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In designing material functionality within the intricate realm of transition metal oxides, lattice structure and d-orbital occupancy are two principal determinants of the correlated physical properties, such as superconductivity. However, the modulation of these two factors is inherently limited by the need to balance thermodynamic stability, kinetic mobility, and synthesis precision, particularly for oxidation-demanding phases. We introduce a methodology, namely the gigantic-oxidative atomically layered epitaxy (GOAL-Epitaxy), enhancing oxidation power 3-4 orders of magnitude beyond oxide molecular beam epitaxy (OMBE) and pulsed laser deposition (PLD), while ensuring atomic-layer-by-layer growth of designed complex structures. Consequently, thermodynamic stability is markedly augmented at elevated temperatures, improving growth kinetics. We demonstrate the accurate synthesis of complex nickelates and cuprates, especially an artificially designed structure as a parent of high-temperature superconductivity, in which alternating single and double NiO2 layers possess distinct nominal d-orbital occupancy. The GOAL-Epitaxy enables material discovery within the vastly broadened growth parameter space.

Revealing the momentum-resolved electronic structure of infinite-layer nickelates is essential for understanding this new class of unconventional superconductors, but has been hindered by the formidable challenges in improving the sample quality. In this work, we report for the first time the angle-resolved photoemission spectroscopy of superconducting La$_{0.8}$Sr$_{0.2}$NiO$_{2}$ films prepared by molecular beam epitaxy and ${\mathrm{\textit{in situ}}}$ atomic-hydrogen reduction. The measured Fermi topology closely matches theoretical calculations, showing a large Ni-$d_{x^2-y^2}$ derived Fermi sheet that evolves from hole-like to electron-like along $k_{z}$, and a three-dimensional (3D) electron pocket centered at Brillouin zone corner. The Ni-$d_{x^2-y^2}$ derived bands show a mass enhancement ($m^*/m_{\rm{DFT}}$) of 2-3,while the 3D electron band shows negligible band renormalization. Moreover, the Ni-$d_{x^2-y^2}$ derived states also display a band dispersion anomaly at higher binding energy, reminiscent of the waterfall feature and kinks observed in cuprates., Comment: 29 pages,13 figures

The observation of superconductivity in infinite-layer nickelates has attracted significant attention due to its potential as a new platform for exploring high $ \mathrm{\textit{T}}_{c} $ superconductivity. However, thus far, superconductivity has only been observed in epitaxial thin films, which limits the manipulation capabilities and modulation methods compared to two-dimensional exfoliated materials. Given the exceptionally giant strain tunability and stacking capability of freestanding membranes, separating superconducting nickelates from the as-grown substrate is a novel way to engineer the superconductivity and uncover the underlying physics. Herein, we report the synthesis of the superconducting freestanding $ \mathrm{La}_{0.8}\mathrm{Sr}_{0.2}\mathrm{Ni}\mathrm{O}_{2} $ membranes ($ \mathrm{\textit{T}}_{c}\mathrm{=}\mathrm{10.9}\;\mathrm{K} $), emphasizing the crucial roles of the interface engineering in the precursor phase film growth and the quick transfer process in achieving superconductivity. Our work offers a new versatile platform for investigating the superconductivity in nickelates, such as the pairing symmetry via constructing Josephson tunneling junctions and higher $ \mathrm{\textit{T}}_{c} $ values via high-pressure experiments., Comment: 20 pages, 9 figures

Freestanding perovskite oxide membranes have drawn great attention recently since they offer exceptional structural tunability and stacking ability, providing new opportunities in fundamental research and potential device applications in silicon-based semiconductor technology. Among different types of sacrificial layers, the $ \mathrm{(Ca, Sr, Ba)}_{3}\mathrm{Al}_{2}\mathrm{O}_{6}$ compounds are most widely used since they can be dissolved in water and prepare high-quality perovskite oxide membranes with clean and sharp surfaces and interfaces. However, the typical transfer process takes a long time (up to hours) in obtaining millimeter-size freestanding membranes, let alone realize wafer-scale samples with high yield. Here, we introduce a new member of the $ \mathrm{SrO-}\mathrm{Al}_{2}\mathrm{O}_{3}$ family,$ \mathrm{Sr}_{4}\mathrm{Al}_{2}\mathrm{O}_{7},$, and demonstrate its high dissolution rate, about 10 times higher than that of $ \mathrm{Sr}_{3}\mathrm{Al}_{2}\mathrm{O}_{6}$. The high-dissolution-rate of $ \mathrm{Sr}_{4}\mathrm{Al}_{2}\mathrm{O}_{7}$ is most likely related to the more discrete Al-O networks and higher concentration of water-soluble Sr-O species in this compound. Our work significantly facilitates the preparation of freestanding membranes and sheds light on the integration of multifunctional perovskite oxides in practical electronic devices., Comment: 11 pages,4 figures

