Detection of very high energy gamma-ray emission from the gravitationally lensed blazar QSO B0218+357 with the MAGIC telescopes

open153siContext. QSO B0218+357 is a gravitationally lensed blazar located at a redshift of 0.944. The gravitational lensing splits the emitted radiation into two components that are spatially indistinguishable by gamma-ray instruments, but separated by a 10–12 day delay. In July 2014, QSO B0218+357 experienced a violent flare observed by the Fermi-LAT and followed by the MAGIC telescopes. Aims. The spectral energy distribution of QSO B0218+357 can give information on the energetics of z ∼ 1 very high energy gamma-ray sources. Moreover the gamma-ray emission can also be used as a probe of the extragalactic background light at z ∼ 1. Methods. MAGIC performed observations of QSO B0218+357 during the expected arrival time of the delayed component of the emission. The MAGIC and Fermi-LAT observations were accompanied by quasi-simultaneous optical data from the KVA telescope and X-ray observations by Swift-XRT. We construct a multiwavelength spectral energy distribution of QSO B0218+357 and use it to model the source. The GeV and sub-TeV data obtained by Fermi-LAT and MAGIC are used to set constraints on the extragalactic background light. Results. Very high energy gamma-ray emission was detected from the direction of QSO B0218+357 by the MAGIC telescopes during the expected time of arrival of the trailing component of the flare, making it the farthest very high energy gamma-ray source detected to date. The observed emission spans the energy range from 65 to 175 GeV. The combined MAGIC and Fermi-LAT spectral energy distribution of QSO B0218+357 is consistent with current extragalactic background light models. The broadband emission can be modeled in the framework of a two-zone external Compton scenario, where the GeV emission comes from an emission region in the jet, located outside the broad line region.openAhnen, M. L.; Ansoldi, S.; Antonelli, L. A.; Antoranz, P.; Arcaro, CORNELIA HANNA ESTHER; Babic, A.; Banerjee, B.; Bangale, P.; Barres De Almeida, U.; Barrio, J. A.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Berti, A.; Biasuzzi, B.; Biland, A.; Blanch, O.; Bonnefoy, S.; Bonnoli, G.; Borracci, F.; Bretz, T.; Buson, S.; Carosi, A.; Chatterjee, A.; Clavero, R.; Colin, P.; Colombo, E.; Contreras, J. L.; Cortina, J.; Covino, S.; Da Vela, P.; Dazzi, F.; De Angelis, A.; De Lotto, B.; De Onã Wilhelmi, E.; Di Pierro, F.; Doert, M.; Domínguez, A.; Dominis Prester, D.; Dorner, D.; Doro, Michele; Einecke, S.; Eisenacher Glawion, D.; Elsaesser, D.; Engelkemeier, M.; Fallah Ramazani, V.; Fernández Barral, A.; Fidalgo, D.; Fonseca, M. V.; Font, L.; Frantzen, K.; Fruck, C.; Galindo, D.; Garciá López, R. J.; Garczarczyk, M.; Garrido Terrats, D.; Gaug, M.; Giammaria, P.; Godinović, N.; Gora, D.; Guberman, D.; Hadasch, D.; Hahn, A.; Hayashida, M.; Herrera, J.; Hose, J.; Hrupec, D.; Hughes, G.; Idec, W.; Kodani, K.; Konno, Y.; Kubo, H.; Kushida, J.; La Barbera, A.; Lelas, D.; Lindfors, E.; Lombardi, S.; Longo, F.; López, M.; López Coto, R.; Majumdar, P.; Makariev, M.; Mallot, K.; Maneva, G.; Manganaro, M.; Mannheim, K.; Maraschi, L.; Marcote, B.; Mariotti, Mose'; Martínez, M.; Mazin, D.; Menzel, U.; Miranda, J. M.; Mirzoyan, R.; Moralejo, A.; Moretti, E.; Nakajima, D.; Neustroev, V.; Niedzwiecki, A.; Nievas Rosillo, M.; Nilsson, K.; Nishijima, K.; Noda, K.; Nogués, L.; Paiano, Simona; Palacio, J.; Palatiello, M.