arXiv subjects

Lior Shamir

Publications and source records attributed to Lior Shamir.

At least 37 records · Page 2Linked to original sources

arXiv2023

Large-scale asymmetry in the distribution of galaxy spin directions -- analysis and reproduction

Recent independent observations using several different telescope systems an analysis methods have provided evidence of parity violation between the number of galaxies that spin in opposite directions. On the other hand, other studies argued that no parity violation can be identified. This paper provides detailed analysis, statistical inference, and reproduction of previous reports that show no preferred spin direction. Code and data used for the reproduction are publicly available. The results show that the data used in all of these studies agrees with the observation of a preferred direction as observed from Earth. In some of these studies the datasets were too small, or the statistical analysis was incomplete. In other papers the results were impacted by experimental design decisions that lead directly to show non-preferred direction. In some of these cases these decisions are not stated in the papers, but were revealed after further investigation in cases where the reproduction of the work did not match the results reported in the papers. These results show that the data used in all of these previous studies in fact agree with the contention that galaxies as observed from Earth have a preferred spin direction, and the distribution of galaxy spin directions as observed from Earth form a cosmological-scale dipole axis. This study also shows that the reason for the observations is not necessarily an anomaly in the large-scale structure, and can also be related to internal structure of galaxies.

astro-ph.CO↗

arXiv2023

A data science and machine learning approach to continuous analysis of Shakespeare's plays

The availability of quantitative text analysis methods has provided new ways of analyzing literature in a manner that was not available in the pre-information era. Here we apply comprehensive machine learning analysis to the work of William Shakespeare. The analysis shows clear changes in the style of writing over time, with the most significant changes in the sentence length, frequency of adjectives and adverbs, and the sentiments expressed in the text. Applying machine learning to make a stylometric prediction of the year of the play shows a Pearson correlation of 0.71 between the actual and predicted year, indicating that Shakespeare's writing style as reflected by the quantitative measurements changed over time. Additionally, it shows that the stylometrics of some of the plays is more similar to plays written either before or after the year they were written. For instance, Romeo and Juliet is dated 1596, but is more similar in stylometrics to plays written by Shakespeare after 1600. The source code for the analysis is available for free download.

cs.CL↗

arXiv2023

Outlier galaxy images in the Dark Energy Survey and their identification with unsupervised machine learning

The Dark Energy Survey is able to collect image data of an extremely large number of extragalactic objects, and it can be reasonably assumed that many unusual objects of high scientific interest are hidden inside these data. Due to the extreme size of DES data, identifying these objects among many millions of other celestial objects is a challenging task. The problem of outlier detection is further magnified by the presence of noisy or saturated images. When the number of tested objects is extremely high, even a small rate of noise or false positives leads to a very large number of false detections, making an automatic system impractical. This study applies an automatic method for automatic detection of outlier objects in the first data release of the Dark Energy Survey. By using machine learning-based outlier detection, the algorithm is able to identify objects that are visually different from the majority of the other objects in the database. An important feature of the algorithm is that it allows to control the false-positive rate, and therefore can be used for practical outlier detection. The algorithm does not provide perfect accuracy in the detection of outlier objects, but it reduces the data substantially to allow practical outlier detection. For instance, the selection of the top 250 objects after applying the algorithm to more than $2\cdot10^6$ DES images provides a collection of uncommon galaxies. Such collection would have been extremely time-consuming to compile by using manual inspection of the data.

astro-ph.GA↗

arXiv2023

Is the Observable Universe Consistent with the Cosmological Principle?

The Cosmological Principle (CP) -- the notion that the Universe is spatially isotropic and homogeneous on large scales -- underlies a century of progress in cosmology. It is conventionally formulated through the Friedmann-Lemaître-Robertson-Walker (FLRW) cosmologies as the spacetime metric, and culminates in the successful and highly predictive $Λ$-Cold-Dark-Matter ($Λ$CDM) model. Yet, tensions have emerged within the $Λ$CDM model, most notably a statistically significant discrepancy in the value of the Hubble constant, $H_0$. Since the notion of cosmic expansion determined by a single parameter is intimately tied to the CP, implications of the $H_0$ tension may extend beyond $Λ$CDM to the CP itself. This review surveys current observational hints for deviations from the expectations of the CP, highlighting synergies and disagreements that warrant further study. Setting aside the debate about individual large structures, potential deviations from the CP include variations of cosmological parameters on the sky, discrepancies in the cosmic dipoles, and mysterious alignments in quasar polarizations and galaxy spins. While it is possible that a host of observational systematics are impacting results, it is equally plausible that precision cosmology may have outgrown the FLRW paradigm, an extremely pragmatic but non-fundamental symmetry assumption.

