Miracle-dz/UniFAR-FTUs huggingface dataset:
GLM-130B: An Open Bilingual Pre-trained Model

We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as good as GPT-3 (davinci) and unveil how models of such a scale can be successfully pre-trained. Over the course of this effort, we face numerous unexpected technical and engineering challenges, particularly on loss spikes and divergence. In this paper, we introduce the training process of GLM-130B including its design choices, training strategies for both efficiency and stability, and engineering efforts. The resultant GLM-130B model offers significant outperformance over GPT-3 175B (davinci) on a wide range of popular English benchmarks while the performance advantage is not observed in OPT-175B and BLOOM-176B. It also consistently and significantly outperforms ERNIE TITAN 3.0 260B -- the largest Chinese language model -- across related benchmarks. Finally, we leverage a unique scaling property of GLM-130B to reach INT4 quantization without post training, with almost no performance loss, making it the first among 100B-scale models and more importantly, allowing its effective inference on 4$\times$RTX 3090 (24G) or 8$\times$RTX 2080 Ti (11G) GPUs, the most affordable GPUs required for using 100B-scale models. The GLM-130B model weights are publicly accessible and its code, training logs, related toolkit, and lessons learned are open-sourced at \url{https://github.com/THUDM/GLM-130B/}.
THE He ii POST-REIONIZATION EPOCH: HST/COS OBSERVATIONS OF THE QUASAR HS1700+6416

The reionization epoch of singly ionized helium (He ii) is believed to start at redshifts z ∼ 3.5–4 and be nearly complete by z ≃ 2.7. We explore the post-reionization epoch with far-ultraviolet spectra of the bright, high-redshift quasar HS1700+6416 taken by the Cosmic Origins Spectrograph (COS) on the Hubble Space Telescope, which show strong He ii (λ303.78) absorption shortward of the QSO redshift, zQSO = 2.75. We discuss these data as they probe the post-reionization history of He ii and the local ionization environment around the quasar and transverse to the line of sight, finding that quasars are likely responsible for much of the ionization. We compare previous spectra taken by the Far-Ultraviolet Spectroscopic Explorer to the current COS data, which have a substantially higher signal-to-noise ratio. The Gunn–Peterson trough recovers at lower redshifts, with the effective optical depth falling from τeff ≃ 1.8 at z ∼ 2.7 to τeff ≃ 0.7 at z ∼ 2.3, higher than has been reported in earlier work. We see an interesting excess of flux near the He ii Lyα break, which could be quasar line emission, although likely not He ii Lyα. We present spectra of four possible transverse-proximity quasars, although the UV hardness data are not of sufficient quality to say if their effects are seen along the HS1700 sightline.
Collisional excitation of doubly deuterated ammonia ND2H by para-H2

Collisional de-excitation rates of partially deuterated molecules are different from the fully hydrogenated species because of lowering of symmetry. We compute the collisional (de)excitation rates of ND2H by ground-state para-H2, extending the previous results for helium. We describe the changes in the potential energy surface of NH3–H2 involved by the presence of two deuterium nuclei. Cross-sections are calculated within the full close-coupling approach and augmented with coupled-state calculations. Collisional rate coefficients are given between 5 and 35 K, a range of temperatures which is relevant to cold interstellar conditions. We find that the collisional rates of ND2H by H2 are about 1 order of magnitude higher than those obtained with helium as perturber. These results are essential to radiative transfer modelling and will allow to interpret the millimetre and submillimetre detections of ND2H with better constraints than previously.
Buoyancy-driven bubbly flows: scaling of velocities in bubble columns operated in the heterogeneous regime

