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Let $G=(V,E)$ be a graph on $n$ vertices, and let $\lambda_1(L(G))\ge \cdots\ge \lambda_{n-1}(L(G))\ge \lambda_n(L(G))=0$ be the eigenvalues of its Laplacian matrix $L(G)$. Brouwer conjectured that for every $1\le k\le n$, $\sum_{i=1}^k \lambda_i(L(G)) \le |E|+\binom{k+1}{2}$. Here, we prove the following weak version of Brouwer's conjecture: For every $1\leq k \leq n$, \[ \sum_{i=1}^k \lambda_i(L(G)) \leq |E|+k^2+15k\log{k}+65k. \] For a graph $G=(V,E)$, we define its partition density $\tilde{\rho}(G)$ as the maximum, over all subgraphs $H$ of $G$, of the ratio between the number of edges of $H$ and the number of vertices in the largest connected component of $H$. Our argument relies on the study of the structure of the graphs $G$ satisfying $\tilde{\rho}(G)< k$. In particular, using a result of Alon, McDiarmid and Reed, we show that every such graph can be decomposed into at most $k+ 15\log{k}+65$ edge-disjoint star forests (that is, forests whose connected components are all isomorphic to stars). In addition, we show that for every graph $G=(V,E)$ and every $1\le k\le |V|$, \[ \sum_{i=1}^k \lambda_i(L(G)) \leq |E|+k\cdot \nu(G) + \left\lfloor\frac{k}{2}\right\rfloor, \] where $\nu(G)$ is the maximum size of a matching in $G$.

The discontinuous operations inherent in quantization and sparsification introduce obstacles to backpropagation. This is particularly challenging when training deep neural networks in ultra-low precision and sparse regimes. We propose a novel, robust, and universal solution: a denoising affine transform that stabilizes training under these challenging conditions. By formulating quantization and sparsification as perturbations during training, we derive a perturbation-resilient approach based on ridge regression. Our solution employs a piecewise constant backbone model to ensure a performance lower bound and features an inherent noise reduction mechanism to mitigate perturbation-induced corruption. This formulation allows existing models to be trained at arbitrarily low precision and sparsity levels with off-the-shelf recipes. Furthermore, our method provides a novel perspective on training temporal binary neural networks, contributing to ongoing efforts to narrow the gap between artificial and biological neural networks.

Due to their short orbital periods and relatively high flux ratios, irradiated brown dwarfs in binaries with white dwarfs offer better opportunities to study irradiated atmospheres than hot Jupiters, which have lower planet-to-star flux ratios. WD1032+011 is an eclipsing, tidally locked white dwarf-brown dwarf binary with a 9950 K white dwarf orbited by a 69.7 M$_{Jup}$ brown dwarf in a 0.09 day orbit. We present time-resolved Hubble Space Telescope Wide Field Camera 3 spectrophotometric data of WD1032+011. We isolate the phase-dependent spectra of WD1032+011B, finding a 210 K difference in brightness temperature between the dayside and nightside. The spectral type of the brown dwarf is identified as L1 peculiar, with atmospheric retrievals and comparison to field brown dwarfs showing evidence for a cloud-free atmosphere. The retrieved temperature of the dayside is $1748^{+66}_{-67}$ K, with a nightside temperature of $1555^{+76}_{-62}$ K, showing an irradiation-driven temperature contrast coupled with inefficient heat redistribution from the dayside to the nightside. The brown dwarf radius is inflated, likely due to the constant irradiation from the white dwarf, making it the only known inflated brown dwarf in an eclipsing white dwarf-brown dwarf binary., Comment: 20 pages, 23 figures. Accepted for Publication in MNRAS

