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The U.S. has witnessed a resurgence of labor activism, with teachers at the forefront. We examine how teacher strikes affect compensation, working conditions, and productivity with an original dataset of 772 teacher strikes generating 48 million student days idle between 2007 and 2023. Using an event study framework, we find that, on average, strikes increase compensation by 8% and lower pupil-teacher ratios by 0.5 students, driven by new state revenues. We find little evidence of sizable impacts on student achievement up to five years post-strike, though strikes lasting 10 or more days decrease math achievement in the short-term.

With the rise of medical foundation models and the growing availability of imaging data, scalable pretraining techniques offer a promising way to identify imaging biomarkers predictive of future disease risk. While current self-supervised methods for 3D medical imaging models capture local structural features like organ morphology, they fail to link pixel biomarkers with long-term health outcomes due to a missing context problem. Current approaches lack the temporal context necessary to identify biomarkers correlated with disease progression, as they rely on supervision derived only from images and concurrent text descriptions. To address this, we introduce time-to-event pretraining, a pretraining framework for 3D medical imaging models that leverages large-scale temporal supervision from paired, longitudinal electronic health records (EHRs). Using a dataset of 18,945 CT scans (4.2 million 2D images) and time-to-event distributions across thousands of EHR-derived tasks, our method improves outcome prediction, achieving an average AUROC increase of 23.7% and a 29.4% gain in Harrell's C-index across 8 benchmark tasks. Importantly, these gains are achieved without sacrificing diagnostic classification performance. This study lays the foundation for integrating longitudinal EHR and 3D imaging data to advance clinical risk prediction., Comment: 34 pages, 19 figures

Transformers, originally prominent in NLP and computer vision, are now being adapted for ECG signal analysis. This paper introduces a novel hierarchical transformer architecture that segments the model into multiple stages by assessing the spatial size of the embeddings, thus eliminating the need for additional downsampling strategies or complex attention designs. A classification token aggregates information across feature scales, facilitating interactions between different stages of the transformer. By utilizing depth-wise convolutions in a six-layer convolutional encoder, our approach preserves the relationships between different ECG leads. Moreover, an attention gate mechanism learns associations among the leads prior to classification. This model adapts flexibly to various embedding networks and input sizes while enhancing the interpretability of transformers in ECG signal analysis., Comment: 5 pages,3 figures,under review by ISBI 2025

Quantum error correction (QEC) is a crucial prerequisite for future large-scale quantum computation. Finding and analyzing new QEC codes, along with efficient decoding and fault-tolerance protocols, is central to this effort. Holographic codes are a recent class of QEC subsystem codes derived from holographic bulk/boundary dualities. In addition to exploring the physics of such dualities, these codes possess useful QEC properties such as tunable encoding rates, distance scaling competitive with topological codes, and excellent recovery thresholds. To allow for a comprehensive analysis of holographic code constructions, we introduce LEGO_HQEC, a software package utilizing the quantum LEGO formalism. This package constructs holographic codes on regular hyperbolic tilings and generates their stabilizer generators and logical operators for a specified number of seed codes and layers. Three decoders are included: an erasure decoder based on Gaussian elimination; an integer-optimization decoder; and a tensor-network decoder. With these tools, LEGO_HQEC thus enables future systematic studies regarding the utility of holographic codes for practical quantum computing.

Researchers have long recognized the socio-technical gaps in personal tracking research, where machines can never fully model the complexity of human behavior, making it only able to produce basic rule-based outputs or "black-box" results that lack clear explanations. Real-world deployments rely on experts for this complex translation from sparse data to meaningful insights. In this study, we consider this translation process from data to insights by experts as "sensemaking" and explore how HCI researchers can support it through Vital Insight, an evidence-based 'sensemaking' system that combines direct representation and indirect inference through visualization and Large Language Models. We evaluate Vital Insight in user testing sessions with 14 experts in multi-modal tracking, synthesize design implications, and develop an expert sensemaking model where they iteratively move between direct data representations and AI-supported inferences to explore, retrieve, question, and validate insights.

