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Optically pumped magnetometers (OPMs) are compact and lightweight sensors that can measure magnetic fields generated by current flow in neuronal assemblies in the brain. Such sensors enable construction of magnetoencephalography (MEG) instrumentation, with significant advantages over conventional MEG devices including adaptability to head size, enhanced movement tolerance, lower complexity and improved data quality. However, realising the potential of OPMs depends on our ability to perform system calibration, which means finding sensor locations, orientations, and the relationship between the sensor output and magnetic field (termed sensor gain). Such calibration is complex in OPMMEG since, for example, OPM placement can change from subject to subject (unlike in conventional MEG where sensor locations or orientations are fixed). Here, we present two methods for calibration, both based on generating well-characterised magnetic fields across a sensor array. Our first device (the HALO) is a head mounted system that generates dipole like fields from a set of coils. Our second (the matrix coil (MC)) generates fields using coils embedded in the walls of a magnetically shielded room. Our results show that both methods offer an accurate means to calibrate an OPM array (e.g. sensor locations within 2 mm of the ground truth) and that the calibrations produced by the two methods agree strongly with each other. When applied to data from human MEG experiments, both methods offer improved signal to noise ratio after beamforming suggesting that they give calibration parameters closer to the ground truth than factory settings and presumed physical sensor coordinates and orientations. Both techniques are practical and easy to integrate into real world MEG applications. This advances the field significantly closer to the routine use of OPMs for MEG recording., Comment: 36 pages, 10 figures

Driven-dissipative nonlinear systems exhibit rich critical behavior, related to bifurcation, bistability and switching, which underlie key phenomena in areas ranging from physics, chemistry and biology to social sciences and economics. The importance of rare fluctuations leading to a dramatic jump between two very distinct states, such as survival and extinction in population dynamics, success and bankruptcy in economics and the occurrence of earthquakes or of epileptic seizures, have been already established. In the quantum domain, switching is of importance in both chemical reactions and the devices used in quantum state detection and amplification. In particular, the simplest driven single oscillator model serves as an insightful starting point. Here we describe switching induced by quantum fluctuations and illustrate that an instanton approach within Keldysh field theory can provide a deep insight into such phenomena. We provide a practical recipe to compute the switching rates semi-analytically, which agrees remarkably well with exact solutions across a wide domain of drive amplitudes spanning many orders of magnitude. Being set up in the framework of Keldysh coherent states path integrals, our approach opens the possibility of studying quantum activation in many-body systems where other approaches are inapplicable.

Complex oxides are well known to develop oxygen ordering patterns with well defined periodicities, but their interplay with electronic correlations remains largely unexplored. Here, we report resonant and non-resonant x-ray diffraction data indicating a four-unit-cell periodic superstructure related to oxygen vacancy ordering in La$_{2-x}$Ca$_{x}$CuO$_{4}$ films with doping levels from the underdoped ($x = 0.15$) to the extremely overdoped ($x = 0.50$) regime. Whereas the lattice superstructure is temperature independent up to 300 K, a strongly temperature dependent electronic charge density wave (CDW) is observed in the underdoped and slightly overdoped regimes ($x\leq0.20$). The periodicity, in-plane and out-of-plane correlation lengths of the CDW are locked in by the lattice superstructure. Our results highlight the necessity to consider lattice and electronic energetics on equal footing in the high-temperature oxygen-disordered phase to explain oxygen ordering phenomena in complex oxides., Comment: 4 figures, supplement included

Both magnetism and spin-orbit coupling in systems with broken inversion symmetry lift the spin degeneracy of electronic bands, but the consequences of interplay between these mechanisms remain poorly understood. Here, we show that ultrathin transition ferromagnet-heavy metal bilayers exhibit anomalous temperature- and electric bias-dependent behaviors in the vicinity of the Curie temperature, inconsistent with the usual Weiss magnetism. Characterization by several complementary techniques and analysis of the dependence on composition reveal that these effects originate from interfacial spin-orbit interaction, which results in the emergence of a state with distinct magnetic and magnetoelectronic properties that can be described as Rashba magnetism. Our findings open a new route for the characterization and control of spin-orbit phenomena in heterostructures enabling the development of efficient spin-orbitronic devices., Comment: 6 pages, 4 figures, comments are welcome