astro-ph.CO↗

arXiv2023

Reanalysis of the spin direction distribution of Galaxy Zoo SDSS spiral galaxies

The distribution of the spin directions of spiral galaxies in the Sloan Digital Sky Survey has been a topic of debate in the past two decades, with conflicting conclusions reported even in cases where the same data was used. Here we follow one of the previous experiments by applying the SpArcFiRe algorithm to annotate the spin directions in original dataset of Galaxy Zoo 1. The annotation of the galaxy spin directions is done after a first step of selecting the spiral galaxies in three different manners: manual analysis by Galaxy Zoo classifications, by a model-driven computer analysis, and with no selection of spiral galaxies. The results show that when spiral galaxies are selected by Galaxy Zoo volunteers, the distribution of their spin directions as determined by SpArcFiRe is not random, which agrees with previous reports. When selecting the spiral galaxies using a model-driven computer analysis or without selecting the spiral galaxies at all, the distribution is also not random. Simple binomial distribution analysis shows that the probability of the parity violation to occur by chance is lower than 0.01. Fitting the spin directions as observed from Earth to cosine dependence exhibits a dipole axis with statistical strength of 2.33$σ$ to 3.97$σ$. These experiments show that regardless of the selection mechanism and the analysis method, all experiments show similar conclusions. These results are aligned with previous reports using other methods and telescopes, suggesting that the spin directions of spiral galaxies as observed from Earth exhibit a dipole axis formed by their spin directions. Possible explanations can be related to the large-scale structure of the Universe, or to internal structure of galaxies. The catalogs of annotated galaxies generated as part of this study are available.

astro-ph.CO↗

arXiv2022

A possible tension between galaxy rotational velocity and observed physical properties

The discrepancy between the mass of galaxies and their rotational velocity is one of the most puzzling scientific phenomena. Despite over a century of research, this phenomenon is not fully understood. Common explanations include dark matter and MOND, among other theories. Here we report on another observation that shows tension between the physics of galaxy rotation and its rotational velocity. We compare the brightness of galaxies, and find that galaxies that spin in the same direction as the Milky Way have different brightness than galaxies that spin in the opposite direction. While such difference in brightness is expected due to Doppler shift, it is expected to be subtle. The results show that the difference in brightness is large enough to be detected by Earth-based telescopes. That observed difference corresponds to physical properties of galaxies with far greater rotational velocity than the rotational velocity of the Milky Way. The difference is consistent in both the Northern galactic pole and the Southern galactic pole, and is not observed in parts of the sky that are perpendicular to the galactic pole. The differences are observed by several different instruments such DECam, SDSS, Pan-STARRS, and HST. The observation is also consistent across annotation methods, including different computer-based methods, manual annotation, or crowdsourcing annotations through Galaxy Zoo, all show similar results. Another possible explanation to the observation is parity violation in the large-scale structure, such that the magnitude of the parity violation was stronger in the earlier Universe. It can also be linked to other anomalies such as the Ho tension. Analysis of Ho using Ia supernovae shows smaller Ho tension when the spin directions of the host galaxies are consistent, although these results are based on a small number of supernovae, and may not be statistically significant.

astro-ph.GA↗

arXiv2022

Analysis of spin directions of galaxies in the DESI Legacy Survey

The DESI Legacy Survey is a digital sky survey with a large footprint compared to other Earth-based surveys, covering both the Northern and Southern hemispheres. This paper shows the distribution of the spin directions of spiral galaxies imaged by DESI Legacy Survey. A simple analysis of dividing nearly 1.3$\cdot10^6$ spiral galaxies into two hemispheres shows a higher number of galaxies spinning counterclockwise in the Northern hemisphere, and a higher number of galaxies spinning clockwise in the Southern hemisphere. That distribution is consistent with previous observations, but uses a far larger number of galaxies and a larger footprint. The larger footprint allows a comprehensive analysis without the need to fit the distribution into an a priori model, making this study different from all previous analyses of this kind. Fitting the spin directions of the galaxies to cosine dependence shows a dipole axis alignment with probability of $P<10^{-5}$. The analysis is done with a trivial selection of the galaxies, as well as simple explainable annotation algorithm that does not make use of any form of machine learning, deep learning, or pattern recognition. While further work will be required, these results are aligned with previous studies suggesting the possibility of a large-scale alignment of galaxy angular momentum.

