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Revista Mexicana de Física

Characterizing errors for Quantum Fourier Transform on IBM Q

Carolina Allende, André Fonseca de Oliveira, Efrain Buksman

Published Apr 5, 2022• 0 citations
Publisher

Abstract

The performance of today's quantum computers are affected by noise. This effect can be analyzed in the result of simple quantum algorithms in real quantum computers. The noise can be characterized as a decoherence error or a systematic error, the last could be corrected by a unitary rotation. In this article we propose two methods to model a systematic error, in the Quantum Fourier Transform algorithm (QFT). The first method uses the isotropic index presented in `` [1] and needs to reconstruct the density matrix of the experimental state, while the second method, although less general, only needs to reconstruct the reduced density matrices for each qubit. In both methods, a unitary transformation is proposed, which approximates the experimental result to the expected theoretical state. As an example, the QFT algorithm is analyzed for two qubit states, in quantum IBM Q computer ibmq\_santiago.

DOI
10.31349/revmexfis.68.031402

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The performance of today's quantum computers are affected by noise. This effect can be analyzed in the result of simple quantum algorithms in real quantum computers. The noise can be characterized as a decoherence error or a systematic error, the last could be corrected by a unitary rotation. In this article we propose two methods to model a systematic error, in the Quantum Fourier Transform algorithm (QFT). The first method uses the isotropic index presented in `` [1] and needs to reconstruct the density matrix of the experimental state, while the second method, although less general, only needs to reconstruct the reduced density matrices for each qubit. In both methods, a unitary transformation is proposed, which approximates the experimental result to the expected theoretical state. As an example, the QFT algorithm is analyzed for two qubit states, in quantum IBM Q computer ibmq_santiago.
We analyze the influence of errors on the implementation of the quantum Fourier transformation (QFT) on the Ising quantum computer (IQC). Two kinds of errors are studied: (i) due to spurious transitions caused by pulses and (ii) due to external perturbation. The scaling of errors with system parameters and number of qubits is explained. We use two different procedures to fight each of them. To suppress spurious transitions we use correcting pulses (generalized 2πk2πk2πk method) while to suppress errors due to external perturbation we use an improved QFT algorithm. As a result, the fidelity of quantum computation is increased by several orders of magnitude and is thus stable in a much wider range of physical parameters.
The Quantum Fourier Transform (QFT) grants competitive advantages, especially in resource usage and circuit approximation, for performing arithmetic operations on quantum computers, and offers a potential route towards a numerical quantum-computational paradigm. In this paper, we utilize efficient techniques to implement QFT-based integer addition and multiplications. These operations are fundamental to various quantum applications including Shor's algorithm, weighted sum optimization problems in data processing and machine learning, and quantum algorithms requiring inner products. We carry out performance evaluations of these implementations based on IBM's superconducting qubit architecture using different compatible noise models. We isolate the sensitivity of the component quantum circuits on both one-/two-qubit gate error rates, and the number of the arithmetic operands' superposed integer states. We analyze performance, and identify the most effective approximation depths for quantum add and quantum multiply within the given context. We observe significant dependency of the optimal approximation depth on the degree of machine noise and the number of superposed states in certain performance regimes. Finally, we elaborate on the algorithmic challenges - relevant to signed, unsigned, modular and non-modular versions - that could also be applied to current implementations of QFT-based subtraction, division, exponentiation, and their potential tensor extensions. We analyze performance trends in our results and speculate on possible future development within this computational paradigm.
The results of quantum process tomography on a three-qubit nuclear magnetic resonance quantum information processor are presented and shown to be consistent with a detailed model of the system-plus-apparatus used for the experiments. The quantum operation studied was the quantum Fourier transform, which is important in several quantum algorithms and poses a rigorous test for the precision of our recently developed strongly modulating control fields. The results were analyzed in an attempt to decompose the implementation errors into coherent (overall systematic), incoherent (microscopically deterministic), and decoherent (microscopically random) components. This analysis yielded a superoperator consisting of a unitary part that was strongly correlated with the theoretically expected unitary superoperator of the quantum Fourier transform, an overall attenuation consistent with decoherence, and a residual portion that was not completely positive-although complete positivity is required for any quantum operation. By comparison with the results of computer simulations, the lack of complete positivity was shown to be largely a consequence of the incoherent errors which occurred over the full quantum process tomography procedure. These simulations further showed that coherent, incoherent, and decoherent errors can often be identified by their distinctive effects on the spectrum of the overall superoperator. The gate fidelity of the experimentally determined superoperator was 0.64, while the correlation coefficient between experimentally determined superoperator and the simulated superoperator was 0.79; most of the discrepancies with the simulations could be explained by the cumulative effect of small errors in the single qubit gates.
We analyze the influence of errors on the implementation of the quantum Fourier transformation. Two kinds of errors are studied: (i) systematic errors due to off-resonant transitions and (ii) errors due to an external perturbation. The scaling of errors with system parameters and the number of qubits is analyzed. To suppress off-resonant transitions, we use correcting pulses while in order to suppress errors due to an external perturbation, we use an improved quantum Fourier transformation algorithm. As a result, the fidelity of quantum computation is increased by several orders of magnitude and is thus stable in a much wider range of physical parameters.
We analyze the basic aspects of the quantum information theory, namely the quantum version of the theory that is behind all the classical implementations like computers and communications. We focus on quantum computation, defining its fundamental unit: the qubit, namely a quantum two-level system that will be described in detail in this thesis. We then concentrate on the possible transformations gates that can be applied to qubits, both unitary and non-unitary ones. The challenges in the construction of qubits are impressive: in particular, it is difficult to isolate the system from the environment. This interaction is modeled by non-unitary transformations. The characteristic times connected to these processes are the relaxation time, the time in which a state decays in another state, and the decoherence time, the time in which quantum coherence is lost. These times are fundamental in quantum computing since they quantify how many operations can be performed on qubits and still obtain reliable results. We measure these characteristic times on the IBM quantum processor ’ibmq_16_melbourne’ performing three different experiments: one for the relaxation time and two for the decoherence time, namely Ramsey and Echo experiments. Finally, we implement a quantum algorithm, an algorithm that uses the resources of quantum mechanics, like entanglement. We focus on finding a protocol to define the quantum version of the elementary cellular automata, the quantum elementary cellular automata, and run it on the IBM processor. They are dynamical systems defined on a lattice in which the evolution is defined using simple local update rules. Comparing the physical results with theoretical expectations and noise-affected simulations we show the performance of the IBM processor.