We advocate for a large scale imaging survey of nearby young moving groups and star-forming regions to directly detect exoplanets over an unexplored range of masses, ages and orbits. Discovered objects will be identified early enough in JWST's lifetime to leverage its unparalleled capabilities for long-term atmospheric characterisation, and will uniquely complement the known population of exoplanets and brown dwarfs. Furthermore, this survey will constrain the occurrence of the novel wide sub-Jovian exoplanet population, informing multiple theories of planetary formation and evolution. Observations with NIRCam F200W+F444W dual-band coronagraphy will readily provide sub-Jupiter mass sensitivities beyond ~0.4" (F444W) and can also be used to rule out some contaminating background sources (F200W). At this large scale, targets can be sequenced by spectral type to enable robust self-referencing for PSF subtraction. This eliminates the need for dedicated reference observations required by GO programs and dramatically increases the overall science observing efficiency. With an exposure of ~30 minutes per target, the sub-Jupiter regime can be explored across 250 targets for ~400 hours of exposure time including overheads. An additional, pre-allocated, ~100 hours of observing time would enable rapid multi-epoch vetting of the lowest mass detections (which are undetectable in F200W). The total time required for a survey such as this is not fixed, and could be scaled in conjunction with the minimum number of detected exoplanet companions., Comment: 5 pages, 2 figures. This white paper was submitted following a call from the "Working Group on Strategic Exoplanet Initiatives with HST and JWST" (https://sites.google.com/view/exoplanet-strategy-wg, final report in 10.48550/arXiv.2404.02932)

Large area observations of extragalactic deep fields with the James Webb Space Telescope (JWST) have provided a wealth of candidate low-mass L- and T-class brown dwarfs. The existence of these sources, which are at derived distances of hundreds of parsecs to several kiloparsecs from the Sun, has strong implications for the low-mass end of the stellar initial mass function, and the link between stars and planets at low metallicities. In this letter, we present a JWST/NIRSpec PRISM spectrum of brown dwarf JADES-GS-BD-9, confirming its photometric selection from observations taken as part of the JWST Advanced Deep Extragalactic Survey (JADES) program. Fits to this spectrum indicate that the brown dwarf has an effective temperature of 800-900K (T5 - T6) at a distance of $1.8 - 2.3$kpc from the Sun, with evidence of the source being at low metallicity ([M/H] $\leq -0.5$). Finally, because of the cadence of JADES NIRCam observations of this source, we additionally uncover a proper motion between the 2022 and 2023 centroids, and we measure a proper motion of $20 \pm 4$ mas yr$^{-1}$ (a transverse velocity of 214 km s$^{-1}$ at 2.25 kpc). At this predicted metallicity, distance, and transverse velocity, it is likely that this source belongs either to the edge of the Milky Way thick disk or the galactic halo. This spectral confirmation demonstrates the efficacy of photometric selection of these important sources across deep extragalactic JWST imaging., Comment: 10 pages, 4 figures, Accepted for publication in The Astrophysical Journal, August 30 2024

Video frame interpolation (VFI) aims to synthesize intermediate frames in between existing frames to enhance visual smoothness and quality. Beyond the conventional methods based on the reconstruction loss, recent works employ the high quality generative models for perceptual quality. However, they require complex training and large computational cost for modeling on the pixel space. In this paper, we introduce disentangled Motion Modeling (MoMo), a diffusion-based approach for VFI that enhances visual quality by focusing on intermediate motion modeling. We propose disentangled two-stage training process, initially training a frame synthesis model to generate frames from input pairs and their optical flows. Subsequently, we propose a motion diffusion model, equipped with our novel diffusion U-Net architecture designed for optical flow, to produce bi-directional flows between frames. This method, by leveraging the simpler low-frequency representation of motions, achieves superior perceptual quality with reduced computational demands compared to generative modeling methods on the pixel space. Our method surpasses state-of-the-art methods in perceptual metrics across various benchmarks, demonstrating its efficacy and efficiency in VFI. Our code is available at: https://github.com/JHLew/MoMo

