no code implementations • 21 Nov 2023 • Hrant Gharibyan, Vincent Su, Hayk Tepanyan
We present hierarchical learning, a novel variational architecture for efficient training of large-scale variational quantum circuits.
no code implementations • 1 Feb 2021 • Sepehr Nezami, Henry W. Lin, Adam R. Brown, Hrant Gharibyan, Stefan Leichenauer, Grant Salton, Leonard Susskind, Brian Swingle, Michael Walter
In [1] we discussed how quantum gravity may be simulated using quantum devices and gave a specific proposal -- teleportation by size and the phenomenon of size-winding.
Quantum Physics High Energy Physics - Theory
no code implementations • 12 Nov 2020 • Alexander Buser, Hrant Gharibyan, Masanori Hanada, Masazumi Honda, Junyu Liu
We propose a new framework for simulating $\text{U}(k)$ Yang-Mills theory on a universal quantum computer.
High Energy Physics - Theory High Energy Physics - Lattice Quantum Physics
no code implementations • 12 Nov 2020 • Hrant Gharibyan, Masanori Hanada, Masazumi Honda, Junyu Liu
Furthermore, for certain states in the Berenstein-Maldacena-Nastase (BMN) matrix model, several supersymmetric quantum field theories dual to superstring/M-theory can be realized on a quantum device.
High Energy Physics - Theory High Energy Physics - Lattice Quantum Physics
