5 papers
Bias Analysis and Regularization of Sequential Minimal Optimization in Variational Quantum Eigensolvers
Samuele Pedrielli, Frederik Stalschus, Stefan Kühn +3
The Nakanishi Fujii Todo (NFT) algorithm, also known as Rotosolve, implements Sequential Minimal Optimization for Variational Quantum Eigensolvers (SMO-VQE) by exploiting the trigo…
Computing quantum entanglement with machine learning
Andrea Bulgarelli, Elia Cellini, Karl Jansen +5
Entanglement calculations in quantum field theories are extremely challenging and typically rely on the replica trick, where the problem is rephrased in a study of defects. We demo…
Fermion Discretization Effects in the Two-Flavor Lattice Schwinger Model: A Study with Matrix Product States
Tim Schwägerl, Karl Jansen, Stefan Kühn
We present a comprehensive tensor network study of staggered, Wilson, and twisted mass fermions in the Hamiltonian formulation, using the massive two-flavor Schwinger model as a be…
Gaussian boson sampling for binary optimization
Jean Cazalis, Tirth Shah, Yahui Chai +2
Binary optimization is a fundamental area in computational science, with wide-ranging applications from logistics to cryptography, where the tasks are often formulated as Quadratic…
Small-scale Hamiltonian optimization of interpolating operators for Lagrangian lattice quantum field theory
Artur Avkhadiev, Lena Funcke, Karl Jansen +2
Lattice quantum field theory calculations may potentially combine the advantages of Hamiltonian formulations with the scalability and control of conventional Lagrangian frameworks.…