Nano-patterned magnetic materials have opened new venues on the investigation of strongly correlated phenomena including artificial spin-ice systems, geometric frustration, magnetic monopoles, for technologically important applications such as reconfigurable ferromagnetism. With the advent of atomically thin two-dimensional (2D) van der Waals (vdW) magnets a pertinent question is whether such compounds could make their way into this realm where interactions can be tailored so that unconventional states of matter could be assessed. Here we show that square islands of CrGeTe3 vdW ferromagnets distributed in a grid manifest antiferromagnetic correlations, essential to enable frustration resulting in an artificial spin-ice. By using a combination of SQUID-on-tip microscopy, focused ion beam lithography, and atomistic spin dynamic simulations, we show that pristine, isolated CGT flakes as small as 150*150*60 nm3 have tunable dipole-dipole interactions, which can be precisely controlled by their lateral spacing. There is a crossover between non-interacting islands and significant inter-island anticorrelation depending how they are spatially distributed allowing the creation of complex magnetic patterns not observable at the isolated flakes. Our findings suggest that the cross-talk between the nano-patterned magnets can be explored in the generation of even more complex spin configurations where exotic interactions may be manipulated in an unprecedent way., Comment: Main text: 12 pages, 5 figures. Supplementary information: 11 pages, 5 figures

The coercivity of single-domain magnetic nanoparticles typically decreases with the nanoparticle size and reaches zero when thermal fluctuations overcome the magnetic anisotropy. Here, we used SQUID-on-tip microscopy to investigate the coercivity of square-shaped CrGeTe3 nanoislands with a wide range of sizes and width-to-thickness aspect ratios. The results reveal an anomalous size-dependent coercivity, with smaller islands exhibiting higher coercivity. The nonconventional scaling of the coercivity in CrGeTe3 nanoislands was found to be inversely proportional to the island width and thickness (1 over wd). This scaling implies that the nanoisland magnetic anisotropy is proportional to the perimeter rather than the volume, suggesting a magnetic edge state. In addition, we observe that 1600 nm wide islands display multi-domain structures with zero net remnant field, corresponding to the magnetic properties of pristine CrGeTe3 flakes. Our findings highlight the significant influence of edge states on the magnetic properties of CrGeTe3 and deepen our understanding of low-dimensional magnetic systems., Comment: Main text: 11 pages, 3 figures. Supplementary information: 10 pages, 9 figures

The growing demand for machine learning in healthcare requires processing increasingly large electronic health record (EHR) datasets, but existing pipelines are not computationally efficient or scalable. In this paper, we introduce meds_reader, an optimized Python package for efficient EHR data processing that is designed to take advantage of many intrinsic properties of EHR data for improved speed. We then demonstrate the benefits of meds_reader by reimplementing key components of two major EHR processing pipelines, achieving 10-100x improvements in memory, speed, and disk usage. The code for meds_reader can be found at https://github.com/som-shahlab/meds_reader., Comment: Findings paper presented at Machine Learning for Health (ML4H) symposium 2024, December 15-16, 2024, Vancouver, Canada, 8 pages

We develop variational search distributions (VSD), a method for finding discrete, combinatorial designs of a rare desired class in a batch sequential manner with a fixed experimental budget. We formalize the requirements and desiderata for this problem and formulate a solution via variational inference. In particular, VSD uses off-the-shelf gradient based optimization routines, can learn powerful generative models for designs, and can take advantage of scalable predictive models. We derive asymptotic convergence rates for learning the true conditional generative distribution of designs with certain configurations of our method. After illustrating the generative model on images, we empirically demonstrate that VSD can outperform existing baseline methods on a set of real sequence-design problems in various biological systems., Comment: 34 pages with supplementary material included

Due to the similarities between electron-nucleus ($eA$) and neutrino-nucleus scattering ($\nu A$), $eA$ data can contribute key information to improve cross-section modeling in $eA$ and hence in $\nu A$ event generators. However, to compare data and generated events, either the data must be radiatively corrected or radiative effects need to be included in the event generators. We implemented a universal radiative corrections program that can be used with all reaction mechanisms and any $eA$ event generator. Our program includes real photon radiation by the incident and scattered electrons, and virtual photon exchange and photon vacuum polarization diagrams. It uses the ``extended peaking" approximation for electron radiation and neglects charged hadron radiation. This method, validated with GENIE, can also be extended to simulate $\nu A$ radiative effects. This work facilitates data-event-generator comparisons used to improve $\nu A$ event generators for the next-generation of neutrino experiments.

