Miracle-dz/UniFAR-FTUs huggingface dataset:
A Unified Model for Multiepoch Neutrino Events and Broadband Spectral Energy Distribution of TXS 0506+056

The blazar TXS 0506+056 has been proposed as a high-energy neutrino emitter. However, it has been shown that the standard one-zone model cannot produce sufficiently high neutrino flux due to constraints from the X-ray data, implying more complex properties of the radiation zones in the blazar than that described by the standard one-zone model. In this work, we investigate multiepoch high-energy muon-neutrino events associated with the blazar TXS 0506+056 that occurred in 2014–2015, 2017–2018, 2021–2022, and 2022–2023, respectively. We applied the so-called “stochastic dissipation model” to account for the neutrino-blazar associations detected in the four epochs simultaneously. This model describes a scenario in which the emission of the blazar arises from the superimposition of two components: a persistent component related to the quasi-stable state of the blazar and a transient component responsible for the sudden enhancement of the blazar’s flux, either in electromagnetic radiation or in neutrino emission. The latter component could form at a random distance along the jet by a strong energy dissipation event. Under such an assumption, the multiepoch broadband spectral energy distribution can be well explained, and the expected number of high-energy neutrino events is statistically realistic. The expected number of neutrino events in half year is around 8.2, 0.07, 0.73, and 0.41, corresponding to the epoch in 2014–2015, 2017–2018, 2021–2022, and 2022–2023, respectively. Hence, our model self-consistently explains the episodic neutrino emission from TXS 0506+056.
Towards better representation of Indian summer monsoon rainfall in CMIP6 models: Evaluation of MISO and MJO simulation

The seasonal prediction of the Indian summer monsoon (ISM) and Monsoon Intraseasonal Oscillations (MISO), as well as the Madden Julian Oscillations (MJO) that strongly modulate MISO, is important to the country for water and crop management. We have analyzed the precipitation, convection, and total cloud fraction (TCF) in the sixth Coupled Model Intercomparison Projects (CMIP6). This study highlights the significant differences in simulating MISO and MJO between the two groups of selected CMIP6 models and physical reasons behind them. The mean and intraseasonal features of MISO and MJO varied significantly in CMIP6 models, which are linked with a better depiction of convection and total cloud fraction. The probability distributions of rainfall and OLR in CMIP6 models indicate significant variations in simulating ISM precipitating clouds. TaiESM1 and IITM-ESM demonstrate improvements in capturing the MISO features. TaiESM1 depicts better eastward propagation of MJO during both summer and winter. The biases in OLR and TCF are also less in the IITM-ESM and TaiESM1 models than in CanESM5 and FGOALS-g3. The results demonstrate the importance of cloud and convection in CMIP6 models to depict realistic MISO and MJO and provide a road map for improving ISM climate prediction and projections. Keywords: ISM rainfall, CMIP6 models, MISO, MJO
A Hamilton-Jacobi-Bellman Approach to Ellipsoidal Approximations of Reachable Sets for Linear Time-Varying Systems

Reachable sets for a dynamical system describe collections of system states that can be reached in finite time, subject to system dynamics. They can be used to guarantee goal satisfaction in controller design or to verify that unsafe regions will be avoided. However, general-purpose methods for computing these sets suffer from the curse of dimensionality, which typically prohibits their use for systems with more than a small number of states, even if they are linear. In this paper, we demonstrate that viscosity supersolutions and subsolutions of a Hamilton-Jacobi-Bellman equation can be used to generate, respectively, under-approximating and over-approximating reachable sets for time-varying nonlinear systems. Based on this observation, we derive dynamics for a union and intersection of ellipsoidal sets that, respectively, under-approximate and over-approximate the reachable set for linear time-varying systems subject to an ellipsoidal input constraint and an ellipsoidal terminal (or initial) set. We demonstrate that the dynamics for these ellipsoids can be selected to ensure that their boundaries coincide with the boundary of the exact reachable set along a solution of the system. The ellipsoidal sets can be generated with polynomial computational complexity in the number of states, making our approximation scheme computationally tractable for continuous-time linear time-varying systems of relatively high dimension.
The Role of Identification in Data-driven Policy Iteration: A System Theoretic Study

