301 research outputs found
Monitoring the solid-state dewetting of densely packed arrays of Au nanoparticles
We report a real time, in-situ spectroscopic ellipsometry study of the temperature-induced solid-state dewetting of Au nanowires into nanoparticles. Very large spectral variations are observed at different temperatures. Analysis of the key features in the acquired spectra reveals two different regimes: up to 300 \ub0C the variation in the optical response is dominated by solid-state dewetting, while above that temperature, smaller variations not compatible with such mechanism are visible. Therefore our ellipsometry measurements allow us to determine in real time at which temperature the solid-state dewetting ceases and the morphology of our sample becomes stable. We point out that this observation is possible thanks to the higher sensitiviy of ellipsometry with respect to reflectance/transmittance measurements
Tamm Plasmon Resonance as Optical Fingerprint of Silver/Bacteria Interaction
The incorporation of responsive elements into photonic crystals is an effective strategy for fabricating active optical components to be used as sensors, actuators, and modulators. In particular, the combination of simple multilayered dielectric mirrors with optically responsive plasmonic materials has proven to be successful. Recently, Tamm plasmon (TP) modes have emerged as powerful tools for these purposes. These modes arise at the interface between a distributed Bragg reflector (DBR) and a plasmonic layer and can be excited at a normal incidence angle. Although the TP field is located usually at the DBR/metal interface, recent studies have demonstrated that nanoscale corrugation of the metal layer permits access to the TP mode from outside, thus opening exciting perspectives for many real-life applications. In this study, we show that the TP resonance obtained by capping a DBR with a nanostructured layer of silver is responsive to Escherichia coli. Our data indicate that the modification of the TP mode originates from the well-known capability of silver to interact with bacteria, within a process in which the release of Ag+ ions leaves an excess of negative charge in the metal lattice. Finally, we exploited this effect to devise a case study in which we optically differentiated between the presence of proliferative and nonproliferative bacteria using the TP resonance as a read-out. These findings make these devices promising all-optical probes for bacterial metabolic activity, including their response to external stressors
Advanced Virgo Plus: Future Perspectives
While completing the commissioning phase to prepare the Virgo interferometer for the next joint Observation Run (O4), the Virgo collaboration is also finalizing the design of the next upgrades to the detector to be employed in the following Observation Run (O5). The major upgrade will concern decreasing the thermal noise limit, which will imply using very large test masses and increased laser beam size. But this will not be the only upgrade to be implemented in the break between the O4 and O5 observation runs to increase the Virgo detector strain sensitivity. The paper will cover the challenges linked to this upgrade and implications on the detector's reach and observational potential, reflecting the talk given at 12th Cosmic Ray International Seminar - CRIS 2022 held in September 2022 in Napoli
The Advanced Virgo+ status
The gravitational wave detector Advanced Virgo+ is currently in the commissioning phase in view of the fourth Observing Run (O4). The major upgrades with respect to the Advanced Virgo configuration are the implementation of an additional recycling cavity, the Signal Recycling cavity (SRC), at the output of the interferometer to broaden the sensitivity band and the Frequency Dependent Squeezing (FDS) to reduce quantum noise at all frequencies. The main difference of the Advanced Virgo + detector with respect to the LIGO detectors is the presence of marginally stable recycling cavities, with respect to the stable recycling cavities present in the LIGO detectors, which increases the difficulties in controlling the interferometer in presence of defects (both thermal and cold defects). This work will focus on the interferometer commissioning, highlighting the control challenges to maintain the detector in the working point which maximizes the sensitivity and the duty cycle for scientific data taking
Virgo Detector Characterization and Data Quality: results from the O3 run
The Advanced Virgo detector has contributed with its data to the rapid growth
of the number of detected gravitational-wave (GW) signals in the past few
years, alongside the two Advanced LIGO instruments. First during the last month
of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact
binary mergers GW170814 and GW170817), and then during the full Observation Run
3 (O3): an 11-months data taking period, between April 2019 and March 2020,
that led to the addition of about 80 events to the catalog of transient GW
sources maintained by LIGO, Virgo and now KAGRA. These discoveries and the
manifold exploitation of the detected waveforms require an accurate
characterization of the quality of the data, such as continuous study and
monitoring of the detector noise sources. These activities, collectively named
{\em detector characterization and data quality} or {\em DetChar}, span the
whole workflow of the Virgo data, from the instrument front-end hardware to the
final analyses. They are described in details in the following article, with a
focus on the results achieved by the Virgo DetChar group during the O3 run.
