Vous devez simuler des réactions chimiques avec l’informatique quantique. Quels sont les outils les plus fiables ?

It is important to point out here that the hardware resources we have today are "hybrid" in nature. That means we do not yet have a full scale quantum computer that only runs on pure quantum hardware. These intermediate scale devices today make use of both CPUs & QPUs (either on edge or on cloud) to run algorithms. Moreover, the algorithms themselves are designed to utilize both the quantum and classical resources. That said, the parts that run on the core of the quantum processors are certain gate operations. The rest (inter-process communication, storage, information handling, etc) is mostly done on the classical computers. To proceed out of this NISQ era & into the world of full scale quantum computing, we need fault tolerance.

Choosing the right hardware platform for quantum simulations requires careful consideration of factors such as speed, stability, and ease of operation. Superconducting qubits provide speed but are prone to errors, while trapped ions provide stability at the expense of speed. Photonic qubits are easy to generate but difficult to entangle, while topological qubits, while powerful, are still experimental. The decision depends on the simulation goals and budget constraints, allowing for customized choices or a mixed approach.

Keep in mind that due to the limited resources provided in numbers of qubits or runtime there are a lot of simplifications needed like born-oppenheimer or reduction of considered orbitals. So research hast also bei done in area of used algorithms not only using VQE or QFT.

Simulating chemical reactions using quantum computing is very important, and the choice of reliable tools depends on factors such as application preferences and simulation requirements. Low-level languages such as QASM or Quil provide direct control of quantum gates, while high-level languages such as Qiskit or Cirq provide libraries for building algorithms. Domain-specific languages such as OpenFermion or Tequila focus on quantum chemistry. The choice should meet the needs of the simulation, consider the required level of abstraction and functionality, and consider adaptability or a combination of these systems.

Quantum Chemistry related simulation projects require a set of quantum algorithms suitable to measure, optimise and translate the quantum mechanical energy states associated with the chemical processes. Quantum phase estimation algorithm and Variational Quantum Eigen solver algorithm are quite prominent schemes to measure the ground state and first degree quantisation state from chemical processes. Once the ground state properties are clearly understood it becomes possible to simulate various combinations of chemical reactions within the feasible energy environment.

Cloud services are essential for quantum simulations, with options such as IBM Quantum, Amazon Braket, IonQ, and PsiQuantum. They provide access to various qubits and frameworks such as Qiskit, Cirq, Q# and Quil. For photonic qubits, consider Xanadu or PsiQuantum and Strawberry Fields or Qibo frameworks. Adjust your choices based on your simulation needs. Quantum computing is very efficient in modeling chemical reactions and requires careful planning. Optimize your experience by choosing reliable tools that meet your needs across hardware platforms, software frameworks, and cloud services.

If you're interested in experimenting with quantum computing and its diverse applications, I'd recommend Cirq as a platform for developing tools harnessing the power of quantum computers. It allows us to leverage quantum computing capabilities in unexplored fields. Feel free to check out the tool I developed using Cirq for OSINT, shared on my profile!