Search

Hard X-ray-selected samples of Active Galactic Nuclei (AGN) provide one of the cleanest views of supermassive black hole accretion, but are biased against objects obscured by Compton-thick gas column densities of $N_{\rm H}$ $>$ 10$^{24}$ cm$^{-2}$. To tackle this issue, we present the NuSTAR Local AGN $N_{\rm H}$ Distribution Survey (NuLANDS)$-$a legacy sample of 122 nearby ($z$ $<$ 0.044) AGN primarily selected to have warm infrared colors from IRAS between 25$-$60 $\mu$m. We show that optically classified type 1 and 2 AGN in NuLANDS are indistinguishable in terms of optical [OIII] line flux and mid-to-far infrared AGN continuum bolometric indicators, as expected from an isotropically selected AGN sample, while type 2 AGN are deficient in terms of their observed hard X-ray flux. By testing many X-ray spectroscopic models, we show the measured line-of-sight column density varies on average by $\sim$ 1.4 orders of magnitude depending on the obscurer geometry. To circumvent such issues we propagate the uncertainties per source into the parent column density distribution, finding a directly measured Compton-thick fraction of 35 $\pm$ 9%. By construction, our sample will miss sources affected by severe narrow-line reddening, and thus segregates sources dominated by small-scale nuclear obscuration from large-scale host-galaxy obscuration. This bias implies an even higher intrinsic obscured AGN fraction may be possible, although tests for additional biases arising from our infrared selection find no strong effects on the measured column-density distribution. NuLANDS thus holds potential as an optimized sample for future follow-up with current and next-generation instruments aiming to study the local AGN population in an isotropic manner., Comment: Accepted for publication in ApJ. 50 pages (78 including appendix and bibliography), 21 figures

We present Gemini near-infrared integral field spectrograph (NIFS) K-band observations of the central 400 pc of NGC 1266, a nearby (D$\approx$30 Mpc) post-starburst galaxy with a powerful multi-phase outflow and a shocked ISM. We detect 7 H$_2$ ro-vibrational emission lines excited thermally to $T$$\sim$2000 K, and weak Br$\gamma$ emission, consistent with a fast C-shock. With these bright H$_2$ lines, we observe the spatial structure of the shock with an unambiguous tracer for the first time. The Br$\gamma$ emission is concentrated in the central $\lesssim$100 pc, indicating that any remaining star-formation in NGC 1266 is in the nucleus while the surrounding cold molecular gas has little on-going star-formation. Though it is unclear what fraction of this Br$\gamma$ emission is from star-formation or the AGN, assuming it is entirely due to star-formation we measure an instantaneous star-formation rate of 0.7 M$_\odot$ yr$^{-1}$, though the star-formation rate may be significantly higher in the presence of additional extinction. NGC 1266 provides a unique laboratory to study the complex interactions between AGN, outflows, shocks, and star-formation, all of which are necessary to unravel the evolution of the post-starburst phase., Comment: ApJ accepted

We present the CO(1-0) maps of 28 infrared-bright galaxies from the Great Observatories All-Sky Luminous Infrared Galaxy Survey (GOALS) taken with the Combined Array for Research in Millimeter Astronomy (CARMA). We detect 100GHz continuum in 16 of 28 galaxies, which trace both active galactic nuclei (AGNs) and compact star-forming cores. The GOALS galaxies show a variety of molecular gas morphologies, though in the majority of cases, the average velocity fields show a gradient consistent with rotation. We fit the full continuum SEDs of each of the source using either MAGPHYS or SED3FIT (if there are signs of an AGN) to derive the total stellar mass, dust mass, and star formation rates of each object. We adopt a value determined from luminous and ultraluminous infrared galaxies (LIRGs and ULIRGs) of $\alpha_{\rm CO}=1.5^{+1.3}_{-0.8}~M_\odot$ (K km s$^{-1}$ pc$^2)^{-1}$, which leads to more physical values for $f_{\rm mol}$ and the gas-to-dust ratio. Mergers tend to have the highest gas-to-dust ratios. We assume the cospatiality of the molecular gas and star formation, and plot the sample on the Schmidt-Kennicutt relation, we find that they preferentially lie above the line set by normal star-forming galaxies. This hyper-efficiency is likely due to the increased turbulence in these systems, which decreases the freefall time compared to star-forming galaxies, leading to "enhanced" star formation efficiency. Line wings are present in a non-negligible subsample (11/28) of the CARMA GOALS sources and are likely due to outflows driven by AGNs or star formation, gas inflows, or additional decoupled gas components., Comment: 29 pages, 4 tables, 11 figures, Accepted by the Astrophysical Journal