Concurrently, a companion article describes the tools that have been used by
the Virgo DetChar group to perform this work.Comment: 57 pages, 18 figures. To be submitted to Class. and Quantum Grav.
This is the "Results" part of preprint arXiv:2205.01555 [gr-qc] which has
been split into two companion articles: one about the tools and methods, the
other about the analyses of the O3 Virgo dat
Virgo Detector Characterization and Data Quality: tools
Detector characterization and data quality studies -- collectively referred
to as {\em DetChar} activities in this article -- are paramount to the
scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA
global network of ground-based gravitational-wave (GW) detectors. They take
place during each phase of the operation of the instruments (upgrade, tuning
and optimization, data taking), are required at all steps of the dataflow (from
data acquisition to the final list of GW events) and operate at various
latencies (from near real-time to vet the public alerts to offline analyses).
This work requires a wide set of tools which have been developed over the years
to fulfill the requirements of the various DetChar studies: data access and
bookkeeping; global monitoring of the instruments and of the different steps of
the data processing; studies of the global properties of the noise at the
detector outputs; identification and follow-up of noise peculiar features
(whether they be transient or continuously present in the data); quick
processing of the public alerts. The present article reviews all the tools used
by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3,
from April 2019 to March 2020), mainly to analyse the Virgo data acquired at
EGO. Concurrently, a companion article focuses on the results achieved by the
DetChar group during the O3 run using these tools.Comment: 44 pages, 16 figures. To be submitted to Class. and Quantum Grav.
This is the "Tools" part of preprint arXiv:2205.01555 [gr-qc] which has been
split into two companion articles: one about the tools and methods, the other
about the analyses of the O3 Virgo dat
Virgo Detector Characterization and Data Quality during the O3 run
The Advanced Virgo detector has contributed with its data to the rapid growth
of the number of detected gravitational-wave signals in the past few years,
alongside the two LIGO instruments. First, during the last month of the
Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary
mergers GW170814 and GW170817) and then during the full Observation Run 3 (O3):
an 11 months data taking period, between April 2019 and March 2020, that led to
the addition of about 80 events to the catalog of transient gravitational-wave
sources maintained by LIGO, Virgo and KAGRA. These discoveries and the manifold
exploitation of the detected waveforms require an accurate characterization of
the quality of the data, such as continuous study and monitoring of the
detector noise. These activities, collectively named {\em detector
characterization} or {\em DetChar}, span the whole workflow of the Virgo data,
from the instrument front-end to the final analysis. They are described in
details in the following article, with a focus on the associated tools, the
results achieved by the Virgo DetChar group during the O3 run and the main
prospects for future data-taking periods with an improved detector.Comment: 86 pages, 33 figures. This paper has been divided into two articles
which supercede it and have been posted to arXiv on October 2022. Please use
these new preprints as references: arXiv:2210.15634 (tools and methods) and
arXiv:2210.15633 (results from the O3 run
Search of the early O3 LIGO data for continuous gravitational waves from the Cassiopeia A and Vela Jr. supernova remnants
