Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Feedback Particle Filter and related Controlled Interacting Particle Systems (CIPS)

In this survey, we describe controlled interacting particle systems (CIPS) to approximate the solution of the optimal filtering and the optimal control problems. Part I of the survey is focussed on the feedback particle filter (FPF) algorithm, its derivation based on optimal transportation theory, and its relationship to the ensemble Kalman filter (EnKF) and the conventional sequential importance sampling-resampling (SIR) particle filters. The central numerical problem of FPF -- to approximate the solution of the Poisson equation -- is described together with the main solution approaches. An analytical and numerical comparison with the SIR particle filter is given to illustrate the advantages of the CIPS approach. Part II of the survey is focussed on adapting these algorithms for the problem of reinforcement learning. The survey includes several remarks that describe extensions as well as open problems in this subject.
Deep Learning for Bias‐Correcting CMIP6‐Class Earth System Models

The accurate representation of precipitation in Earth system models (ESMs) is crucial for reliable projections of the ecological and socioeconomic impacts in response to anthropogenic global warming. The complex cross‐scale interactions of processes that produce precipitation are challenging to model, however, inducing potentially strong biases in ESM fields, especially regarding extremes. State‐of‐the‐art bias correction methods only address errors in the simulated frequency distributions locally at every individual grid cell. Improving unrealistic spatial patterns of the ESM output, which would require spatial context, has not been possible so far. Here, we show that a postprocessing method based on physically constrained generative adversarial networks (cGANs) can correct biases of a state‐of‐the‐art, CMIP6‐class ESM both in local frequency distributions and in the spatial patterns at once. While our method improves local frequency distributions equally well as gold‐standard bias‐adjustment frameworks, it strongly outperforms any existing methods in the correction of spatial patterns, especially in terms of the characteristic spatial intermittency of precipitation extremes.
Fermi-Dirac staircase occupation of Floquet bands and current rectification inside the optical gap of metals: An exact approach

We consider a model of a Bloch band subjected to an oscillating electric field and coupled to a featureless fermionic heat bath, which can be solved exactly. We demonstrate rigorously that in the limit of vanishing coupling to this bath (so that it acts as an ideal thermodynamic bath) the occupation of the Floquet band is not a simple Fermi-Dirac distribution function of the Floquet energy, but instead it becomes a ``staircase'' version of this distribution. We show that this distribution generically leads to a finite rectified electric current within the optical gap of a metal even in the limit of vanishing carrier relaxation rates, providing a rigorous demonstration that such rectification is generically possible and clarifying previous statements in the optoelectronics literature. We show that this current remains non-zero even up to the leading perturbative second order in the amplitude of electric fields, and that it approaches the standard perturbative expression of the Jerk current obtained from a simpler Boltzmann description within a relaxation time approximation when the frequencies are small compared to the bandwidth.
Axisymmetric bubble collapse in a quiescent liquid pool. II. Experimental study

We present an experimental study of the detachment of a gas bubble growing quasistatically at constant flow rate conditions from a vertical nozzle placed at the bottom of a quiescent pool of water. In particular, we focus on the dynamics of the necking process and on its dependence on both the Bond and Weber numbers, respectively, defined as Bo=ρga2/σ, and WeQ=ρQ2/(π2a3σ). Here, a, ρ, σ, g, and Q are the inner radius of the nozzle, the liquid density, the gas-liquid surface tension, the gravitational acceleration, and the gas flow rate. Our experimental data indicate that the collapse process is not only driven by capillarity but also by the liquid hydrostatic pressure. Good agreement is achieved between the measurements of the collapse time and that given by the scaling proposed as tc=tσ/1+121/3Bo2/3 where tσ=(ρa3/σ)1/2 is the capillary time, valid in the limit WeQ→0. In addition, the details of the final instants previous to pinch-off have been analyzed by recording the time evolution of both the bubble.
Dynamical properties of quantum many-body systems with long-range interactions

Employing large-scale quantum Monte Carlo simulations, we systematically compute the energy spectra of the 2D spin-1/2 Heisenberg model with long-range interactions. With the $1/r^{\alpha}$ ferromagnetic and staggered antiferromagnetic interactions, we find the explicit range in $\alpha$ for {\color{black} the short-range Goldstone-type (gapless), anomalous Goldstone-type (gapless) and Higgs-type (gapped) spectra. Accompanied by the spin wave analysis, our numerical results vividly reveal how the long-range interactions alter the usual linear and quadratic magnon dispersions in 2D quantum magnets and give rise to anomalous dynamical exponents. Moreover, we find explicit case where the gapped excitation exists even when the Hamiltonian is extensive. This work provides the first set of unbiased dynamical data} of long-range quantum many-body systems and suggests that many universally accepted low-energy customs for short-range systems need to be substantially modified for long-range ones which are of immediate relevance to the ongoing experimental efforts from quantum simulators to 2D quantum moir\'e materials.
Magnetic Reconnection as the Driver of the Solar Wind

