Neural-network-guided frequency optimization lowers measured single- and two-qubit gate errors on a superconducting chip and yields better VQE energies.
Spurious microwave crosstalk in floating superconducting circuits
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abstract
Crosstalk is a major concern in the implementation of large-scale quantum computation since it can degrade the performance of qubit addressing and cause gate errors. Finding the origin of crosstalk and separating contributions from different channels are essential prerequisites for figuring out crosstalk mitigation schemes. Here, by performing circuit analysis of two coupled floating transmon qubits, we demonstrate that, even if the stray coupling, e.g., between a qubit and the drive line of its nearby qubit, is absent, microwave crosstalk between qubits can still exist due to the presence of a spurious crosstalk channel. This channel arises from free modes, which are supported by the floating structure of transmon qubits, i.e., the two superconducting islands of each qubit with no galvanic connection to the ground. For various geometric layouts of floating transmon qubits, we give the contributions of microwave crosstalk from the spurious channel and show that this channel can become a performance-limiting factor in qubit addressing. This research could provide guidance for suppressing microwave crosstalk between floating superconducting qubits through the design of qubit circuits.
fields
quant-ph 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
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Neural Network-Based Frequency Optimization for Superconducting Quantum Chips
Neural-network-guided frequency optimization lowers measured single- and two-qubit gate errors on a superconducting chip and yields better VQE energies.