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In this last part of the series we prove that the slow (inverse logarithmic) decay in time of solutions to the linearised Einstein equations on Schwarzschild-Anti-de Sitter backgrounds obtained in~\cite{Gra.Hol24,Gra.Hol24a} is in fact optimal by constructing quasimode solutions for the Teukolsky system. The main difficulties compared with the case of the scalar wave equation treated in earlier works arise from the first order terms in the Teukolsky equation, the coupling of the Teukolsky quantities at the conformal boundary and ensuring that the relevant quasimode solutions satisfy the Teukolsky-Starobinsky relations. The proof invokes a quasimode construction for the corresponding Regge-Wheeler system (which can be fully decoupled at the expense of a higher order boundary condition) and a reverse Chandrasekhar transformation which generates solutions of the Teukolsky system from solutions of the Regge-Wheeler system. Finally, we provide a general discussion of the well-posedness theory for the higher order boundary conditions that typically appear in the process of decoupling., Comment: 37 pages, 2 figures

Within the Milky Way (MW), younger stellar populations exhibit steeper (more negative) metallicity radial gradients; the origin of this trend remains debated. The FIRE-2 cosmological simulations of MW-mass galaxies show the same trend as the MW, which in FIRE-2 arises because the metallicity gradient of the interstellar medium (ISM), and thus of stars at birth, became steeper over time. We seek to understand this evolution in the context of inside-out radial growth of galaxies. Most FIRE-2 galaxies grew radially inside-out in both gas and stars; specifically, their surface density profiles, $\Sigma(R)$, became shallower over time. Combined with a realized superlinear (Kennicutt-Schmidt-like) relation between star formation and total gas density, the profile of the ratio $\Sigma_{\rm star}(R)/\Sigma_{\rm gas}(R)$ became shallower (flatter) over time. Thus, if metals stayed where they were injected into the ISM from stars, the metallicity gradient would become shallower over time, as some models predict. However, metallicity gradients in FIRE-2 became steeper over time, because of the additional effects of (radial) mixing of metals in the ISM. Specifically, the velocity dispersion and net radial advection of gas declined over time, as ISM turbulence decreased and the disk settled, leading to upside-down vertical growth. In FIRE-2, this evolution in metal mixing of gas associated with upside-down growth dominates over inside-out radial growth, causing the metallicity radial gradient of the ISM and of stars at birth to become steeper over time. We argue that this reflects the ISM history of the MW and of typical MW-mass galaxies., Comment: 22 pages, submitted to ApJ

$FeCr_2S_4$ is a ferrimagnet with two oppositely-ordered spin sublattices (Fe and Cr), connected via superexchange interaction, giving a non-zero net magnetic moment. We show how the magnetic dynamics of the sublattices can be selectively manipulated by resonantly perturbing the Fe sublattice using ultrashort laser pulses. The mid-infrared excitation through intra-atomic Fe $d-d$ transitions triggers a markedly slower magneto-optical Kerr effect dynamics compared to an off-resonant pumping affecting both the two sublattices simultaneously. The analysis and conclusions are supported by probing resonantly and off-resonantly to the Fe sublattice., Comment: 29 pages, 19 figures

Humanitarian organizations distribute aid to people affected by armed conflicts or natural disasters. Digitalization has the potential to increase the efficiency and fairness of aid-distribution systems, and recent work by Wang et al. has shown that these benefits are possible without creating privacy harms for aid recipients. However, their work only provides a solution for one particular aid-distribution scenario in which aid recipients receive a pre-defined set of goods. Yet, in many situations it is desirable to enable recipients to decide which items they need at each moment to satisfy their specific needs. We formalize these needs into functional, deployment, security, and privacy requirements, and design a privacy-preserving digital wallet for aid distribution. Our smart-card-based solution enables aid recipients to spend a pre-defined budget at different vendors to obtain the items that they need. We prove our solution's security and privacy properties, and show it is practical at scale.

Bulk-edge correspondence is a wide-ranging principle that applies to topological matter, as well as a precise result established in a large and growing number of cases. According to the principle, the distinctive topological properties of matter, thought of as extending indefinitely in space, are equivalently reflected in the excitations running along its boundary, when one is present. Indices encode those properties, and their values, when differing, are witness to a violation of that correspondence. We address such violations, as they are encountered in a hydrodynamic context. The model concerns a shallow layer of fluid in a rotating frame and provides a local description of waves propagating either across the oceans or along a coastline; it becomes topological when suitably modified at short distances. The edge index is sensitive to boundary conditions, as exemplified in earlier work, hence exhibiting a violation. Here we present classification of all (local, self-adjoint) boundary conditions and a parameterization of their manifold. They come in four families, distinguished in part by the degree of their underlying differential operators. Essentially, that degree counts the degrees of freedom of the hydrodynamic field that are constrained at the boundary by way of their normal derivatives. Generally, both the correspondence and its violation are typical. Within families though, the maximally possible amount of violation is increasing with its degree. Several indices of interest are charted for all boundary conditions. A single spectral mechanism for the onset of violations is furthermore identified. The role of a symmetry is investigated., Comment: Setup and main results: pp. 1-14; Details of the setup and proofs: pp. 15-57; Appendices: pp. 57-78. Eleven Figures