We present EUV solar observations showing evidence for omnipresent jetting activity driven by small-scale magnetic reconnection at the base of the solar corona. We argue that the physical mechanism that heats and drives the solar wind at its source is ubiquitous magnetic reconnection in the form of small-scale jetting activity (a.k.a. jetlets). This jetting activity, like the solar wind and the heating of the coronal plasma, is ubiquitous regardless of the solar cycle phase. Each event arises from small-scale reconnection of opposite-polarity magnetic fields producing a short-lived jet of hot plasma and Alfvén waves into the corona. The discrete nature of these jetlet events leads to intermittent outflows from the corona, which homogenize as they propagate away from the Sun and form the solar wind. This discovery establishes the importance of small-scale magnetic reconnection in solar and stellar atmospheres in understanding ubiquitous phenomena such as coronal heating and solar wind acceleration. Based on previous analyses linking the switchbacks to the magnetic network, we also argue that these new observations might provide the link between the magnetic activity at the base of the corona and the switchback solar wind phenomenon. These new observations need to be put in the bigger picture of the role of magnetic reconnection and the diverse form of jetting in the solar atmosphere.
Transferable Energy Storage Bidder

Energy storage resources must consider both price uncertainties and their physical operating characteristics when participating in wholesale electricity markets. This is a challenging problem as electricity prices are highly volatile, and energy storage has efficiency losses, power, and energy constraints. This article presents a novel, versatile, and transferable approach combining model-based optimization with a convolutional long short-term memory network for energy storage to respond to or bid into wholesale electricity markets. We test our proposed approach using historical prices from New York State, showing it achieves state-of-the-art results, achieving between 70% to near 90% profit ratio compared to perfect foresight cases, in both price response and wholesale market bidding setting with various energy storage durations. We also test a transfer learning approach by pre-training the bidding model using New York data and applying it to arbitrage in Queensland, Australia. The result shows transfer learning achieves exceptional arbitrage profitability with as little as three days of local training data, demonstrating its significant advantage over training from scratch in scenarios with very limited data availability.
AmbieGen: A Search-based Framework for Autonomous Systems Testing

Thorough testing of safety-critical autonomous systems, such as self-driving cars, autonomous robots, and drones, is essential for detecting potential failures before deployment. One crucial testing stage is model-in-the-loop testing, where the system model is evaluated by executing various scenarios in a simulator. However, the search space of possible parameters defining these test scenarios is vast, and simulating all combinations is computationally infeasible. To address this challenge, we introduce AmbieGen, a search-based test case generation framework for autonomous systems. AmbieGen uses evolutionary search to identify the most critical scenarios for a given system, and has a modular architecture that allows for the addition of new systems under test, algorithms, and search operators. Currently, AmbieGen supports test case generation for autonomous robots and autonomous car lane keeping assist systems. In this paper, we provide a high-level overview of the framework's architecture and demonstrate its practical use cases.
Discrete Radio Sources in the Spiral Galaxy NGC 6946

We analyze the 2″-resolution, high-sensitivity radio continuum observations of the nearby spiral galaxy NGC 6946 at 6 and 20 cm by Lacey, Duric, & Goss to derive a luminosity function at each wavelength for 43 H II region candidates and for 15 supernova remnant (SNR) candidates. The H II region radio luminosity functions are best fitted by power laws consistent with the shape of the optical luminosity function of Bonnarel, Boulsteix, & Marcelin. The SNR luminosity functions are fitted by considerably steeper power laws than the H II region luminosity functions. Extinctions to the H II regions are estimated from a comparison of radio flux densities with new optical fluxes derived from the Hα observations of Van Dyk. A dependence of extinction on galactocentric radius is investigated, but none is found.
Boundary Layer Solutions Induced by Displacement Boundary Conditions of Shear Deformable Beams and Accuracy Study of Several Higher-Order Beam Theories

Although a number of the higher-order/refined beam theories had been proposed for the analysis of shear deformable beams, these beam theories cannot properly take account of the displacement boundary conditions of shear deformable beams, and they are not capable of characterizing the boundary layer effects resulting from the displacement boundary conditions. A new beam theory with the sixth-order differential equilibrium equations is employed in this paper to analytically solve the boundary layer solutions of three typical beams with clamped ends. The influences of the boundary layer solutions given by the new sixth-order beam theory on the deflections, shear forces and stresses are studied, and the resulting solutions are evaluated by the finite-element results. The accuracy assessment of the deflections given by various higher-order/refined beam theories is also carried out by comparing these analytical solutions of deflections with the numerical results. The numerical results show that the new sixth-order beam theory can properly deal with the displacement boundary conditions of shear deformable beams and yield accurate solutions of both displacements and stresses. Furthermore, the new sixth-order beam theory is also capable of properly characterizing the boundary layer effect induced by the displacement boundary conditions. The current study also shows that the boundary layer solutions at the zone of clamped ends do not considerably affect the deflections; however, they contribute significantly to the localized distributions of the shear force and the normal stresses at the zone of the clamped ends. In particular, the resulting normal stresses at the beam surfaces of a clamped end are much larger than those predicted by Timoshenko beam theory.
Bringing data minimization to digital wallets at scale with general-purpose zero-knowledge proofs

