Search by speaker

Filter institution








Filter content






Wed, 19. Mar at 13:00
ZIB, Room 2006 (S...
Entanglement detection via Frank-Wolfe algorithms
Abstract. Entanglement is the core feature in the quantum world, which plays an important role in many quantum information processes. For low-dimensional and small systems, quantum entanglement can be detected by the positive partial transpose (PPT) criterion sufficiently and necessarily. However, it is tricky to detect entanglement for high-dimensional and/or large multipartite quantum systems, both theoretically and numerically. In this work, with the help of the Frank-Wolfe algorithms, or named conditional gradient algorithms, and their progress in recent years, we develop a high-precision numerical tool that can certify quantum entanglement and quantum separability at the same time. Our method can detect the entanglement of bipartite systems with local dimensions higher than 20. For multipartite systems, our method can characterize entanglement within not only a specific partition, but also the more general k-separability structure, which includes the genuine multipartite entanglement (GME) problem (i.e., 2-separability), up to 10 qubits. Moreover, the overall design of the tool is oriented towards experimentation, which can access the raw data and achieve an operational entanglement witness. Last but not least, our method supports the analysis of noise robustness for arbitrary noise types, not limited to conventional white noise.
Wed, 19. Mar at 16:15
Arnimallee 3
Embedding Spanning Trees in (n,d,λ)-graphs via Sorting Networks
Abstract. My bachelor thesis analyses the paper by Joseph Hyde, Natasha Morrison, Alp Müyesser and Matías Pavez-Signé (arXiv:2311.03185v1). The aim is to find arbitrary spanning trees in pseudorandom graphs. This is done by first identifying a large number of long paths within the tree, then embedding the remaining vertices of the tree, then using perfect matchings to embed large parts of the paths and finally using a sorting network to connect the correct ends of the paths. The focus is on the extendability technique, construction of a sorting network and embedding trees.
Fri, 21. Mar
Simultaneous Contact Representations of Planar Graphs
Wed, 26. Mar at 13:00
ZIB, Room 2006 (S...
Advancing Climate Strategies - High-Resolution Canopy Height Estimation from Space
Abstract. Reliable and detailed information on forest canopy height is essential for understanding the health and carbon dynamics of forests, which play a pivotal role in climate adaptation and mitigation strategies. Traditional methods of forest monitoring, while foundational, lack the global coverage and are often costly, hindering effective policymaking. Jan Pauls and colleagues have developed a novel framework using satellite data to estimate canopy height on a global scale. The approach combines cutting-edge data preprocessing techniques, a unique loss function to mitigate geolocation inaccuracies, and data filtering from the Shuttle Radar Topography Mission to enhance prediction reliability in mountainous areas. The framework significantly improves upon existing global-scale canopy height maps. By offering a high-resolution (10 m) global canopy height map, the produced map provides critical insights into forest dynamics, aiding in more effective forest management and climate change mitigation efforts. This talk will explore the methods and implications of this work, demonstrating how advancements in Earth observation and machine learning can revolutionize global forest assessments and ecological studies.
Wed, 02. Apr at 16:30
EN 058
When alcoved polytopes add
Abstract. Alcoved polytopes are characterized by the property that all facet normal directions are parallel to the roots e_i - e_j. This fundamental class of polytopes appears in several applications such as optimization, tropical geometry or physics.<br>This talk focuses on the type fan of alcoved polytopes which is the subdivision of the metric cone by combinatorial types of alcoved polytopes. The type fan governs when the Minkowski sum of alcoved polytopes is again alcoved. We prove that the structure of the type fan is governed by its two-dimensional faces and give criteria to study the rays of alcoved simplices.<br>This talk is based on joint work with Nick Early and Leonid Monin.
Wed, 09. Apr at 13:00
ZIB, Room 2006 (S...
Koopman von Neumann mechanics
Wed, 16. Apr at 13:00
