Engineering topics

Sakamoto, Takanori

Publications and source records attributed to Sakamoto, Takanori.

12 records

DOE OSTI2021

Gravitational wave physics and astronomy in the nascent era

The detections of gravitational waves (GW) by the LIGO/Virgo collaborations provide various possibilities for both physics and astronomy. We are quite sure that GW observations will develop a lot, both in precision and in number, thanks to the continuous work on the improvement of detectors, including the expected new detector, KAGRA, and the planned detector, LIGO-India. On this occasion, we review the fundamental outcomes and prospects of gravitational wave physics and astronomy. We survey the development, focusing on representative sources of gravitational waves: binary black holes, binary neutron stars, and supernovae. We also summarize the role of gravitational wave observations as a probe of new physics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Bimodal Long-lasting Components in Short Gamma-Ray Bursts: Promising Electromagnetic Counterparts to Neutron Star Binary Mergers

Long-lasting emission of short gamma-ray bursts (GRBs) is crucial to reveal the physical origin of the central engine as well as to detect electromagnetic (EM) counterparts to gravitational waves (GWs) from neutron star binary mergers. We investigate 65 X-ray light curves of short GRBs, which is six times more than previous studies, by combining both Swift /BAT and XRT data. The light curves are found to consist of two distinct components at >5 σ with bimodal distributions of luminosity and duration, i.e., extended (with a timescale of ≲10{sup 3} s) and plateau emission (with a timescale of ≳10{sup 3} s), which are likely the central engine activities, but not afterglows. The extended emission has an isotropic energy comparable to the prompt emission, while the plateau emission has ∼0.01–1 times this energy. Half (50%) of our sample has both components, while the other half is consistent with having both components. This leads us to conjecture that almost all short GRBs have both the extended and plateau emission. The long-lasting emission can be explained by the jets from black holes with fallback ejecta, and could power macronovae (or kilonovae) like GRB 130603B and GRB 160821B. Based on the observed properties, we quantify the detectability of EM counterparts to GWs, including the plateau emission scattered to the off-axis angle, with CALET /HXM, INTEGRAL /SPI-ACS, Fermi /GBM, MAXI /GSC, Swift /BAT, XRT, the future ISS-Lobster /WFI, Einstein Probe /WXT, and eROSITA .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

THE THIRD SWIFT BURST ALERT TELESCOPE GAMMA-RAY BURST CATALOG

To date, the Burst Alert Telescope (BAT) onboard Swift has detected ∼1000 gamma-ray bursts (GRBs), of which ∼360 GRBs have redshift measurements, ranging from z = 0.03 to z = 9.38. We present the analyses of the BAT-detected GRBs for the past ∼11 years up through GRB 151027B. We report summaries of both the temporal and spectral analyses of the GRB characteristics using event data (i.e., data for each photon within approximately 250 s before and 950 s after the BAT trigger time), and discuss the instrumental sensitivity and selection effects of GRB detections. We also explore the GRB properties with redshift when possible. The result summaries and data products are available at http://swift.gsfc.nasa.gov/results/batgrbcat/index.html. In addition, we perform searches for GRB emissions before or after the event data using the BAT survey data. We estimate the false detection rate to be only one false detection in this sample. There are 15 ultra-long GRBs (∼2% of the BAT GRBs) in this search with confirmed emission beyond ∼1000 s of event data, and only two GRBs (GRB 100316D and GRB 101024A) with detections in the survey data prior to the starting of event data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Modeling the Swift BAT trigger algorithm with machine learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift/BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of ≳97% (≲3% error), which is a significant improvement on a cut in GRB flux, which has an accuracy of 89.6% (10.4% error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of n{sub 0}∼0.48{sub −0.23}{sup +0.41} Gpc{sup −3} yr{sup −1} with power-law indices of n{sub 1}∼1.7{sub −0.5}{sup +0.6} and n{sub 2}∼−5.9{sub −0.1}{sup +5.7} for GRBs above and below a break point of z{sub 1}∼6.8{sub −3.2}{sup +2.8}. This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2016

