G. Jin
Please Note
4 records found
1
Topology in engineered quantum systems
Device design and artificial material implementation
I study four questions through theoretical analysis and proposed experimental implementations: Can topological edge states stabilize quantum entanglement? How can topological phase transitions be controlled and measured? What are the practical limitations of topological protection in finite systems? How do topological quantum walks relate to quantum algorithms?
The results show that topological edge states do stabilize entangled Bell states against parameter fluctuations compared to trivial states. Real-time tuning of SSH arrays enables tracking of topological phase transitions and mid-gap state evolution. However, conventional topological invariants can mislead in finite systems, to which I propose a criterion bridging experimentally measurable quantities with real-space topology. Finally, discrete-time quantum walks on topological systems exhibit localization phenomena reminiscent of quantum search algorithms.
This work demonstrates that simple topological models can be implemented in realistic quantum hardware, revealing both the potential and limitations of topological protection in finite, noisy systems. The results inform future applications in quantum simulation and algorithm design while providing practical guidance for engineering topological features in quantum technologies.
...
I study four questions through theoretical analysis and proposed experimental implementations: Can topological edge states stabilize quantum entanglement? How can topological phase transitions be controlled and measured? What are the practical limitations of topological protection in finite systems? How do topological quantum walks relate to quantum algorithms?
The results show that topological edge states do stabilize entangled Bell states against parameter fluctuations compared to trivial states. Real-time tuning of SSH arrays enables tracking of topological phase transitions and mid-gap state evolution. However, conventional topological invariants can mislead in finite systems, to which I propose a criterion bridging experimentally measurable quantities with real-space topology. Finally, discrete-time quantum walks on topological systems exhibit localization phenomena reminiscent of quantum search algorithms.
This work demonstrates that simple topological models can be implemented in realistic quantum hardware, revealing both the potential and limitations of topological protection in finite, noisy systems. The results inform future applications in quantum simulation and algorithm design while providing practical guidance for engineering topological features in quantum technologies.
Topological properties of quantum systems are among the most intriguing emerging phenomena in condensed matter physics. A crucial property of topological systems is the symmetry-protected robustness towards local noise. Experiments have demonstrated topological phases of matter in various quantum systems. However, using the robustness of such modes to stabilize quantum correlations is still a highly sought-after milestone. In this work, we put forward a concept of using topological modes to stabilize fully entangled quantum states, and we demonstrate the stability of the entanglement with respect to parameter fluctuations. Specifically, we see that entanglement remains stable against parameter fluctuations in the topologically nontrivial regime, while entanglement in the trivial regime is highly susceptible to local noise. We supplement our scheme with an experimentally realistic and detailed proposal based on coupled superconducting resonators and qubits. Our proposal sets an approach for generating long-lived quantum modes with robustness towards disorder in the circuit parameters via a bottom-up experimental approach relying on easy-to-engineer building blocks.
Large-scale quantum devices provide insights beyond the reach of classical simulations. However, for a reliable and verifiable quantum simulation, the building blocks of the quantum device require exquisite benchmarking. This benchmarking of large-scale dynamical quantum systems represents a major challenge due to lack of efficient tools for their simulation. Here, we present a scalable algorithm based on neural networks for Hamiltonian tomography in out-of-equilibrium quantum systems. We illustrate our approach using a model for a forefront quantum simulation platform: ultracold atoms in optical lattices. Specifically, we show that our algorithm is able to reconstruct the Hamiltonian of an arbitrary sized bosonic ladder system using an accessible amount of experimental measurements. We are able to significantly increase the previously known parameter precision.