45 citations · 129 across the 44 of their papers we have counts for
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Ground-State Preparation of the Fermi-Hubbard Model on a Quantum Computer with 2D Topology via Quantum Eigenvalue Transformation of Unitary Matrices
Thilo R. Müller, Manuel Geiger, Christian B. Mendl
Quantum computing holds immense promise for simulating quantum systems, a critical task for advancing our understanding of complex quantum phenomena. One of the primary goals in th…
Predicting interacting Green's functions with neural networks
Egor Agapov, Oriol Bertomeu, Andrés Carballo +2
Strongly correlated materials exhibit complex electronic phenomena that are challenging to capture with traditional theoretical methods, yet understanding these systems is crucial…
Belief propagation for general graphical models with loops
Pedro Hack, Jonas Hitter, Christian B. Mendl +1
There is an increasing interest in scaling tensor network methods through belief propagation (BP), as well as increasing the accuracy of BP through tensor network methods. We devel…
Quantum-Classical Computing via Tensor Networks
Nathaniel Tornow, Christian B. Mendl, Pramod Bhatotia
Circuit knitting offers a promising path to the scalable execution of large quantum circuits by breaking them into smaller sub-circuits whose output is recombined through classical…
Enhanced Krylov Methods for Molecular Hamiltonians: Reduced Memory Cost and Complexity Scaling via Tensor Hypercontraction
Yu Wang, Maxine Luo, Matthias Reumann +1
We introduce an algorithm that is simultaneously memory-efficient and low-scaling for applying ab initio molecular Hamiltonians to matrix-product states (MPS) via the tensor-hyperc…
A Riemannian Approach to the Lindbladian Dynamics of a Locally Purified Tensor Network
Emiliano Godinez-Ramirez, Richard Milbradt, Christian B. Mendl
Tensor networks offer a valuable framework for implementing Lindbladian dynamics in many-body open quantum systems with nearest-neighbor couplings. In particular, a tensor network…