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Labor organization efforts grew following the pandemic in the United States at tech companies, automakers, and even higher education institutions. This brief examines unionization trends at private colleges and universities from 2007 to 2023, revealing staff as the main force behind unionization attempts, followed by contingent faculty. Major unions like the SEIU and the AFL-CIO play significant roles in representing college and university employees. This study underscores the importance of understanding historic unionization efforts, shedding light on often overlooked staff categories like maintenance and security.

Lattice gauge theories (LGTs) can be employed to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-body interactions in materials. Studying dynamical properties of emergent phases can be challenging as it requires solving many-body problems that are generally beyond perturbative limits. We investigate the dynamics of local excitations in a $\mathbb{Z}_2$ LGT using a two-dimensional lattice of superconducting qubits. We first construct a simple variational circuit which prepares low-energy states that have a large overlap with the ground state; then we create particles with local gates and simulate their quantum dynamics via a discretized time evolution. As the effective magnetic field is increased, our measurements show signatures of transitioning from deconfined to confined dynamics. For confined excitations, the magnetic field induces a tension in the string connecting them. Our method allows us to experimentally image string dynamics in a (2+1)D LGT from which we uncover two distinct regimes inside the confining phase: for weak confinement the string fluctuates strongly in the transverse direction, while for strong confinement transverse fluctuations are effectively frozen. In addition, we demonstrate a resonance condition at which dynamical string breaking is facilitated. Our LGT implementation on a quantum processor presents a novel set of techniques for investigating emergent particle and string dynamics.

The interest of oil industry in increasing heavy oil production has promoted the use of enhanced oil recovery techniques such as $CO_{2}$ injection, which produce a decrease of oil viscosity and displacement of heavy oil from reservoir to surface. The design of these processes requires accurate data of densities, viscosities or surface tensions of ($CO_{2}$ + hydrocarbon) mixtures in order to simulate the behaviour of these mixtures in the reservoir. An automated Anton Paar DMA HPM vibrating-tube densimeter was used to measure densities of this kind of mixtures, and a new mixture injection system, by means of two syringe pumps, was developed for the densimeter. The equipment operates at high pressure, which is controlled through a back pressure valve and a variable volume cylinder with a stepper motor. The estimated standard uncertainty of the density is $\mathrm{\pm0.9 \ kg \cdot m^{-3}}$ at temperatures below 373.15 K and pressure range (0.1-140) MPa.In this paper, the densities of the mixtures ($CO_{2}$ + $n$-decane), ($CO_{2}$ + $n$-dodecane) and ($CO_{2}$ + squalane) are reported at $T$ = (283.15-393.15) K and $p$ = (10-100) MPa.

The present work aims to measure speeds of sound $c$ in a biogas mixture of $CH_{4}$ + $N_{2}$ + $CO_{2}$ + $CO$, at $p$ = (1-12) MPa and $T$ = (273, 300 and 325) K, using a spherical acoustical resonator. The results are fitted to the virial acoustic equation of state, and the virial acoustic coefficients are obtained, $\beta_{a}$ and $\gamma_{a}$ and extrapolated to zero pressure, determining the adiabatic coefficient as perfect gas, $\gamma^{pg}$, and the isobaric and isochoric heat capacities as perfect gas, $C_{p}^{pg}$ and $C_{V}^{pg}$, respectively. The speeds of sound are acquired with a mean expanded relative uncertainty of 165 parts in $10^{6}$ ($k$ = 2) and are compared with the results predicted by the reference equation of state for this kind of mixture (natural gas-like mixtures), EoS GERG-2008. Relative deviations between experimental data and values estimated by this model were less than 700 parts in $10^{6}$ at $T$ = 325 K, and below 400 parts in $10^{6}$, and within measurement uncertainty of at $T$ = 300 K, although appreciably higher at isotherm $T$ = 273 K at the highest pressure data for this work, and even reaching values above 3 400 parts in $10^{6}$.

Over the Nullarbor Plain in South Australia, the Desert Fireball Network detected a fireball on the night of 1 June 2019 (7:30 pm local time), and six weeks later recovered a single meteorite (42 g) named Arpu Kuilpu. This meteorite was then distributed to a consortium of collaborating institutions to be measured and analyzed by a number of methodologies including: SEM-EDS, EPMA, ICP-MS, gamma-ray spectrometry, ideal gas pycnometry, magnetic susceptibility measurement, {\mu}CT, optical microscopy, and accelerator and noble gas mass spectrometry techniques. These analyses revealed that Arpu Kuilpu is an unbrecciated H5 ordinary chondrite, with minimal weathering (W0-1) and minimal shock (S2). The olivine and pyroxene mineral compositions (in mol%) are Fa: 19.2 +- 0.2, and Fs: 16.8 +- 0.2, further supporting the H5 type and class. The measured oxygen isotopes are also consistent with an H chondrite ({\delta}17O = 2.904 +- 0.177; {\delta}18O = 4.163 +- 0.336; {\Delta}17O = 0.740 +- 0.002). Ideal gas pycnometry measured bulk and grain densities of 3.66 +- 0.02 and 3.77 +- 0.02 g cm-3, respectively, yielding a porosity of 3.0 % +- 0.7. The magnetic susceptibility of this meteorite is log X = 5.16 +- 0.08. The most recent impact-related heating event experienced by Arpu Kuilpu was measured by 40Ar/39Ar chronology to be 4467 +- 16 Ma, while the cosmic ray exposure age is estimated to be between 6-8 Ma. The noble gas isotopes, radionuclides, and fireball observations all indicate that Arpu Kuilpu's meteoroid was quite small (maximum radius of 10 cm, though more likely between 1-5 cm). Although this meteorite is a rather ordinary ordinary chondrite, its prior orbit resembled that of a Jupiter Family Comet (JFC) further lending support to the assertion that many cm- to m-sized objects on JFC orbits are asteroidal rather than cometary in origin.

