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In this paper, we propose LiOn-XA, an unsupervised domain adaptation (UDA) approach that combines LiDAR-Only Cross-Modal (X) learning with Adversarial training for 3D LiDAR point cloud semantic segmentation to bridge the domain gap arising from environmental and sensor setup changes. Unlike existing works that exploit multiple data modalities like point clouds and RGB image data, we address UDA in scenarios where RGB images might not be available and show that two distinct LiDAR data representations can learn from each other for UDA. More specifically, we leverage 3D voxelized point clouds to preserve important geometric structure in combination with 2D projection-based range images that provide information such as object orientations or surfaces. To further align the feature space between both domains, we apply adversarial training using both features and predictions of both 2D and 3D neural networks. Our experiments on 3 real-to-real adaptation scenarios demonstrate the effectiveness of our approach, achieving new state-of-the-art performance when compared to previous uni- and multi-model UDA methods. Our source code is publicly available at https://github.com/JensLe97/lion-xa., Comment: Preprint, Paper has been accepted at IROS2024

Quantum cat maps are toy models in quantum chaos associated to hyperbolic symplectic matrices $A\in \operatorname{Sp}(2n,\mathbb{Z})$. The macroscopic limits of sequences of eigenfunctions of a quantum cat map are characterized by semiclassical measures on the torus $\mathbb{R}^{2n}/\mathbb{Z}^{2n}$. We show that if the characteristic polynomial of every power $A^k$ is irreducible over the rationals, then every semiclassical measure has full support. The proof uses an earlier strategy of Dyatlov-J\'ez\'equel [arXiv:2108.10463] and the higher-dimensional fractal uncertainty principle of Cohen [arXiv:2305.05022]. Our irreducibility condition is generically true, in fact we show that asymptotically for $100\%$ of matrices $A$, the Galois group of the characteristic polynomial of $A$ is $S_2 \wr S_n$. When the irreducibility condition does not hold, we show that a semiclassical measure cannot be supported on a finite union of parallel non-coisotropic subtori. On the other hand, we give examples of semiclassical measures supported on the union of two transversal symplectic subtori for $n=2$, inspired by the work of Faure-Nonnenmacher-De Bi\`evre [arXiv:nlin/0207060] in the case $n=1$. This is complementary to the examples by Kelmer [arXiv:math-ph/0510079] of semiclassical measures supported on a single coisotropic subtorus., Comment: 64 pages, 2 figures; with an appendix by Theresa C. Anderson and Robert J. Lemke Oliver

Speckle patterns manifesting from the interaction of coherent X-rays with matter offer a glimpse into the dynamics of nanoscale domains that underpin many emergent phenomena in quantum materials. While the dynamics of the average structure can be followed with time-resolved X-ray diffraction, the ultrafast evolution of local structures in nonequilibrium conditions have thus far eluded detection due to experimental limitations, such as insufficient X-ray coherent flux. Here we demonstrate a nonequilibrium speckle visibility experiment using a split-and-delay setup at an X-ray free-electron laser. Photoinduced electronic domain fluctuations of the magnetic model material Fe$_{3}$O$_{4}$ reveal changes of the trimeron network configuration due to charge dynamics that exhibit liquid-like fluctuations, analogous to a supercooled liquid phase. This suggests that ultrafast dynamics of electronic heterogeneities under optical stimuli are fundamentally different from thermally-driven ones.

Optical two-way time and frequency transfer is an enabling technology that has applications ranging from fundamental investigations of relativity to the operation of global navigation satellite systems. While fiber frequency combs have demonstrated the most stable optical links, they are not ideal for applications that require very low SWaP-C. Here, we demonstrate two-way time and frequency transfer using electro-optic combs that have a direct path to full chip-scale integration. This two-way electro-optic time and frequency transfer system demonstrated instabilities as low as 15 fs at 1 s of averaging time. These results show a pathway to highly stable, agile and low SWaP-C time transfer networks., Comment: 7 pages, 5 figures