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along integration lines. VT methods are non-invasive, non-intrusive and offer more information on the field than classical point measurements; they are typically used to reconstruct divergence-free (or source-free) velocity and flow fields. In this paper, we show that VT can also be used for the reconstruction of fields with non-zero divergence. In particular, we study electric fields generated by dipole sources in bounded domains which arise, for example, in electroencephalography (EEG) source imaging. To the best of our knowledge, VT has not previously been used to reconstruct such fields. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modelling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field., Comment: Application in EEG Source Imaging

In situ imageomics leverages machine learning techniques to infer biological traits from images collected in the field, or in situ, to study individuals organisms, groups of wildlife, and whole ecosystems. Such datasets provide real-time social and environmental context to inferred biological traits, which can enable new, data-driven conservation and ecosystem management. The development of machine learning techniques to extract biological traits from images are impeded by the volume and quality data required to train these models. Autonomous, unmanned aerial vehicles (UAVs), are well suited to collect in situ imageomics data as they can traverse remote terrain quickly to collect large volumes of data with greater consistency and reliability compared to manually piloted UAV missions. However, little guidance exists on optimizing autonomous UAV missions for the purposes of remote sensing for conservation and biodiversity monitoring. The UAV video dataset curated by KABR: In-Situ Dataset for Kenyan Animal Behavior Recognition from Drone Videos required three weeks to collect, a time-consuming and expensive endeavor. Our analysis of KABR revealed that a third of the videos gathered were unusable for the purposes of inferring wildlife behavior. We analyzed the flight telemetry data from portions of UAV videos that were usable for inferring wildlife behavior, and demonstrate how these insights can be integrated into an autonomous remote sensing system to track wildlife in real time. Our autonomous remote sensing system optimizes the UAV's actions to increase the yield of usable data, and matches the flight path of an expert pilot with an 87% accuracy rate, representing an 18.2% improvement in accuracy over previously proposed methods.

Biphasic interfaces are complex but fascinating regimes that display a number of properties distinct from those of the bulk. The CO$_2$-H$_2$O interface, in particular, has been the subject of a number of studies on account of its importance for the carbon life cycle as well as carbon capture and sequestration schemes. Despite this attention, there remain a number of open questions on the nature of the CO$_2$-H$_2$O interface, particularly concerning the interfacial tension and phase behavior of CO$_2$ at the interface. In this paper, we seek to address these ambiguities using ab initio-quality simulations. Harnessing the benefits of machine-learned potentials and enhanced statistical sampling methods, we present an ab initio-level description of the CO$_2$-H$_2$O interface. Interfacial tensions are predicted from 1-500 bar and found to be in close agreement with experiment at the pressures for which experimental data is available. Structural analyses indicate the build-up of an adsorbed, saturated CO$_2$ film forming at low pressure (20 bar) with properties similar to those of the bulk liquid, but preferential perpendicular alignment with respect to the interface. CO$_2$ monolayer build-up coincides with a reduced structuring of water molecules close to the interface. This study highlights the predictive nature of machine-learned potentials for complex macroscopic properties of biphasic interfaces, and the mechanistic insight obtained into carbon dioxide aggregation at the water interface is of high relevance for geoscience, climate research, and materials science., Comment: 14 pages, 10 figures

We use Resonant Inelastic X-ray Scattering (RIXS) to compare the doping dependence of magnetic excitations of an Infinite-Layer nickelate to those of a prototypical superconducting cuprate. The polarization analysis of RIXS spectra establishes the dominant spin-flip nature of the mid-infrared peak in both cases. Hole doping leads to opposite behavior of the magnetic energy in the two materials. By fitting the data with an original Hubbard-based model for dynamic susceptibility, we find that t is comparable in the two materials while U is about twice larger in the nickelate. This finding accounts for the smaller magnetic bandwidth of nickelates and for its decrease upon doping., Comment: 7 pages with bibliography, 4 figures

In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many works have analyzed and extended the original SRP method to reduce its computational cost, to allow it to locate multiple sources, or to improve its performance in adverse environments. In this work, we review over 200 papers on the SRP method and its variants, with emphasis on the SRP-PHAT method. We also present eXtensible-SRP, or X-SRP, a generalized and modularized version of the SRP algorithm which allows the reviewed extensions to be implemented. We provide a Python implementation of the algorithm which includes selected extensions from the literature.