This paper presents the design and technical progress of a precision X-Y stage for detector dithering and flexure compensation. The stage is being developed for use in the Magellan InfraRed Multi-Object Spectrograph, MIRMOS. MIRMOS is a very large Nasmyth mounted spectrograph containing a combination of refractive, reflective and diffractive optics mounted on a long cryogenic optical bench. The instrument utilizes five science cameras, each having a custom x-y stage to control the in-plane detector position within each camera, providing both dithering capability for improved sampling, and flexure compensation to correct for image motion that results from the gravity variant operation of the instrument. Designed to operate at 120~K, the stage will accurately control detector position in two orthogonal degrees of freedom, and have manual fine adjustment features to set detector tip, tilt and piston. The piezo-driven flexure stage provides high-resolution backlash-free motion of the detector and is very compact along the optical path, keeping camera length to a minimum. A magnetoresistive bridge provides position feedback in each degree of freedom, greatly reducing hysteresis, which is common in piezoelectric actuators. The system is designed to operate in open loop using a lookup table keyed to the Nasmyth rotator angle for flexure control. Here, the optomechanical design of the stage, electrical control system, and current performance results from early prototype efforts are presented and discussed., Comment: Proceedings of SPIE Astronomical Telescopes + Instrumentation 2024, 11 pages, 10 figures

The Magellan InfraRed Multi-Object Spectrograph (MIRMOS) is a planned next generation multi-object and integral field spectrograph for the 6.5m Magellan telescopes at Las Campanas Observatory in Chile. MIRMOS will perform R$\sim$3700 spectroscopy over a simultaneous wavelength range of 0.886 - 2.404$\mu$m (Y,J,H,K bands) in addition to imaging over the range of 0.7 - 0.886$\mu$m. The integral field mode of operation for MIRMOS will be achieved via an image slicer style integral field unit (IFU) located on a linear stage to facilitate movement into the beam during use or storage while operating in multi-object mode. The IFU will provide a $\rm \sim20"\times26"$ field of view (FoV) made up of $\rm0.84"\times26"$ slices. This will be the largest FoV IFS operating at these wavelengths from either the ground or space, making MIRMOS an ideal instrument for a wide range of science cases including studying the high redshift circumgalactic medium and emission line tracers from ionized and molecular gas in nearby galaxies. In order to achieve the desired image quality and FoV while matching the focal ratio to the multi-object mode, our slicer design makes use of novel freeform surfaces for the pupil mirrors, which require the use of high precision multi-axis diamond milling to manufacture. We present here the optical design and predicted performance of the MIRMOS IFU along with a conceptual design for the opto-mechanical system., Comment: Proceedings of SPIE Astronomical Telescopes + Instrumentation 2024, 9 pages, 6 figures

Neural Architecture Search (NAS) methods have shown to output networks that largely outperform human-designed networks. However, conventional NAS methods have mostly tackled the single dataset scenario, incuring in a large computational cost as the procedure has to be run from scratch for every new dataset. In this work, we focus on predictor-based algorithms and propose a simple and efficient way of improving their prediction performance when dealing with data distribution shifts. We exploit the Kronecker-product on the randomly wired search-space and create a small NAS benchmark composed of networks trained over four different datasets. To improve the generalization abilities, we propose GRASP-GCN, a ranking Graph Convolutional Network that takes as additional input the shape of the layers of the neural networks. GRASP-GCN is trained with the not-at-convergence accuracies, and improves the state-of-the-art of 3.3 % for Cifar-10 and increasing moreover the generalization abilities under data distribution shift.

