Ultrafast Quenching of the Exchange Interaction in a Mott Insulator

We investigate how fast and how effective photocarrier excitation can modify the exchange interaction $J_\mathrm{ex}$ in the prototype Mott-Hubbard insulator. We demonstrate an ultrafast quenching of $J_\mathrm{ex}$ both by evaluating exchange integrals from a time-dependent response formalism and by explicitly simulating laser-induced spin precession in an antiferromagnet that is canted by an external magnetic field. In both cases, the electron dynamics is obtained from nonequilibrium dynamical mean-field theory. We find that the modified $J_\mathrm{ex}$ emerges already within a few electron hopping times after the pulse, with a reduction that is comparable to the effect of chemical doping.Comment: 8 pages, 4 figure

Investigating ultrafast quantum magnetism with machine learning

We investigate the efficiency of the recently proposed Restricted Boltzmann Machine (RBM) representation of quantum many-body states to study both the static properties and quantum spin dynamics in the two-dimensional Heisenberg model on a square lattice. For static properties we find close agreement with numerically exact Quantum Monte Carlo results in the thermodynamical limit. For dynamics and small systems, we find excellent agreement with exact diagonalization, while for systems up to N=256 spins close consistency with interacting spin-wave theory is obtained. In all cases the accuracy converges fast with the number of network parameters, giving access to much bigger systems than feasible before. This suggests great potential to investigate the quantum many-body dynamics of large scale spin systems relevant for the description of magnetic materials strongly out of equilibrium.Comment: 18 pages, 5 figures, data up to N=256 spins added, minor change

Ultrafast and reversible control of the exchange interaction in Mott insulators

The strongest interaction between microscopic spins in magnetic materials is the exchange interaction $J_\text{ex}$. Therefore, ultrafast control of $J_\text{ex}$ holds the promise to control spins on ultimately fast timescales. We demonstrate that time-periodic modulation of the electronic structure by electric fields can be used to reversibly control $J_\text{ex}$ on ultrafast timescales in extended antiferromagnetic Mott insulators. In the regime of weak driving strength, we find that $J_\text{ex}$ can be enhanced and reduced for frequencies below and above the Mott gap, respectively. Moreover, for strong driving strength, even the sign of $J_\text{ex}$ can be reversed and we show that this causes time reversal of the associated quantum spin dynamics. These results suggest wide applications, not only to control magnetism in condensed matter systems, for example, via the excitation of spin resonances, but also to assess fundamental questions concerning the reversibility of the quantum many-body dynamics in cold atom systems.Comment: 9 pages, 4 figure

Second Low Temperature Phase Transition in Frustrated UNi_4B

Hexagonal UNi_4B is magnetically frustrated, yet it orders antiferromagnetically at T_N = 20 K. However, one third of the U-spins remain paramagnetic below this temperature. In order to track these spins to lower temperature, we measured the specific heat C of \unib between 100 mK and 2 K, and in applied fields up to 9 T. For zero field there is a sharp kink in C at $T^\ast\approx$ 330 mK, which we interpret as an indication of a second phase transition involving paramagnetic U. The rise in $\gamma = C/T$ between 7 K and 330 mK and the absence of a large entropy liberated at $T^\ast$ may be due to a combination of Kondo screening effects and frustration that strongly modifies the low T transition.Comment: 4 pages, 4 figure

Parametrically driven THz magnon-pairs: predictions towards ultimately fast and minimally dissipative switching

Findings ways to achieve switching between magnetic states at the fastest possible time scale that simultaneously dissipates the least amount of energy is one of the main challenges in magnetism. Antiferromagnets exhibit intrinsic dynamics in the THz regime, the highest among all magnets and are therefore ideal candidates to address this energy-time dilemma. Here we study theoretically THz-driven parametric excitation of antiferromagnetic magnon-pairs at the edge of the Brillouin zone and explore the potential for switching between two stable oscillation states. Using a semi-classical theory, we predict that switching can occur at the femtosecond time scale with an energy dissipation down to a few zepto Joule. This result touches the thermodynamical bound of the Landauer principle, and approaches the quantum speed limit up to 5 orders of magnitude closer than demonstrated with magnetic systems so far.Comment: 8 pages, 4 figure

Optical control of competing exchange interactions and coherent spin-charge coupling in two-orbital Mott insulators

In order to have a better understanding of ultrafast electrical control of exchange interactions in multi-orbital systems, we study a two-orbital Hubbard model at half filling under the action of a time-periodic electric field. Using suitable projection operators and a generalized time-dependent canonical transformation, we derive an effective Hamiltonian which describes two different regimes. First, for a wide range of non-resonant frequencies, we find a change of the bilinear Heisenberg exchange $J_{\textrm{ex}}$ that is analogous to the single-orbital case. Moreover we demonstrate that also the additional biquadratic exchange interaction $B_{\textrm{ex}}$ can be enhanced, reduced and even change sign depending on the electric field. Second, for special driving frequencies, we demonstrate a novel spin-charge coupling phenomenon enabling coherent transfer between spin and charge degrees of freedom of doubly ionized states. These results are confirmed by an exact time-evolution of the full two-orbital Mott-Hubbard Hamiltonian.Comment: 3 pages, 6 figure

Stable and fast semi-implicit integration of the stochastic Landau-Lifshitz equation

We propose new semi-implicit numerical methods for the integration of the stochastic Landau-Lifshitz equation with built-in angular momentum conservation. The performance of the proposed integrators is tested on the 1D Heisenberg chain. For this system, our schemes show better stability properties and allow us to use considerably larger time steps than standard explicit methods. At the same time, these semi-implicit schemes are also of comparable accuracy to and computationally much cheaper than the standard midpoint implicit method. The results are of key importance for atomistic spin dynamics simulations and the study of spin dynamics beyond the macro spin approximation.Comment: 24 pages, 5 figure

Quantum many-body dynamics of the Einstein-de Haas effect

In 1915, Einstein and de Haas and Barnett demonstrated that changing the magnetization of a magnetic material results in mechanical rotation, and vice versa. At the microscopic level, this effect governs the transfer between electron spin and orbital angular momentum, and lattice degrees of freedom, understanding which is key for molecular magnets, nano-magneto-mechanics, spintronics, and ultrafast magnetism. Until now, the timescales of electron-to-lattice angular momentum transfer remain unclear, since modeling this process on a microscopic level requires addition of an infinite amount of quantum angular momenta. We show that this problem can be solved by reformulating it in terms of the recently discovered angulon quasiparticles, which results in a rotationally invariant quantum many-body theory. In particular, we demonstrate that non-perturbative effects take place even if the electron--phonon coupling is weak and give rise to angular momentum transfer on femtosecond timescales.Comment: 15 pages, 5 figure

Supervised learning of an opto-magnetic neural network with ultrashort laser pulses

The explosive growth of data and its related energy consumption is pushing the need to develop energy-efficient brain-inspired schemes and materials for data processing and storage. Here, we demonstrate experimentally that Co/Pt films can be used as artificial synapses by manipulating their magnetization state using circularly-polarized ultrashort optical pulses at room temperature. We also show an efficient implementation of supervised perceptron learning on an opto-magnetic neural network, built from such magnetic synapses. Importantly, we demonstrate that the optimization of synaptic weights can be achieved using a global feedback mechanism, such that the learning does not rely on external storage or additional optimization schemes. These results suggest there is high potential for realizing artificial neural networks using optically-controlled magnetization in technologically relevant materials, that can learn not only fast but also energy-efficient.Comment: 9 pages, 4 figure