Abstract The hydrodynamics of bubble columns in the heterogeneous regime is revisited. Focusing on air–water systems at large aspect ratio, we show from dimensional analysis that buoyancy equilibrates inertia, and that velocities scale as $(gD\varepsilon )^{1/2}$, where $D$ is the bubble column diameter, $\varepsilon$ the void fraction and $g$ the gravitational acceleration. From new experiments in a $0.4$ m diameter column with ${{O}}(10^3)$ particle Reynolds number bubbles and from a detailed analysis of published data, we confirm the self-organization prevailing in the heterogeneous regime, and that the liquid flow rate is only set by the column diameter $D$. Besides, direct liquid and gas velocity measurements demonstrate that the relative velocity increases above the terminal velocity $U_T$ in the heterogeneous regime, and that it tends to ${\sim }2.4 U_T$ at very large gas superficial velocities $V_{sg}$. The proposed velocity scaling is shown to hold for liquid and gas mean velocities and for their standard deviations. Furthermore, it is found to be valid over a wide range of conditions, corresponding to Froude numbers $Fr=V_{sg}/(gD)^{1/2}$ from 0.02 to 0.5. Then, the relevance of this scaling for coalescing media is discussed. Moreover, following the successful prediction of the void fraction with a Zuber & Findlay approach at the beginning of the heterogeneous regime, we show how the void fraction is correlated with $Fr$. Further investigations are finally suggested to connect the increase in relative velocity with meso-scale structures known to exist in the heterogeneous regime.
Climatology of midlatitude ionospheric disturbances from the Very Large Array Low‐frequency Sky Survey

The results of a climatological study of ionospheric disturbances derived from observations of cosmic sources from the Very Large Array (VLA) Low‐frequency Sky Survey (VLSS) are presented. We have used the ionospheric corrections applied to the 74 MHz interferometric data within the VLSS imaging process to obtain fluctuation spectra for the total electron content (TEC) gradient on spatial scales from a few to hundreds of kilometers and temporal scales from less than one minute to nearly an hour. The observations sample nearly all times of day and all seasons. They also span latitudes and longitudes from 28°N to 40°N and 95°W to 114°W, respectively. We have binned and averaged the fluctuation spectra according to time of day, season, and geomagnetic (Kp index) and solar (F10.7) activity. These spectra provide a detailed, multiscale account of seasonal and intraday variations in ionospheric activity with wavelike structures detected at wavelengths between about 35 and 250 km. In some cases, trends between spectral power and Kp index and/or F10.7 are also apparent. In addition, the VLSS observations allow for measurements of the turbulent power spectrum down to periods of 40 s (scales of ∼0.4 km at the height of the E‐region). While the level of turbulent activity does not appear to have a strong dependence on eitherKp index or F10.7, it does appear to be more pronounced during the winter daytime, summer nighttime, and near dusk during the spring.
PARTICLE ACCELERATION DURING MAGNETOROTATIONAL INSTABILITY IN A COLLISIONLESS ACCRETION DISK

Particle acceleration during the magnetorotational instability (MRI) in a collisionless accretion disk was investigated by using a particle-in-cell simulation. We discuss the important role that magnetic reconnection plays not only on the saturation of MRI but also on the relativistic particle generation. The plasma pressure anisotropy of p⊥ > p‖ induced by the action of MRI dynamo leads to rapid growth in magnetic reconnection, resulting in the fast generation of nonthermal particles with a hard power-law spectrum. This efficient particle acceleration mechanism involved in a collisionless accretion disk may be a possible model to explain the origin of high-energy particles observed around massive black holes.
SIMPLE: A Gradient Estimator for k-Subset Sampling

$k$-subset sampling is ubiquitous in machine learning, enabling regularization and interpretability through sparsity. The challenge lies in rendering $k$-subset sampling amenable to end-to-end learning. This has typically involved relaxing the reparameterized samples to allow for backpropagation, with the risk of introducing high bias and high variance. In this work, we fall back to discrete $k$-subset sampling on the forward pass. This is coupled with using the gradient with respect to the exact marginals, computed efficiently, as a proxy for the true gradient. We show that our gradient estimator, SIMPLE, exhibits lower bias and variance compared to state-of-the-art estimators, including the straight-through Gumbel estimator when $k = 1$. Empirical results show improved performance on learning to explain and sparse linear regression. We provide an algorithm for computing the exact ELBO for the $k$-subset distribution, obtaining significantly lower loss compared to SOTA.
Stars Crushed by Black Holes. III. Mild Compression of Radiative Stars by Supermassive Black Holes

