the Development of Prodigious Young Mathematicians

I am the founder of the Rāmānujan Institute for the Development of Prodigious Young Mathematicians, which aims to foster the education and growth of children and young people aged 2 to 16 who demonstrate exceptional mathematical abilities. Our institute is dedicated to providing an advanced and challenging curriculum that not only prepares students for prestigious competitions, such as the International Mathematical Olympiad (IMO), but also supports their overall development. We focus on nurturing mathematical talent while ensuring that our students develop the skills necessary for success in academic and professional environments. Through mentorship programs and a commitment to inclusivity, we strive to create a community where young mathematicians can thrive and make significant contributions to the field. I am also Marcos Eduardo Elias, an engineer and mathematician. My academic journey began with a Bachelor’s degree in Mechatronic Engineering from the Polytechnic School of the University of São Paulo (USP). My education culminated in a Doctorate in Mathematics from St. Petersburg State University, specializing in Real, Complex, and Functional Analysis. I have held teaching positions at institutions such as Ibmec, Insper, and FGV-SP. I am also a member of the Brazilian Mathematical Society. In the financial sector, I founded several institutions, including GAS Investimentos (later Vinci Partners), Empiricus Research, Turing High Frequency Trading, Modena Capital and Guiar Investments. In the financial markets, I am known as the Volatility Hunter, and - in the last 30 years, I have been relentlessly searching for highly asymmetric upside risk (I am on the right side of the barbell). I have been contributing to the MIT Sloan Management Review, primarily on topics related to risk management. My current research interests include real, complex, and functional analysis, linear algebra for quantum algorithmics, Feigenbaum-Coullet-Tresser universality, stochastic calculus, and Grothendieck's Standard Conjectures on Algebraic Cycles.

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