A quantum eigenstate of a classically chaotic system is referred as scarred by an unstable periodic orbit if its probability density is concentrated in the vicinity of that orbit. Recently, a new class of scarring - variational scarring - was discovered in numerical studies of disordered quantum dots, arising from near-degeneracies in the quantum spectrum associated with classical resonances of the unperturbed system. Despite the increasing body of theoretical evidence on variational scarring, its experimental observation has remained out of reach. Motivated by this dearth, we argue and demonstrate that variational scarring can occur in an elliptical quantum dot fabricated on monolayer graphene, and locally perturbed by a nanotip. Then, we further show that the fingerprint of these variational scars can potentially be detected via scanning tunneling microscopy, thus offering an attractive experimental pathway for the first validation of this puzzling quantum-chaotic phenomenon.

Given a complex-projective klt pair $(X, \Delta)$ with standard coefficients and such that $K_X + \Delta$ is ample, we determine necessary and sufficient conditions for the pair $(X, \Delta)$ to be uniformized by a bounded symmetric domain. As an application, we obtain characterizations of orbifold quotients of the polydisc and of the four classical irreducible bounded symmetric domains in terms of Miyaoka-Yau-type Chern equalities.

Deep learning has made significant strides in medical imaging, leveraging the use of large datasets to improve diagnostics and prognostics. However, large datasets often come with inherent errors through subject selection and acquisition. In this paper, we investigate the use of Diffusion Autoencoder (DAE) embeddings for uncovering and understanding data characteristics and biases, including biases for protected variables like sex and data abnormalities indicative of unwanted protocol variations. We use sagittal T2-weighted magnetic resonance (MR) images of the neck, chest, and lumbar region from 11186 German National Cohort (NAKO) participants. We compare DAE embeddings with existing generative models like StyleGAN and Variational Autoencoder. Evaluations on a large-scale dataset consisting of sagittal T2-weighted MR images of three spine regions show that DAE embeddings effectively separate protected variables such as sex and age. Furthermore, we used t-SNE visualization to identify unwanted variations in imaging protocols, revealing differences in head positioning. Our embedding can identify samples where a sex predictor will have issues learning the correct sex. Our findings highlight the potential of using advanced embedding techniques like DAEs to detect data quality issues and biases in medical imaging datasets. Identifying such hidden relations can enhance the reliability and fairness of deep learning models in healthcare applications, ultimately improving patient care and outcomes., Comment: This paper was accepted in the "Workshop on Interpretability of Machine Intelligence in Medical Image Computing" (iMIMIC) at MICCAI 2024

The current research evaluates user experience and preference when interacting with a patient-reported outcome measure (PROM) healthcare application displayed on a single tablet in comparison to interaction with the same application distributed across two tablets. We conducted a within-subject user study with 43 participants who engaged with and rated the usability of our system and participated in a post-experiment interview to collect subjective data. Our findings showed significantly higher usability and higher pragmatic quality ratings for the single tablet condition. However, some users attribute a higher level of presence to the avatar and prefer it to be placed on a second tablet., Comment: In 30th ACM Symposium on Virtual Reality Software and Technology (VRST 2024)

We experimentally determine the bounds of the magnetic-field-induced superconducting and magnetic phases near the crystalline $b$ axis of uranium ditelluride (UTe$_2$). By measuring the magnetoresistance as a function of rotation angle and field strength in magnetic fields as large as 41.5 T, we have studied these boundaries in three dimensions of magnetic field direction. The phase boundaries in all cases obey crystallographic symmetries and no additional symmetries, evidence against any symmetry-breaking quadrupolar or higher magnetic order. We find that the upper critical field of the zero-field superconducting state is well-described by an anisotropic mass model. In contrast, the angular boundaries of the $b$-axis-oriented field-reentrant superconducting phase are nearly constant as a function of field up to the metamagnetic transition, with anisotropy between the $ab$ and $bc$ planes that is comparable to the angular anisotropy of the metamagnetic transition itself. We discuss the relationship between the observed superconducting boundaries and the underlying $\mathbf{d}$ vector that represents the spin-triplet order parameter. Additionally, we report an unexplained normal-state feature in resistance and track its evolution as a function of field strength and angle., Comment: 17 pages, 16 figures

We show that strong interactions violating the conservation of lepton numbers in the neutrino sector could significantly alter the standard low entropy picture for the pre-supernova collapsing core of a massive star. A rapid neutrino-antineutrino equilibration leads to entropy generation and enhanced electron capture and, hence, a lower electron fraction than in the standard model. This would affect the downstream core evolution, the prospects for a supernova explosion, and the emergent neutrino signal. If realized by lepton-number-violating neutrino self-interactions (LNV $\nu$SI), the relevant mediator mass and coupling ranges can be probed by future accelerator-based experiments., Comment: 5+8 pages, 2+5 figures. Comments are welcome!

