A brief description of your project (1-2 paragraphs).
ADAPT-QSCI a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian is used. The ansatz to prepare the ground state is adaptively constructed using QSCI (quantum-selected configuration interaction), starting from Hartree Fock.
Several techniques are introduced to reduce the classical computational cost for evaluating gradients that will be used for choosing the generator to append to the ansatz.
This will be used for reference during score evaluation. The results from less than ten calculation are also acceptable
Score 2.03453573 (updated from 2.16047840 on 2/1 9:00JST)
Team name:
QunaSys
Team members:
List up all members' name Kamoshita
Project Description:
A brief description of your project (1-2 paragraphs).
ADAPT-QSCI a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian is used. The ansatz to prepare the ground state is adaptively constructed using QSCI (quantum-selected configuration interaction), starting from Hartree Fock.
Several techniques are introduced to reduce the classical computational cost for evaluating gradients that will be used for choosing the generator to append to the ansatz.
Presentation:
ADAPT-QSCI_QAGC2024.pdf
Source code:
A link to the final source code for your team's hackathon project (e.g., a GitHub repo). https://github.com/QunaSys/quantum-algorithm-grand-challenge-2024/blob/main/problem/example_adaptqsci.py
Your score (Optional)
This will be used for reference during score evaluation. The results from less than ten calculation are also acceptable Score 2.03453573 (updated from 2.16047840 on 2/1 9:00JST)