Conceptual Maps and Integrated Experiments for Teaching/Learning Physics of Photonic Devices

AbstractThis paper presents the experimental approach and an example of using conceptual maps as a method based on constructivist mode of learning, teaching and researching knowledge of quantum Physics, using photonic devices. Understanding the Planck relationship, which links energy and frequency as a result of quantification of the energy, is a crucial step. It is one of the most famous examples of the corpuscular nature of light, which led to the development of quantum mechanics in the early 20th century, and whose explanation is still the standard in teaching Physics in high school. The paper also presents the verification of Einstein's theory and determination of Planck's constant using electroluminescent phenomenon for LEDs of different colours. Conceptual maps are a powerful tool not only for perceiving, representing and achieving knowledge, but also for creating new knowledge. It is essential helping students to understand that all concepts are somehow related to each other. Selecting cross-links as specific as possible and identifying the most appropriate linking words to connect concepts are crucial aims. CmapTools software tool can serve as a basis for a new kind of integration of Internet resources and all classroom experiences, inside Physics laboratories, and outside them. If it is used in conjunction with conceptual maps designed to support learning, it provides a new educational model

Cosmic void exclusion models and their impact on the distance scale measurements from large scale structure

Baryonic Acoustic Oscillations (BAOs) studies based on the clustering of voids and matter tracers provide important constraints on cosmological parameters related to the expansion of the Universe. However, modelling the void exclusion effect is an important challenge for fully exploiting the potential of these kind of analyses. We thus develop two numerical methods to describe the clustering of cosmic voids. Neither model requires additional cosmological information beyond that assumed within the galaxy de-wiggled model. The models consist in power spectra whose performance we assess in comparison to a parabolic model on both Patchy boxes and light-cones. Moreover, we test their robustness against systematic effects and the reconstruction technique. The void model power spectra and the parabolic model with a fixed parameter provide strongly correlated values for the Alcock-Paczynski ($\alpha$) parameter, for boxes and light-cones likewise. The resulting $\alpha$ values - for all three models - are unbiased and their uncertainties are correctly estimated. However, the numerical models show less variation with the fitting range compared to the parabolic one. The Bayesian evidence suggests that the numerical techniques are often favoured compared to the parabolic model. Moreover, the void model power spectra computed on boxes can describe the void clustering from light-cones as well as from boxes. The same void model power spectra can be used for the study of pre- and post-reconstructed data-sets. Lastly, the two numerical techniques are resilient against the studied systematic effects. Consequently, using either of the two new void models, one can more robustly measure cosmological parameters.Comment: 18 pages, 24 figure

Cosmic Void Baryon Acoustic Oscillation Measurement: Evaluation of Sensitivity to Selection Effects

Cosmic voids defined as a subset of Delaunay Triangulation (DT) circumspheres have been used to measure the Baryon Acoustic Oscillations (BAO) scale; providing tighter constraints on cosmological parameters when combined with matter tracers. These voids are defined as spheres larger than a given radius threshold, which is constant over the survey volume. However, the response of these void tracers to observational systematics has not yet been studied. In this work we analyse the response of void clustering to selection effects. We find for the case of moderate (<20 per cent) incompleteness, void selection based on a constant radius cut yields robust measurements. This is particularly true for BAO-reconstructed galaxy samples, where large-scale void exclusion effects are mitigated. Moreover, we observe for the case of severe (up to 90 per cent) incompleteness -- such as can be found at the edges of the radial selection function -- that an accurate estimation of the void distribution is necessary for unbiased clustering measurements. In addition, we find that without reconstruction, using a constant threshold under these conditions produces a stronger void exclusion effect that can affect the clustering on large scales. A new void selection criteria dependent on the (local) observed tracer density that maximises the BAO peak significance prevents the aforementioned exclusion features from contaminating the BAO signal. Finally, we verify, with large simulations including light cone evolution, that both void sample definitions (local and constant) yield unbiased and consistent BAO scale measurements.Comment: 16 pages, 16 figures. Accepted by MNRA