partially_open1412sìWe present directed searches for continuous gravitational waves from the neutron stars in the Cassiopeia A (Cas A) and Vela Jr. supernova remnants. We carry out the searches in the LIGO detector data from the first six months of the third Advanced LIGO and Virgo observing run using the weave semicoherent method, which sums matched-filter detection-statistic values over many time segments spanning the observation period. No gravitational wave signal is detected in the search band of 20–976 Hz for assumed source ages greater than 300 years for Cas A and greater than 700 years for Vela Jr. Estimates from simulated continuous wave signals indicate we achieve the most sensitive results to date across the explored parameter space volume, probing to strain magnitudes as low as
∼6.3×10^−26 for Cas A and ∼5.6×10^−26 for Vela Jr. at frequencies near 166 Hz at 95% efficiency.openAbbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adhikari, N.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agarwal, D.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Albanesi, S.; Allocca, A.; Altin, P. A.; Amato, A.; Anand, C.; Anand, S.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Andrade, T.; Andres, N.; Andrić, T.; Angelova, S. V.; Ansoldi, S.; Antelis, J. M.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arène, M.; Arnaud, N.; Aronson, S. M.; Arun, K. G.; Asali, Y.; Ashton, G.; Assiduo, M.; Aston, S. M.; Astone, P.; Aubin, F.; Austin, C.; Babak, S.; Badaracco, F.; Bader, M. K. M.; Badger, C.; Bae, S.; Baer, A. M.; Bagnasco, S.; Bai, Y.; Baird, J.; Ball, M.; Ballardin, G.; Ballmer, S. W.; Balsamo, A.; Baltus, G.; Banagiri, S.; Bankar, D.; Barayoga, J. C.; Barbieri, C.; Barish, B. 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T.; Cousins, B.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Criswell, A. W.; Croquette, M.; Crowder, S. G.; Cudell, J. R.; Cullen, T. J.; Cumming, A.; Cummings, R.; Cunningham, L.; Cuoco, E.; Curyło, M.; Dabadie, P.; Canton, T. Dal; Dall’Osso, S.; Dálya, G.; Dana, A.; DaneshgaranBajastani, L. M.; D’Angelo, B.; Danilishin, S.; D’Antonio, S.; Danzmann, K.; Darsow-Fromm, C.; Dasgupta, A.; Datrier, L. E. H.; Datta, S.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Davis, M. C.; Daw, E. J.; Dean, R.; DeBra, D.; Deenadayalan, M.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Favero, V.; De Lillo, F.; De Lillo, N.; Del Pozzo, W.; DeMarchi, L. M.; De Matteis, F.; D’Emilio, V.; Demos, N.; Dent, T.; Depasse, A.; De Pietri, R.; De Rosa, R.; De Rossi, C.; DeSalvo, R.; De Simone, R.; Dhurandhar, S.; Díaz, M. C.; Diaz-Ortiz, M.; Didio, N. A.; Dietrich, T.; Di Fiore, L.; Di Fronzo, C.; Di Giorgio, C.; Di Giovanni, F.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Ding, B.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Divakarla, A. K.; Dmitriev, A.; Doctor, Z.; D’Onofrio, L.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Drago, M.; Driggers, J. C.; Drori, Y.; Ducoin, J.-G.; Dupej, P.; Durante, O.; D’Urso, D.; Duverne, P.-A.; Dwyer, S. E.; Eassa, C.; Easter, P. J.; Ebersold, M.; Eckhardt, T.; Eddolls, G.; Edelman, B.; Edo, T. B.; Edy, O.; Effler, A.; Eichholz, J.; Eikenberry, S. S.; Eisenmann, M.; Eisenstein, R. A.; Ejlli, A.; Engelby, E.; Errico, L.; Essick, R. C.; Estellés, H.; Estevez, D.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Ewing, B. E.; Fafone, V.; Fair, H.; Fairhurst, S.; Farah, A. M.; Farinon, S.; Farr, B.; Farr, W. M.; Farrow, N. W.; Fauchon-Jones, E. J.; Favaro, G.; Favata, M.; Fays, M.; Fazio, M.; Feicht, J.; Fejer, M. M.; Fenyvesi, E.; Ferguson, D. L.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, T. A.; Fidecaro, F.; Figura, P.; Fiori, I.; Fishbach, M.; Fisher, R. P.; Fittipaldi, R.; Fiumara, V.; Flaminio, R.; Floden, E.; Fong, H.; Font, J. A.; Fornal, B.; Forsyth, P. W. F.; Franke, A.; Frasca, S.; Frasconi, F.; Frederick, C.; Freed, J. P.; Frei, Z.; Freise, A.; Frey, R.; Fritschel, P.; Frolov, V. V.; Fronzé, G. G.; Fulda, P.; Fyffe, M.; Gabbard, H. A.; Gadre, B. U.; Gair, J. R.; Gais, J.; Galaudage, S.; Gamba, R.; Ganapathy, D.; Ganguly, A.; Gaonkar, S. G.; Garaventa, B.; García-Núñez, C.; García-Quirós, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gayathri, V.; Gemme, G.; Gennai, A.; George, J.; Gerberding, O.; Gergely, L.; Gewecke, P.