A new determination of the molar gas constant was performed from measurements of the speed of sound in argon at the triple point of water and extrapolation to zero pressure. A new resonant cavity was used. This is a triaxial ellipsoid whose walls are gold-coated steel and which is divided into two identical halves that are bolted and sealed with an O-ring. Microwave and electroacoustic traducers are located in the northern and southern parts of the cavity, respectively, so that measurements of microwave and acoustic frequencies are carried out in the same experiment. Measurements were taken at pressures from 600 kPa to 60 kPa and at 273.16 K. The internal equivalent radius of the cavity was accurately determined by microwave measurements and the first four radial symmetric acoustic modes were simultaneously measured and used to calculate the speed of sound. The improvements made using the new cavity have reduced by half the main contributions to the uncertainty due to the radius determination using microwave measurements which amounts to 4.7 parts in $10^{6}$ and the acoustic measurements, 4.4 parts in $10^{6}$, where the main contribution (3.7 parts in $10^{6}$) is the relative excess half-widths associated with the limit of our acoustic model, compared with our previous measurements. As a result of all the improvements with the new cavity and the measurements performed, we determined the molar gas constant $R$ = (8.314 449 $\pm$ 0.000 056) J/(K mol) which corresponds to a relative standard uncertainty of 6.7 parts in $10^{6}$. The value reported in this paper lies -1.3 parts in $10^{6}$ below the recommended value of CODATA 2014, although still within the range consistent with it.

We analyze JWST MIRI/MRS IFU observations of three Seyferts and showcase the intriguing polycyclic aromatic hydrocarbon (PAH) emission characteristics in regions of $\sim 500\,\rm pc$ scales over or around their active galactic nuclei (AGN). Combining the model predictions and the measurements of PAH features and other infrared emission lines, we find that the central regions containing a high fraction of neutral PAHs with small sizes, e.g., those in ESO137-G034, are in highly heated environments, due to collisional shock heating, with hard and moderately intense radiation fields. Such environments are proposed to be associated with inhibited growth or preferential erosion of PAHs, decreasing the average PAH size and the overall abundance of PAHs. We additionally find that the central regions containing a high fraction of ionized PAHs with large sizes, e.g., those in MCG-05-23-016, are likely experiencing severe photo-ionization because of the radiative effects from the radiative shock precursor besides the AGN. The severe photo-ionization can contribute to the ionization of all PAHs and further destruction of small PAHs. Overall, different Seyferts, even different regions in the same galaxy, e.g., those in NGC\,3081, can contain PAH populations of different properties. Specifically, Seyferts that exhibit similar PAH characteristics to ESO137-G034 and MCG-05-23-016 also tend to have similar emission line properties to them, suggesting that the explanations for PAH characteristics of ESO137-G034 and MCG-05-23-016 may also apply generally. These results have promising application in the era of JWST, especially in diagnosing different (i.e., radiative, and kinetic) AGN feedback modes., Comment: 20 pages (6 pages in the appendix), 6 figures in the main text, ApJL resubmitted after addressing referee's comments

Utilizing JWST MIRI/MRS IFU observations of the kiloparsec scale central regions, we showcase the diversity of ionized gas distributions and kinematics in six nearby Seyfert galaxies included in the GATOS survey. Specifically, we present spatially resolved flux distribution and velocity field maps of six ionized emission lines covering a large range of ionization potentials ($15.8-97.1$ eV). Based on these maps, we showcase the evidence of ionized gas outflows in the six targets, and find some highly disturbed regions in NGC\,5728, NGC\,5506, and ESO137-G034. We propose AGN-driven radio jets plausibly play an important role in triggering these highly disturbed regions. With the outflow rates estimated based on [Ne~{\footnotesize V}] emission, we find the six targets tend to have ionized outflow rates converged to a narrower range than previous finding. These results have important implication for the outflow properties in AGN of comparable luminosity., Comment: 34 pages (11 pages in the appendix), 18 figures in the main text, ApJ in press (accepted on July 26th)

The development of a novel technique based on a cylindrical microwave resonator for high pressure phase equilibrium determination is described. Electric permittivity or dielectric constant is a physical property that depends on temperature and pressure $\epsilon$($p$,$T$). Based on this property, a measuring technique consisting of a cylindrical resonant cavity that works in the microwave spectrum has been developed. Equilibrium data of fluid mixtures are measured at high pressure using a synthetic method, where phase transition is determined under isothermal conditions due to the change of the dielectric constant. This technique may be a more accurate alternative to conventional visual synthetic methods. The technique was validated measuring pure $CO_{2}$, and phase behaviour was then determined for two binary mixtures [$CO_{2}$ (0.6) + $CH_{4}$ (0.4)] and [$CO_{2}$ (0.4) + $CH_{4}$ (0.6)], results for which are presented. These systems are interesting for the study of biogas-like mixtures. In addition, data were compared with the equation of state used for natural gas GERG-2008, and also, they were modelled using Peng-Robinson equation of state and Wong-Sandler mixing rules, which are widely employed in chemical industries and which give good results.

This work aims to provide accurate and wide-ranging experimental new speed of sound data $w$($p$,$T$) of two binary ($CH_{4}$ + $He$) mixtures at a nominal helium content of 5% and 10% at pressures $p$ = (0.5 up to 20) MPa and temperatures $T$ = (273.16, 300, 325, 350 and 375) K. For this purpose, the most accurate technique for determining speed of sound in gas phase has been used: the spherical acoustic resonator. Speed of sound is determined with an overall relative expanded ($k$ = 2) uncertainty of 230 parts in $10^{6}$ and compared to reference models for multicomponent natural gas-like mixtures: AGA8-DC92 and GERG-2008 equations of state. Relative deviations of experimental data from model estimations are outside the experimental uncertainty limit, although all points are mostly within the AGA uncertainty of 0.2% and GERG uncertainty of 0.5% and worsen as the helium content increases. Absolute average deviations are better than 0.45% for GERG and below 0.14% for AGA models in (0.95 $CH_{4}$ + 0.05 $He$) mixture and below 0.83% for GERG and within 0.22% for AGA equations in (0.90 $CH_{4}$ + 0.10 $He$) mixture.