Today, digital identity management for individuals is either inconvenient and error-prone or creates undesirable lock-in effects and violates privacy and security expectations. These shortcomings inhibit the digital transformation in general and seem particularly concerning in the context of novel applications such as access control for decentralized autonomous organizations and identification in the Metaverse. Decentralized or self-sovereign identity (SSI) aims to offer a solution to this dilemma by empowering individuals to manage their digital identity through machine-verifiable attestations stored in a"digital wallet"application on their edge devices. However, when presented to a relying party, these attestations typically reveal more attributes than required and allow tracking end users' activities. Several academic works and practical solutions exist to reduce or avoid such excessive information disclosure, from simple selective disclosure to data-minimizing anonymous credentials based on zero-knowledge proofs (ZKPs). We first demonstrate that the SSI solutions that are currently built with anonymous credentials still lack essential features such as scalable revocation, certificate chaining, and integration with secure elements. We then argue that general-purpose ZKPs in the form of zk-SNARKs can appropriately address these pressing challenges. We describe our implementation and conduct performance tests on different edge devices to illustrate that the performance of zk-SNARK-based anonymous credentials is already practical. We also discuss further advantages that general-purpose ZKPs can easily provide for digital wallets, for instance, to create"designated verifier presentations"that facilitate new design options for digital identity infrastructures that previously were not accessible because of the threat of man-in-the-middle attacks.
Permutation Statistics in Conjugacy Classes of the Symmetric Group

We introduce the notion of a weighted inversion statistic on the symmetric group, and examine its distribution on each conjugacy class. Our work generalizes the study of several common permutation statistics, including the number of inversions, the number of descents, the major index, and the number of excedances. As a consequence, we obtain explicit formulas for the first moments of several statistics by conjugacy class. We also show that when the cycle lengths are sufficiently large, the higher moments of arbitrary permutation statistics are independent of the conjugacy class. Fulman (J. Comb. Theory Ser. A., 1998) previously established this result for major index and descents. We obtain these results, in part, by generalizing the techniques of Fulman (ibid.), and introducing the notion of permutation constraints. For permutation statistics that can be realized via symmetric constraints, we show that each moment is a polynomial in the degree of the symmetric group.
New applications of the Mellin transform to automorphic L-fuctions

Cf [2, Theorem D]. In this article, we follow some questions that arose naturally in this context. The first one was suggested by a remark of Sarnak, according to which we cannot have such universal bounds for short intervals, e.g. for the integral on [−1, 1] in (0.1); at least such cannot be obtained if m is allowed to vary. See the Introduction to [2], § 2. The argument does not succeed if m is fixed; neither did the author succeed in finding, for m fixed, an absolute bound on a short interval. This remains an interesting problem. In Chapter 2, we obtain a universal lower bound, for m fixed, for the integral on an interval [−A logC,A logC] where C is the analytic conductor. Even then, we could not obtain a fixed lower bound. Rather, we prove that this integral is larger than c(logC)−1/2 where c > 0 is an absolute constant. This may not be optimal, but it is commensurable with the Lindelöf conjecture. (We hope that an analytic number theorist familiar with the use of the Mellin transform, as in the proof of the approximate functional equation, will be able substantially to improve this result.) Moreover, we can shift the ordinate and obtain a general result on an interval [X − T,X + T ] where X is arbitrary and T is of the order of logX . See Theorem 2.2,
The Airy2 process and the 3D Ising model

The Ferrari–Spohn diffusion process arises as limit process for the 2D Ising model as well as random walks with area penalty. Motivated by the 3D Ising model, we consider M such diffusions conditioned not to intersect. We show that the top process converges to the Airy2 process as M→∞ . We then explain the relation with the 3D Ising model and present some conjectures about it.
Gradient phonotactic acceptability a case study from Slovak