Join order selection (JOS) is the problem of ordering join operations to minimize total query execution cost and it is the core NP-hard combinatorial optimization problem of query optimization. In this paper, we present JoinGym, a lightweight and easy-to-use query optimization environment for reinforcement learning (RL) that captures both the left-deep and bushy variants of the JOS problem. Compared to existing query optimization environments, the key advantages of JoinGym are usability and significantly higher throughput which we accomplish by simulating query executions entirely offline. Under the hood, JoinGym simulates a query plan's cost by looking up intermediate result cardinalities from a pre-computed dataset. We release a novel cardinality dataset for $3300$ SQL queries based on real IMDb workloads which may be of independent interest, e.g., for cardinality estimation. Finally, we extensively benchmark four RL algorithms and find that their cost distributions are heavy-tailed, which motivates future work in risk-sensitive RL. In sum, JoinGym enables users to rapidly prototype RL algorithms on realistic database problems without needing to setup and run live systems., Comment: JoinGym is available at https://github.com/kaiwenw/JoinGym!

The recently emerging superconductivity in infinite-layer nickelates, with isostructure and isoelectron of cuprates, provides a new platform to explore the pairing mechanism of high-temperature superconductors. In this work, we studied the upper critical field ($H_{\rm{c2}}$) of a high-quality La$_{0.8}$Sr$_{0.2}$NiO$_{2}$ thin film with superconducting transition temperature, $T_{\rm{c}}$ = 18.8 K, using high magnetic field up to 56 T. A very large $H_{\rm{c2}}$, $\sim$ 40 T for $H$ $\Arrowvert$ $c$ and $\sim$ 52 T for $H$ $\Arrowvert$ $ab$, was confirmed, which suggests that infinite-layer nickelates also have great application potential. The anisotropy of $H_{\rm{c2}}$ monotonically decreases from $\sim$ 10 near $T_{\rm{c}}$ to $\sim$ 1.5 at 2 K. Angle dependence of $H_{\rm{c2}}$ confirms the crossover of superconductivity from two-dimensional (2D) to three-dimensional (3D) as the temperature decreases. We discussed that the interstitial orbital effect causes the weakening of anisotropy. The observed abnormal upturning of $H_{\rm{c2}}$ at low temperatures is found to be a universal behavior independent of film quality and rare earth elements. Therefore, it should not be the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state due to the fact that it is in the dirty limit and insensitive to disorder., Comment: 8 pages, 5 figures

We present Ditto, an automated framework for cloning end-to-end cloud applications, both monolithic and microservices, which captures I/O and network activity, as well as kernel operations, in addition to application logic. Ditto takes a hierarchical approach to application cloning, starting with capturing the dependency graph across distributed services, to recreating each tier's control/data flow, and finally generating system calls and assembly that mimics the individual applications. Ditto does not reveal the logic of the original application, facilitating publicly sharing clones of production services with hardware vendors, cloud providers, and the research community. We show that across a diverse set of single- and multi-tier applications, Ditto accurately captures their CPU and memory characteristics as well as their high-level performance metrics, is portable across platforms, and facilitates a wide range of system studies.