Anomaly detection is crucial in large-scale industrial manufacturing as it helps detect and localise defective parts. Pre-training feature extractors on large-scale datasets is a popular approach for this task. Stringent data security and privacy regulations and high costs and acquisition time hinder the availability and creation of such large datasets. While recent work in anomaly detection primarily focuses on the development of new methods built on such extractors, the importance of the data used for pre-training has not been studied. Therefore, we evaluated the performance of eight state-of-the-art methods pre-trained using dynamically generated fractal images on the famous benchmark datasets MVTec and VisA. In contrast to existing literature, which predominantly examines the transfer-learning capabilities of fractals, in this study, we compare models pre-trained with fractal images against those pre-trained with ImageNet, without subsequent fine-tuning. Although pre-training with ImageNet remains a clear winner, the results of fractals are promising considering that the anomaly detection task required features capable of discerning even minor visual variations. This opens up the possibility for a new research direction where feature extractors could be trained on synthetically generated abstract datasets reconciling the ever-increasing demand for data in machine learning while circumventing privacy and security concerns.

We present a catalog of hard X-ray serendipitous sources detected in the first 80 months of observations by the Nuclear Spectroscopic Telescope Array (NuSTAR). The NuSTAR serendipitous survey 80-month (NSS80) catalog has an unprecedented $\sim$ 62 Ms of effective exposure time over 894 unique fields (a factor of three increase over the 40-month catalog), with an areal coverage of $\sim $36 deg$^2$, larger than all NuSTAR extragalactic surveys. NSS80 provides 1274 hard X-ray sources in the $3-24$ keV band (822 new detections compared to the previous 40-month catalog). Approximately 76% of the NuSTAR sources have lower-energy ($<10$ keV) X-ray counterparts from Chandra, XMM-Newton, and Swift-XRT. We have undertaken an extensive campaign of ground-based spectroscopic follow-up to obtain new source redshifts and classifications for 427 sources. Combining these with existing archival spectroscopy provides redshifts for 550 NSS80 sources, of which 547 are classified. The sample is primarily composed of active galactic nuclei (AGN), detected over a large range in redshift ($z$ = 0.012-3.43), but also includes 58 spectroscopically confirmed Galactic sources. In addition, five AGN/galaxy pairs, one dual AGN system, one BL Lac candidate, and a hotspot of 4C 74.26 (radio quasar) have been identified. The median rest-frame $10-40$ keV luminosity and redshift of the NSS80 are $\langle{L_\mathrm{10-40 keV}}\rangle$ = 1.2 $\times$ 10$^{44}$ erg s$^{-1}$ and $\langle z \rangle = 0.56$. We investigate the optical properties and construct composite optical spectra to search for subtle signatures not present in the individual spectra, finding an excess of redder BL AGN compared to optical quasar surveys predominantly due to the presence of the host-galaxy and, at least in part, due to dust obscuration., Comment: Accepted for publication in ApJ:S. 57 pages, 32 figures

We present a Rabi-type measurement of two ground-state hydrogen hyperfine transitions performed in two opposite external magnetic field directions. This puts first constraints at the level of 2.3 10^-21 GeV on a set of coefficients of the Standard Model Extension, which were not measured by previous experiments. Moreover, we introduce a novel method, applicable to antihydrogen hyperfine spectroscopy in a beam, that determines the zero-field hyperfine transition frequency from the two transitions measured at the same magnetic field. Our value, nu_0 = 1.420 405 751 63(63) GHz, is in agreement with literature at a relative precision of 0.44 ppb. This is the highest precision achieved on hydrogen in a beam, improving over previous results by a factor of 6., Comment: 8 pages, 5 figures, 2 tables, corresponding author: chloe.m@cern.ch (C. Malbrunot)

The landscape of deep learning research is moving towards innovative strategies to harness the true potential of data. Traditionally, emphasis has been on scaling model architectures, resulting in large and complex neural networks, which can be difficult to train with limited computational resources. However, independently of the model size, data quality (i.e. amount and variability) is still a major factor that affects model generalization. In this work, we propose a novel technique to exploit available data through the use of automatic data augmentation for the tasks of image classification and semantic segmentation. We introduce the first Differentiable Augmentation Search method (DAS) to generate variations of images that can be processed as videos. Compared to previous approaches, DAS is extremely fast and flexible, allowing the search on very large search spaces in less than a GPU day. Our intuition is that the increased receptive field in the temporal dimension provided by DAS could lead to benefits also to the spatial receptive field. More specifically, we leverage DAS to guide the reshaping of the spatial receptive field by selecting task-dependant transformations. As a result, compared to standard augmentation alternatives, we improve in terms of accuracy on ImageNet, Cifar10, Cifar100, Tiny-ImageNet, Pascal-VOC-2012 and CityScapes datasets when plugging-in our DAS over different light-weight video backbones.

