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We report real-time simulations of far-from-equilibrium dynamics of a holographic superfluid in three dimensions. The holographic duality maps a strongly coupled superfluid to a weakly coupled theory with gravity in a higher-dimensional curved space which we study numerically. Starting from configurations of dense tangles of quantized vortex lines, the superfluid exhibits turbulent behavior during its evolution towards thermal equilibrium. Specifically, we observe two subsequent universal regimes of quasi-stationary scaling in the occupation number spectrum, the first of which is Kolmogorov-like. Indications for the strongly dissipative nature of vortex dynamics in the three-dimensional holographic superfluid are found in the rapid shrinking and annihilation of small vortex rings that emerge from frequent reconnections of vortex lines during the evolution., Comment: 16 pages, videos and additional material at https://www.thphys.uni-heidelberg.de/~holography/Turbulence3D/

We investigate generic inequalities of various contributions to the shear modulus $\mu$ in ensembles of amorphous elastic bodies. We focus first on a simple elastic network model with connectivity matrices (CMs) which are either annealed or quenched, at or out of equilibrium. The stress-fluctuation formalism relation for $\mu$ is rewritten as $\mu = \mu_1 + \mu_a$ with $\mu_1 \ge 0$ characterizing the variance of the quenched shear stresses and $\mu_a$ being a simple average over all states and CMs. For equilibrium CM-distributions $\mu_a$ becomes equivalent to the shear modulus of annealed systems, i.e. $\mu_a \ge 0$, while more generally $\mu_a$ may become strongly negative as shown by considering a temperature quench and a scalar active two-temperature model. Consistent relations are also found for glass-forming colloids where $\mu-\mu_1=\mu_a=0$ for equilibrium ensembles, i.e. $\mu$ is set by the quenched shear stresses, while $\mu_a$ becomes again negative otherwise., Comment: 7 pages, 6 figures

Generalizing recent work on isotropic tensor fields in isotropic and achiral condensed matter systems from two to arbitrary dimensions we address both mathematical aspects assuming perfectly isotropic systems and applications focusing on correlation functions of displacement and strain field components in amorphous solids. Various general points are exemplified using simulated polydisperse Lennard-Jones particles in two dimensions. It is shown that the strain components in reciprocal space have essentially a complex circularly-symmetric Gaussian distribution albeit weak non-Gaussianity effects become visible for large wavenumbers q where also anisotropy effects become relevant. The dynamical strain correlation functions are strongly non-monotonic with respect to q with a minimum roughly at the breakdown of the continuum limit., Comment: 22 pages, 11 figures, 1 tables

PDE-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes that are required to accurately compute the PDE solution introduce an enormous number of parameters and require large scale computing resources such as more processors and more memory to solve such systems in a reasonable time. For inverse problems constrained by time dependent PDEs, the adjoint method that is often employed to efficiently compute gradients and higher order derivatives requires solving a time-reversed, so-called adjoint PDE that depends on the forward PDE solution at each timestep. This necessitates the storage of a high dimensional forward solution vector at every timestep. Such a procedure quickly exhausts the available memory resources. Several approaches that trade additional computation for reduced memory footprint have been proposed to mitigate the memory bottleneck, including checkpointing and compression strategies. In this work, we propose a close-to-ideal scalable compression approach using autoencoders to eliminate the need for checkpointing and substantial memory storage, thereby reducing both the time-to-solution and memory requirements. We compare our approach with checkpointing and an off-the-shelf compression approach on an earth-scale ill-posed seismic inverse problem. The results verify the expected close-to-ideal speedup for both the gradient and Hessian-vector product using the proposed autoencoder compression approach. To highlight the usefulness of the proposed approach, we combine the autoencoder compression with the data-informed active subspace (DIAS) prior to show how the DIAS method can be affordably extended to large scale problems without the need of checkpointing and large memory.

Strain correlation functions in two-dimensional isotropic elastic bodies are shown both theoretically (using the general structure of isotropic tensor fields) and numerically (using a glass-forming model system) to depend on the coordinates of the field variable (position vector r in real space or wavevector q in reciprocal space) and thus on the direction of the field vector and the orientation of the coordinate system. Since the fluctuations of the longitudinal and transverse components of the strain field in reciprocal space are known in the long-wavelength limit from the equipartition theorem, all components of the correlation function tensor field are imposed and no additional physical assumptions are needed. An observed dependence on the field vector direction thus cannot be used as an indication for anisotropy or for a plastic rearrangement. This dependence is different for the associated strain response field containing also information on the localized stress perturbation, Comment: 17 pages, 7 figures. arXiv admin note: text overlap with arXiv:2303.16571