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Paredes Fortuny, X.; Pedaletti, G.; Peresano, M.; Perri, L.; Persic, M.; Poutanen, J.; Prada Moroni, P. G.; Prandini, Elisa; Puljak, I.; Garcia, J. R.; Reichardt, I.; Rhode, W.; Ribó, M.; Rico, J.; Saito, T.; Satalecka, K.; Schroeder, S.; Schweizer, T.; Shore, S. N.; Sillanpaä, A.; Sitarek, J.; Snidaric, I.; Sobczynska, D.; Stamerra, A.; Strzys, M.; Surić, T.; Takalo, L.; Tavecchio, F.; Temnikov, P.; Terzić, T.; Tescaro, Diego; Teshima, M.; Torres, D. F.; Toyama, T.; Treves, A.; Vanzo, G.; Verguilov, V.; Vovk, I.; Ward, J. E.; Will, M.; M. H., Wu; Zanin, Roberta; Desiante, R.Ahnen, M. L.; Ansoldi, S.; Antonelli, L. A.; Antoranz, P.; Arcaro, CORNELIA HANNA ESTHER; Babic, A.; Banerjee, B.; Bangale, P.; Barres De Almeida, U.; Barrio, J. A.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Berti, A.; Biasuzzi, B.; Biland, A.; Blanch, O.; Bonnefoy, S.; Bonnoli, G.; Borracci, F.; Bretz, T.; Buson, S.; Carosi, A.; Chatterjee, A.; Clavero, R.; Colin, P.; Colombo, E.; Contreras, J. L.; Cortina, J.; Covino, S.; Da Vela, P.; Dazzi, F.; De Angelis, A.; De Lotto, B.; De Onã Wilhelmi, E.; Di Pierro, F.; Doert, M.; Domínguez, A.; Dominis Prester, D.; Dorner, D.; Doro, Michele; Einecke, S.; Eisenacher Glawion, D.; Elsaesser, D.; Engelkemeier, M.; Fallah Ramazani, V.; Fernández Barral, A.; Fidalgo, D.; Fonseca, M. V.; Font, L.; Frantzen, K.; Fruck, C.; Galindo, D.; Garciá López, R. J.; Garczarczyk, M.; Garrido Terrats, D.; Gaug, M.; Giammaria, P.; Godinović, N.; Gora, D.; Guberman, D.; Hadasch, D.; Hahn, A.; Hayashida, M.; Herrera, J.; Hose, J.; Hrupec, D.; Hughes, G.; Idec, W.; Kodani, K.; Konno, Y.; Kubo, H.; Kushida, J.; La Barbera, A.; Lelas, D.; Lindfors, E.; Lombardi, S.; Longo, F.; López, M.; López Coto, R.; Majumdar, P.; Makariev, M.; Mallot, K.; Maneva, G.; Manganaro, M.; Mannheim, K.; Maraschi, L.; Marcote, B.; Mariotti, Mose'; Martínez, M.; Mazin, D.; Menzel, U.; Miranda, J. M.; Mirzoyan, R.; Moralejo, A.; Moretti, E.; Nakajima, D.; Neustroev, V.; Niedzwiecki, A.; Nievas Rosillo, M.; Nilsson, K.; Nishijima, K.; Noda, K.; Nogués, L.; Paiano, Simona; Palacio, J.; Palatiello, M.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Paredes Fortuny, X.; Pedaletti, G.; Peresano, M.; Perri, L.; Persic, M.; Poutanen, J.; Prada Moroni, P. G.; Prandini, Elisa; Puljak, I.; Garcia, J. R.; Reichardt, I.; Rhode, W.; Ribó, M.; Rico, J.; Saito, T.; Satalecka, K.; Schroeder, S.; Schweizer, T.; Shore, S. N.; Sillanpaä, A.; Sitarek, J.; Snidaric, I.; Sobczynska, D.; Stamerra, A.; Strzys, M.; Surić, T.; Takalo, L.; Tavecchio, F.; Temnikov, P.; Terzić, T.; Tescaro, Diego; Teshima, M.; Torres, D. F.; Toyama, T.; Treves, A.; Vanzo, G.; Verguilov, V.; Vovk, I.; Ward, J. E.; Will, M.; Wu, M. H.; Zanin, Roberta; Desiante, R

