Quantum computing crucially relies on the ability to efficiently characterize the quantum states output by quantum hardware. Conventional methods which probe these states through direct measurements and classically computed correlations become computationally expensive when increasing the system size. Quantum neural networks tailored to recognize specific features of quantum states by combining unitary operations, measurements and feedforward promise to require fewer measurements and to tolerate errors.
View Article and Find Full Text PDFQuantum computers hold the promise of solving computational problems that are intractable using conventional methods. For fault-tolerant operation, quantum computers must correct errors occurring owing to unavoidable decoherence and limited control accuracy. Here we demonstrate quantum error correction using the surface code, which is known for its exceptionally high tolerance to errors.
View Article and Find Full Text PDFPurpose: To identify facilitators and barriers associated with returning home for older adults having received inpatient rehabilitation after traumatic brain injury (TBI).
Methods: A qualitative design was used. Five older patients with TBI and four family caregivers were interviewed and six healthcare professionals participated in a focus group.
High fidelity two-qubit gates exhibiting low cross talk are essential building blocks for gate-based quantum information processing. In superconducting circuits, two-qubit gates are typically based either on rf-controlled interactions or on the in situ tunability of qubit frequencies. Here, we present an alternative approach using a tunable cross-Kerr-type ZZ interaction between two qubits, which we realize with a flux-tunable coupler element.
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