Compared to the wide array of advanced Monte Carlo methods supported by modern probabilistic programming languages (PPLs), PPL support for variational inference (VI) is less developed: users are typically limited to a predefined selection of variational objectives and gradient estimators, which are implemented monolithically (and without formal correctness arguments) in PPL backends. In this paper, we propose a more modular approach to supporting variational inference in PPLs, based on compositional program transformation. In our approach, variational objectives are expressed as programs, that may employ first-class constructs for computing densities of and expected values under user-defined models and variational families. We then transform these programs systematically into unbiased gradient estimators for optimizing the objectives they define. Our design enables modular reasoning about many interacting concerns, including automatic differentiation, density accumulation, tracing, and the application of unbiased gradient estimation strategies. Additionally, relative to existing support for VI in PPLs, our design increases expressiveness along three axes: (1) it supports an open-ended set of user-defined variational objectives, rather than a fixed menu of options; (2) it supports a combinatorial space of gradient estimation strategies, many not automated by today's PPLs; and (3) it supports a broader class of models and variational families, because it supports constructs for approximate marginalization and normalization (previously introduced only for Monte Carlo inference). We implement our approach in an extension to the Gen probabilistic programming system (genjax.vi, implemented in JAX), and evaluate on several deep generative modeling tasks, showing minimal performance overhead vs. hand-coded implementations and performance competitive with well-established open-source PPLs.

This article presents GenSQL, a probabilistic programming system for querying probabilistic generative models of database tables. By augmenting SQL with only a few key primitives for querying probabilistic models, GenSQL enables complex Bayesian inference workflows to be concisely implemented. GenSQL's query planner rests on a unified programmatic interface for interacting with probabilistic models of tabular data, which makes it possible to use models written in a variety of probabilistic programming languages that are tailored to specific workflows. Probabilistic models may be automatically learned via probabilistic program synthesis, hand-designed, or a combination of both. GenSQL is formalized using a novel type system and denotational semantics, which together enable us to establish proofs that precisely characterize its soundness guarantees. We evaluate our system on two case real-world studies -- an anomaly detection in clinical trials and conditional synthetic data generation for a virtual wet lab -- and show that GenSQL more accurately captures the complexity of the data as compared to common baselines. We also show that the declarative syntax in GenSQL is more concise and less error-prone as compared to several alternatives. Finally, GenSQL delivers a 1.7-6.8x speedup compared to its closest competitor on a representative benchmark set and runs in comparable time to hand-written code, in part due to its reusable optimizations and code specialization., Comment: 54 pages, 30 figures, 1 table, published at PLDI 2024

We prove that it is impossible to distinguish two spatially overlapping fluorescent molecules from a single rotating molecule, even if one modulates the polarization of pumping light or the detection dipole-spread function (DSF). If the target is known to be a dipole pair, existing imaging methods perform poorly for measuring their angular separation. We propose simultaneously modulating the excitation polarization and DSF, which demonstrates robust discrimination between dipole pairs versus single molecules. Our method improves the precision of measuring centroid orientation by 50% and angular separation by 4- to 6-fold over existing techniques., Comment: 6 pages, 4 figures

The Simons Observatory will map the temperature and polarization over half of the sky, at millimeter wavelengths in six spectral bands from the Atacama Desert in Chile. These data will provide new insights into the genesis, content, and history of our Universe; the astrophysics of galaxies and galaxy clusters; objects in our solar system; and time-varying astrophysical phenomena. This ambitious new instrument suite, initially comprising three 0.5 m small-aperture telescopes and one 6 m large aperture telescope, is designed using a common combination of new technologies and new implementations to realize an observatory significantly more capable than the previous generation. In this paper, we present the pre-deployment performance of the first mid-frequency "optics tube" which will be fielded on the large aperture telescope with sensitivity to the 90 and 150 GHz spectral bands. This optics tube contains lenses, filters, detectors, and readout components, all of which operate at cryogenic temperatures. It is one of seven that form the core of the large aperture telescope receiver in its initial deployment. We describe this optics tube, including details of comprehensive testing methods, new techniques for beam and passband characterization, and its measured performance. The performance metrics include beams, optical efficiency, passbands, and forecasts for the on-sky performance of the system. We forecast a sensitivity that exceeds the requirements of the large aperture telescope with greater than 30% margin in each spectral band, and predict that the instrument will realize diffraction-limited performance and the expected detector passbands.