astro-ph.CO↗

arXiv2022

Asymmetry in galaxy spin directions -- analysis of data from DES and comparison to four other sky surveys

The paper shows an analysis of the large-scale distribution of galaxy spin directions of 739,286 galaxies imaged by DES. The distribution of the spin directions of the galaxies exhibits a large-scale dipole axis. Comparison of the location of the dipole axis to a similar analysis with data from SDSS, Pan-STARRS, and DESI Legacy Survey shows that all sky surveys exhibit dipole axes within 52$^o$ or less from each other, well within 1$σ$ error. While non-random distribution is unexpected, the findings are consistent across all sky surveys, regardless of the telescope or whether the data were annotated manually or automatically. Possible errors that can lead to the observation are discussed. The paper also discusses previous studies showing opposite conclusions,and analyzes the decisions that led to these results. Although the observation is provocative, and further research will be required, the existing evidence justifies to consider the contention that galaxy spin directions as observed from Earth are not necessarily randomly distributed. Possible explanations can be related to mature cosmological theories, but also to the internal structure of galaxies.

astro-ph.CO↗

arXiv2022

Using 3D and 2D analysis for analyzing large-scale asymmetry in galaxy spin directions

The nature of galaxy spin is still not fully known. Iye et al (2021) applied a 3D analysis to a dataset of bright SDSS galaxies that was used in the past for photometric analysis. They showed that the distribution of spin directions of spiral galaxies is random, providing a dipole axis with low statistical significance of 0.29$σ$. However, to show random distribution, two decisions were made, each can lead to random distribution regardless of the real distribution of the spin direction of galaxies. The first decision was to limit the dataset arbitrarily to z$<$0.1, which is a redshift range in which previous literature already showed that random distribution is expected. More importantly, while the 3D analysis requires the redshift of each galaxy, the analysis was done with the photometric redshift. If the asymmetry existed, its signal is expected to be an order of magnitude weaker than the error of the photometric redshift, and therefore the low statistical signal under these conditions is expected. When using the exact same data without limiting to $z_{phot}<0.1$ and without using the photometric redshift, the distribution of the spin directions in that dataset shows a statistical signal of $>2σ$. Code and data for reproducing the analysis are publicly available. These results are in agreement with other experiments with SDSS, Pan-STARRS, HST, and the DESI Legacy Survey. The paper also examines other previous studies that showed random distribution in galaxy spin directions. While further research will be required, the current evidence suggest that large-scale asymmetry between the number of clockwise and counterclockwise galaxies cannot be ruled out.

astro-ph.CO↗

arXiv2022

Analysis of $\sim10^6$ spiral galaxies from four telescopes shows large-scale patterns of asymmetry in galaxy spin directions

The ability to collect unprecedented amounts of astronomical data has enabled the studying scientific questions that were impractical to study in the pre-information era. This study uses large datasets collected by four different robotic telescopes to profile the large-scale distribution of the spin directions of spiral galaxies. These datasets cover the Northern and Southern hemispheres, in addition to data acquired from space by the Hubble Space Telescope. The data were annotated automatically by a fully symmetric algorithm, as well as manually through a long labor-intensive process, leading to a dataset of nearly $10^6$ galaxies. The data shows possible patterns of asymmetric distribution of the spin directions, and the patterns agree between the different telescopes. The profiles also agree when using automatic or manual annotation of the galaxies, showing very similar large-scale patterns. Combining all data from all telescopes allows the most comprehensive analysis of its kind to date in terms of both the number of galaxies and the footprint size. The results show a statistically significant profile that is consistent across all telescopes. The instruments used in this study are DECam, HST, SDSS, and Pan-STARRS. The paper also discusses possible sources of bias, and analyzes the design of previous work that showed different results. Further research will be required to understand and validate these preliminary observations.