In magnetic pyrochlore materials, the interplay of spin-orbit coupling, electronic correlations, and geometrical frustration gives rise to exotic quantum phases, including topological semimetals and spin ice. While these phases have been observed in isolation, the interface-driven phenomena emerging from their interaction have never been realized previously. Here, we report on the discovery of interfacial electronic anisotropy and rotational symmetry breaking at a heterostructure consisting of the Weyl semimetal Eu2Ir2O7 and spin ice Dy2Ti2O7. Subjected to magnetic fields, we unveil a six-fold anisotropic transport response that is theoretically accounted by a Kondo-coupled heterointerface, where the spin ice's field-tuned magnetism induces electron scattering in the Weyl semimetal's topological Fermi-arc states. Furthermore, at elevated magnetic fields, we reveal a two-fold anisotropic response indicative of a new symmetry-broken many-body state. This discovery showcases the nascent potential of complex quantum architectures in search of emergent phenomena unreachable in bulk crystals.

Starting from the proof of the $C^0$-inextendibility of Schwarzschild by Sbierski, the past decade has seen renewed interest in showing low-regularity inextendibility for known spacetime models. Specifically, a lot of attention has been paid to FLRW spacetimes and there is an ever growing array of results in the literature. Apart from hoping to provide a concise summary of the state of the art we present an extension of work by Galloway and Ling on $C^0$-inextendibility of certain FLRW spacetimes within a subclass of spherically symmetric spacetimes, to $C^0$-inextendibility within a subclass of axisymmetric spacetimes. Notably our result works in the case of flat FLRW spacetimes with $a(t)\to 0$ for $t\to 0^+$, a setting where other known $C^0$-inextendibility results for FLRW spacetimes due to Sbierski do not apply.

Stochastic effects significantly influence the dynamics of traffic flows. Many dynamic traffic assignment (DTA) models attempt to capture these effects by prescribing a specific ratio that determines how flow splits across different routes based on the routes' costs. In this paper, we propose a new framework for DTA that incorporates the interplay between the routing decisions of each single traffic participant, the stochastic nature of predicting the future state of the network, and the physical flow dynamics. Our framework consists of an edge loading operator modeling the physical flow propagation and a routing operator modeling the routing behavior of traffic participants. The routing operator is assumed to be set-valued and capable to model complex (deterministic) equilibrium conditions as well as stochastic equilibrium conditions assuming that measurements for predicting traffic are noisy. As our main results, we derive several quite general equilibrium existence and uniqueness results which not only subsume known results from the literature but also lead to new results. Specifically, for the new stochastic prediction equilibrium, we show existence and uniqueness under natural assumptions on the probability distribution over the predictions., Comment: 34 pages, 2 figures

Quantum scars refer to eigenstates with enhanced probability density along unstable classical periodic orbits (POs). First predicted 40 years ago, scars are special eigenstates that counterintuitively defy ergodicity in quantum systems whose classical counterpart is chaotic. Despite the importance and long history of scars, their direct visualization in quantum systems remains an open field. Here we demonstrate that, by using an in-situ graphene quantum dot (GQD) creation and wavefunction mapping technique, quantum scars are imaged for Dirac electrons with nanometer spatial resolution and meV energy resolution with a scanning tunneling microscope. Specifically, we find enhanced probability densities in the form of lemniscate-shaped and streak-like patterns within our stadium-shaped GQDs. Both features show equal energy interval recurrence, consistent with predictions for relativistic quantum scars. By combining classical and quantum simulations, we demonstrate that the observed patterns correspond to two unstable POs that exist in our stadium-shaped GQD, thus proving they are both quantum scars. In addition to providing the first unequivocal visual evidence of quantum scarring, our work offers insight into the quantum-classical correspondence in relativistic chaotic quantum systems and paves the way to experimental investigation of other recently proposed scarring species such as perturbation-induced scars, chiral scars, and antiscarring.

Noncentrosymmetric 2D superconductors with large spin-orbit coupling offer an opportunity to explore superconducting behaviors far beyond the Pauli limit. One such superconductor, few-layer T$_d$-MoTe$_2$, has large upper critical fields that can exceed the Pauli limit by up to 600%. However, the mechanisms governing this enhancement are still under debate, with theory pointing towards either spin-orbit parity coupling or tilted Ising spin-orbit coupling. Moreover, ferroelectricity concomitant with superconductivity has been recently observed in the bilayer, where strong changes to superconductivity can be observed throughout the ferroelectric transition pathway. Here, we report the superconducting behavior of bilayer T$_d$-MoTe$ _2$ under an in-plane magnetic field, while systematically varying magnetic field angle and out-of-plane electric field strength. We find that superconductivity in bilayer MoTe$_2$ exhibits a two-fold symmetry with an upper critical field maxima occurring along the b-axis and minima along the a-axis. The two-fold rotational symmetry remains robust throughout the entire superconducting region and ferroelectric hysteresis loop. Our experimental observations of the spin-orbit coupling strength (up to 16.4 meV) agree with the spin texture and spin splitting from first-principles calculations, indicating that tilted Ising spin-orbit coupling is the dominant underlying mechanism.