In this paper, we propose a new secure machine learning inference platform assisted by a small dedicated security processor, which will be easier to protect and deploy compared to today's TEEs integrated into high-performance processors. Our platform provides three main advantages over the state-of-the-art: (i) We achieve significant performance improvements compared to state-of-the-art distributed Privacy-Preserving Machine Learning (PPML) protocols, with only a small security processor that is comparable to a discrete security chip such as the Trusted Platform Module (TPM) or on-chip security subsystems in SoCs similar to the Apple enclave processor. In the semi-honest setting with WAN/GPU, our scheme is 4X-63X faster than Falcon (PoPETs'21) and AriaNN (PoPETs'22) and 3.8X-12X more communication efficient. We achieve even higher performance improvements in the malicious setting. (ii) Our platform guarantees security with abort against malicious adversaries under honest majority assumption. (iii) Our technique is not limited by the size of secure memory in a TEE and can support high-capacity modern neural networks like ResNet18 and Transformer. While previous work investigated the use of high-performance TEEs in PPML, this work represents the first to show that even tiny secure hardware with really limited performance can be leveraged to significantly speed-up distributed PPML protocols if the protocol can be carefully designed for lightweight trusted hardware., Comment: IEEE S&P'24 submitted

Planning-based reinforcement learning has shown strong performance in tasks in discrete and low-dimensional continuous action spaces. However, planning usually brings significant computational overhead for decision-making, and scaling such methods to high-dimensional action spaces remains challenging. To advance efficient planning for high-dimensional continuous control, we propose Trajectory Autoencoding Planner (TAP), which learns low-dimensional latent action codes with a state-conditional VQ-VAE. The decoder of the VQ-VAE thus serves as a novel dynamics model that takes latent actions and current state as input and reconstructs long-horizon trajectories. During inference time, given a starting state, TAP searches over discrete latent actions to find trajectories that have both high probability under the training distribution and high predicted cumulative reward. Empirical evaluation in the offline RL setting demonstrates low decision latency which is indifferent to the growing raw action dimensionality. For Adroit robotic hand manipulation tasks with high-dimensional continuous action space, TAP surpasses existing model-based methods by a large margin and also beats strong model-free actor-critic baselines., Comment: Accepted by ICLR2023. Code available at https://github.com/ZhengyaoJiang/latentplan

The aggressive performance optimizations in modern microprocessors can result in security vulnerabilities. For example, timing-based attacks in processor caches can steal secret keys or break randomization. So far, finding cache-timing vulnerabilities is mostly performed by human experts, which is inefficient and laborious. There is a need for automatic tools that can explore vulnerabilities given that unreported vulnerabilities leave the systems at risk. In this paper, we propose AutoCAT, an automated exploration framework that finds cache timing-channel attack sequences using reinforcement learning (RL). Specifically, AutoCAT formulates the cache timing-channel attack as a guessing game between an attack program and a victim program holding a secret. This guessing game can thus be solved via modern deep RL techniques. AutoCAT can explore attacks in various cache configurations without knowing design details and under different attack and victim program configurations. AutoCAT can also find attacks to bypass certain detection and defense mechanisms. In particular, AutoCAT discovered StealthyStreamline, a new attack that is able to bypass performance counter-based detection and has up to a 71% higher information leakage rate than the state-of-the-art LRU-based attacks on real processors. AutoCAT is the first of its kind in using RL for crafting microarchitectural timing-channel attack sequences and can accelerate cache timing-channel exploration for secure microprocessor designs.

After being expected as a promising analogue to cuprates for decades, superconductivity was recently discovered in infinite-layer nickelates, providing new opportunities to explore mechanisms of high-temperature superconductivity. However, in sharp contrast to the single-band quasi-two-dimensional superconductivity in cuprates, nickelates exhibit a multi-band electronic structure and an unexpected isotropic superconductivity as reported recently, which challenges the cuprate-like picture in nickelates. Here, we show the superconductivity in nickelates is actually anisotropic and quasi-two-dimensional in nature, as that in cuprates. By synthesizing high-quality lanthanide nickelate films with enhanced crystallinity and superconductivity ($T_{c}^{onset}$ = 18.8 K, $T_{c}^{zero}$ = 16.5 K), strong anisotropic magnetotransport behaviors have been observed. The quasi-two-dimensional nature is further confirmed by the existence of a cusp-like peak of the angle-dependent $T_{c}$, and a Berezinskii-Kosterlitz-Thouless transition near $T_{c}$. Our work thus suggests a quasi-two-dimensional superconductivity in infinite-layer nickelates, implying a single-3$d_{x^2-y^2}$-band cuprate-like picture may remain valid in these compounds., Comment: 32 pages, 4 main figures, 6 extended data

