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 Jul 2020 • John Martyn, Guifre Vidal, Chase Roberts, Stefan Leichenauer
For that purpose, we propose a plausible candidate state $|\Sigma_{\ell}\rangle$ (built as a superposition of product states corresponding to images in the training set) and investigate its entanglement properties.
no code implementations • 3 Jun 2020 • Jinhui Wang, Chase Roberts, Guifre Vidal, Stefan Leichenauer
Originating from condensed matter physics, tensor networks are compact representations of high-dimensional tensors.
1 code implementation • 27 May 2020 • Daniel Liang, Li Li, Stefan Leichenauer
The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.
Quantum Physics
no code implementations • 4 Oct 2019 • Guillaume Verdon, Jacob Marks, Sasha Nanda, Stefan Leichenauer, Jack Hidary
We introduce a new class of generative quantum-neural-network-based models called Quantum Hamiltonian-Based Models (QHBMs).
2 code implementations • 26 Sep 2019 • Guillaume Verdon, Trevor McCourt, Enxhell Luzhnica, Vikash Singh, Stefan Leichenauer, Jack Hidary
We introduce Quantum Graph Neural Networks (QGNN), a new class of quantum neural network ansatze which are tailored to represent quantum processes which have a graph structure, and are particularly suitable to be executed on distributed quantum systems over a quantum network.
1 code implementation • 28 Jun 2019 • Martin Ganahl, Ashley Milsted, Stefan Leichenauer, Jack Hidary, Guifre Vidal
We use the MERA to approximate the ground state wave function of the infinite, one-dimensional transverse field Ising model at criticality, and extract conformal data from the optimized ansatz.
Computational Physics
1 code implementation • 7 Jun 2019 • Stavros Efthymiou, Jack Hidary, Stefan Leichenauer
We demonstrate the use of tensor networks for image classification with the TensorNetwork open source library.
3 code implementations • 3 May 2019 • Ashley Milsted, Martin Ganahl, Stefan Leichenauer, Jack Hidary, Guifre Vidal
TensorNetwork is an open source library for implementing tensor network algorithms in TensorFlow.
2 code implementations • 3 May 2019 • Chase Roberts, Ashley Milsted, Martin Ganahl, Adam Zalcman, Bruce Fontaine, Yijian Zou, Jack Hidary, Guifre Vidal, Stefan Leichenauer
TensorNetwork is an open source library for implementing tensor network algorithms.