Correlation functions of components of second-order tensor fields in isotropic systems can be reduced to an isotropic forth-order tensor field characterized by a few invariant correlation functions (ICFs). It is emphasized that components of this field depend in general on the coordinates of the field vector variable and thus on the orientation of the coordinate system. These angular dependencies are distinct from those of ordinary anisotropic systems. As a simple example of the procedure to obtain the ICFs we discuss correlations of time-averaged stresses in isotropic glasses where only one ICF in reciprocal space becomes a finite constant e for large sampling times and small wavevectors. It is shown that e is set by the typical size of the frozen-in stress components normal to the wavevectors, i.e. it is caused by the symmetry breaking of the stress for each independent configuration. Using the presented general mathematical formalism for isotropic tensor fields this finding explains in turn the observed long-range stress correlations in real space. Under additional but rather general assumptions e is shown to be given by a thermodynamic quantity, the equilibrium Young modulus E. We thus relate for certain isotropic amorphous bodies the existence of finite Young or shear moduli to the symmetry breaking of a stress component in reciprocal space., Comment: 21 pages, 9 figures

Human-robot interaction relies on a noise-robust audio processing module capable of estimating target speech from audio recordings impacted by environmental noise, as well as self-induced noise, so-called ego-noise. While external ambient noise sources vary from environment to environment, ego-noise is mainly caused by the internal motors and joints of a robot. Ego-noise and environmental noise reduction are often decoupled, i.e., ego-noise reduction is performed without considering environmental noise. Recently, a variational autoencoder (VAE)-based speech model has been combined with a fully adaptive non-negative matrix factorization (NMF) noise model to recover clean speech under different environmental noise disturbances. However, its enhancement performance is limited in adverse acoustic scenarios involving, e.g. ego-noise. In this paper, we propose a multichannel partially adaptive scheme to jointly model ego-noise and environmental noise utilizing the VAE-NMF framework, where we take advantage of spatially and spectrally structured characteristics of ego-noise by pre-training the ego-noise model, while retaining the ability to adapt to unknown environmental noise. Experimental results show that our proposed approach outperforms the methods based on a completely fixed scheme and a fully adaptive scheme when ego-noise and environmental noise are present simultaneously., Comment: Accepted to the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023)

This work unifies the analysis of various randomized methods for solving linear and nonlinear inverse problems by framing the problem in a stochastic optimization setting. By doing so, we show that many randomized methods are variants of a sample average approximation. More importantly, we are able to prove a single theoretical result that guarantees the asymptotic convergence for a variety of randomized methods. Additionally, viewing randomized methods as a sample average approximation enables us to prove, for the first time, a single non-asymptotic error result that holds for randomized methods under consideration. Another important consequence of our unified framework is that it allows us to discover new randomization methods. We present various numerical results for linear, nonlinear, algebraic, and PDE-constrained inverse problems that verify the theoretical convergence results and provide a discussion on the apparently different convergence rates and the behavior for various randomized methods.

Focusing on non-ergodic macroscopic systems we reconsider the variances of time averages time-series. The total variance (direct average over all time-series) is known to be the sum of an internal variance (fluctuations within the meta-basins) and an external variance (fluctuations between meta-basins). It is shown that whenever the time-averaged observable can be expressed as a volume average of a local field the three variances can be written as volume averages of correlation functions with the total correlation function being the sum of an internal and an external correlation function. The dependences of the the different variancescan thus be traced back to the internal and the external correlation function. Various relations are illustrated using lattice spring models with spatially correlated spring constants., Comment: 15 pages, 14 figures

Focusing on simulated polymer glasses well below the glass transition, we confirm the validity and the efficiency of the recently proposed simple-average expression $G(t) = \mu_A - h(t)$ for the computational determination of the shear stress relaxation modulus $G(t)$. Here, $\mu_A = G(0)$ characterizes the affine shear transformation of the system at $t=0$ and $h(t)$ the mean-square displacement of the instantaneous shear stress as a function of time $t$. This relation is seen to be particulary useful for systems with quenched or sluggish transient shear stresses which necessarily arise below the glass transition. The commonly accepted relation $G(t)=c(t)$ using the shear stress auto-correlation function $c(t)$ becomes incorrect in this limit., Comment: 5 pages, 2 figures. arXiv admin note: text overlap with arXiv:1711.00725

Assuming Gaussian chain statistics along the chain contour, we generate by means of a proper fractal generator hyperbranched polymer trees which are marginally compact. Static and dynamical properties, such as the radial intrachain pair density distribution or the shear-stress relaxation modulus, are investigated theoretically and by means of computer simulations. We emphasize that albeit the self-contact density diverges logarithmically with the total mass $N$, this effect becomes rapidly irrelevant with increasing spacer length $S$. In addition to this it is seen that the standard Rouse analysis must necessarily become inappropriate for compact objects for which the relaxation time $\tau_p$ of mode $p$ must scale as $\tau_p \sim (N/p)^{5/3}$ rather than the usual square power law for linear chains., Comment: 14 pages, 11 figures

