scholarly journals Erratum: Micromachined Integrated Quantum Circuit Containing a Superconducting Qubit [Phys. Rev. Applied 7 , 044018 (2017)]

2017 ◽  
Vol 8 (3) ◽  
Author(s):  
T. Brecht ◽  
Y. Chu ◽  
C. Axline ◽  
W. Pfaff ◽  
J. Z. Blumoff ◽  
...  
Keyword(s):  
Quantum Circuit ◽  
Superconducting Qubit

Experimental demonstration of optimized quantum process tomography on the IBM quantum experience

2020 ◽  
pp. 2040004
Author(s):  
Akshay Gaikwad ◽  
Krishna Shende ◽  
Kavita Dorai
Keyword(s):  
Quantum Circuit ◽  
Quantum Gates ◽  
Experimental Demonstration ◽  
Superconducting Qubit ◽  
Quantum Process ◽  
Single Qubit ◽  
Quantum Process Tomography ◽  
Process Tomography ◽  
Quantum Processor ◽  
Least Squares Optimization

We experimentally performed complete and optimized quantum process tomography of quantum gates implemented on superconducting qubit-based IBM QX2 quantum processor via two constrained convex optimization (CCO) techniques: least squares optimization and compressed sensing optimization. We studied the performance of these methods by comparing the experimental complexity involved and the experimental fidelities obtained. We experimentally characterized several two-qubit quantum gates: identity gate, a controlled-NOT gate, and a SWAP gate. The general quantum circuit is efficient in the sense that the data needed to perform CCO-based process tomography can be directly acquired by measuring only a single qubit. The quantum circuit can be extended to higher dimensions and is also valid for other experimental platforms.

scholarly journals Hybrid Quantum Circuit with a Superconducting Qubit Coupled to a Spin Ensemble

2011 ◽  
Vol 107 (22) ◽  
Author(s):  
Y. Kubo ◽  
C. Grezes ◽  
A. Dewes ◽  
T. Umeda ◽  
J. Isoya ◽  
...  
Keyword(s):  
Quantum Circuit ◽  
Superconducting Qubit

scholarly journals Improved Superconducting Qubit State Readout by Path Interference

2021 ◽  
Vol 38 (11) ◽  
pp. 110303
Author(s):  
Zhiling Wang ◽  
Zenghui Bao ◽  
Yukai Wu ◽  
Yan Li ◽  
Cheng Ma ◽  
...  
Keyword(s):  
Quantum Information Processing ◽  
Quantum Circuit ◽  
Qubit State ◽  
Microwave Cavity ◽  
Single Shot ◽  
Superconducting Qubit ◽  
Constructive Interference ◽  
State Discrimination ◽  
Convenient Approach ◽  
Photon States

High fidelity single shot qubit state readout is essential for many quantum information processing protocols. In superconducting quantum circuit, the qubit state is usually determined by detecting the dispersive frequency shift of a microwave cavity from either transmission or reflection. We demonstrate the use of constructive interference between the transmitted and reflected signal to optimize the qubit state readout, with which we find a better resolved state discrimination and an improved qubit readout fidelity. As a simple and convenient approach, our scheme can be combined with other qubit readout methods based on the discrimination of cavity photon states to further improve the qubit state readout.

scholarly journals Quantum computed moments correction to variational estimates

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 373
Author(s):  
Harish J. Vallury ◽  
Michael A. Jones ◽  
Charles D. Hill ◽  
Lloyd C. L. Hollenberg
Keyword(s):  
Quantum Circuit ◽  
Variational Calculation ◽  
Order Effects ◽  
Quantum Magnetism ◽  
Superconducting Qubit ◽  
Problem Size ◽  
Variational Calculations ◽  
State Variation ◽  
Random Coupling ◽  
Trial State