Heterostructures from complex oxides allow one to combine various electronic and magnetic orders as to induce new quantum states. A prominent example is the coupling between superconducting and magnetic orders in multilayers from high-Tc cuprates and manganites. A key role is played here by the interfacial CuO2 layer whose distinct properties remain to be fully understood. Here, we study with resonant inelastic X-ray scattering (RIXS) the magnon excitations of this interfacial CuO2 layer. In particular, we show that the underlying antiferromagnetic exchange interaction at the interface is strongly suppressed to J ~ 70 meV, as compared to J ~ 130 meV for the CuO2 layers away from the interface. Moreover, we observe an anomalous momentum dependence of the intensity of the interfacial magnon mode and show that it suggests that the antiferromagnetic order is accompanied by a particular kind of orbital order that yields a so-called altermagnetic state. Such a two-dimensional altermagnet has recently been predicted to enable new spintronic applications and superconducting proximity effects.

We show that chimpanzee behaviour understanding from camera traps can be enhanced by providing visual architectures with access to an embedding of text descriptions that detail species behaviours. In particular, we present a vision-language model which employs multi-modal decoding of visual features extracted directly from camera trap videos to process query tokens representing behaviours and output class predictions. Query tokens are initialised using a standardised ethogram of chimpanzee behaviour, rather than using random or name-based initialisations. In addition, the effect of initialising query tokens using a masked language model fine-tuned on a text corpus of known behavioural patterns is explored. We evaluate our system on the PanAf500 and PanAf20K datasets and demonstrate the performance benefits of our multi-modal decoding approach and query initialisation strategy on multi-class and multi-label recognition tasks, respectively. Results and ablations corroborate performance improvements. We achieve state-of-the-art performance over vision and vision-language models in top-1 accuracy (+6.34%) on PanAf500 and overall (+1.1%) and tail-class (+2.26%) mean average precision on PanAf20K. We share complete source code and network weights for full reproducibility of results and easy utilisation.

The intimate correlation between the local atomic arrangement and electronic states in Li-ion battery cathode materials plays a crucial role in determining their electrochemical properties, including capacity, cycling stability, and rate capability. Despite almost 30 years of research efforts on high performance cathodes based on Ni rich layered oxides, there is still no consensus on LiNiO2 local atomic and electronic structure. Ni sites could be either Jahn-Teller distorted or bond disproportionated and the role of Ni and oxygen in the charge compensation mechanism remains unclear. In this study, we compare the local and electronic structure of LiNiO2 and NaNiO2, a long-range Jahn-Teller system, using a novel approach which aims at correlating the results from bulk spectroscopy techniques, particularly under operando conditions, obtained on standard samples to ensure sample interoperability and enhance the reliability and robustness of our results. Despite being a site-selective and local technique, XAS is unable to discriminate between the proposed scenarios, as confirmed also by theoretical calculations. On the contrary, Raman spectroscopy show local structural differences between monoclinic distorted NaNiO2 and rhombohedral LiNiO2. Additionally, HAXPES confirms the presence of multiple formal oxidation states for Ni, and RIXS data provides evidence of 3d8 states, confirming the negative charge transfer character of Ni and some degree of bond disproportionation in LiNiO2. Regarding the charge compensation mechanism, XRS and RIXS support the participation of oxygen holes in the redox activity, while Raman spectroscopy does not detect molecular oxygen. By combing several high-fidelity spectroscopy datasets, this study shows the value of correlative characterization workflows to provide insights into complex structural-electrochemical relationships.

