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Generic image inpainting aims to complete a corrupted image by borrowing surrounding information, which barely generates novel content. By contrast, multi-modal inpainting provides more flexible and useful controls on the inpainted content, \eg, a text prompt can be used to describe an object with richer attributes, and a mask can be used to constrain the shape of the inpainted object rather than being only considered as a missing area. We propose a new diffusion-based model named SmartBrush for completing a missing region with an object using both text and shape-guidance. While previous work such as DALLE-2 and Stable Diffusion can do text-guided inapinting they do not support shape guidance and tend to modify background texture surrounding the generated object. Our model incorporates both text and shape guidance with precision control. To preserve the background better, we propose a novel training and sampling strategy by augmenting the diffusion U-net with object-mask prediction. Lastly, we introduce a multi-task training strategy by jointly training inpainting with text-to-image generation to leverage more training data. We conduct extensive experiments showing that our model outperforms all baselines in terms of visual quality, mask controllability, and background preservation.

We study differential complexes of Kolmogorov-Alexander-Spanier type on metric measure spaces associated with unbounded non-local operators, such as operators of fractional Laplacian type. We define Hilbert complexes, observe invariance properties and obtain self-adjoint non-local analogues of Hodge Laplacians. For $d$-regular measures and operators of fractional Laplacian type we provide results on removable sets in terms of Hausdorff measures. We prove a Mayer-Vietoris principle and a Poincar\'e lemma and verify that in the compact Riemannian manifold case the deRham cohomology can be recovered.

Object detection neural network models need to perform reliably in highly dynamic and safety-critical environments like automated driving or robotics. Therefore, it is paramount to verify the robustness of the detection under unexpected hardware faults like soft errors that can impact a systems perception module. Standard metrics based on average precision produce model vulnerability estimates at the object level rather than at an image level. As we show in this paper, this does not provide an intuitive or representative indicator of the safety-related impact of silent data corruption caused by bit flips in the underlying memory but can lead to an over- or underestimation of typical fault-induced hazards. With an eye towards safety-related real-time applications, we propose a new metric IVMOD (Image-wise Vulnerability Metric for Object Detection) to quantify vulnerability based on an incorrect image-wise object detection due to false positive (FPs) or false negative (FNs) objects, combined with a severity analysis. The evaluation of several representative object detection models shows that even a single bit flip can lead to a severe silent data corruption event with potentially critical safety implications, with e.g., up to (much greater than) 100 FPs generated, or up to approx. 90% of true positives (TPs) are lost in an image. Furthermore, with a single stuck-at-1 fault, an entire sequence of images can be affected, causing temporally persistent ghost detections that can be mistaken for actual objects (covering up to approx. 83% of the image). Furthermore, actual objects in the scene are continuously missed (up to approx. 64% of TPs are lost). Our work establishes a detailed understanding of the safety-related vulnerability of such critical workloads against hardware faults., Comment: 15 pages, accepted in safecomp22 conference

SCALES is a high-contrast, infrared coronagraphic imager and integral field spectrograph (IFS) to be deployed behind the W.M. Keck Observatory adaptive optics system. A reflective optical design allows diffraction-limited imaging over a large wavelength range (1.0 - 5.0 microns). A microlens array-based IFS coupled with a lenslet reformatter ("slenslit") allow spectroscopy at both low (R = 35 - 250) and moderate (R = 2000 - 6500) spectral resolutions. The large wavelength range, diffraction-limited performance, high contrast coronagraphy and cryogenic operation present a unique optical design challenge. We present the full SCALES optical design, including performance modeling and analysis and manufacturing., Comment: SPIE Astronomical Telescopes and Instrumentation, 2022

We present the design of SCALES (Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy) a new 2-5 micron coronagraphic integral field spectrograph under construction for Keck Observatory. SCALES enables low-resolution (R~50) spectroscopy, as well as medium-resolution (R~4,000) spectroscopy with the goal of discovering and characterizing cold exoplanets that are brightest in the thermal infrared. Additionally, SCALES has a 12x12" field-of-view imager that will be used for general adaptive optics science at Keck. We present SCALES's specifications, its science case, its overall design, and simulations of its expected performance. Additionally, we present progress on procuring, fabricating and testing long lead-time components., Comment: 19 pages, 12 Figures, SPIE Astronomical Telescopes + Instrumentation, (#12184-18), 2022, Montreal, Canada

Machine learning can provide predictions with disparate outcomes, in which subgroups of the population (e.g., defined by age, gender, or other sensitive attributes) are systematically disadvantaged. In order to comply with upcoming legislation, practitioners need to locate such disparate outcomes. However, previous literature typically detects disparities through statistical procedures for when the sensitive attribute is specified a priori. This limits applicability in real-world settings where datasets are high dimensional and, on top of that, sensitive attributes may be unknown. As a remedy, we propose a data-driven framework called Automatic Location of Disparities (ALD) which aims at locating disparities in machine learning. ALD meets several demands from industry: ALD (1) is applicable to arbitrary machine learning classifiers; (2) operates on different definitions of disparities (e.g., statistical parity or equalized odds); and (3) deals with both categorical and continuous predictors even if disparities arise from complex and multi-way interactions known as intersectionality (e. g., age above 60 and female). ALD produces interpretable audit reports as output. We demonstrate the effectiveness of ALD based on both synthetic and real-world datasets. As a result, we empower practitioners to effectively locate and mitigate disparities in machine learning algorithms, conduct algorithmic audits, and protect individuals from discrimination.

