Large-scale Velocity Field Research Articles

The Formation of Filaments and Dense Cores in the Cocoon Nebula (IC 5146)

We present 850 μm linear polarization and C18O (3 − 2) and 13CO (3 − 2) molecular line observations toward the filaments (F13 and F13S) in the Cocoon Nebula (IC 5146) using the JCMT POL-2 and Heterodyne Array Receiver Program instruments. F13 and F13S are found to be thermally supercritical with identified dense cores along their crests. Our findings include that the polarization fraction decreases in denser regions, indicating reduced dust grain alignment efficiency. The magnetic field vectors at core scales tend to be parallel to the filaments, but disturbed at the high density regions. Magnetic field strengths measured using the Davis–Chandrasekhar–Fermi method are 58 ± 31 and 40 ± 9 μG for F13 and F13S, respectively, and it reveals subcritical and sub-Alfvénic filaments, emphasizing the importance of magnetic fields in the Cocoon region. Sinusoidal C18O (3 − 2) velocity and density distributions are observed along the filaments’ skeletons, and their variations are mostly displaced by ∼1/4 × the wavelength of the sinusoid, indicating core formation occurred through the fragmentation of a gravitationally unstable filament, but with shorter core spacings than predicted. Large-scale velocity fields of F13 and F13S, studied using 13CO (3 − 2) data, present a V-shape transverse velocity structure. We propose a scenario for the formation and evolution of F13 and F13S, along with the dense cores within them. A radiation shock front generated by a B-type star collided with a sheet-like cloud about 1.4 Myr ago. The filaments became thermally critical due to mass infall through self-gravity ∼1 Myr ago, and subsequently, dense cores formed through gravitational fragmentation, accompanied by the disturbance of the magnetic field.

Global POD Modes From PIV Asynchronous Patches

A method is proposed to obtain full-domain spatial modes based on Proper Orthogonal Decomposition (POD) of Particle Image Velocimetry (PIV) measurements performed at different (overlapping) spatial locations. When performing robotic volumetric Particle Image Velocimetry (PIV) (Jux et al., 2018), the large-scale mean velocity fields are estimated merging several measurements performed at different (adjacent) locations covered by the robot sequence. The proposed methodology leverages the definition of POD modes as eigenvectors of the spatial correlation matrix to obtain also large-scale modes. Performing measurements over overlapping (50-75%) regions allows to approximate the correlation matrix in the two adjacent domains. When applied over a sequence of views, this method has the potential to deliver full-domain POD modes spanning the volume covered by the robot sequence, even if different regions are covered asynchronously. This methodology is particularly well-suited for applications that seek to investigate large-scale flow structures, whenever the dynamic spatial range (DSR) of the measurement system does not allow to capture the whole domain at once. The methodology is validated using a 2D experimental dataset of a turbulent boundary layer, where patches are artificially created from splitting the PIV measurements, later used as ground truth to assess the results. Furthermore, we apply the technique to a 3D robotic volumetric PIV experiment of the flow around a wall-mounted cube.

Approximations for the divergence of the reconstructed local large-scale structure velocity field and its possible implications for Cosmology

We characterize the peculiar velocity field of the local large-scale structure reconstructed from the 2M++ survey, by treating it as a fluid, extracting the divergence via different approximations over a range of averaged scales. This reconstructed field is important for cosmology, since it was used to correct the peculiar redshifts of the last SNIA compilation Pantheon+. The results have intriguing implications for the LLSS fluid dynamics and particularly for the “Tilted Cosmology” model, although those results have to be taken carefully as the velocity field could contain significant bias due to the reconstruction procedure. Those possible bias and its influence in our results are discussed. Representative values of the apparent deceleration parameter (q̃) are computed, in order to compare our results with the theoretical predictions of the tilted-universe scenario. We conclude that better velocity field reconstructions are necessary in order to constrain the parameters implied in LLSS research and alternative cosmologies.

The large-scale velocity field from the Cosmicflows-4 data

ABSTRACT The reconstruction of the large-scale velocity field from the grouped Cosmicflows-4 (CF4) database is presented. The lognormal bias of the inferred distances and velocities data is corrected by the Bias Gaussianization correction scheme, and the linear density and velocity fields are reconstructed by means of the Wiener filter and constrained realizations (CRs) algorithm. These tools are tested against a suite of random and constrained Cosmicflows-3-like mock data. The CF4 data consist of three main subsamples – the 6dFGS and the SDSS data – and the ‘others’. The individual contributions of the subsamples have been studied. The quantitative analysis of the velocity field is done mostly by the mean overdensity (ΔL(R)) and the bulk velocity (Vbulk(R)) profiles of the velocity field out to $300\, {{h^{-1}\, {\rm Mpc}}}$. The Vbulk(R) and ΔL(R) profiles of the CF4 data without its 6dFGS component are consistent with the cosmic variance to within 1σ. The 6dFGS sample dominates the Vbulk (ΔL) profile beyond $\sim 120\, {{h^{-1}\, {\rm Mpc}}}$, and drives it to roughly a 3.4σ (−1.9σ) excess (deficiency) relative to the cosmic variance at $R\sim 250\ (190)\ \, {{h^{-1}\, {\rm Mpc}}}$. The excess in the amplitude of Vbulk is dominated by its Supergalactic X component, roughly in the direction of the Shapley Concentration. The amplitude and alignment of the inferred velocity field from the CF4 data are at $\sim (2{-}3)\, \sigma$ discrepancy with respect to the Lambda cold dark matter model. Namely, it is somewhat atypical but yet there is no compelling tension with the model.

