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We present a multi-probe transport analysis that effectively separates bulk and edge currents in large Hall bar devices with standard geometries. Applied to transport measurements on all possible four-probe configurations of six-probe Hall bar devices made of inverted three-layer InAs/GaInSb quantum wells (QWs), our analysis not only reveals the presence of dissipative edge currents in the topological gap, but also allows the temperature dependence of bulk and edge conductivity to be evaluated separately. The temperature dependence of the edge conductivity for Hall bar channels from 10 $\mu$m to 70~$\mu$m in the range of 1.5 K to 45 K is consistent with the theoretical expectation of weakly interacting helical edge electrons with backscattering due to localized magnetic moments of charge impurities. We argue that these charge impurities are naturally associated with intrinsic Ga-antisite defects, which act as double acceptors in InAs/Ga(In)Sb-based QWs.

We characterize the Tukey order, the Galvin property/Cohesive ultrafilters from \cite{Kanamori1978} in terms of ultrapowers. We use this characterization to measure the distance between the Tukey order and other well-known orders of ultrafilters. Secondly, we improve two theorems of Kanamori \cite{Kanamori1978} from the 70's. We then study the point spectrum and the depth spectrum of an ultrafilter, and give a simple answer to Kanamori's question \cite[Question 2]{Kanamori1978} starting from a supercompact cardinal. Finally, we prove some consistency results regarding the depth spectrum of an ultrafilter, starting from the optimal assumption of $o(\kappa)=\kappa^{++}$, using a Woodin-like surgery argument.

This paper explores the application of the Condorcet Jury theorem to the domain of sentiment analysis, specifically examining the performance of various large language models (LLMs) compared to simpler natural language processing (NLP) models. The theorem posits that a majority vote classifier should enhance predictive accuracy, provided that individual classifiers' decisions are independent. Our empirical study tests this theoretical framework by implementing a majority vote mechanism across different models, including advanced LLMs such as ChatGPT 4. Contrary to expectations, the results reveal only marginal improvements in performance when incorporating larger models, suggesting a lack of independence among them. This finding aligns with the hypothesis that despite their complexity, LLMs do not significantly outperform simpler models in reasoning tasks within sentiment analysis, showing the practical limits of model independence in the context of advanced NLP tasks.

In this paper, we demonstrate that non-generative, small-sized models such as FinBERT and FinDRoBERTa, when fine-tuned, can outperform GPT-3.5 and GPT-4 models in zero-shot learning settings in sentiment analysis for financial news. These fine-tuned models show comparable results to GPT-3.5 when it is fine-tuned on the task of determining market sentiment from daily financial news summaries sourced from Bloomberg. To fine-tune and compare these models, we created a novel database, which assigns a market score to each piece of news without human interpretation bias, systematically identifying the mentioned companies and analyzing whether their stocks have gone up, down, or remained neutral. Furthermore, the paper shows that the assumptions of Condorcet's Jury Theorem do not hold suggesting that fine-tuned small models are not independent of the fine-tuned GPT models, indicating behavioural similarities. Lastly, the resulted fine-tuned models are made publicly available on HuggingFace, providing a resource for further research in financial sentiment analysis and text classification.

We report on the observation and comprehensive study of the terahertz radiation induced magneto-photogalvanic effect (MPGE) in bulk CdHgTe crystals hosting Kane fermions. The MPGE has been detected in Cd$_{x}$Hg$_{1-x}$Te films with Cd contents $x = 0.15$ and $0.22$ subjected to an in-plane magnetic field. At liquid helium temperature we observed multiple resonances in MPGE current upon variation of magnetic field. In the $x = 0.22$ with noninverted band structure, the resonances are caused by cyclotron resonance (CR) and photoionization of an impurity level. In the $x = 0.15$ films with an inverted band structure, they originate from the CR and interband optical transitions. Band structure calculated by the Kane model perfectly describes positions of all resonances. In particularly, the resonant MPGE caused by interband transitions excited by THz radiation is caused by the gapless energy spectrum of Kane fermions realized in materials with certain Cd contents and temperature range. In addition to the resonant MPGE current we detected a nonresonant one due to indirect optical transitions (Drude-like). This contribution has a nonmonotonic magnetic field dependence increasing linearly at low magnetic field $B$, approaching a maximum at moderate field and decreasing at high $B$. While the nonresonant MPGE decreases drastically with increasing temperature, it is well measurable up to room temperature. The developed theory demonstrates that the MPGE current arises due to cubic in momentum spin-dependent terms in the scattering probability. The asymmetry caused by these effects results in a pure spin current which is converted into an electric current due to the Zeeman effect.