Several Pulsar Timing Array (PTA) collaborations have recently found evidence for a Gravitational Wave Background (GWB) by measuring the perturbations that this background induces in the time-of-arrivals of pulsar signals. These perturbations are expected to be correlated across different pulsars and, for isotropic GWBs, the expected values of these correlations (obtained by averaging over different GWB realizations) are a simple function of the pulsars' angular separations, known as the Hellings-Downs (HD) correlation function. On the other hand, anisotropic GWBs would induce deviations from these HD correlations in a way that can be used to search for anisotropic distributions of the GWB power. However, even for isotropic GWBs, interference between GW sources radiating at overlapping frequencies induces deviations from the HD correlation pattern, an effect known in the literature as "cosmic variance". In this work, we study the impact of cosmic variance on PTA anisotropy searches. We find that the fluctuations in cross-correlations related to cosmic variance can lead to the miss-classification of isotropic GWBs as anisotropic, leading to a false detection rate of $\sim 50\%$ for frequentist anisotropy searches. We also observe that cosmic variance complicates the reconstruction of the GWB sky map, making it more challenging to resolve bright GW hotspots, like the ones expected to be produced from a Supermassive Black Hole Binaries population. These findings highlight the need to refine anisotropy search techniques to improve our ability to reconstruct the GWB sky map and accurately assess the significance of any isotropy deviations we might find in it., Comment: 15 pages, 8 figures

Medical image distributions shift constantly due to changes in patient population and discrepancies in image acquisition. These distribution changes result in performance deterioration; deterioration that continual learning aims to alleviate. However, only adaptation with data rehearsal strategies yields practically desirable performance for medical image segmentation. Such rehearsal violates patient privacy and, as most continual learning approaches, overlooks unexpected changes from out-of-distribution instances. To transcend both of these challenges, we introduce a distribution-aware replay strategy that mitigates forgetting through auto-encoding of features, while simultaneously leveraging the learned distribution of features to detect model failure. We provide empirical corroboration on hippocampus and prostate MRI segmentation.

Several Pulsar Timing Array (PTA) collaborations have recently found evidence for a gravitational wave background (GWB) permeating our galaxy. The origin of this background is still unknown. Indeed, while the gravitational wave emission from inspiraling supermassive black hole binaries (SMBHB) is the primary candidate for its origin, several cosmological sources have also been proposed. One distinctive feature of SMBHB-generated backgrounds is the presence of GWB anisotropies stemming from the binaries distribution in the local Universe. However, none of the anisotropy searches performed to date reported a detection. In this work, we show that the lack of anisotropy detection is not currently in tension with a SMBHB origin of the background. We accomplish this by calculating the anisotropy detection probability of present and future PTAs. We find that a PTA with the noise characteristics of the NANOGrav 15-year data set had only a $~2\%-11\%$ probability of detecting SMBHB-generated anisotropies, depending on the properties of the SMBHB population. However, we estimate that for the IPTA DR3 data set these probabilities will increase to $~4\%-28\%$, putting more pressure on the SMBHB interpretation in case of a null detection. We also identify SMBHB populations that are more likely to produce detectable levels of anisotropies. This information could be used together with the spectral properties of the GWB to characterize the SMBHB population., Comment: 16 pages, 7 figures

Understanding how light modifies long-range order is key to improve our ability to control material functionality on an ultrafast timescale. Transient spatial heterogeneity has been proposed in many materials, but isolating the dynamics of different regions experimentally has been challenging. Here we address this issue and measure the dynamics of orbital order melting in the layered manganite, La0.5Sr1.5MnO4, and isolate the surface dynamics from the bulk for the first time. Bulk measurements show orbital order is rapidly suppressed, but the correlation length surprisingly increases. However, the surface dynamics, show a stronger suppression and a significant decrease in correlation length. By isolating the surface changes, we find that light preferentially melts a less ordered surface and the loss of long-range order is likely driven by the formation of local and disordered polarons. Melting the disordered surface effectively increases the average correlation of the bulk probed volume, resolving the contradictory response. These results show that surface scattering methods are necessary to understand both surface and bulk dynamics in heterogeneous materials., Comment: 22 pages, 8 figures

