28 research outputs found
Convolutional neural networks: a magic bullet for gravitational-wave detection?
In the last few years, machine learning techniques, in particular
convolutional neural networks, have been investigated as a method to replace or
complement traditional matched filtering techniques that are used to detect the
gravitational-wave signature of merging black holes. However, to date, these
methods have not yet been successfully applied to the analysis of long
stretches of data recorded by the Advanced LIGO and Virgo gravitational-wave
observatories. In this work, we critically examine the use of convolutional
neural networks as a tool to search for merging black holes. We identify the
strengths and limitations of this approach, highlight some common pitfalls in
translating between machine learning and gravitational-wave astronomy, and
discuss the interdisciplinary challenges. In particular, we explain in detail
why convolutional neural networks alone cannot be used to claim a statistically
significant gravitational-wave detection. However, we demonstrate how they can
still be used to rapidly flag the times of potential signals in the data for a
more detailed follow-up. Our convolutional neural network architecture as well
as the proposed performance metrics are better suited for this task than a
standard binary classifications scheme. A detailed evaluation of our approach
on Advanced LIGO data demonstrates the potential of such systems as trigger
generators. Finally, we sound a note of caution by constructing adversarial
examples, which showcase interesting "failure modes" of our model, where inputs
with no visible resemblance to real gravitational-wave signals are identified
as such by the network with high confidence.Comment: First two authors contributed equally; appeared at Phys. Rev.
Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks
Atmospheric retrievals (AR) of exoplanets typically rely on a combination of
a Bayesian inference technique and a forward simulator to estimate atmospheric
properties from an observed spectrum. A key component in simulating spectra is
the pressure-temperature (PT) profile, which describes the thermal structure of
the atmosphere. Current AR pipelines commonly use ad hoc fitting functions here
that limit the retrieved PT profiles to simple approximations, but still use a
relatively large number of parameters. In this work, we introduce a
conceptually new, data-driven parameterization scheme for physically consistent
PT profiles that does not require explicit assumptions about the functional
form of the PT profiles and uses fewer parameters than existing methods. Our
approach consists of a latent variable model (based on a neural network) that
learns a distribution over functions (PT profiles). Each profile is represented
by a low-dimensional vector that can be used to condition a decoder network
that maps to . When training and evaluating our method on two publicly
available datasets of self-consistent PT profiles, we find that our method
achieves, on average, better fit quality than existing baseline methods,
despite using fewer parameters. In an AR based on existing literature, our
model (using two parameters) produces a tighter, more accurate posterior for
the PT profile than the five-parameter polynomial baseline, while also speeding
up the retrieval by more than a factor of three. By providing parametric access
to physically consistent PT profiles, and by reducing the number of parameters
required to describe a PT profile (thereby reducing computational cost or
freeing resources for additional parameters of interest), our method can help
improve AR and thus our understanding of exoplanet atmospheres and their
habitability.Comment: Accepted for publication in Astronomy & Astrophysic
Comparing Apples with Apples: Robust Detection Limits for Exoplanet High-Contrast Imaging in the Presence of non-Gaussian Noise
Over the past decade, hundreds of nights have been spent on the worlds
largest telescopes to search for and directly detect new exoplanets using
high-contrast imaging (HCI). Thereby, two scientific goals are of central
interest: First, to study the characteristics of the underlying planet
population and distinguish between different planet formation and evolution
theories. Second, to find and characterize planets in our immediate Solar
neighborhood. Both goals heavily rely on the metric used to quantify planet
detections and non-detections.
Current standards often rely on several explicit or implicit assumptions
about the noise. For example, it is often assumed that the residual noise after
data post-processing is Gaussian. While being an inseparable part of the
metric, these assumptions are rarely verified. This is problematic as any
violation of these assumptions can lead to systematic biases. This makes it
hard, if not impossible, to compare results across datasets or instruments with
different noise characteristics.
We revisit the fundamental question of how to quantify detection limits in
HCI. We focus our analysis on the error budget resulting from violated
assumptions. To this end, we propose a new metric based on bootstrapping that
generalizes current standards to non-Gaussian noise. We apply our method to
archival HCI data from the NACO-VLT instrument and derive detection limits for
different types of noise. Our analysis shows that current standards tend to
give detection limit that are about one magnitude too optimistic in the
speckle-dominated regime. That is, HCI surveys may have excluded planets that
can still exist.Comment: After first iteration with the referee, resubmitted to AJ. Comments
welcome
CROCODILE \\ Incorporating medium-resolution spectroscopy of close-in directly imaged exoplanets into atmospheric retrievals via cross-correlation
The investigation of the atmospheres of closely separated, directly imaged
gas giant exoplanets is challenging due to the presence of stellar speckles
that pollute their spectrum. To remedy this, the analysis of medium- to
high-resolution spectroscopic data via cross-correlation with spectral
templates (cross-correlation spectroscopy) is emerging as a leading technique.
