Fast Quantum State Reconstruction via Accelerated Non-Convex Programming
We propose a new quantum state reconstruction method that combines ideas from compressed sensing, non-convex optimization, and acceleration methods. The algorithm, called Momentum-Inspired Factored Gradient Descent (MiFGD), extends the applicability of quantum tomography for larger systems. Despite...
Main Authors: | Junhyung Lyle Kim, George Kollias, Amir Kalev, Ken X. Wei, Anastasios Kyrillidis |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-01-01
|
Series: | Photonics |
Subjects: | |
Online Access: | https://www.mdpi.com/2304-6732/10/2/116 |
Similar Items
-
New Quantum Hermite-Hadamard Inequalities Utilizing Harmonic Convexity of the Functions
by: Bandar Bin-Mohsin, et al.
Published: (2019-01-01) -
Some New Quantum Hermite–Hadamard Inequalities for Co-Ordinated Convex Functions
by: Fongchan Wannalookkhee, et al.
Published: (2022-06-01) -
On $\mathscr{M}$-convex functions
by: Muhammad Uzair Awan, et al.
Published: (2020-03-01) -
On Some New Simpson’s Formula Type Inequalities for Convex Functions in Post-Quantum Calculus
by: Miguel J. Vivas-Cortez, et al.
Published: (2021-12-01) -
Several Quantum Hermite–Hadamard-Type Integral Inequalities for Convex Functions
by: Loredana Ciurdariu, et al.
Published: (2023-06-01)