The Antiproton Decelerator (AD) at CERN provides antiproton bunches with a kinetic energy of 5.3 MeV. The Extra-Low ENergy Antiproton ring at CERN, commissioned at the AD in 2018, now supplies a bunch of electron-cooled antiprotons at a fixed energy of 100 keV. The MUSASHI antiproton trap was upgraded by replacing the radio-frequency quadrupole decelerator with a pulsed drift tube to re-accelerate antiprotons and optimize the injection energy into the degrader foils. By increasing the beam energy to 119 keV, a cooled antiproton accumulation efficiency of (26 +- 6)% was achieved., Comment: 22 pages, 8 figures

Spitzer spectral maps reveal a disk of highly luminous, warm (>150 K) H2 in the center of the massive spiral galaxy Messier 58, which hosts a radio-loud AGN. The inner 2.6 kpc of the galaxy appears to be overrun by shocks from the radio jet cocoon. Gemini NIRI imaging of the H2 1-0 S(1) emission line, ALMA CO 2-1, and HST multiband imagery indicate that much of the molecular gas is shocked in-situ, corresponding to lanes of dusty molecular gas that spiral towards the galaxy nucleus. The CO 2-1 and ionized gas kinematics are highly disturbed, with velocity dispersion up to 300 km/s. Dissipation of the associated kinetic energy and turbulence, likely injected into the ISM by radio-jet driven outflows, may power the observed molecular and ionized gas emission from the inner disk. The PAH fraction and composition in the inner disk appear to be normal, in spite of the jet and AGN activity. The PAH ratios are consistent with excitation by the interstellar radiation field from old stars in the bulge, with no contribution from star formation. The phenomenon of jet-shocked H2 may substantially reduce star formation and help to regulate the stellar mass of the inner disk and supermassive black hole in this otherwise normal spiral galaxy. Similarly strong H2 emission is found at the centers of several nearby spiral and lenticular galaxies with massive bulges and radio-loud AGN., Comment: 18 pages, 12 figures, 1 Table, accepted for publication in the Astrophysical Journal

Stellar and black hole feedback heat and disperse surrounding cold gas clouds, launching gas flows off circumnuclear and galactic disks and producing a dynamic interstellar medium. On large scales bordering the cosmic web, feedback drives enriched gas out of galaxies and groups, seeding the intergalactic medium with heavy elements. In this way, feedback shapes galaxy evolution by shutting down star formation and ultimately curtailing the growth of structure after the peak at redshift 2-3. To understand the complex interplay between gravity and feedback, we must resolve both the key physics within galaxies and map the impact of these processes over large scales, out into the cosmic web. The Advanced X-ray Imaging Satellite (AXIS) is a proposed X-ray probe mission for the 2030s with arcsecond spatial resolution, large effective area, and low background. AXIS will untangle the interactions of winds, radiation, jets, and supernovae with the surrounding ISM across the wide range of mass scales and large volumes driving galaxy evolution and trace the establishment of feedback back to the main event at cosmic noon., Comment: 29 pages, 18 figures; this white paper is part of a series commissioned for the AXIS Probe mission concept

Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high-resolution over the entire brain. The constant demand for higher spatial resolution in 1H-MRSI led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, the Marchenko-Pastur principal component analysis (MP-PCA) based denoising and the low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential and impact on preclinical 14.1T fast in vivo 1H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte-Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio SNR while preserving noise properties in each spectrum for both in vivo and Monte-Carlo datasets. Relative metabolite concentrations were not significantly altered by either methods and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted on lower concentrated metabolites. Our study provided a framework on how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1H-FID MRSI data at 14.1T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care especially for low-concentrated metabolites., Comment: Brayan Alves and Dunja Simicic are joint first authors. Currently in revision for NMR in Biomedicine

