ANALYTIC ONE-BIT AND CNOT GATE CONSTRUCTIONS OF GENERAL n-QUBIT CONTROLLED GATES

2008 ◽  
Vol 06 (03) ◽  
pp. 447-462 ◽  
Author(s):  
YANG LIU ◽  
GUI LU LONG ◽  
YANG SUN
Keyword(s):  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing ◽  
The Other ◽  
General Construction ◽  
Cnot Gate ◽  
Construction Methods ◽  
Analytic Expressions

General n-qubit controlled unitary gates are frequently used in quantum information processing tasks. Barenco, Bennett, Cleve, Di Vincenzo, Margolus and Shor [Phys. Rev. A52 (1995) 3457] have given the general construction methods, and explicit results for up-to-four-qubits controlled unitary gates. We extended their calculation and gave two analytic expressions for the construction of general n-qubit controlled unitary gates in terms of one-qubit and two-qubit CNOT gates. There are two expressions – one is exponential in the qubit number which is efficient for up to ten qubits, and the other is polynomial in the qubit number, which is efficient for more than ten qubits.

scholarly journals Comparing the randomized benchmarking figure with the average infidelity of a quantum gate-set

2019 ◽  
Vol 17 (04) ◽  
pp. 1950031
Author(s):  
Jiaan Qi ◽  
Hui Khoon Ng
Keyword(s):  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing ◽  
The Other ◽  
Quantum Gate ◽  
High Fidelity ◽  
Number Formula

Randomized benchmarking (RB) is a popular procedure used to gauge the performance of a set of gates useful for quantum information processing (QIP). Recently, Proctor et al. [Phys. Rev. Lett. 119 (2017) 130502] demonstrated a practically relevant example where the RB measurements give a number [Formula: see text], very different from the actual average gate-set infidelity [Formula: see text], despite past theoretical assurances that the two should be equal. Here, we derive formulas for [Formula: see text], and for [Formula: see text] from the RB protocol, in a manner permitting easy comparison of the two. We show in general that, indeed, [Formula: see text], i.e. RB does not measure average infidelity, and, in fact, neither one bounds the other. We give several examples, all plausible in real experiments, to illustrate the differences in [Formula: see text] and [Formula: see text]. Many recent papers on experimental implementations of QIP have claimed the ability to perform high-fidelity gates because they demonstrated small [Formula: see text] values using RB. Our analysis shows that such a statement from RB alone has to be interpreted with caution.

Quantum Information Processing

2001 ◽  
Author(s):  
David P. DiVincenzo ◽  
Charles H. Bennett
Keyword(s):  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing

QCCM - Center for NMR Quantum Information Processing

2011 ◽  
Author(s):  
David G. Cory ◽  
Chandrasekhar Ramanathan ◽  
Raymond Laflamme ◽  
Joseph V. Emerson ◽  
Jonathan Baugh
Keyword(s):  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing

scholarly journals An improved novel quantum image representation and its experimental test on IBM quantum experience

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Su ◽  
Xuchao Guo ◽  
Chengqi Liu ◽  
Shuhan Lu ◽  
Lin Li
Keyword(s):  
Image Processing ◽  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing ◽  
Image Representation ◽  
Reference Value ◽  
Vertical Position ◽  
Quantum Image ◽  
Quantum Image Representation ◽  
Ibm Quantum Experience

AbstractQuantum image representation (QIR) is a necessary part of quantum image processing (QIP) and plays an important role in quantum information processing. To address the problems that NCQI cannot handle images with inconsistent horizontal and vertical position sizes and multi-channel image processing, an improved color digital image quantum representation (INCQI) model based on NCQI is proposed in this paper. The INCQI model can process color images and facilitate multi-channel quantum image transformations and transparency information processing of images using auxiliary quantum bits. In addition, the quantum image control circuit was designed based on INCQI. And quantum image preparation experiments were conducted on IBM Quantum Experience (IBMQ) to verify the feasibility and effectiveness of INCQI quantum image preparation. The prepared image information was obtained by quantum measurement in the experiment, and the visualization of quantum information was successfully realized. The research in this paper has some reference value for the research related to QIP.

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