The goal of this article is to study fundamental mechanisms behind so-called indirect and direct data-driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of the desired optimal controller, are considered. In indirect policy iteration, data are used to obtain an updated model estimate through a recursive identification scheme, which is used in a certainty-equivalent fashion to perform the classic policy iteration update. By casting the concurrent model identification and control design as a feedback interconnection between two algorithmic systems, we provide a closed-loop analysis that shows convergence and robustness properties for arbitrary levels of excitation in the data. In direct policy iteration, data are used to approximate the value function and design the associated controller without requiring the intermediate identification step. After proposing an extension to a recently proposed scheme that overcomes potential identifiability issues, we establish under which conditions this procedure is guaranteed to deliver the optimal controller. Based on these analyses we are able to compare the strengths and limitations of the two approaches, highlighting aspects such as the required samples, convergence properties, and excitation requirement. Simulations are also provided to illustrate the results.
Point-hyperplane incidences via extremal graph theory

The study of counting point-hyperplane incidences in the $d$-dimensional space was initiated in the 1990's by Chazelle and became one of the central problems in discrete geometry. It has interesting connections to many other topics, such as additive combinatorics and theoretical computer science. Assuming a standard nondegeneracy condition, i.e., that no $s$ points are contained in the intersection of $s$ hyperplanes, the currently best known upper bound on the number of incidences of $n$ points and $m$ hyperplanes in $\mathbb{R}^d$ is $O_{d, s}((mn)^{1-1/(d+1)}+m+n). $ This bound by Apfelbaum and Sharir is based on geometrical space partitioning techniques. In this paper, we propose a novel combinatorial approach to estimate the number of point-hyperplane incidences over arbitrary fields using forbidden induced patterns in incidence graphs. Perhaps surprisingly, this approach matches the best known bounds in $\mathbb{R}^d$ for many interesting values of $m, n, d$, e.g. when $m=n$ and $d$ is odd. Moreover, in finite fields our bounds are sharp as a function of $m$ and $n$ in every dimension. We also study the size of the largest complete bipartite graph in point-hyperplane incidence graphs with a given number of edges and obtain optimal bounds as well.
Phenomenology of particle creation in Weyl geometry

Short review of the Weyl geometry is given. To describe the phenomenological particle creation we suggest the modified perfect fluid model taking into account the back reaction on the geometry of both the already created particles and the very process of their creation. It is found that the relation for particle creation is conformal invariant. This requires the creation law consisting of the source terms as the Weyl Lagrangian plus two quite new terms depending of the particle number density.
All invariant contact metric structures on tangent sphere bundles of compact rank-one symmetric spaces

All invariant contact metric structures on tangent sphere bundles of each compact rank-one symmetric space are obtained explicitly, distinguishing for the orthogonal case those that are K-contact, Sasakian or 3-Sasakian. Only the tangent sphere bundle of complex projective spaces admits 3-Sasakian metrics and there exists a unique orthogonal Sasakian-Einstein metric. Furthermore, there is a unique invariant contact metric that is Einstein, in fact Sasakian-Einstein, on tangent sphere bundles of spheres and real projective spaces. Each invariant contact metric, Sasakian, Sasakian-Einstein or 3-Sasakian structure on the unit tangent sphere of any compact rank-one symmetric space is extended, respectively, to an invariant almost Kahler, Kahler, Kahler Ricci-flat or hyperKahler structure on the punctured tangent bundle.
Braid group actions, Baxter polynomials, and affine quantum groups