The Simons Observatory (SO) is a cosmic microwave background (CMB) survey experiment that includes small-aperture telescopes (SATs) observing from an altitude of 5,200 m in the Atacama Desert in Chile. The SO SATs will cover six spectral bands between 27 and 280 GHz to search for primordial B-modes to a sensitivity of $\sigma(r)=0.002$, with quantified systematic errors well below this value. Each SAT is a self-contained cryogenic telescope with a 35$^\circ$ field of view, 42 cm diameter optical aperture, 40 K half-wave plate, 1 K refractive optics, and $<0.1$ K focal plane that holds $>12,000$ TES detectors. We describe the nominal design of the SATs and present details about the integration and testing for one operating at 93 and 145 GHz.

Quantization-aware training comes with a fundamental challenge: the derivative of quantization functions such as rounding are zero almost everywhere and nonexistent elsewhere. Various differentiable approximations of quantization functions have been proposed to address this issue. In this paper, we prove that when the learning rate is sufficiently small, a large class of weight gradient estimators is equivalent with the straight through estimator (STE). Specifically, after swapping in the STE and adjusting both the weight initialization and the learning rate in SGD, the model will train in almost exactly the same way as it did with the original gradient estimator. Moreover, we show that for adaptive learning rate algorithms like Adam, the same result can be seen without any modifications to the weight initialization and learning rate. We experimentally show that these results hold for both a small convolutional model trained on the MNIST dataset and for a ResNet50 model trained on ImageNet.

FM1/NM/FM2 trilayers have garnered considerable attention because of their potential in spintronic applications. A thorough investigation of the spin transport properties of these trilayers is therefore important. Asymmetric trilayers, particularly those including Platinum (Pt) as a spacer are less explored. Pt mediates exchange coupling between the two FM layers and thus offers a unique platform to investigate the spin-transport properties under indirect exchange coupling conditions through the spin-pumping mechanism. Our analytical focus on the acoustic mode of the ferromagnetic resonance spectrum, facilitated by the distinct magnetizations of the Ni80Fe20 and Co layers, allows for the isolation of individual layer resonances. The derived spin-pumping induced damping of the Ni80Fe20 and Co layers reveals a direct dependence on the Pt spacer thickness. Furthermore, fitting of the weighted average of the damping parameters to the spin-pumping induced damping of acoustic mode reveals that the observed FMR spectra is indeed a result of the in-phase precession of the magnetizations in two FM layers. The extracted effective spin-mixing conductance varies with the FM/NM interface, specifically 1.72x10^19 m^(-2) at the Ni80Fe20/Pt and 4.07x10^19 m^(-2) at the Co/Pt interface, indicating a strong correlation with interfacial characteristics. Additionally, we deduce the spin diffusion length in Pt to be between 1.02 and 1.55 nm and calculate the interfacial spin transparency and spin current densities, highlighting significant disparities between the Ni80Fe20/Pt and Co/Pt interfaces. This detailed analysis enhances our understanding of spin transport in Ni80Fe20/Pt/Co trilayers. It offers insights important for advancing spintronic device design and lays the groundwork for future theoretical investigations of trilayer system., Comment: 16 pages, 11 figures

Brown dwarfs in ultra-short period orbits around white dwarfs offer a unique opportunity to study the properties of tidally-locked, fast rotating (1-3 hr), and highly-irradiated atmospheres. Here, we present phase-resolved spectrophotometry of the white dwarf-brown dwarf (WD-BD) binary SDSS 1557, which is the fifth WD-BD binary in our six-object sample. Using the Hubble Space Telescope Wide Field Camera 3 Near-infrared G141 instrument, the 1.1 to 1.7 $\mu$m phase curves show rotational modulations with semi-amplitudes of 10.5$\pm$0.1%. We observe a wavelength dependent amplitude, with longer wavelengths producing larger amplitudes, while no wavelength dependent phase shifts were identified. The phase-resolved extracted BD spectra exhibit steep slopes and are nearly featureless. A simple radiative energy redistribution atmospheric model recreates the hemisphere integrated brightness temperatures at three distinct phases and finds evidence for weak redistribution efficiency. Our model also predicts a higher inclination than previously published. We find that SDSS 1557B, the second most irradiated BD in our sample, is likely dominated by clouds on the night side, whereas the featureless day side spectrum is likely dominated by H$^-$ opacity and a temperature inversion, much like the other highly-irradiated BD EPIC2122B., Comment: 19 pages and 11 figures. Accepted to Astrophysical Journal

