DC 15 – Constrained Optimization with Low-Rank Tensor Approximations

Project Title: Constrained Optimization with Low-Rank Tensor ApproximationsAdvisors: F. Oztoprak Topkaya (Artelys), M. Gabay (Artelys), B. Mourrain (Inria), C. Riener (UiT) Mentor: A. Mantzaflaris (Inria) Objectives: In certain applications, the desired solution of an optimization problem can be stated as a tensor. Typically, the size of such a tensor grows…

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DC 14 – Tensor and polynomial optimisation for quantum information networks

Project Title: Tensor and polynomial optimisation for quantum information networksAdvisors: A. Acin (ICFO), V. Magron (LAAS) Mentor: S. Mansfield (Quandela) Objectives: We consider quantum communication systems with network of users, corresponding to a network of Hilbert space tensor products, which raises important computational challenges. Different type of correlations will be…

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DC 13 – State preparation of matrix-product operations

Project Title: State preparation of matrix-product operationsAdvisors: J. Marecek (CTU) , D. Henrion (LAAS), M. Korda (LAAS) Mentor: G. Korpas (HSBC Lab) Objectives: Many practical quantum circuits operate with multiple quantum registers, storing multiple types of input, some ancillas, and some output registers. In the corresponding initial state preparation, one…

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DC 12 – Approximation hierarchies for quantum entanglement detection

Project Title: Approximation hierarchies for quantum entanglement detectionAdvisors: M. Laurent (NWO-I), V. Magron (CNRS), Mentor: M. Almeida (Quantinuum) Objectives: Tensor products model quantum state systems consisting of multiple subsystems. Detecting whether a quantum state is entangled (or separable) is a fundamental question in quantum information theory, which boils down to…

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DC 11 – Geometry of Hermitian tensor spaces

Project Title: Geometry of Hermitian tensor spacesAdvisors: G. Ottaviani (UniFI), Yang Qi (Inria), B. Mourrain (Inria) Mentor: E. Rubei (UniFI) Objectives: Tensor spaces have natural distances invariant under the orthogonal group or the unitary group, respectively in the real or the complex setting. Several optimisation problems in tensor spaces consist…

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DC 9-Algorithms for Tensor Decomposition

Project Title: Algorithms for Tensor DecompositionAdvisors: A. Bernardi (UniTN), A. Oneto (UniTN), B. Mourrain (Inria) Mentor: Federico Lucca (BlueTensor) Objectives: The objective of the project is from the academic side it intends to investigate and develop new methods and algorithms for tensor decomposition (TD), and from the industrial side the…

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DC 8- Tensor optimization for storage integration

Project Title: Tensor optimization for storage integrationAdvisors: C. Bordin (UiT), C. Riener (UiT), M. Schweighofer (UKON), Mentors: Julien Moisan (Arva), Sigurd Bakkejord (Arva), Inga Setsa Holmstrand (Arva). Objectives: Optimal integration of storage in power and energy networks with a high share of intermittent renewable energy sources is one of the…

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DC 7-Tensor decomposition with group invariance

Project Title: Tensor decomposition with group invarianceAdvisors: H. Munthe-Kaas (UiT), C. Riener (UiT), E. Hubert (Inria), Mentor: Florian Strohl (UiT) Objectives: The so called orbit recovery problem is the problem of recovering a planted signal from noisy measurements under unknown group actions. More concretely, one tries to recover the unknown…

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DC 6 – Gibbs manifolds and semidefinite programming

Project Title: Gibbs manifolds and semidefinite programmingAdvisors: B. Sturmfels (MPG), S. Telen (MPG), M. Laurent (NWO-I), Mentor: Georgios Korpas (HSBC) Objectives: Interior point methods for linear programming use regularization to reduce the problem to smooth convex optimisation on a polytope. A popular choice for the regularization is a strictly convex…

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