Publications

We investigate the dynamics of hydrodynamically interacting motile and non-motile stress-generating swimmers or particles as they invade a surrounding viscous fluid. Colonies of aligned pusher particles are shown to elongate in the direction of particle orientation and undergo a cascade of transverse concentration instabilities. Colonies of aligned puller particles instead are found to elongate in the direction opposite the particle orientation and exhibit dramatic splay as the group moves into the bulk. A linear stability analysis of concentrated line distributions of particles is performed and growth rates are found, using an active slender-body approximation, to match the results of numerical simulations. Thin concentrated bands of aligned pusher particles are always unstable, while bands of aligned puller particles can either be stable (immotile particles) or unstable (motile particles) with a growth rate which is non-monotonic in the force dipole strength. We also prove a surprising "no-flow theorem": a distribution initially isotropic in orientation loses isotropy immediately but in such a way that results in no fluid flow anywhere at any time.

We present a new method for the analysis of electromagnetic scattering from homogeneous penetrable bodies. Our approach is based on a reformulation of the governing Maxwell equations in terms of two uncoupled vector Helmholtz systems: one for the electric feld and one for the magnetic field. This permits the derivation of resonance-free Fredholm equations of the second kind that are stable at all frequencies, insensitive to the genus of the scatterers, and invertible for all passive materials including those with negative permittivities or permeabilities. We refer to these as decoupled field integral equations.

Insights from spectroscopic experiments led to the development of quantum mechanics as the com- mon framework for describing the physical and chemical properties of atoms, molecules and mate- rials. Later, a full quantum description of charged particles, electromagnetic radiation and relativity was developed, leading to quantum-electrodynamics (QED). This is, to our current understanding, the most fundamental theory describing photon-matter interactions in correlated many-body sys- tems. In the low-energy regime, simplified models of QED were developed for describing and an- alyzing spatial and time-resolved spectroscopies encompassing a wide range of energy, time, and space scales as well as physical systems. In this review, we highlight the interrelations and limita- tions of such theoretical models by showing how they appear as low-energy simplifications of the full QED formalism, where anti-particles and the internal structure of the nuclei are neglected. Tak- ing molecular systems as reference, we discuss how the breakdown of some of the well-established simplifications to low-energy QED challenges our conventional understanding of light-matter inter- actions. New features of collective QED effects in complex interacting many-particle systems could become, besides high-precision atomic measurements and simulations of particle-physics problems in solid-state systems, an alternative material-based route to further advance the currently most fun- damental theory for light-matter interactions.

We introduce linear-response theory for non-relativistic quantum-electrodynamics in the long wavelength limit, which allows us to treat correlated excited-state phenomena of matter-photon systems from first principles. By using quantum-electrodynamical density-functional theory we can reformulate the resulting fully coupled photon-matter response equations as a pseudo-eigenvalue problem. This provides a direct extension of the conventional matter-only response theory. Our approach can be solved numerically very efficiently and existing ab-initio density-functional response implementations can be easily extended to take the full photon-matter response into account. We highlight how the coupling between light and matter changes the usual response functions and introduces new types of response functions that measure the matter-photon subsystem responses. We show how correlating light and matter changes the Maxwell equations and highlight how the spectra of real systems are changed upon strongly coupling to the photon field. A key feature of treating the combined matter-photon response is that natural lifetimes of excitations become directly accessible from first principles and no artificial broadening of spectra is required anymore. By introducing a straightforward extension of the random-phase approximation for the coupled matter-photon problem, we are able to present the first ab-initio spectra for a real molecular system that is coupled to the quantized electromagnetic field.

Using a nonequilibrium implementation of the extended dynamical mean field theory (EDMFT) we simulate the relaxation after photo excitation in a strongly correlated electron system with antiferromagnetic spin interactions. We consider the t-J model and focus on the interplay between the charge- and spin-dynamics in different excitation and doping regimes. The appearance of string states after a weak photo excitation manifests itself in a nontrivial scaling of the relaxation time with the exchange coupling and leads to a correlated oscillatory evolution of the kinetic energy and spin-spin correlation function. A strong excitation of the system, on the other hand, suppresses the spin correlations and results in a relaxation that is controlled by hole scattering. We discuss the possibility of detecting string states in optical and cold atom experiments.

