Publications

The interplay between delocalisation and repulsive interactions can cause electronic systems to undergo a Mott transition between a metal and an insulator. Here we use neural network hidden fermion determinantal states (HFDS) to uncover this transition in the disordered, fully-connected Hubbard model. Whilst dynamical mean-field theory (DMFT) provides exact solutions to physical observables of the model in the thermodynamic limit, our method allows us to directly access the wavefunction for finite system sizes well beyond the reach of exact diagonalisation. We directly benchmark our results against state-of-the-art calculations obtained using a Matrix Product State (MPS) ansatz. We demonstrate how HFDS is able to obtain more accurate results in the metallic regime and in the vicinity of the transition, with the volume law of entanglement exhibited by the system being prohibitive to the MPS ansatz. We use the HFDS method to calculate the amplitudes of the wavefunction, the energy and double occupancy, the quasi-particle weight and the energy gap, hence providing novel insights into this model and the nature of the transition. Our work paves the way for the study of strongly correlated electron systems with neural quantum states.

Quantum Monte Carlo (QMC) can play a very important role in generating accurate data needed for constructing potential energy surfaces. We argue that QMC has advantages in terms of a smaller systematic bias and an ability to cover phase space more completely. The stochastic noise can ease the training of the machine learning model. We discuss how stochastic errors affect the generation of effective models by analyzing the errors within a linear least squares procedure, finding that there is an advantage to having many relatively imprecise data points for constructing models. We then analyze the effect of noise on a model of many-body silicon finding that noise in some situations improves the resulting model. We then study the effect of QMC noise on two machine learning models of dense hydrogen used in a recent study of its phase diagram. The noise enable us to estimate the errors in the model. We conclude with a discussion of future research problems.

Real-time calculations in tensor networks are strongly limited in time by entanglement growth, restricting the achievable frequency resolution of Green's functions, spectral functions, self-energies, and other related quantities. By extending the time evolution to contours in the complex plane, entanglement growth is curtailed, enabling numerically efficient high-precision calculations of time-dependent correlators and Green's functions with detailed frequency resolution. Various approaches to time evolution in the complex plane and the required post-processing for extracting the pure real-time and frequency information are compared. We benchmark our results on the examples of the single-impurity Anderson model using matrix-product states and of the three-band Hubbard-Kanamori and Dworin-Narath models using a tree tensor network. Our findings indicate that the proposed methods are also applicable to challenging realistic calculations of materials.

For decades, frustrated quantum magnets have been a seed for scientific progress and innovation in condensed matter. As much as the numerical tools for low-dimensional quantum magnetism have thrived and improved in recent years due to breakthroughs inspired by quantum information and quantum computation, higher-dimensional quantum magnetism can be considered as the final frontier, where strong quantum entanglement, multiple ordering channels, and manifold ways of paramagnetism culminate. At the same time, efforts in crystal synthesis have induced a significant increase in the number of tangible frustrated magnets which are generically three-dimensional in nature, creating an urgent need for quantitative theoretical modeling. We review the pseudo-fermion (PF) and pseudo-Majorana (PM) functional renormalization group (FRG) and their specific ability to address higher-dimensional frustrated quantum magnetism. First developed more than a decade ago, the PFFRG interprets a Heisenberg model Hamiltonian in terms of Abrikosov pseudofermions, which is then treated in a diagrammatic resummation scheme formulated as a renormalization group flow of m-particle pseudofermion vertices. The article reviews the state of the art of PFFRG and PMFRG and discusses their application to exemplary domains of frustrated magnetism, but most importantly, it makes the algorithmic and implementation details of these methods accessible to everyone. By thus lowering the entry barrier to their application, we hope that this review will contribute towards establishing PFFRG and PMFRG as the numerical methods for addressing frustrated quantum magnetism in higher spatial dimensions.