Interpretation of data from faint dwarf galaxies is made challenging by observations limited to only the brightest stars. We present a major improvement to tackle this challenge by undertaking zoomed cosmological simulations that resolve the evolution of all individual stars more massive than $0.5\,{\rm M}_{\odot}$, thereby explicitly tracking all observable stars for the Hubble time. For the first time, we predict observable color-magnitude diagrams and the spatial distribution of $\approx 100,000$ stars within four faint ($M_{\star} \approx 10^5 \, \,{\rm M}_{\odot}$) dwarf galaxies directly from their cosmological initial conditions. In all cases, simulations predict complex light profiles with multiple components, implying that typical observational measures of structural parameters can make total V-band magnitudes appear up to 0.5 mag dimmer compared to estimates from simulations. Furthermore, when only small ($\lessapprox100$) numbers of stars are observable, shot noise from realizations of the color-magnitude diagram introduces uncertainties comparable to the population scatter in, e.g., total magnitude, half-light radius, and mean iron abundance measurements. Estimating these uncertainties with fully self-consistent mass growth, star formation and chemical enrichment histories paves the way for more robust interpretation of dwarf galaxy data., Comment: Submitted to ApJL, comments welcome

Van der Waals (vdW) materials supporting phonon polaritons (PhPs) - light coupled to lattice vibrations - have gathered significant interest because of their intrinsic anisotropy and low losses. In particular, $\alpha$-MoO$_3$ supports PhPs with in-plane anisotropic propagation, which has been exploited to tune the optical response of twisted bilayers and trilayers. Additionally, various studies have explored the realization of polaritonic crystals (PCs) - lattices with periods comparable to the polariton wavelength -. PCs consisting of hole arrays etched in $\alpha$-MoO$_3$ slabs exhibit Bragg resonances dependent on the angle between the crystallographic axes and the lattice vectors. However, such PC concept, with a fixed orientation and size of its geometrical parameters, constrains practical applications and introduces additional scattering losses due to invasive fabrication processes. Here we demonstrate a novel PC concept that overcomes these limitations, enabling low-loss optical tuning. It comprises a rotatable pristine $\alpha$-MoO$_3$ layer located on a periodic hole array fabricated in a metallic layer. Our design prevents degradation of the $\alpha$-MoO$_3$ optical properties caused by fabrication, preserving its intrinsic low-loss and in-plane anisotropic propagation of PhPs. The resulting PC exhibits rotation of the Bloch modes, which is experimentally visualized by scanning near-field microscopy. In addition, we experimentally determine the polaritons momentum and reconstruct their band structure. These results pave the way for mechanically tunable nanooptical components based on polaritons for potential lasing, sensing, or energy harvesting applications.

Speed of sound is one of the thermodynamic properties that can be measured with least uncertainty and is of great interest in developing equations of state. Moreover, accurate models are needed by the H2 industry to design the transport and storage stages of hydrogen blends in the natural gas network. This research aims to provide accurate data for ($CH_{4}$ + $H_{2}$) mixtures of nominal (5, 10, and 50) mol-% of hydrogen, in the $p$ = (0.5 up to 20) MPa pressure range and with temperatures $T$ = (273.16, 300, 325, 350, and 375) K. Using an acoustic spherical resonator, speed of sound was determined with an overall relative expanded ($k$ = 2) uncertainty of 220 parts in $10^{6}$ (0.022%). Data were compared to reference equations of state for natural gas-like mixtures, such as AGA8-DC92 and GERG-2008. Average absolute deviations below 0.095% and percentage deviations between 0.029% and up to 0.30%, respectively, were obtained. Additionally, results were fitted to the acoustic virial equation of state and adiabatic coefficients, molar isochoric heat capacities and molar isobaric heat capacities as perfect-gas, together with second and third acoustic virial coefficients were estimated. Density second virial coefficients were also obtained.

Continuing our study on ($CO_{2}$ + $O_{2}$) mixtures, this work reports new experimental($p$, $\rho$, $T$) data for two oxygen-rich mixtures with mole fractions $x$($O_{2}$) = (0.50 and 0.75) mol/mol, in the temperature range $T$ = (250-375) K and pressure range $p$ = (0.5-20) MPa, using a single-sinker densimeter. Experimental density data were compared to two well-established equation-of-state models: EOS-CG and GERG-2008. In the $p$, $T$-range investigated, the EOS-CG gave a better reproduction for the equimolar mixture $x$($O_{2}$) = 0.5, whereas the GERG-2008 performed significantly better for the oxygen-rich mixture $x$($O_{2}$) = 0.75. The EOS-CG generally overestimates the density, while the GERG-2008 underestimates it. This complete set of new experimental data, together with previous measurements, is used to calculate the virial coefficients $B$($T$, $x$) and $C$($T$, $x$), as well as the second interaction virial coefficient $B_{12}$($T$) for the ($CO_{2}$ + $O_{2}$) system.

We analyze JWST MIRI/MRS observations of the infrared PAH bands in the nuclear and circumnuclear regions of local AGN from the GATOS Survey. In this work, we examine the PAH properties in the circumnuclear regions of AGN and AGN-outflows, and compare them to those in star-forming regions and the innermost regions of AGN. This study employs 4.9-28.1 micron sub-arcsecond angular resolution data to investigate the properties of PAH in three nearby sources (DL~30-40 Mpc). Our findings align with previous JWST studies, showing that the central regions of AGN show a larger fraction of neutral PAH molecules (i.e. elevated 11.3/6.2 and 11.3/7.7 PAH ratios) compared to star-forming galaxies. We find that the AGN might affect not only the PAH population in the innermost region but also in the extended regions up to ~kpc scales. By comparing our observations to PAH diagnostic diagrams, we find that, in general, regions located in the projected direction of the AGN-outflow occupy similar positions on the PAH diagnostic diagrams as those of the innermost regions of AGN. Star-forming regions that are not affected by the AGN in these galaxies share the same part of the diagram as Star-forming galaxies. We examine the potential of the PAH-H2 diagram to disentangle AGN versus star-forming activity. Our results suggest that in Sy-like AGN, illumination and feedback from the AGN might affect the PAH population at nuclear and kpc scales, in particular, the ionization state of the PAH grains. However, PAH sizes are rather similar. The carriers of the ionized PAH bands (6.2 and 7.7 micron) are less resilience than those of neutral PAH bands (11.3 micron), which might be particularly important for strongly AGN-host coupled systems. Therefore, caution must be applied when using PAH bands as star-formation rate indicators in these systems even at kpc scales, with the ionized ones being more affected by the AGN., Comment: Accepted for publication in A&A. 21 pages, 13 Figures