Using the FIRE-2 cosmological zoom-in simulations, we investigate the temporal evolution of gas-phase metallicity radial gradients of Milky Way-mass progenitors in the redshift range of $0.4

We present the Wavefront Sensor units of the Gravity Plus Adaptive Optics (GPAO) system, which will equip all 8m class telescopes of the VLTI and is an instrumental part of the GRAVITY+ project. It includes two modules for each Wavefront Sensor unit: a Natural Guide Star sensor with high-order 40x40 Shack-Hartmann and a Laser Guide Star 30x30 sensor. The state-of-the-art AO correction will considerably improve the performance for interferometry, in particular high-contrast observations for NGS observations and all-sky coverage with LGS, which will be implemented for the first time on VLTI instruments. In the following, we give an overview of the Wavefront Sensor units system after completion of their integration and characterization., Comment: Optical and Infrared Interferometry and Imaging IX

Schur functions have been shown to satisfy certain stability properties and recurrence relations. In this paper, we prove analogs of these properties with Schur's $Q$-functions using vertex operator methods., Comment: 21 pages

Motivated by crowdsourcing, we consider a problem where we partially observe the correctness of the answers of $n$ experts on $d$ questions. In this paper, we assume that both the experts and the questions can be ordered, namely that the matrix $M$ containing the probability that expert $i$ answers correctly to question $j$ is bi-isotonic up to a permutation of it rows and columns. When $n=d$, this also encompasses the strongly stochastic transitive (SST) model from the tournament literature. Here, we focus on the relevant problem of deciphering small entries of $M$ from large entries of $M$, which is key in crowdsourcing for efficient allocation of workers to questions. More precisely, we aim at recovering a (or several) level set $p$ of the matrix up to a precision $h$, namely recovering resp. the sets of positions $(i,j)$ in $M$ such that $M_{ij}>p+h$ and $M_{i,j}

The Thouless theory of quantum pumps establishes the conditions for quantized particle transport per cycle, and determines its value. When describing the pump from a moving reference frame, transported and existing charges transform, though not independently. This transformation is inherent to Galilean space and time, but it is underpinned by a transformation of vector bundles. Different formalisms can be used to describe this transformation, including one based on Bloch theory. Depending on the chosen formalism, the two types of charges will be realized as indices of either the same or different kinds. Finally, we apply the bulk-edge correspondence principle, so as to implement the transformation law within B\"uttiker's scattering theory of quantum pumps., Comment: 23 pages, 2 figures

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view spectrum and segmentation maps. This extension enhances the representation of scenes with multiple spectra, providing insights into the underlying materials and segmentation. We introduce an improved physically-based rendering approach for Gaussian splats, estimating reflectance and lights per spectra, thereby enhancing accuracy and realism. In a comprehensive quantitative and qualitative evaluation, we demonstrate the superior performance of our approach with respect to other recent learning-based spectral scene representation approaches (i.e., XNeRF and SpectralNeRF) as well as other non-spectral state-of-the-art learning-based approaches. Our work also demonstrates the potential of spectral scene understanding for precise scene editing techniques like style transfer, inpainting, and removal. Thereby, our contributions address challenges in multi-spectral scene representation, rendering, and editing, offering new possibilities for diverse applications.

Pd$_3$Bi$_2$Se$_2$ is a rare realization of a superconducting metal with a non-zero $Z_2$ topological invariant. We report the growth of high-quality single crystals of layered Pd$_3$Bi$_2$Se$_2$ with a superconducting transition at $T_c$ ~ 0.80 K and upper critical fields of ~10 mT and ~5 mT for the in-plane and out-of-plane directions, respectively. Our density functional theory (DFT) calculations reveal three pairs of doubly degenerate bands crossing the Fermi level, all displaying clear three-dimensional dispersion consistent with the overall low electronic anisotropy (<2). The multiband electronic nature of Pd$_3$Bi$_2$Se$_2$ is evident in magneto-transport measurements, yielding a sign-changing Hall resistivity at low temperatures. The magnetoresistance is non-saturating and follows Kohler's scaling rule. We interpret the magneto-transport data in terms of open orbits that are revealed in the DFT-calculated Fermi surface. de Haas-van Alphen (dHvA) oscillation measurements using torque magnetometry on single crystals yield four frequencies for out-of-plane fields: $F_\alpha = (150 \pm 26)$T, $F_\beta = (293 \pm 10)$T, $F_\gamma = (375 \pm 20)$T, and $F_\eta = (1017 \pm 12)$T, with the low frequency dominating the spectrum. Through the measurement of angular dependent dHvA oscillations and DFT calculations, we identify the $F_\alpha$ frequency with an approximately ellipsoidal electron pocket centered on the $L_2$ point of the Brillouin zone. Lifshitz-Kosevich analysis of the dHvA oscillations reveals a small cyclotron effective mass: $m^* = (0.11 \pm 0.02) m_0$ and a nontrivial Berry phase for the dominant orbit. The presence of nontrivial topology in a bulk superconductor positions Pd$_3$Bi$_2$Se$_2$ as a potential candidate for exploring topological superconductivity., Comment: 30 pages, 5 figures

