Exploring Quantum Materials with the 1D Hubbard Model for Applications in Quantum Networks

• Grant number: 25/07040-5
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)
• Start date: July 01, 2025
• End date: June 30, 2026
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Physical-Chemistry
• Principal Investigator: Vivian Vanessa França Henn
• Grantee: Marina Heloysa Sanino da Silva
• Supervisor: Kae Nemoto
• Host Institution: Instituto de Química (IQ). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil
• Institution abroad: Okinawa Institute Of Science And Technology, Japan
• Associated to the scholarship: 23/02293-7 - Quantum phase transitions in superfluid nanostructures, BP.DD

Abstract

The increasing demand for quantum networks drives research into how different architectures affect stability. One approach is to simulate these systems through electronic interactions and entanglement to evaluate network cohesion. This work employs the one-dimensional Hubbard model to represent qubits with varying property distributions. Additionally, it explores how these properties enhance quantum materials, particularly diamonds with nitrogen-vacancy (NV) centers, to analyze phase transitions and entanglement properties relevant to robust quantum communication.This project studies the robustness of qubit networks against noise using the Hubbard model in different topologies. Each site in the chain represents a qubit, acting as a node in the quantum network. Connections arise from interactions between neighboring fermions, characterized by an interaction strength V . While previous studies focused on noisy quantum repeaters, this work investigates electronic interactions and entanglement in network stabilization. In the case of NV centers, the hybrid system is modeled as a chain with vacancies embedded in a superconducting lattice.To integrate these structures into the Hubbard model, site interactions are adjusted based on topology. Using density matrix renormalization group (DMRG) methods, this study examines entanglement distribution and how different interactions impact network reliability and hybrid material properties. This approach provides insights into how connection patterns influence entanglement and network resilience.