This paper details the first application of a software tagging algorithm to reduce radon-induced backgrounds in liquid noble element time projection chambers, such as XENON1T and XENONnT. The convection velocity field in XENON1T was mapped out using $^{222}\text{Rn}$ and $^{218}\text{Po}$ events, and the root-mean-square convection speed was measured to be $0.30 \pm 0.01$ cm/s. Given this velocity field, $^{214}\text{Pb}$ background events can be tagged when they are followed by $^{214}\text{Bi}$ and $^{214}\text{Po}$ decays, or preceded by $^{218}\text{Po}$ decays. This was achieved by evolving a point cloud in the direction of a measured convection velocity field, and searching for $^{214}\text{Bi}$ and $^{214}\text{Po}$ decays or $^{218}\text{Po}$ decays within a volume defined by the point cloud. In XENON1T, this tagging system achieved a $^{214}\text{Pb}$ background reduction of $6.2^{+0.4}_{-0.9}\%$ with an exposure loss of $1.8\pm 0.2 \%$, despite the timescales of convection being smaller than the relevant decay times. We show that the performance can be improved in XENONnT, and that the performance of such a software-tagging approach can be expected to be further improved in a diffusion-limited scenario. Finally, a similar method might be useful to tag the cosmogenic $^{137}\text{Xe}$ background, which is relevant to the search for neutrinoless double-beta decay., Comment: 17 pages, 19 figures

Steered Response Power (SRP) is a widely used method for the task of sound source localization using microphone arrays, showing satisfactory localization performance on many practical scenarios. However, its performance is diminished under highly reverberant environments. Although Deep Neural Networks (DNNs) have been previously proposed to overcome this limitation, most are trained for a specific number of microphones with fixed spatial coordinates. This restricts their practical application on scenarios frequently observed in wireless acoustic sensor networks, where each application has an ad-hoc microphone topology. We propose Neural-SRP, a DNN which combines the flexibility of SRP with the performance gains of DNNs. We train our network using simulated data and transfer learning, and evaluate our approach on recorded and simulated data. Results verify that Neural-SRP's localization performance significantly outperforms the baselines., Comment: Presented at Asilomar Conference on Signals, Systems, and Computers

Studies have shown that in noisy acoustic environments, providing binaural signals to the user of an assistive listening device may improve speech intelligibility and spatial awareness. This paper presents a binaural speech enhancement method using a complex convolutional neural network with an encoder-decoder architecture and a complex multi-head attention transformer. The model is trained to estimate individual complex ratio masks in the time-frequency domain for the left and right-ear channels of binaural hearing devices. The model is trained using a novel loss function that incorporates the preservation of spatial information along with speech intelligibility improvement and noise reduction. Simulation results for acoustic scenarios with a single target speaker and isotropic noise of various types show that the proposed method improves the estimated binaural speech intelligibility and preserves the binaural cues better in comparison with several baseline algorithms., Comment: Accepted to ICASSP 2024

Strongly-correlated transition-metal oxides are widely known for their various exotic phenomena. This is exemplified by rare-earth nickelates such as LaNiO$_{3}$, which possess intimate interconnections between their electronic, spin, and lattice degrees of freedom. Their properties can be further enhanced by pairing them in hybrid heterostructures, which can lead to hidden phases and emergent phenomena. An important example is the LaNiO$_{3}$/LaTiO$_{3}$ superlattice, where an interlayer electron transfer has been observed from LaTiO$_{3}$ into LaNiO$_{3}$ and is predicted to result in a high-spin state. However, macroscopic emergence of magnetic order has so far not been observed. Here, by using muon spin rotation, x-ray absorption, and resonant inelastic x-ray scattering, we present direct evidence of an emergent antiferromagnetic order with high magnon energy and exchange interactions at the LaNiO$_{3}$/LaTiO$_{3}$ interface. As the magnetism is purely interfacial, a single LaNiO$_{3}$/LaTiO$_{3}$ interface can essentially behave as an atomically thin quasi-two-dimensional antiferromagnet, potentially allowing its technological utilisation in advanced spintronic devices. Furthermore, its strong quasi-two-dimensional magnetic correlations and orbitally-polarized planar ligand holes make its electronic and magnetic configurations resemble the precursor states of superconducting cuprates and nickelates, but with an S $\rightarrow$ 1 spin state instead., Comment: 41 pages, 13 figures

The multi-staged XENON program at INFN Laboratori Nazionali del Gran Sasso aims to detect dark matter with two-phase liquid xenon time projection chambers of increasing size and sensitivity. The XENONnT experiment is the latest detector in the program, planned to be an upgrade of its predecessor XENON1T. It features an active target of 5.9 tonnes of cryogenic liquid xenon (8.5 tonnes total mass in cryostat). The experiment is expected to extend the sensitivity to WIMP dark matter by more than an order of magnitude compared to XENON1T, thanks to the larger active mass and the significantly reduced background, improved by novel systems such as a radon removal plant and a neutron veto. This article describes the XENONnT experiment and its sub-systems in detail and reports on the detector performance during the first science run., Comment: 32 pages, 19 figures

