Aleksandra Ćiprijanović

Aleksandra Ćiprijanović
Fermi National Accelerator Laboratory (Fermilab) | Fermilab · Scientific Computing Division

Dr

About

36
Publications
2,514
Reads
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155
Citations
Introduction
- Deep learning for merging galaxy classification - Likelihood-free inference for astronomy
Additional affiliations
April 2020 - present
Fermi National Accelerator Laboratory (Fermilab)
Position
  • PostDoc Position
October 2019 - April 2020
March 2018 - October 2019
Faculty of Mathematics, University of Belgrade
Position
  • Professor
Education
October 2011 - December 2016
Faculty of Mathematics, University of Belgrade
Field of study
  • Astrophysics
October 2010 - September 2011
Faculty of Mathematics, University of Belgrade
Field of study
  • Astrophysics
October 2006 - September 2010
Faculty of Mathematics, University of Belgrage
Field of study
  • Astrophysics

Publications

Publications (36)
Article
Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as “ghosting artifacts” or “ghosts”) and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. However, the identification o...
Preprint
Full-text available
With increased adoption of supervised deep learning methods for work with cosmological survey data, the assessment of data perturbation effects (that can naturally occur in the data processing and analysis pipelines) and the development of methods that increase model robustness are increasingly important. In the context of morphological classificat...
Preprint
Full-text available
Deep learning models are being increasingly adopted in wide array of scientific domains, especially to handle high-dimensionality and volume of the scientific data. However, these models tend to be brittle due to their complexity and overparametrization, especially to the inadvertent adversarial perturbations that can appear due to common image pro...
Preprint
Full-text available
Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as "ghosting artifacts" or "ghosts") and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. However, the identification o...
Article
In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrumen...
Article
Searches for low-surface-brightness galaxies (LSBGs) in galaxy surveys are plagued by the presence of a large number of artifacts (e.g., objects blended in the diffuse light from stars and galaxies, Galactic cirrus, star-forming regions in the arms of spiral galaxies, etc.) that have to be rejected through time consuming visual inspection. In futur...
Preprint
Full-text available
In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrumen...
Preprint
Searches for low-surface-brightness galaxies (LSBGs) in galaxy surveys are plagued by the presence of a large number of artifacts (e.g., objects blended in the diffuse light from stars and galaxies, Galactic cirrus, star-forming regions in the arms of spiral galaxies, etc.) that have to be rejected through time consuming visual inspection. In futur...
Conference Paper
Full-text available
In astronomy, neural networks are often trained on simulated data with the prospect of being applied to real observations. Unfortunately, simply training a deep neural network on images from one domain does not guarantee satisfactory performance on new images from a different domain. The ability to share cross-domain knowledge is the main advantage...
Preprint
Full-text available
In astronomy, neural networks are often trained on simulated data with the prospect of being applied to real observations. Unfortunately, simply training a deep neural network on images from one domain does not guarantee satisfactory performance on new images from a different domain. The ability to share cross-domain knowledge is the main advantage...
Article
Full-text available
We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e., z=2). We extract images of merging and non-merging galaxies from the Illustris-1 cosmological simulation and apply observational a...
Preprint
We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract images of merging and non-merging galaxies from the Illustris-1 cosmological simulation and apply observational...
Preprint
Full-text available
In this paper we present the updated empirical radio surface- brightness-to-diameter (Σ-D) relation for Galactic supernova remnants (SNRs) calibrated using 110 SNRs with reliable distances. We apply orthogonal fitting procedure and kernel density smoothing in the Σ ¡ D plane and compare the results with the latest theoretical Σ - D relations derive...
Preprint
Full-text available
We present detection of 67 HII regions and two optical supernova remnant (SNR) candidates in the nearby irregular galaxy NGC 2366. The SNR candidates were detected by applying [SII]/H$\alpha$ ratio criterion to observations made with the 2-m RCC telescope at Rozhen National Astronomical Observatory in Bulgaria. In this paper we report coordinates,...
Article
Full-text available
We present detection of 64 H II regions, three superbubbles and two optical supernova remnant (SNR) candidates in the nearby irregular galaxy NGC 2366. The SNR candidates were detected by applying [S II]/Hα ratio criterion to observations made with the 2-m RCC telescope at Rozhen National Astronomical Observatory in Bulgaria. In this paper we repor...
Preprint
Full-text available
Female role models reduce the impact on women of stereotype threat, i.e., of being at risk of conforming to a negative stereotype about one's social, gender, or racial group. This can lead women scientists to underperform or to leave their scientific career because of negative stereotypes such as, not being as talented or as interested in science a...
