Deep Optical Imaging Research Articles

Automated High-Throughput Atomic Force Microscopy Single-Cell Nanomechanical Assay Enabled by Deep Learning-Based Optical Image Recognition.

Mechanical forces are essential for life activities, and the mechanical phenotypes of single cells are increasingly gaining attention. Atomic force microscopy (AFM) has been a standard method for single-cell nanomechanical assays, but its efficiency is limited due to its reliance on manual operation. Here, we present a study of deep learning image recognition-assisted AFM that enables automated high-throughput single-cell nanomechanical measurements. On the basis of the label-free identification of the cell structures and the AFM probe in optical bright-field images as well as the consequent automated movement of the sample stage and AFM probe, the AFM probe tip could be accurately and sequentially moved onto the specific parts of individual living cells to perform a single-cell indentation assay or single-cell force spectroscopy in a time-efficient manner. The study illustrates a promising method based on deep learning for achieving operator-independent high-throughput AFM single-cell nanomechanics, which will benefit the application of AFM in mechanobiology.

FMAW-YOLOv5s: A deep learning method for detection of methane plumes using optical images

Natural gas hydrates stored in the subsurface seabed of continental margins are one of the most important carbon reservoirs on Earth. Research on natural gas hydrates is of great significance to global warming and ecological protection. Methane plumes caused by crustal dynamics are usually considered as a sign of existence of natural gas hydrates. Detection of methane plumes thus becomes the first step of cold seep research. This paper conducts comprehensive research on detection of methane plumes based on deep learning methods and optical images. First, we proposed a method of creating high quality and balanced datasets for methane plumes detection tasks using open-source videos. We then proposed a FMAW-YOLOv5s method for methane plumes detection. The FMAW-YOLOv5s method improves the traditional YOLOv5s in design of backbone network, neck network and loss function. The FMAW-YOLOv5s method can realize accurate and fast detection of methane plumes with a precision of 96.9% and FPS of 141.7. The lightweight feature of FMAW-YOLOv5s also enables the deployment in edge computing devices such as AUVs and ROVs. This research can not only promote the study of cold seep activities, but also provide meaningful insights for detection of other underwater events such as gas pipelines leakage.

Distance estimation of gamma-ray-emitting BL Lac objects from imaging observations

The direct redshift determination of BL Lac objects is highly challenging as the emission in the optical and near-infrared bands is largely dominated by the non-thermal emission from the relativistic jet, which points very close to our line of sight. Therefore, the optical spectra of BL Lac objects often show no spectral lines from the host galaxy. In this work, we aim to overcome this difficulty by attempting to detect the host galaxy and derive redshift constraints based on assumptions on the galaxy magnitude (`imaging redshifts'). Imaging redshifts were derived by obtaining deep optical images under good seeing conditions, making it possible to detect the host galaxy as a weak extension of the point-like source. We then derived the imaging redshift by using the host galaxy as a standard candle, employing two different methods. We determine the imaging redshift for 9 out of 17 blazars that we observed as part of this programme. The redshift range of these targets is 0.28-0.60, and the two methods used to derive the redshift give very consistent results within the uncertainties. We also performed a detailed comparison of the imaging redshifts with those obtained using other methods, such as direct spectroscopic constraints or looking for groups of galaxies close to the blazar. We show that the constraints from the different methods are consistent and that combining the three constraints narrows down the redshift. For example, in the case of J2156.0+1818, which is the most distant source for which we detect the host galaxy, the redshift range is narrowed to $0.63<z<0.71$. This makes the source interesting for future studies of extragalactic background light in the Cherenkov Telescope Array Observatory era.