Let $k$ be a number field. We provide an asymptotic formula for the number of Galois extensions of $k$ with absolute discriminant bounded by some $X \geq 1$, as $X\to\infty$. We also provide an asymptotic formula for the closely related count of extensions $K/k$ whose normal closure has discriminant bounded by $X$. The key behind these results is a new upper bound on the number of Galois extensions of $k$ with a given Galois group $G$ and discriminant bounded by $X$; we show the number of such extensions is $O_{[k:\mathbb{Q}],G} (X^{ \frac{4}{\sqrt{|G|}}})$. This improves over the previous best bound $O_{k,G,\epsilon}(X^{\frac{3}{8}+\epsilon})$ due to Ellenberg and Venkatesh. In particular, ours is the first bound for general $G$ with an exponent that decays as $|G| \to \infty$.

Given a finite group G, we prove that the vector space spanned by the faithful irreducible characters of G is generated by the monomial characters in the vector space. As a consequence, we show that in any family of G-extensions of a fixed number field F, almost all are subject to a strong effective version of the Chebotarev density theorem. We use this version of the Chebotarev density theorem to deduce several consequences for class groups in families of number fields., Comment: 50 pages

In recent years, modern techniques in deep learning and large-scale datasets have led to impressive progress in 3D instance segmentation, grasp pose estimation, and robotics. This allows for accurate detection directly in 3D scenes, object- and environment-aware grasp prediction, as well as robust and repeatable robotic manipulation. This work aims to integrate these recent methods into a comprehensive framework for robotic interaction and manipulation in human-centric environments. Specifically, we leverage 3D reconstructions from a commodity 3D scanner for open-vocabulary instance segmentation, alongside grasp pose estimation, to demonstrate dynamic picking of objects, and opening of drawers. We show the performance and robustness of our model in two sets of real-world experiments including dynamic object retrieval and drawer opening, reporting a 51% and 82% success rate respectively. Code of our framework as well as videos are available on: https://spot-compose.github.io/., Comment: Accepted at ICRA 2024 Workshops. Code and videos available at https://spot-compose.github.io/

Deep Graph Neural Networks struggle with oversmoothing. This paper introduces a novel, physics-inspired GNN model designed to mitigate this issue. Our approach integrates with existing GNN architectures, introducing an entropy-aware message passing term. This term performs gradient ascent on the entropy during node aggregation, thereby preserving a certain degree of entropy in the embeddings. We conduct a comparative analysis of our model against state-of-the-art GNNs across various common datasets., Comment: 4 pages, 3 figures

Like many states, Massachusetts has intensified efforts in recent years to improve literacy outcomes, particularly in the early grades. Initiatives have focused on providing guidance and resources for implementing changes in curriculum, instruction, and additional screening and support for struggling students. In September 2022, the Board of Elementary and Secondary Education in Massachusetts amended state law to require that all elementary schools assess each student's reading abilities and early literacy skills a minimum of twice per year from kindergarten through at least of grade 3. The goal of such screening is to identify students who may be at risk of reading difficulty and proactively intervene to ensure that all students have the foundational skills needed to be successful readers. Beginning with the 2020/21 school year, the Massachusetts Department of Elementary and Secondary Education (DESE) began collecting literacy screening assessment data from schools and districts participating in certain state grants. The goal of collecting the data is to analyze patterns of performance to inform improvement efforts--for example, knowing when students struggle or how they progress over time may help schools, districts, and the state target resources and supports. Using the benchmarks provided within each assessment to identify students at risk of reading difficulty, this issue brief provides a first look at student progress within and across grade levels based on available data.