It is a classical result in representation theory that the braid group $\mathscr{B}_\mathfrak{g}$ of a simple Lie algebra $\mathfrak{g}$ acts on any integrable representation of $\mathfrak{g}$ via triple products of exponentials in its Chevalley generators. In this article, we show that a modification of this construction induces an action of $\mathscr{B}_\mathfrak{g}$ on the commutative subalgebra $Y_\hbar^0(\mathfrak{g})\subset Y_\hbar(\mathfrak{g})$ of the Yangian by Hopf algebra automorphisms, which gives rise to a representation of the Hecke algebra of type $\mathfrak{g}$ on a flat deformation of the Cartan subalgebra $\mathfrak{h}[t]\subset \mathfrak{g}[t]$. By dualizing, we recover a representation of $\mathscr{B}_\mathfrak{g}$ constructed in the works of Y. Tan and V. Chari, which was used to obtain sufficient conditions for the cyclicity of any tensor product of irreducible representations of $Y_\hbar(\mathfrak{g})$ and the quantum loop algebra $U_q(L\mathfrak{g})$. We apply this dual action to prove that the cyclicity conditions from the work of Tan are identical to those obtained in the recent work of the third author and S. Gautam. Finally, we study the $U_q(L\mathfrak{g})$-counterpart of the braid group action on $Y_\hbar^0(\mathfrak{g})$, which arises from Lusztig's braid group operators and recovers the aforementioned $\mathscr{B}_\mathfrak{g}$-action defined by Chari.
Generalized exponential pullback attractor for a nonautonomous wave equation

In this work we introduce the concept of generalized exponential $\mathfrak{D}$-pullback attractor for evolution processes, where $\mathfrak{D}$ is a universe of families in $X$, which is a compact and positively invariant family that pullback attracts all elements of $\mathfrak{D}$ with an exponential rate. Such concept was introduced in arXiv:2311.15630 for the general case of decaying functions (which include the exponential decay), but for fixed bounded sets rather than to universe of families. We prove a result that ensures the existence of a generalized exponential $\mathfrak{D}_{\mathcal{C}^\ast}$-pullback attractor for an evolution process, where $\mathfrak{D}_{\mathcal{C}^\ast}$ is a specific universe. This required an adaptation of the results of arXiv:2311.15630, which only covered the case of a polynomial rate of attraction, for fixed bounded sets. Later, we prove that a nonautonomous wave equation has a generalized exponential $\mathfrak{D}_{\mathcal{C}^\ast}$-pullback attractor. This, in turn, also implies the existence of the $\mathfrak{D}_{\mathcal{C}^\ast}$-pullback attractor for such problem.
Mission: Impossible Language Models

Chomsky and others have very directly claimed that large language models (LLMs) are equally capable of learning languages that are possible and impossible for humans to learn. However, there is very little published experimental evidence to support such a claim. Here, we develop a set of synthetic impossible languages of differing complexity, each designed by systematically altering English data with unnatural word orders and grammar rules. These languages lie on an impossibility continuum: at one end are languages that are inherently impossible, such as random and irreversible shuffles of English words, and on the other, languages that may not be intuitively impossible but are often considered so in linguistics, particularly those with rules based on counting word positions. We report on a wide range of evaluations to assess the capacity of GPT-2 small models to learn these uncontroversially impossible languages, and crucially, we perform these assessments at various stages throughout training to compare the learning process for each language. Our core finding is that GPT-2 struggles to learn impossible languages when compared to English as a control, challenging the core claim. More importantly, we hope our approach opens up a productive line of inquiry in which different LLM architectures are tested on a variety of impossible languages in an effort to learn more about how LLMs can be used as tools for these cognitive and typological investigations.
CTMCs with Imprecisely Timed Observations

Labeled continuous-time Markov chains (CTMCs) describe processes subject to random timing and partial observability. In applications such as runtime monitoring, we must incorporate past observations. The timing of these observations matters but may be uncertain. Thus, we consider a setting in which we are given a sequence of imprecisely timed labels called the evidence. The problem is to compute reachability probabilities, which we condition on this evidence. Our key contribution is a method that solves this problem by unfolding the CTMC states over all possible timings for the evidence. We formalize this unfolding as a Markov decision process (MDP) in which each timing for the evidence is reflected by a scheduler. This MDP has infinitely many states and actions in general, making a direct analysis infeasible. Thus, we abstract the continuous MDP into a finite interval MDP (iMDP) and develop an iterative refinement scheme to upper-bound conditional probabilities in the CTMC. We show the feasibility of our method on several numerical benchmarks and discuss key challenges to further enhance the performance.
Localized Gradual Photomediated Brightness and Lifetime Increase of Superacid Treated Monolayer MoS$_2$

