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Experimental Monte Carlo quantum process certification.
L Steffen1, M P da Silva, A Fedorov
1Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland.
Physical Review Letters
|September 26, 2012
Summary
Quantum process tomography is too complex for current experiments. This study implements a faster Monte Carlo method to accurately determine the fidelity of multi-qubit quantum gates.
Area of Science:
- Quantum Information Processing
- Quantum Computing
- Experimental Quantum Physics
Background:
- Quantum process tomography is computationally intensive and time-consuming for current quantum processors.
- Characterizing quantum experiments with more than a few qubits is becoming impractical.
- New methods are needed to efficiently assess the performance of quantum gates.
Purpose of the Study:
- To experimentally implement and validate a novel, more practical approach for determining quantum process fidelity.
- To assess the fidelity of essential two- and three-qubit gates in a circuit quantum electrodynamics architecture.
- To demonstrate the feasibility of using Monte Carlo sampling for efficient quantum gate characterization.
Main Methods:
- Utilized a circuit quantum electrodynamics (cQED) platform for experimental implementation.
- Employed a recently proposed method comparing experimental data directly with an ideal process via Monte Carlo sampling.
- Focused on characterizing two-qubit gates (CPHASE, CNOT) and three-qubit gates (Toffoli, sequential CPHASE).
Main Results:
- Successfully implemented the Monte Carlo sampling scheme on a cQED system.
- Determined the fidelity of various two- and three-qubit quantum gates experimentally.
- Demonstrated the practicality and efficiency of this new method compared to traditional tomography.
Conclusions:
- The Monte Carlo sampling approach offers a practical and efficient alternative to quantum process tomography for characterizing quantum gates.
- This method is suitable for assessing the fidelity of complex quantum operations in experimental setups.
- The findings pave the way for more routine and scalable characterization of quantum processors.
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