Answer Set Programming (ASP) is a declarative problem solving paradigm that can be used to encode a combinatorial problem as a logic program whose stable models correspond to the solutions of the considered problem. ASP has been widely applied to various domains in AI and beyond. The question "What can be said about stable models of a logic program from its static information?" has been investigated and proved useful in many circumstances. In this work, we dive into this direction more deeply by making the connection between a logic program and a Boolean network, which is a prominent modeling framework with applications to various areas. The proposed connection can bring the existing results in the rich history on static analysis of Boolean networks to explore and prove more theoretical results on ASP, making it become a unified and powerful tool to further study the static analysis of ASP. In particular, the newly obtained insights have the potential to benefit many problems in the field of ASP.

We develop the non-normal variations of two classical Prikry-type forcings; namely, Magidor and Radin forcings. We generalize the fact that the non-normal Prikry forcing is a projection of the extender-based to a coordinate of the extender to our forcing and the Radin/Magidor-Radin-extender-based forcing from \cite{CarmiMagidorRadin,CarmiRadin}. Then, we show that both the non-normal variation of Magidor and Radin forcings can add a Cohen generic function to every limit point of cofinality $\omega$ of the generic club. Second, we show that this phenomenon is limited to the cases where the forcings are not designed to change the cofinality of a measurable $\kappa$ to $\omega_1$. Specifically, in the above-mentioned circumstances these forcings do not project onto any $\kappa$-distributive forcing. We use that to conclude that the extender-based Radin/Magidor-Radin forcing does not add fresh subsets to $\kappa$ as well. In the second part of the paper we focus on the natural non-normal variation of Gitik's forcing from \cite[\S3]{GitikNonStationary}. Our main result shows that this poset can be employed to change the cofinality of a measurable cardinal $\kappa$ to $\omega_1$ while introducing a Cohen subset of $\kappa$.

We provide two types of guessing principles for ultrafilter ($\diamondsuit^{-}_{\lambda}(U), \ \diamondsuit^p_\lambda(U)$) on $\omega$ which form subclasses of Tukey-top ultrafilters, and construct such ultrafilters in $ZFC$. These constructions are essentially different from Isbell's construction \cite{Isbell65} of Tukey-top ultrafilters. We prove using the Borel-Cantelli Lemma that full guessing is not possible and rule out several stronger guessing principles e.g. we prove that no Dodd-sound ultrafilters exist on $\omega$. We then apply these guessing principles to force a $q$-point which is Tukey-top (answering a question from \cite{Benhanou/Dobrinen23}), and prove that the class of ultrafilters which satisfy $\neg\diamondsuit^{-}_\lambda$ is closed under Fubini sum. Finally, we show that $\diamondsuit^{-}_\lambda$ and $\diamondsuit^p_\lambda$ can be separated.

This paper introduces a new risk-on risk-off strategy for the stock market, which combines a financial stress indicator with a sentiment analysis done by ChatGPT reading and interpreting Bloomberg daily market summaries. Forecasts of market stress derived from volatility and credit spreads are enhanced when combined with the financial news sentiment derived from GPT-4. As a result, the strategy shows improved performance, evidenced by higher Sharpe ratio and reduced maximum drawdowns. The improved performance is consistent across the NASDAQ, the S&P 500 and the six major equity markets, indicating that the method generalises across equities markets.

The tool mpbn offers a Python programming interface for an easy interactive editing of Boolean networks and the efficient computation of elementary properties of their dynamics, including fixed points, trap spaces, and reachability properties under the Most Permissive update mode. Relying on Answer-Set Programming logical framework, we show that mpbn is scalable to models with several thousands of nodes and is one of the best-performing tool for computing minimal and maximal trap spaces of Boolean networks, a key feature for understanding and controling their stable behaviors. The tool is available at https://github.com/bnediction/mpbn.