Monolayer semiconducting transition metal dichalcogenides (S-TMDs) have been extensively studied as materials for next-generation optoelectronic devices due to their direct band gap and high exciton binding energy at room temperature. Under a superacid treatment of bis(trifluoromethane)sulfonimide (TFSI), sulfur-based TMDs such as MoS$_2$ can emit strong photoluminescence (PL) with photoluminescence quantum yield (PLQY) approaching unity. However, the magnitude of PL enhancement varies by more than two orders of magnitude in published reports. A major culprit behind the discrepancy is sulfur-based TMD's sensitivity to above band-gap photostimulation. Here, we present a detailed study of how TFSI-treated MoS$_2$ reacts to photostimulation with increasing PL occurring hours after constant or pulsed laser exposure. The PL of TFSI-treated MoS$_2$ is enhanced up to 74 times its initial intensity after 5 hours of continuous exposure to 532nm laser light. Photostimulation also enhances the PL of untreated MoS$_2$ but with a much smaller enhancement. Caution should be taken when probing MoS$_2$ PL spectra as above-bandgap light can alter the resulting intensity and peak wavelength of the emission over time. The presence of air is verified to play a key role in the photostimulated enhancement effect. Additionally, the rise of PL intensity is mirrored by an increase in measured carrier lifetime of up to ~400ps consistent with the suppression of non-radiative pathways. This work demonstrates why variations in PL intensity are observed across samples and provides an understanding of the changes in carrier lifetimes to better engineer next-generation optoelectronic devices.
WISE: full-Waveform variational Inference via Subsurface Extensions

We introduce a probabilistic technique for full-waveform inversion, employing variational inference and conditional normalizing flows to quantify uncertainty in migration-velocity models and its impact on imaging. Our approach integrates generative artificial intelligence with physics-informed common-image gathers, reducing reliance on accurate initial velocity models. Considered case studies demonstrate its efficacy producing realizations of migration-velocity models conditioned by the data. These models are used to quantify amplitude and positioning effects during subsequent imaging.
Distributed Optimal Output Consensus Control of Heterogeneous Multi-Agent Systems with Safety Constraints

In this paper, we develop a novel dynamic distributed optimal safe consensus protocol to simultaneously achieve safety requirements and output optimal consensus. Specifically, we construct a distributed projection optimization algorithm with an expanding constraint set in the decision-making layer, while we propose a reference tracking safety controller to ensure that each agent's output remains within a shrinking safety set in the control layer.We also establish the convergence and safety analysis of the closed-loop system using the small-gain theorem and time-varying control barrier function (CBF) theory, respectively. Besides, unlike previous works on distributed optimal consensus, our approach does not require prior knowledge of the local objective or gradient function and adopts a mild assumption on the dynamics of multiagent systems (MASs) by using the transmission zeros condition.
YOLO-Former: YOLO Shakes Hand With ViT

The proposed YOLO-Former method seamlessly integrates the ideas of transformer and YOLOv4 to create a highly accurate and efficient object detection system. The method leverages the fast inference speed of YOLOv4 and incorporates the advantages of the transformer architecture through the integration of convolutional attention and transformer modules. The results demonstrate the effectiveness of the proposed approach, with a mean average precision (mAP) of 85.76\% on the Pascal VOC dataset, while maintaining high prediction speed with a frame rate of 10.85 frames per second. The contribution of this work lies in the demonstration of how the innovative combination of these two state-of-the-art techniques can lead to further improvements in the field of object detection.
Convective stability in scalar balance laws

We fill the two main remaining gaps in the full classification of non-degenerate planar traveling waves of scalar balance laws from the point of view of spectral and nonlinear stability/instability under smooth perturbations. On one hand we investigate the impact on the classification of allowing to restrict perturbations by further localization constraints, the so-called convective stability analysis. On the other hand, in the multidimensional case we extend the existing analysis to general perturbations, relaxing the artificial restriction, assumed so far, that initial perturbations are supported away from characteristic points. A striking feature of the latter analysis is that it involves infinite-dimensional families of genuinely multidimensional traveling waves that live near the perturbed planar traveling wave.
The exact Maxwell evolution equation of resonators dynamics: the temporal coupled-mode theory revisited