Low-precision quantization is recognized for its efficacy in neural network optimization. Our analysis reveals that non-quantized elementwise operations which are prevalent in layers such as parameterized activation functions, batch normalization, and quantization scaling dominate the inference cost of low-precision models. These non-quantized elementwise operations are commonly overlooked in SOTA efficiency metrics such as Arithmetic Computation Effort (ACE). In this paper, we propose ACEv2 - an extended version of ACE which offers a better alignment with the inference cost of quantized models and their energy consumption on ML hardware. Moreover, we introduce PikeLPN, a model that addresses these efficiency issues by applying quantization to both elementwise operations and multiply-accumulate operations. In particular, we present a novel quantization technique for batch normalization layers named QuantNorm which allows for quantizing the batch normalization parameters without compromising the model performance. Additionally, we propose applying Double Quantization where the quantization scaling parameters are quantized. Furthermore, we recognize and resolve the issue of distribution mismatch in Separable Convolution layers by introducing Distribution-Heterogeneous Quantization which enables quantizing them to low-precision. PikeLPN achieves Pareto-optimality in efficiency-accuracy trade-off with up to 3X efficiency improvement compared to SOTA low-precision models., Comment: Accepted in CVPR 2024. 10 Figures, 9 Tables

Within the framework of natural orbital functional theory, having a convenient representation of the occupation numbers and orbitals becomes critical for the computational performance of the calculations. Recognizing this, we propose an innovative parametrization of the occupation numbers that takes advantage of the electron-pairing approach used in Piris natural orbital functionals through the adoption of the softmax function, a pivotal component in modern deep-learning models. Our approach not only ensures adherence to the N-representability of the first-order reduced density matrix (1RDM) but also significantly enhances the computational efficiency of 1RDM functional theory calculations. The effectiveness of this alternative parameterization approach was assessed using the W4-17-MR molecular set, which demonstrated faster and more robust convergence compared to previous implementations., Comment: 13 pages, 6 Figures

Listing and counting triangles in graphs is a key algorithmic kernel for network analyses, including community detection, clustering coefficients, k-trusses, and triangle centrality. In this paper, we propose the novel concept of a cover-edge set that can be used to find triangles more efficiently. Leveraging the breadth-first search (BFS) method, we can quickly generate a compact cover-edge set. Novel sequential and parallel triangle counting algorithms that employ cover-edge sets are presented. The novel sequential algorithm performs competitively with the fastest previous approaches on both real and synthetic graphs, such as those from the Graph500 Benchmark and the MIT/Amazon/IEEE Graph Challenge. We implement 22 sequential algorithms for performance evaluation and comparison. At the same time, we employ OpenMP to parallelize 11 sequential algorithms, presenting an in-depth analysis of their parallel performance. Furthermore, we develop a distributed parallel algorithm that can asymptotically reduce communication on massive graphs. In our estimate from massive-scale Graph500 graphs, our distributed parallel algorithm can reduce the communication on a scale~36 graph by 1156x and on a scale~42 graph by 2368x. Comprehensive experiments are conducted on the recently launched Intel Xeon 8480+ processor and shed light on how graph attributes, such as topology, diameter, and degree distribution, can affect the performance of these algorithms.

Characterising charge transport in a material is central to the understanding of its electrical properties, and can usually only be inferred from bulk measurements of derived quantities such as current flow. Establishing connections between host material impurities and transport properties in emerging electronics materials, such as wide bandgap semiconductors, demands new diagnostic methods tailored to these unique systems, and the presence of optically-active defect centers in these materials offers a non-perturbative, in-situ characterisation system. Here, we combine charge-state sensitive optical microscopy and photoelectric detection of nitrogen-vacancy (NV) centres to directly image the flow of charge carriers inside a diamond optoelectronic device, in 3D and with temporal resolution. We optically control the charge state of background impurities inside the diamond on-demand, resulting in drastically different current flow such as filamentary channels nucleating from specific, defective regions of the device. We then optically engineered conducting channels that control carrier flow, key steps towards optically reconfigurable, wide bandgap designer optoelectronics. We anticipate our approach might be extended to probe other wide-bandgap semiconductors (SiC, GaN) relevant to present and emerging electronic technologies., Comment: 6 pages main text + 11 pages supplement, 3 figures, 8 supplementary figures. Comments welcome

