Scalably learning quantum many-body Hamiltonians from dynamical data
The physics of a closed quantum mechanical system is governed by its Hamiltonian.
However, in most practical situations, this Hamiltonian is not precisely known, and ultimately …
However, in most practical situations, this Hamiltonian is not precisely known, and ultimately …
Growing extended Laughlin states in a quantum gas microscope: A patchwork construction
The study of fractional Chern insulators and their exotic anyonic excitations poses a major
challenge in current experimental and theoretical research. Quantum simulators, in …
challenge in current experimental and theoretical research. Quantum simulators, in …
Characterization of partially accessible anisotropic spin chains in the presence of anti-symmetric exchange
S Cavazzoni, M Adani, P Bordone… - New Journal of …, 2024 - iopscience.iop.org
We address quantum characterization of anisotropic spin chains in the presence of anti-
symmetric exchange, and investigate whether the Hamiltonian parameters of the chain may …
symmetric exchange, and investigate whether the Hamiltonian parameters of the chain may …
Microscopy of bosonic charge carriers in staggered magnetic fields
The interplay of spin and charge degrees of freedom is believed to underlie various
unresolved phenomena in strongly correlated systems. Quantum simulators based on …
unresolved phenomena in strongly correlated systems. Quantum simulators based on …
Bayesian optimization for robust state preparation in quantum many-body systems
New generations of ultracold-atom experiments are continually raising the demand for
efficient solutions to optimal control problems. Here, we apply Bayesian optimization to …
efficient solutions to optimal control problems. Here, we apply Bayesian optimization to …
Preparing quantum states by measurement-feedback control with Bayesian optimization
The preparation of quantum states is crucial for enabling quantum computations and
simulations. In this work, we present a general framework for preparing ground states of …
simulations. In this work, we present a general framework for preparing ground states of …
Discrete real-time learning of quantum-state subspace evolution of many-body systems in the presence of time-dependent control fields
A method is presented for discrete real-time learning (DRTL) of the evolution of a many-body
quantum state in the presence of time-dependent control fields. The DRTL method is based …
quantum state in the presence of time-dependent control fields. The DRTL method is based …
Solving The Quantum Many-Body Hamiltonian Learning Problem with Neural Differential Equations
Understanding and characterising quantum many-body dynamics remains a significant
challenge due to both the exponential complexity required to represent quantum many-body …
challenge due to both the exponential complexity required to represent quantum many-body …
Many-body dynamics with explicitly time-dependent neural quantum states
Simulating the dynamics of many-body quantum systems is a significant challenge,
especially in higher dimensions where entanglement grows rapidly. Neural quantum states …
especially in higher dimensions where entanglement grows rapidly. Neural quantum states …
Fractional chern insulators in Hofstadter-Hubbard models
FA Palm - 2023 - edoc.ub.uni-muenchen.de
Seit der Entdeckung des integralen und des fraktionalen Quanten-Hall-Effekts in den
1980ern hat das Zusammenspiel topologischer Eigenschaften und starker …
1980ern hat das Zusammenspiel topologischer Eigenschaften und starker …