astro-ph.CO↗

arXiv2022

A Possible Large-scale Alignment of Galaxy Spin Directions -- Analysis of 10 Datasets from SDSS, Pan-STARRS, and HST

Multiple observations made by several different telescopes have shown asymmetry between the number of spiral galaxies rotating in opposite directions in different parts of the sky. One of the immediate questions regarding the possible asymmetry of the spin directions is whether the distribution forms a cosmological-scale axis. This paper analyzes and compares 10 different datasets published in the past decade, collected by SDSS, Pan-STARRS, and Hubble Space Telescope. The datasets contain spiral galaxies separated by their spin direction, and the distribution can show dipole axes. The analysis shows that the directions of the most probable dipole axes are consistent in datasets that have similar average redshift, but different between datasets that have different average redshift. The analysis also shows that the location of the most probable axis correlates with the average redshift of the galaxies in the datasets. That is, the location of the most probable axis shifts when the redshift gets higher, and the correlation is statistically significant. This provides a certain indication of a drift in a possible axis formed by the distribution of galaxy spin directions, or a cosmological scale structure that peaks at a certain distance from Earth.

astro-ph.CO↗

arXiv2022

Large-scale asymmetry in galaxy spin directions -- analysis of galaxies with spectra in DES, SDSS, and DESI Legacy Survey

Multiple previous studies using several different probes have shown considerable evidence for the existence of cosmological-scale anisotropy and a Hubble-scale axis. One of the probes that show such evidence is the distribution of the directions toward which galaxies spin. The advantage of the analysis of the distribution of galaxy spin directions compared to the CMB anisotropy is that the ratio of galaxy spin directions is a relative measurement, and therefore less sensitive to background contamination such as Milky Way obstruction. Another advantage is that many spiral galaxies have spectra, and therefore allow to analyze the location of such axis relative to Earth. This paper shows an analysis of the distribution of the spin directions of over 90K galaxies with spectra. That analysis is also compared to previous analyses using the Earth-based SDSS, Pan-STARRS, and DESI Legacy Survey, as well as space-based data collected by HST. The results show very good agreement between the distribution patterns observed with the different telescopes. The dipole or quadrupole axes formed by the spin directions of the galaxies with spectra do not necessarily go directly through Earth.

astro-ph.CO↗

arXiv2022

Self-Supervised Approach to Addressing Zero-Shot Learning Problem

In recent years, self-supervised learning has had significant success in applications involving computer vision and natural language processing. The type of pretext task is important to this boost in performance. One common pretext task is the measure of similarity and dissimilarity between pairs of images. In this scenario, the two images that make up the negative pair are visibly different to humans. However, in entomology, species are nearly indistinguishable and thus hard to differentiate. In this study, we explored the performance of a Siamese neural network using contrastive loss by learning to push apart embeddings of bumblebee species pair that are dissimilar, and pull together similar embeddings. Our experimental results show a 61% F1-score on zero-shot instances, a performance showing 11% improvement on samples of classes that share intersections with the training set.

cs.CV↗

arXiv2022

New evidence and analysis of cosmological-scale asymmetry in galaxy spin directions

In the past several decades, multiple cosmological theories that are based on the contention that the Universe has a major axis have been proposed. Such theories can be based on the geometry of the Universe, or multiverse theories such as black hole cosmology. The contention of a cosmological-scale axis is supported by certain evidence such as the dipole axis formed by the CMB distribution. Here I study another form of cosmological-scale axis, based on the distribution of the spin direction of spiral galaxies. Data from four different telescopes is analyzed, showing nearly identical axis profiles when the distribution of the redshifts of the galaxies is similar.

astro-ph.CO↗

arXiv2022

Systematic biases when using deep neural networks for annotating large catalogs of astronomical images