Prediction of user action in moving-target selection tasks

Selection of moving targets is a common task in human–computer interaction (HCI), and more specifically in virtual reality (VR). In spite of the increased number of applications involving moving–target selection, HCI and VR studies have largely focused on static-target selection. Compared to its static-target counterpart, however, moving-target selection poses special challenges, including the need to continuously and simultaneously track the target and plan to reach for it, which may be difficult depending on the user’s reactiveness and the target’s movement. Action prediction has proven to be the most comprehensive enhancement to address moving-target selection challenges. Current predictive techniques, however, heavily rely on continuous tracking of user actions, without considering the possibility that target-reaching actions may have a dominant pre-programmed component—this theory is known as the pre-programmed control theory. Thus, based on the pre-programmed control theory, this research explores the possibility of predicting moving-target selection prior to action execution. Specifically, three levels of action prediction are investigated: action performance, prospective action difficulty, and intention. The proposed performance models predict the movement time (MT) required to reach for a moving target in 2-D and 3-D space, and are useful to compare users and interfaces objectively. The prospective difficulty (PD) models predict the subjective effort required to reach for a moving target, without actually executing the action, and can therefore be measured when performance can not. Finally, the intention models predict the target that the user plans to select, and can therefore be used to facilitate the selection of the intended target. Intention prediction models are developed using decision trees and scoring functions, and evaluated in two VR studies: the first investigates undirected selection (i.e., tasks in which the users are free to select an object among multiple others), and the second directed selection (i.e., the more common experimental task in which users are instructed to select a specific object). PD models for 1-D, and 2-D moving-target selection tasks are developed based on Fitts’ Law, and evaluated in an online experiment. Finally, MT models with the same structural form of the aforementioned PD models are evaluated in a 3-D moving-target selection experiment deployed in VR. Aside from intention predictions on directed selection, all of the explored models yield relatively high accuracies—up to ~78% predicting intended targets in undirected tasks, R^2 = .97 predicting PD, and R^2 = .93 predicting MT

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Integral Field Unit Observations of NGC 891: Kinematics of the Diffuse Ionized Gas Halo

We present high and moderate spectral resolution spectroscopy of diffuse ionized gas (DIG) emission in the halo of NGC 891. The data were obtained with the SparsePak integral field unit at the WIYN Observatory. The wavelength coverage includes the [NII]6548,6583, Halpha, and [SII]6716,6731 emission lines. Position-velocity (PV) diagrams, constructed using spectra extracted from four SparsePak pointings in the halo, are used to examine the kinematics of the DIG. Using two independent methods, a vertical gradient in azimuthal velocity is found to be present in the northeast quadrant of the halo, with magnitude approximately 15-18 km/s/kpc, in agreement with results from HI observations. The kinematics of the DIG suggest that this gradient begins at approximately 1 kpc above the midplane. In another part of the halo, the southeast quadrant, the kinematics are markedly different, and suggest rotation at about 175 km/s, much slower than the disk but with no vertical gradient. We utilize an entirely ballistic model of disk-halo flow in an attempt to reproduce the kinematics observed in the northeast quadrant. Analysis shows that the velocity gradient predicted by the ballistic model is far too shallow. Based on intensity cuts made parallel to the major axis in the ballistic model and an Halpha image of NGC 891 from the literature, we conclude that the DIG halo is much more centrally concentrated than the model, suggesting that hydrodynamics dominate over ballistic motion in shaping the density structure of the halo. Velocity dispersion measurements along the minor axis of NGC 891 seem to indicate a lack of radial motions in the halo, but the uncertainties do not allow us to set firm limits.Comment: 31 pages, 10 figures. Accepted for publication in the Astrophysical Journa

Detection of very high energy gamma-ray emission from the gravitationally-lensed blazar QSO B0218+357 with the MAGIC telescopes