To enhance accuracy of robot state estimation, active sensing (or perception-aware) methods seek trajectories that maximize the information gathered by the sensors. To this aim, one possibility is to seek trajectories that minimize the (estimation error) covariance matrix output by an extended Kalman filter (EKF), w.r.t. its control inputs over a given horizon. However, this is computationally demanding. In this article, we derive novel backpropagation analytical formulas for the derivatives of the covariance matrices of an EKF w.r.t. all its inputs. We then leverage the obtained analytical gradients as an enabling technology to derive perception-aware optimal motion plans. Simulations validate the approach, showcasing improvements in execution time, notably over PyTorch's automatic differentiation. Experimental results on a real vehicle also support the method., Comment: Submitted at IORS 2024

We used a dataset of daily Bloomberg Financial Market Summaries from 2010 to 2023, reposted on large financial media, to determine how global news headlines may affect stock market movements using ChatGPT and a two-stage prompt approach. We document a statistically significant positive correlation between the sentiment score and future equity market returns over short to medium term, which reverts to a negative correlation over longer horizons. Validation of this correlation pattern across multiple equity markets indicates its robustness across equity regions and resilience to non-linearity, evidenced by comparison of Pearson and Spearman correlations. Finally, we provide an estimate of the optimal horizon that strikes a balance between reactivity to new information and correlation.

We developed the theory of deterministic ideals and present a systematic study of the pseudo-intersection property with respect to an ideal introduced in \cite{TomNatasha2}. We apply this theory to prove that for any two ultrafilters $U,V$ on $\omega$, $U\cdot V\equiv_T V\cdot U$. Additionally, we analyze the class of ultrafilters which are Tukey above $\omega^\omega$. Our theory applies the study of the Tukey types of a general sum of ultrafilters, which, as evidenced by the results of this paper, can be quite complex. Finally, we introduce the hierarchy of $\alpha$-almost rapid ultrafilters. We prove that it is consistent for them to form a strictly wider class than the rapid ultrafilters, and give an example of a non-rapid $p$-point which is Tukey above $\omega^\omega$. This answers several questions from previous papers on the subject.

This paper provides the mathematical expressions, formulated in classical trigonometric terms, that are required (i) to compute an animal's body orientations and rotations in 3D space from data acquired at high-frequency by on-board accelerometers, magnetometers and gyrometers, (ii) to relate 3D rotations to changes in 3D orientation, (iii) to represent their spherical distributions through kernel density estimation (KDE), and (iv) to reconstruct fine-scale movements. The way the huge amount of data that is acquired by these on-board devices can be more easily managed is also considered., Comment: 26 pages, 6 figures, 3 appendices

Two-dimensional Dirac fermions in HgTe quantum wells close to the topological phase transition can generate significant cyclotron emission that is magnetic field tunable in the Terahertz (THz) frequency range. Due to their relativistic-like dynamics, their cyclotron mass is strongly dependent on their electron concentration in the quantum well, providing a second tunability lever and paving the way for a gate-tunable, permanent-magnet Landau laser. In this work, we demonstrate the proof-of-concept of such a back-gate tunable THz cyclotron emitter at fixed magnetic field. The emission frequency detected at 1.5 Tesla is centered on 2.2 THz and can already be electrically tuned over 250 GHz. With an optimized gate and a realistic permanent magnet of 1.0 Tesla, we estimate that the cyclotron emission could be continuously and rapidly tunable by the gate bias between 1 and 3 THz, that is to say on the less covered part of the THz gap., Comment: 6 pages, 4 figures

We demonstrate that the technology of Radin forcing can be used to transfer compactness properties at a weakly inaccessible but not strong limit cardinal to a strongly inaccessible cardinal. As an application, relative to the existence of large cardinals, we construct a model of set theory in which there is a cardinal $\kappa$ that is $n$-$d$-stationary for all $n\in \omega$ but not weakly compact. This is in sharp contrast to the situation in the constructible universe $L$, where $\kappa$ being $(n+1)$-$d$-stationary is equivalent to $\kappa$ being $\mathbf{\Pi}^1_n$-indescribable. We also show that it is consistent that there is a cardinal $\kappa\leq 2^\omega$ such that $P_\kappa(\lambda)$ is $n$-stationary for all $\lambda\geq \kappa$ and $n\in \omega$, answering a question of Sakai., Comment: Accepted version