Tidal features and disc thicknesses of edge-on galaxies in the SDSS Stripe 82

ABSTRACT We examine deep optical images of edge-on galaxies selected from the Sloan Digital Sky Survey (SDSS) Stripe 82. The entire sample consists of over 800 genuine edge-on galaxies with spectroscopic redshifts out to $z\sim 0.2$. To discern the faintest details around the galaxies, we use three different data sources with a photometric depth of down to 30 mag arcsec$^{-2}$ in the r band: SDSS Stripe 82, Hyper Suprime-Cam Strategic Program, and DESI Legacy Imaging Surveys. Our analysis of the deep images reveals a variety of low surface brightness features. 49 galaxies exhibit prominent tidal structures, including tidal tails, stellar streams, bridges, and diffuse shells. Additionally, 56 galaxies demonstrate peculiar structural features such as lopsided discs, faint warps, and dim polar rings. Overall, we detect low surface brightness structures in 94 galaxies out of 838, accounting for 11 per cent of the sample. Notably, the fraction of tidal structures is only 5.8 per cent, which is significantly lower than that obtained in modern cosmological simulations and observations. Previous studies have shown that strongly interacting galaxies have stellar discs about 1.5–2 times thicker than those without apparent interactions. In an analysis where tidal features are carefully masked for precise disc axis ratio measurements, we show that discs of galaxies with tidal features are 1.33 times thicker, on average, than control galaxies that do not have visible tidal features. Furthermore, we find that edge-on galaxies with tidal structures tend to have a higher fraction of oval and boxy discs than galaxies without tidal features.

CAVITY, Calar Alto Void Integral-field Treasury surveY and project extension

We have learnt in the last decades that the majority of galaxies belong to high density regions interconnected in a sponge-like fashion. This large-scale structure is characterised by clusters, filaments, and walls, where most galaxies concentrate, but also under-dense regions called voids. The void regions and the galaxies within represent an ideal place for the study of galaxy formation and evolution, as they are largely unaffected by the complex physical processes that transform galaxies in high-density environments. The void galaxies may hold the key to answer current challenges to the Lambda CDM paradigm as well. The CAVITY survey is a Legacy project approved by the Calar Alto Observatory to obtain spatially resolved spectroscopic information of $ void galaxies in the Local Universe (0.005 < z < 0.050), covering -17.0 to -21.5 in $ r$ band absolute magnitude. It officially started in January 2021 and has been awarded 110 useful dark observing nights at the 3.5 m telescope using the PMAS spectrograph. Complementary follow-up projects, including deep optical imaging, integrated as well as resolved CO data, and integrated HI spectra, have joined the PMAS observations and naturally complete the scientific aim of characterising galaxies in cosmic voids. The extension data has been named CAVITY+. The data will be available to the whole community in different data releases, the first of which is planned for July 2024, and it will provide the community with PMAS datacubes for around 100 void galaxies through a user friendly and well documented database platform. Here, we present the survey, sample selection, data reduction, quality control schemes, science goals, and some examples of the scientific power of the CAVITY and CAVITY+ data.

Deep Optical Emission-line Images of Nine Known and Three New Galactic Supernova Remnants

Deep optical emission-line images are presented for nine known plus three new Galactic supernova remnants (SNRs), all but one having at least one angular dimension >1°. Wide-field images taken in Hα and [O iii] λ5007 reveal many new and surprising remnant structures including large remnant shock extensions and “breakout” features not seen in published optical or radio data. These images represent over 12,000 individual images totaling more than 1000 hr of exposure time taken over the last 2 yr mainly using small aperture telescopes, which detected fainter nebular line emissions than published emission-line images. During the course of this imaging program, we discovered three new SNRs, namely G107.5-5.1 (the Nereides Nebula), G209.9-8.2, and G210.5+1.3, two of which have diameters >1.°5. In addition to offering greater structural detail on the nine already known SNRs, a key finding of this study is the importance of [O iii] emission-line imaging for mapping the complete shock emissions of Galactic SNRs.

Star formation exists in all early-type galaxies – evidence from ubiquitous structure in UV images

ABSTRACT Recent surveys have demonstrated the widespread presence of ultraviolet (UV) emission in early-type galaxies (ETGs), suggesting the existence of star formation in many of these systems. However, potential UV contributions from old and young stars, together with model uncertainties, makes it challenging to confirm the presence of young stars using integrated photometry alone. This is particularly true in ETGs that are fainter in the UV and have red UV-optical colours. An unambiguous way of disentangling the source of the UV is to look for structure in UV images. Optical images of ETGs, which are dominated by old stars, are smooth and devoid of structure. If the UV is also produced by these old stars, then the UV images will share this smoothness, while, if driven by young stars, they will exhibit significant structure. We compare the UV and optical morphologies of 32 ETGs (93 per cent of which are at z < 0.03) using quantitative parameters (concentration, asymmetry, clumpiness, and the Sérsic index), calculated via deep UV and optical images with similar resolution. Regardless of stellar mass, UV-optical colour or the presence of interactions, the asymmetry and clumpiness of ETGs is significantly larger (often by several orders of magnitudes) in the UV than in the optical, while the UV Sérsic indices are typically lower than their optical counterparts. The ubiquitous presence of structure demonstrates that the UV flux across our entire ETG sample is dominated by young stars and indicates that star formation exists in all ETGs in the nearby Universe.