When a pulse of light traverses a material, it incurs a time delay referred to as the group delay. Should the group delay experienced by photons be attributed to the time they spend as atomic excitations? However reasonable this connection may seem, it appears problematic when the frequency of the light is close to the atomic resonance, as the group delay becomes negative in this regime. To address this question, we use the cross-Kerr effect to probe the degree of atomic excitation caused by a resonant transmitted photon, by measuring the phase shift on a separate beam that is weak and off-resonant. Our results, over a range of pulse durations and optical depths, are consistent with the recent theoretical prediction that the mean atomic excitation time caused by a transmitted photon (as measured via the time integral of the observed phase shift) equals the group delay experienced by the light. Specifically, we measure mean atomic excitation times ranging from $(-0.82\pm 0.31) \tau_0$ for the most narrowband pulse to $(0.54\pm 0.28) \tau_0$ for the most broadband pulse, where $\tau_0$ is the non-post-selected excitation time, given by the scattering (absorption) probability multiplied by the atomic lifetime $\tau_{\rm sp}$. These results suggest that negative values taken by times such as the group delay have more physical significance than has generally been appreciated.

Nekrashevych associated to each self-similar group action an ample groupoid and a C*-algebra. We provide exact sequences to compute the homology of the groupoid and the K-theory of the C*-algebra in terms of the homology of the group and K-theory of the group C*-algebra via the transfer map and the virtual endomorphism. Complete computations are then performed for the Grigorchuk group, the Grigorchuk--Erschler group, Gupta--Sidki groups and many others. Results are proved more generally for self-similar groupoids. As a consequence of our results and recent results of Xin Li, we are able to show that R\"over's simple group containing the Grigorchuk group is rationally acyclic but has nontrivial Schur multiplier. We prove many more R\"over--Nekrashevych groups of self-similar groups are rationally acyclic.

High-velocity stellar collisions near supermassive black holes may result in a complete disruption of the stars. The initial disruption can have energies on par with supernovae and power a very fast transient. In this work we examine the primary flare that will follow the initial transient, which arises when streams of gas from the disrupted stars travel around the central black hole and collide with each other on the antipodal side with respect to the original collision. We present a simple analytic estimate for the properties of the flare, which depends on the distance of the collision from the central black hole and on the center of mass velocity of the colliding stars. We also present first of their kind radiation-hydrodynamics simulations of a few examples of stellar collisions and post-collision flow of the ejected gas, and calculate the expected bolometric light curves. We find that such post-collision flares are expected to be similar to flares which arise in tidal disruptions events of single stars., Comment: 8 pages,published in ApJL

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Mental health has become a growing concern among university students. While medication is a common treatment, understanding how university students manage their medication for mental health symptoms in real-world practice has not been fully explored. In this study, we conducted semi-structured interviews with university students to understand the unique challenges in the mental health medication management process and their coping strategies, particularly examining the role of various technologies in this process. We discovered that due to struggles with self-acceptance and the interdependent relationship between medication, symptoms, schedules, and life changes, the medication management process for students was a highly dynamic journey involving frequent dosage changes. Thus, students adopted flexible strategies of using minimal technology to manage their medication in different situations while maintaining a high degree of autonomy. Based on our findings, we propose design implications for future technologies to seamlessly integrate into their daily lives and assist students in managing their mental health medications.

Several recent techniques for modifying topological codes with single-qubit Clifford operators have shown high resilience against pure Pauli noise. Paramount to these findings has been the demonstration that several variants exhibit error thresholds often attaining or exceeding the zero-rate hashing bound, a known benchmark for code-capacity noise channels, for biased noise. Additionally, direct comparison with the hashing bound has shown that several topological codes outperform the hashing bound at points of finite Pauli noise biases. Motivated by these observations, we study zero-rate holographic quantum error correction codes, discovering very high threshold values under diverse and finitely-biased noise channels using a tensor-network decoding approach. Our results establish that all codes tested achieve or surpass the hashing bound at various points, ranging from pure 2-Pauli noise ($\eta = 0$) to pure 1-Pauli noise ($\eta = +\infty$), thereby demonstrating that holographic codes exhibit excellent error tolerance in the code-capacity picture. Such findings imply the existence of a structured and systematic method for constructing high-threshold codes suitable for realistically motivated noise channels. To our knowledge, this work is also the first instance of such remarkable threshold behavior in stabilizer quantum codes for the pure 2-Pauli noise regime, as well as for finitely-biased noise channels., Comment: 8 pages, 5 figures, 2 tables