Beginning with the 2020/21 school year, the Massachusetts Department of Elementary and Secondary Education (DESE) began collecting literacy screening assessment data from schools and districts participating in certain state grants. Screening assessment benchmark scores were available for just over 35,000 unique students across 2020/21 and 2021/22, representing about 10 percent of the state's population of grade K--3 students and including students from 43 districts and 159 schools. The screening assessments in use in the state vary in how they were designed, how they are administered, and how they define risk of reading difficulty. Most, but not all, screening assessments also include several levels of risk. These differences, along with the fact that students take these assessments several times per year, mean that multiple methods are used to calculate numbers of students at risk of reading difficulty across assessments in the state and that the meaning of "risk" can differ somewhat across assessments. The screening assessment data include more economically disadvantaged and English learner students and fewer grade 3 students than the state as a whole, suggesting some caution may be needed in generalizing from results of these analyses to the state. Nonetheless, these literacy screening assessment data provide an initial opportunity to examine student performance in the early grades and assess the extent to which intended policy outcomes in literacy are being achieved. This report provides a first look at the literacy performance of students in grades K-3 in Massachusetts based on available data from both the 2020/21 and 2021/22 school years.

This brief provides information about student literacy performance of students with different background characteristics and learning environments. It draws from data collected and analyzed in the report "A First Look at Early Literacy Performance in Massachusetts: Results of Initial Analysis Based on State Grantee Literacy Screening Assessments," which provides the first-ever large-scale information about early literacy performance and progress of students in grades K-3 in Massachusetts.

Beginning with the 2020-21 school year, the Massachusetts Department of Elementary and Secondary Education began collecting literacy screening assessment data from schools and districts participating in certain state grants in order to analyze patterns of performance to inform improvement efforts. These assessments, which were selected from a list of state-approved screener products, vary in how they were designed, how they are administered, and how they define risk of reading difficulty, making it difficult to compare and summarize performance for students in different schools and districts. However, grade 3 students do take one common assessment: the Massachusetts Comprehensive Assessment System (MCAS) English Language Arts (ELA) assessment. MCAS therefore provides a mechanism to compare literacy benchmarks using a common metric. This issue brief describes what it means to be "at risk" of reading difficulty as defined by each screening assessment and then provides results of a study that links screener benchmark scores to the MCAS grade 3 scale.

We present a new set up for resonant inelastic hard X-ray scattering at the Bernina beamline of SwissFEL with energy, momentum, and temporal resolution. The compact R=0.5 m Johann-type spectrometer can be equipped with up to 3 crystal analysers and allows efficient collection of RIXS spectra. Optical pumping for time-resolved studies can be realized with a broad span of optical wavelengths. We demonstrate the performance of the set-up at overall ~180 meV resolution in a study of ground-state and photoexcited (at 400 nm) honeycomb 5d iridate $\alpha$-$\mathrm{Li_2IrO_3}$. Steady-state RIXS spectra at the Iridium ${L_3}$-edge (11.214 keV) have been collected and are in very good agreement with data collected at synchrotrons. The time-resolved RIXS transients (pumped minus unpumped spectra) exhibit changes in the energy-loss region <2 eV, whose features mostly result from the hopping nature of 5d electrons in the honeycomb lattice. These changes are ascribed to modulations of the Ir-to-Ir intersite transition scattering efficiency, which we associate to a transient screening of the on-site Coulomb interaction., Comment: 17 + 7 pages, 4 + 6 figures

A folklore conjecture asserts the existence of a constant $c_n > 0$ such that $\#\mathcal{F}_n(X) \sim c_n X$ as $X\to \infty$, where $\mathcal{F}_n(X)$ is the set of degree $n$ extensions $K/\mathbb{Q}$ with discriminant bounded by $X$. This conjecture is known if $n \leq 5$, but even the weaker conjecture that there exists an absolute constant $C\geq 1$ such that $\#\mathcal{F}_n(X) \ll_n X^C$ remains unknown and apparently out of reach. Here, we make progress on this weaker conjecture (which we term the "uniform exponent conjecture") in two ways. First, we reduce the general problem to that of studying relative extensions of number fields whose Galois group is an almost simple group in a natural primitive permutation representation. Second, for almost all such groups, we prove the strongest known upper bound on the number of such extensions. These bounds have the effect of resolving the uniform exponent conjecture for solvable groups, sporadic groups, exceptional groups, and classical groups of bounded rank., Comment: v2: Updated references and incorporated minor improvements, corrected typos