The launch of the James Webb Space Telescope (JWST) marks a pivotal moment for precise atmospheric characterization of Y dwarfs, the coldest brown dwarf spectral type. In this study, we leverage moderate spectral resolution observations (R $\sim$ 2700) with the G395H grating of the Near-Infrared Spectrograph (NIRSpec) onboard of JWST to characterize the nearby (9.9 pc) Y dwarf WISEPA J182831.08+265037.8 (WISE 1828). With the NIRSpec G395H 2.88-5.12 $\mathrm{\mu}$m spectrum, we measure the abundances of CO, CO$_2$, CH$_4$, H$_2$S, NH$_3$, and H$_2$O, which are the major carbon, nitrogen, oxygen, and sulfur bearing species in the atmosphere. Based on the retrieved volume mixing ratios with the atmospheric retrieval framework CHIMERA, we report that the C/O ratio is $0.45 \pm 0.01$, close to the solar C/O value of 0.55, and the metallicity to be +0.30 $\pm$ 0.02 dex. Comparison between the retrieval results with the forward modeling results suggests that the model bias for C/O and metallicity could be as high as 0.03 and 0.97 dex respectively. We also report a lower limit of the $^{12}$CO/$^{13}$CO ratio of $>40 $, being consistent with the nominal solar value of 90. Our results highlight the potential of JWST in measuring the C/O ratios down to percent-level precision and characterizing isotopologues of cold planetary atmospheres similar to WISE 1828., Comment: 18 pages + references, including 11 figures, accepted for publication in The Astronomical Journal

Polarization information of the light can provide rich cues for computer vision and scene understanding tasks, such as the type of material, pose, and shape of the objects. With the advent of new and cheap polarimetric sensors, this imaging modality is becoming accessible to a wider public for solving problems such as pose estimation, 3D reconstruction, underwater navigation, and depth estimation. However, we observe several limitations regarding the usage of this sensorial modality, as well as a lack of standards and publicly available tools to analyze polarization images. Furthermore, although polarization camera manufacturers usually provide acquisition tools to interface with their cameras, they rarely include processing algorithms that make use of the polarization information. In this paper, we review recent advances in applications that involve polarization imaging, including a comprehensive survey of recent advances on polarization for vision and robotics perception tasks. We also introduce a complete software toolkit that provides common standards to communicate with and process information from most of the existing micro-grid polarization cameras on the market. The toolkit also implements several image processing algorithms for this modality, and it is publicly available on GitHub: https://github.com/vibot-lab/Pola4all_JEI_2023.

Using only 34 published tables, we reconstruct five variables (census block, sex, age, race, and ethnicity) in the confidential 2010 Census person records. Using the 38-bin age variable tabulated at the census block level, at most 20.1% of reconstructed records can differ from their confidential source on even a single value for these five variables. Using only published data, an attacker can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. The tabular publications in Summary File 1 thus have prohibited disclosure risk similar to the unreleased confidential microdata. Reidentification studies confirm that an attacker can, within blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with nonmodal characteristics) with 95% accuracy, the same precision as the confidential data achieve and far greater than statistical baselines. The flaw in the 2010 Census framework was the assumption that aggregation prevented accurate microdata reconstruction, justifying weaker disclosure limitation methods than were applied to 2010 Census public microdata. The framework used for 2020 Census publications defends against attacks that are based on reconstruction, as we also demonstrate here. Finally, we show that alternatives to the 2020 Census Disclosure Avoidance System with similar accuracy (enhanced swapping) also fail to protect confidentiality, and those that partially defend against reconstruction attacks (incomplete suppression implementations) destroy the primary statutory use case: data for redistricting all legislatures in the country in compliance with the 1965 Voting Rights Act.