Accurate calibration of finite element (FE) models of human intervertebral discs (IVDs) is essential for their reliability and application in diagnosing and planning treatments for spinal conditions. Traditional calibration methods are computationally intensive, requiring iterative, derivative-free optimization algorithms that often take hours or days to converge. This study addresses these challenges by introducing a novel, efficient, and effective calibration method for an L4-L5 IVD FE model using a neural network (NN) surrogate. The NN surrogate predicts simulation outcomes with high accuracy, outperforming other machine learning models, and significantly reduces the computational cost associated with traditional FE simulations. Next, a Projected Gradient Descent (PGD) approach guided by gradients of the NN surrogate is proposed to efficiently calibrate FE models. Our method explicitly enforces feasibility with a projection step, thus maintaining material bounds throughout the optimization process. The proposed method is evaluated against state-of-the-art Genetic Algorithm (GA) and inverse model baselines on synthetic and in vitro experimental datasets. Our approach demonstrates superior performance on synthetic data, achieving a Mean Absolute Error (MAE) of 0.06 compared to the baselines' MAE of 0.18 and 0.54, respectively. On experimental specimens, our method outperforms the baseline in 5 out of 6 cases. Most importantly, our approach reduces calibration time to under three seconds, compared to up to 8 days per sample required by traditional calibration. Such efficiency paves the way for applying more complex FE models, enabling accurate patient-specific simulations and advancing spinal treatment planning., Comment: Under submission. Project code: https://github.com/matanat/IVD-CalibNN/

We demonstrate that the most popular variants of all common algebraic multidimensional rootfinding algorithms are unstable by analyzing the conditioning of subproblems that are constructed at intermediate steps. In particular, we give multidimensional polynomial systems for which the conditioning of a subproblem can be worse than the conditioning of the original problem by a factor that grows exponentially with the number of variables.

This is the main paper of a series establishing the linear stability of Schwarzschild-Anti-de Sitter (AdS) black holes to gravitational perturbations. Specifically, we prove that solutions to the linearisation of the Einstein equations $\textrm{Ric}(g) = \Lambda g$ with $\Lambda<0$ around a Schwarzschild-AdS metric arising from regular initial data and with standard Dirichlet-type boundary conditions imposed at the conformal boundary (inherited from fixing the conformal class of the non-linear metric) remain globally uniformly bounded on the black hole exterior and in fact decay inverse logarithmically in time to a linearised Kerr-AdS metric. The proof exploits a hierarchical structure of the equations of linearised gravity in double null gauge and crucially relies on boundedness and logarithmic decay results for the Teukolsky system, which are independent results proven in Part II of the series. Contrary to the asymptotically flat case, addition of a residual pure gauge solution to the original solution is not required to prove decay of all linearised null curvature and Ricci coefficients. One may however normalise the solution at the conformal boundary to be in standard AdS-form by adding such a pure gauge solution, which is constructed dynamically from the trace of the original solution at the conformal boundary and quantitatively controlled by initial data.

We prove boundedness and inverse logarithmic decay in time of solutions to the Teukolsky equations on Schwarzschild-Anti-de Sitter backgrounds with standard boundary conditions originating from fixing the conformal class of the non-linear metric on the boundary. The proofs rely on (1) a physical space transformation theory between the Teukolsky equations and the Regge-Wheeler equations on Schwarzschild-Anti de Sitter backgrounds and (2) novel energy and Carleman estimates handling the coupling of the two Teukolsky equations through the boundary conditions thereby generalising earlier work of \cite{Hol.Smu13} for the covariant wave equation. Specifically, we also produce purely physical space Carleman estimates.