Minimization on the sphere and cut selection for the Capra-cutting plane method
Wed, 16. Apr at 15:15
WIAS, Erhard-Schm...
Wed, 16. Apr at 16:30
EN 058
D-Finite Functions
Abstract. A function is called D-finite if it satisfies a linear differential equations with polynomial coefficients. Such functions play a role in many different areas, including combinatorics, number theory, and mathematical physics. Computer algebra provides many algorithms for dealing with D-finite functions. Of particular importance are operations that preserve D-finiteness. In the talk, we will give an overview over some of these techniques.
Tue, 22. Apr at 13:00
2.417
Wed, 23. Apr at 11:30
online
Entanglement Detection via Frank-Wolfe Algorithms
Abstract
Wed, 23. Apr at 13:00
ZIB, Room 2006 (S...
Multi-node quantum circuit simulation with decision diagram in HPC
Wed, 23. Apr at 16:30
EN 058
Colored multiset Eulerian polynomials
Abstract. The central objects in this talk are the descent polynomials of colored permutations on multisets, referred to as colored multiset Eulerian polynomials. These polynomials generalize the colored Eulerian polynomials that appear frequently in algebraic combinatorics and are known to admit desirable distributional properties, including real-rootedness, log-concavity, unimodality and the alternatingly increasing property. In joint work with Bin Han and Liam Solus, symmetric colored multiset Eulerian polynomials are identified and used to prove sufficient conditions for a colored multiset Eulerian polynomial to satisfy the self-interlacing property. This property implies that the polynomial obtains all of the aforementioned distributional properties as well as others, including bi-gamma-positivity. To derive these results, multivariate generalizations of a generating function identity due to MacMahon are deduced. The results are applied to a pair of questions, both previously studied in several special cases, that are seen to admit more general answers when framed in the context of colored multiset Eulerian polynomials. The first question pertains to s-Eulerian polynomials, and the second to interpretations of gamma-coefficients. We will see some of these results in detail, depending on the pace of the talk. We may also discuss some connections between multiset permutations and polytopes from algebraic statistics.
Tue, 29. Apr at 11:15
1.023 (BMS Room, ...
Wed, 30. Apr at 15:15
WIAS, Erhard-Schm...
Wed, 30. Apr at 15:45
Rudower Chaussee ...
Wed, 30. Apr at 16:30
EN 058
Wed, 07. May at 11:30
online
A New Approach to Metastability in Multi-Agent Systems
Abstract
Wed, 07. May at 15:15
WIAS, Erhard-Schm...
Tue, 13. May at 11:15
1.023 (BMS Room, ...
Wed, 14. May at 14:00
WIAS, Erhard-Schm...
Wed, 14. May at 15:30
WIAS, Erhard-Schm...
Wed, 21. May at 11:30
online
Demand Strip Packing
Wed, 04. Jun at 11:30
online
On the Expressivity of Neural Networks
Abstract
Wed, 11. Jun at 15:15
WIAS, Erhard-Schm...
Wed, 18. Jun at 11:30
online
Convolutional Brenier Generative Networks
Abstract
Wed, 18. Jun at 13:00
ZIB, Room 2006 (S...
Bounding geometric penalties in Riemannian optimization
Abstract. Riemannian optimization refers to the optimization of functions defined over Riemannian manifolds. Such problems arise when the constraints of Euclidean optimization problems can be viewed as Riemannian manifolds, such as the symmetric positive-definite cone, the sphere, or the set of orthogonal linear layers for a neural network. This Riemannian formulation enables us to leverage the geometric structure of such problems by viewing them as unconstrained problems on a manifold. The convergence rates of Riemannian optimization algorithms often rely on geometric quantities depending on the sectional curvature and the distance between iterates and an optimizer. Numerous previous works bound the latter only by assumption, resulting in incomplete analysis and unquantified rates. In this talk, I will discuss how to remove this limitation for multiple algorithms and as a result quantify their rates of convergence.
Wed, 02. Jul at 11:30
online
Informing Opinion Dynamics Models with Online Social Network Data
Abstract
Wed, 02. Jul at 15:15
WIAS, Erhard-Schm...
Fri, 04. Jul at 14:15
TU (C 130)
Kovalevskaya Lecture
Sun, 06. Jul at 15:30
Rudower Chaussee ...
Positive sectional curvature and Ricci flow
Abstract
Wed, 09. Jul at 15:15
WIAS, Erhard-Schm...
Wed, 16. Jul at 11:30
online
Data-Adaptive Discretization of Inverse Problems
Abstract
Wed, 16. Jul at 15:15
WIAS, Erhard-Schm...