Optical properties of Y dwarfs observed with the Gran Telescopio Canarias

Our science goals are to characterise the optical properties of Y dwarfs and to study their consistency with theoretical models. A sample of five Y dwarfs was observed with three optical and near-infrared instruments at the 10.4\,m Gran Telescopio Canarias. Deep near-infrared ($J$- or $H$-band) and multicolour optical images ($z$-, $i$-, $r$-, $g$-, $u$-bands) of the five targets and a low-resolution far-red optical spectrum for one of the targets were obtained. One of the Y dwarfs, WISE J173835.53+273258.9 (Y0), was clearly detected in the optical ($z$- and $i$-bands) and another, WISE J182831.08+265037.7 (Y2), was detected only in the $z$-band. We measured the colours of our targets and found that the $z-J$ and $i-z$ colours of the Y dwarfs are bluer than those of mid- and late-T dwarfs. This optical blueing has been predicted by models, but our data indicates that it is sharper and happens at temperatures about 150 K warmer than expected. The culprit is the K I resonance doublet, which weakens more abruptly in the T- to Y-type transition than expected. Moreover, we show that the alkali resonance lines (Cs I and K I) are weaker in Y dwarfs than in T dwarfs; the far-red optical spectrum of WISE J173835.53+273258.9 is similar to that of late-T dwarfs, but with stronger methane and water features; and we noted the appearance of new absorption features that we propose could be due to hydrogen sulphide. Last but not least, in 2014, WISE J173835.53+273258.9 presented a bluer $i-z$ colour than in 2021 by a factor of 2.8 (significance of 2.5sigma ). Thanks to our deep optical images, we found that the 2014 $i$-band spectrum was contaminated by a galaxy bluer than the Y dwarf. The optical properties of Y dwarfs presented here pose new challenges to the modelling of grain sedimentation in extremely cool objects. The weakening of the very broad K I resonance doublet due to condensation in dust grains is more abrupt than theoretically anticipated. Consequently, the observed blueing of the $z-J$ and $i-z$ colours of Y dwarfs with respect to T dwarfs is more pronounced than predicted by models and could boost the potential of upcoming deep large-area optical surveys regarding their ability to detect extremely cool objects.

The Magellan M2FS Spectroscopic Survey of High-redshift Galaxies: The Brightest Lyman-break Galaxies at z ∼ 6

We present a study of a sample of 45 spectroscopically confirmed, UV luminous galaxies at z ∼ 6. They were selected as bright Lyman-break galaxies (LBGs) using deep multiband optical images in more than 2 deg2 of the sky, and subsequently identified via their strong Lyα emission. The majority of these LBGs span an absolute UV magnitude range from −22.0 to −20.5 mag with Lyα equivalent width (EW) between ∼10 and ∼200 Å, representing the most luminous galaxies at z ∼ 6 in terms of both UV continuum emission and Lyα line emission. We model the spectral energy distributions of 10 LBGs that have deep infrared observations from Hubble Space Telescope, JWST, and/or Spitzer, and find that they have a wide range of stellar masses and ages. They also have high star formation rates ranging from a few tens to a few hundreds of solar mass per year. Five of the LBGs have JWST or HST images, and four of them show compact morphology in these images, including one that is roughly consistent with a point source, suggesting that UV luminous galaxies at this redshift are generally compact. The fraction of our photometrically selected LBGs with strong Lyα emission (EW > 25 Å) is about 0.2, which is consistent with previous results and supports a moderate evolution of the intergalactic medium opacity at the end of cosmic reionization. Using deep X-ray images, we do not find evidence of strong active galactic nucleus (AGN) activity in these galaxies, but our constraint is loose, and we are not able to rule out the possibility of any weak AGN activity.