The effects of confinement on electron transport in GaN have been studied via an ensemble Monte-Carlo code. Excellent agreement is obtained with experimental data from the literature up to moderate fields. In agreement with experimental results, negative-differential-conductivity is not observed in velocity-field curves. The reasons for this are discussed in detail. The dynamics of the non-equilibrium confined electron-LO phonon system is studied via a bulk phonon spectrum. In contrast to the bulk electron case hot or non-equilibrium phonons do not play a significant role in determining the transport properties. This is explained via the energy and momentum conservation rules for the polar optical phonon scattering. In addition, impact ionization is shown to be insignificant for the applied fields considered., Comment: 5 pages, 6 figures

Given a semigroup $S$, for each Green's relation $\mathcal{K}\in\{\mathcal{L},\mathcal{R},\mathcal{J},\mathcal{H}\}$ on $S,$ the $\mathcal{K}$-height of $S,$ denoted by $H_{\mathcal{K}}(S),$ is the height of the poset of $\mathcal{K}$-classes of $S.$ More precisely, if there is a finite bound on the sizes of chains of $\mathcal{K}$-classes of $S,$ then $H_{\mathcal{K}}(S)$ is defined as the maximum size of such a chain; otherwise, we say that $S$ has infinite $\mathcal{K}$-height. We discuss the relationships between these four $\mathcal{K}$-heights. The main results concern the class of stable semigroups, which includes all finite semigroups. In particular, we prove that a stable semigroup has finite $\mathcal{L}$-height if and only if it has finite $\mathcal{R}$-height if and only if it has finite $\mathcal{J}$-height. In fact, for a stable semigroup $S,$ if $H_{\mathcal{L}}(S)=n$ then $H_{\mathcal{R}}(S)\leq2^n-1$ and $H_{\mathcal{J}}(S)\leq2^n-1,$ and we exhibit a family of examples to prove that these bounds are sharp. Furthermore, we prove that if $2\leq H_{\mathcal{L}}(S)<\infty$ and $2\leq H_{\mathcal{R}}(S)<\infty,$ then $H_{\mathcal{J}}(S)\leq H_{\mathcal{L}}(S)+H_{\mathcal{R}}(S)-2.$ We also show that for each $n\in\mathbb{N}$ there exists a semigroup $S$ such that $H_{\mathcal{L}}(S)=H_{\mathcal{R}}(S)=2^n+n-3$ and $H_{\mathcal{J}}(S)=2^{n+1}-4.$ By way of contrast, we prove that for a regular semigroup the $\mathcal{L}$-, $\mathcal{R}$- and $\mathcal{H}$-heights coincide with each other, and are greater or equal to the $\mathcal{J}$-height. Moreover, in a stable, regular semigroup the $\mathcal{L}$-, $\mathcal{R}$-, $\mathcal{H}$- and $\mathcal{J}$-heights are all equal.

Van der Waals materials provide a versatile toolbox for the emergence of new quantum phenomena and the fabrication of functional heterostructures. Among them, the trihalide VI3 stands out for its unique magnetic and structural landscape. Here we investigate the spin and orbital magnetic degrees of freedom in the layered ferromagnet VI3 by means of temperature-dependent x-ray absorption spectroscopy and x-ray magnetic circular and linear dichroism. We detect localized electronic states and reduced magnetic dimensionality, due to electronic correlations. We furthermore provide experimental evidence of (a) an unquenched orbital magnetic moment (up to 0.66(7)) in the ferromagnetic state, and (b) an instability of the orbital moment in proximity of the spin reorientation transition. Our results support a coherent picture where electronic correlations give rise to a strong magnetic anisotropy and a large orbital moment, and establish VI3 as a prime candidate for the study of orbital quantum effects.