Active soft matter frequently shows motility-induced phase separation (MIPS), where self-propelled particles condensate into clusters with an inner liquid-like structure. Such activity may also result in motility-induced crystallization (MIC) into clusters with an inner crystalline structure. We present a higher-order active Phase-Field-Crystal (PFC) model and employ it to study the interplay of passive (i.e., thermodynamic) and active (i.e., motility-induced) condensation and crystallization. Morphological phase diagrams indicate the various occurring phase coexistences and transitions, e.g., the destruction of passive clusters by density-independent activity and the creation of such clusters by a density-dependent activity. Finally, rotating crystallites are analyzed in some detail.

We implement a variant of the quantum pigeonhole paradox thought experiment to study whether classical counting principles survive in the quantum domain. We observe strong measurements significantly violate the pigeonhole principle (that among three pigeons in two holes, at least one pair must be in the same hole) and the sum rule (that the number of pigeon pairs in the same hole is the sum of the number of pairs across each of the holes) in an ensemble that is pre and postselected into particular separable states. To investigate whether measurement disturbance is a viable explanation for these counter-intuitive phenomena, we employ the first ever variable-strength measurement of a non-local observable. As we decrease the measurement strength, we find the violation of the sum rule decreases, yet the pigeonhole principle remains violated. In the weak limit, the sum rule is restored due to the cancellation between two weak values with equal and opposite imaginary parts. We observe the same kind of cancellation at higher measurement strengths, thus raising the question: do strong measurements have imaginary parts?, Comment: 8 pages, 4 figures

We introduce a new class of qubit codes that we call Evenbly codes, building on a previous proposal of hyperinvariant tensor networks. Its tensor network description consists of local, non-perfect tensors describing CSS codes interspersed with Hadamard gates, placed on a hyperbolic $\{p,q\}$ geometry with even $q\geq 4$, yielding an infinitely large class of subsystem codes. We construct an example for a $\{5,4\}$ manifold and describe strategies of logical gauge fixing that lead to different rates $k/n$ and distances $d$, which we calculate analytically, finding distances which range from $d=2$ to $d \sim n^{2/3}$ in the ungauged case. Investigating threshold performance under erasure, depolarizing, and pure Pauli noise channels, we find that the code exhibits a depolarizing noise threshold of about $19.1\%$ in the code-capacity model and $50\%$ for pure Pauli and erasure channels under suitable gauges. We also test a constant-rate version with $k/n = 0.125$, finding excellent error resilience (about $40\%$) under the erasure channel. Recovery rates for these and other settings are studied both under an optimal decoder as well as a more efficient but non-optimal greedy decoder. We also consider generalizations beyond the CSS tensor construction, compute error rates and thresholds for other hyperbolic geometries, and discuss the relationship to holographic bulk/boundary dualities. Our work indicates that Evenbly codes may show promise for practical quantum computing applications., Comment: 22 pages, 13 figures

Given a presentation of a monoid $M$, combined work of Pride and of Guba and Sapir provides an exact sequence connecting the relation bimodule of the presentation (in the sense of Ivanov) with the first homology of the Squier complex of the presentation, which is naturally a $\mathbb ZM$-bimodule. This exact sequence was used by Kobayashi and Otto to prove the equivalence of Pride's finite homological type (FHT) property with the homological finiteness condition bi-$\mathrm{FP}_3$. Guba and Sapir used this exact sequence to describe the abelianization of a diagram group. We prove here a generalization of this exact sequence of bimodules for presentations of associative algebras. Our proof is more elementary than the original proof for the special case of monoids.