We study THz-driven condensate dynamics in epitaxial thin films of MgB$_{2}$, a prototype two-band superconductor (SC) with weak interband coupling. The temperature and excitation density dependent dynamics follow the behavior predicted by the phenomenological bottleneck model for the single-gap SC, implying adiabatic coupling between the two condensates on the ps timescale. The amplitude of the THz-driven suppression of condensate density reveals an unexpected decrease in pair-breaking efficiency with increasing temperature - unlike in the case of optical excitation. The reduced pair-breaking efficiency of narrow-band THz pulses, displaying minimum near $\approx0.7$ T$_{c}$, is attributed to THz-driven, long-lived, non-thermal quasiparticle distribution, resulting in Eliashberg-type enhancement of superconductivity, competing with pair-breaking.

As a fundamental part of computational healthcare, Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) provide volumetric data, making the development of algorithms for 3D image analysis a necessity. Despite being computationally cheap, 2D Convolutional Neural Networks can only extract spatial information. In contrast, 3D CNNs can extract three-dimensional features, but they have higher computational costs and latency, which is a limitation for clinical practice that requires fast and efficient models. Inspired by the field of video action recognition we propose a new 2D-based model dubbed Slice SHift UNet (SSH-UNet) which encodes three-dimensional features at 2D CNN's complexity. More precisely multi-view features are collaboratively learned by performing 2D convolutions along the three orthogonal planes of a volume and imposing a weights-sharing mechanism. The third dimension, which is neglected by the 2D convolution, is reincorporated by shifting a portion of the feature maps along the slices' axis. The effectiveness of our approach is validated in Multi-Modality Abdominal Multi-Organ Segmentation (AMOS) and Multi-Atlas Labeling Beyond the Cranial Vault (BTCV) datasets, showing that SSH-UNet is more efficient while on par in performance with state-of-the-art architectures.

The ASACUSA-Cusp collaboration has recently upgraded the positron system to improve the production of antihydrogen. Previously, the experiment suffered from contamination of the vacuum in the antihydrogen production trap due to the transfer of positrons from the high pressure region of a buffer gas trap. This contamination reduced the lifetime of antiprotons. By adding a new positron accumulator and therefore decreasing the number of transfer cycles, the contamination of the vacuum has been reduced. Further to this, a new rare gas moderator and buffer gas trap, previously used at the Aarhus University, were installed. Measurements from Aarhus suggested that the number of positrons could be increased by a factor of four in comparison to the old system used at CERN. This would mean a reduction of the time needed for accumulating a sufficient number of positrons (of the order of a few million) for an antihydrogen production cycle. Initial tests have shown that the new system yields a comparable number of positrons to the old system., Comment: 10 pages, 5 figures, under consideration for the Special Collection "Non-Neutral Plasmas: Achievements and Perspectives" in JPP

Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous non-invasive acquisition of MR spectra from multiple spatial locations inside the brain. While 1H-MRSI is increasingly used in the human brain, it is not yet widely applied in the preclinical settings, mostly because of difficulties specifically related to very small nominal voxel size in the rodent brain and low concentration of brain metabolites, resulting in low signal-to-noise ratio SNR. In this context, we implemented a free induction decay 1H-MRSI sequence (1H-FID-MRSI) in the rat brain at 14.1T. We combined the advantages of 1H-FID-MRSI with the ultra-high magnetic field to achieve higher SNR, coverage and spatial resolution in the rodent brain, and developed a custom dedicated processing pipeline with a graphical user interface: MRS4Brain toolbox. LCModel fit, using the simulated metabolite basis-set and in-vivo measured MM, provided reliable fits for the data at acquisition delays of 1.3 and 0.94 ms. The resulting Cram\'er-Rao lower bounds were sufficiently low (<30%) for eight metabolites of interest, leading to highly reproducible metabolic maps. Similar spectral quality and metabolic maps were obtained between 1 and 2 averages, with slightly better contrast and brain coverage due to increased SNR in the latter case. Furthermore, the obtained metabolic maps were accurate enough to confirm the previously known brain regional distribution of some metabolites. The acquisitions proved high reproducibility over time. We demonstrated that the increased SNR and spectral resolution at 14.1T can be translated into high spatial resolution in 1H-FID-MRSI of the rat brain in 13 minutes, using the sequence and processing pipeline described herein. High-resolution 1H-FID-MRSI at 14.1T provided reproducible and high-quality metabolic mapping of brain metabolites with significantly reduced technical limitations., Comment: Dunja Simicic and Brayan Alves are joint first authors