This work aims to address the technical aspects related to the thermodynamic characterization of natural gas mixtures blended with hydrogen for the introduction of alternative energy sources within the Power-to-Gas framework. For that purpose, new experimental speed of sound data are presented in the pressure range between (0.1 up to 13) MPa and at temperatures of (260, 273.16, 300, 325, and 350) K for two mixtures qualified as primary calibration standards: a 11 component synthetic natural gas mixture (11 M), and another low-calorific $H_{2}$-enriched natural gas mixture with a nominal molar percentage $x_{H_{2}}$ = 3%. Measurements have been gathered using a spherical acoustic resonator with an experimental expanded ($k$ = 2) uncertainty better than 200 parts in $10^{6}$ (0.02%) in the speed of sound. The heat capacity ratio as perfect-gas $\gamma_{pg}$, the molar heat capacity as perfect-gas $C_{p,m}^{pg}$, and the second $\beta_{a}$ and third $\gamma_{a}$ acoustic virial coefficients are derived from the speed of sound values. All the results are compared with the reference mixture models for natural gas-like mixtures, the AGA8-DC92 EoS and the GERG-2008 EoS, with special attention to the impact of hydrogen on those properties. Data are found to be mostly consistent within the model uncertainty in the 11 M synthetic mixture as expected, but for the hydrogen-enriched mixture in the limit of the model uncertainty at the highest measuring pressures.

This work presents phase envelope and speed of sound data for the (0.60 $CO_{2}$ + 0.40 $C_{3}H_{8}$) and (0.80 $CO_{2}$ + 0.20 $C_{3}H_{8}$) binary mixtures. Phase equilibria was measured using a cylindrical resonator working in the microwave band whereas an acoustic resonator was used for speed of sound measurements. The experimental results were compared with GERG-2008 equation of state, obtaining average absolute deviations by 0.24% in pressure for phase equilibria data and 0.025% for speed of sound data. Speed of sound values were used to derive perfect-gas heat capacities, acoustic virial coefficients, and second density virial coefficients. In addition, AGA8-DC92 equation of state performance was checked for the results derived from speeds of sound.

This work aims to address the technical concerns related to the thermodynamic characterization of gas mixtures blended with hydrogen for the implementation of hydrogen as a new energy vector. For this purpose, new experimental speed of sound measurements have been done in gaseous and supercritical phases of two binary mixtures of nitrogen and hydrogen using the most accurate technique available, i.e., the spherical acoustic resonator, yielding an experimental expanded ($k$ = 2) uncertainty of only 220 parts in $10^{6}$ (0.022%). The measurements cover the pressure range between (0.5 and 20) MPa, the temperature range between (260 and 350) K, and the composition range with a nominal mole percentage of hydrogen of (5 and 10) mol%, respectively. From the speed of sound data sets, thermophysical properties that are relevant for the characterization of the mixture, namely the second $\beta_{a}$ and third $\gamma_{a}$ acoustic virial coefficients, are derived. These results are thoroughly compared and discussed with the established reference mixture models valid for mixtures of nitrogen and hydrogen, such as the AGA8-DC92 EoS, the GERG-2008 EoS, and the recently developed adaptation of the GERG-2008 EoS, here denoted GERG-$H_{2}$_improved EoS. Special attention has been given to the effect of hydrogen concentration on those properties, showing that only the GERG-$H_{2}$_improved EoS is consistent with the data sets within the experimental uncertainty in most measuring conditions.

Context: In the context of Galactic archaeology, the outer halo remains relatively unexplored with respect to its metallicity distribution, merger debris, and the abundance of known very/extremely metal-poor ([Fe/H]<-2.5) stars. Aim: We utilize the Pristine survey's publicly available, Pristine data release 1 (PDR1) and Pristine-Gaia synthetic (PGS) catalogues of photometric metallicities, to select Red Giant Branch (RGB) stars in the outer halo. Methods: The RGB selection pipeline selects giants based on the absence of a well-measured parallax in the brightness range where dwarfs have reasonable parallax estimate from Gaia DR3 data. The photometric distances are calculated using a BaSTI-isochrone fitting code and the photometric metallicities. Results: Photometric distances derived from PDR1- and PGS-giants show typical uncertainties of 12% and a scatter of up to 20% and 40% respectively, when validated against inverted-parallax and Starhorse-code distances. The PDR1-giants catalogue provides a low-to-no bias view of the metallicity structure versus distance compared to the PGS-giants catalogue (with a distance-metallicity selection bias), while the PGS-giants catalogue provides an all-sky view of the outer halo, especially in the VMP end. The PDR1-giants catalogue is used to study the metallicity distribution function of the halo out to ~100 kpc, using Gaussian Mixture Model decomposition. Additionally, we use the PDR1-giants with radial velocities from spectroscopic surveys to map the metallicity view of the integrals-of-motion space where accreted dwarf galaxy debris conserve their orbital parameters for a long time. Using the PGS-giants catalogue, we associate 41 stars tentatively to the stellar counterpart of the Magellanic stream in the VMP end, out to 70 kpc. Conclusions: We publish two RGB catalogues between -4.0<[Fe/H]<+0.1 with reliable photometric distances and metallicities., Comment: Submitted to A&A, 25 pages (19 Figures) + 4 pages (6 Figures) in Appendix. Comments are very welcome, enjoy reading! The catalogues will be published upon acceptance

