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One of the main statistical features of near-neutral atmospheric boundary layer (ABL) turbulence is the positive vertical velocity skewness $Sk_w$ above the roughness sublayer or the buffer region in smooth-walls. The $Sk_w$ variations are receiving renewed interest in many climate-related parameterizations of the ABL given their significance to cloud formation and to testing sub-grid schemes for Large Eddy Simulations (LES). The vertical variations of $Sk_w$ are explored here using high Reynolds number wind tunnel and flume experiments collected above smooth, rough, and permeable-walls in the absence of buoyancy and Coriolis effects. These laboratory experiments form a necessary starting point to probe the canonical structure of $Sk_w$ as they deal with a key limiting case (i.e. near-neutral conditions) that has received much less attention compared to its convective counterpart in atmospheric turbulence studies. Diagnostic models based on cumulant expansions, realizability constraints, and the now-popular constant mass flux approach routinely employed in the convective boundary layer as well as prognostic models based on third-order budgets are used to explain variations in $Sk_w$ for the idealized laboratory conditions. The failure of flux-gradient relations to model $Sk_w$ from the gradients of the vertical velocity variance $\sigma_w^2$ are explained and corrections based on models of energy transport offered. Novel links between the diagnostic and prognostic models are also featured, especially for the inertial term in the third order budget of the vertical velocity fluctuation. The co-spectral properties of $w'/\sigma_w$ versus $w'^2/\sigma_w^2$ are also presented for the first time to assess the dominant scales governing $Sk_w$ in the inner and outer layers, where $w'$ is the fluctuating vertical velocity and $\sigma_w$ is the vertical velocity standard deviation.

Today's large language models (LLMs) can solve challenging question-answering tasks, and prompt engineering techniques, such as chain-of-thought (CoT), have gained attention for enhancing the explanation and correctness of outputs. Nevertheless, models require significant time to generate answers augmented with lengthy reasoning details. To address this issue, this paper analyzes the impact of output lengths on LLM inference pipelines and proposes novel metrics to evaluate them in terms of \textit{correct conciseness}. It also examines the impact of controlling output length through a refined prompt engineering strategy, Constrained-CoT (CCoT), which encourages the model to limit output length. Experiments on pre-trained LLMs demonstrated the benefit of the proposed metrics and the effectiveness of CCoT across different models. For instance, constraining the reasoning of LLaMA2-70b to 100 words improves the accuracy from 36.01\% (CoT) to 41.07\% (CCoT) on the GSM8K dataset, while reducing the average output length by 28 words., Comment: Preprint version, under review

We provide empirical evidence that within the inertial sub layer of adiabatic turbulent flows over smooth walls, the skewness of the vertical velocity component $Sk_w$ displays universal behaviour, being constant and constrained within the range $Sk_w \approx 0.1-0.16$, regardless of flow configuration and Reynolds number. A theoretical model is proposed to explain the observed behaviour, including the observed range of variations of $Sk_w$. The model clarifies why $Sk_w$ cannot be predicted from down-gradient closure approximations routinely employed in meteorological and climate models whereby $Sk_w$ impacts cloud formation and dispersion processes. The model also offers an alternative and implementable approach.

Turbulent flows over a large surface area (S) covered by n obstacles experience an overall drag due to the presence of the ground and the protruding obstacles into the flow. The drag partition between the roughness obstacles and the ground is analyzed using an analytical model proposed by Raupach (1992) and is hereafter referred to as R92. The R92 is based on the premise that the wake behind an isolated roughness element can be described by a shelter area A and a shelter volume V. The individual sizes of A and V without any interference from other obstacles can be determined from scaling analysis for the spread of wakes. To upscale from an individual roughness element to n/S elements where wakes may interact, R92 adopted a background stress re-normalizing instead of reducing A or V with each element addition. This work shows that R92's approach only converges to a linear reduction in A and V for small n/S where wakes have low probability of interacting with one another. This probabilistic nature suggests that up-scaling from individual to multiple roughness elements can be re-formulated using stochastic averaging methods proposed here. The two approaches are shown to recover R92 under plausible conditions. Comparisons between R92 and available data on blocks and vegetation-like roughness elements confirm the practical utility of R92 and its potential use in large-scale models provided the relevant parameters accommodate certain features of the roughness element type (cube versus vegetation-like) and, to a lesser extent, their configuration throughout S.