Counterfactual explanations (CEs) aim to enhance the interpretability of machine learning models by illustrating how alterations in input features would affect the resulting predictions. Common CE approaches require an additional model and are typically constrained to binary counterfactuals. In contrast, we propose a novel method that operates directly on the latent space of a generative model, specifically a Diffusion Autoencoder (DAE). This approach offers inherent interpretability by enabling the generation of CEs and the continuous visualization of the model's internal representation across decision boundaries. Our method leverages the DAE's ability to encode images into a semantically rich latent space in an unsupervised manner, eliminating the need for labeled data or separate feature extraction models. We show that these latent representations are helpful for medical condition classification and the ordinal regression of severity pathologies, such as vertebral compression fractures (VCF) and diabetic retinopathy (DR). Beyond binary CEs, our method supports the visualization of ordinal CEs using a linear model, providing deeper insights into the model's decision-making process and enhancing interpretability. Experiments across various medical imaging datasets demonstrate the method's advantages in interpretability and versatility. The linear manifold of the DAE's latent space allows for meaningful interpolation and manipulation, making it a powerful tool for exploring medical image properties. Our code is available at https://doi.org/10.5281/zenodo.13859266., Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2024:024. arXiv admin note: text overlap with arXiv:2303.12031

We study the perfect transfer of information in 1+1D continuous quantum systems. This includes effective descriptions of inhomogeneous spin chains, for which the notion of perfect state transfer in quantum information was introduced, and here phrased in terms of waves. We show that reflection symmetry is necessary for perfect wave transfer (PWT) in any inhomogeneous conformal field theory, and even sufficient when restricted to one-particle excitations. To determine if or when it is sufficient more generally, we first break conformal invariance and study a broad class of 1+1D bosonic theories. We show that the question can then be posed as an inverse Sturm-Liouville problem that determines when the bosonic theory exhibits PWT. We demonstrate how to uniquely solve this problem, which also shows that reflection symmetry is sufficient for the special case with conformal invariance. Using bosonization, our continuum results extend these notions to interacting quantum field theories., Comment: 7 pages + SM, RevTeX, 2 figures

Ferroelectrics under suitable electric boundary conditions can present a negative capacitance response, whereby the total voltage drop across the ferroelectric opposes the externally applied bias. When the ferroelectric is in a heterostructure, this behavior yields a voltage amplification in the other elements, an effect that could be leveraged in low-power electronic devices. Interestingly, the mentioned voltage amplification should have an accompanying elastic effect. Specifically, in the typical case that the materials in contact with the ferroelectric are non-polar dielectrics, those should present an enhanced electrostrictive response. Here we use atomistic simulations - of model PbTiO$_{3}$/SrTiO$_{3}$ ferroelectric/dielectric superlattices displaying negative capacitance - to show that this is indeed the case: we reveal the enhanced elastic response of the dielectric layer and show that it is clearly linked to the voltage amplification. We argue that this "elastic amplification" could serve as a convenient experimental fingerprint for negative capacitance. Further, we propose that it may have interest on its own, e.g. for the development of low-power electromechanical actuators.

Sound produces surface waves along the cochlea's basilar membrane. To achieve the ear's astonishing frequency resolution and sensitivity to faint sounds, dissipation in the cochlea must be canceled via active processes in hair cells, effectively bringing the cochlea to the edge of instability. But how can the cochlea be globally tuned to the edge of instability with only local feedback? To address this question, we use a discretized version of a standard model of basilar membrane dynamics, but with an explicit contribution from active processes in hair cells. Surprisingly, we find the basilar membrane supports two qualitatively distinct sets of modes: a continuum of localized modes and a small number of collective extended modes. Localized modes sharply peak at their resonant position and are largely uncoupled. As a result, they can be amplified almost independently from each other by local hair cells via feedback reminiscent of self-organized criticality. However, this amplification can destabilize the collective extended modes; avoiding such instabilities places limits on possible molecular mechanisms for active feedback in hair cells. Our work illuminates how and under what conditions individual hair cells can collectively create a critical cochlea., Comment: 9 pages, 6 figures

Superconductivity of iron chalocogenides is strongly enhanced under applied pressure yet its underlying pairing mechanism remains elusive. Here, we present a quantum oscillations study up to 45 T in the high-$T_c$ phase of tetragonal FeSe$_{0.82}$S$_{0.18}$ up to 22 kbar. Under applied pressure, the quasi-two dimensional multiband Fermi surface expands and the effective masses remain large, whereas the superconductivity displays a three-fold enhancement. Comparing with chemical pressure tuning of FeSe$_{1-x}$S$_x$, the Fermi surface enlarges in a similar manner but the effective masses and $T_c$ are suppressed. These differences may be attributed to the changes in the density of states influenced by the chalcogen height, which could promote stronger spin fluctuations pairing under pressure. Furthermore, our study also reveals unusual scattering and broadening of superconducting transitions in the high-pressure phase, indicating the presence of a complex pairing mechanism., Comment: 22 pages, 17 figures