A monoid $S$ is right coherent if every finitely generated subact of every finitely presented right $S$-act itself has a finite presentation; it is weakly right coherent if every finitely generated right ideal of $S$ has a finite presentation. We show that full and partial transformation monoids, symmetric inverse monoids and partition monoids over an infinite set are all weakly right coherent, but that none of them is right coherent. Left coherency and weak left coherency are defined dually, and the corresponding results hold for these properties. In order to prove the non-coherency results, we give a presentation of an inverse semigroup which does not embed into any left or right coherent monoid., Comment: 10 pages

Model-based optimization (MBO) is increasingly applied to design problems in science and engineering. A common scenario involves using a fixed training set to train models, with the goal of designing new samples that outperform those present in the training data. A major challenge in this setting is distribution shift, where the distributions of training and design samples are different. While some shift is expected, as the goal is to create better designs, this change can negatively affect model accuracy and subsequently, design quality. Despite the widespread nature of this problem, addressing it demands deep domain knowledge and artful application. To tackle this issue, we propose a straightforward method for design practitioners that detects distribution shifts. This method trains a binary classifier using knowledge of the unlabeled design distribution to separate the training data from the design data. The classifier's logit scores are then used as a proxy measure of distribution shift. We validate our method in a real-world application by running offline MBO and evaluate the effect of distribution shift on design quality. We find that the intensity of the shift in the design distribution varies based on the number of steps taken by the optimization algorithm, and our simple approach can identify these shifts. This enables users to constrain their search to regions where the model's predictions are reliable, thereby increasing the quality of designs.

The essential building blocks of cuprate superconductors are two-dimensional CuO$_2$ sheets interspersed with charge reservoir layers. In bilayer cuprates, two closely spaced CuO$_2$ sheets are separated by a larger distance from the subsequent pair in the next unit cell. In contrast to single-layer cuprates, prior theoretical work on bilayer systems has predicted two distinct acoustic plasmon bands for a given out-of-plane momentum transfer. Here we report random phase approximation (RPA) calculations for bilayer systems which corroborate the existence of two distinct plasmons bands. We find that the intensity of the lower-energy band is negligibly small, whereas the higher-energy band carries significant spectral weight. We also present resonant inelastic x-ray scattering (RIXS) experiments at the O $K$-edge on the bilayer cuprate Y$_{0.85}$Ca$_{0.15}$Ba$_2$Cu$_3$O$_7$ (Ca-YBCO), which show only one dispersive plasmon branch, in agreement with the RPA calculations. In addition, the RPA results indicate that the dispersion of the higher-energy plasmon band in Ca-YBCO is not strictly acoustic, but exhibits a substantial energy gap of approximately 250 meV at the two-dimensional Brillouin zone center., Comment: 9 pages, 7 figures

We investigated the high energy spin excitations in electron-doped $\mathrm{La}_{2-x} \mathrm{Ce}_x \mathrm{CuO}_{4}$, a cuprate superconductor, by resonant inelastic x-ray scattering (RIXS) measurements. Efforts were paid to disentangle the paramagnon signal from non-spin-flip spectral weight mixing in the RIXS spectrum at $\bf{Q_{\|}}$ = $(0.6\pi, 0)$ and $(0.9\pi, 0)$ along the (1 0) direction. Our results show that, for doping level x from 0.07 to 0.185, the variation of the paramagnon excitation energy is marginal. We discuss the implication of our results in connection with the evolution of the electron correlation strength in this system., Comment: in press on Phys. Rev. Lett

The height of a poset $P$ is the supremum of the cardinalities of chains in $P$. The exact formula for the height of the subgroup lattice of the symmetric group $\mathcal{S}_n$ is known, as is an accurate asymptotic formula for the height of the subsemigroup lattice of the full transformation monoid $\mathcal{T}_n$. Motivated by the related question of determining the heights of the lattices of left- and right congruences of $\mathcal{T}_n$, we develop a general method for computing the heights of lattices of both one- and two-sided congruences for semigroups. We apply this theory to obtain exact height formulae for several monoids of transformations, matrices and partitions, including: the full transformation monoid $\mathcal{T}_n$, the partial transformation monoid $\mathcal{PT}_n$, the symmetric inverse monoid $\mathcal{I}_n$, the monoid of order-preserving transformations $\mathcal{O}_n$, the full matrix monoid $\mathcal{M}(n,q)$, the partition monoid $\mathcal{P}_n$, the Brauer monoid $\mathcal{B}_n$ and the Temperley-Lieb monoid $\mathcal{TL}_n$.

