Search for: All records

Deep‐focus earthquakes at 350–660 km are presumably caused by olivine‐spinel phase transformation (PT). This cannot, however, explain the observed high seismic strain rate, which requires PT to complete within seconds, while metastable olivine does not transform for over a million years. Recent theory quantitatively describes how severe plastic deformations (SPD) can solve this dilemma but lacking experimental proof. Here, we introduce dynamic rotational diamond anvil cell with rough diamond anvils to impose SPD on San Carlos olivine. While olivine never transformed to spinel at room temperature, we obtained reversible olivine‐ringwoodite PT under SPD at 15–28 GPa within tens of seconds. The PT pressure reduces with increasing dislocation density, microstrain, plastic strain, and decreasing crystallite size. Results demonstrate a new strain‐induced PT mechanism compared to a pressure/temperature‐induced one. Combined with SPD during olivine subduction, this mechanism can accelerate olivine‐ringwoodite PT from millions of years to timescales relevant to earthquakes. 

This paper proposes a novel oversampling approach that strives to balance the class priors with a considerably imbalanced data distribution of high dimensionality. The crux of our approach lies in learning interpretable latent representations that can model the synthetic mechanism of the minority samples by using a generative adversarial network (GAN). A Bayesian regularizer is imposed to guide the GAN to extract a set of salient features that are either disentangled or intentionally entangled, with their interplay controlled by a prescribed structure, defined with human-in-the-loop. As such, our GAN enjoys an improved sample complexity, being able to synthesize high-quality minority samples even if the sizes of minority classes are extremely small during training. Empirical studies substantiate that our approach can empower simple classifiers to achieve superior imbalanced classification performance over the state-of-the-art competitors and is robust across various imbalance settings. Code is released in github.com/fudonglin/IMSIC. 

Garnet is an important mineral phase in the upper mantle as it is both a key component in bulk mantle rocks, and a primary phase at high-pressure within subducted basalt. Here, we focus on the strength of garnet and the texture that develops within garnet during accommodation of differential deformational strain. We use X-ray diffraction in a radial geometry to analyze texture development in situ in three garnet compositions under pressure at 300 K: a natural garnet (Prp60Alm37) to 30 GPa, and two synthetic majorite-bearing compositions (Prp59Maj41 and Prp42Maj58) to 44 GPa. All three garnets develop a modest (100) texture at elevated pressure under axial compression. Elasto-viscoplastic self-consistent (EVPSC) modeling suggests that two slip systems are active in the three garnet compositions at all pressures studied: {110}<1-21 11> and {001}<110>. We determine a flow strength of ~5 GPa at pressures between 10 to 15 GPa for all three garnets; these values are higher than previously measured yield strengths measured on natural and majoritic garnets. Strengths calculated using the experimental lattice strain differ from the strength generated from those calculated using EVPSC. Prp67Alm33, Prp59Maj41 and Prp42Maj58 are of comparable strength to each other at room temperature, which indicates that majorite substitution does not greatly affect the strength of garnets. Additionally, all three garnets are of similar strength as lower mantle phases such as bridgmanite and ferropericlase, suggesting that garnet may not be notably stronger than the surrounding lower mantle/deep upper mantle phases at the base of the upper mantle. 

This work considers the sample and computational complexity of obtaining an $$\epsilon$$-optimal policy in a discounted Markov Decision Process (MDP), given only access to a generative model. In this model, the learner accesses the underlying transition model via a sampling oracle that provides a sample of the next state, when given any state-action pair as input. We are interested in a basic and unresolved question in model based planning: is this naïve “plug-in” approach — where we build the maximum likelihood estimate of the transition model in the MDP from observations and then find an optimal policy in this empirical MDP — non-asymptotically, minimax optimal? Our main result answers this question positively. With regards to computation, our result provides a simpler approach towards minimax optimal planning: in comparison to prior model-free results, we show that using \emph{any} high accuracy, black-box planning oracle in the empirical model suffices to obtain the minimax error rate. The key proof technique uses a leave-one-out analysis, in a novel “absorbing MDP” construction, to decouple the statistical dependency issues that arise in the analysis of model-based planning; this construction may be helpful more generally. 

Photoacoustic laser streaming provides a versatile technique to manipulate liquids and their suspended objects with light. However, only gold was used in the initial demonstrations. In this work, we first demonstrate that laser streaming can be achieved with common non-plasmonic metals such as Fe and W by their ion implantations in transparent substrates. We then investigate the effects of ion dose, substrate material and thickness on the strength and duration of streaming. Finally, we vary laser pulse width, repetition rate and power to understand the observed threshold power for laser streaming. It is found that substrate thickness has a negligible effect on laser streaming down to 0.1 mm, glass and quartz produce much stronger streaming than sapphire because of their smaller thermal conductivity, while quartz exhibits the longest durability than glass and sapphire under the same laser intensity. Compared with Au, Fe and W with higher melting points show a longer lifetime although they require a higher laser intensity to achieve a similar speed of streaming. To generate a continuous laser streaming, the laser must have a minimum pulse repetition rate of 10 Hz and meet the minimum pulse width and energy to generate a transient vapor layer. This vapor layer enhances the generation of ultrasound waves, which are required for observable fluid jets. Principles of laser streaming and temperature simulation are used to explain these observations, and our study paves the way for further materials engineering and device design for strong and durable laser streaming.