Miracle-dz/UniFAR-FTUs huggingface dataset:
Heralded Magnetism in Non-Hermitian Atomic Systems

Quantum phase transitions are usually studied in terms of Hermitian Hamiltonians. However, cold-atom experiments are intrinsically non-Hermitian due to spontaneous decay. Here, we show that non-Hermitian systems exhibit quantum phase transitions that are beyond the paradigm of Hermitian physics. We consider the non-Hermitian XY model, which can be implemented using three-level atoms with spontaneous decay. We exactly solve the model in one dimension and show that there is a quantum phase transition from short-range order to quasi-long-range order despite the absence of a continuous symmetry in the Hamiltonian. The ordered phase has a frustrated spin pattern. The critical exponent $\nu$ can be 1 or 1/2. Our results can be seen experimentally with trapped ions, cavity QED, and atoms in optical lattices.
Rejecting noise in Baikal-GVD data with neural networks

Baikal-GVD is a large (∼ 1 km3) underwater neutrino telescope installed in the fresh waters of Lake Baikal. The deep lake water environment is pervaded by background light, which is detectable by Baikal-GVD's photosensors. We introduce a neural network for an efficient separation of these noise hits from the signal ones, stemmng from the propagation of relativistic particles through the detector. The model has a U-Net-like architecture and employs temporal (causal) structure of events. The neural network's metrics reach up to 99% signal purity (precision) and 96% survival efficiency (recall) on Monte-Carlo simulated dataset. We compare the developed method with the algorithmic approach to rejecting the noise and discuss other possible architectures of neural networks, including graph-based ones.
Trace ideal and annihilator of Ext and Tor of regular fractional ideals, and some applications

Given a commutative Noetherian ring R with total ring of fractions Q ( R ), and a ﬁnitely generated R -submodule M of Q ( R ), we prove an equality between trace ideal, and certain annihilator of Ext and Tor of M . As a consequence, we answer in one-dimensional local analytically unramiﬁed case, a question raised by the present author and R. Takahashi. As another application, we give an alternative proof of a recent result of ¨O. Esentepe that for one-dimensional analytically unramiﬁed Gorenstein local rings, the cohomology annihilator of Iyengar and Takahashi coincides with the conductor ideal.
Radio Galaxies and Quasars in Clusters of Galaxies

The study of radio galaxies situated within clusters of galaxies has become a broad field, with hundreds of papers published in the last few years. This review will therefore be restricted mainly to consideration of the interactions between the extended components of radio sources in clusters and the diffuse gas (intracluster medium, ICM) which occurs in clusters. In particular, attention will be focused on what we can learn about the ICM from this interaction, in conjunction with other data such as X-ray observations. In the case of quasars in clusters of galaxies the emphasis is rather different, so discussion of this topic is deferred to section 6.
A semi‐smooth Newton method for an inverse problem in option pricing

We present an optimal control approach using a Lagrangian framework to identify local volatility functions from given option prices. We employ a globalized sequential quadratic programming (SQP) algorithm and implement a line search strategy. The linear‐quadratic optimal control problems in each iteration are solved by a primal‐dual active set strategy which leads to a semi‐smooth Newton method. We present first‐ and second‐order analysis as well as numerical results. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Effect of Earth-Moon’s gravity on TianQin’s range acceleration noise. II. Impact of orbit selection

The paper is a sequel to our previous work (Zhang et al. Phys. Rev. D 103, 062001 (2021)). For proposed geocentric space-based gravitational wave detectors such as TianQin, gLISA, and GADFLI, the gravity-field disturbances, i.e., the so called ``orbital noise'', from the Earth-Moon system on the sensitive intersatellite laser interferometric measurements should be carefully evaluated and taken into account in the concept studies. Based on TianQin, we investigate how the effect, in terms of frequency spectra, varies with different choices of orbital orientations and radii through single-variable studies, and present the corresponding roll-off frequencies that may set the lower bounds of the targeted detection bands. The results, including the special cases of geostationary orbits (gLISA/GADFLI) and repeat orbits, can provide a useful input to orbit and constellation design for future geocentric missions.
Quantum Mechanics: An Experimentalist's Approach