It is well-known that by placing judiciously chosen image point forces and doublets to the Stokeslet above a flat wall, the no-slip boundary condition can be conveniently imposed on the wall [Blake, J. R. Math. Proc. Camb. Philos. Soc. 70(2), 1971: 303.]. However, to further impose periodic boundary conditions on directions parallel to the wall usually involves tedious derivations because single or double periodicity in Stokes flow may require the periodic unit to have no net force, which is not satisfied by the well-known image system. In this work we present a force-neutral image system. This neutrality allows us to represent the Stokes image system in a universal formulation for non-periodic, singly periodic and doubly periodic geometries. This formulation enables the black-box style usage of fast kernel summation methods. We demonstrate the efficiency and accuracy of this new image method with the periodic kernel independent fast multipole method in both non-periodic and doubly periodic geometries. We then extend this new image system to other widely used Stokes fundamental solutions, including the Laplacian of the Stokeslet and the Rotne-Prager-Yamakawa tensor.

Temporally precise movement patterns underlie many motor skills and innate actions, yet the flexibility with which the timing of such stereotyped behaviors can be modified is poorly understood. To probe this, we induce adaptive changes to the temporal structure of birdsong. We find that the duration of specific song segments can be modified without affecting the timing in other parts of the song. We derive formal prescriptions for how neural networks can implement such flexible motor timing. We find that randomly connected recurrent networks, a common approximation for how neocortex is wired, do not generally conform to these, though certain implementations can approximate them. We show that feedforward networks, by virtue of their one-to-one mapping between network activity and time, are better suited. Our study provides general prescriptions for pattern generator networks that implement flexible motor timing, an important aspect of many motor skills, including birdsong and human speech.

We examine various integration schemes for the time-dependent Kohn-Sham equations. Contrary to the time-dependent Schrödinger's equation, this set of equations is non-linear, due to the dependence of the Hamiltonian on the electronic density. We discuss some of their exact properties, and in particular their symplectic structure. Four different families of propagators are considered, specifically the linear multistep, Runge-Kutta, exponential Runge-Kutta, and the commutator-free Magnus schemes. These have been chosen because they have been largely ignored in the past for time-dependent electronic structure calculations. The performance is analyzed in terms of cost-versus-accuracy. The clear winner, in terms of robustness, simplicity, and efficiency is a simplified version of a fourth-order commutator-free Magnus integrator. However, in some specific cases, other propagators, such as some implicit versions of the multistep methods, may be useful.

The experimental realization of increasingly complex synthetic quantum systems calls for the development of general theoretical methods to validate and fully exploit quantum resources. Quantum state tomography (QST) aims to reconstruct the full quantum state from simple measurements, and therefore provides a key tool to obtain reliable analytics. However, exact brute-force approaches to QST place a high demand on computational resources, making them unfeasible for anything except small systems. Here we show how machine learning techniques can be used to perform QST of highly entangled states with more than a hundred qubits, to a high degree of accuracy. We demonstrate that machine learning allows one to reconstruct traditionally challenging many-body quantities—such as the entanglement entropy—from simple, experimentally accessible measurements. This approach can benefit existing and future generations of devices ranging from quantum computers to ultracold-atom quantum simulators.

We develop a constructive approach to generate artificial neural networks representing the exact ground states of a large class of many-body lattice Hamiltonians. It is based on the deep Boltzmann machine architecture, in which two layers of hidden neurons mediate quantum correlations among physical degrees of freedom in the visible layer. The approach reproduces the exact imaginary-time Hamiltonian evolution, and is completely deterministic. In turn, compact and exact network representations for the ground states are obtained without stochastic optimization of the network parameters. The number of neurons grows linearly with the system size and total imaginary time, respectively. Physical quantities can be measured by sampling configurations of both physical and neuron degrees of freedom. We provide specific examples for the transverse-field Ising and Heisenberg models by implementing efficient sampling. As a compact, classical representation for many-body quantum systems, our approach is an alternative to the standard path integral, and it is potentially useful also to systematically improve on numerical approaches based on the restricted Boltzmann machine architecture.