Recent improvements in the energy resolution of resonant inelastic x-ray scattering experiments (RIXS) at the Cu-L$_3$ edge have enabled the study of lattice, spin, and charge excitations. Here, we report on the detection of a low intensity signal at 140meV, twice the energy of the bond-stretching (BS) phonon mode, in the cuprate superconductor $\textrm{Bi}_2\textrm{Sr}_2\textrm{Ca}\textrm{Cu}_2\textrm{O}_{8+x}$ (Bi-2212). Ultra-high resolution polarimetric RIXS measurements allow us to resolve the outgoing polarization of the signal and identify this feature as a two-phonon excitation. Further, we study the connection between the two-phonon mode and the BS one-phonon mode by constructing a joint density of states toy model that reproduces the key features of the data.

The precision in reconstructing events detected in a dual-phase time projection chamber depends on an homogeneous and well understood electric field within the liquid target. In the XENONnT TPC the field homogeneity is achieved through a double-array field cage, consisting of two nested arrays of field shaping rings connected by an easily accessible resistor chain. Rather than being connected to the gate electrode, the topmost field shaping ring is independently biased, adding a degree of freedom to tune the electric field during operation. Two-dimensional finite element simulations were used to optimize the field cage, as well as its operation. Simulation results were compared to ${}^{83m}\mathrm{Kr}$ calibration data. This comparison indicates an accumulation of charge on the panels of the TPC which is constant over time, as no evolution of the reconstructed position distribution of events is observed. The simulated electric field was then used to correct the charge signal for the field dependence of the charge yield. This correction resolves the inconsistent measurement of the drift electron lifetime when using different calibrations sources and different field cage tuning voltages.

In strongly correlated systems the complete determination of the dynamical susceptibility $\chi(\textbf{q}, \omega)$ is of special relevance because of the entwinement of the spin and charge components. Although Resonant Inelastic X-Ray Scattering (RIXS) spectra are directly related to both the charge ($\chi''_c(\textbf{q}, \omega)$) and the spin ($\chi''_s(\textbf{q}, \omega)$) contributions, only the latter has been extensively studied with RIXS so far. Here we show how to extract from RIXS spectra of high-$T_c$ superconducting cuprates relevant properties of $\chi''_c$, such as the presence of the superconducting gap and of the pseudogap. In particular, we exploit the temperature dependence of the Cu L$_3$ edge RIXS spectra of underdoped YBa$_2$Cu$_3$O$_{7-\delta}$ at specific wave-vectors q. The signature of the two gaps is in the departure of the low energy Bosonic excitation continuum from the statistical temperature-dependence. This approach can be immediately used to investigate systematically the nature of the pseudogap in cuprates, thereby taking advantage of the RIXS technique that does not suffer the limitations of surface-sensitive electron spectroscopies. Its extension to other interesting materials is foreseen., Comment: 14 pages, 12 figures

Distributed Microphone Arrays (DMAs) present many challenges with respect to centralized microphone arrays. An important requirement of applications on these arrays is handling a variable number of input channels. We consider the use of Graph Neural Networks (GNNs) as a solution to this challenge. We present a localization method using the Relation Network GNN, which we show shares many similarities to classical signal processing algorithms for Sound Source Localization (SSL). We apply our method for the task of SSL and validate it experimentally using an unseen number of microphones. We test different feature extractors and show that our approach significantly outperforms classical baselines., Comment: Presented as a poster at ICASSP 2023

Xenon dual-phase time projections chambers (TPCs) have proven to be a successful technology in studying physical phenomena that require low-background conditions. With 40t of liquid xenon (LXe) in the TPC baseline design, DARWIN will have a high sensitivity for the detection of particle dark matter, neutrinoless double beta decay ($0\nu\beta\beta$), and axion-like particles (ALPs). Although cosmic muons are a source of background that cannot be entirely eliminated, they may be greatly diminished by placing the detector deep underground. In this study, we used Monte Carlo simulations to model the cosmogenic background expected for the DARWIN observatory at four underground laboratories: Laboratori Nazionali del Gran Sasso (LNGS), Sanford Underground Research Facility (SURF), Laboratoire Souterrain de Modane (LSM) and SNOLAB. We determine the production rates of unstable xenon isotopes and tritium due to muon-included neutron fluxes and muon-induced spallation. These are expected to represent the dominant contributions to cosmogenic backgrounds and thus the most relevant for site selection.