Deep convolutional neural networks (DCNNs) have become the most common solution for automatic image annotation due to their non-parametric nature, good performance, and their accessibility through libraries such as TensorFlow. Among other fields, DCNNs are also a common approach to the annotation of large astronomical image databases acquired by digital sky surveys. One of the main downsides of DCNNs is the complex non-intuitive rules that make DCNNs act as a ``black box", providing annotations in a manner that is unclear to the user. Therefore, the user is often not able to know what information is used by the DCNNs for the classification. Here we demonstrate that the training of a DCNN is sensitive to the context of the training data such as the location of the objects in the sky. We show that for basic classification of elliptical and spiral galaxies, the sky location of the galaxies used for training affects the behavior of the algorithm, and leads to a small but consistent and statistically significant bias. That bias exhibits itself in the form of cosmological-scale anisotropy in the distribution of basic galaxy morphology. Therefore, while DCNNs are powerful tools for annotating images of extended sources, the construction of training sets for galaxy morphology should take into consideration more aspects than the visual appearance of the object. In any case, catalogs created with deep neural networks that exhibit signs of cosmological anisotropy should be interpreted with the possibility of consistent bias.

astro-ph.GA↗

arXiv2021

eGAN: Unsupervised approach to class imbalance using transfer learning

Class imbalance is an inherent problem in many machine learning classification tasks. This often leads to trained models that are unusable for any practical purpose. In this study we explore an unsupervised approach to address these imbalances by leveraging transfer learning from pre-trained image classification models to encoder-based Generative Adversarial Network (eGAN). To the best of our knowledge, this is the first work to tackle this problem using GAN without needing to augment with synthesized fake images. In the proposed approach we use the discriminator network to output a negative or positive score. We classify as minority, test samples with negative scores and as majority those with positive scores. Our approach eliminates epistemic uncertainty in model predictions, as the P(minority) + P(majority) need not sum up to 1. The impact of transfer learning and combinations of different pre-trained image classification models at the generator and discriminator is also explored. Best result of 0.69 F1-score was obtained on CIFAR-10 classification task with imbalance ratio of 1:2500. Our approach also provides a mechanism of thresholding the specificity or sensitivity of our machine learning system. Keywords: Class imbalance, Transfer Learning, GAN, nash equilibrium

cs.LG↗

arXiv2021

Large-scale asymmetry in galaxy spin directions: evidence from the Southern hemisphere

Recent observations using several different telescopes and sky surveys showed patterns of asymmetry in the distribution of galaxies by their spin directions as observed from Earth. These studies were done with data imaged from the Northern hemisphere, showing excellent agreement between different telescopes and different analysis methods. Here, data from the DESI Legacy Survey was used. The initial dataset contains $\sim2.2\cdot10^7$ galaxy images, reduced to $\sim8.1\cdot10^5$ galaxies annotated by their spin direction using a symmetric algorithm. That makes it not just the first analysis of its kind in which the majority of the galaxies are in the Southern hemisphere, but also by far the largest dataset used for this purpose to date. The results show strong agreement between opposite parts of the sky, such that the asymmetry in one part of the sky is similar to the inverse asymmetry in the corresponding part of the sky in the opposite hemisphere. Fitting the distribution of galaxy spin directions to cosine dependence shows a dipole axis with probability of 4.66$σ$. Interestingly, the location of the most likely axis is within close proximity to the CMB Cold Spot. The profile of the distribution is nearly identical to the asymmetry profile of the distribution identified in Pan-STARRS, and it is within 1$σ$ difference from the distribution profile in SDSS and HST. All four telescopes show similar large-scale profile of asymmetry.

astro-ph.CO↗

arXiv2021

AdeNet: Deep learning architecture that identifies damaged electrical insulators in power lines

Ceramic insulators are important to electronic systems, designed and installed to protect humans from the danger of high voltage electric current. However, insulators are not immortal, and natural deterioration can gradually damage them. Therefore, the condition of insulators must be continually monitored, which is normally done using UAVs. UAVs collect many images of insulators, and these images are then analyzed to identify those that are damaged. Here we describe AdeNet as a deep neural network designed to identify damaged insulators, and test multiple approaches to automatic analysis of the condition of insulators. Several deep neural networks were tested, as were shallow learning methods. The best results (88.8\%) were achieved using AdeNet without transfer learning. AdeNet also reduced the false negative rate to $\sim$7\%. While the method cannot fully replace human inspection, its high throughput can reduce the amount of labor required to monitor lines for damaged insulators and provide early warning to replace damaged insulators.

cs.LG↗