A software simulator for noisy quantum circuits

Chaudhary, Himanshu; Mahato, Biplab; Priyadarshi, Lakshya; Roshan, Naman; Utkarsh, .; Patel, Apoorva

doi:10.1142/s0129183122501030

Cited by 7 publications

(7 citation statements)

References 4 publications

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“…Te same can be obtained, the third column: Te upper part: (4, 3) corresponds to * 1V { }; the lower part: (8, 3) corresponds to 1 * V { }, (6, 3) corresponds to 10V { }, (5, 3) corresponds to 1V * { }; the last element in this column to be set to 0 (7,3) Corresponding to V1 * { }; Te fourth column will not be repeated; it can be seen that in the lower half, except for the last element to be set to 0 in each column, the even-numbered column corresponds to the matrix structure of the previous column (odd-numbered column), and the matrix of the oddnumbered column is determined by referring to the frst column.…”

Section: Te Matrix Structure Corresponding To the Secondmentioning

confidence: 75%

“…Te HHL quantum algorithm is faster than the ordinary computer basically algorithm. When using the problem, only the solution matrix is sparse, the number of preconditions for solving the matrix is relatively low, and the complexity of the time calculation for measuring the absolute value of the solution vector can be reduced from the previous computer's O (NK) to the HHL quantum algorithm [3].…”

Section: Methods and Principlesmentioning

confidence: 99%

“…) of the two-bit quantum circuit, and C 3 is set to * , that is: (3,2); Te lower part corresponds to the lower part of the frst column in order. Te matrix…”

Section: Te Matrix Structure Corresponding To the Secondmentioning

confidence: 99%

See 2 more Smart Citations

Analysis on Simplified Method of IoT-based HHL Algorithm Corresponding Quantum Circuit for Quantum Computer Application

Qian

2023

Mobile Information Systems

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Whether it is a traditional industry or a Frontier field, it has unveiled the trend of industrial IoT construction and application, which plays a vital role in building a strong manufacturing country and promoting high-quality economic development in China. HHL algorithm has become one of the important quantum algorithms, but there are few researches on the construction of quantum circuits and the application of quantum sequencing. In this paper, a model based on the quantum circuit corresponding to the HHL algorithm to deal with the quantum application problem is proposed. A quantum circuit based on HHL algorithm is used to solve the linear system, and the numerical solution of the target partial differential equation is obtained. Finally, the experimental analysis shows that, in the process of processing quantum computer application problems based on quantum circuit, it can reduce the computation amount of quantum circuit corresponding to HHL algorithm, improve the simulation efficiency of quantum circuit, and reduce the occupation of hardware resources, which has a certain effectiveness and superiority. This discussion brings new ideas for intelligent IoT technology and provides implications for the study of simplified methods of HHL algorithms corresponding to quantum circuits to deal with computer application problems.

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Section: Te Matrix Structure Corresponding To the Secondmentioning

confidence: 75%

Section: Methods and Principlesmentioning

confidence: 99%

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Analysis on Simplified Method of IoT-based HHL Algorithm Corresponding Quantum Circuit for Quantum Computer Application

Qian

2023

Mobile Information Systems

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“…The computational capability of the current generation quantum devices is considerably restricted due to poor qubit quality, limited qubit connectivity, and shorter coherence time. In general, in the case of the circuit execution on NISQ devices, this can be realized in terms of noise-induced errors in the system: (1) Memory errors, (2) Gate implementation errors, and (3) Measurement errors [39,40]. The effect of these errors on the result of circuit execution can be understood in the following way.…”

Section: Discussionmentioning

confidence: 99%

Circuit centric quantum architecture design

Azad

Papneja

Saini

et al. 2021

IET Quantum Communication

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With the development in the field of quantum physics, several methods for building a quantum computer have emerged. These differ in qubit technologies, interaction topologies, and noise characteristics. In this article, insights are given into the circuitcentric architecture design of Noisy Intermediate-Scale Quantum (NISQ) devices. The dependence of the circuit size, circuit depth on the interaction and connection between different qubits present in quantum hardware are discussed. A noise-aware procedure is presented which helps in determining the optimal interactions between different qubits of a quantum chip to execute a given circuit in the most efficient way possible. In this article, the 5-qubit hardware in a noiseless setting is illustrated with an example. Also, a benchmark-driven analysis is performed to show the importance of noise adaptivity in determining the hardware reliability. It is concluded that a generalized and flexible procedure such as this approach can aid in determining the design of hardware accurately for which the circuit runs efficiently, that is, with the least number of clock cycles, the lowest gate operations, and noise-based errors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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“…The quantum hardware that exists today are imperfect, as a result of which a computation being run on them may suffer various kinds of errors [28]. Therefore, in order to realistically simulate and characterize the per- formance of a parameterized quantum circuit (PQC), we must include these errors in our computation.…”

Section: A Effect Of Noisementioning

confidence: 99%

qLEET: Visualizing Loss Landscapes, Expressibility, Entangling Power and Training Trajectories for Parameterized Quantum Circuits

Azad,

Sinha

2022

Preprint

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We present qLEET, an open-source Python package for studying parameterized quantum circuits (PQCs), which are widely used in various variational quantum algorithms (VQAs) and quantum machine learning (QML) algorithms. qLEET enables computation of properties such as expressibility and entangling power of a PQC by studying its entanglement spectrum and the distribution of parameterized states produced by it. Furthermore, it allows users to visualize the training trajectories of PQCs along with high-dimensional loss landscapes generated by them for different objective functions. It supports quantum circuits and noise models built using popular quantum computing libraries such as Qiskit, Cirq, and Pyquil. In our work, we demonstrate how qLEET provides opportunities to design and improve hybrid quantum-classical algorithms by utilizing intuitive insights from the ansatz capability and structure of the loss landscape.

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A software simulator for noisy quantum circuits

Cited by 7 publications

References 4 publications

Analysis on Simplified Method of IoT-based HHL Algorithm Corresponding Quantum Circuit for Quantum Computer Application

Analysis on Simplified Method of IoT-based HHL Algorithm Corresponding Quantum Circuit for Quantum Computer Application

Circuit centric quantum architecture design

qLEET: Visualizing Loss Landscapes, Expressibility, Entangling Power and Training Trajectories for Parameterized Quantum Circuits

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