Preface 1. Introduction 2. Mathematical preliminaries 3. The rules of quantum mechanics 4. The connection between the fundamental rules and wave mechanics 5. Further illustrations of the rules of quantum mechanics 6. Further developments in one-dimensional wave mechanics 7. The theory of angular momentum 8. Wave mechanics in three dimensions: hydrogenic atoms 9. Time-independent approximations for bound state problems 10. Applications of static perturbation theory 11. Identical particles 12. Atomic structure 13. Molecules 14. The stability of matter 15. Photons 16. Interaction of non-relativistic charged particles and radiation 17. Further topics in perturbation theory 18. Scattering 19. Special relativity and quantum mechanics: the Klein-Gordon equation 20. The Dirac equation 21. Interaction of a relativistic spin 1/2 particle with an external electromagnetic field 22. The Dirac field 23. Interaction between relativistic electrons, positrons, and photons 24. The quantum mechanics of weak interactions 25. The quantum measurement problem Appendix A: useful inequalities for quantum mechanics Appendix B: Bell's inequality Appendix C: spin of the photon: vector spherical waves Works cited Bibliography Index.
The Dyson equation for $2$-positive maps and H\"older bounds for the L\'evy distance of densities of states

The so-called density of states is a Borel probability measure on the real line associated with the solution of the Dyson equation which we set up, on any fixed $C^\ast$-probability space, for a selfadjoint offset and a $2$-positive linear map. Using techniques from free noncommutative function theory, we prove explicit H\"older bounds for the L\'evy distance of two such measures when any of the two parameters varies. As the main tools for the proof, which are also of independent interest, we show that solutions of the Dyson equation have strong analytic properties and evolve along any $C^1$-path of $2$-positive linear maps according to an operator-valued version of the inviscid Burgers equation.
How “free” are free neutrons in neutron-star crusts and what does it imply for pulsar glitches?

Abstract The neutron superfluid permeating the inner crust of mature neutron stars is expected to play a key role in various astrophysical phenomena like pulsar glitches. Despite the absence of viscous drag, the neutron superfluid can still be coupled to the solid crust due to non-dissipative entrainment effects. Entrainment challenges the interpretation of pulsar glitches and suggests that a revision of the interpretation of other observed neutron-star phenomena might be necessary.
An extensive spectroscopic time-series of three Wolf-Rayet stars. I. The lifetime of large-scale structures in the wind of WR 134

During the summer of 2013, a 4-month spectroscopic campaign took place to observe the variabilities in three Wolf-Rayet stars. The spectroscopic data have been analyzed for WR 134 (WN6b), to better understand its behaviour and long-term periodicity, which we interpret as arising from corotating interaction regions (CIRs) in the wind. By analyzing the variability of the He II $\lambda$5411 emission line, the previously identified period was refined to P = 2.255 $\pm$ 0.008 (s.d.) days. The coherency time of the variability, which we associate with the lifetime of the CIRs in the wind, was deduced to be 40 $\pm$ 6 days, or $\sim$ 18 cycles, by cross-correlating the variability patterns as a function of time. When comparing the phased observational grayscale difference images with theoretical grayscales previously calculated from models including CIRs in an optically thin stellar wind, we find that two CIRs were likely present. A separation in longitude of $\Delta \phi \simeq$ 90$^{\circ}$ was determined between the two CIRs and we suggest that the different maximum velocities that they reach indicate that they emerge from different latitudes. We have also been able to detect observational signatures of the CIRs in other spectral lines (C IV $\lambda\lambda$5802,5812 and He I $\lambda$5876). Furthermore, a DAC was found to be present simultaneously with the CIR signatures detected in the He I $\lambda$5876 emission line which is consistent with the proposed geometry of the large-scale structures in the wind. Small-scale structures also show a presence in the wind, simultaneously with the larger scale structures, showing that they do in fact co-exist.
Evaluation of the electrical contact area in contact-mode scanning probe microscopy

The tunneling current through an atomic force microscopy (AFM) tip is used to evaluate the effective electrical contact area, which exists between tip and sample in contact-AFM electrical measurements. A simple procedure for the evaluation of the effective electrical contact area is described using conductive atomic force microscopy (C-AFM) in combination with a thin dielectric. We characterize the electrical contact area for coated metal and doped-diamond tips operated at low force (<200 nN) in contact mode. In both cases, we observe that only a small fraction (<10 nm2) of the physical contact (∼100 nm2) is effectively contributing to the transport phenomena. Assuming this reduced area is confined to the central area of the physical contact, these results explain the sub-10 nm electrical resolution observed in C-AFM measurements.
Mutual information based objective model for assessment of visual quality

Abstract The humans are the ultimate assessor of image or video quality. Thus, evaluating the quality using human perception is a very crucial and interesting topic in the quality assessment research domain. Even though the subjective assessment is the most reliable one, it is time consuming and costly. On the other hand, the objective model provides the assessment result with much less time and labour, albeit with certain degree of tolerable error. In this piece of work, a new objective model, namely visual attentive information fidelity (VAIF) has been proposed in the spatial domain, instead of transformed domain, for assessment of visual quality in a scene or in a patch of the scene. VAIF relates mutual information (MI) and image fidelity using source and destination model. The proposed objective model metrics has been correlated with subjective measurement metrics like MOS, NAS.
Categorification of the polynomial ring

