Quantum Simulation of Nuclear Shell Model Maps Seven Nuclei, Enabling Calculations on Noisy Intermediate-scale Quantum Devices

The challenge of accurately modelling the behaviour of atomic nuclei remains a central problem in nuclear physics, often exceeding the capabilities of traditional computational methods. Chandan Sarma, Paul Stevenson, and colleagues at the University of Surrey now present a novel approach to this problem, utilising quantum computers to simulate nuclear structure. Their work introduces a new strategy for mapping complex nuclear calculations onto qubits, the fundamental units of quantum information, by representing entire configurations of nucleons rather than individual particles. This method allows for the construction of simpler quantum circuits, making it more feasible to run simulations on today’s limited, yet rapidly developing, quantum hardware, and the team successfully demonstrates simulations of heavier nuclei like polonium and lead. By combining this innovative mapping technique with error mitigation strategies, they achieve results that deviate by less than four percent from established theoretical predictions, paving the way for near-term quantum simulations that can advance our understanding of nuclear forces and structure.

Quantum simulation of nuclear shell model: bridging theory and hardware limitations Chandan Sarma and P. D. The key innovation lies in representing each Slater determinant with a single qubit, rather than assigning qubits to individual particles. This approach simplifies quantum circuits and enables more efficient simulation of larger nuclear systems than previously possible. The researchers demonstrate the feasibility of this method, paving the way for more accurate and scalable quantum simulations of nuclear structure.

The method allows for the construction of simpler quantum circuits, more compatible with current, noisy intermediate-scale quantum devices. The team applied this approach to seven nuclei, including lithium isotopes and heavier nuclei like polonium and lead. These circuits, representing their ground states, were run on both a simulated quantum computer and actual quantum hardware, demonstrating the feasibility of simulating polonium and lead as 22- and 29-qubit systems, respectively. Zero-Noise Extrapolation, a technique for reducing errors, was employed to improve the accuracy of the results.

Nuclear Structure Solved with Quantum Algorithms

This research details a study exploring the use of Variational Quantum Eigensolvers to solve the nuclear many-body problem. The researchers are calculating the ground state energies of light nuclei using quantum computers, focusing on a qubit mapping strategy where each Slater determinant is represented by a single qubit. The work includes encoding nuclear states into qubits, designing quantum circuits, running these circuits on quantum computers, mitigating errors, and comparing the quantum results to traditional nuclear physics calculations. The results show that, with error mitigation, the quantum calculations achieve accuracy comparable to traditional methods for the nuclei studied. The researchers highlight the trade-offs between qubit count and circuit complexity, and suggest that their approach is promising for scaling up quantum simulations of nuclear systems. Key findings include an effective qubit mapping strategy, improved scalability due to reduced circuit depth, successful error mitigation, calculations performed on a range of nuclei, and benchmarking against established nuclear physics calculations.

Mapping Complex Nuclei with Fewer Qubits

This work presents a new strategy for mapping qubits to represent complex nuclear systems within the Variational Eigensolver framework. By assigning each Slater determinant to a single qubit, the team constructed simpler quantum circuits suitable for current, noisy intermediate-scale quantum devices. Applying this method to nuclei ranging from lithium to lead, they successfully simulated the ground state of polonium and lead, demonstrating the feasibility of tackling heavier nuclei with available quantum resources. The results indicate that this qubit mapping approach is particularly effective for lighter nuclei and two-nucleon systems, achieving ground state energy predictions with less than four percent deviation from established shell model calculations after error mitigation.

To address inherent errors in quantum computation, the researchers employed Zero-Noise Extrapolation, a technique that reduces the impact of noise by systematically increasing the complexity of the quantum circuits and extrapolating to a zero-noise limit. While initial simulations revealed some underbinding, the application of error mitigation significantly improved accuracy. The authors acknowledge that the method’s performance can vary depending on the nucleus, and that the largest systems, such as lead, are more susceptible to hardware errors. Future work will likely focus on refining the error mitigation techniques and extending the method to even heavier nuclei, potentially unlocking new insights into the structure and behaviour of matter at the atomic level.