HQS Noise App

Quantum algorithms for open quantum systems

HQStage Module

Quantum Computing

The HQS Noise App is a poweful software package, which harnesses the power of quantum computers for quantum simulation of open quantum systems and has interesting capabilities for applications such as quantum machine learning. This unique tool offers a novel approach to the mapping of problems, from diverse fields such as chemistry, materials science, and other quantum mechanical challenges, onto a quantum computer.

Scalable approaches from NISQ to error-corrected quantum computers

What sets the HQS Noise App apart is its scalable approach to quantum simulations. This scalability ensures that the app remains relevant and effective as technology advances. It is perfectly suited for the current generation of noisy intermediate-scale quantum (NISQ) computers, but is also designed with the future in mind, allowing for easy portability to the fully error-corrected quantum computers of tomorrow. In essence, the HQS Noise App is not just a tool for today's quantum computing needs, but a bridge to the quantum future, ready to evolve and adapt as quantum technology continues to advance.

Benefits

  • Implements the simulation of mixed systems, e.g. spins coupled to fermions or bosons, which can be relevant for effects like light-matter interaction or microscopic vibrations in materials.

  • Has a unique approach to quantum simulation, which focuses on simulating full time evolutions. This is a scalable approach which maximizes the power of the quantum computer and directly connects to the future of using fully error corrected quantum computers.

  • Can derive a continuous closed-form master equation description of a noisy quantum computer performing a quantum simulation.

  • The easiest way to enter the world of dissipative time evolution and non-unitary gates, which is the most promising path to quantum advantage.

Get Your Free Trial now!

Features

  • Convenient implementation of quantum algorithms to simulate the time evolution of spin Hamiltonians.

  • Special algorithms for the time evolution of system-bath spin-problems.

  • Automatic conversion of spin-fermion and spin-boson open quantum systems to spin-spin system-bath models that can be time propagated with the quantum computer.

  • Create optimized system-bath quantum circuits based on the device and noise information for simulating open quantum systems.

  • Add device and noise information of your problem into the HQS Noise App, where quantum circuits are automatically adjusted accordingly.

  • Derive effective noisy algorithm models for incoherent time propagation to gain insights into the effects of noise during circuit execution.

  • Various options to tweak quantum circuits to use device noise more effectively (e.g. symmetrization and additional waiting times).

  • Python interface for easy usage and integration.

Use Case

The HQS Noise App is beneficial to developers and researchers working in the field of quantum computing. Developers can use a scalable quantum algorithm implemented in the HQS Noise App to develop approaches for quantum simulation and potentially for quantum machine learning. Researchers can study the effects of noise on gate-based quantum simulations and design system-bath quantum circuits for simulating open quantum systems.

Example of classifying a Hamiltonian as ferromagnetic or anti-ferromagnetic using time propagation on a noisy quantum computer.

The HQS Noise App can provide an open system model for the time propagation on a noisy quantum computer. The time evolution under the noisy algorithm model, matches a full simulation of the quantum computer. For more details, see also the HQS Noise App examples and the following paper: Describing Trotterized Time Evolutions on Noisy Quantum Computers via Static Effective Lindbladians

The HQS Noise App can approximate a fermionic bath with the help of the available qubits on a quantum computer. The spectral function of a fermionic bath can be approximated with only three bosonic modes, which can be represented by three qubits on the quantum computer (in the simplest case). For more details see the HQS Noise App examples and the following paper: A quantum algorithm for solving open system dynamics on quantum computers using noise

What Customers Are Saying

“In the BASIQ project of the DLR Quantum Computing Initiative (DLR QCI), we use the HQS Noise App to understand how the noise present on the hardware can be utilised to simulate battery materials. The effect of the noise strongly depends on the exact circuit we use for the simulation. With the HQS Noise App, we have a framework at hand with which we can investigate exactly that.”

— German Aerospace Center (DLR)
Dr. Alejandro D. Somoza | Research Scientist

“In collaboration with HQS, we have advanced our understanding of noise effects on NMR spectra. The user-friendly HQS Noise App simplifies circuit design and implementation, providing accurate simulations in noisy quantum environments. Its exceptional capabilities tailored for noisy quantum computers allow for seamless creation of circuits for trotterized time evolution, shedding light on the impact of noise during circuit execution. Our journey in quantum computing has been significantly enhanced by the HQS Noise App, with cloud access and compatibility with open-source backends."