We investigate simple models for strictly non-ergodic stochastic processes $x_t$ ($t$ being the discrete time step) focusing on the expectation value $v$ and the standard deviation $\delta v$ of the empirical variance $v[x]$ of finite time series $x$. $x_t$ is averaged over a fluctuating field $\sigma_{r}$ ($r$ being the microcell position) characterized by a quenched spatially correlated Gaussian field. Due to the quenched field $\delta v(\Delta t)$ becomes a finite constant, $\Delta_{ne} > 0$, for large sampling times $\Delta t$. The volume dependence of the non-ergodicity parameter $\Delta_{ne}$ is investigated for different spatial correlations. Models with marginally long-ranged $\fr$-correlations are successfully mapped on shear-stress data from simulated amorphous glasses of polydisperse beads., Comment: 11 pages, 8 figures

The possibility of two interaction regions (IRs) is a design requirement for the Electron Ion Collider (the EIC). There is also a significant interest from the nuclear physics community in a 2nd IR with measurements capabilities complementary to those of the first IR. While the 2nd IR will be in operation over the entire energy range of ~20GeV to ~140GeV center of mass (CM). The 2nd IR can also provide an acceptance coverage complementary to that of the first. We present a brief overview and the current progress of the 2nd IR design in terms of the parameters, magnet layout, and beam dynamics., Comment: To be published in the proceedings of IPAC'21

We investigate the standard deviation $\delta v(\tsamp)$ of the variance $v[\xbf]$ of time series $\xbf$ measured over a finite sampling time $\tsamp$ focusing on non-ergodic systems where independent "configurations" $c$ get trapped in meta-basins of a generalized phase space. It is thus relevant in which order averages over the configurations $c$ and over time series $k$ of a configuration $c$ are performed. Three variances of $v[\xbf_{ck}]$ must be distinguished: the total variance $\dvtot = \dvint + \dvext$ and its contributions $\dvint$, the typical internal variance within the meta-basins, and $\dvext$, characterizing the dispersion between the different basins. We discuss simplifications for physical systems where the stochastic variable $x(t)$ is due to a density field averaged over a large system volume $V$. The relations are illustrated for the shear-stress fluctuations in quenched elastic networks and low-temperature glasses formed by polydisperse particles and free-standing polymer films. The different statistics of $\svint$ and $\svext$ are manifested by their different system-size dependence, Comment: 15 pages, 10 figures

We use holography to investigate the dynamics of a vortex-anti-vortex dipole in a strongly coupled superfluid in 2+1 dimensions. The system is evaluated in numerical real-time simulations in order to study the evolution of the vortices as they approach and eventually annihilate each other. A tracking algorithm with sub-plaquette resolution is introduced which permits a high-precision determination of the vortex trajectories. With the increased precision of the trajectories it becomes possible to directly compute the vortex velocities and accelerations. We find that in the holographic superfluid the vortices follow universal trajectories independent of their initial separation, indicating that a vortex-anti-vortex pair is fully characterized by its separation. Subtle non-universal effects in the vortex motion at early times of the evolution can be fully attributed to artifacts due to the numerical initialization of the vortices. We also study the dependence of the dynamics on the temperature of the superfluid., Comment: 46 pages

Holographic duality provides a description of strongly coupled quantum systems in terms of weakly coupled gravitational theories in a higher-dimensional space. It is a challenge, however, to quantitatively determine the physical parameters of the quantum systems corresponding to generic holographic theories. Here, we address this problem for the two-dimensional holographic superfluid, known to exhibit strong dissipation. We numerically simulate the motion of a vortex dipole and perform a high-precision matching of the corresponding dynamics resulting from the dissipative Gross-Pitaevskii equation. Excellent agreement is found for the vortex core shape and the spatio-temporal trajectories. A further comparison to the Hall-Vinen-Iordanskii equations for point vortices interacting with the superfluid allows us to determine the friction parameters of the holographic superfluid. Our results suggest that holographic vortex dynamics can be applied to experimentally accessible superfluids like strongly coupled ultracold Bose gases or thin helium films with temperatures in the Kelvin range. This would make holographic far-from-equilibrium dynamics and turbulence amenable to experimental tests., Comment: 16 pages; videos and additional material at https://www.thphys.uni-heidelberg.de/~holography/holoDGPE

Extending recent work on stress fluctuations in complex fluids and amorphous solids we describe in general terms the ensemble average $v(\Delta t)$ and the standard deviation $\delta v(\Delta t)$ of the variance $v[\mathbf{x}]$ of time series $\mathbf{x}$ of a stochastic process $x(t)$ measured over a finite sampling time $\Delta t$. Assuming a stationary, Gaussian and ergodic process, $\delta v$ is given by a functional $\delta v_G[h]$ of the autocorrelation function $h(t)$. $\delta v(\Delta t)$ is shown to become large and similar to $v(\Delta t)$ if $\Delta t$ corresponds to a fast relaxation process. Albeit $\delta v = \delta v_G[h]$ does not hold in general for non-ergodic systems, the deviations for common systems with many microstates are merely finite-size corrections. Various issues are illustrated for shear-stress fluctuations in simple coarse-grained model systems., Comment: 19 pages, 18 figures, submitted to EPJE