| 1. |
- Rosenberg, D., et al.
(författare)
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3D integrated superconducting qubits
- 2017
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Ingår i: npj Quantum Information. - : Springer Science and Business Media LLC. - 2056-6387. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- As the field of quantum computing advances from the few-qubit stage to larger-scale processors, qubit addressability and extensibility will necessitate the use of 3D integration and packaging. While 3D integration is well-developed for commercial electronics, relatively little work has been performed to determine its compatibility with high-coherence solid-state qubits. Of particular concern, qubit coherence times can be suppressed by the requisite processing steps and close proximity of another chip. In this work, we use a flip-chip process to bond a chip with superconducting flux qubits to another chip containing structures for qubit readout and control. We demonstrate that high qubit coherence (T1, T2, echo > 20 μs) is maintained in a flip-chip geometry in the presence of galvanic, capacitive, and inductive coupling between the chips.
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| 2. |
- Gustavsson, S., et al.
(författare)
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Suppressing relaxation in superconducting qubits by quasiparticle pumping
- 2016
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 354:6319, s. 1573-1577
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Tidskriftsartikel (refereegranskat)abstract
- Copyright 2016 by the American Association for the Advancement of Science; all rights reserved.Dynamical error suppression techniques are commonly used to improve coherence in quantum systems.They reduce dephasing errors by applying control pulses designed to reverse erroneous coherent evolution driven by environmental noise. However, such methods cannot correct for irreversible processes such as energy relaxation.We investigate a complementary, stochastic approach to reducing errors: Instead of deterministically reversing the unwanted qubit evolution, we use control pulses to shape the noise environment dynamically. In the context of superconducting qubits, we implement a pumping sequence to reduce the number of unpaired electrons (quasiparticles) in close proximity to the device. A 70%reduction in the quasiparticle density results in a threefold enhancement in qubit relaxation times and a comparable reduction in coherence variability.
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| 3. |
- Kjaergaard, M., et al.
(författare)
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Demonstration of Density Matrix Exponentiation Using a Superconducting Quantum Processor
- 2022
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Ingår i: Physical Review X. - 2160-3308. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Quantum computers hold the potential to outperform classical supercomputers at certain tasks. To implement algorithms on a quantum computer, programmers use conventional computers and hardware to create a set of classical control signals that implement a desired quantum algorithm. However, feeding the quantum information forward requires an inefficient conversion: extraction of quantum information, conversion to classical control signals, and reinjection of those signals into the system to implement quantum operations. Here, we demonstrate a more natively quantum strategy to programming quantum computers. Our approach uses the density matrix exponentiation (DME) protocol, a general technique for using a quantum state to enact a quantum operation. It can be thought of as a subroutine with which programmers can turn multiple copies of a quantum state into instructions for next steps in a quantum algorithm.We implement DME using two qubits in a superconducting quantum processor. Our implementation relies on a high-fidelity two-qubit gate and a novel technique called quantum measurement emulation to approximately reset a known quantum state. These developments enable us to demonstrate the DME protocol for the first time on a small-scale quantum processor and benchmark its performance.While DME was originally proposed in the context of a specific quantum machine-learning algorithm, it may also represent a fundamentally different approach to quantum programming. It allows the possibility of encoding quantum algorithms directly into quantum states and executing those algorithms on other quantum states, enabling a new class of efficient quantum algorithms.
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