Despite its widespread significance, the temporal coupled-mode theory (CMT) lacks a foundational validation based on electromagnetic principles and stands as a phenomenological theory relying on fitted coupling coefficients. We employ an ab initio Maxwellian approach using quasinormal-mode theory to derive an"exact"Maxwell evolution (EME) equation for resonator dynamics. While the resulting differential equation bears resemblance to the classical one, it introduces novel terms embodying distinct physics, suggesting that the CMT predictions could be faulted by dedicated experiments, for instance carried out with short pulses or resonators of sizes comparable to or greater than the wavelength. Nonetheless, our examination indicates that, despite its inherent lack of strictness, the CMT enables precise predictions for numerous nanophotonics-related experiments due to the flexibility provided by the fitted coupling coefficients. The new EME equation is anticipated to be applicable to all electromagnetic resonator geometries, and the theoretical approach we have taken can be extended to other wave physics.
Towards High-Quality and Efficient Speech Bandwidth Extension with Parallel Amplitude and Phase Prediction

Speech bandwidth extension (BWE) refers to widening the frequency bandwidth range of speech signals, enhancing the speech quality towards brighter and fuller. This paper proposes a generative adversarial network (GAN) based BWE model with parallel prediction of Amplitude and Phase spectra, named AP-BWE, which achieves both high-quality and efficient wideband speech waveform generation. The proposed AP-BWE generator is entirely based on convolutional neural networks (CNNs). It features a dual-stream architecture with mutual interaction, where the amplitude stream and the phase stream communicate with each other and respectively extend the high-frequency components from the input narrowband amplitude and phase spectra. To improve the naturalness of the extended speech signals, we employ a multi-period discriminator at the waveform level and design a pair of multi-resolution amplitude and phase discriminators at the spectral level, respectively. Experimental results demonstrate that our proposed AP-BWE achieves state-of-the-art performance in terms of speech quality for BWE tasks targeting sampling rates of both 16 kHz and 48 kHz. In terms of generation efficiency, due to the all-convolutional architecture and all-frame-level operations, the proposed AP-BWE can generate 48 kHz waveform samples 292.3 times faster than real-time on a single RTX 4090 GPU and 18.1 times faster than real-time on a single CPU. Notably, to our knowledge, AP-BWE is the first to achieve the direct extension of the high-frequency phase spectrum, which is beneficial for improving the effectiveness of existing BWE methods.
Beyond Diagonal RIS for Multi-Band Multi-Cell MIMO Networks: A Practical Frequency-Dependent Model and Performance Analysis

This paper delves into the unexplored frequency-dependent characteristics of beyond diagonal reconfigurable intelligent surfaces (BD-RISs). A generalized practical frequency-dependent reflection model is proposed as a fundamental framework for configuring fully-connected and group-connected RISs in a multi-band multi-base station (BS) multiple-input multiple-output (MIMO) network. Leveraging this practical model, multi-objective optimization strategies are formulated to maximize the received power at multiple users connected to different BSs, each operating under a distinct carrier frequency. By relying on matrix theory and exploiting the symmetric structure of the reflection matrices inherent to BD-RISs, closed-form relaxed solutions for the challenging optimization problems are derived. The ideal solutions are then combined with codebook-based approaches to configure the practical capacitance values for the BD-RISs. Simulation results reveal the frequency-dependent behaviors of different RIS architectures and demonstrate the effectiveness of the proposed schemes. Notably, BD-RISs exhibit superior resilience to frequency deviations compared to conventional single-connected RISs. Moreover, the proposed optimization approaches prove effective in enabling the targeted operation of BD-RISs across one or more carrier frequencies. The results also shed light on the potential for harmful interference in the absence of proper synchronization between RISs and adjacent BSs.