The famous edge flow decomposition theorem of Gallai (1958) states that any static edge $s$,$d$-flow in a directed graph can be decomposed into a linear combination of incidence vectors of paths and cycles. In this paper, we study the decomposition problem for the setting of dynamic edge $s$,$d$-flows assuming a quite general dynamic flow propagation model. We prove the following decomposition theorem: For any dynamic edge $s$,$d$-flow with finite support, there exists a decomposition into a linear combination of $s$,$d$-walk inflows and circulations, i.e. edge flows that circulate along cycles with zero transit time. We show that a variant of the classical algorithmic approach of iteratively subtracting walk inflows from the current dynamic edge flow converges to a dynamic circulation. The algorithm terminates in finite time, if there is a lower bound on the minimum edge travel times. We further characterize those dynamic edge flows which can be decomposed purely into linear combinations of $s$,$d$-walk inflows. The proofs rely on the new concept of parameterized network loadings which describe how particles of a different walk flow would hypothetically propagate throughout the network under the fixed travel times induced by the given edge flow. We show several technical properties of this type of network loading and as a byproduct we also derive some general results on dynamic flows which could be of interest outside the context of this paper as well., Comment: 54 pages, 3 figures

Magnetotransport, the response of electrical conduction to external magnetic field, acts as an important tool to reveal fundamental concepts behind exotic phenomena and plays a key role in enabling spintronic applications. Magnetotransport is generally sensitive to magnetic field orientations. In contrast, efficient and isotropic modulation of electronic transport, which is useful in technology applications such as omnidirectional sensing, is rarely seen, especially for pristine crystals. Here we propose a strategy to realize extremely strong modulation of electron conduction by magnetic field which is independent of field direction. GdPS, a layered antiferromagnetic semiconductor with resistivity anisotropies, supports a field-driven insulator-to-metal transition with a paradoxically isotropic gigantic negative magnetoresistance insensitive to magnetic field orientations. This isotropic magnetoresistance originates from the combined effects of a near-zero spin-orbit coupling of Gd3+-based half-filling f-electron system and the strong on-site f-d exchange coupling in Gd atoms. Our results not only provide a novel material system with extraordinary magnetotransport that offers a missing block for antiferromagnet-based ultrafast and efficient spintronic devices, but also demonstrate the key ingredients for designing magnetic materials with desired transport properties for advanced functionalities., Comment: 44 pages, 18 figures

High-significance evidences of the existence of a high-energy diffuse flux of cosmic neutrinos have emerged in the last decade from several observations by the IceCube Collaboration. The ANTARES neutrino telescope took data for 15 years in the Mediterranean Sea, from 2007 to 2022, and collected a high-purity all-flavour neutrino sample. The search for a diffuse cosmic neutrino signal using this dataset is presented in this article. This final analysis did not provide a statistically significant observation of the cosmic diffuse flux. However, this is converted into limits on the properties of the cosmic neutrino spectrum. In particular, given the sensitivity of the ANTARES neutrino telescope between 1 and 50 TeV, constraints on single-power-law hypotheses are derived for the cosmic diffuse flux below 20 TeV, especially for power-law fits of the IceCube data with spectral index softer than 2.8.

In this study, a novel material from the rare-earth based breathing pyrochlore family, Ba3Tm2Zn5O11, was successfully synthesized. Powder X-ray diffraction and high-resolution powder neutron diffraction confirmed phase purity and crystal structure, while thermogravimetric analysis revealed incongruent melting behavior compared to its counterpart, Ba3Yb2Zn5O11. High-quality single crystals of Ba3Tm2Zn5O11 were grown using the traveling solvent floating zone technique and assessed using Laue diffractometer and single crystal X-ray diffraction. Thermodynamic characterization indicated paramagnetic behavior down to 0.05 K, and inelastic neutron scattering measurements identified distinct crystal electric field bands. Additional low-energy excitation studies on single crystals revealed dispersionless bands at 0.8 and 1 meV. Computed phonon dispersions from first principles calculations ruled out phonons as the source of these modes, further illustrating the puzzling and unique properties of Ba3Tm2Zn5O11.

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles. Three published neural network-based shower separation models were applied to simulation and experimental data to measure the performance of the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL) technological prototype in distinguishing the energy deposited by a single charged and single neutral hadron for Particle Flow. The performance of models trained using only standard spatial and energy and charged track position information from an event was compared to models trained using timing information available from AHCAL, which is expected to improve sensitivity to shower development and, therefore, aid in clustering. Both simulation and experimental data were used to train and test the models and their performances were compared. The best-performing neural network achieved significantly superior event reconstruction when timing information was utilised in training for the case where the charged hadron had more energy than the neutral one, motivating temporally sensitive calorimeters. All models under test were observed to tend to allocate energy deposited by the more energetic of the two showers to the less energetic one. Similar shower reconstruction performance was observed for a model trained on simulation and applied to data and a model trained and applied to data.

