Search arXivSearch

arXiv · 1606.06608

Engineering dissipation with phononic spectral hole burning

Abstract

Optomechanics, nano-electromechanics, and integrated photonics have brought about a renaissance in phononic device physics and technology. Central to this advance are devices and materials that support ultra long-lived photonic and phononic excitations, providing access to novel regimes of classical and quantum dynamics based on tailorable photon-phonon coupling. Silica-based devices have been at the forefront of such innovations for their ability to support optical excitations persisting for nearly 1 billion cycles, and for their low optical nonlinearity. Remarkably, acoustic phonon modes can persist for a comparable number of cycles in crystalline solids at cryogenic temperatures, permitting radical enhancement of photon-phonon coupling. However, it has not been possible to achieve similar phononic coherence times in silica, as silica becomes acoustically opaque at low temperatures. In this paper, we demonstrate that intrinsic forms of phonon dissipation are greatly reduced (by > 90%) using nonlinear saturation with continuous driving fields of disparate frequencies. We demonstrate steady-state phononic spectral hole burning for the first time, and show that this technique for controlling dissipation in glass produces a wide-band transparency window. These studies were carried out in a micro-scale fiber waveguide where the acoustic intensities necessary to manipulate phonon dissipation can be achieved with optically generated phonon fields of modest (nW) powers. We developed a simple model that explains both dissipative and dispersive changes produced by phononic saturation. In showing how the dissipative and dispersive properties of glasses can be manipulated using external fields, we open the door to dynamical phononic switching and the use of glasses as low loss phononic media which may enable new forms of controllable laser dynamics, information processing, and precision metrology.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

R. O. Behunin, P. Kharel, W. H. Renninger, P. T. Rakich. 2016-06-21. Engineering dissipation with phononic spectral hole burning. https://doi.org/10.1038/nmat4819

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The critical slowing down in training diffusion models

Computational sampling has been central to the sciences since the mid-20th century. While machine-learning-based approaches have recently enabled major advances, their behavior remains poorly understood, with limited theoretical control over when and why they succeed. Here we provide such insight for diffusion models---a class of generative schemes highly effective in practice---by analyzing their application to the $O(n)$ model of statistical field theory in the Gaussian limit $n \to \infty$. In this analytically tractable setting, we show that training a score model with a one-layer network architecture matching the exact solution exhibits a form of critical slowing down in parameter learning. This slowing down also impacts the generation process, indicating that the well-known difficulties of sampling near criticality persist even for learned generative models. To overcome this bottleneck, we consider the power of architectural depth. We find that using a two-layer architecture drastically reduces the critical slowing down, with the training time scaling logarithmically rather than quadratically with system size. Using a Fourier implementation of the architecture, we further show that this acceleration in training time can be achieved without drastically increasing operational complexity. Taken together, these results demonstrate that diffusion models can overcome the critical slowing down through appropriate architectural design, and establish a controlled framework for understanding and improving learned sampling methods in statistical physics and beyond.

cond-mat.dis-nn

Switching diffusivity selects Pareto tail exponent in random growth with redistribution

Random multiplicative growth with redistribution generates stationary Pareto wealth tails in the Bouchaud-Mézard model, but assumes a fixed multiplicative noise intensity. This is restrictive for physical and financial growth processes, where volatility (diffusivity) is often fluctuating. We replace the constant noise intensity by a switching diffusivity and ask how these fluctuations select the Pareto stationary tail. For a geometric Brownian motion with switching diffusivity, the long-time Gaussian limit holds when the redraw law has finite mean and variance. The asymptotic variance retains a contribution from diffusivity persistence. With redistribution and a general redraw law, the stationary large-wealth problem is characterized by a spectral condition for admissible algebraic modes. For a two-state diffusivity, an exact tail analysis gives a Pareto exponent interpolating between the high-diffusivity slow-refresh limit and the mean-diffusivity fast-refresh Bouchaud-Mézard limit.

cond-mat.dis-nn

Signatures of Nonergodicity in Sparse Random Matrices

The prevalence of sparsity in the Fock space graph of interacting many-body systems motivates an investigation into the spectral statistics of sparse random matrices with on-site disorder. We numerically determine the delocalization-localization transition in the ground state as a function of the sparsity. The short-range energy correlation in the bulk indicates that the Anderson transition at infinite temperature occurs at the critical percolation limit of the sparse graph. By analytically deriving the energy moments and calculating the shifted kurtosis, we show that the critical sparsity threshold matches the Anderson transition. Furthermore, long-range energy correlations in the bulk spectrum reveal a Thouless energy scale, suggesting a broad nonergodic regime within the delocalized phase.

cond-mat.dis-nn