1,680 research outputs found

    The effect of peculiar velocities on the epoch of reionization (EoR) 21-cm signal

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    We have used semi-numerical simulations of reionization to study the behaviour of the power spectrum of the EoR 21-cm signal in redshift space. We have considered two models of reionization, one which has homogeneous recombination (HR) and the other incorporating inhomogeneous recombination (IR). We have estimated the observable quantities --- quadrupole and monopole moments of HI power spectrum at redshift space from our simulated data. We find that the magnitude and nature of the ratio between the quadrupole and monopole moments of the power spectrum (P2s/P0sP^s_2 /P^s_0) can be a possible probe for the epoch of reionization. We observe that this ratio becomes negative at large scales for xHI0.7x_{HI} \leq 0.7 irrespective of the reionization model, which is a direct signature of an inside-out reionization at large scales. It is possible to qualitatively interpret the results of the simulations in terms of the fluctuations in the matter distribution and the fluctuations in the neutral fraction which have power spectra and cross-correlation PΔΔ(k)P_{\Delta \Delta}(k), Pxx(k)P_{xx}(k) and PΔx(k)P_{\Delta x}(k) respectively. We find that at large scales the fluctuations in matter density and neutral fraction is exactly anti-correlated through all stages of reionization. This provides a simple picture where we are able to qualitatively interpret the behaviour of the redshift space power spectra at large scales with varying xHIx_{HI} entirely in terms of a just two quantities, namely xHIx_{HI} and the ratio Pxx/PΔΔP_{xx}/P_{\Delta \Delta}. The nature of PΔxP_{\Delta x} becomes different for HR and IR scenarios at intermediate and small scales. We further find that it is possible to distinguish between an inside-out and an outside-in reionization scenario from the nature of the ratio P2s/P0sP^s_2 /P^s_0 at intermediate length scales.Comment: 11 pages, 6 figures. Accepted for publication in MNRAS. Replaced to match the accepted version. Added one appendix to quantify the possible uncertainties in the estimation of the multipole moments of redshift space power spectru

    Detecting ionized bubbles in redshifted 21 cm maps

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    The reionization of the Universe, it is believed, occurred by the growth of ionized regions (bubbles) in the neutral intergalactic medium (IGM). We study the possibility of detecting these bubbles in radio-interferometric observations of redshifted neutral hydrogen (HI) 21 cm radiation. The signal 1 mJy will be buried in noise and foregrounds, the latter being at least a few orders of magnitude stronger than the signal. We develop a visibility based formalism that uses a filter to optimally combine the entire signal from a bubble while minimizing the noise and foreground contributions. This formalism makes definite predictions on the ability to detect an ionized bubble or conclusively rule out its presence in a radio- interferometric observation. We make predictions for the currently functioning GMRT and a forthcoming instrument, the MWA at a frequency of 150 MHz (corresponding to a redshift of 8.5). For both instruments, we show that a 3 sigma detection will be possible for a bubble of comoving radius R_b > 40 Mpc (assuming it to be spherical) in 100 hrs of observation and R_b 22 Mpc in 1000 hrs of observation, provided the bubble is at the center of the field of view. In both these cases the filter effectively removes the expected foreground contribution so that it is below the signal, and the system noise is the deciding criteria. We find that there is a fundamental limitation on the smallest bubble that can be detected arising from the statistical fluctuations in the HI distribution. Assuming that the HI traces the dark matter we find that it will not be possible to detect bubbles with R_b < 8 Mpc using the GMRT and R_b < 16 Mpc using the MWA, however large be the integration time.Comment: 11 pages, 10 figures, 1 table. Accepted for Publication in MNRAS. Revised to match the accepted versio

    Constraining Quasar and IGM Properties Through Bubble Detection in Redshifted 21-cm Maps