We develop a diagrammatic categorification of the polynomial ring $Z[x]$. Our categorification satisfies a version of Bernstein-Gelfand-Gelfand reciprocity property with the indecomposable projective modules corresponding to $x^n$ and standard modules to $(x-1)^n$ in the Grothendieck ring.
Enabling students critical thinking dispositions in hospitality financial management

ABSTRACT Several studies suggest that graduates lack the critical thinking skills required for problem-solving and effective financial decision-making in the hospitality industry. Since higher education may not be able to meet all the demands and needs of the hospitality industry; such institutions struggle to provide students with the necessary critical thinking skills. Authentic assessment is one possible strategy, which is recognized, to develop critical thinking skills amongst hospitality graduates. Hence, the purpose of this research is to explore to what extent authentic assessment enables critical thinking skills amongst first-year students in hospitality financial management. This article employed a qualitative case study research design within an interpretative lens. Twenty-four, first-year, hospitality financial management students, were purposively engaged in online reflections and semi-structured interviews. The findings of the study presented three themes that resonate with the critical thinking frameworks.
From User Control and Explainability in Recommendation Interfaces to Visual XAI

Transparency and explainability are topics studied for more than two decades in the area of recommender systems, due to its impact on the user experience of personalized systems. Interestingly, only in recent years these topics have reached importance within Artificial Intelligence (AI) as a whole, under the umbrella of the term XAI (eXplainable AI). Some authors have shown that advances in XAI from different fields (computer science, design, HCI, IR, AI, etc.) have not been properly integrated into a common body of knowledge due to lack of connection among these communities. This talk gives one small step to bridge this gap, by showing how works on explainability, transparency, visualization, user interfaces and user control in recommender systems are significantly related to XAI and can inspire new ideas of research on visual XAI.
BRIGHT SUPERNOVAE FROM MAGNETAR BIRTH

Following an initial explosion that might be launched either by magnetic interactions or neutrinos, a rotating magnetar radiating according to the classic dipole formula could power a very luminous supernova. While some 56Ni might be produced in the initial explosion, the peak of the light curve in a Type I supernova would not be directly related to its mass. In fact, the peak luminosity would be most sensitive to the dipole field strength of the magnetar. The tail of the light curve could resemble radioactive decay for some time but, assuming complete trapping of the pulsar emission, would eventually be brighter. Depending on the initial explosion energy, both high and moderate velocities could accompany a very luminous light curve.
Legal Element-oriented Modeling with Multi-view Contrastive Learning for Legal Case Retrieval

Legal case retrieval, which aims to retrieve relevant cases given a query case, plays an essential role in the legal system. While recent research efforts improve the performance of traditional ad-hoc retrieval models, legal case retrieval is still challenging since queries are legal cases, which contain hundreds of tokens. Legal cases are much longer and more complicated than keywords queries. Apart from that, the definition of legal relevance is beyond the general definition. In addition to general topical relevance, the relevant cases also involve similar situations and legal elements, which can support the judgment of the current case. In this paper, we propose an interaction-focused network for legal case retrieval with a multi-view contrastive learning objective. The contrastive learning views, including case-view and element-view, aim to overcome the above challenges. The case-view contrastive learning minimizes the hidden space distance between relevant legal case representations produced by a pre-trained language model (PLM) encoder. The element-view builds positive and negative instances by changing legal elements of cases to help the network better compute legal relevance. To achieve this, we employ a legal element knowledge-aware indicator to detect legal elements of cases. We conduct extensive experiments on the benchmark of relevant case retrieval. Evaluation results indicate our proposed method obtains significant improvement over the existing methods.
Flow–structure interaction of a starting jet through a flexible circular nozzle