Star formation in the central molecular zone (CMZ) is suppressed with respect to that of the Galactic disk, and this is likely related to its high turbulent environment. This turbulence impedes the potential detection of prestellar cores. We present the temperature, density, and spatial structure of the CMZ molecular cloud G+0.693-0.027, which has been proposed to host a prestellar cluster in the Sgr B2 region. We analysed multiple HC$_{3}$N rotational transitions that were observed with the IRAM 30m, APEX, Yebes 40m, and GBT radio telescopes, together with SMA+APEX spatially resolved maps. The spectral shape of HC$_{3}$N lines shows three velocity components: a broad component with a line width of 23 km s$^{-1}$ (C1), and two narrow components with line widths of 7.2 and 8.8 km s$^{-1}$ (C2 and C3). This suggests that a fraction of the molecular gas in this cloud is undergoing turbulence dissipation. From a non-local thermodynamic equilibrium analysis we have found H$_{2}$ densities of 2$\times$10$^{4}$ cm$^{-3}$, 5$\times$10$^{4}$ cm$^{-3}$, and 4$\times$10$^{5}$ cm$^{-3}$ and kinetic temperatures of 140 K, 30 K, and 80 K for C1, C2, and C3, respectively. The spatially resolved maps confirm that the colder and high-density condensations C2 and C3, which peak in the 70-85 km s$^{-1}$ velocity range, are embedded in a more diffuse and warmer gas (C1). The larger-scale structure of the Sgr B2 region shows a hole at 40-50 km s$^{-1}$ that is likely due to a small cloud that shocked the Sgr B2 region and is spatially related with a massive cloud at 60-80 km s$^{-1}$. We propose that the impacting small cloud sequentially triggered the formation of Sgr B2(M), (N), and (S) and the condensations in G+0.693-0.027 during its passage. Based on the analysis of the masses of the two condensations and on the virial parameters, C2 might expand, while C3 might further fragment or collapse., Comment: 21 pages, 16 figures, 5 tables, 4 appendix - Accepted for publication in A&A

We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine learning tool, named \texttt{SMDET}, applied to time series images from the Wide-field Infrared Survey Explorer. We gathered photometric and astrometric data to estimate each candidate's spectral type, distance, and tangential velocity. This sample has a photometrically estimated spectral class distribution of 28 M dwarfs, 64 L dwarfs, and 18 T dwarfs. We also identify a T subdwarf candidate, two extreme T subdwarf candidates, and two candidate young ultracool dwarfs. Five objects did not have enough photometric data for any estimations to be made. To validate our estimated spectral types, spectra were collected for 2 objects, yielding confirmed spectral types of T5 (estimated T5) and T3 (estimated T4). Demonstrating the effectiveness of machine learning tools as a new large-scale discovery technique., Comment: 14 pages, 8 figures, 2 tables, extended table 1, accepted to Astronomical Journal

Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. In this work, we present two surface code memories operating below this threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of $\Lambda$ = 2.14 $\pm$ 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% $\pm$ 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of 2.4 $\pm$ 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 $\mu$s at distance-5 up to a million cycles, with a cycle time of 1.1 $\mu$s. To probe the limits of our error-correction performance, we run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or 3 $\times$ 10$^9$ cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms., Comment: 10 pages, 4 figures, Supplementary Information

In the late stages of accretion leading up to the formation of planetesimals, particles grew to pebbles the size of 1-mm to tens of cm. That is the same size range that dominates the present-day comet mass loss. Meteoroids that size cause visible meteors on Earth. Here, we hypothesize that the size distribution and the physical and chemical properties of young meteoroid streams still contain information about the conditions in the solar nebula during these late stages of accretion. From observations of 47 young meteor showers, we find that freshly ejected meteoroids from long-period comets tend to have low bulk density and are distributed with equal surface area per log-mass interval (magnitude distribution index chi ~ 1.85), suggesting gentle accretion conditions. Jupiter-family comets, on the other hand, mostly produce meteoroids twice as dense and distributed with a steeper chi ~ 2.15 or even chi ~ 2.5, which implies that those pebbles grew from particles fragmenting in a collisional cascade or by catastrophic collisions, respectively. Both comet populations contain an admixture of compact materials that are sometimes sodium-poor, but Jupiter-family comets show a higher percentage (~8% on average) than long-period comet showers (~4%), and a wider range. While there are exceptions in both groups, the implication is that most long-period comets formed under gentle particle growth conditions, possibly near the 30 AU edge of the Trans Neptunian Disk, while most Jupiter family comets formed closer to the Sun where pebbles reached or passed the fragmentation barrier. This is possible if the Scattered Disk represents all objects scattered by Neptune during its migration, while the present-day outer Oort cloud formed only during and after the Sun had moved away from sibling stars., Comment: 82 pages, 14 figures, 3 tables

Recent analyses highlight challenges in autonomous vehicle technologies, particularly failures in decision-making under dynamic or emergency conditions. Traditional automated driving systems recalculate the entire trajectory in a changing environment. Instead, a novel approach retains valid trajectory segments, minimizing the need for complete replanning and reducing changes to the original plan. This work introduces a trajectory repairing framework that calculates a feasible evasive trajectory while computing the Feasible Time-to-React (F-TTR), balancing the maintenance of the original plan with safety assurance. The framework employs a binary search algorithm to iteratively create repaired trajectories, guaranteeing both the safety and feasibility of the trajectory repairing result. In contrast to earlier approaches that separated the calculation of safety metrics from trajectory repairing, which resulted in unsuccessful plans for evasive maneuvers, our work has the anytime capability to provide both a Feasible Time-to-React and an evasive trajectory for further execution.

Phonon polaritons (PhPs) (light coupled to lattice vibrations) in the highly anisotropic polar layered material molybdenum trioxide (\alpha-MoO_3) are currently the focus of intense research efforts due to their extreme subwavelength field confinement, directional propagation and unprecedented low losses. Nevertheless, prior research has primarily concentrated on exploiting the squeezing and steering capabilities of \alpha-MoO_3 PhPs, without inquiring much into the dominant microscopic mechanism that determines their long lifetimes, key for their implementation in nanophotonic applications. This study delves into the fundamental processes that govern PhP damping in \alpha-MoO_3 by combining ab initio calculations with scattering-type scanning near-field optical microscopy (s-SNOM) and Fourier-transform infrared (FTIR) spectroscopy measurements across a broad temperature range (from 8 to 300 K). The remarkable agreement between our theoretical predictions and experimental observations allows us to identify third-order anharmonic phonon-phonon scattering as the main damping mechanism of \alpha-MoO_3 PhPs. These findings shed light on the fundamental limits of low-loss PhPs, a crucial factor for assessing their implementation into nanophotonic devices., Comment: 24 pages, 4 figures