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    The infrared detection of a z>7 quasar has opened up a new window to directly probe the IGM during the epoch of reionization. In this paper we theoretically consider the possibility of detecting the ionized bubble around a z=8 quasar using targeted redshifted 21-cm observations with the GMRT. The apparent shape and size of the ionized bubble, as seen by a distant observer, depends on the parameters \dot{N}_{phs}/C, x_HI/C and \tau_Q where \dot{N}_{phs}, \tau_Q, x_HI and C are respectively the photon emission rate, age of the quasar, the neutral fraction and clumping factor of the IGM.Here we have analytically estimated the shape and size of a quasar's ionized bubble assuming an uniform IGM and ignoring other ionizing sources besides the quasar, and used this as a template for matched filter bubble search with the GMRT visibility data. We have assumed that \dot{N}_{phs} is known from the infrared spectrum and C from theoretical considerations, which gives us two free parameters x_HI and \tau_Q for bubble. Considering 1,000 hr of observation, we find that there is a reasonably large region of parameter space where a 3\sigma detection is possible. We also find that it will be possible to place lower limits on x_HI and \tau_Q with this observation. Deeper follow up observations can place upper limits on \tau_Q and x_HI. Value of C affect the estimation of x_HI but the estimation of \tau_Q remains unaffected.We have used a semi-numerical technique to simulate the apparent shape and size of quasar ionized bubbles considering the presence of other ionizing sources and inhomogeneities in the IGM. The presence of other sources increase the size of the quasar bubble, leading to underestimation of x_HI. Clustering of other ionizing sources around the quasar can produce severe distortions in bubble's shape. However, this does not severely affect parameter estimation in the bubbles that are large.Comment: 18 pages, 16 figures, 3 tables. Minor change in text. Accepted for publication in MNRA