The morphological mix of dwarf galaxies in the nearby Universe

ABSTRACT We use a complete, unbiased sample of 257 dwarf (10$^{8}\, {\rm M}_{\odot } \lt M_{\rm {\star }} \lt 10^{9.5}\, {\rm M}_{\odot }$) galaxies at z < 0.08, in the COSMOS field, to study the morphological mix of the dwarf population in low-density environments. Visual inspection of extremely deep optical images and their unsharp-masked counterparts reveals three principal dwarf morphological classes. 43 per cent and 45 per cent of dwarfs exhibit the traditional ‘early-type’ (elliptical/S0) and ‘late-type’ (spiral) morphologies, respectively. However, 10 per cent populate a ‘featureless’ class, that lacks both the central light concentration seen in early-types and any spiral structure – this class is missing in the massive-galaxy regime. 14 per cent, 27 per cent, and 19 per cent of early-type, late-type, and featureless dwarfs respectively show evidence for interactions, which drive around 20 per cent of the overall star formation activity in the dwarf population. Compared to their massive counterparts, dwarf early-types show a much lower incidence of interactions, are significantly less concentrated and share similar rest-frame colours as dwarf late-types. This suggests that the formation histories of dwarf and massive early-types are different, with dwarf early-types being shaped less by interactions and more by secular processes. The lack of large groups or clusters in COSMOS at z < 0.08, and the fact that our dwarf morphological classes show similar local density, suggests that featureless dwarfs in low-density environments are created via internal baryonic feedback, rather than by environmental processes. Finally, while interacting dwarfs can be identified using the asymmetry parameter, it is challenging to cleanly separate early and late-type dwarfs using traditional morphological parameters, such as ‘CAS’, M20, and the Gini coefficient (unlike in the massive-galaxy regime).

Deep learning-based optical coherence tomography angiography image construction using spatial vascular connectivity network

Optical coherence tomography angiography (OCTA) provides unrivaled capability for depth-resolved visualization of retinal vasculature at the microcapillary level resolution. For OCTA image construction, repeated OCT scans from one location are required to identify blood vessels with active blood flow. The requirement for multi-scan-volumetric OCT can reduce OCTA imaging speed, which will induce eye movements and limit the image field-of-view. In principle, the blood flow should also affect the reflectance brightness profile along the vessel direction in a single-scan-volumetric OCT. Here we report a spatial vascular connectivity network (SVC-Net) for deep learning OCTA construction from single-scan-volumetric OCT. We quantitatively determine the optimal number of neighboring B-scans as image input, we compare the effects of neighboring B-scans to single B-scan input models, and we explore different loss functions for optimization of SVC-Net. This approach can improve the clinical implementation of OCTA by improving transverse image resolution or increasing the field-of-view.

Diagnosing osteoporosis using deep neural networkassisted optical image processing method

Diagnosing osteoporosis using deep neural networkassisted optical image processing method

An almost dark galaxy with the mass of the Small Magellanic Cloud

Almost dark galaxies are objects that have eluded detection by traditional surveys such as the Sloan Digital Sky Survey (SDSS). The low surface brightness of these galaxies (μr(0) > 26 mag arcsec−2), and hence their low surface stellar mass density (a few solar masses per pc2 or less), suggest that the energy density released by baryonic feedback mechanisms is inefficient in modifying the distribution of the dark matter halos they inhabit. For this reason, almost dark galaxies are particularly promising for probing the microphysical nature of dark matter. In this paper, we present the serendipitous discovery of Nube, an almost dark galaxy with ⟨μV⟩e ∼ 26.7 mag arcsec−2. The galaxy was identified using deep optical imaging from the IAC Stripe82 Legacy Project. Follow-up observations with the 100 m Green Bank Telescope strongly suggest that the galaxy is at a distance of 107 Mpc. Ultra-deep multi-band observations with the 10.4 m Gran Telescopio Canarias favour an age of ∼10 Gyr and a metallicity of [Fe/H] ∼ −1.1. With a stellar mass of ∼4 × 108 M⊙ and a half-mass radius of Re = 6.9 kpc (corresponding to an effective surface density of ⟨Σ⟩e ∼ 0.9 M⊙ pc−2), Nube is the most massive and extended object of its kind discovered so far. The galaxy is ten times fainter and has an effective radius three times larger than typical ultradiffuse galaxies with similar stellar masses. Galaxies with comparable effective surface brightness within the Local Group have very low mass (tens of 105 M⊙) and compact structures (effective radius Re < 1 kpc). Current cosmological simulations within the cold dark matter scenario, including baryonic feedback, do not reproduce the structural properties of Nube. However, its highly extended and flattened structure is consistent with a scenario where the dark matter particles are ultralight axions with a mass of mB = (0.8−0.2+0.4) × 10−23 eV.