We aim to define a robust Bayesian framework combining, for the first time,
three widespread direct-imaging techniques, namely photometry, low-resolution
spectroscopy, and medium-resolution cross-correlation spectroscopy in order to
derive the atmospheric properties of close-in directly imaged exoplanets. Our
framework CROCODILE (cross-correlation retrievals of directly imaged
self-luminous exoplanets) naturally combines the three techniques by adopting
adequate likelihood functions. To validate our routine, we simulated
observations of gas giants similar to the well-studied ~Pictoris~b
planet and we explored the parameter space of their atmospheres to search for
potential biases. We obtain more accurate measurements of atmospheric
properties when combining photometry, low- and medium-resolution spectroscopy
into atmospheric retrievals than when using the techniques separately as is
usually done in the literature. We find that medium-resolution () K-band cross-correlation spectroscopy alone is not suitable to constrain
the atmospheric properties of our synthetic datasets; however, this problem
disappears when simultaneously fitting photometry and low-resolution () spectroscopy between the Y and M bands. Our framework allows the
atmospheric characterisation of directly imaged exoplanets using the
high-quality spectral data that will be provided by the new generation of
instruments such as VLT/ERIS, JWST/MIRI, and ELT/METIS
BDSM Disclosure and Stigma Management: Identifying Opportunities for Sex Education
While participation in the activities like bondage, domination, submission/sadism, masochism that fall under the umbrella term BDSM is widespread, stigma surrounding BDSM poses risks to practitioners who wish to disclose their interest. We examined risk factors involved with disclosure to posit how sex education might diffuse stigma and warn of risks. Semi-structured interviews asked 20 adults reporting an interest in BDSM about their disclosure experiences. Most respondents reported their BDSM interests starting before age 15, sometimes creating a phase of anxiety and shame in the absence of reassuring information. As adults, respondents often considered BDSM central to their sexuality, thus disclosure was integral to dating. Disclosure decisions in nondating situations were often complex considerations balancing desire for appropriateness with a desire for connection and honesty. Some respondents wondered whether their interests being found out would jeopardize their jobs. Experiences with stigma varied widely
Integrated photonic-based coronagraphic systems for future space telescopes
The detection and characterization of Earth-like exoplanets around Sun-like
stars is a primary science motivation for the Habitable Worlds Observatory.
However, the current best technology is not yet advanced enough to reach the
10^-10 contrasts at close angular separations and at the same time remain
insensitive to low-order aberrations, as would be required to achieve
high-contrast imaging of exo-Earths. Photonic technologies could fill this gap,
potentially doubling exo-Earth yield. We review current work on photonic
coronagraphs and investigate the potential of hybridized designs which combine
both classical coronagraph designs and photonic technologies into a single
optical system. We present two possible systems. First, a hybrid solution which
splits the field of view spatially such that the photonics handle light within
the inner working angle and a conventional coronagraph that suppresses
starlight outside it. Second, a hybrid solution where the conventional
coronagraph and photonics operate in series, complementing each other and
thereby loosening requirements on each subsystem. As photonic technologies
continue to advance, a hybrid or fully photonic coronagraph holds great
potential for future exoplanet imaging from space.Comment: Conference Proceedings of SPIE: Techniques and Instrumentation for
Detection of Exoplanets XI, vol. 12680 (2023
Visible extreme adaptive optics on extremely large telescopes: Towards detecting oxygen in Proxima Centauri b and analogs
Looking to the future of exo-Earth imaging from the ground, core technology
developments are required in visible extreme adaptive optics (ExAO) to enable
the observation of atmospheric features such as oxygen on rocky planets in
visible light. UNDERGROUND (Ultra-fast AO techNology Determination for
Exoplanet imageRs from the GROUND), a collaboration built in Feb. 2023 at the
Optimal Exoplanet Imagers Lorentz Workshop, aims to (1) motivate oxygen
detection in Proxima Centauri b and analogs as an informative science case for
high-contrast imaging and direct spectroscopy, (2) overview the state of the
field with respect to visible exoplanet imagers, and (3) set the instrumental
requirements to achieve this goal and identify what key technologies require
further development.Comment: SPIE Proceeding: 2023 / 12680-6
Vampires in the village Žrnovo on the island of Korčula: following an archival document from the 18th century
Središnja tema rada usmjerena je na raščlambu spisa pohranjenog u Državnom arhivu u Mlecima (fond: Capi del Consiglio de’ Dieci: Lettere di Rettori e di altre cariche) koji se odnosi na događaj iz 1748. godine u korčulanskom selu Žrnovo, kada su mještani – vjerujući da su se pojavili vampiri – oskvrnuli nekoliko mjesnih grobova. U radu se podrobno iznose osnovni podaci iz spisa te rečeni događaj analizira u širem društvenom kontekstu i prate se lokalna vjerovanja.The main interest of this essay is the analysis of the document from the State Archive in Venice (file: Capi del Consiglio de’ Dieci: Lettere di Rettori e di altre cariche) which is connected with the episode from 1748 when the inhabitants of the village Žrnove on the island of Korčula in Croatia opened tombs on the local cemetery in the fear of the vampires treating.
This essay try to show some social circumstances connected with this event as well as a local vernacular tradition concerning superstitions