The variational principle of quantum mechanics is the backbone of hybrid quantum computing for a range of applications. However, as the problem size grows, quantum logic errors and the effect of barren plateaus overwhelm the quality of the results. There is now a clear focus on strategies that require fewer quantum circuit steps and are robust to device errors. Here we present an approach in which problem complexity is transferred to dynamic quantities computed on the quantum processor – Hamiltonian moments, ⟨Hn⟩. From these quantum computed moments, an estimate of the ground-state energy can be obtained using the ``infimum'' theorem from Lanczos cumulant expansions which manifestly corrects the associated variational calculation. With higher order effects in Hilbert space generated via the moments, the burden on the trial-state quantum circuit depth is eased. The method is introduced and demonstrated on 2D quantum magnetism models on lattices up to 5×5 (25 qubits) implemented on IBM Quantum superconducting qubit devices. Moments were quantum computed to fourth order with respect to a parameterised antiferromagnetic trial-state. A comprehensive comparison with benchmark variational calculations was performed, including over an ensemble of random coupling instances. The results showed that the infimum estimate consistently outperformed the benchmark variational approach for the same trial-state. These initial investigations suggest that the quantum computed moments approach has a high degree of stability against trial-state variation, quantum gate errors and shot noise, all of which bodes well for further investigation and applications of the approach.

scholarly journals Robustly decorrelating errors with mixed quantum gates

2021 ◽  
Author(s):  
Anthony Polloreno ◽  
Kevin Young
Keyword(s):  
Optimal Control ◽  
Quantum Information ◽  
Marked Reduction ◽  
Quantum Circuit ◽  
Physical Review ◽  
Quantum Gates ◽  
Superconducting Qubit ◽  
Convex Programs ◽  
Quantum Operations ◽  
Quantum Optimal Control

Abstract Coherent errors in quantum operations are ubiquitous. Whether arising from spurious environmental couplings or errors in control fields, such errors can accumulate rapidly and degrade the performance of a quantum circuit significantly more than an average gate fidelity may indicate. As shown by Hastings [1] and Campbell [2], by replacing the deterministic implementation of a quantum gate with a randomized ensemble of implementations, one can dramatically suppress coherent errors. Our work begins by reformulating the results of Hastings and Campbell as a quantum optimal control problem. We then discuss a family of convex programs able to solve this problem, as well as a set of secondary objectives designed to improve the performance, implementability, and robustness of the resulting mixed quantum gates. Finally, we implement these mixed quantum gates on a superconducting qubit and discuss randomized benchmarking results consistent with a marked reduction in the coherent error. [1] M. B. Hastings, Quantum Information & Computation 17, 488 (2017). [2] E. Campbell, Physical Review A 95, 042306 (2017).

scholarly journals Micromachined Integrated Quantum Circuit Containing a Superconducting Qubit

2017 ◽  
Vol 7 (4) ◽  
Author(s):  
T. Brecht ◽  
Y. Chu ◽  
C. Axline ◽  
W. Pfaff ◽  
J. Z. Blumoff ◽  
...  
Keyword(s):  
Quantum Circuit ◽  
Superconducting Qubit

scholarly journals Spectrum of the Dicke model in a superconducting qubit-oscillator system

2019 ◽  
Vol 99 (6) ◽  
Author(s):  
S. Ashhab ◽  
Y. Matsuzaki ◽  
K. Kakuyanagi ◽  
S. Saito ◽  
F. Yoshihara ◽  
...  
Keyword(s):  
Superconducting Qubit ◽  
Oscillator System ◽  
Dicke Model

scholarly journals A divide-and-conquer algorithm for quantum state preparation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Israel F. Araujo ◽  
Daniel K. Park ◽  
Francesco Petruccione ◽  
Adenilton J. da Silva
Keyword(s):  
Computational Cost ◽  
Quantum Circuit ◽  
Divide And Conquer ◽  
Computational Time ◽  
Quantum Computers ◽  
Dimensional Vector ◽  
Quantum Devices ◽  
Divide And Conquer Algorithm ◽  
Quantum State Preparation ◽  
Quantum Device

AbstractAdvantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states require quantum circuits with depth O(N) to load an N-dimensional vector. Here, we show that it is possible to load an N-dimensional vector with exponential time advantage using a quantum circuit with polylogarithmic depth and entangled information in ancillary qubits. Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space. We demonstrate a proof of concept on a real quantum device and present two applications for quantum machine learning. We expect that this new loading strategy allows the quantum speedup of tasks that require to load a significant volume of information to quantum devices.

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