GeoAI Dataset for Training Deep Learning-Based Optical Satellite Image Matching Model

Satellite imagery is being used to monitor the Earth, as it allows for the continuous provision of multi-temporal observations with consistent quality. To analyze time series remote sensing data with high accuracy, the process of image registration must be conducted beforehand. Image registration techniques are mainly divided into region-based registration and feature-based registration, and both techniques extract the same points based on the similarity of spectral characteristics and object shapes between master and slave images. In addition, recently, deep learning-based siamese neural network and convolutional neural network models have been utilized to match images. This has high performance compared to previous non-deep learning algorithms, but a very large amount of data is required to train a deep learning-based image registration model. In this study, we aim to generate a dataset for training a deep learning-based optical image registration model. To build the data, we acquired Satellite Side-Looking (S2Looking) data, an open dataset, and performed preprocessing and data augmentation on the data to create input data. After that, we added offsets to the X and Y directions between the master and slave images to create label data. The preprocessed input data and labeled data were used to build a dataset suitable for image registration. The data is expected to be useful for training deep learning-based satellite image registration models.

A multiwavelength study of spiral structure in galaxies. II. Spiral arms in deep optical observations

ABSTRACT In this paper, we look to analyse the spiral features of grand-design, multiarmed, and flocculent spiral galaxies using deep optical imaging from DESI Legacy Imaging Surveys. We explore the resulting distributions of various characteristics of spiral structure beyond the optical radius, such as the distributions of azimuthal angle, the extent of spiral arms, and of the spiral arm widths for the aforementioned galaxy classes. We also compare the measured properties for isolated galaxies and galaxies in groups and clusters. We find that, on average, compared to multiarmed and flocculent spiral galaxies, the spiral arms of grand-design galaxies exhibit slightly larger azimuthal angles, greater extent, and larger widths in the periphery of the galaxy. Furthermore, on average, isolated galaxies tend to have slightly smaller widths of outer spiral arms compared to galaxies in tight environments, which is likely related to the tidally induced mechanism for generating wider outer spiral arms. We also report that breaks of the disc surface brightness profiles are often related to the truncation of spiral arms in galaxies.

Human selection bias drives the linear nature of the more ground truth effect in explainable deep learning optical coherence tomography image segmentation.

Supervised deep learning (DL) algorithms are highly dependent on training data for which human graders are assigned, for example, for optical coherence tomography (OCT) image annotation. Despite the tremendous success of DL, due to human judgment, these ground truth labels can be inaccurate and/or ambiguous and cause a human selection bias. We therefore investigated the impact of the size of the ground truth and variable numbers of graders on the predictive performance of the same DL architecture and repeated each experiment three times. The largest training dataset delivered a prediction performance close to that of human experts. All DL systems utilized were highly consistent. Nevertheless, the DL under-performers could not achieve any further autonomous improvement even after repeated training. Furthermore, a quantifiable linear relationship between ground truth ambiguity and the beneficial effect of having a larger amount of ground truth data was detected and marked as the more-ground-truth effect.

Lanthanide doped NaYF4 core@multi-shell nanoparticles: Synthetic strategy for emission in divergent spectral regions

We present the use of lanthanide doped NaYF4 based core@multiple-shell nanoparticles as optical materials showing merged possibilities of engineered photon management processes. We have successfully synthesized and characterized series of NaYF4 core@shell@shell@shell nanomaterials in which the core parts were doped with NIR absorbing/emitting lanthanides (i.e., Nd3+, Yb3+, and Tm3+) to benefit from the complete separation of peristatic quenching processes connected to the interaction with solvent and/or ligand molecules. Followed by covering with an inert shell, Pr3+ ions were doped for VIS-to-UVC up-conversion in the next layer , and finally covered with yet another un-doped protecting shell. The obtained materials were characterized by the means of morphology, crystal structure and spectroscopic properties, with the emphasis put on the measurements in the UVC and NIR spectral regions. The obtained results showed the interesting possibility of merging within designed nanoparticles architectures both UVC light generation for future therapeutic purposes and NIR emission for deep tissue optical imaging diagnostics.