—Forschungszentrum Jülich
Prof. Dr. Frank Wilhelm-Mauch | Quantum Physicist

Related Case Study

Empfohlen
MANIQU: Efficient material simulation on NISQ quantum computers
MANIQU: Efficient material simulation on NISQ quantum computers

In collaboration with Bosch, BASF SE, Friedrich-Alexander-Universität Erlangen, and Heinrich-Heine-Universität Düsseldorf, HQS leads the MANIQU project. Focused on quantum material simulations, HQS introduces the HQS Spin Mapper for transition metal-containing materials. Addressing challenges in simulating strongly correlated electron systems, the project explores NISQ devices' accuracy for material properties. HQS's hybrid algorithms, integrated into the Noise App, enable real-time quantum simulations, a breakthrough for properties beyond the ground state. The Spin Mapper facilitates electronic system simulation on NISQ devices through spin interactions, uncovering unexplored possibilities. Additionally, the enhanced Qolossal tool offers precise simulations of large material sections, incorporating temperature, topological effects, and more. HQS's role in workflow integration ensures a commercially usable application, accessible remotely via a cloud-based platform. This collaboration pioneers quantum-driven innovations for future markets.

Read More →

Theoretical Background

Empfohlen
Demonstration of system-bath physics on gate-based quantum computer
Demonstration of system-bath physics on gate-based quantum computer

Authors: Pascal Stadler, Matteo Lodi, Andisheh Khedri, Rolando Reiner, Kirsten Bark, Nicolas Vogt, Michael Marthaler, and Juha Leppäkangas

We demonstrate algorithmic cooling on IBM-Q devices. We utilize inherent qubit noise to simulate the equilibration of an interacting spin system towards its ground state, when coupled to a dissipative auxiliary-spin bath. The steady-state correlations in the system are defined by the system Hamiltonian and are stable as long as the algorithm can be executed. In particular, we demonstrate the relaxation of system spins to ferromagnetic and antiferromagnetic ordering, controlled by the definition of the system Hamiltonian. We are able to perform simulated cooling for global systems of up to three system spins and four auxiliary spins.

Read More →
A quantum algorithm for solving open system dynamics on quantum computers using noise
A quantum algorithm for solving open system dynamics on quantum computers using noise

Authors: Juha Leppäkangas, Nicolas Vogt, Keith R. Fratus, Kirsten Bark, Jesse A. Vaitkus, Pascal Stadler, Jan-Michael Reiner, Sebastian Zanker, Michael Marthaler

In this paper, we present a quantum algorithm that uses noise as a resource. The goal of our quantum algorithm is the calculation of operator averages of an open quantum system evolving in time. Selected low-noise system qubits and noisy bath qubits represent the system and the bath of the open quantum system. All incoherent qubit noise can be mapped to bath spectral functions. The form of the spectral functions can be tuned digitally, allowing for the time evolution of a wide range of open-system models at finite temperatures. We study the feasibility of this approach with a focus on the solution of the spin-boson model and assume intrinsic qubit noise that is dominated by damping and dephasing. We find that classes of open quantum systems exist where our algorithm performs very well, even with gate errors as high as 1%. In general, the presented algorithm performs best if the system-bath interactions can be decomposed into native gates.

Read More →
Describing Trotterized Time Evolutions on Noisy Quantum Computers via Static Effective Lindbladians
Describing Trotterized Time Evolutions on Noisy Quantum Computers via Static Effective Lindbladians

Authors: Keith R. Fratus, Kirsten Bark, Nicolas Vogt, Juha Leppäkangas, Sebastian Zanker, Michael Marthaler, Jan-Michael Reiner
We consider the extent to which a noisy quantum computer is able to simulate the time evolution of a quantum spin system in a faithful manner. Given a specific set of assumptions regarding the manner in which noise acting on such a device can be modeled at the circuit level, we show how the effects of noise can be reinterpreted as a modification to the dynamics of the original system being simulated. In particular, we find that this modification corresponds to the introduction of static Lindblad noise terms, which act in addition to the original unitary dynamics. The form of these noise terms depends not only on the underlying noise processes occurring on the device but also on the original unitary dynamics, as well as the manner in which these dynamics are simulated on the device, i.e., the choice of a quantum algorithm. We call this effectively simulated open quantum system the noisy algorithm model. Our results are confirmed through numerical analysis.

Read More →

Get started with HQStage

HQStage can be managed using our intuitive Cloud website.