Proximally-sensed laser scanning offers significant potential for automated forest data capture, but challenges remain in automatically identifying tree species without additional ground data. Deep learning (DL) shows promise for automation, yet progress is slowed by the lack of large, diverse, openly available labeled datasets of single tree point clouds. This has impacted the robustness of DL models and the ability to establish best practices for species classification. To overcome these challenges, the FOR-species20K benchmark dataset was created, comprising over 20,000 tree point clouds from 33 species, captured using terrestrial (TLS), mobile (MLS), and drone laser scanning (ULS) across various European forests, with some data from other regions. This dataset enables the benchmarking of DL models for tree species classification, including both point cloud-based (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view image-based methods (SimpleView, DetailView, YOLOv5). 2D image-based models generally performed better (average OA = 0.77) than 3D point cloud-based models (average OA = 0.72), with consistent results across different scanning platforms and sensors. The top model, DetailView, was particularly robust, handling data imbalances well and generalizing effectively across tree sizes. The FOR-species20K dataset, available at https://zenodo.org/records/13255198, is a key resource for developing and benchmarking DL models for tree species classification using laser scanning data, providing a foundation for future advancements in the field.

Relational databases often suffer from uninformative descriptors of table contents, such as ambiguous columns and hard-to-interpret values, impacting both human users and text-to-SQL models. In this paper, we explore the use of large language models (LLMs) to automatically generate detailed natural language descriptions for SQL database columns, aiming to improve text-to-SQL performance and automate metadata creation. We create a dataset of gold column descriptions based on the BIRD-Bench benchmark, manually refining its column descriptions and creating a taxonomy for categorizing column difficulty. Through evaluating several LLMs, we find that incorporating these column descriptions consistently enhances text-to-SQL model performance, particularly for larger models like GPT-4o, Qwen2 72B and Mixtral 22Bx8. However, models struggle with columns that exhibit inherent ambiguity, highlighting the need for manual expert input. Notably, Qwen2-generated descriptions, containing by annotators deemed superfluous information, outperform manually curated gold descriptions, suggesting that models benefit from more detailed metadata than humans expect. Future work will investigate the specific features of these high-performing descriptions and explore other types of metadata, such as numerical reasoning and synonyms, to further improve text-to-SQL systems. The dataset, annotations and code will all be made available.

AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they also pose significant challenges for assessment and learning outcomes. We conceptualize these challenges through the lens of vulnerability, the potential for university assessments and learning outcomes to be impacted by student use of generative AI. We investigate the potential scale of this vulnerability by measuring the degree to which AI assistants can complete assessment questions in standard university-level STEM courses. Specifically, we compile a novel dataset of textual assessment questions from 50 courses at EPFL and evaluate whether two AI assistants, GPT-3.5 and GPT-4 can adequately answer these questions. We use eight prompting strategies to produce responses and find that GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. When grouping courses in our dataset by degree program, these systems already pass non-project assessments of large numbers of core courses in various degree programs, posing risks to higher education accreditation that will be amplified as these models improve. Our results call for revising program-level assessment design in higher education in light of advances in generative AI., Comment: 20 pages, 8 figures

AI-driven program repair uses AI models to repair buggy software by producing patches. Rapid advancements in AI surely impact state-of-the-art performance of program repair. Yet, grasping this progress requires frequent and standardized evaluations. We propose RepairBench, a novel leaderboard for AI-driven program repair. The key characteristics of RepairBench are: 1) it is execution-based: all patches are compiled and executed against a test suite, 2) it assesses frontier models in a frequent and standardized way. RepairBench leverages two high-quality benchmarks, Defects4J and GitBug-Java, to evaluate frontier models against real-world program repair tasks. We publicly release the evaluation framework of RepairBench. We will update the leaderboard as new frontier models are released.

We determine all reduced saturated fusion systems supported on a finite $p$-group of nilpotency class two. As a consequence, we obtain a new proof of Gilman & Gorenstein's classification of finite simple groups with class two Sylow $2$-subgroups.

Marginal structural models are a popular method for estimating causal effects in the presence of time-varying exposures. In spite of their popularity, no scalable non-parametric estimator exist for marginal structural models with multi-valued and time-varying treatments. In this paper, we use machine learning together with recent developments in semiparametric efficiency theory for longitudinal studies to propose such an estimator. The proposed estimator is based on a study of the non-parametric identifying functional, including first order von-Mises expansions as well as the efficient influence function and the efficiency bound. We show conditions under which the proposed estimator is efficient, asymptotically normal, and sequentially doubly robust in the sense that it is consistent if, for each time point, either the outcome or the treatment mechanism is consistently estimated. We perform a simulation study to illustrate the properties of the estimators, and present the results of our motivating study on a COVID-19 dataset studying the impact of mobility on the cumulative number of observed cases., Comment: 15 pages, 1 figure, 3 tables

Thermodynamical systems at the nanoscale, such as single molecules interacting with highly structured vibrational environments, typically undergo non-equilibrium physical processes that lack precise microscopic descriptions. Photoisomerization is such an example which has emerged as a platform on which to study single-molecule ultrafast photochemical processes from a quantum resource theoretic perspective. However, upper bounds on its efficiency have only been obtained under significant simplifications that make the mathematics of the resource-theoretical treatment manageable. Here we generalize previous models for the photoisomers, while retaining the full vibrational structure, and still get analytical bounds on the efficiency of hotoisomerization. We quantify the impact of such vibrational structure on the optimal photoisomerization quantum yield both when the vibrational coordinate has no dynamics of its own and when we take into account the vibrational dynamics. This work serves as an example of how to bridge the gap between the abstract language of quantum resource theories and the open system formulation of nanoscale processes., Comment: 13 pages, 6 figures

We present team semantics for two of the most important linear and branching time specification languages, Linear Temporal Logic (LTL) and Computation Tree Logic (CTL). With team semantics, LTL is able to express hyperproperties, which have in the last decade been identified as a key concept in the verification of information flow properties. We study basic properties of the logic and classify the computational complexity of its satisfiability, path, and model checking problem. Further, we examine how extensions of the basic logic react to adding additional atomic operators. Finally, we compare its expressivity to the one of HyperLTL, another recently introduced logic for hyperproperties. Our results show that LTL with team semantics is a viable alternative to HyperLTL, which complements the expressivity of HyperLTL and has partially better algorithmic properties. For CTL with team semantics, we investigate the computational complexity of the satisfiability and model checking problem. The satisfiability problem is shown to be EXPTIME-complete while we show that model checking is PSPACE-complete.

