18 citations · 43 across the 9 of their papers we have counts for
9 papers
Geometric inflation of deviations challenges neural quantum states in dynamics of quantum Ising models
Wladislaw Krinitsin, Jonas B. Rigo, Mohammad Abedi +1
Neural quantum states (NQS) have emerged as a powerful framework for simulating non-equilibrium dynamics in strongly correlated quantum systems, offering scalable variational repre…
Neural quantum states in condensed matter: advances, best practices, and prospects
Jonas B. Rigo, Björn J. Wurst, Rajah Nutakki +2
Neural quantum states provide flexible variational representations of quantum many-body wave functions by combining neural-network parametrizations with Monte Carlo sampling. In th…
Compressed minimum-purity time evolution for late-time quantum dynamics
Moksh Bhateja, Jonas B. Rigo, Markus Schmitt
Unitary time evolution of initially simple quantum many-body states rapidly generates entanglement and complex correlations, which limits direct numerical simulations. The late-tim…
Operator Lanczos Approach enabling Neural Quantum States as Real-Frequency Impurity Solvers
Jonas B. Rigo, Markus Schmitt
To understand the intricate exchange between electrons of different bands in strongly correlated materials, it is essential to treat multi-orbital models accurately. For this purpo…
Unsupervised Learning of Effective Quantum Impurity Models
Jonas B. Rigo, Andrew K. Mitchell
Generalized quantum impurity models -- which feature a few localized and strongly-correlated degrees of freedom coupled to itinerant conduction electrons -- describe diverse physic…
Linear response quantum transport through interacting multi-orbital nanostructures
Emma L. Minarelli, Jonas B. Rigo, Andrew K. Mitchell
Nanoelectronics devices, such as quantum dot systems or single-molecule transistors, consist of a quantum nanostructure coupled to a macroscopic external electronic circuit. Thermo…
Two-channel charge-Kondo physics in graphene quantum dots
Emma L. Minarelli, Jonas B. Rigo, Andrew K. Mitchell
Nanoelectronic quantum dot devices exploiting the charge-Kondo paradigm have been established as versatile and accurate analog quantum simulators of fundamental quantum impurity mo…
Automatic Differentiable Numerical Renormalization Group
Jonas B. Rigo, Andrew K. Mitchell
Machine learning techniques have recently gained prominence in physics, yielding a host of new results and insights. One key concept is that of backpropagation, which computes the…
Machine learning effective models for quantum systems
Jonas B. Rigo, Andrew K. Mitchell
The construction of good effective models is an essential part of understanding and simulating complex systems in many areas of science. It is a particular challenge for correlated…