A series of Ruddlesden-Popper nickelates, Nd$_{n+1}$Ni$_{n}$O$_{3n+1}$ (${n}$ = 1-5), have been stabilized in thin film form using reactive molecular-beam epitaxy. High crystalline quality has been verified by X-ray diffraction and scanning transmission electron microscopy. X-ray photoelectron spectroscopy indicates the ${n}$-dependent valence states of nickel in these compounds. Metal-insulator transitions show clear ${n}$ dependence for intermediate members (${n}$ = 3-5), and the low-temperature resistivities of which show logarithmic dependence, resembling the Kondo-scattering as observed in the parent compounds of superconducting infinite-layer nickelates., Comment: 12 pages, 4 figures

The recent discovery of superconductivity in infinite-layer nickelate films has aroused great interest since it provides a new platform to explore the mechanism of high-temperature superconductivity. However, superconductivity only appears in the thin film form and synthesizing superconducting nickelate films is extremely challenging, limiting the in-depth studies on this compound. Here, we explore the critical parameters in the growth of high quality nickelate films using molecular beam epitaxy (MBE). We found that stoichiometry is crucial in optimizing the crystalline structure and realizing superconductivity in nickelate films. In precursor NdNiO3 films, optimal stoichiometry of cations yields the most compact lattice while off-stoichiometry of cations causes obvious lattice expansion, influencing the subsequent topotactic reduction and the emergence of superconductivity in infinite-layer nickelates. Surprisingly, in-situ reflection high energy electron diffraction (RHEED) indicates that some impurity phases always appear once Sr ions are doped into NdNiO3 although the X-ray diffraction (XRD) data are of high quality. While these impurity phases do not seem to suppress the superconductivity, their impacts on the electronic and magnetic structure deserve further studies. Our work demonstrates and highlights the significance of cation stoichiometry in superconducting nickelate family., Comment: 12 pages, 3 figures

The newly found superconductivity in infinite-layer nickelate superconducting films has attracted much attention, because their crystalline and electronic structures are similar to high-$T_c$ cuprate superconductors. The upper critical field can provide much information on superconductivity, but detailed experimental data are still lacking in these films. Here we present temperature and angle dependence of resistivity measured under different magnetic fields ($H$) in Nd$_{0.8}$Sr$_{0.2}$NiO$_{2}$ thin films. The onset superconducting transition occurs at about 16.2 K at 0 T. Temperature dependent upper critical fields determined by using a criterion very close to the onset transition show a clear negative curvature near the critical transition temperature, which is explained as the consequence of the paramagnetically limited effect on superconductivity. The temperature dependent anisotropy of the upper critical field is obtained from resistivity data, which yields a value decreasing from 3 to 1.2 with lowering temperature. This can be explained by a variable contribution from the orbital limit effect on upper critical field. The angle dependent resistivity at a fixed temperature and different magnetic fields cannot be scaled to one curve, which deviates from the prediction of the anisotropic Ginzburg-Landau theory. However, at low temperatures, the increased resistivity by magnetic field can be scaled by the parameter $H^\beta |\cos\theta|$ ($1<\beta<6$) with $\theta$ the angle enclosed between $c$-axis and the applied magnetic field. As the first detailed study on the upper critical field of the nickelate thin films, our results clearly indicate a small anisotropy and paramagnetically limited effect of superconductivity in nickelate superconductors., Comment: 22 pages, 5 figures

The pairing mechanism in cuprates remains as one of the most challenging issues in the field of condensed matter physics. The unique 3d9 electron orbital of the Cu2+ ionic states in cuprates is supposed to be the major player for the occurrence of superconductivity. Recently, superconductivity at about 9-15 K was discovered in infinite layer thin films of nickelate Nd1-xSrxNiO2 (x=0.1-0.2) which is believed to have the similar 3d9 orbital electrons. The key issue concerned here is about the superconducting gap function. Here we report the first set data of single particle tunneling measurements on the superconducting nickelate thin films. We find predominantly two types of tunneling spectra, one shows a V-shape feature which can be fitted very well by a d-wave gap function with gap maximum of about 3.9 meV, another one exhibits a full gap of about 2.35 meV. Some spectra demonstrate mixed contributions of these two components. Our results suggest that the newly found Ni-based superconductors play as close analogs to cuprates, and thus demonstrate the commonality of unconventional superconductivity., Comment: 24 pages, 4 figures in Main Text and 7 figures in Supplementary Information