Context. QSO B0218+357 is a gravitationally lensed blazar located at a redshift of 0.944. The gravitational lensing splits the emitted radiation into two components, spatially indistinguishable by gamma-ray instruments, but separated by a 10-12 day delay. In July 2014, QSO B0218+357 experienced a violent flare observed by the Fermi-LAT and followed by the MAGIC telescopes. Aims. The spectral energy distribution of QSO B0218+357 can give information on the energetics of z ~ 1 very high energy gamma- ray sources. Moreover the gamma-ray emission can also be used as a probe of the extragalactic background light at z ~ 1. Methods. MAGIC performed observations of QSO B0218+357 during the expected arrival time of the delayed component of the emission. The MAGIC and Fermi-LAT observations were accompanied by quasi-simultaneous optical data from the KVA telescope and X-ray observations by Swift-XRT. We construct a multiwavelength spectral energy distribution of QSO B0218+357 and use it to model the source. The GeV and sub-TeV data, obtained by Fermi-LAT and MAGIC, are used to set constraints on the extragalactic background light. Results. Very high energy gamma-ray emission was detected from the direction of QSO B0218+357 by the MAGIC telescopes during the expected time of arrival of the trailing component of the flare, making it the farthest very high energy gamma-ray sources detected to date. The observed emission spans the energy range from 65 to 175 GeV. The combined MAGIC and Fermi-LAT spectral energy distribution of QSO B0218+357 is consistent with current extragalactic background light models. The broad band emission can be modeled in the framework of a two zone external Compton scenario, where the GeV emission comes from an emission region in the jet, located outside the broad line region.Comment: 11 pages, 6 figures, accepted for publication in A&

The Photodetector Array Camera and Spectrometer (PACS) on the Herschel Space Observatory

The Photodetector Array Camera and Spectrometer (PACS) is one of the three science instruments on ESA's far infrared and submillimetre observatory. It employs two Ge:Ga photoconductor arrays (stressed and unstressed) with 16x25 pixels, each, and two filled silicon bolometer arrays with 16x32 and 32x64 pixels, respectively, to perform integral-field spectroscopy and imaging photometry in the 60-210\mu\ m wavelength regime. In photometry mode, it simultaneously images two bands, 60-85\mu\ m or 85-125\mu\m and 125-210\mu\ m, over a field of view of ~1.75'x3.5', with close to Nyquist beam sampling in each band. In spectroscopy mode, it images a field of 47"x47", resolved into 5x5 pixels, with an instantaneous spectral coverage of ~1500km/s and a spectral resolution of ~175km/s. We summarise the design of the instrument, describe observing modes, calibration, and data analysis methods, and present our current assessment of the in-orbit performance of the instrument based on the Performance Verification tests. PACS is fully operational, and the achieved performance is close to or better than the pre-launch predictions

The Science Case for an Extended Spitzer Mission

Although the final observations of the Spitzer Warm Mission are currently scheduled for March 2019, it can continue operations through the end of the decade with no loss of photometric precision. As we will show, there is a strong science case for extending the current Warm Mission to December 2020. Spitzer has already made major impacts in the fields of exoplanets (including microlensing events), characterizing near Earth objects, enhancing our knowledge of nearby stars and brown dwarfs, understanding the properties and structure of our Milky Way galaxy, and deep wide-field extragalactic surveys to study galaxy birth and evolution. By extending Spitzer through 2020, it can continue to make ground-breaking discoveries in those fields, and provide crucial support to the NASA flagship missions JWST and WFIRST, as well as the upcoming TESS mission, and it will complement ground-based observations by LSST and the new large telescopes of the next decade. This scientific program addresses NASA's Science Mission Directive's objectives in astrophysics, which include discovering how the universe works, exploring how it began and evolved, and searching for life on planets around other stars.Comment: 75 pages. See page 3 for Table of Contents and page 4 for Executive Summar

Time Dependent Modeling of the Markarian 501 X-ray and TeV Gamma-Ray Data Taken During March and April, 1997

