Open Source Variational Quantum Eigensolver Extension of the Quantum Learning Machine (QLM) for Quantum Chemistry

TL;DR

The work presents OpenVQE, an open-source extension of the Atos QLM for quantum chemistry that pairs a flexible VQE framework with the myQLM-fermion module. It enables implementation and testing of chemically inspired UCC and adaptive ADAPT-VQE strategies, supporting excitations beyond UCCSD and offering a robust simulation environment up to tens of qubits. Through extensive noiseless benchmarks on molecules with 4–24 qubits, the authors demonstrate how active-space selection, MP2 pre-screening, and adaptive ansätze can improve chemical accuracy while managing circuit depth and parameter counts. The combination of OpenVQE with myQLM-fermion and QLM’s interoperability provides a scalable, open platform for developing, benchmarking, and deploying variational quantum algorithms for quantum chemistry on current and near-term quantum hardware.

Abstract

Quantum Chemistry (QC) is one of the most promising applications of Quantum Computing. However, present quantum processing units (QPUs) are still subject to large errors. Therefore, noisy intermediate-scale quantum (NISQ) hardware is limited in terms of qubits counts and circuit depths. Specific algorithms such as Variational Quantum Eigensolvers (VQEs) can potentially overcome such issues. We introduce here a novel open-source QC package, denoted Open-VQE, providing tools for using and developing chemically-inspired adaptive methods derived from Unitary Coupled Cluster (UCC). It facilitates the development and testing of VQE algorithms. It is able to use the Atos Quantum Learning Machine (QLM), a general quantum programming framework enabling to write, optimize and simulate quantum computing programs. Along with Open-VQE, we introduce myQLM-Fermion, a new open-source module (that includes the key QLM ressources that are important for QC developments (fermionic second quantization tools etc...). The Open-VQE package extends therefore QLM to QC providing: (i) the functions to generate the different types of excitations beyond the commonly used UCCSD ans{ä}tz;(ii) a new implementation of the "adaptive derivative assembled pseudo-Trotter method" (ADAPT-VQE), written in simple class structure python codes. Interoperability with other major quantum programming frameworks is ensured thanks to myQLM, which allows users to easily build their own code and execute it on existing QPUs. The combined Open-VQE/myQLM-Fermion quantum simulator facilitates the implementation, tests and developments of variational quantum algorithms towards choosing the best compromise to run QC computations on present quantum computers while offering the possibility to test large molecules. We provide extensive benchmarks for several molecules associated to qubit counts ranging from 4 up to 24.

Figures (6)

• Figure 1: The QLM workflow for quantum chemistry. Top row: Steps to prepare a variational quantum job containing a parameterized circuit and the Hamiltonian whose ground state energy one wants to approximate. The leftmost (grey) box uses standard third-party quantum chemistry modules. Orange boxes stand for QLM libraries. Bottom row: QLM stack, with plugins (orange boxes) that pre- and post-process the job and results, and a QPU (green box) that executes the quantum job and returns a result.
• Figure 2: Overview of the QLM environment. Documentation of my-QLM/myQLM-fermion is given in myQLMmyqlm-fermion.
• Figure 3: Flow chart of the OpenVQE package. The code is given in our Github repository and documentation openvqe.
• Figure 4: Panel(a): timings for the application of a UCCSD circuit by OpenVQE while increasing the number of qubits. Panel (b): timings for the evaluation of increasing size molecular Hamiltonians (summed over Pauli strings and using using JW transformation) for the following molecules: H$_2$, H$_4$, LiH, H$_2$O, NH$_3$, CH$_4$, CO, HCN, C$_2$H$_2$ . Panel (c) shows the number of CNOT gates required to complete the UCCSD circuit and the number of Pauli strings in the Hamiltonian.
• Figure 5: VQE results for the H$_6$ molecule using the STO-3G basis set (a) and for LiH with the 6-31G basis (b). The dissociation profile is showed, using different active space selections and are calculated by using the first order trotterization UCCSD ansatz. The size of qubits represents the number of active spin-orbitals. The blue line indicates the chemical accuracy.