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological implications from multi-tracer BAO analysis with galaxies and voids

We construct cosmic void catalogues with the DIVE void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction applied, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident for the galaxy-galaxy, galaxy-void, and void-void correlation functions of all datasets, including the ones cross correlating luminous red galaxy and emission line galaxy samples. Two multi-tracer BAO fitting schemes are then tested, one combining the galaxy and void correlation functions with a weight applied to voids, and the other using a single BAO dilation parameter for all clustering measurements of different tracers. Both methods produce consistent results with mock catalogues, and on average ~10 per cent improvements of the BAO statistical uncertainties are observed for all samples, compared to the results from galaxies alone. By combining the clustering of galaxies and voids, the uncertainties of BAO measurements from the SDSS data are reduced by 5 to 15 per cent, yielding 0.9, 0.8, 1.1, 2.3, and 2.9 per cent constraints on the distance $D_{_{\rm V}}(z)$, at effective redshifts of 0.38, 0.51, 0.70, 0.77, and 0.85, respectively. When combined with BAO measurements from SDSS MGS, QSO, and Ly$\alpha$ samples, as well as the BBN results, we obtain $H_0 = 67.58 \pm 0.91\,{\rm km}\,{\rm s}^{-1}\,{\rm Mpc}^{-1}$, $\Omega_{\rm m} = 0.290 \pm 0.015$, and $\Omega_\Lambda h^2 = 0.3241 \pm 0.0079$ in the flat-$\Lambda$CDM framework, where the 1$\,\sigma$ uncertainties are around 6, 6, and 17 per cent smaller respectively, compared to constraints from the corresponding anisotropic BAO measurements without voids and LRG-ELG cross correlations.Comment: 33 pages, 30 figures, submitted to MNRA

DESI mock challenge: constructing DESI galaxy catalogues based on FastPM simulations

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must buildrealistic simulations and robust covariance matrices. We build galaxy catalogues by applying a halo occupation distribution(HOD) model upon the FASTPM simulations, such that the resulting galaxy clustering reproduces high-resolution N-bodysimulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxytwo-point clustering measurements – monopole and quadrupole – to a precision required by the DESI Year 1 emission line galaxysample down to non-linear scales, i.e. k 10 Mpc h−1. Furthermore, we compute covariance matrices basedon the resulting FASTPM galaxy clustering – monopole and quadrupole. We study for the first time the effect of fitting on Fourierconjugate (e.g. power spectrum) on the covariance matrix of the Fourier counterpart (e.g. correlation function). We estimate theuncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the differentcovariance matrices. Nevertheless, for most studied scales the scatter is between 2 and 10 per cent. Consequently, using thecurrent pipeline we can precisely reproduce the clustering of N-body simulations and the resulting covariance matrices providerobust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESIdata analyses and their extension for other studies

Void BAO measurements on quasars from eBOSS

We present the clustering of voids based on the quasar (QSO) sample of the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in configuration space. We define voids as overlapping empty circumspheres computed by Delaunay tetrahedra spanned by quartets of quasars, allowing for an estimate of the depth of underdense regions. To maximise the BAO signal-to-noise ratio, we consider only voids with radii larger than 36$h^{-1}$Mpc. Our analysis shows a negative BAO peak in the cross-correlation of QSOs and voids. The joint BAO measurement of the QSO auto-correlation and the corresponding cross-correlation with voids shows an improvement in 70$\%$ of the QSO mocks with an average improvement of $\sim5\%$. However, on the SDSS data, we find no improvement compatible with cosmic variance. For both mocks and data, adding voids does not introduce any bias. We find under the flat $\Lambda$CDM assumption, a distance joint measurement on data at the effective redshift $z_{\rm eff}=1.48$ of $D_V(z_{\rm eff})=26.297\pm0.547$. A forecast of a DESI-like survey with 1000 boxes with a similar effective volume recovers the same results as for light-cone mocks with an average of 4.8$\%$ improvement in 68$\%$ of the boxes