In this paper, we prove that the trajectories of unreduced $\phi$-simple Chaplygin kinetic systems are reparametrizations of horizontal geodesics with respect to a modified Riemannian metric. Furthermore, our proof is constructive and these Riemannian metrics, which are not unique, are obtained explicitly in interesting examples. We also extend these results to $\phi$-simple Chaplygin mechanical systems (not necessarily kinetic).

When sheared, granular media experience localized plastic events known as shear transformations which generate anisotropic internal stresses. Under strong confining pressure, the response of granular media to local force multipoles is essentially linear, resulting in quadrupolar propagated stresses. This can lead to additional plastic events along the direction of relative stress increase. Closer to the unjamming transition however, as the confining pressure and the shear modulus vanish, nonlinearities become relevant. Yet, the consequences of these nonlinearities on the stress response to plastic events remains poorly understood. We show with granular dynamics simulations that this brings about an isotropization of the propagated stresses, in agreement with a previously developed continuum elastic model. This could significantly modify the yielding transition of weakly-jammed amorphous media, which has been conceptualized as an avalanche of such plastic events., Comment: Main: 5 pages, 4 figures. SI: 9 pages, 8 figures

Due to climate change the frequency and intensity of extreme rainfall events, which contribute to urban flooding, are expected to increase in many places. These floods can damage transport infrastructure and disrupt mobility, highlighting the need for cities to adapt to escalating risks. Reinforcement learning (RL) serves as a powerful tool for uncovering optimal adaptation strategies, determining how and where to deploy adaptation measures effectively, even under significant uncertainty. In this study, we leverage RL to identify the most effective timing and locations for implementing measures, aiming to reduce both direct and indirect impacts of flooding. Our framework integrates climate change projections of future rainfall events and floods, models city-wide motorized trips, and quantifies direct and indirect impacts on infrastructure and mobility. Preliminary results suggest that our RL-based approach can significantly enhance decision-making by prioritizing interventions in specific urban areas and identifying the optimal periods for their implementation.

Combining a precise sputter etching method with subsequent AlO$_x$ growth within an atomic layer deposition chamber enables fabrication of atomically flat lateral patterns of SiO$_2$ and AlO$_x$. The transfer of MoSe$_2$ monolayers onto these dielectrically modulated substrates results in formation of lateral heterojunctions, with the flat substrate topography leading to minimal strain across the junction. Kelvin probe force microscopy (KPFM) measurements show significant variations in the contact potential difference (CPD) across the interface, with AlO$_x$ regions inducing a 230~mV increase in CPD. Spatially resolved photoluminescence spectroscopy reveals shifts in spectral weight of neutral and charged exciton species across the different dielectric regions. On the AlO$_x$ side, the Fermi energy moves closer to the conduction band, leading to a higher trion-to-exciton ratio, indicating a bandgap shift consistent with CPD changes. In addition, transient reflection spectroscopy highlights the influence of the dielectric environment on carrier dynamics, with the SiO$_2$ side exhibiting rapid carrier decay typical of neutral exciton recombination. In contrast, the AlO$_x$ side shows slower, mixed decay behavior consistent with conversion of trions back into excitons. These results demonstrate how dielectric substrate engineering can tune the electronic and optical characteristics of proximal two-dimensional materials, allowing scalable fabrication of advanced junctions for novel (opto)electronics applications., Comment: 24 pages, 5 figures. SI: 2 pages, 3 figures. We welcome your feedback!

For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of their free parameters. In this study, we review and compare a wide range of Markov Chain Monte Carlo (MCMC) and nested sampling techniques to determine their relative efficacy on functions that resemble those encountered most frequently in the particle astrophysics literature. Our first series of tests explores a series of high-dimensional analytic test functions that exemplify particular challenges, for example highly multimodal posteriors or posteriors with curving degeneracies. We then investigate two real physics examples, the first being a global fit of the $\Lambda$CDM model using cosmic microwave background data from the Planck experiment, and the second being a global fit of the Minimal Supersymmetric Standard Model using a wide variety of collider and astrophysics data. We show that several examples widely thought to be most easily solved using nested sampling approaches can in fact be more efficiently solved using modern MCMC algorithms, but the details of the implementation matter. Furthermore, we also provide a series of useful insights for practitioners of particle astrophysics and cosmology., Comment: 45 pages, 8 figures, 20 tables

This paper introduces the hypothetical track-length fitting algorithm, a novel method for measuring the kinetic energies of ionizing particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

Antiferromagnetic materials have great potential for spintronic applications at terahertz (THz) frequencies. However, in contrast to ferromagnets, experimental studies of antiferromagnets are often challenging due to a lack of straightforward external control of the N\'eel vector $\mathbf{L}$. Here, we study an AFM|FM stack consisting of an antiferromagnetic metal layer (AFM) of the novel material Mn2Au and a ferromagnetic metal layer (FM) of NiFe. In this exchange-spring system, $\mathbf{L}$ of AFM Mn2Au can be controlled by the application of an external magnetic field B_ext. To characterize the AFM|FM stack as a function of the quasi-static $\mathbf{B}_{\mathrm{ext}}$, we perform THz-pump magneto-optic probe experiments. We identify signal components that can consistently be explained by the in-plane antiferromagnetic magnon mode excited by field-like N\'eel spin-orbit torques (NSOTs). Remarkably, we find that the $\mathbf{B}_{\mathrm{ext}}$- and THz-pump-induced changes in the optical response of the sample are dominated exclusively by the spin degrees of freedom of AFM. We fully calibrate the magnetic circular and magnetic linear optical birefringence of AFM and extract the efficiency of the NSOTs. Finally, by selective excitation of domains with different orientation of $\mathbf{L}$, we are able to determine the relative volume fraction of 0{\deg}, 90{\deg}, 180{\deg} and 270{\deg} domains distribution during the quasi-static reversal of $\mathbf{L}$ by $\mathbf{B}_{\mathrm{ext}}$. Our insights are an important prerequisite for future studies of ultrafast coherent switching of spins by THz NSOTs and show that THz-pump magneto-optic-probe experiments are a powerful tool to characterize magnetic properties of antiferromagnets.