Flattery is an important aspect of human communication that facilitates social bonding, shapes perceptions, and influences behavior through strategic compliments and praise, leveraging the power of speech to build rapport effectively. Its automatic detection can thus enhance the naturalness of human-AI interactions. To meet this need, we present a novel audio textual dataset comprising 20 hours of speech and train machine learning models for automatic flattery detection. In particular, we employ pretrained AST, Wav2Vec2, and Whisper models for the speech modality, and Whisper TTS models combined with a RoBERTa text classifier for the textual modality. Subsequently, we build a multimodal classifier by combining text and audio representations. Evaluation on unseen test data demonstrates promising results, with Unweighted Average Recall scores reaching 82.46% in audio-only experiments, 85.97% in text-only experiments, and 87.16% using a multimodal approach., Comment: Interspeech 2024

We investigate the endofullerene system Ne@C$_{70}$, by constructing a three-dimensional Potential Energy Surface (PES) describing the translational motion of the Ne atom. We compare a plethora of electronic structure methods including: MP2, SCS-MP2, SOS-MP2, RPA@PBE, C(HF)-RPA, which were previously used for He@C$_{60}$ in J. Chem. Phys. 160, 104303 (2024), alongside B86bPBE-25X-XDM and B86bPBE-50X-XDM. The reduction in symmetry moving from C$_{60}$ to C$_{70}$ introduces a double well potential along the anisotropic direction, which forms a test of the sensitivity and effectiveness of the methods. Due to the large cost of these calculations, the PES is interpolated using Gaussian Process Regression due to its effectiveness with sparse training data. The nuclear Hamiltonian is diagonalised using a symmetrised double minimum basis set outlined in J. Chem. Phys. 159, 164308 (2023), with translational energies having error bars $\pm 1$ and $\pm 2$ cm$^{-1}$. We quantify the shape of the ground state wavefunction by considering its prolateness and kurtosis, and compare the eigenfunctions between electronic structure methods from their Hellinger distance. We find no consistency between electronic structure methods as they find a range of barrier heights and minima positions of the double well, and different translational eigenspectra which also differ from the Lennard-Jones (LJ) PES given in J. Chem. Phys. 101, 2126,2140 (1994). We find that generating effective LJ parameters for each electronic structure method cannot reproduce the full PES, nor recreate the eigenstates and this suggests that the LJ form of the PES, while simple, may not be best suited to describe these systems. Even though MP2 and RPA@PBE performed best for He@C$_{60}$, due to the lack of concordance between all electronic structure methods we require more experimental data in order to properly validate the choice., Comment: 12 pages, 4 figures; SI 6 pages, 3 figures

In this work we study the properties of dissipatively stabilized steady states of noisy quantum algorithms, exploring the extent to which they can be well approximated as thermal distributions, and proposing methods to extract the effective temperature T. We study an algorithm called the Relaxational Quantum Eigensolver (RQE), which is one of a family of algorithms that attempt to find ground states and balance error in noisy quantum devices. In RQE, we weakly couple a second register of auxiliary "shadow" qubits to the primary system in Trotterized evolution, thus engineering an approximate zero-temperature bath by periodically resetting the auxiliary qubits during the algorithm's runtime. Balancing the infinite temperature bath of random gate error, RQE returns states with an average energy equal to a constant fraction of the ground state. We probe the steady states of this algorithm for a range of base error rates, using several methods for estimating both T and deviations from thermal behavior. In particular, we both confirm that the steady states of these systems are often well-approximated by thermal distributions, and show that the same resources used for cooling can be adopted for thermometry, yielding a fairly reliable measure of the temperature. These methods could be readily implemented in near-term quantum hardware, and for stabilizing and probing Hamiltonians where simulating approximate thermal states is hard for classical computers., Comment: 14 pages, 7 Figures

Taking over arbitrary tasks like humans do with a mobile service robot in open-world settings requires a holistic scene perception for decision-making and high-level control. This paper presents a human-inspired scene perception model to minimize the gap between human and robotic capabilities. The approach takes over fundamental neuroscience concepts, such as a triplet perception split into recognition, knowledge representation, and knowledge interpretation. A recognition system splits the background and foreground to integrate exchangeable image-based object detectors and SLAM, a multi-layer knowledge base represents scene information in a hierarchical structure and offers interfaces for high-level control, and knowledge interpretation methods deploy spatio-temporal scene analysis and perceptual learning for self-adjustment. A single-setting ablation study is used to evaluate the impact of each component on the overall performance for a fetch-and-carry scenario in two simulated and one real-world environment.

Objectives: To present a publicly available torso segmentation network for large epidemiology datasets on volumetric interpolated breath-hold examination (VIBE) images. Materials & Methods: We extracted preliminary segmentations from TotalSegmentator, spine, and body composition networks for VIBE images, then improved them iteratively and retrained a nnUNet network. Using subsets of NAKO (85 subjects) and UK Biobank (16 subjects), we evaluated with Dice-score on a holdout set (12 subjects) and existing organ segmentation approach (1000 subjects), generating 71 semantic segmentation types for VIBE images. We provide an additional network for the vertebra segments 22 individual vertebra types. Results: We achieved an average Dice score of 0.89 +- 0.07 overall 71 segmentation labels. We scored > 0.90 Dice-score on the abdominal organs except for the pancreas with a Dice of 0.70. Conclusion: Our work offers a detailed and refined publicly available full torso segmentation on VIBE images., Comment: https://github.com/robert-graf/TotalVibeSegmentator