Neural network variational Monte Carlo for positronic chemistry.

Quantum chemical calculations of the ground-state properties of positron-molecule complexes are challenging. The main difficulty lies in employing an appropriate basis set for representing the coalescence between electrons and a positron. Here, we tackle this problem with the recently developed Fermionic neural network (FermiNet) wavefunction, which does not depend on a basis set.

An exact chiral amorphous spin liquid.

Topological insulator phases of non-interacting particles have been generalized from periodic crystals to amorphous lattices, which raises the question whether topologically ordered quantum many-body phases may similarly exist in amorphous systems? Here we construct a soluble chiral amorphous quantum spin liquid by extending the Kitaev honeycomb model to random lattices with fixed coordination number three. The model retains its exact solubility but the presence of plaquettes with an odd number of sides leads to a spontaneous breaking of time reversal symmetry. We unearth a rich phase diagram displaying Abelian as well as a non-Abelian quantum spin liquid phases with a remarkably simple ground state flux pattern.

Discovering Quantum Phase Transitions with Fermionic Neural Networks.

Deep neural networks have been very successful as highly accurate wave function Ansätze for variational Monte Carlo calculations of molecular ground states. We present an extension of one such Ansatz, FermiNet, to calculations of the ground states of periodic Hamiltonians, and study the homogeneous electron gas. FermiNet calculations of the ground-state energies of small electron gas systems are in excellent agreement with previous initiator full configuration interaction quantum Monte Carlo and diffusion Monte Carlo calculations.

z: Neutron cross section separation from wide-angle uniaxial polarization analysis.

We introduce a simple method to extract the nuclear coherent and isotope incoherent, spin incoherent, and magnetic neutron scattering cross section components from powder scattering data measured using a single neutron beam polarization direction and a position-sensitive detector with large out-of-plane coverage. The method draws inspiration from polarized small-angle neutron scattering and contrasts with conventional so-called "xyz" polarization analysis on wide-angle instruments, which requires measurements with three orthogonal polarization directions. The viability of the method is demonstrated on both simulated and experimental data for the classical "spin ice" system HoTiO, the latter from the LET direct geometry spectrometer at the ISIS facility.