Quantum Simulation of the Nuclear Shell Model NSM: Bridging Theory and Hardware Limitations
A fundamental issue in contemporary nuclear physics is the difficulty of adequately simulating the behaviour of atomic nuclei, which frequently surpasses the capacity of conventional classical computer techniques. The challenge arises from the “curse of dimensionality” that all many-body problems share, which states that the number of valence particles causes the size of the Hilbert space to increase combinatorically. In an effort to make massive nuclear shell model difficulties manageable, researchers have recently presented a revolutionary solution to this problem by simulating nuclear structure using quantum computers.
You can also read PsiQuantum Alpha System to lead the Quantum Computing Race
The Foundation: The Nuclear Shell Model
The Nuclear Shell Model NSM has been a fundamental paradigm for explaining the structural characteristics of atomic nuclei since it was first proposed by Mayer and Jensen in 1955. The NSM uses the mutual interaction of nucleons (protons and neutrons) travelling inside a basis of single-particle orbitals to explain nuclear states in its Configuration Interaction (CI) formalism.
In this approach, the second quantization is usually used to write the Nuclear shell model Hamiltonian. The single-particle energies and the two-body matrix elements are represented by the parameters in this Hamiltonian. Specific quantum numbers, such as the total angular momentum, its projection along the axis, the isospin projection, and the radial and orbital angular momentum, define each single-particle state.
Slater Determinants (SDs) of single-particle states are expanded to represent nuclear wave functions. Despite the relative efficiency of this basis representation, particularly for nuclei close to magic numbers, many nuclear systems are still unavailable for calculations using the classical shell model due to the many-body basis’s sharp increase in dimension. The investigation of quantum computation as the next development in computer science has been prompted by this constraint.
You can also read Orange QS Celebrates 5 Years of Quantum Innovation in Delft
Leveraging Quantum Computing for Nuclear Structure
By taking advantage of the multi-qubit Hilbert space‘s exponential scaling, quantum computation holds the potential to transcend the classical bounds of the NSM. Using quantum algorithms to investigate nuclear structure, the NSM has emerged as a crucial model. The Variational Quantum Eigensolver (VQE) algorithm is commonly used on modern quantum hardware, which is distinguished by intrinsic noise and decoherence. The VQE is appropriate for determining the ground state energies of nuclei because it naturally seeks the lowest energy states. Nuclear shell model are encoded into qubits, quantum circuits (ansatzes) are designed, these circuits are run on quantum hardware, and mistakes are minimized.
The Innovative Qubit Mapping Strategy
A novel qubit mapping technique within the VQE framework is the main breakthrough recently demonstrated in quantum simulations of the Nuclear Shell Model NSM. This innovative approach maps each Slater Determinant (SD) to a single qubit, as opposed to the traditional approach where qubits are assigned to specific single-particle states. Instead of representing individual nucleons, this method represents complete nucleon configurations.
The main advantage of this SD-based mapping is that it makes it possible to build smaller quantum circuits, even though in some particular situations it might raise the total number of qubits needed. This simplification results in fewer two-qubit gates and a large reduction in circuit depth, both of which are important causes of error in existing Noisy Intermediate-Scale Quantum (NISQ) devices. For near-term quantum simulations, this encoding technique provides a feasible path by exchanging a higher number of qubits for a simpler circuit.
The many-particle matrix element between two potential Slater determinants is shown in this technique. A qubit Hamiltonian (like the one found in Equation 5 in the sources) can therefore be easily created by rewriting the shell model Hamiltonian.
To create the ground state wave function, the researchers mostly employed a single excitation ansatz based on single excitation Givens rotations. For lighter nuclei, a comparison with a double excitation ansatz revealed that the single excitation ansatz needed substantially less resources, particularly fewer two-qubit gates and a significantly smaller circuit depth.
You can also read Reduced Density Matrix RDMs For Many-Body Systems
Demonstrated Feasibility and Error Mitigation
Seven distinct nuclei were successfully treated using this method:
- Four lithium isotopes shell
- Fluorine-18 shell.
- Two heavier nuclei, Polonium-210
The simulations proved that the available quantum resources could be used to tackle heavier nuclei. As an illustration, the ground state of was simulated as both a 22-qubit and a 29-qubit system. Both simulated quantum devices were used to execute the circuits.
The researchers used Zero-Noise Extrapolation (ZNE) to deal with the inherent noise in quantum processing. By employing two-qubit gate folding to gradually increase the complexity of the quantum circuits and then projecting the outcomes back to a zero-noise limit, this method lowers noise.
Although first simulations frequently showed slight underbidding, accuracy was greatly increased by using ZNE. Following mitigation, the quantum computing best results for each of the seven nuclei under study differed from established shell model predictions by less than 4%. This accomplishment shows how quantum algorithms are opening the door for near-term simulations that can improve the comprehension of nuclear shell model forces and structure when paired with creative mapping methods and error-reduction tactics.
In conclusion
The SD-based qubit mapping method works very well for lighter nuclei and two-nucleon systems, showing that as hardware moves closer to utility-scale devices, a promising path for scalable quantum simulations in nuclear physics is to trade a higher qubit count for a lower gate complexity.
You can also read Reduced Density Matrix RDMs For Many-Body Systems
