Cornell and LSU Researchers Develop Quantum Algorithm for Advanced Nuclear Simulations

Researchers from Cornell University and Louisiana State University have developed a quantum algorithm for neutron-nucleus simulations, designed to meet the growing computational demands of nuclear structure and reaction modelling. The algorithm can solve for any band-diagonal to full Hamiltonian matrices, and can accommodate a general central potential. It also supports the complete form of the chiral effective field-theory nucleon-nucleon potentials used in ab initio nuclear calculations. The team’s work provides the first solutions of neutron-alpha dynamics from quantum simulations suitable for noisy intermediate-scale quantum processors.

What is the New Quantum Algorithm for Neutron-Nucleus Simulations?

A team of researchers from the School of Applied and Engineering Physics at Cornell University and the Department of Physics and Astronomy at Louisiana State University have developed a novel quantum algorithm for neutron-nucleus simulations. This algorithm is designed to address the increasing computational demands of nuclear structure and reactions modeling. The algorithm can solve for any band-diagonal to full Hamiltonian matrices, accommodating a general central potential, including exponential Gaussian-like potentials and ab initio intercluster potentials optical potentials.

The algorithm is also capable of accommodating the complete form of the chiral effective field-theory nucleon-nucleon potentials used in ab initio nuclear calculations. The researchers have made this potential available for three different qubit encodings, including the one-hot, binary, and Gray encodings. They also provide a comprehensive analysis of the number of Pauli terms and commuting sets involved.

How Does the New Quantum Algorithm Work?

The researchers found that the Gray encoding allows for an efficient scaling of the model-space size, or the number of basis states used. It is more resource-efficient not only for tridiagonal Hamiltonians, as suggested earlier, but also for band-diagonal Hamiltonians having bandwidth up to N.

The team introduced a new commutativity scheme called distance-grouped commutativity (DGC) and compared its performance with the well-known qubit-commutativity (QC) scheme. They laid out the explicit grouping of Pauli strings and the diagonalizing unitary under the DGC scheme and found that it outperforms the QC scheme, albeit at the cost of a more complex diagonalizing unitary.

What are the Applications of the New Quantum Algorithm?

The researchers provided the first solutions of the neutron-alpha dynamics from quantum simulations suitable for noisy intermediate-scale quantum processors. They used an optical potential rooted in first principles and conducted a study of the bound-state physics in neutron-Carbon systems. They also compared the efficacy of the one-hot and Gray encodings.

The algorithm is expected to help address the explosive growth in computational resource demands with the increasing number of particles and size of the spaces in which they reside. This is particularly relevant in nuclear structure calculations, where major progress in the development of high-precision internucleon interactions, along with the utilization of high-performance computing resources, have tremendously advanced nuclear science explorations.

What are the Future Directions for this Research?

The researchers concluded their study by outlining future directions for their work. They believe that their algorithm can help address long-term challenges in nuclear structure and reactions modeling by harnessing the advantages of quantum computing.

The team started with the simplest case of two clusters, one of which is a neutron, and provided the first solutions of the neutron-nucleus dynamics from quantum simulations. They believe that their work is suitable for the far-term error-corrected regime as well as for the noisy intermediate-scale quantum (NISQ) processors, coupled with the noise-resilient (NR) training method.

What is the Significance of this Research?

This research is significant as it presents a novel approach to addressing the computational demands of nuclear structure and reactions modeling. The development of a quantum algorithm for neutron-nucleus simulations represents a significant advancement in the field of nuclear physics.

The algorithm’s ability to accommodate a wide range of potentials and its efficient scaling of the model-space size make it a promising tool for future research. Furthermore, the introduction of a new commutativity scheme could have implications for the development of more efficient quantum algorithms. The researchers’ work on neutron-alpha dynamics and neutron-Carbon systems also provides valuable insights into these complex systems.