The development of the Keck All sky Precision Adaptive optics (KAPA) project was initiated in September 2018 to upgrade the Keck I adaptive optics (AO) system to enable laser tomography adaptive optics (LTAO) with a four laser guide star (LGS) asterism. The project includes the replacement of the existing LMCT laser with a Toptica laser, the implementation of a new real-time controller (RTC) and wavefront sensor optics and camera, and a new daytime calibration and test platform to provide the required infrastructure for laser tomography. The work presented here describes the new daytime calibration infrastructure to test the performance for the KAPA tomographic algorithms. This paper outlines the hardware infrastructure for daytime calibration and performance assessment of tomographic algorithms. This includes the implementation of an asterism simulator having fiber-coupled light sources simulating four Laser Guide Stars (LGS) and two Natural Guide Stars (NGS) at the AO bench focus, as well as the upgrade of the existing TelSim on the AO bench to simulate focal anisoplanatism and wind driven atmospheric turbulence. A phase screen, that can be adjusted in effective altitude, is used to simulate wind speeds up to 10 m/s for a duration of upto 3 s., Comment: 15 pages, 13 figures. Publishd as part of SPIE Astronomical telescopes + Instrumentation 2022 proceedings

Improving direct detection capability close to the star through improved star-subtraction and post-processing techniques is vital for discovering new low-mass companions and characterizing known ones at longer wavelengths. We present results of 17 binary star systems observed with the Magellan Adaptive Optics system (MagAO) and the Clio infrared camera on the Magellan Clay Telescope using Binary Differential Imaging (BDI). BDI is an application of Reference Differential Imaging (RDI) and Angular Differential Imaging (ADI) applied to wide binary star systems (2\arcsec $<\Delta \rho<$ 10\arcsec) within the isoplanatic patch in the infrared. Each star serves as the point-spread-function (PSF) reference for the other, and we performed PSF estimation and subtraction using Principal Component Analysis. We report contrast and mass limits for the 35 stars in our initial survey using BDI with MagAO/Clio in L$^\prime$ and 3.95$\mu$m bands. Our achieved contrasts varied between systems, and spanned a range of contrasts from 3.0-7.5 magnitudes and a range of separations from 0.2\arcsec to $\sim$2\arcsec. Stars in our survey span a range of masses, and our achieved contrasts correspond to late-type M dwarf masses down to $\sim$10 M$_{\rm{jup}}$. We also report detection of a candidate companion signal at 0.2\arcsec (18 AU) around HIP 67506 A (SpT G5V, mass $\sim$1.2\Msun), which we estimate to be ~60-90 M$_{\rm{jup}}$. We found that the effectiveness of BDI is highest for approximately equal brightness binaries in high-Strehl conditions., Comment: 25 pages, 8 figures, 3 tables; Accepted to MNRAS

In this work we present a keV-scale sterile-neutrino search with the first tritium data of the KATRIN experiment, acquired in the commissioning run in 2018. KATRIN performs a spectroscopic measurement of the tritium $\beta$-decay spectrum with the main goal of directly determining the effective electron anti-neutrino mass. During this commissioning phase a lower tritium activity facilitated the search for sterile neutrinos with a mass of up to $1.6\, \mathrm{keV}$. We do not find a signal and set an exclusion limit on the sterile-to-active mixing amplitude of down to $\sin^2\theta < 5\cdot10^{-4}$ ($95\,\%$ C.L.), improving current laboratory-based bounds in the sterile-neutrino mass range between 0.1 and $1.0\, \mathrm{keV}$.

Some extensions of the Standard Model of Particle Physics allow for Lorentz invariance and Charge-Parity-Time (CPT)-invariance violations. In the neutrino sector strong constraints have been set by neutrino-oscillation and time-of-flight experiments. However, some Lorentz-invariance-violating parameters are not accessible via these probes. In this work, we focus on the parameters $(a_{\text{of}}^{(3)})_{00}$, $(a_{\text{of}}^{(3)})_{10}$ and $(a_{\text{of}}^{(3)})_{11}$ which would manifest themselves in a non-isotropic beta-decaying source as a sidereal oscillation and an overall shift of the spectral endpoint. Based on the data of the first scientific run of the KATRIN experiment, we set the first limit on $\left|(a_{\text{of}}^{(3)})_{11}\right|$ of $< 3.7\cdot10^{-6}$ GeV at 90\% confidence level. Moreover, we derive new constraints on $(a_{\text{of}}^{(3)})_{00}$ and $(a_{\text{of}}^{(3)})_{10}$.

We present the fifth incarnation of the Mid-Infrared Array Camera (MIRAC-5) instrument which will use a new GeoSnap (3 - 13 microns) detector. Advances in adaptive optics (AO) systems and detectors are enabling ground-based mid-infrared systems capable of high spatial resolution and deep contrast. As one of the only 3 - 13 micron cameras used in tandem with AO, MIRAC-5 will be complementary to the James Webb Space Telescope (JWST) and capable of characterizing gas giant exoplanets and imaging forming protoplanets (helping to characterize their circumplanetary disks). We describe key features of the MIRAC-5 GeoSnap detector, a long-wave Mercury-Cadmium-Telluride (MCT) array produced by Teledyne Imaging Sensors (TIS), including its high quantum efficiency (> 65%), large well-depth, and low noise. We summarize MIRAC-5's important capabilities, including prospects for obtaining the first continuum mid-infrared measurements for several gas giants and the first 10.2-10.8 micron NH3 detection in the atmosphere of the warm companion GJ 504b (Teff ~550 K) within 8 hours of observing time. Finally, we describe plans for future upgrades to MIRAC-5 such as adding a coronagraph. MIRAC-5 will be commissioned on the MMT utilizing the new MAPS AO system in late 2022 with plans to move to Magellan with the MagAO system in the future., Comment: 8 pages, 4 figures, To appear in the SPIE Proceedings 'Astronomical Telescopes and Instrumentation' (2022)