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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Computer Vision
Solve computer vision problems.
Quantum Computing
Use quantum computing to solve optimization problems.
publications
An iterative quantum approach for transformation estimation from point sets
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Natacha Kuete Meli, Florian Mannel and Jan Lellmann
Download here
A universal quantum algorithm for weighted maximum cut and Ising problems
Published in Springer Quantum Inf Process, 2023
Natacha Kuete Meli, Florian Mannel and Jan Lellmann
Download here
talks
Quantum Computing for Binary Optimization and Beyond: Bridging Classical and Quantum Landscapes
Published:
Talk summary
In this talk, I introduce quantum computing and discuss through adiabatic and universal paradigms its capabilities in solving challenging Quadratic Unconstrained Binary Optimization (QUBO) problems. While classical methods often struggle with such hard combinatorial problems, Adiabatic Quantum Computers (AQC) excel at solving them, inspiring even new mappings of practical optimization problems to QUBO forms. I will present an algorithm for rigid point-sets registration using AQC. Moving to universal quantum computing, I will introduce Variational Quantum Computing (VQC). VQC involves a hybrid quantum-classical computational loop, where a quantum computer executes only some specific, ideally quantum-native tasks, and a classical computer runs an optimization procedure to optimize over some objective function. A significant class of variational quantum objective functions allows the evaluation of their exact analytical gradients, enabling the use of gradient-based solvers. I will go over the possibility of solving QUBO problems with VQC. [Slides]
Ph.D. Thesis Defense
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Talk summary
Talk for my Ph.D. thesis defense. [Slides][Dissertation]
Quantum Binary Optimization
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Talk summary
Binary optimization is an omnipresent problem in computer vision. It helps, for example, to model decision problems such as labeling, matching, tracking, clustering, and more. However, solving binary optimization problems classically is challenging due to their discrete and combinatorial nature. Over the last few years, quantum computing, especially adiabatic quantum computing, has shown promising results in solving binary problems, raising the question of whether more efficient solvers exploiting quantum properties could be designed. In this talk, I discuss quantum solvers for binary optimization problems. Specifically, I will present a variational solver that splits the task hybridly into quantum and classical parts, where a quantum computer executes only some specific, ideally quantum-native tasks, and a classical computer runs an optimization procedure to optimize the objective function. I will show how to evaluate the objective and even compute its analytical gradient on the quantum hardware, allowing the use of gradient-based sub-solvers for optimizing the objective. [Slides]
teaching
Computer graphics
Undergraduate and graduate course, University of Luebeck, 2020
Summer term 2020 (~ 40 students per semester).
Mathematical methods of image processing
Undergraduate and graduate course, University of Luebeck, 2021
Winter term 2021 (~ 30 students per semester).
Seminar numerical optimization
Undergraduate and graduate course, University of Luebeck, 2022
Winter terms 2021 and 2022 (~ 2 students per semester under my supervision).
Non-Boolean quantum amplitude amplification for discret optimization.
B.Sc, University of Luebeck, 2023
Student: Josephine Elisabeth Oettinger
Linear algebra
undergraduate course, University of Luebeck, 2023
Summer term 2021 and winter term 2023 (~30 students per semester in my exercise group).
Optimization
Undergraduate course, University of Luebeck, 2023
Summer terms 2022 and 2023 (~ 12 students per semester).
Quantum image processing
Undergraduate and Graduate course, University of Luebeck, 2023
Winter terms 2021, 2022 and 2023 (~ 15 students per semester).