    MSIR@FIRE: A Comprehensive Report from 2013 to 2016

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    [EN] India is a nation of geographical and cultural diversity where over 1600 dialects are spoken by the people. With the technological advancement, penetration of the internet and cheaper access to mobile data, India has recently seen a sudden growth of internet users. These Indian internet users generate contents either in English or in other vernacular Indian languages. To develop technological solutions for the contents generated by the Indian users using the Indian languages, the Forum for Information Retrieval Evaluation (FIRE) was established and held for the first time in 2008. Although Indian languages are written using indigenous scripts, often websites and user-generated content (such as tweets and blogs) in these Indian languages are written using Roman script due to various socio-cultural and technological reasons. A challenge that search engines face while processing transliterated queries and documents is that of extensive spelling variation. MSIR track was first introduced in 2013 at FIRE and the aim of MSIR was to systematically formalize several research problems that one must solve to tackle the code mixing in Web search for users of many languages around the world, develop related data sets, test benches and most importantly, build a research community focusing on this important problem that has received very little attention. This document is a comprehensive report on the 4 years of MSIR track evaluated at FIRE between 2013 and 2016.Somnath Banerjee and Sudip Kumar Naskar are supported by Media Lab Asia, MeitY, Government of India, under the Visvesvaraya PhD Scheme for Electronics & IT. The work of Paolo Rosso was partially supported by the MISMIS research project PGC2018-096212-B-C31 funded by the Spanish MICINN.Banerjee, S.; Choudhury, M.; Chakma, K.; Kumar Naskar, S.; Das, A.; Bandyopadhyay, S.; Rosso, P. (2020). MSIR@FIRE: A Comprehensive Report from 2013 to 2016. 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The first cross-script code-mixed question answering corpus. In: Proceedings of the workshop on modeling, learning and mining for cross/multilinguality (MultiLingMine 2016), co-located with the 38th European Conference on Information Retrieval (ECIR). 2016.Banerjee S, Naskar SK, Rosso P, Bandyopadhyay S. Named entity recognition on code-mixed cross-script social media content. Comput Sistemas. 2017;21(4):681–92.Barman U, Das A, Wagner J, Foster J. Code mixing: a challenge for language identification in the language of social media. In: Proceedings of the first workshop on computational approaches to code switching. 2014. pp. 13–23.Bhardwaj P, Pakray P, Bajpeyee V, Taneja A. Information retrieval on code-mixed Hindi–English tweets. In: Working notes of FIRE 2016—forum for information retrieval evaluation, Kolkata, India, December 7–10, 2016, CEUR workshop proceedings. 2016.Bhargava R, Khandelwal S, Bhatia A, Sharmai Y. Modeling classifier for code mixed cross script questions. In: Working notes of FIRE 2016—forum for information retrieval evaluation, Kolkata, India, December 7–10, 2016, CEUR workshop proceedings. CEUR-WS.org. 2016.Bhattacharjee D, Bhattacharya, P. Ensemble classifier based approach for code-mixed cross-script question classification. In: Working notes of FIRE 2016—forum for information retrieval evaluation, Kolkata, India, December 7–10, 2016, CEUR workshop proceedings. CEUR-WS.org. 2016.Chakma K, Das A. CMIR: a corpus for evaluation of code mixed information retrieval of Hindi–English tweets. In: The 17th international conference on intelligent text processing and computational linguistics (CICLING). 2016.Choudhury M, Chittaranjan G, Gupta P, Das A. Overview of fire 2014 track on transliterated search. Proceedings of FIRE. 2014. pp. 68–89.Ganguly D, Pal S, Jones GJ. Dcu@fire-2014: fuzzy queries with rule-based normalization for mixed script information retrieval. In: Proceedings of the forum for information retrieval evaluation, ACM, 2014. pp. 80–85.Gella S, Sharma J, Bali K. Query word labeling and back transliteration for Indian languages: shared task system description. FIRE Working Notes. 2013;3.Gupta DK, Kumar S, Ekbal A. Machine learning approach for language identification and transliteration. In: Proceedings of the forum for information retrieval evaluation, ACM, 2014. pp. 60–64.Gupta P, Bali K, Banchs RE, Choudhury M, Rosso P. Query expansion for mixed-script information retrieval. In: Proceedings of the 37th international ACM SIGIR conference on research and development in information retrieval, ACM, 2014. pp. 677–686.Gupta P, Rosso P, Banchs RE. Encoding transliteration variation through dimensionality reduction: fire shared task on transliterated search. In: Fifth forum for information retrieval evaluation. 2013.HB Barathi Ganesh, M Anand Kumar, KP Soman. Distributional semantic representation for information retrieval. 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In: Working notes of FIRE 2016—forum for information retrieval evaluation, Kolkata, India, December 7–10, 2016, CEUR workshop proceedings. 2016.Anand Kumar M, Soman KP. Amrita-CEN@MSIR-FIRE2016: Code-mixed question classification using BoWs and RNN embeddings. In: Working notes of FIRE 2016—forum for information retrieval evaluation, Kolkata, India, December 7–10, 2016, CEUR workshop proceedings. CEUR-WS.org. 2016.Majumder G, Pakray P. NLP-NITMZ@MSIR 2016 system for code-mixed cross-script question classification. In: Working notes of FIRE 2016—forum for information retrieval evaluation, Kolkata, India, December 7–10, 2016, CEUR workshop proceedings. CEUR-WS.org. 2016.Mandal S, Banerjee S, Naskar SK, Rosso P, Bandyopadhyay S. Adaptive voting in multiple classifier systems for word level language identification. In: FIRE workshops, 2015. pp. 47–50.Mukherjee A, Ravi A , Datta K. Mixed-script query labelling using supervised learning and ad hoc retrieval using sub word indexing. In: Proceedings of the Forum for Information Retrieval Evaluation, Bangalore, India, 2014.Pakray P, Bhaskar P. Transliterated search system for Indian languages. In: Pre-proceedings of the 5th FIRE-2013 workshop, forum for information retrieval evaluation (FIRE). 2013.Patel S, Desai V. Liga and syllabification approach for language identification and back transliteration: a shared task report by da-iict. In: Proceedings of the forum for information retrieval evaluation, ACM, 2014. pp. 43–47.Prabhakar DK, Pal S. Ism@fire-2013 shared task on transliterated search. In: Post-Proceedings of the 4th and 5th workshops of the forum for information retrieval evaluation, ACM, 2013. p. 17.Prabhakar DK, Pal S. Ism@ fire-2015: mixed script information retrieval. In: FIRE workshops. 2015. pp. 55–58.Prakash A, Saha SK. A relevance feedback based approach for mixed script transliterated text search: shared task report by bit Mesra. 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    Detailed study of the ELAIS N1 field with the uGMRT - I. Characterizing the 325 MHz foreground for redshifted 21 cm observations