We report the existence of localized states in dipolar Bose-Einstein condensates confined to a tubular geometry. We first perform a bifurcation analysis to track their emergence in a one-dimensional domain for numerical feasibility and find that localized states can become the ground state in suitable parameter regions. Their existence for parameters featuring a supercritical primary bifurcation shows that the latter is not sufficient to conclude that the phase transition is of second order, hence density modulations can jump rather than emerging gradually. Finally, we show that localized states also exist in a three-dimensional domain.

In the standard circuit model of quantum computation, the number and quality of the quantum gates composing the circuit influence the runtime and fidelity of the computation. The fidelity of the decomposition of quantum algorithms, represented as unitary matrices, to bounded depth quantum circuits depends strongly on the set of gates available for the decomposition routine. To investigate this dependence, we explore the design space of discrete quantum gate sets and present a software tool for comparative analysis of quantum processing units and control protocols based on their native gates. The evaluation is conditioned on a set of unitary transformations representing target use cases on the quantum processors. The cost function considers three key factors: (i) the statistical distribution of the decomposed circuits' depth, (ii) the statistical distribution of process fidelities for the approximate decomposition, and (iii) the relative novelty of a gate set compared to other gate sets in terms of the aforementioned properties. The developed software, YAQQ (Yet Another Quantum Quantizer), enables the discovery of an optimized set of quantum gates through this tunable joint cost function. To identify these gate sets, we use the novelty search algorithm, circuit decomposition techniques, and stochastic optimization to implement YAQQ within the Qiskit quantum simulator environment. YAQQ exploits reachability tradeoffs conceptually derived from quantum algorithmic information theory. Our results demonstrate the pragmatic application of identifying gate sets that are advantageous to popularly used quantum gate sets in representing quantum algorithms. Consequently, we demonstrate pragmatic use cases of YAQQ in comparing transversal logical gate sets in quantum error correction codes, designing optimal quantum instruction sets, and compiling to specific quantum processors.

Metallic transition metal dichalcogenides (TMDs), consisting of H-NbSe$_2$, H-NbS$_2$, H-TaSe$_2$ and H-TaS$_2$, remain superconducting down to a thickness of a single layer. In these materials, thickness affects a variety of properties, including Ising protection, two-band superconductivity, and the critical temperature $T_C$, which decreases for the Nb-based, and increases for the Ta-based materials. This contradicting trend is puzzling, and has precluded the development of a unified theory. We approach the question of thickness-evolution of $T_C$ and the superconducting gap $\Delta$ by measuring high-resolution tunneling spectra in TaS$_2$-based stacked devices. Our measurements allow for simultaneous evaluation of $\Delta$, $T_C$, and the upper critical field $H_{C2}$. The latter, we find, is strongly enhanced towards the single-layer limit, following a $H_{C2} \propto \Delta^2$ proportionality ratio. Our main finding is that the same ratio holds for the entire family of metallic TMDs: TaS$_2$ and NbSe$_2$ of all thicknesses, bulk TaSe$_2$ and bulk NbS$_2$, extending over 4 orders of magnitude in $H_{C2}$ and covering both clean and dirty limits. We propose that this tunability across the TMD family is controlled by the competing charge density wave (CDW) phase. Using Gor'kov's theory, we calculate how a CDW order affects the quasiparticle density of states and the resulting $T_C$ and $H_{C2}$. Our results suggest that CDW is the key determinant factor limiting $T_C$ in the TMD family. They also show that $H_{C2}$ is universally enhanced by a factor of two orders of magnitude above the expected value, an effect that remains an open question., Comment: 28 pages, 16 figures

I explicitly compute the Eilenberg-Mac Lane homology of a completely simple semigroup using topological means. I also complete Gray and Pride's investigation into the homological finiteness properties of completely simple semigroups, as well as studying their topological finiteness properties. I give a topological proof of Pride's unpublished homological lower bound for the deficiency of a monoid or semigroup.

Investigating children's embodied learning in mixed-reality environments, where they collaboratively simulate scientific processes, requires analyzing complex multimodal data to interpret their learning and coordination behaviors. Learning scientists have developed Interaction Analysis (IA) methodologies for analyzing such data, but this requires researchers to watch hours of videos to extract and interpret students' learning patterns. Our study aims to simplify researchers' tasks, using Machine Learning and Multimodal Learning Analytics to support the IA processes. Our study combines machine learning algorithms and multimodal analyses to support and streamline researcher efforts in developing a comprehensive understanding of students' scientific engagement through their movements, gaze, and affective responses in a simulated scenario. To facilitate an effective researcher-AI partnership, we present an initial case study to determine the feasibility of visually representing students' states, actions, gaze, affect, and movement on a timeline. Our case study focuses on a specific science scenario where students learn about photosynthesis. The timeline allows us to investigate the alignment of critical learning moments identified by multimodal and interaction analysis, and uncover insights into students' temporal learning progressions.