Ensuring the accuracy of responses provided by large language models (LLMs) is crucial, particularly in clinical settings where incorrect information may directly impact patient health. To address this challenge, we construct K-QA, a dataset containing 1,212 patient questions originating from real-world conversations held on K Health (an AI-driven clinical platform). We employ a panel of in-house physicians to answer and manually decompose a subset of K-QA into self-contained statements. Additionally, we formulate two NLI-based evaluation metrics approximating recall and precision: (1) comprehensiveness, measuring the percentage of essential clinical information in the generated answer and (2) hallucination rate, measuring the number of statements from the physician-curated response contradicted by the LLM answer. Finally, we use K-QA along with these metrics to evaluate several state-of-the-art models, as well as the effect of in-context learning and medically-oriented augmented retrieval schemes developed by the authors. Our findings indicate that in-context learning improves the comprehensiveness of the models, and augmented retrieval is effective in reducing hallucinations. We make K-QA available to to the community to spur research into medically accurate NLP applications., Comment: The data and the evaluation script are available at https://github.com/Itaymanes/K-QA. Results and model comparisons can be viewed at https://huggingface.co/spaces/Itaykhealth/K-QA

The mixed-valence compound SmB6 with partially filled samarium 4f flat bands hybridizing with 5d conduction bands is a paramount example of a correlated topological heavy-fermion system. In this study we revisit the topology of SmB6 with the band theory paradigm and uncover previously overlooked aspects resulting from the formation of multiple topological gaps in the electronic structure. By invoking topological quantum chemistry (TQC) we provide a detailed classification of the strong and crystalline topological features that derive from the existence of such topological gaps. To corroborate this classification, we calculate Wilson loops and simulate the surface electronic structure using a minimal tight-binding model, allowing us to describe its surface states and confirm the crystalline topology. We finally discuss its implications for experiments.

Unlike the surface code, quantum low-density parity-check (QLDPC) codes can have a finite encoding rate, potentially lowering the error correction overhead. However, finite-rate QLDPC codes have nonlocal stabilizers, making it difficult to design stabilizer measurement circuits that are low-depth and do not decrease the effective distance. Here, we demonstrate that a popular family of finite-rate QLDPC codes, hypergraph product codes, has the convenient property of distance-robustness: any stabilizer measurement circuit preserves the effective distance. In particular, we prove the depth-optimal circuit in [Tremblay et al, PRL 129, 050504 (2022)] is also optimal in terms of effective distance., Comment: 5 pages plus references, comments welcome

Axion insulators are 3D magnetic higher-order topological insulators protected by inversion-symmetry that exhibit hinge-localized chiral channels and induce quantized topological magnetoelectric effects. Recent research has suggested that axion insulators may be capable of detecting dark-matter axion-like particles by coupling to their axionic excitations. Beyond its fundamental theoretical interest, designing a photonic AXI offers the potential to enable the development of magnetically-tunable photonic switch devices through the manipulation of the axionic modes and their chiral propagation using external magnetic fields. Motivated by these facts, in this work, we propose a novel approach to induce axionic band topology in gyrotropic 3D Weyl photonic crystals gapped by supercell modulation. To quantize an axionic angle, we create domain-walls across inversion-symmetric photonic crystals, incorporating a phase-obstruction in the supercell modulation of their dielectric elements. This allows us to bind chiral channels on inversion-related hinges, ultimately leading to the realization of an axionic chiral channel of light. Moreover, by controlling the material gyrotropic response, we demonstrate a physically accessible way of manipulating the axionic modes through a small external magnetic bias, which provides an effective topological switch between different 1D chiral photonic fiber configurations. Remarkably, the unidirectional axionic hinge states supported by the photonic axion insulator are buried in a fully connected 3D dielectric structure, thereby being protected from radiation through the electromagnetic continuum. As a result, they are highly suitable for applications in guided-light communication, where the preservation and non-reciprocal propagation of photonic signals are of paramount importance., Comment: 6 figures and 11 pages

