Speaker
Description
Quantum computing opens up new possibilities for the simulation of many-body nuclear systems.
As the number of particles in a many-body system increases, the size of the associated Hamiltonian increases exponentially. This presents a challenge when performing calculations on large systems when using classical computing methods. By using a quantum computer, one may be able to overcome this difficulty thanks to the exponential way the Hilbert space of a quantum computer grows with the number of quantum bits (qubits).
Our aim is to develop quantum computing algorithms which can reproduce and predict nuclear structure such as level schemes and level densities. As a sample Hamiltonian, we use the Lipkin-Meshkov-Glick model [1] and have further tested our methods against recent quantum computing calculations of the deuteron binding energy [2].
We use an efficient encoding of the Hamiltonian onto many-qubit systems, and have developed an algorithm allowing the full excitation spectrum of a nucleus to be determined with a variational algorithm capable of implementation on today's quantum computers with a limited number of qubits. Our algorithm uses the variance of the Hamiltonian, $\langle H^2\rangle-\langle H\rangle^2$, as a cost function for the widely-used variational quantum eigensolver (VQE).
In our presentation, we will show the motivations for the work, the simplified encoding method, and example results obtained using variational quantum algorithms to produce nuclear excited states spectra, as well as commenting on prospects for future applications.
[1] H. J. Lipkin, N. Meshkov, and A. J. Glick, Nulcear Physics 62, 188 (1965)
[2] E. F. Dumitrscu \textit{et al.}, Physical Review Letters 120, 210501 (2018)