Complex organic molecules (COMs) detected in the gas phase are thought to be mostly formed on icy grains, but no unambiguous detection of icy COMs larger than CH3OH has been reported so far. Exploring this matter in more detail has become possible with the JWST the critical 5-10 $\mu$m range. In the JOYS+ program, more than 30 protostars are being observed with the MIRI/MRS. This study explores the COMs ice signatures in the low and high-mass protostar, IRAS 2A and IRAS 23385, respectively. We fit continuum and silicate subtracted observational data with IR laboratory ice spectra. We use the ENIIGMA fitting tool to find the best fit between the lab data and the observations and to performs statistical analysis of the solutions. We report the best fits for the spectral ranges between 6.8 and 8.6 $\mu$m in IRAS 2A and IRAS 23385, originating from simple molecules, COMs, and negative ions. The strongest feature in this range (7.7 $\mu$m) is dominated by CH4 and has contributions of SO2 and OCN-. Our results indicate that the 7.2 and 7.4 $\mu$m bands are mostly dominated by HCOO-. We find statistically robust detections of COMs based on multiple bands, most notably CH3CHO, CH3CH2OH, and CH3OCHO. The likely detection of CH3COOH is also reported. The ice column density ratios between CH3CH2OH and CH3CHO of IRAS 2A and IRAS 23385, suggests that these COMs are formed on icy grains. Finally, the derived ice abundances for IRAS 2A correlate well with those in comet 67P/GC within a factor of 5. Based on the MIRI/MRS data, we conclude that COMs are present in interstellar ices, thus providing additional proof for a solid-state origin of these species in star-forming regions. The good correlation between the ice abundances in comet 67P and IRAS 2A is in line with the idea that cometary COMs can be inherited from the early protostellar phases., Comment: Accepted for publication in A&A

The widespread application of metal additive manufacturing (AM) is limited by the ability to control the complex interactions between the energy source and the feedstock material. Here we develop a generalizable process to introduce nanoscale grooves to the surface of metal powders which increases the powder absorptivity by up to 70% during laser powder bed fusion. Absorptivity enhancements in copper, copper-silver, and tungsten enables energy efficient manufacturing, with printing of pure copper at relative densities up to 92% using laser energy densities as low as 82 J/mm^3. Simulations show the enhanced powder absorptivity results from plasmon-enabled light concentration in nanoscale grooves combined with multiple scattering events. The approach taken here demonstrates a general method to enhance the absorptivity and printability of reflective and refractory metal powders by changing the surface morphology of the feedstock without altering its composition.

The unprecedented medium-resolution (R~1500-3500) near- and mid-infrared (1-18um) spectrum provided by JWST for the young (140+/-20Myr) low-mass (12-20MJup) L-T transition (L7) companion VHS1256b gives access to a catalogue of molecular absorptions. In this study, we present a comprehensive analysis of this dataset utilizing a forward modelling approach, applying our Bayesian framework, ForMoSA. We explore five distinct atmospheric models to assess their performance in estimating key atmospheric parameters: Teff, log(g), [M/H], C/O, gamma, fsed, and R. Our findings reveal that each parameter's estimate is significantly influenced by factors such as the wavelength range considered and the model chosen for the fit. This is attributed to systematic errors in the models and their challenges in accurately replicating the complex atmospheric structure of VHS1256b, notably the complexity of its clouds and dust distribution. To propagate the impact of these systematic uncertainties on our atmospheric property estimates, we introduce innovative fitting methodologies based on independent fits performed on different spectral windows. We finally derived a Teff consistent with the spectral type of the target, considering its young age, which is confirmed by our estimate of log(g). Despite the exceptional data quality, attaining robust estimates for chemical abundances [M/H] and C/O, often employed as indicators of formation history, remains challenging. Nevertheless, the pioneering case of JWST's data for VHS1256b has paved the way for future acquisitions of substellar spectra that will be systematically analyzed to directly compare the properties of these objects and correct the systematics in the models., Comment: 32 pages, 16 figures, 6 tables, 2 appendices

