Application of quantum simulations in hydrogen research

A software platform for quantum simulation

Goal

The AQUAS project aims to take hydrogen research and production to a new level by quantum simulation. Accurate simulation of electrolysis materials will enable the desired increase in process efficiency. This will be achieved by validating and implementing innovative software tools using hybrid classical-quantum algorithms. The focus will be on preparing algorithms that are ready for use on existing and future fault-aware hardware.

Motivation

Transition to hydrogen-based energy calls for increased efficiency in fuel cells and electrolyzers. Quantum-chemical atomistic simulations enable a more detailed view of the specific processes and materials, facilitating significant advances in the entire research field. However, the current state of research and available hardware limit the predictive power of these calculations. The use of hybrid algorithms, however, promises more precise computation. In this context, “hybrid” means that classical and quantum computers are closely intertwined.

Proceeding

Quantum mechanical simulation based on a combination of classical computers and quantum computers promises more accurate insights into relevant materials and catalysts for hydrogen production. This will be made possible by implementing two distinct approaches. The first will be to use variational quantum algorithms. The second will be a new approach for embedded simulations. Its main idea is to divide the material simulation problem into sub-problems, some of which are to be solved on the quantum computer and others using classical computation. Quantum machine learning (QML) methods will complement the procedure.

Key Facts

Project coordination

HQS Quantum Simulation GmbH

Supported by

Federal Ministry for Economic Affairs and Climate Action
Continuing Link
Grant Number: 01MQ22003A

Running time

January 2022 - December 2024

Budget

total: 3,5 Mio. €
Grants: 2,7 Mio. €

Consortium

Deutsches Zentrum für Luft- und Raumfahrt e.V.
German Aerospace Center

Institute of Engineering Thermodynamics, Stuttgart

Deutsches Zentrum für Luft- und Raumfahrt e.V.
German Aerospace Center

Institute for Software Technology, Köln

Fraunhofer
Institute for Manufacturing Engineering and Automation IPA, Stuttgart

HQS Quantum Simulations GmbH
(consortial leader)

Ulm University
Institute of Theoretical Chemistry

Papers

  • Variational algorithms such as the Quantum Approximate Optimization Algorithm have attracted attention due to their potential for solving problems using near-term quantum computers. The ZZ interaction typically generates the primitive two-qubit gate in such algorithms applied for a time, typically a variational parameter, γ. Different compilation techniques exist with respect to the implementation of two-qubit gates. Due to the importance of the ZZ-gate, we present an error analysis comparing the continuous-angle controlled phase gate (CP) against the fixed angle controlled Z-gate (CZ). We analyze both techniques under the influence of coherent over-rotation and depolarizing noise. We show that CP and CZ compilation techniques achieve comparable ZZ-gate fidelities if the incoherent error is below 0.03% and the coherent error is below 0.8%. Thus, we argue that for small coherent and incoherent error a non-parameterized two-qubit gate such as CZ in combination with virtual Z decomposition for single-qubit gates could lead to a significant reduction in the calibration required and, therefore, a less error-prone quantum device. We show that above a coherent error of 0.04π (2%), the CZ gate fidelity depends significantly on γ.

  • In this work, we propose a multi-scale protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged-Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points on the path are fitted with a machine-learning technique (in our case symmetric gradient domain machine learning or sGDML) to produce a semi-local reactive Potential Energy Surface (PES), embracing reactants, products and transition state (TS) regions. This approach has been successfully applied to a unimolecular (Bergman cyclization of enediyne) and a bimolecular (SN2 substitution) reaction. In particular, we demonstrate that with only 50 to 150 energy-force evaluations with the accurate reference methods (here CASSCF and CCSD) it is possible to construct a semi-local PES giving qualitative agreement for stationary-point geometries, intrinsic reaction-coordinates and barriers. Furthermore, we find a qualitative agreement in vibrational frequencies and reaction rate coefficients. The key aspect of the method's performance is its multi-scale nature, which not only saves computational effort but also allows extracting meaningful information along the reaction path, characterized by zero gradients in all but one direction. Agnostic to the nature of the TS and computationally economic, the protocol can be readily automated and routinely used for mechanistic reaction studies.

Contact

Dr. Vladimir Rybkin

Grant Manager of AQUAS

HQS Quantum Simulations GmbH
Rintheimer Straße 23
D-76131 Karlsruhe

E-Mail: vladimir.rybkin@quantumsimulations.de

Dr. Michael Marthaler

CEO and Co-Founder
HQS Quantum Simulations GmbH

HQS Quantum Simulations GmbH
Rintheimer Straße 23
D-76131 Karlsruhe

E-Mail: michael.marthaler@quantumsimulations.de