We continue the study of the Galvin property. In particular, we deepen the connection between certain diamond-like principles and non-Galvin ultrafilters. We also show that any Dodd sound ultrafilter that is not a $p$-point is non-Galvin. We use these ideas to formulate an essentially optimal large cardinal hypothesis that ensures the existence of a non-Galvin ultrafilter, improving on results of Benhamou and Dobrinen. Finally, we use a strengthening of the Ultrapower Axiom to prove that in all the known canonical inner models, a $\kappa$-complete ultrafilter on $\kappa$ has the Galvin property if and only if it is an iterated sum of $p$-points., Comment: Added references and attributions, reorganized the proof of the main theorem, no new ideas

This article presents a comprehensive overview of the digital twin technology and its capability levels, with a specific focus on its applications in the wind energy industry. It consolidates the definitions of digital twin and its capability levels on a scale from 0-5; 0-standalone, 1-descriptive, 2-diagnostic, 3-predictive, 4-prescriptive, 5-autonomous. It then, from an industrial perspective, identifies the current state of the art and research needs in the wind energy sector. The article proposes approaches to the identified challenges from the perspective of research institutes and offers a set of recommendations for diverse stakeholders to facilitate the acceptance of the technology. The contribution of this article lies in its synthesis of the current state of knowledge and its identification of future research needs and challenges from an industry perspective, ultimately providing a roadmap for future research and development in the field of digital twin and its applications in the wind energy industry.

We develop the theory of cofinal types of ultrafilters over measurable cardinals and establish its connections to Galvin's property. We generalize fundamental results from the countable to the uncountable, but often in surprisingly strengthened forms, and present models with varying structures of the cofinal types of ultrafilters over measurable cardinals., Comment: Accepted version

We obtain a small ultrafilter number at $\aleph_{\omega_1}$. Moreover, we develop a version of the overlapping strong extender forcing with collapses which can keep the top cardinal $\kappa$ inaccessible. We apply this forcing to construct a model where $\kappa$ is the least inaccessible and $V_\kappa$ is a model of GCH at regulars, failures of SCH at singulars, and the ultrafilter numbers at all singulars are small.

We improve Galvin's Theorem for ultrafilters which are p-point limits of p-points. This implies that in all the canonical inner models up to a superstrong cardinal, every kappa-complete ultrafilter over a measurable cardinal kappa satisfies the Galvin property. On the other hand, we prove that supercompact cardinals always carry non-Galvin kappa-complete ultrafilters. Finally, we prove that diamond_kappa implies the existence of a kappa-complete filter which extends the club filter and fails to satisfy the Galvin property. This answers questions Gitik, Shelah, Garti and the author.

Objective. In neuroscience, time-frequency analysis has been used to get insight into brain rhythms from brain recordings. In event-related protocols, one applies it to investigate how the brain responds to a stimulation repeated over many trials. In this framework, three measures have been considered: the amplitude of the transform for each single trial averaged across trials, avgAMP; inter-trial phase coherence, ITC; and the power of the evoked potential transform, POWavg. These three measures are sensitive to different aspects of event-related responses, ITC and POWavg sharing a common sensitivity to phase resetting phenomena. Methods. In the present manuscript, we further investigated the connection between ITC and POWavg using theoretical calculations, a simulation study and analysis of experimental data. Results. We derived exact expressions for the relationship between POWavg and ITC in the particular case of the S-transform of an oscillatory signal. In the more general case, we showed that POWavg and ITC are connected through a relationship that roughly reads $\mathrm{POWavg} \approx \mathrm{avgAMP}^2 \times \mathrm{ITC}^2$. This result was confirmed on simulations. We finally compared the theoretical prediction with results from real data. Conclusion. We showed that POWavg and ITC are related through an approximate, simple relationship that also involves avgAMP. Significance. The presented relationship between POWavg, ITC, and avgAMP confirms previous empirical evidence and provides a novel perspective to investigate evoked brain rhythms. It may provide a significant refinement to the neuroscientific toolbox for studying evoked oscillations.

We address the question of the consistency strength of certain filters and ultrafilters which fail to satisfy the Galvin property. We answer questions \cite[Questions 7.8,7.9]{TomMotiII}, \cite[Question 5]{NegGalSing} and improve theorem \cite[Theorem 2.3]{NegGalSing}.