Quantinuum scientists succeed in simplifying adiabatic quantum computing

Researchers at Quantinuum, a Honeywell subsidiary, have taken an important step towards achieving more efficient adiabatic quantum computation, which is critical for solving complex combinatorial optimization problems.

According to a research paper published on preprint server ArXiv, the team proposed novel tensor network algorithms designed to optimize quantum circuits, a key component of adiabatic quantum computing.

In contrast to the traditional approach of using the Trotter product formula to convert adiabatic time evolution into quantum circuits, the researchers employed an anti-adiabatic drive to augment the process: such an increase would normally increase the depth of the circuit with each time step, thus requiring more computational resources.

However, this time around, the team took a different approach, encapsulating both adiabatic time evolution and antiadiabatic driving over multiple time steps by classically optimizing parameterized quantum circuits with a fixed depth. In other words, this approach helps guide the quantum system to reach the lowest energy state smoothly and efficiently in multiple stages. Ultimately, this makes it possible to capture the evolution of a quantum system without the need for increasingly complex circuits.

The paper reports that these optimization circuits greatly outperform the traditional Trotter product formulation. Applying these methods to a model system for quantum computation: the quantum Ising chain (which varies in size from N=7 to 31), the results show that the classical optimization circuits are much more efficient in preparing the ground state of the system under consideration.

The researchers also explored the potential of these optimized quantum circuits for solving combinatorial optimization problems; such problems are notoriously difficult to solve, but are of paramount importance in a variety of fields such as logistics, finance and resource management. The new approach numerically demonstrates that specific one-dimensional quantum many-body systems can be accurately represented by attaching shallow one-dimensional quantum circuits, which are optimized using standard tensor network techniques.

Furthermore, it is shown that the method can be extended to two-dimensional quantum systems by employing the appropriate tensor network algorithms. This scalability is crucial as it shows that the methods have the potential to be applied to more complex and practical problems in the future.

These findings are far-reaching. Adiabatic quantum computing is a promising avenue for solving certain types of problems that are currently intractable to classical computers. By refining and reducing the complexity of the quantum circuits required for adiabatic evolution, this research could bring the full potential of quantum computing closer to reality.

Quantinuum's work not only provides practical solutions to technical challenges in the field of quantum computing, but also opens up new possibilities for applying adiabatic methods to solve nonlocal, challenging classical problems.

As the field of quantum computing continues to evolve, the ability to efficiently simulate adiabatic processes on gate-based quantum computers may lead to breakthroughs in a wide range of disciplines, from materials science to cryptography, and drive the quest for fully functional and efficient quantum computers.