Tight-binding models can accurately predict the band structure and topology of crystalline systems and they have been heavily used in solid-state physics due to their versatility and low computational cost. It is quite straightforward to build an accurate tight-binding model of any crystalline system using the maximally localized Wannier functions of the crystal as a basis. In 1D and 2D photonic crystals, it is possible to express the wave equation as two decoupled scalar eigenproblems where finding a basis of maximally localized Wannier functions is feasible using standard Wannierization methods. Unfortunately, in 3D photonic crystals, the vectorial nature of the electromagnetic solutions cannot be avoided. This precludes the construction of a basis of maximally localized Wannier functions via usual techniques. In this work, we show how to overcome this problem by using topological quantum chemistry which will allow us to express the band structure of the photonic crystal as a difference of elementary band representations. This can be achieved by the introduction of a set of auxiliary modes, as recently proposed by Solja\v{c}i\'c et. al., which regularize the $\Gamma$-point obstruction arising from transversality constraint of the Maxwell equations. The decomposition into elementary band representations allows us to isolate a set of pseudo-orbitals that permit us to construct an accurate transversality-enforced tight-binding model (TETB) that matches the dispersion, symmetry content, and topology of the 3D photonic crystal under study. Moreover, we show how to introduce the effects of a gyrotropic bias in the framework, modeled via non-minimal coupling to a static magnetic field. Our work provides the first systematic method to analytically model the photonic bands of the lowest transverse modes over the entire BZ via a TETB model., Comment: 3 figures

Quantum error correction (QEC) is theoretically capable of achieving the ultimate estimation limits in noisy quantum metrology. However, existing quantum error-correcting codes designed for noisy quantum metrology generally exploit entanglement between one probe and one noiseless ancilla of the same dimension, and the requirement of noiseless ancillas is one of the major obstacles to implementing the QEC metrological protocol in practice. Here we successfully lift this requirement by explicitly constructing two types of multi-probe quantum error-correcting codes, where the first one utilizes a negligible amount of ancillas and the second one is ancilla-free. Specifically, we consider Hamiltonian estimation under Markovian noise and show that (i)~when the Heisenberg limit (HL) is achievable, our new codes can achieve the HL and its optimal asymptotic coefficient; (ii)~when only the standard quantum limit (SQL) is achievable (even with arbitrary adaptive quantum strategies), the optimal asymptotic coefficient of the SQL is also achievable by our new codes under slight modifications., Comment: 40 pages, 6 figures, new results added, an error fixed, published version

Target tracking represents a state estimation problem recurrent in many practical scenarios like air traffic control, autonomous vehicles, marine radar surveillance and so on. In a Bayesian perspective, when phenomena like clutter are present, the vast majority of the existing tracking algorithms have to deal with association hypotheses which can grow in the number over time; in that case, the posterior state distribution can become computationally intractable and approximations have to be introduced. In this work, the impact of the number of hypotheses and corresponding reductions is investigated both in terms of employed computational resources and tracking performances. For this purpose, a recently developed adaptive mixture model reduction algorithm is considered in order to assess its performances when applied to the problem of single object tracking in the presence of clutter and to provide additional insights on the addressed problem.

By means of group theory, topological quantum chemistry, first-principles and Monte Carlo calculations, we analyze the topology of the 2D buckled honeycomb lattice phonon spectra. Taking the pure crystal structure as an input, we show that eleven distinct phases are possible, five of which necessarily have non-trivial topology according to topological quantum chemistry. Another four of them are also identified as topological using Wilson loops in an analytical model that includes all the symmetry allowed force constants up to third nearest neighbors, making a total of nine topological phases. We then compute the ab initio phonon spectra for the two-dimensional crystals of Si, Ge, P, As and Sb in this structure and construct its phase diagram. Despite the large proportion of topological phases found in the analytical model, all of the crystals lie in a trivial phase. By analyzing the force constants space using Monte Carlo calculations, we elucidate why topological phonon phases are physically difficult to realize in real materials with this crystal structure.