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, Shaon; Ghosh, Shrobana; Giacomazzo, B.; Giacoppo, L.; Giaime, J. A.; Giardina, K. D.; Gibson, D. R.; Gier, C.; Giesler, M.; Giri, P.; Gissi, F.; Glanzer, J.; Gleckl, A. E.; Godwin, P.; Goetz, E.; Goetz, R.; Gohlke, N.; Goncharov, B.; González, G.; Gopakumar, A.; Gosselin, M.; Gouaty, R.; Gould, D. W.; Grace, B.; Grado, A.; Granata, M.; Granata, V.; Grant, A.; Gras, S.; Grassia, P.; Gray, C.; Gray, R.; Greco, G.; Green, A. C.; Green, R.; Gretarsson, A. M.; Gretarsson, E. M.; Griffith, D.; Griffiths, W.; Griggs, H. L.; Grignani, G.; Grimaldi, A.; Grimm, S. J.; Grote, H.; Grunewald, S.; Gruning, P.; Guerra, D.; Guidi, Gianluca; Guimaraes, A. R.; Guixé, G.; Gulati, H. K.; Guo, H.-K.; Guo, Y.; Gupta, Anchal; Gupta, Anuradha; Gupta, P.; Gustafson, E. K.; Gustafson, R.; Guzman, F.; Haegel, L.; Halim, O.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O.; Hansen, H.; Hansen, T. J.; Hanson, J.; Harder, T.; Hardwick, T.; Haris, K.; Harms, J.; Harry, G. M.; Harry, I. W.; Hartwig, D.; Haskell, B.; Hasskew, R. K.; Haster, C.-J.; Haughian, K.; Hayes, F. J.; Healy, J.; Heidmann, A.; Heidt, A.; Heintze, M. 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Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo
Despite the growing number of confident binary black hole coalescences
observed through gravitational waves so far, the astrophysical origin of these
binaries remains uncertain. Orbital eccentricity is one of the clearest tracers
of binary formation channels. Identifying binary eccentricity, however, remains
challenging due to the limited availability of gravitational waveforms that
include effects of eccentricity. Here, we present observational results for a
waveform-independent search sensitive to eccentric black hole coalescences,
covering the third observing run (O3) of the LIGO and Virgo detectors. We
identified no new high-significance candidates beyond those that were already
identified with searches focusing on quasi-circular binaries. We determine the
sensitivity of our search to high-mass (total mass ) binaries
covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to
compare model predictions to search results. Assuming all detections are indeed
quasi-circular, for our fiducial population model, we place an upper limit for
the merger rate density of high-mass binaries with eccentricities at Gpc yr at 90\% confidence level.Comment: 24 pages, 5 figure
The population of merging compact binaries inferred using gravitational waves through GWTC-3
We report on the population properties of 76 compact binary mergers detected with gravitational waves below a false alarm rate of 1 per year through GWTC-3. The catalog contains three classes of binary mergers: BBH, BNS, and NSBH mergers. We infer the BNS merger rate to be between 10 and 1700 and the NSBH merger rate to be between 7.8 and 140 , assuming a constant rate density versus comoving volume and taking the union of 90% credible intervals for methods used in this work. Accounting for the BBH merger rate to evolve with redshift, we find the BBH merger rate to be between 17.9 and 44 at a fiducial redshift (z=0.2). We obtain a broad neutron star mass distribution extending from to . We can confidently identify a rapid decrease in merger rate versus component mass between neutron star-like masses and black-hole-like masses, but there is no evidence that the merger rate increases again before 10 . We also find the BBH mass distribution has localized over- and under-densities relative to a power law distribution. While we continue to find the mass distribution of a binary's more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above . The rate of BBH mergers is observed to increase with redshift at a rate proportional to with for . Observed black hole spins are small, with half of spin magnitudes below . We observe evidence of negative aligned spins in the population, and an increase in spin magnitude for systems with more unequal mass ratio
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