Phonotactic well-formedness judgments are usually gradient, the theoretical interpretation of which is controversial in the phonological literature. In this study we present experimental evidence from Slovak that speakers do have intuitions about unattested grammatical forms as well as attested marginal ones and these intuitions can be modeled fairly closely by gradient phonotactic learners like, for instance, the Hayes-Wilson Phonotactic Learner. Our results suggest that in gradient phonotactic judgments the knowledge of the relative probability of various combinations of natural classes plays a decisive role. We pay special attention to sonority reversal clusters in Slovak and claim that these sequences, although attested in the language, are on the verge of grammaticality and thus prone to change.
Explaining workers’ inactivity in social colonies from first principles

Social insects are among the ecologically most successful collectively living organisms, with efficient division of labour a key feature of this success. Surprisingly, these efficient colonies often have a large proportion of inactive workers in their workforce, sometimes referred to as lazy workers. The dominant hypotheses explaining this are based on specific life-history traits, specific behavioural features or uncertain environments where inactive workers can provide a ‘reserve’ workforce that can spring into action quickly. While there is a number of experimental studies that show and investigate the presence of inactive workers, mathematical and computational models exploring specific hypotheses are not common. Here, using a simple mathematical model, we show that a parsimonious hypothesis can explain this puzzling social phenomenon. Our model incorporates social interactions and environmental influences into a game-theoretical framework and captures how individuals react to environment by allocating their activity according to environmental conditions. This model shows that inactivity can emerge under specific environmental conditions as a by-product of the task allocation process. Our model confirms the empirical observation that in the case of worker loss, prior homeostatic balance is re-established by replacing some of the lost force with previously inactive workers. Most importantly, our model shows that inactivity in social colonies can be explained without the need to assume an adaptive function for this phenomenon.
Diagnostic testing in people with primary ciliary dyskinesia: An international participatory study

Diagnostic tests are important in primary ciliary dyskinesia (PCD), a rare disease, to confirm the diagnosis and characterize the disease. We compared diagnostic tests for PCD between countries worldwide, assessed whether people with PCD recall their tests, and identified factors associated with the use of tests. We used cross-sectional data from COVID-PCD--an international participatory cohort study collecting information directly from people with PCD. The baseline questionnaire inquired about tests used for PCD diagnosis. Using logistic regression, we investigated factors associated with measurement of nasal nitric oxide (nNO), biopsy for electron or video microscopy, and genetic testing. We included data from 747 participants (60% females) from 49 countries worldwide with median age 27 (interquartile range 12-44). Most (92%) reported diagnostic tests for PCD. Participants reported measurements of nNO (342; 49%), biopsy samples (561; 75%), and genetic tests (435; 58%). The reported use of individual tests, such as genetics, varied between countries from 38% in Switzerland to 68% in North America. Participant recall of test type also differed between countries with lowest recall in Switzerland. One-third (232; 36%) of participants reported all three tests (nNO, biopsy, and genetics). Recently diagnosed people reported more tests [nNO odds ratio (OR) 2.2, 95% Confidence Interval (CI) 1.5-3.2; biopsy OR 3.2, 95%CI 2.1-4.9; genetics OR 4.7, 95%CI 3.2-6.9] and those with situs abnormalities fewer tests (nNO OR 0.5, 95%CI 0.4-0.7; biopsy OR 0.5, 95%CI 0.4-0.8; genetics OR 0.7, 95%CI 0.5-0.94). Our results indicate PCD diagnostic testing differed widely around the world and many patients received incomplete diagnostic work-up based only on clinical features or single tests. People diagnosed long ago and those with situs abnormalities possibly benefit from supplementary testing to refine their diagnosis as a prerequisite for personalized medicine.
Development of a Suicide Prevention Life Gatekeeper Training Program in China: A Delphi study

Introduction: Youth suicide has been a pressing public mental health concern in China, yet there is a lack of localised gatekeeper intervention programs developed for Chinese schools. Life Gatekeeper was the first systematically developed gatekeeper program which aimed to equip teachers and parents with knowledge, skills, and ability to identify and intervene students at high risk of suicide. This study aimed to achieve expert consensus on the content of this program. Methods: The Delphi method was used to elicit consensus on statements essential to include in the training program. In the form of scoring existing statements and responding to open-ended questions, experts have the opportunity to evaluate the content, delivery form, feasibility, and overall feeling of the initial training program. Two Delphi rounds were conducted among Chinese panel members with diversified professional backgrounds in suicide research and practice. Statements were accepted for inclusion in the adjusted training program if they were endorsed by at least 80% of the panel. Results: Consensus was achieved on 201 statements out of 207 statements for inclusion in the adapted guidelines for the gatekeeper programme, with 151 from the original questionnaire, and 50 generated from the comments of the panel members. These endorsed statements were used to develop the Life Gatekeeper training program. Conclusion: This Delphi study provided an evidence base in developing of the first gatekeeper training program in China. We hope that the current study could pave the way for more evidence based suicide prevention programs in China. Further study is warranted to evaluate the effectiveness of the Life Gatekeeper training program.