Modeling the Swift Bat Trigger Algorithm with Machine Learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift / BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of greater than or equal to 97 percent (less than or equal to 3 percent error), which is a significant improvement on a cut in GRB flux, which has an accuracy of 89.6 percent (10.4 percent error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of n (sub 0) approaching 0.48 (sup plus 0.41) (sub minus 0.23) per cubic gigaparsecs per year with power-law indices of n (sub 1) approaching 1.7 (sup plus 0.6) (sub minus 0.5) and n (sub 2) approaching minus 5.9 (sup plus 5.7) (sub minus 0.1) for GRBs above and below a break point of z (redshift) (sub 1) approaching 6.8 (sup plus 2.8) (sub minus 3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting.

gamma-ray burst: general â€“ gamma-rays: general â↗

NASA NTRS2015

Modeling the Swift BAT Trigger Algorithm with Machine Learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. (2014) is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of approximately greater than 97% (approximately less than 3% error), which is a significant improvement on a cut in GRB flux which has an accuracy of 89:6% (10:4% error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of eta(sub 0) approximately 0.48(+0.41/-0.23) Gpc(exp -3) yr(exp -1) with power-law indices of eta(sub 1) approximately 1.7(+0.6/-0.5) and eta(sub 2) approximately -5.9(+5.7/-0.1) for GRBs above and below a break point of z(sub 1) approximately 6.8(+2.8/-3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting. The code used in this is analysis is publicly available online.

gamma rays: general↗

NASA NTRS2013

Probing the Cosmic Gamma-Ray Burst Rate with Trigger Simulations of the Swift Burst Alert Telescope

The gamma-ray burst (GRB) rate is essential for revealing the connection between GRBs, supernovae and stellar evolution. Additionally, the GRB rate at high redshift provides a strong probe of star formation history in the early universe. While hundreds of GRBs are observed by Swift, it remains difficult to determine the intrinsic GRB rate due to the complex trigger algorithm of Swift. Current studies of the GRB rate usually approximate the Swift trigger algorithm by a single detection threshold. However, unlike the previously own GRB instruments, Swift has over 500 trigger criteria based on photon count rate and additional image threshold for localization. To investigate possible systematic biases and explore the intrinsic GRB properties, we develop a program that is capable of simulating all the rate trigger criteria and mimicking the image threshold. Our simulations show that adopting the complex trigger algorithm of Swift increases the detection rate of dim bursts. As a result, our simulations suggest bursts need to be dimmer than previously expected to avoid over-producing the number of detections and to match with Swift observations. Moreover, our results indicate that these dim bursts are more likely to be high redshift events than low-luminosity GRBs. This would imply an even higher cosmic GRB rate at large redshifts than previous expectations based on star-formation rate measurements, unless other factors, such as the luminosity evolution, are taken into account. The GRB rate from our best result gives a total number of 4568 +825 -1429 GRBs per year that are beamed toward us in the whole universe.

simulations↗

NASA NTRS2012

GRB 081029: A Gamma-Ray Burst with a Multi-Component Afterglow

We present an analysis of the unusual optical light curve of the gamma-ray burst GRB 081029, a long-soft burst with a redshift of z = 3.8479. We combine X-ray and optical observations from the Swift X-Ray Telescope and the Swift Ultra Violet/Optical Telescope with ground-based optical and infrared data obtained using the REM, ROTSE, and CTIO 1.3-m telescopes to construct a detailed data set extending from 86 s to approx.100,000 s after the BAT trigger. Our data covers a wide energy range, from 10 keV to 0.77 eV (1.24 A to 16000 A). The X-ray afterglow shows a shallow initial decay followed by a rapid decay starting at about 18,000 s. The optical and infrared afterglow, however, shows an uncharacteristic rise at about 3000 s that does not correspond to any feature in the X-ray light curve. Our data are not consistent with synchrotron radiation from a jet interacting with an external medium, a two-component jet, or continuous energy injection from the central engine. We find that the optical light curves can be broadly explained by a collision between two ejecta shells within a two-component jet. A growing number of gamma-ray burst afterglows are consistent with complex jets, which suggests that some (or all) gamma-ray burst jets are complex and will require detailed modelling to fully understand them.injection