A tidal disruption event (TDE) occurs when the gravitational field of a supermassive black hole (SMBH) destroys a star. For TDEs in which the star enters deep within the tidal radius, such that the ratio of the tidal radius to the pericenter distance β satisfies β ≫ 1, the star is tidally compressed and heated. It was predicted that the maximum density and temperature attained during deep TDEs scale as ∝ β 3 and ∝ β 2, respectively, and nuclear detonation is triggered by β ≳ 5, but these predictions have been debated over the last four decades. We perform Newtonian smoothed-particle hydrodynamics simulations of deep TDEs between a Sun-like star and a 106 M ⊙ SMBH for 2 ≤ β ≤ 10. We find that neither the maximum density nor temperature follow the ∝ β 3 and ∝ β 2 scalings or, for that matter, any power-law dependence, and that the maximum-achieved density and temperature are reduced by ∼1 order of magnitude compared to past predictions. We also perform simulations in the Schwarzschild metric and find that relativistic effects modestly increase the maximum density (by a factor of ≲1.5) and induce a time lag relative to the Newtonian simulations, which is induced by time dilation. We also confirm that the time the star spends at high density and temperature is a very small fraction of its dynamical time. We therefore predict that the amount of nuclear burning achieved by radiative stars during deep TDEs is minimal.
The Power of Duality: Response Time Analysis meets Integer Programming

We study a mutually enriching connection between response time analysis in real-time systems and the mixing set problem. Thereby generalizing over known results we present a new approach to the computation of response times in fixed-priority uniprocessor real-time scheduling. We even allow that the tasks are delayed by some period-constrained release jitter. By studying a dual problem formulation of the decision problem as an integer linear program we show that worst-case response times can be computed by algorithmically exploiting a conditional reduction to an instance of the mixing set problem. In the important case of harmonic periods our new technique admits a near-quadratic algorithm to the exact computation of worst-case response times. We show that generally, a smaller utilization leads to more efficient algorithms even in fixed-priority scheduling. Worst-case response times can be understood as least fixed points to non-trivial fixed point equations and as such, our approach may also be used to solve suitable fixed point problems. Furthermore, we show that our technique can be reversed to solve the mixing set problem by computing worst-case response times to associated real-time scheduling task systems. Finally, we also apply our optimization technique to solve 4-block integer programs with simple objective functions.
ACTIVE GALACTIC NUCLEI SELECTED FROM GALEX SPECTROSCOPY: THE IONIZING SOURCE SPECTRUM AT z ∼ 1,

We use a complete sample of Lyα-emission-line-selected active galactic nuclei (AGNs) obtained from nine deep blank fields observed with the grism spectrographs on the Galaxy Evolution Explorer (GALEX) satellite to measure the normalization and the spectral shape of the AGN contribution to the ionizing background (rest-frame wavelengths 700–900 Å) at z ∼ 1. Our sample consists of 139 sources selected in the redshift range z = 0.65–1.25 in the near-ultraviolet (NUV; 2371 Å central wavelength) channel. The area covered is 8.2 deg2 to a NUV magnitude of 20.5 (AB) and 0.92 deg2 at the faintest magnitude limit of 21.8. The GALEX AGN luminosity function agrees well with those obtained using optical and X-ray AGN samples, and the measured redshift evolution of the ionizing volume emissivity is similar to that previously obtained by measuring the GALEX far-ultraviolet (FUV; 1528 Å central wavelength) magnitudes of an X-ray-selected sample. For the first time, we are able to construct the shape of the ionizing background at z ∼ 1 in a fully self-consistent way.
MAtt: A Manifold Attention Network for EEG Decoding