We prove the Effros-Hahn conjecture for groupoid algebras with coefficients in a sheaf, obtaining as a consequence a description of the ideals in skew inverse semigroup rings. We also use the description of the ideals to characterize when the groupoid algebras with coefficients in a sheaf are von Neumann regular, primitive, semiprimitive, or simple. We apply our results to the topological dynamics of actions of inverse semigroups, describing the existence of dense orbits and minimality in terms of primitivity and simplicity, respectively, of the associated algebra. Moreover, we apply our results to the usual complex groupoid algebra of continuous functions with compact support, used to build the C*-algebra associated with a groupoid, and describe criteria for its simplicity.

Recent research indicates that low-inertia viscoelastic channel flow experiences supercritical non-normal mode elastic instability from laminar to sustained chaotic flow due to finite-size perturbations. The challenge of this study is to elucidate a realization of such a pathway when the intensity of the elastic wave is too low to amplify velocity fluctuations above the instability onset. The study identifies two subregions in the transition flow regime at Weissenberg number $Wi>Wi_c$, the instability onset. In the lower subregion at $Wi_c\leq Wi\leq 300$, we discover periodic spikes in the streamwise velocity time series $u(t)$ that appear in the chaotic power spectrum as low-frequency, high-intensity peaks resembling stochastic resonance (SR). In contrast, the spanwise velocity power spectrum, $E_w$, remains flat with low-intensity, noisy, and broad elastic wave peaks. The spikes significantly distort the probability density function of $u$, initiating and amplifying random streaks and wall-normal vorticity fluctuations. The SR appearance is similar to dynamical systems where chaotic attractor and limit cycle interact with external white noise. This similarity is confirmed by presenting a phase portrait in two subregions of the transition regime. In the upper subregion at $Wi>400$ the periodic spikes disappear and $E_w$ becomes chaotic with a large intensity elastic wave sufficient to self-organize and synchronize the streaks into cycles and to amplify the wall normal vorticity according to a recently proposed mechanism., Comment: 13 pages, 13 figures

We present the first combined tuning, using GENIE, of four transverse kinematic imbalance measurements of neutrino-hydrocarbon scattering, both with and without pion final states, from the T2K and MINERvA experiments. As a proof of concept, we have simultaneously tuned the initial state and final-state interaction models (SF-CFG and hA, respectively), producing a new effective model that more accurately describes the data., Comment: 18 pages, 17 figures, accepted version in PRD

The goal of this paper is to use topological methods to compute $\mathrm{Ext}$ between irreducible representations of von Neumann regular monoids in which Green's $\mathscr L$- and $\mathscr J$-relations coincide (e.g., left regular bands). Our results subsume those of S.~Margolis, F.~Saliola, and B.~Steinberg, \emph{Combinatorial topology and the global dimension of algebras arising in combinatorics}, J. Eur. Math. Soc. (JEMS), \textbf{17}, 3037--3080 (2015). Applications include computing $\mathrm{Ext}$ between arbitrary simple modules and computing a quiver presentation for the algebra of Hsiao's monoid of ordered $G$-partitions (connected to the Mantaci-Reutenauer descent algebra for the wreath product $G\wr S_n$). We show that this algebra is Koszul, compute its Koszul dual and compute minimal projective resolutions of all the simple modules using topology. More generally, these results work for CW left regular bands of abelian groups. These results generalize the results of S.~Margolis, F.~V. Saliola, and B.~Steinberg. \emph{Cell complexes, poset topology and the representation theory of algebras arising in algebraic combinatorics and discrete geometry}, Mem. Amer. Math. Soc., \textbf{274}, 1--135, (2021)., Comment: This is the second part of arXiv:2306.16379, the original version (v1,v2) was too long and split in two