Photometric Selection of Unobscured QSOs at the Ecliptic Poles: KMTNet in the South Field and Pan-STARRS in the North Field

We search for quasi-stellar objects (QSOs) in a wide area of the south ecliptic pole (SEP) field, which has been and will continue to be intensively explored through various space missions. For this purpose, we obtain deep broadband optical images of the SEP field covering an area of ∼14.5 × 14.5 deg2 with the Korea Microlensing Telescope Network (KMTNet). The 5σ detection limits for point sources in the BVRI bands are estimated to be ∼22.59, 22.60, 22.98, and 21.85 mag, respectively. Utilizing data from the Wide-field Infrared Survey Explorer, unobscured QSO candidates are selected among the optically pointlike sources using mid-infrared (MIR) and optical–MIR colors. To refine our selection further and eliminate any contamination not adequately removed by the color-based selection, we perform spectral energy distribution fitting with archival photometric data ranging from optical to MIR. As a result, we identify a total of 2383 unobscured QSO candidates in the SEP field. We also apply a similar method to the north ecliptic pole field using Pan-STARRS data and obtain a similar result of identifying 2427 candidates. The differential number count per area of our QSO candidates is in good agreement with those measured from spectroscopically confirmed ones in other fields. Finally, we compare the results with the literature and discuss how this work will impact future studies, especially upcoming space missions.

Deep optical imaging of star-forming blue early-type galaxies

Blue early-type galaxies with galaxy-scale ongoing star formation are interesting targets in order to understand the stellar mass buildup in elliptical and S0 galaxies in the local Universe. We study the star-forming population of blue early-type galaxies to understand the origin of star formation in these otherwise red and dead stellar systems. The legacy survey imaging data taken with the dark energy camera in the g, r, and z bands for 55 star-forming blue early-type galaxies were examined, and g − r color maps were created. We identified low surface brightness features near 37 galaxies, faint-level interaction signatures near 15 galaxies, and structures indicative of recent merger activity in the optical color maps of all 55 galaxies. These features are not visible in the shallow Sloan Digital Sky Survey imaging data in which these galaxies were originally identified. Low surface brightness features found around galaxies could be remnants of recent merger events. The star-forming population of blue early-type galaxies could be post-merger systems that are expected to be the pathway for the formation of elliptical galaxies. We hypothesize that the star-forming population of blue early-type galaxies is a stage in the evolution of early-type galaxies. The merger features will eventually disappear, fuel for star formation will cease, and the galaxy will move to the passive population of normal early-type galaxies.

RASS-MCMF: a full-sky X-ray selected galaxy cluster catalogue

ABSTRACT We present the RASS-MCMF catalogue of 8449 X-ray selected galaxy clusters over 25 000 deg2 of extragalactic sky. The accumulation of deep multiband optical imaging data, the development of the Multi-Component Matched Filter (MCMF) cluster confirmation algorithm, and the release of the DESI Legacy Survey DR10 catalogue makes it possible – for the first time, more than 30 yr after the launch of the ROSAT X-ray satellite – to identify the majority of the galaxy clusters detected in the second ROSAT All-Sky-Survey (RASS) source catalogue (2RXS). The resulting 90 per cent pure RASS-MCMF catalogue is the largest intracluster medium (ICM)-selected cluster sample to date. RASS-MCMF probes a large dynamic range in cluster mass spanning from galaxy groups to the most massive clusters. The cluster redshift distribution peaks at $z$ ∼ 0.1 and extends to redshifts $z$ ∼ 1. Out to $z$ ∼ 0.4, the RASS-MCMF sample contains more clusters per redshift interval (dN/dz) than any other ICM-selected sample. In addition to the main sample, we present two subsamples with 6912 and 5506 clusters, exhibiting 95 per cent and 99 per cent purity, respectively. We forecast the utility of the sample for a cluster cosmological study, using realistic mock catalogues that incorporate most observational effects, including the X-ray exposure time and background variations, the existence likelihood selection and the impact of the optical cleaning with the algorithm MCMF. Using realistic priors on the observable–mass relation parameters from a DES-based weak lensing analysis, we estimate the constraining power of the RASS-MCMF×DES sample to be of 0.026, 0.033, and 0.15 (1σ) on the parameters Ωm, σ8, and $w$, respectively.