Finding the most parsimonious tree inside a phylogenetic network with respect to a given character is an NP-hard combinatorial optimization problem that for many network topologies is essentially inapproximable. In contrast, if the network is a rooted tree, then Fitch's well-known algorithm calculates an optimal parsimony score for that character in polynomial time. Drawing inspiration from this we here introduce a new extension of Fitch's algorithm which runs in polynomial time and ensures an approximation factor of 2 on binary, tree-child phylogenetic networks, a popular topologically-restricted subclass of phylogenetic networks in the literature. Specifically, we show that Fitch's algorithm can be seen as a primal-dual algorithm, how it can be extended to binary, tree-child networks and that the approximation guarantee of this extension is tight. These results for a classic problem in phylogenetics strengthens the link between polyhedral methods and phylogenetics and can aid in the study of other related optimization problems on phylogenetic networks.

This paper is a report of the Workshop on Simulations for Information Access (Sim4IA) workshop at SIGIR 2024. The workshop had two keynotes, a panel discussion, nine lightning talks, and two breakout sessions. Key takeaways were user simulation's importance in academia and industry, the possible bridging of online and offline evaluation, and the issues of organizing a companion shared task around user simulations for information access. We report on how we organized the workshop, provide a brief overview of what happened at the workshop, and summarize the main topics and findings of the workshop and future work., Comment: Preprint of a SIGIR Forum submission for Vol. 58 No. 2 - December 2024

Thanks to the rapidly increasing time-domain facilities, we are entering a golden era of research on gamma-ray bursts (GRBs). In this Letter, we report our observations of GRB 240529A with the Burst Optical Observer and Transient Exploring System, the 1.5-meter telescope at Observatorio Sierra Nevada, the 2.5-meter Wide Field Survey Telescope of China, the Large Binocular Telescope, and the Telescopio Nazionale Galileo. The prompt emission of GRB 240529A shows two comparable energetic episodes separated by a quiescence time of roughly 400 s. Combining all available data on the GRB Coordinates Network, we reveal the simultaneous apparent X-ray plateau and optical re-brightening around $10^3-10^4$ s after the burst. Rather than the energy injection from the magnetar as widely invoked for similar GRBs, the multi-wavelength emissions could be better explained as two shocks launched from the central engine separately. The optical peak time and our numerical modeling suggest that the initial bulk Lorentz factor of the later shock is roughly 50, which indicates that the later jet should be accretion-driven and have a higher mass loading than a typical one. The quiescence time between the two prompt emission episodes may be caused by the transition between different accretion states of a central magnetar or black hole, or the fall-back accretion process. A sample of similar bursts with multiple emission episodes in the prompt phase and sufficient follow-up could help to probe the underlying physics of GRB central engines., Comment: Resubmitted to ApJL after addressing the referee's comments; comments are welcome

Phylogenetic networks describe the evolution of a set of taxa for which reticulate events have occurred at some point in their evolutionary history. Of particular interest is when the evolutionary history between a set of just three taxa has a reticulate event. In molecular phylogenetics, substitution models can model the process of evolution at the genetic level, and the case of three taxa with a reticulate event can be modelled using a substitution model on a mixed graph called a 3-sunlet. We investigate a class of substitution models called group-based phylogenetic models on 3-sunlet networks. In particular, we investigate the discrete geometry of the parameter space and how this relates to the dimension of the phylogenetic variety associated to the model. This enables us to give a dimension formula for this variety for general group-based models when the order of the group is odd.

We search for dark matter (DM) with a mass [3,12] $\mathrm{GeV} / c^2$ using an exposure of 3.51 $\mathrm{t} \times \mathrm{y}$ with the XENONnT experiment. We consider spin-independent, spin-dependent, momentum-dependent, mirror DM, and self-interacting DM with a light mediator coupling to Standard Model particles. Using a lowered energy threshold compared to the previous WIMP search, a blind analysis of [0.5, 5.0] $\mathrm{keV}$ nuclear recoil events reveals no significant signal excess over the background. XENONnT excludes spin-independent DM-nucleon cross sections $>2.5 \times 10^{-45} \mathrm{~cm}^2$ at $90 \%$ confidence level for 6 $\mathrm{GeV} / c^2$ DM. The solar ${ }^8 \mathrm{B}$ neutrino coherent elastic neutrino-nucleus scattering background accounts for approximately half of the background in the signal region. In the considered mass range, the DM sensitivity approaches the 'neutrino fog', the limitation where neutrinos produce a signal that is indistinguishable from that of light DM-xenon nucleus scattering.

Background: Centralized collection and processing of healthcare data across national borders pose significant challenges, including privacy concerns, data heterogeneity and legal barriers. To address some of these challenges, we formed an interdisciplinary consortium to develop a feder-ated health data network, comprised of six institutions across five countries, to facilitate Nordic-Baltic cooperation on secondary use of health data. The objective of this report is to offer early insights into our experiences developing this network. Methods: We used a mixed-method ap-proach, combining both experimental design and implementation science to evaluate the factors affecting the implementation of our network. Results: Technically, our experiments indicate that the network functions without significant performance degradation compared to centralized simu-lation. Conclusion: While use of interdisciplinary approaches holds a potential to solve challeng-es associated with establishing such collaborative networks, our findings turn the spotlight on the uncertain regulatory landscape playing catch up and the significant operational costs., Comment: 24 pages (including appendices), 1 figure

This paper introduces FlowMAC, a novel neural audio codec for high-quality general audio compression at low bit rates based on conditional flow matching (CFM). FlowMAC jointly learns a mel spectrogram encoder, quantizer and decoder. At inference time the decoder integrates a continuous normalizing flow via an ODE solver to generate a high-quality mel spectrogram. This is the first time that a CFM-based approach is applied to general audio coding, enabling a scalable, simple and memory efficient training. Our subjective evaluations show that FlowMAC at 3 kbps achieves similar quality as state-of-the-art GAN-based and DDPM-based neural audio codecs at double the bit rate. Moreover, FlowMAC offers a tunable inference pipeline, which permits to trade off complexity and quality. This enables real-time coding on CPU, while maintaining high perceptual quality., Comment: Submitted to ICASSP 2025