The ASACUSA Cusp experiment requires the production of dense positron plasmas with a high repetition rate to produce a beam of antihydrogen. In this work, details of the positron production apparatus used for the first observation of the antihydrogen beam, and subsequent measurements are described in detail. This apparatus replaced the previous compact trap design resulting in an improvement in positron accumulation by a factor of ($52\pm3)$, Comment: 9 pages, 7 figures

A low energy proton source for non-neutral plasma experiments was developed. Electrons from a hot filament ionize H$_2$ gas inside a geometrically compensated Penning trap to produce protons via dissociative ionization. A rotating wall electric field destabilizes the unwanted H$_2^+$ and H$_3^+$ generated in the process while concentrating protons at the center of the trap. The source produces bunches of protons with relatively low ion contamination (5.5% H$_2^+$ and 15.5% H$_3^+$), with energy tunable from 35 to 300 eV.

Methods for reducing the radius, temperature, and space charge of nonneutral plasma are usually reported for conditions which approximate an ideal Penning Malmberg trap. Here we show that (1) similar methods are still effective under surprisingly adverse circumstances: we perform SDR and SDREVC in a strong magnetic mirror field using only 3 out of 4 rotating wall petals. In addition, we demonstrate (2) an alternative to SDREVC, using e-kick instead of EVC and (3) an upper limit for how much plasma can be cooled to T < 20 K using EVC. This limit depends on the space charge, not on the number of particles or the plasma density., Comment: Version 2: a small discrepancy between the N values for Table 1 and Fig. 3 led to an investigation of the charge counting diagnostic. There is a small energy dependence which only became apparent following improvements to pre-SDREVC. The pulsed dump was modified to reduce this dependence. The data for Table 1 and Fig. 3 was taken again with the improved methods

A new sequence for single-voxel diffusion-weighted 1H MRS (DWS), named DW-SPECIAL, is proposed to improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo (STE) diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current gold-standard for rodent DWS experiments at high fields, were performed at 14.1T on phantoms and in vivo on the rat brain. The apparent diffusion coefficient and intra-stick diffusivity (Callaghan's model) were fitted and compared between the sequences for glutamate, glutamine (Gln), myo-inositol, taurine, total N-acetylaspartate, total choline, total creatine and the macromolecules. The shorter echo time achieved with DW-SPECIAL (18 ms against 33 ms with STE-LASER) substantially limited the metabolites' signal loss caused by J-evolution. In addition, DW-SPECIAL preserved the main advantages of STE-LASER: absence of cross-terms, diffusion time during a STE and limited sensitivity to B1 inhomogeneities. In vivo, compared to STE-LASER, DW-SPECIAL yielded the same spectral quality and reduced the Cramer Rao Lower Bounds (CRLB) for J-coupled metabolites, irrespective of the b-value. DW-SPECIAL also reduced the standard deviation of the metabolites' diffusion estimates based on individual animal fitting without loss of accuracy compared to the fit on the averaged decay. We conclude that due to its reduced echo time, DW-SPECIAL can serve as an alternative to STE-LASER when strongly J-coupled metabolites like Gln are investigated, thereby extending the range of accessible metabolites in the context of DWS acquisitions., Comment: Submitted to Magnetic Resonance in Medecine