A graph is called $d$-rigid if there exists a generic embedding of its vertex set into $\mathbb{R}^d$ such that every continuous motion of the vertices that preserves the lengths of all edges actually preserves the distances between all pairs of vertices. The rigidity of a graph is the maximal $d$ such that the graph is $d$-rigid. We present new sufficient conditions for the $d$-rigidity of a graph in terms of the existence of ``rigid partitions'' -- partitions of the graph that satisfy certain connectivity properties. This extends previous results by Crapo, Lindemann, and Lew, Nevo, Peled and Raz. As an application, we present new results on the rigidity of highly-connected graphs, random graphs, random bipartite graphs, pseudorandom graphs, and dense graphs. In particular, we prove that random $C d\log d$-regular graphs are typically $d$-rigid, demonstrate the existence of a giant $d$-rigid component in sparse random binomial graphs, and show that the rigidity of relatively sparse random binomial bipartite graphs is roughly the same as that of the complete bipartite graph, which we consider an interesting phenomenon. Furthermore, we show that a graph admitting $\binom{d+1}{2}$ disjoint connected dominating sets is $d$-rigid. This implies a weak version of the Lov\'asz--Yemini conjecture on the rigidity of highly-connected graphs. We also present an alternative short proof for a recent result by Lew, Nevo, Peled, and Raz, which asserts that the hitting time for $d$-rigidity in the random graph process typically coincides with the hitting time for minimum degree $d$., Comment: 30 pages. In this updated version, we have added a theorem concerning the rigidity of dense graphs and incorporated references to Vill\'anyi's recent resolution of the Lov\'asz-Yemini conjecture

In this work, we extend the Piris natural orbital functionals (PNOFs) to excited states by coupling their reconstructed second-order reduced density matrices with the extended random-phase approximation (ERPA). We have named the general implementation as PNOF-ERPA, and we refer to specific cases as PNOF-ERPA0, PNOF-ERPA1 and PNOF-ERPA2, according to how the excitation operator is built. The approaches have been tested in the first excited states of H2, HeH+, LiH and Li2, showing good results compared with the full configuration interaction (FCI) method. As expected, an increase in accuracy is observed when going from ERPA0 to ERPA1 and ERPA2. We have also studied the effect of electron correlation included by PNOF5, PNOF7 and the recently proposed global NOF (GNOF) on the predicted excited states. PNOF5 appears to be good and may even provide better results in very small systems, but including more electron correlation becomes important as the system size increases, where PNOF7 and GNOF provide better results. This effect can already be seen in the excitation energies of the neon atom, where GNOF provides more accurate values than PNOF5 and PNOF7. Overall, the extension of PNOF to excited states has been successful, making the PNOF-ERPA method promising for further applications., Comment: 18 pages, 10 figures

In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm$^{2}$ dose). Peaks in the Raman fingerprint region (300$\unicode{x2013}$1900 cm$^{-1}$), in particular, in the amide I band (1600$\unicode{x2013}$1700 cm$^{-1}$), can be used to quantify the percentage of protein secondary structures. Under this band, hidden signals of $\mathrm{C}$=$\mathrm{O}$ stretching, belonging to different structures, are superimposed$\unicode{x2014}$producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of NIR-exposed tubulin, characterized by a notable decrease in alpha-helix content and a concurrent increase in beta-sheets compared to the control samples. The alpha-helix to beta-sheet transition suggests that PBM reduces microtubule stability and introduces dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer's disease., Comment: 15 pages, 3 figures

A statewide coalition of nearly 50 experts -- including doctors, medical and environmental health researchers, educators, youth and community groups -- worked together to explore the challenges of climate change from the perspective of children's health and education. The insights and recommendations are published in this report. It is presented in four parts: (1) demonstrates how climate change is impacting children's physical health, mental health, and access to educational opportunity; (2) assesses schools' current capacity to operate safely and reliably, to safeguard students' health and wellbeing, and to develop students' climate literacy; and (3) lays out the authors' vision for climate-resilient and sustainable schools; and (4) propose a statewide Master Plan process, engaging key agencies and stakeholders, as an essential first step toward fully operationalizing the vision for climate-resilient and sustainable schools. [For the executive summary, see ED629546. This report was written in collaboration with the Stanford University's Sean N. Parker Center for Allergy and Asthma Research, Center for Innovation in Global Health, Action Lab for Planetary Health (ALPHA), UndauntedK12, and Ten Strands. The report was sponsored by the 11th Hour Project, Schmidt Family Foundation.]