Holland, Stephen T.↗

NASA NTRS2012

The HEASARC Swift Gamma-Ray Burst Archive: The Pipeline and the Catalog

Since its launch in late 2004, the Swift satellite triggered or observed an average of one gamma-ray burst (GRB) every 3 days, for a total of 771 GRBs by 2012 January. Here, we report the development of a pipeline that semi automatically performs the data-reduction and data-analysis processes for the three instruments on board Swift (BAT, XRT, UVOT). The pipeline is written in Perl, and it uses only HEAsoft tools and can be used to perform the analysis of a majority of the point-like objects (e.g., GRBs, active galactic nuclei, pulsars) observed by Swift. We run the pipeline on the GRBs, and we present a database containing the screened data, the output products, and the results of our ongoing analysis. Furthermore, we created a catalog summarizing some GRB information, collected either by running the pipeline or from the literature. The Perl script, the database, and the catalog are available for downloading and querying at the HEASARC Web site.

BURST ARCHIVE↗

NASA NTRS2012

Identifying the Location in the Host Galaxy of Short GRB 1111l7A with the Chandra Sub- Arcsecond Position

We present our successful program using Chandra for identifying the X-ray afterglow with sub-arcsecond accuracy for the short GRB 111117A d iscovered by Swift and Fermi. Thanks to our rapid target of opportuni ty request, Chandra clearly detected the X-ray afterglow, whereas no optical afterglow was found in deep optical observations. Instead, we clearly detect the host galaxy in optica; and also in near-infrared b ands. We found that the best photometric redshift fitofthe host is z = 1.31:(+0.46/-0.23) (90% confidence), making it one of the highest redshift short GRBs. Furthermore, we see an offset of 1.0+/-O.2 arcseco nds, which corresponds to 8.4+/-1.7 kpc aSBuming z= 1.31, between the host and the afterglow position. We discuss the importance of using Chandra for obtaining sub-arcsecond localization of the afterglow in X -rays for short GRBs to study GRB environments in great detail.

Sakamoto, Takanori↗

NASA NTRS2008

Reviewing E(sub peak) Relations with Swift and Suzaku Data

In recent years several authors have derived correlations between gamma-ray burst (GRB) spectral peak energy (E(sub peak)) and either isotropic-equivalent radiated energy (E(sub iso)) or peak luminosity (L(sub iso)). Since these relationships are controversial, but could provide redshift estimators, it is important to determine whether bursts detected by Swift exhibit the same correlations. Swift has greatly added to the number of GRBs for which redshifts are known and hence E(sub iso) and L(sub iso) could be calculated. However, for most bursts it is not possible to adequately constrain E(sub peak) with Swift data alone since most GRBs have E(sub peak) above the energy range (15-50 keV) of the Swift Burst Alert Telescope (BAT). Therefore we have analyzed the spectra of 78 bursts (31 with redshift) which were detected by both Swift/BAT and the Suzaku Wide-band All-sky Monitor (WAM), which covers the energy range 50-5000 keV. For most bursts in this sample we can precisely determine E(sub peak) and for bursts with known redshift we can compare how the E(sub peak) relations for the Swift/Suzaku sample compare to earlier published results. Keywords: gamma rays: bursts

Krimm, Hans A.↗

NASA NTRS2007

A Burst Chasing X-ray Polarimeter

Gamma-ray bursts are one of the most powerful explosions in the universe and have been detected out to distances of almost 13 billion light years. The exact origin of these energetic explosions is still unknown but the resulting huge release of energy is thought to create a highly relativistic jet of material and a power-law distribution of electrons. There are several theories describing the origin of the prompt GRB emission that currently cannot be distinguished. Measurements of the linear polarization would provide unique and important constraints on the mechanisms thought to drive these powerful explosions. We present the design of a sensitive, and extremely versatile gamma-ray burst polarimeter. The instrument is a photoelectric polarimeter based on a time-projection chamber. The photoelectric time-projection technique combines high sensitivity with broad band-pass and is potentially the most powerful method between 2 and 100 keV where the photoelectric effect 1s the dominant interaction process We present measurements of polarized and unpolarized X-rays obtained with a prototype detector and describe the two mission concepts, the Gamma-Ray Burst Polarimeter (GRBP) for thc U S Naval Academy satellite MidSTAR-2, and thc Low Energy Polarimeter (LEP) onboard POET, a broadband polarimetry concept for a small explorer mission.

Hill, Joanne E.↗