Void BAO measurements on quasars from eBOSS

We present the clustering of voids based on the quasar (QSO) sample of the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in configuration space. We define voids as overlapping empty circumspheres computed by Delaunay tetrahedra spanned by quartets of quasars, allowing for an estimate of the depth of underdense regions. To maximise the BAO signal-to-noise ratio, we consider only voids with radii larger than 36$h^{-1}$Mpc. Our analysis shows a negative BAO peak in the cross-correlation of QSOs and voids. The joint BAO measurement of the QSO auto-correlation and the corresponding cross-correlation with voids shows an improvement in 70$\%$ of the QSO mocks with an average improvement of $\sim5\%$. However, on the SDSS data, we find no improvement compatible with cosmic variance. For both mocks and data, adding voids does not introduce any bias. We find under the flat $\Lambda$CDM assumption, a distance joint measurement on data at the effective redshift $z_{\rm eff}=1.48$ of $D_V(z_{\rm eff})=26.297\pm0.547$. A forecast of a DESI-like survey with 1000 boxes with a similar effective volume recovers the same results as for light-cone mocks with an average of 4.8$\%$ improvement in 68$\%$ of the boxes

Cosmic void exclusion models and their impact on the distance scale measurements from large scale structure

Baryonic Acoustic Oscillations (BAOs) studies based on the clustering of voids and matter tracers provide important constraints on cosmological parameters related to the expansion of the Universe. However, modelling the void exclusion effect is an important challenge for fully exploiting the potential of these kind of analyses. We thus develop two numerical methods to describe the clustering of cosmic voids. Neither model requires additional cosmological information beyond that assumed within the galaxy de-wiggled model. The models consist in power spectra whose performance we assess in comparison to a parabolic model on both Patchy boxes and light-cones. Moreover, we test their robustness against systematic effects and the reconstruction technique. The void model power spectra and the parabolic model with a fixed parameter provide strongly correlated values for the Alcock-Paczynski ($\alpha$) parameter, for boxes and light-cones likewise. The resulting $\alpha$ values - for all three models - are unbiased and their uncertainties are correctly estimated. However, the numerical models show less variation with the fitting range compared to the parabolic one. The Bayesian evidence suggests that the numerical techniques are often favoured compared to the parabolic model. Moreover, the void model power spectra computed on boxes can describe the void clustering from light-cones as well as from boxes. The same void model power spectra can be used for the study of pre- and post-reconstructed data-sets. Lastly, the two numerical techniques are resilient against the studied systematic effects. Consequently, using either of the two new void models, one can more robustly measure cosmological parameters

Cosmic void exclusion models and their impact on the distance scale measurements from large scale structure

Baryonic Acoustic Oscillations (BAOs) studies based on the clustering of voids and matter tracers provide important constraints on cosmological parameters related to the expansion of the Universe. However, modelling the void exclusion effect is an important challenge for fully exploiting the potential of these kind of analyses. We thus develop two numerical methods to describe the clustering of cosmic voids. Neither model requires additional cosmological information beyond that assumed within the galaxy de-wiggled model. The models consist in power spectra whose performance we assess in comparison to a parabolic model on both Patchy boxes and light-cones. Moreover, we test their robustness against systematic effects and the reconstruction technique. The void model power spectra and the parabolic model with a fixed parameter provide strongly correlated values for the Alcock-Paczynski ($\alpha$) parameter, for boxes and light-cones likewise. The resulting $\alpha$ values - for all three models - are unbiased and their uncertainties are correctly estimated. However, the numerical models show less variation with the fitting range compared to the parabolic one. The Bayesian evidence suggests that the numerical techniques are often favoured compared to the parabolic model. Moreover, the void model power spectra computed on boxes can describe the void clustering from light-cones as well as from boxes. The same void model power spectra can be used for the study of pre- and post-reconstructed data-sets. Lastly, the two numerical techniques are resilient against the studied systematic effects. Consequently, using either of the two new void models, one can more robustly measure cosmological parameters