  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{\"a}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.