We present new estimates on the fraction of heavily X-ray obscured, Compton-thick (CT) active galactic nuclei (AGNs) out to a redshift of $z \leq$ 0.8. From a sample of 540 AGNs selected by mid-IR (MIR) properties in observed X-ray survey fields, we forward model the observed-to-intrinsic X-ray luminosity ratio ($R_{L_{\text{X}}}$) with a Markov chain Monte Carlo (MCMC) simulation to estimate the total fraction of CT AGNs ($f_{\text{CT}}$), many of which are missed in typical X-ray observations. We create model $N_{\text{H}}$ distributions and convert these to $R_{L_{\text{X}}}$ using a set of X-ray spectral models. We probe the posterior distribution of our models to infer the population of X-ray non-detected sources. From our simulation we estimate a CT fraction of $f_{\text{CT}}$ = $\text{0.555}^{+\text{0.037}}_{-\text{0.032}}$. We perform an X-ray stacking analysis for sources in Chandra X-ray Observatory fields and find that the expected soft (0.5-2 keV) and hard (2-7 keV) observed fluxes drawn from our model to be within 0.48 and 0.12 dex of our stacked fluxes, respectively. Our results suggests at least 50% of all MIR-selected AGNs, possibly more, are Compton-thick ($N_{\text{H}} \gtrsim$ 10$^{\text{24}}$ cm$^{-\text{2}}$), which is in excellent agreement with other recent work using independent methods. This work indicates that the total number of AGNs is higher than can be identified using X-ray observations alone, highlighting the importance of a multiwavelength approach. A high $f_{\text{CT}}$ also has implications for black hole (BH) accretion physics and supports models of BH and galaxy co-evolution that include periods of heavy obscuration., Comment: 14 pages, 6 figures, 1 table, plus appendix figures. Accepted for publication in ApJ

Lossless compression of dynamic 2D+t and 3D+t medical data is challenging regarding the huge amount of data, the characteristics of the inherent noise, and the high bit depth. Beyond that, a scalable representation is often required in telemedicine applications. Motion Compensated Temporal Filtering works well for lossless compression of medical volume data and additionally provides temporal, spatial, and quality scalability features. To achieve a high quality lowpass subband, which shall be used as a downscaled representative of the original data, graph-based motion compensation was recently introduced to this framework. However, encoding the motion information, which is stored in adjacency matrices, is not well investigated so far. This work focuses on coding these adjacency matrices to make the graph-based motion compensation feasible for data compression. We propose a novel coding scheme based on constructing so-called motion maps. This allows for the first time to compare the performance of graph-based motion compensation to traditional block- and mesh-based approaches. For high quality lowpass subbands our method is able to outperform the block- and mesh-based approaches by increasing the visual quality in terms of PSNR by 0.53dB and 0.28dB for CT data, as well as 1.04dB and 1.90dB for MR data, respectively, while the bit rate is reduced at the same time.

Professional applications like telemedicine often require scalable lossless coding of sensitive data. 3-D subband coding has turned out to offer good compression results for dynamic CT data and additionally provides a scalable representation in terms of low- and highpass subbands. To improve the visual quality of the lowpass subband, motion compensation can be incorporated into the lifting structure, but leads to inferior compression results at the same time. Prior work has shown that a denoising filter in the update step can improve the compression ratio. In this paper, we present a new processing order of motion compensation and denoising in the update step and additionally introduce a second denoising filter in the prediction step. This allows for reducing the overall file size by up to 4.4%, while the visual quality of the lowpass subband is kept nearly constant.

For the lossless compression of dynamic 3-D+t volumes as produced by medical devices like Computed Tomography, various coding schemes can be applied. This paper shows that 3-D subband coding outperforms lossless HEVC coding and additionally provides a scalable representation, which is often required in telemedicine applications. However, the resulting lowpass subband, which shall be used as a downscaled representative of the whole original sequence, contains a lot of ghosting artifacts. This can be alleviated by incorporating motion compensation methods into the subband coder. This results in a high quality lowpass subband but also leads to a lower compression ratio. In order to cope with this, we introduce a new approach for improving the compression efficiency of compensated 3-D wavelet lifting by performing denoising in the update step. We are able to reduce the file size of the lowpass subband by up to 1.64\%, while the lowpass subband is still applicable for being used as a downscaled representative of the whole original sequence., Comment: Picture Coding Symposium (PCS), San Francisco, CA, USA, 2018, pp. 56-60

