8 papers
Hybrid Quantum-Classical Neural Networks for Recognizing Quantum Phases
Colin Scarato, Johannes Knörzer, Markus K. Hoffmann +11
Identifying quantum phases of matter is key to understanding strongly correlated materials, but remains a challenging task for both conventional computers and current quantum proce…
Hybrid quantum-classical neural network for sample-efficient recognition of topological phases
Markus K. Hoffmann, Leon C. Sander, Colin Scarato +4
With increasing maturity of quantum computers, standard methods for characterizing global properties of their output quantum states via direct measurements and classical post-proce…
Performance Characterization of a Multi-Module Quantum Processor with Static Inter-Chip Couplers
Graham J. Norris, Kieran Dalton, Dante Colao Zanuz +8
Three-dimensional integration technologies such as flip-chip bonding are a key prerequisite to realize large-scale superconducting quantum processors. Modular architectures, in whi…
Realizing a Continuous Set of Two-Qubit Gates Parameterized by an Idle Time
Colin Scarato, Kilian Hanke, Ants Remm +6
Continuous gate sets are a key ingredient for near-term quantum algorithms. Here, we demonstrate a hardware-efficient, continuous set of controlled arbitrary-phase ($\mathrm{C}Z_θ…
Calibrating Magnetic Flux Control in Superconducting Circuits by Compensating Distortions on Time Scales from Nanoseconds up to Tens of Microseconds
Christoph Hellings, Nathan Lacroix, Ants Remm +8
Fast tuning of the transition frequency of superconducting qubits using magnetic flux is essential, for example, for realizing high-fidelity two-qubit gates with low leakage or for…
Experimentally Informed Decoding of Stabilizer Codes Based on Syndrome Correlations
Ants Remm, Nathan Lacroix, Lukas Bödeker +9
High-fidelity decoding of quantum error correction codes relies on an accurate experimental model of the physical errors occurring in the device. Because error probabilities can de…