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    In this first paper of the series, we present initial results of newly upgraded Giant Meterwave Radio Telescope (uGMRT) observation of European Large-Area ISO Survey-North 1 (ELAIS-N1) at 325 MHz with 32 MHz bandwidth. Precise measurement of fluctuations in Galactic and extragalactic foreground emission as a function of frequency as well as angular scale is necessary for detecting redshifted 21-cm signal of neutral hydrogen from Cosmic Dawn, Epoch of Reionization (EoR) and post-reionization epoch. Here, for the first time we have statistically quantified the Galactic and extragalactic foreground sources in the ELAIS-N1 field in the form of angular power spectrum using the newly developed Tapered Gridded Estimator (TGE). We have calibrated the data with and without direction-dependent calibration techniques. We have demonstrated the effectiveness of TGE against the direction dependent effects by using higher tapering of field of view (FoV). We have found that diffuse Galactic synchrotron emission (DGSE) dominates the sky, after point source subtraction, across the angular multipole range 11155083 1115 \leqslant \mathcal{\ell} \leqslant 5083 and 15654754 1565 \leqslant \mathcal{\ell} \leqslant 4754 for direction-dependent and -independent calibrated visibilities respectively. The statistical fluctuations in DGSE has been quantified as a power law of the form C=Aβ\mathcal{C}_{\mathcal{\ell}}= A \mathcal{\ell}^{-\beta} . The best fitted values of (A, β\beta) are (62±6 62 \pm 6 mK2mK^{2}, 2.55±0.32.55 \pm 0.3 ) and (48±4 48 \pm 4 mK2mK^{2}, 2.28±0.42.28 \pm 0.4 ) for the two different calibration approaches. For both the cases, the power law index is consistent with the previous measurements of DGSE in other parts of sky.Comment: 13 pages, 5figures, 4 tables; accepted for publication in MNRA

    Towards 21-cm Intensity Mapping at z=2.28z=2.28 with uGMRT using the Tapered Gridded Estimator I: Foreground Avoidance

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    The post-reionization (z6)(z \le 6) neutral hydrogen (HI) 21-cm intensity mapping signal holds the potential to probe the large scale structures, study the expansion history and constrain various cosmological parameters. Here we apply the Tapered Gridded Estimator (TGE) to estimate P(k,k)P(k_{\perp},k_{\parallel}) the power spectrum of the z=2.28z = 2.28 (432.8MHz)(432.8\, {\rm MHz}) redshifted 21-cm signal using a 24.4MHz24.4\,{\rm MHz} sub-band drawn from uGMRT Band 3 observations of European Large-Area ISO Survey-North 1 (ELAIS-N1). The TGE allows us to taper the sky response which suppresses the foreground contribution from sources in the periphery of the telescope's field of view. We apply the TGE on the measured visibility data to estimate the multi-frequency angular power spectrum (MAPS) C(Δν)C_{\ell}(\Delta\nu) from which we determine P(k,k)P(k_{\perp},k_{\parallel}) using maximum-likelihood which naturally overcomes the issue of missing frequency channels (55 \% here). The entire methodology is validated using simulations. For the data, using the foreground avoidance technique, we obtain a 2σ2\,\sigma upper limit of Δ2(k)(133.97)2mK2\Delta^2(k) \le (133.97)^2 \, {\rm mK}^{2} for the 21-cm brightness temperature fluctuation at k=0.347Mpc1k = 0.347 \, \textrm{Mpc}^{-1}. This corresponds to [ΩHIbHI]0.23[\Omega_{\rm HI}b_{\rm HI}] \le 0.23, where ΩHI\Omega_{\rm HI} and bHIb_{\rm HI} respectively denote the cosmic \HI mass density and the \HI bias parameter. A previous work has analyzed 8MHz8 \, {\rm MHz} of the same data at z=2.19z=2.19, and reported Δ2(k)(61.49)2mK2\Delta^{2}(k) \le (61.49)^{2} \, {\rm mK}^{2} and [ΩHIbHI]0.11[\Omega_{\rm HI} b_{\rm HI}] \le 0.11 at k=1Mpc1k=1 \, {\rm Mpc}^{-1}. The upper limits presented here are still orders of magnitude larger than the expected signal corresponding to ΩHI103\Omega_{\rm HI} \sim 10^{-3} and bHI2b_{\rm HI} \sim 2 .Comment: 13 pages, 11 figures, accepted for publication in MNRA

    Towards 2121-cm intensity mapping at z=2.28z=2.28 with uGMRT using the tapered gridded estimator III: Foreground removal