Recognition of electroencephalographic (EEG) signals highly affect the efficiency of non-invasive brain-computer interfaces (BCIs). While recent advances of deep-learning (DL)-based EEG decoders offer improved performances, the development of geometric learning (GL) has attracted much attention for offering exceptional robustness in decoding noisy EEG data. However, there is a lack of studies on the merged use of deep neural networks (DNNs) and geometric learning for EEG decoding. We herein propose a manifold attention network (mAtt), a novel geometric deep learning (GDL)-based model, featuring a manifold attention mechanism that characterizes spatiotemporal representations of EEG data fully on a Riemannian symmetric positive definite (SPD) manifold. The evaluation of the proposed MAtt on both time-synchronous and -asyncronous EEG datasets suggests its superiority over other leading DL methods for general EEG decoding. Furthermore, analysis of model interpretation reveals the capability of MAtt in capturing informative EEG features and handling the non-stationarity of brain dynamics.
Internal Longest Palindrome Queries in Optimal Time

Palindromes are strings that read the same forward and backward. Problems of computing palindromic structures in strings have been studied for many years with a motivation of their application to biology. The longest palindrome problem is one of the most important and classical problems regarding palindromic structures, that is, to compute the longest palindrome appearing in a string T of length n . The problem can be solved in O ( n ) time by the famous algorithm of Man-acher [Journal of the ACM, 1975]. In this paper, we consider the problem in the internal model. The internal longest palindrome query is, given a substring T [ i.j ] of T as a query, to compute the longest palindrome appearing in T [ i.j ] . The best known data structure for this problem is the one proposed by Amir et al. [Algorithmica, 2020], which can answer any query in O (log n ) time. In this paper, we propose a linear-size data structure that can answer any internal longest palindrome query in constant time. Also, given the input string T , our data structure can be constructed in O ( n ) time.
Making Your First Choice: To Address Cold Start Problem in Vision Active Learning

Active learning promises to improve annotation efficiency by iteratively selecting the most important data to be annotated first. However, we uncover a striking contradiction to this promise: active learning fails to select data as efficiently as random selection at the first few choices. We identify this as the cold start problem in vision active learning, caused by a biased and outlier initial query. This paper seeks to address the cold start problem by exploiting the three advantages of contrastive learning: (1) no annotation is required; (2) label diversity is ensured by pseudo-labels to mitigate bias; (3) typical data is determined by contrastive features to reduce outliers. Experiments are conducted on CIFAR-10-LT and three medical imaging datasets (i.e. Colon Pathology, Abdominal CT, and Blood Cell Microscope). Our initial query not only significantly outperforms existing active querying strategies but also surpasses random selection by a large margin. We foresee our solution to the cold start problem as a simple yet strong baseline to choose the initial query for vision active learning. Code is available: https://github.com/c-liangyu/CSVAL
On the Influence of Cognitive Styles on Users' Understanding of Explanations

Artificial intelligence (AI) is becoming increasingly complex, making it difficult for users to understand how the AI has derived its prediction. Using explainable AI (XAI)-methods, researchers aim to explain AI decisions to users. So far, XAI-based explanations pursue a technology-focused approach - neglecting the influence of users' cognitive abilities and differences in information processing on the understanding of explanations. Hence, this study takes a human-centered perspective and incorporates insights from cognitive psychology. In particular, we draw on the psychological construct of cognitive styles that describe humans' characteristic modes of processing information. Applying a between-subject experiment design, we investigate how users' rational and intuitive cognitive styles affect their objective and subjective understanding of different types of explanations provided by an AI. Initial results indicate substantial differences in users' understanding depending on their cognitive style. We expect to contribute to a more nuanced view of the interrelation of human factors and XAI design.
Strain engineering of two-dimensional piezo-photocatalytic materials for hydrogen production

