A novel approach to noisy gates for simulating quantum computers

We present a novel method for simulating the noisy behaviour of quantum computers, which allows to efficiently incorporate environmental effects in the driven evolution implementing the gates acting on the qubits. We show how to modify the noiseless gate executed by the computer to include any Markovian noise, hence resulting in what we will call a noisy gate. We compare our method with the IBM Qiskit simulator, and show that it follows more closely both the analytical solution of the Lindblad equation as well as the behaviour of a real quantum computer, where we ran algorithms involving up to 18 qubits; as such, our protocol offers a more accurate simulator for NISQ devices. The method is flexible enough to potentially describe any noise, including non-Markovian ones. The noise simulator based on this work is available as a python package at this link: https://pypi.org/project/quantum-gates

Rieger, C., Di Marcantonio, F., Wixinger, R. "Quantum Computing Applications and Use-cases"

Abstract In this introduction to the foundations of quantum machine learning, we will dive into key concepts such as data encoding, feature map selection, and the comparison of different metrics for quantum kernel estimation. By the end of the session, students should be able to understand the basic steps and considerations in implementing and assessing quantum algorithms for machine learning. Bio Francesco Di Marcantonio Francesco is a PhD student at CERN and University of the Basque Country. He studied at KTH and Politecnico di Torino and focuses on the simulation of Quantum Matter with Tensor Network Methods and other techniques related to Quantum Computation. Roman Wixinger Roman is a Software Engineer with a background in Physics. He studied at ETH Zurich and does research in Quantum Computing and Particle Physics at CERN and the University of Tokyo

A novel approach to noisy gates for simulating quantum computers

We present a novel method for simulating the noisy behaviour of quantum computers, which allows to efficiently incorporate environmental effects in the driven evolution implementing the gates acting on the qubits. We show how to modify the noiseless gate executed by the computer to include any Markovian noise, hence resulting in what we will call a noisy gate. We compare our method with the IBM Qiskit simulator, and show that it follows more closely both the analytical solution of the Lindblad equation as well as the behaviour of a real quantum computer, where we ran algorithms involving up to 18 qubits; as such, our protocol offers a more accurate simulator for NISQ devices. The method is flexible enough to potentially describe any noise, including non-Markovian ones. The noise simulator based on this work is available as a python package at this link: https://pypi.org/project/quantum-gates