4 citations · 4 across the 6 of their papers we have counts for
7 papers
Quantum non-Markovian response spectra
Aaron Sander, John F. Kam, Gauthameshwar S. +2
Quantum systems are rarely isolated from their surroundings. These hidden environments can retain information and return it later, producing correlated errors in quantum computers…
Scalable Lindblad Noise Learning via Stochastic Tensor-Network Simulation
Alejandro R. Ramos Ramos, Maximilian Fröhlich, Aaron Sander +4
Learning dissipation rates in large-scale open quantum systems is a major obstacle for near-term quantum technologies, as existing Lindblad estimation methods are typically limited…
Basis-update and Galerkin time integration in canonical matrix-product-state form
Maximilian Fröhlich, Richard M. Milbradt, Martin Eigel +3
Matrix product state algorithms must enlarge their bond spaces as entanglement grows and compress them to control cost. We formulate basis-update and Galerkin (BUG) time integratio…
Noisy quantum circuit simulation with the tensor jump method
Maximilian Fröhlich, Aaron Sander, Martin Eigel +2
Classical simulation of noisy quantum circuits is essential for validating algorithms, benchmarking hardware, and assessing error-mitigation strategies, but remains limited by the…
Quantum circuit simulation with a local time-dependent variational principle
Aaron Sander, Maximilian Fröhlich, Mazen Ali +6
Classical simulations of quantum circuits are vital for assessing potential quantum advantage and benchmarking devices, yet they require sophisticated methods to avoid the exponent…
Large-scale stochastic simulation of open quantum systems
Aaron Sander, Maximilian Fröhlich, Martin Eigel +6
Understanding the precise interaction mechanisms between quantum systems and their environment is crucial for advancing stable quantum technologies, designing reliable experimental…
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…