TBA
Tag: quantum computation
-
Monthly meeting Computing Track May26
Speaker:TBA
Title:TBA
Abstract: TBA
-
A Novel Mathematical Formulation of Density Functional Theory
Speaker:Håkon R. Fredheim
Title: A Novel Mathematical Formulation of Density Functional Theory
Abstract: In this talk, I present my recent work with Simen Kvaal, where we developed a novel mathematical framework for density functional theory (DFT), the “gold standard method” used in large-scale many-particle quantum chemistry calculations. I present some preliminary results, where we address some open mathematical questions in DFT using our framework. Paper: https://arxiv.org/abs/2510.12242
-
Novel methods for quantum information processing
Speaker: Franz Luef, NTNU
Title: Novel methods for quantum information processing
Abstract: In this talk I present a way to transfer methods from signal processing, like the short-time Fourier transform or the wavelet transform and the respective reconstruction formulae, to the quantum setting. This approach works for discrete variables and continuous variables quantum systems. The focus is going to be on the operator short-time Fourier transform and the polarized Cohen’s class of an operator. This is joint work with Monika Doerfler, Henry McNulty and Eirik Skrettingland.
-
Expressive and Constraint-Preserving QAOA for the Minimum Vertex Cover with Optimized Initializations
Speaker: Finley Quinton, NTNU
Title: Expressive and Constraint-Preserving QAOA for the Minimum Vertex Cover with Optimized Initializations
Abstract: Our work investigates advanced Quantum Approximate Optimization Algorithm (QAOA) strategies for the Minimum Vertex Cover (MVC) problem on weighted graphs, emphasizing constraint-preserving mixers and their performance against traditional penalty-based approaches. We analyze both the standard constraint-preserving mixer and a multi-angle variant, exploring how careful parameter initialization and constraint enforcement can improve convergence and solution quality. In the multi-angle setting, we propose strategies to reduce the number of parameters to optimize, aiming to improve scalability and mitigate barren plateaus. Extensive experiments on different weighted graph instances highlight the advantages of these approaches, demonstrating more reliable performance and better alignment with problem-specific structures.
-
Mapping quantum circuits to shallow-depth measurement patterns based on graph states
Speaker: Dr. Matthias Heller, Fraunhofer Institute for Computer Graphics Research IGD
Title: Mapping quantum circuits to shallow-depth measurement patterns based on graph states
Abstract: The paradigm of measurement-based quantum computing (MBQC) starts from a highly entangled resource state on which unitary operations are executed through adaptive measurements and corrections ensuring determinism. This is set in contrast to the more common quantum circuit model, in which unitary operations are directly implemented through quantum gates prior to final measurements. In this work, we incorporate concepts from MBQC into the circuit model to create a hybrid simulation technique, permitting us to split any quantum circuit into a classically efficiently simulatable Clifford-part and a second part consisting of a stabilizer state and local (adaptive) measurement instructions, a so-called standard form, which is executed on a quantum computer. We further process the stabilizer state with the graph state formalism, thus, enabling a significant decrease in circuit depth for certain applications.
