filmov
tv
QIP2021 Tutorial: Convex optimization and quantum information theory (Hamza Fawzi)
Показать описание
Speaker: Hamza Fawzi (Department of Applied Mathematics and Theoretical Physics, University of Cambridge, UK)
Abstract:
This tutorial will cover some applications of convex optimization, and more particularly semidefinite programming, to quantum information theory. In particular, I will explain how semidefinite programming can be used to formulate certain optimization problems involving quantum entropies. I will also discuss semidefinite relaxations to polynomial optimization problems, with a focus on the separability problem.
Get entangled with us!
Abstract:
This tutorial will cover some applications of convex optimization, and more particularly semidefinite programming, to quantum information theory. In particular, I will explain how semidefinite programming can be used to formulate certain optimization problems involving quantum entropies. I will also discuss semidefinite relaxations to polynomial optimization problems, with a focus on the separability problem.
Get entangled with us!
3:02:31
QIP2021 Tutorial: Convex optimization and quantum information theory (Hamza Fawzi)
0:03:14
QIP2021 - 3D World Tutorial
0:29:04
QIP2021 No quantum speedup over gradient descent for non-smooth convex optimization (Suhail Sherif)
3:04:45
QIP2021 Tutorial: Quantum algorithms (Andrew Childs)
0:19:03
QIP 2022 | Near-Optimal Classical and Quantum Lower Bounds For Convex ... (Suhail Sherif)
0:29:52
QIP2021 | New quantum Rényi divergences and their application to device-independent... (Peter Brown)...
3:00:19
QIP2021 Tutorial: Correlation Measures with the Tensorization Property (Salman Beigi)
0:32:12
QIP2021 | Emergent classicality in multipartite channels (Daniel Ranard)
0:27:58
QIP2021 | The Quantum Approximate Optimization Algorithm (Leo Zhou)
0:30:15
QIP2021 | Quantum algorithms for escaping from saddle points (Jiaqi Leng)
0:09:48
CPAIOR 2022: Copositive Optimization via Ising Solvers
0:37:35
Haoran Sun - Recent Advances in Distributed Non-Convex Optimization and Learning
0:29:13
QIP 2022 | A quantum advantage for a Natural Streaming Problem (John Kallaugher)
0:31:11
QIP2021 | Circuit lower bounds for low-energy states of code Hamiltonians (Chinmay Nirkhe)
0:27:02
Iterative algorithm for convex optimization over quantum states and channels - Vikesh Siddhu
0:22:43
QIP 2021 | Constant-sized robust self-tests for states and measurements of un... (Jitendra Prakash)
0:29:09
QIP2021 | Optimal universal programming of unitary gates (Yuxiang Yang)
0:29:46
QIP2021 | Fundamental aspects of solving quantum problems with machine learning (Hsin-Yuan Huang)
0:31:10
QIP2021 | The PPT-squared conjecture holds for all Choi type map (Satvik Singh)
0:28:27
QIP2021 | Subsystem codes with high thresholds (Oscar Higgott)
0:04:11
All Optimization Problems Perfectly Solved | Quantum Computing Series
0:16:19
Spotlight Talk: How to Escape Saddle Points Efficiently
0:29:45
QIP2021 | Using Metrological Bounds in Quantum Error Correction (Aleksander Kubica)
0:13:30
Convex optimization book - solution - exercise - 2.3 - midpoint convexity
Комментарии