HQS Noise App User Guide

The HQS Noise App offers a novel approach to mapping problems from diverse fields such as chemistry, materials science, and other quantum mechanical problems onto a quantum computer. What sets the HQS Noise App apart is its scalable approach to quantum simulation based on simulating time evolutions. This approach is designed for simulation of mixed systems, e.g. spins coupled to fermions or bosons, which can be relevant for effects like light-matter interactions or microscopic vibrations in materials. In addition, it provides novel capabilities for applications like quantum machine learning. While the HQS Noise App is primarily tailored to NISQ devices, its relevance and significance extends to the era of fully error-corrected quantum computing. The Phase Estimation Algorithm, a key component for conducting quantum simulations on error-corrected quantum hardware, is grounded on the principle of time evolution. This principle is the cornerstone of the HQS Noise App, highlighting its continuing importance in quantum computing.

The HQS NoiseApp ca be used from two different perspectives:

To derive effective noisy algorithm models to gain insights into the effects of noise during circuit execution.
To use the noisy algorithm model to create optimized system-bath quantum circuits to simulate a open quantum system of interest on a noisy quantum computer.

The theoretical foundations to this software package have been published in two arxiv papers: noise mapping and bath fitting.

For a detailed scientific discussion we refer the readers to the arxiv papers. This User Guide will provide a concise summary of the fundamental physical concepts and an introduction to the Python interface of this software package.

Fundamental physical concepts

Noise models

We consider physical noise, meaning noise on the hardware-level, that is caused by qubits coupling to some fluctuating environment either during control operations or at all times. This is assumed to cause damping, dephasing, and/or depolarization of their quantum states. Our model of a noisy quantum computer is based on adding corresponding non-unitary (noise) operations after or before (ideal) unitary gate operations. This model is described in detail on page modeling.

Noise mapping

The first use of the HQS Noise App is to investigate how noise affects gate-based quantum simulation of noiseless systems. Particularly, it solves the Lindblad open-system model that the noisy quantum hardware is effectively running. Foundations of this mapping (between physical and simulated noise) are discussed on page mapping or in more detail in this arxiv paper. The shown mathematical derivation may be somewhat cumbersome in some places, but luckily the mathematics of connecting physical and effective noise for arbitrary quantum algorithms is done automatically by the HQS Noise App.

The system-bath approach

The second functionality of the HQS Noise App is to design system-bath quantum circuits to simulate an open quantum system of interest with the help of the physical noise on a quantum computer, thus turning parts of the noise on the device into a resource for computation. The basis of the system-bath approach is discussed in the system bath section of this user guide or in the arxiv paper.

Using the program

Python interface

On the interface page, we go through the Python interface of the HQS Noise App and discuss how to extract the noisy algorithm model, how to create system-bath simulation circuits, and how to fit a system-bath on a quantum computer to given bosonic baths, fermionic baths or a given spectral function.

HQS Noise App User Documentation