Phonons play a crucial role in many properties of solid state systems, such as thermal and electrical conductivity, neutron scattering and associated effects or superconductivity. Hence, it is expected that topological phonons will also lead to rich and unconventional physics and the search of materials hosting topological phonons becomes a priority in the field. In electronic crystalline materials, a large part of the topological properties of Bloch states can be indicated by their symmetry eigenvalues in reciprocal space. This has been adapted to the high-throughput calculations of topological materials, and more than half of the stoichiometric materials on the databases are found to be topological insulators or semi-metals. Based on the existing phonon materials databases, here we have performed the first catalogue of topological phonon bands for more than ten thousand three-dimensional crystalline materials. Using topological quantum chemistry, we calculate the band representations, compatibility relations, and band topologies of each isolated set of phonon bands for the materials in the phonon databases. We have also calculated the real space invariants for all the topologically trivial bands and classified them as atomic and obstructed atomic bands. In particular, surface phonon modes (dispersion) are calculated on different cleavage planes for all the materials. Remarkably, we select more than one thousand "ideal" non-trivial phonon materials to fascinate the future experimental studies. All the data-sets obtained in the the high-throughput calculations are used to build a Topological Phonon Database., Comment: 8+535 pages, 187 figures, 21 tables. The Topological Phonon Database is available at https://www.topologicalquantumchemistry.com/topophonons or https://www.topologicalquantumchemistry.fr/topophonons

In 2D Chern insulators (2D CI), the topology of the bulk states is captured by a topological invariant, the Chern number. The scalar bulk-boundary correspondence (sBBC) relates the change in Chern number across an interface with the number of 1D chiral edge modes at the interface. However, 3D Chern insulators (3D CI) can be characterized by a Chern vector C = (Cx, Cy, Cz) and a more general vector bulk-boundary correspondence (vBBC) is needed to correctly predict the propagation of the surface modes. In this work the possible interfaces between 3D photonic CIs are explored, focusing on possible changes in Chern vector orientation. To formulate a 3D vBBC, a link is derived between the Chern vector discontinuity across an interface and the winding of the surface equifrequency loops on the boundary. Lastly, it is demonstrated how to correctly predict the number and the propagation direction of topological photonic surface modes in 3D CIs.

In target tracking and sensor fusion contexts it is not unusual to deal with a large number of Gaussian densities that encode the available information (multiple hypotheses), as in applications where many sensors, affected by clutter or multimodal noise, take measurements on the same scene. In such cases reduction procedures must be implemented, with the purpose of limiting the computational load. In some situations it is required to fuse all available information into a single hypothesis, and this is usually done by computing the barycenter of the set. However, such computation strongly depends on the chosen dissimilarity measure, and most often it must be performed making use of numerical methods, since in very few cases the barycenter can be computed analytically. Some issues, like the constraint on the covariance, that must be symmetric and positive definite, make it hard the numerical computation of the barycenter of a set of Gaussians. In this work, Fixed-Point Iterations (FPI) are presented for the computation of barycenters according to several dissimilarity measures, making up a useful toolbox for fusion/reduction of Gaussian sets in applications where specific dissimilarity measures are required.

We study the dynamical Mahler measure of multivariate polynomials and present dynamical analogues of various results from the classical Mahler measure as well as examples of formulas allowing the computation of the dynamical Mahler measure in certain cases. We discuss multivariate analogues of dynamical Kronecker's Lemma and present some improvements on the result for two variables due to Carter, Lal\'in, Manes, Miller, and Mocz., Comment: 22 pages, 5 figures

In this paper, we show that the concatenation of the Fibonacci sequence is \textit{normal} in base $10$, meaning every string of a given length, $k$, occurs as frequently as every other string of length $k$ (there are as many $1$'s as $2$'s and as many $704$'s and $808$'s). Although we know that almost every number is normal, we can name very few of them. It is still unclear if $e$, $\pi$, or $\sqrt{2}$ are normal. We show that concatenating the Fibonacci sequence behind a decimal creates a normal number in every base of the form $5^x\times2^y$. We then provide evidence that potentially extends our result to all integer bases, and claim that the Fibonacci concatenation is \textit{absolutely normal}.

We discuss several aspects of the dynamical Mahler measure for multivariate polynomials. We prove a weak dynamical version of Boyd--Lawton formula and we characterize the polynomials with integer coefficients having dynamical Mahler measure zero both for the case of one variable (Kronecker's lemma) and for the case of two variables, under the assumption that the dynamical version of Lehmer's question is true., Comment: Corrections and updates based on referee report. One section (former section 2) removed