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In this paper we derive from simple and reasonable assumptions a Gaussian noise model for NISQ Quantum Amplitude Estimation (QAE). We provide results from QAE run on various IBM superconducting quantum computers and Honeywells H1 trapped-ion quantum computer to show that the proposed model is a good fit for real-world experimental data. We then give an example of how to embed this noise model into any NISQ QAE algorithm, such that the amplitude estimation is noise-aware.
This paper focuses on the quantum amplitude estimation algorithm, which is a core subroutine in quantum computation for various applications. The conventional approach for amplitude estimation is to use the phase estimation algorithm, which consists
Simultaneous quantum estimation of multiple parameters has recently become essential in quantum metrology. Although the ultimate sensitivity of a multiparameter quantum estimation in noiseless environments can beat the standard quantum limit that eve
A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise for large circuits involving many qubits and gates. We present a meth
Recently we find several candidates of quantum algorithms that may be implementable in near-term devices for estimating the amplitude of a given quantum state, which is a core subroutine in various computing tasks such as the Monte Carlo methods. One
We consider performing phase estimation under the following conditions: we are given only one copy of the input state, the input state does not have to be an eigenstate of the unitary, and the state must not be measured. Most quantum estimation algor