If the high-energy emission from TeV blazars is produced by the Synchrotron Self-Compton (SSC) mechanism, then simultaneous X-ray and Gamma-ray observations of these objects are a powerful probe of the electron (and/or positron) populations responsible for this emission. Understanding the emitting particle distributions and their evolution in turn allow us to probe physical conditions in the inner blazar jet and test, for example, various acceleration scenarios. By constraining the SSC emission model parameters, such observations also allow us to predict the intrinsic (unabsorbed) Gamma-ray spectra of these sources, a major uncertainty in current attempts to use the observed Gamma-ray spectra to constrain the intensity of the extragalactic background at optical/infrared wavelengths. As a next step in testing the SSC model and as a demonstration of the potential power of coordinated X-ray and Gamma-ray observations, we attempt to model in detail the X-ray and Gamma-ray light curves of the TeV Blazar Mrk 501 during its April-May 1997 outburst using a time dependent SSC emission model. Extensive, quasi-simultaneous X-ray and gamma-ray coverage exists for this period. We discuss and explore quantitatively several of the flare scenarios presented in the literature. We show that simple two-component models (with a soft, steady X-ray component plus a variable SSC component) involving substantial pre-acceleration of electrons to Lorentz factors on the order of 1E+5 describe the data train surprisingly well. All considered models imply an emission region that is strongly out of equipartition and low radiative efficiencies (ratio between kinetic jet luminosity and comoving radiative luminosity) of 1 per-mill and less.Comment: 16 pages, Refereed Manuscript. Minor changes to previous versio

Reset-free Trial-and-Error Learning for Robot Damage Recovery

The high probability of hardware failures prevents many advanced robots (e.g., legged robots) from being confidently deployed in real-world situations (e.g., post-disaster rescue). Instead of attempting to diagnose the failures, robots could adapt by trial-and-error in order to be able to complete their tasks. In this situation, damage recovery can be seen as a Reinforcement Learning (RL) problem. However, the best RL algorithms for robotics require the robot and the environment to be reset to an initial state after each episode, that is, the robot is not learning autonomously. In addition, most of the RL methods for robotics do not scale well with complex robots (e.g., walking robots) and either cannot be used at all or take too long to converge to a solution (e.g., hours of learning). In this paper, we introduce a novel learning algorithm called "Reset-free Trial-and-Error" (RTE) that (1) breaks the complexity by pre-generating hundreds of possible behaviors with a dynamics simulator of the intact robot, and (2) allows complex robots to quickly recover from damage while completing their tasks and taking the environment into account. We evaluate our algorithm on a simulated wheeled robot, a simulated six-legged robot, and a real six-legged walking robot that are damaged in several ways (e.g., a missing leg, a shortened leg, faulty motor, etc.) and whose objective is to reach a sequence of targets in an arena. Our experiments show that the robots can recover most of their locomotion abilities in an environment with obstacles, and without any human intervention.Comment: 18 pages, 16 figures, 3 tables, 6 pseudocodes/algorithms, video at https://youtu.be/IqtyHFrb3BU, code at https://github.com/resibots/chatzilygeroudis_2018_rt

Precise Stellar Radial Velocities of an M Dwarf with a Michelson Interferometer and a Medium-resolution Near-infrared Spectrograph

Precise near-infrared radial velocimetry enables efficient detection and transit verification of low-mass extrasolar planets orbiting M dwarf hosts, which are faint for visible-wavelength radial velocity surveys. The TripleSpec Exoplanet Discovery Instrument, or TEDI, is the combination of a variable-delay Michelson interferometer and a medium-resolution (R=2700) near-infrared spectrograph on the Palomar 200" Hale Telescope. We used TEDI to monitor GJ 699, a nearby mid-M dwarf, over 11 nights spread across 3 months. Analysis of 106 independent observations reveals a root-mean-square precision of less than 37 m/s for 5 minutes of integration time. This performance is within a factor of 2 of our expected photon-limited precision. We further decompose the residuals into a 33 m/s white noise component, and a 15 m/s systematic noise component, which we identify as likely due to contamination by telluric absorption lines. With further development this technique holds promise for broad implementation on medium-resolution near-infrared spectrographs to search for low-mass exoplanets orbiting M dwarfs, and to verify low-mass transit candidates.Comment: 55 pages and 13 figures in aastex format. Accepted by PAS