Conference Paper
Full-text available
Accretion of gas onto already virialized structures like galaxy clusters should give rise to accretion shocks which can potentially accelerate cosmic rays. Here, we use the radio emission detected from Coma cluster and models of evolution of cosmic accretion shocks, to constrain the possible contribution of unresolved galaxy clusters to the cosmic...
Preprint
Full-text available
Accretion of gas onto already virialized structures like galaxy clusters should give rise to accretion shocks which can potentially accelerate cosmic rays. Here, we use the radio emission detected from Coma cluster and models of evolution of cosmic accretion shocks, to constrain the possible contribution of unresolved galaxy clusters to the cosmic...
Thesis
Full-text available
Studying cosmic rays is very important for better understanding of high energy physical processes, since particles accelerated in space can reach energies far above what we can produce in accelerators on Earth, at the moment. Processes that produce cosmic rays are still unexplained to some extent, and models that have been proposed are awaiting con...
Article
Full-text available
Recently, the first lithium detection outside of the Milky Way was made in low-metallicity gas of the Small Magellanic Cloud, which was at the level of the expected primordial value. Part of the observed lithium in any environment has primordial origin, but there is always some post-BBN (Big Bang Nude synthesis) contamination, since lithium can als...
Article
Recently, the first lithium detection outside of the Milky Way was made in low-metallicity gas of the Small Magellanic Cloud, which was at the level of the expected primordial value. Part of the observed lithium in any environment has primordial origin, but there is always some post-BBN (Big Bang Nucleosynthesis) contamination, since lithium can al...
Article
Full-text available
We present the detection of 16 optical supernova remnant (SNR) candidates in the nearby spiral galaxy IC342. The candidates were detected by applying the [SII]/Hα ratio criterion on observations made with the 2 m RCC telescope at Rozhen National Astronomical Observatory in Bulgaria. In this paper, we report the coordinates, diameters, Hα and [SII]...
Article
Full-text available
Accretion of gas during the large scale structure formation has been thought to give rise to shocks that can accelerate cosmic rays. This process then results in an isotropic extragalactic gamma-ray component that then contributes to the extragalactic gamma-ray background observed by the \emph{Fermi}-LAT. Unfortunately this gamma-ray background com...
Article
Full-text available
We present updated empirical radio surface-brightness-to-diameter ($\Sigma-D$) relation for supernova remnants (SNRs) in our Galaxy. Our original calibration sample of Galactic SNRs with independently determined distances (Pavlovic et al. 2013, hereafter Paper I) is reconsidered and updated with data which became available in the past two years. Th...
Article
Full-text available
For more than a decade now the complete origin of the diffuse gamma-ray emission background (EGRB) has been unknown. Major components like unre-solved star-forming galaxies (making < ∼ 50% of the EGRB) and blazars (< ∼ 23%), have failed to explain the entire background observed by Fermi. Another, though subdominant, contribution is expected to come...
Article
Full-text available
For more than a decade now, the complete origin of the diffuse gamma-ray emission background (EGRB) has been unknown. Major components like unresolved star-forming galaxies (making <~ 50% of the EGRB) and blazars (lsim 23%), have failed to explain the entire background observed by Fermi. Another, though subdominant, contribution is expected to come...
Article
Full-text available
We present observations of a portion of the nearby spiral galaxy IC342 using narrow band [SII] and Hα filters. These observations were carried out in November 2011 with the 2m RCC telescope at Rozhen National Astronomical Observatory in Bulgaria. In this paper we report coordinates, diameters, Hα and [SII] fluxes for 203 HII regions detected in two...
Article
Full-text available
By applying a method of virtual quanta we derive formulae for relativistic non-thermal bremsstrahlung radiation from relativistic electrons as well as from protons and heavier particles with power-law momentum distribution $N(p)dp = k p^{-q} dp.$ We show that emission which originates from an electron scattering on an ion, represents the most signi...
Conference Paper
Full-text available
The extragalactic gamma-ray background measured by The Fermi Gamma-Ray Space Telescope is substantially different from previous measurements. Fermi has clarified that the dominant emission mechanism comes from cosmic-ray interactions with interstellar gas in normal galaxies. We present a constraint of cosmological cosmic-ray contribution to the ext...
Conference Paper
Full-text available
Recently, the modified equipartition calculation for supernova remnants (SNRs) has been derived by Arbutina et al. (2012). Their formulae can be used for SNRs with the spectral indices between 0.5 < α < 1. Here, by using approximately the same analytical method, we derive the equipartition formulae useful for SNRs with spectral index α = 0.5. These...

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Projects (3)
Project
very fantastic improvements we are having with a bunch of very good data and their analyses...