Low-dimensional transition metal dichalcogenides (TMDC) exhibit great photocatalytic performance and tunability. In this work, using first-principles simulations based on density functional theory (DFT), we demonstrate that external electric bias can be employed to further improve the photocatalytic hydrogen production efficiency of the six AB 2 (A=Mo, W and B=S, Se, Te) TMDC monolayers by exploiting their piezoelectric response. In particular, when subjected to a proper amount of electrically induced tensile biaxial strain, most TMDC monolayers turn into potentially ideal photocatalyst towards the hydrogen evolution reaction (HER). The beneficial effects of introducing tensile biaxial strain on the TMDC monolayers are not limited to the reduction of the band gap and proper adjustment of the band edge positions, but also to the modification of the H adsorption free energy in such a way that the HER reaction is noticeably favored.
Coercive second-kind boundary integral equations for the Laplace Dirichlet problem on Lipschitz domains

We present new second-kind integral-equation formulations of the interior and exterior Dirichlet problems for Laplace's equation. The operators in these formulations are both continuous and coercive on general Lipschitz domains in $\mathbb{R}^d$, $d\geq 2$, in the space $L^2(\Gamma)$, where $\Gamma$ denotes the boundary of the domain. These properties of continuity and coercivity immediately imply that (i) the Galerkin method converges when applied to these formulations; and (ii) the Galerkin matrices are well-conditioned as the discretisation is refined, without the need for operator preconditioning (and we prove a corresponding result about the convergence of GMRES). The main significance of these results is that it was recently proved (see Chandler-Wilde and Spence, Numer. Math., 150(2):299-271, 2022) that there exist 2- and 3-d Lipschitz domains and 3-d starshaped Lipschitz polyhedra for which the operators in the standard second-kind integral-equation formulations for Laplace's equation (involving the double-layer potential and its adjoint) $\textit{cannot}$ be written as the sum of a coercive operator and a compact operator in the space $L^2(\Gamma)$. Therefore there exist 2- and 3-d Lipschitz domains and 3-d starshaped Lipschitz polyhedra for which Galerkin methods in $L^2(\Gamma)$ do $\textit{not}$ converge when applied to the standard second-kind formulations, but $\textit{do}$ converge for the new formulations.
Imagen Video: High Definition Video Generation with Diffusion Models

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos using a base video generation model and a sequence of interleaved spatial and temporal video super-resolution models. We describe how we scale up the system as a high definition text-to-video model including design decisions such as the choice of fully-convolutional temporal and spatial super-resolution models at certain resolutions, and the choice of the v-parameterization of diffusion models. In addition, we confirm and transfer findings from previous work on diffusion-based image generation to the video generation setting. Finally, we apply progressive distillation to our video models with classifier-free guidance for fast, high quality sampling. We find Imagen Video not only capable of generating videos of high fidelity, but also having a high degree of controllability and world knowledge, including the ability to generate diverse videos and text animations in various artistic styles and with 3D object understanding. See https://imagen.research. google/video/ for samples.
Control Synthesis for Stability and Safety by Differential Complementarity Problem

This letter develops a novel control synthesis method for safe stabilization of control-affine systems as a Differential Complementarity Problem (DCP). Our design uses a control Lyapunov function (CLF) and a control barrier function (CBF) to define complementarity constraints in the DCP formulation to certify stability and safety, respectively. The CLF-CBF-DCP controller imposes stability as a soft constraint, which is automatically relaxed when the safety constraint is active, without the need for parameter tuning or optimization. We study the closed-loop system behavior with the CLF-CBF-DCP controller and identify conditions on the existence of local equilibria. Although in certain cases the controller yields undesirable local equilibria, those can be confined to a small subset of the safe set boundary by proper choice of the control parameters. Then, our method can avoid undesirable equilibria that CLF-CBF quadratic programming techniques encounter.