Abstract In the present study, the flow–structure interaction of a starting jet through a flexible nozzle is experimentally investigated, with a focus on the optimal flexibility for thrust generation. Water slug is impulsively accelerated through a cylindrical nozzle, fabricated with silicone rubber of varying flexibility. In general, the flexible nozzle modifies the vortical structure of the jet and augments the thrust of the starting jet. The measurement of nozzle surface deformation revealed that a back-and-forth wave propagation on the nozzle surface is responsible for the jet-vortex evolution augmenting the thrust generation. Combining the hydrodynamic conservation equations and the linearized shell theory, we also formulated the governing equations, dominated by two relevant dimensionless parameters: the effective acceleration time of the jet ($\varPi _0$) and the effective nozzle stiffness ($\varPi _1$). Asymptotic analysis of the equation showed that the dimensionless wave speed ($\hat {c}$) is expressed as $\hat {c}=(\varPi _{0}^{2}\varPi _{1}/2)^{0.5}$, and the jet momentum is maximized at $\hat {c}=\hat {c}_{crit}$ ($\simeq 3.0$), the condition at which the release of elastic energy stored during nozzle contraction to the jet is synchronized with the instant of termination of jet acceleration. While $\hat {c}=\hat {c}_{crit}$, the achievable maximum jet velocity decreases with the effective acceleration time of the jet ($\varPi _0$), which is attributed to the reduced speed of the surface wave by the flow inside the nozzle.
Enhancing Collaborative Rationality between Humans and Machines through Data-Driven Decision Evaluation

Organizational decisions have become more data-driven and collaborative, with the increasing utilization of artificial intelligence, machine learning, and analytics to support decision making. While humans and machines are each bounded in their own rationalities, their collaboration has enabled a new, collaborative rationality by augmenting the intelligence and capabilities of each. New research is required to explore the degree and mode of human-machine collaboration, with the aim of enhancing collaborative rationality, and its effect on decision making. Furthermore, the resulting decisions must be evaluated to enable learning, rationalization, and sensemaking from the decision outcomes. However, data-driven decisions are complex in nature, and current theoretical developments fall short in accommodating for their multi-faceted nature and changing context, and there is lack of theoretical support on how, when, and why to evaluate such decisions. Accordingly, we follow a design science research methodology to develop and evaluate a model for data-driven decision evaluation. This model depicts the relationship and role of the multiple elements involved in data-driven decision making, and provides a feedback loop which inputs the results of evaluating decision outcomes back into the process/system, thus enabling learning from the past through experience, and ultimately enhancing collaborative rationality and decision making.
Three-dimensional rotating Couette flow via the generalised quasilinear approximation

We examine the effectiveness of the generalised quasilinear (GQL) approximation introduced by Marston et al. (Phys. Rev. Lett., vol. 116 (21), 2016, 214501). This approximation splits the variables into large and small scales in directions where there is a translational symmetry and removes nonlinear interactions involving only small scales. We utilise as a paradigm problem three-dimensional, turbulent, rotating Couette flow. We compare the results obtained from direct numerical solution of the equations with those from quasilinear (QL) and GQL calculations. In this three-dimensional setting, there is a choice of cutoff wavenumber for the GQL approximation both in the streamwise and in the spanwise directions. We demonstrate that the GQL approximation significantly improves the accuracy of mean flows, spectra and two-point correlation functions over models that are quasilinear in any of the translationally invariant directions, even if only a few streamwise and spanwise modes are included. We argue that this provides significant support for a programme of direct statistical simulation utilising the GQL approximation.
Atrial thrombosis: Not only left, think also about right!

Atrial fibrillation (AF) is the most common arrhythmia in the general population. Systemic thromboembolism from left atrial appendage (LAA) thrombosis is a well‐known complication of AF, whereas thromboembolic complications from a right atrial (RA) thrombus are infrequent. Nevertheless, the prevalence of RA thrombosis is debated; despite having a low prevalence in echocardiographic studies, the higher prevalence found in autoptic studies rises the hypothesis of an under detection of RA clots, possibly related to the limited evaluation of right atrial appendage (RAA) with non‐invasive imaging. Here we present a review of the current literature about RA thrombosis, regarding its diagnosis, differentials, and best treatment options.
Query Prior Matters: A MRC Framework for Multimodal Named Entity Recognition

Multimodal named entity recognition (MNER) is a vision-language task where the system is required to detect entity spans and corresponding entity types given a sentence-image pair. Existing methods capture text-image relations with various attention mechanisms that only obtain implicit alignments between entity types and image regions. To locate regions more accurately and better model cross-/within-modal relations, we propose a machine reading comprehension based framework for MNER, namely MRC-MNER. By utilizing queries in MRC, our framework can provide prior information about entity types and image regions. Specifically, we design two stages, Query-Guided Visual Grounding and Multi-Level Modal Interaction, to align fine-grained type-region information and simulate text-image/inner-text interactions respectively. For the former, we train a visual grounding model via transfer learning to extract region candidates that can be further integrated into the second stage to enhance token representations. For the latter, we design text-image and inner-text interaction modules along with three sub-tasks for MRC-MNER. To verify the effectiveness of our model, we conduct extensive experiments on two public MNER datasets, Twitter2015 and Twitter2017. Experimental results show that MRC-MNER outperforms the current state-of-the-art models on Twitter2017, and yields competitive results on Twitter2015.