Efficient lossless coding of medical volume data with temporal axis can be achieved by motion compensated wavelet lifting. As side benefit, a scalable bit stream is generated, which allows for displaying the data at different resolution layers, highly demanded for telemedicine applications. Additionally, the similarity of the temporal base layer to the input sequence is preserved by the use of motion compensated temporal filtering. However, for medical sequences the overall rate is increased due to the specific noise characteristics of the data. The use of denoising filters inside the lifting structure can improve the compression efficiency significantly without endangering the property of perfect reconstruction. However, the design of an optimum filter is a crucial task. In this paper, we present a new method for selecting the optimal filter strength for a certain denoising filter in a rate-distortion sense. This allows to minimize the required rate based on a single input parameter for the encoder to control the requested distortion of the temporal base layer., Comment: IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), Tampere, Finland, 2020, pp. 1-6

Scalable lossless video coding is an important aspect for many professional applications. Wavelet-based video coding decomposes an input sequence into a lowpass and a highpass subband by filtering along the temporal axis. The lowpass subband can be used for previewing purposes, while the highpass subband provides the residual content for lossless reconstruction of the original sequence. The recursive application of the wavelet transform to the lowpass subband of the previous stage yields coarser temporal resolutions of the input sequence. This allows for lower bit rates, but also affects the visual quality of the lowpass subband. So far, the number of total decomposition levels is determined for the entire input sequence in advance. However, if the motion in the video sequence is strong or if abrupt scene changes occur, a further decomposition leads to a low-quality lowpass subband. Therefore, we propose a content adaptive wavelet transform, which locally adapts the depth of the decomposition to the content of the input sequence. Thereby, the visual quality of the low-pass subband is increased by up to 10.28 dB compared to a uniform wavelet transform with the same number of total decomposition levels, while the required rate is reduced by 1.06% additionally.

An efficient scalable data representation is an important task especially in the medical area, e.g. for volumes from Computed Tomography (CT) or Magnetic Resonance Tomography (MRT), when a downscaled version of the original signal is needed. Image and video coders based on wavelet transforms provide an adequate way to naturally achieve scalability. This paper presents a new approach for improving the visual quality of the lowpass band by using a novel graph-based method for motion compensation, which is an important step considering data compression. We compare different kinds of neighborhoods for graph construction and demonstrate that a higher amount of referenced nodes increases the quality of the lowpass band while the mean energy of the highpass band decreases. We show that for cardiac CT data the proposed method outperforms a traditional mesh-based approach of motion compensation by approximately 11 dB in terms of PSNR of the lowpass band. Also the mean energy of the highpass band decreases by around 30%.

Medical applications like Computed Tomography (CT) or Magnetic Resonance Tomography (MRT) often require an efficient scalable representation of their huge output volumes in the further processing chain of medical routine. A downscaled version of such a signal can be obtained by using image and video coders based on wavelet transforms. The visual quality of the resulting lowpass band, which shall be used as a representative, can be improved by applying motion compensation methods during the transform. This paper presents a new approach of using the distorted edge lengths of a mesh-based compensated grid instead of the approximated intensity values of the underlying frame to perform a motion compensation. We will show that an edge adaptive graph-based compensation and its usage for compensated wavelet lifting improves the visual quality of the lowpass band by approximately 2.5 dB compared to the traditional mesh-based compensation, while the additional filesize required for coding the motion information doesn't change.

Anticipating future actions based on spatiotemporal observations is essential in video understanding and predictive computer vision. Moreover, a model capable of anticipating the future has important applications, it can benefit precautionary systems to react before an event occurs. However, unlike in the action recognition task, future information is inaccessible at observation time -- a model cannot directly map the video frames to the target action to solve the anticipation task. Instead, the temporal inference is required to associate the relevant evidence with possible future actions. Consequently, existing solutions based on the action recognition models are only suboptimal. Recently, researchers proposed extending the observation window to capture longer pre-action profiles from past moments and leveraging attention to retrieve the subtle evidence to improve the anticipation predictions. However, existing attention designs typically use frame inputs as the query which is suboptimal, as a video frame only weakly connects to the future action. To this end, we propose an inductive attention model, dubbed IAM, which leverages the current prediction priors as the query to infer future action and can efficiently process the long video content. Furthermore, our method considers the uncertainty of the future via the many-to-many association in the attention design. As a result, IAM consistently outperforms the state-of-the-art anticipation models on multiple large-scale egocentric video datasets while using significantly fewer model parameters.