We perform a blind search for particle signals in the XENON1T dark matter detector that occur close in time to gravitational wave signals in the LIGO and Virgo observatories. No particle signal is observed in the nuclear recoil, electronic recoil, CE$\nu$NS, and S2-only channels within $\pm$ 500 seconds of observations of the gravitational wave signals GW170104, GW170729, GW170817, GW170818, and GW170823. We use this null result to constrain mono-energetic neutrinos and Beyond Standard Model particles emitted in the closest coalescence GW170817, a binary neutron star merger. We set new upper limits on the fluence (time-integrated flux) of coincident neutrinos down to 17 keV at 90% confidence level. Furthermore, we constrain the product of coincident fluence and cross section of Beyond Standard Model particles to be less than $10^{-29}$ cm$^2$/cm$^2$ in the [5.5-210] keV energy range at 90% confidence level.

Magnetic frustration is a route that can lead to the emergence of novel ground states, including spin liquids and spin ices. Such frustration can be introduced through either the geometry of lattice structures or by incompatible exchange interactions. Identifying suitable strategies to control the degree of magnetic frustration in real systems is an active field of research. In this study, we devise a design principle for the tuning of frustrated magnetism on the square lattice through the manipulation of nearest (NN) and next-nearest neighbor (NNN) antiferromagnetic (AF) exchange interactions. By studying the magnon excitations in epitaxially-strained La$_2$NiO$_4$ films using resonant inelastic x-ray scattering (RIXS) we show that, in contrast to the cuprates, the dispersion peaks at the AF zone boundary. This indicates the presence of an AF-NNN spin interaction. Using first principles simulations and an effective spin-model, we demonstrate the AF-NNN coupling to be a consequence of the two-orbital nature of La$_2$NiO$_4$. Our results demonstrate that compressive strain can enhance this coupling, providing a design principle for the tunability of frustrated magnetism on a square lattice.

Polarization dependent x-ray absorption spectroscopy was used to study the magnetic ground state and the orbital occupation in bulk-phase VI$_3$ van der Waals crystals below and above the ferromagnetic and structural transitions. X-ray natural linear dichroism and X-ray magnetic circular dichroism spectra acquired at the V $L_{2,3}$ edges are compared against multiplet cluster calculations within the frame of the ligand field theory to quantify the intra-atomic electronic interactions at play and evaluate the effects of symmetry reduction occurring in a trigonally distorted VI$_6$ unit. We observed a non zero linear dichroism proving the presence of an anisotropic charge density distribution around the V$^{3+}$ ion due to the unbalanced hybridization between the Vanadium and the ligand states. Such hybridization acts as an effective trigonal crystal field, slightly lifting the degeneracy of the $t_{2g}^2$ ground state. However, the energy splitting associated to the distortion underestimates the experimental band gap, suggesting that the insulating ground state is stabilized by Mott correlation effects rather than via a Jahn-Teller mechanism. Our results clarify the role of the distortion in VI$_3$ and establish a benchmark for the study of the spectroscopic properties of other van der Waals halides, including emerging 2D materials with mono and few-layers thickness, whose fundamental properties might be altered by reduced dimensions and interface proximity.

Fitness functions map large combinatorial spaces of biological sequences to properties of interest. Inferring these multimodal functions from experimental data is a central task in modern protein engineering. Global epistasis models are an effective and physically-grounded class of models for estimating fitness functions from observed data. These models assume that a sparse latent function is transformed by a monotonic nonlinearity to emit measurable fitness. Here we demonstrate that minimizing supervised contrastive loss functions, such as the Bradley-Terry loss, is a simple and flexible technique for extracting the sparse latent function implied by global epistasis. We argue by way of a fitness-epistasis uncertainty principle that the nonlinearities in global epistasis models can produce observed fitness functions that do not admit sparse representations, and thus may be inefficient to learn from observations when using a Mean Squared Error (MSE) loss (a common practice). We show that contrastive losses are able to accurately estimate a ranking function from limited data even in regimes where MSE is ineffective and validate the practical utility of this insight by demonstrating that contrastive loss functions result in consistently improved performance on benchmark tasks.