A recent theory described strange metal behavior in a model of a Fermi surface coupled a two-dimensional quantum critical bosonic field with a spatially random Yukawa coupling. With the assumption of self-averaging randomness, similar to that in the Sachdev-Ye-Kitaev model, numerous observed properties of a strange metal were obtained for wide range of intermediate temperatures, including the linear-in-temperature resistivity. The Harris criterion implies that spatial fluctuations in the local position of the critical point must dominate at lower temperatures. For an M-component boson with M ≥2, we use multiple graphics processing units (GPUs) to compute the real frequency spectrum of the boson propagator in a self-consistent mean-field treatment of the boson self-interactions, but an exact treatment of multiple realizations of the spatial randomness from the random boson mass. We find that Landau damping from the fermions leads to the emergence of the physics of the random transverse-field Ising model at low temperatures, as has been proposed by Hoyos, Kotabage, and Vojta. This regime is controlled by localized overdamped eigenmodes of the bosonic scalar field, also has a resistivity which is nearly linear-in-temperature, and extends into a `quantum critical phase' away from the quantum critical point, as observed in several cuprates. For the M = 1 Ising scalar, the mean-field treatment is not applicable, and so we use Hybrid Monte Carlo simulations running on multiple GPUs; we find a rounded transition and localization physics, with strange metal behavior in an extended region around the transition.

Despite the significant attention it has garnered over the last thirty years, the paradigmatic material strontium ruthenate remains the focus of critical questions regarding strongly correlated materials. As an alternative platform to unravel some of its perplexing characteristics, we propose to study the isostructural and more correlated material strontium ferrite. Using density functional theory combined with dynamical mean-field theory, we attribute the experimentally observed insulating behavior at zero pressure to strong local electronic correlations generated by Mott and Hund's physics. At high pressure, our simulations reproduce the reported insulator-to-metal transition around 18 GPa. Along with distinctive features of a Hund's metal, the resulting metallic state is found to display an electronic structure analogous to that of strontium ruthenate, suggesting that it could exhibit similar low-energy properties.

Quantum geometry plays a pivotal role in the second-order response of PT-symmetric antiferromagnets. Here we study the nonlinear response of 2D altermagnets protected by C

It has been reported that upon doping a Mott insulator, there can be a crossover to a strongly correlated metallic phase followed by a first-order transition to another thermodynamically stable metallic phase. We call this first-order metal-metal transition the Sordi transition. To show theoretically that this transition is observable, it is important to provide calculations in situations where magnetic phase transitions do not hide the Sordi transition. It is also important to show that it can be found on large clusters and with different approaches. Here, we use the dynamical cluster approximation to reveal the Sordi transition on a triangular lattice at finite temperature in situations where there is no long-range magnetic correlations. This is relevant for experiments on candidate spin-liquid organics. We also show that the metallic phase closest to the insulator is a distinct pseudogap phase that occurs because of strong interactions and short-range correlations

Frustrated magnetic systems can host highly interesting phases known as classical spin liquids (CSLs), which feature extensive ground state degeneracy and lack long-range magnetic order. Recently, Yan and Benton et al. proposed a classification scheme of CSLs in the large-N (soft spin) limit [arXiv.2305.00155], [arXiv:2305.19189]. This scheme classifies CSLs into two categories: the algebraic CSLs and the fragile topological CSLs, each with their own correlation properties, low energy effective description, and finer classification frameworks. In this work, we further develop the classification scheme by considering the role of crystalline symmetry. We present a mathematical framework for computing the band representation of the flat bands in the spectrum of these CSLs, which extends beyond the conventional representation analysis. It allows one to determine whether the algebraic CSLs, which features gapless points on their bottom flat bands, are protected by symmetry or not. It also provides more information on the finer classifications of algebraic and fragile topological CSLs. We demonstrate this framework via concrete examples and showcase its power by constructing a pinch-line algebraic CSL protected by symmetry.

Using state of the art tensor network computations combined with spin wave theory, we compute the finite temperature phase diagram of the spin 1/2 J