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    Neutral hydrogen (\ion{H}{i}) 2121-cm intensity mapping (IM) is a promising probe of the large-scale structures in the Universe. However, a few orders of magnitude brighter foregrounds obscure the IM signal. Here we use the Tapered Gridded Estimator (TGE) to estimate the multi-frequency angular power spectrum (MAPS) C(Δν)C_{\ell}(\Delta\nu) from a 24.4MHz24.4\,\rm{MHz} bandwidth uGMRT Band 33 data at 432.8MHz432.8\,\rm{MHz}. In C(Δν)C_{\ell}(\Delta\nu) foregrounds remain correlated across the entire Δν\Delta\nu range, whereas the 2121-cm signal is localized within Δν[Δν]\Delta\nu\le[\Delta \nu] (typically 0.51MHz0.5-1\,\rm{MHz}). Assuming the range Δν>[Δν]\Delta\nu>[\Delta \nu] to have minimal 2121-cm signal, we use C(Δν)C_{\ell}(\Delta\nu) in this range to model the foregrounds. This foreground model is extrapolated to Δν[Δν]\Delta\nu\leq[\Delta \nu], and subtracted from the measured C(Δν)C_{\ell}(\Delta\nu). The residual [C(Δν)]res[C_{\ell}(\Delta\nu)]_{\rm res} in the range Δν[Δν]\Delta\nu\le[\Delta\nu] is used to constrain the 2121-cm signal, compensating for the signal loss from foreground subtraction. [C(Δν)]res[C_{\ell}(\Delta\nu)]_{\rm{res}} is found to be noise-dominated without any trace of foregrounds. Using [C(Δν)]res[C_{\ell}(\Delta\nu)]_{\rm res} we constrain the 2121-cm brightness temperature fluctuations Δ2(k)\Delta^2(k), and obtain the 2σ2\sigma upper limit ΔUL2(k)(18.07)2mK2\Delta_{\rm UL}^2(k)\leq(18.07)^2\,\rm{mK^2} at k=0.247Mpc1k=0.247\,\rm{Mpc}^{-1}. We further obtain the 2σ2\sigma upper limit [\Omega_{\ion{H}{i}}b_{\ion{H}{i}}]_{\rm UL}\leq0.022 where \Omega_{\ion{H}{i}} and b_{\ion{H}{i}} are the comoving \ion{H}{i} density and bias parameters respectively. Although the upper limit is nearly 1010 times larger than the expected 2121-cm signal, it is 33 times tighter over previous works using foreground avoidance on the same data.Comment: Accepted for publication in MNRAS. 16 pages (including Appendix), 8 figures (plus 8 in Appendix), 5 Table

    Simulating the impact of HI fluctuations on matched filter search for ionized bubbles in redshifted 21 cm maps

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    Extending the formalism of Datta, Bharadwaj & Choudhury (2007) for detecting ionized bubbles in redshifted 21 cm maps using a matched-filtering technique, we use different simulations to analyze the impact of HI fluctuations outside the bubble on the detectability of the bubble. In the first three kinds of simulations there is a spherical bubble of comoving radius R_b, the one that we are trying to detect, located at the center, and the neutral hydrogen (HI) outside the bubble traces the underlying dark matter distribution. We consider three different possible scenarios of reionization, i.e., (i) there is a single bubble (SB) in the field of view (FoV) and the hydrogen neutral fraction is constant outside this bubble (ii) patchy reionization with many small ionized bubbles in the FoV (PR1) and (iii) many spherical ionized bubbles of the same radius RbR_b (PR2). The fourth kind of simulation uses more realistic maps based on semi-numeric modelling (SM) of ionized regions. We find that for both the SB and PR1 scenarios the fluctuating IGM restricts bubble detection to size R_b<= 6 Mpc and R_b<= 12 Mpc for the GMRT and the MWA respectively, however large be the integration time. These results are well explained by analytical predictions. Large uncertainty due to the HI fluctuations restricts bubble detection in the PR2 scenario for neutral fraction x_HI<0.6. The matched-filter technique works well even when the targeted ionized bubble is non-spherical due to surrounding bubbles and inhomogeneous recombination (SM). We find that determining the size and positions of the bubbles is not limited by the HI fluctuations in the SB and PR1 scenario but limited by the instrument's angular resolution instead, and this can be done more precisely for larger bubble (abridged).Comment: 14 pages, 15 Postscript figures, Revised to incorporate ionization maps produced by the semi-numeric approach. Accepted for publication in MNRA
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