On the 3D Curvature and Dynamics of the Musca Filament

Filaments are ubiquitous in the interstellar medium, yet their formation and evolution remain the topic of intense debate. In order to obtain a more comprehensive view of the 3D morphology and evolution of the Musca filament, we model the C18O(2-1) emission along the filament crest with several large-scale velocity field structures. This indicates that Musca is well described by a 3D curved cylindrical filament with longitudinal mass inflow to its center unless the filament is a transient structure with a lifetime ≲0.1 Myr. Gravitational longitudinal collapse models of filaments appear unable to explain the observed velocity field. To better understand these kinematics, we further analyze a map of the C18O(2-1) velocity field at the location of SOFIA HAWC+ dust polarization observations that trace the magnetic field in the filament. This unveils an organized magnetic field that is oriented roughly perpendicular to the filament crest. Although the velocity field is also organized, it progressively changes its orientation by more than 90° when laterally crossing the filament crest and thus appears disconnected from the magnetic field in the filament. This strong lateral change of the velocity field over the filament remains unexplained and might be associated with important longitudinal motion that can be associated to the large-scale kinematics along the filament.

Large-scale density and velocity field reconstructions with neural networks

ABSTRACT We assess a neural network (NN) method for reconstructing 3D cosmological density and velocity fields (target) from discrete and incomplete galaxy distributions (input). We employ second-order Lagrangian Perturbation Theory to generate a large ensemble of mock data to train an auto-encoder (AE) architecture with a Mean Squared Error (MSE) loss function. The AE successfully captures non-linear features arising from gravitational dynamics and the discreteness of the galaxy distribution. It preserves the positivity of the reconstructed density field and exhibits a weaker suppression of the power on small scales than the traditional linear Wiener filter (WF), which we use as a benchmark. In the density reconstruction, the reduction of the AE MSE relative to the WF is $\sim 15~{{\ \rm per\ cent}}$ , whereas for the velocity reconstruction a relative reduction of up to a factor of two can be achieved. The AE is advantageous to the WF at recovering the distribution of the target fields, especially at the tails. In fact, trained with an MSE loss, any NN estimate approaches the unbiased mean of the underlying target given the input. This implies a slope of unity in the linear regression of the true on the NN-reconstructed field. Only for the special case of Gaussian fields, the NN and WF estimates are equivalent. Nonetheless, we also recover a linear regression slope of unity for the WF with non-Gaussian fields.

Velocity reconstruction with the cosmic microwave background and galaxy surveys

The kinetic Sunyaev Zel'dovich (kSZ) and moving lens effects, secondary contributions to the cosmic microwave background (CMB), carry significant cosmological information due to their dependence on the large-scale peculiar velocity field. Previous work identified a promising means of extracting this cosmological information using a set of quadratic estimators for the radial and transverse components of the velocity field. These estimators are based on the statistically anisotropic components of the cross-correlation between the CMB and a tracer of large scale structure, such as a galaxy redshift survey. In this work, we assess the challenges to the program of velocity reconstruction posed by various foregrounds and systematics in the CMB and galaxy surveys, as well as biases in the quadratic estimators. To do so, we further develop the quadratic estimator formalism and implement a numerical code for computing properly correlated spectra for all the components of the CMB (primary/secondary blackbody components and foregrounds) and a photometric redshift survey, with associated redshift errors, to allow for accurate forecasting. We create a simulation framework for generating realizations of properly correlated CMB maps and redshift binned galaxy number counts, assuming the underlying fields are Gaussian, and use this to validate a velocity reconstruction pipeline and assess map-based systematics such as masking. We highlight the most significant challenges for velocity reconstruction, which include biases associated with: modelling errors, characterization of redshift errors, and coarse graining of cosmological fields on our past light cone. Despite these challenges, the outlook for velocity reconstruction is quite optimistic, and we use our reconstruction pipeline to confirm that these techniques will be feasible with near-term CMB experiments and photometric galaxy redshift surveys.

Testing Bayesian reconstruction methods from peculiar velocities

ABSTRACT Reconstructing the large-scale density and velocity fields from surveys of galaxy distances is a major challenge for cosmography. The data are very noisy and sparse. Estimated distances, and thereby peculiar velocities, are strongly affected by the Malmquist-like lognormal bias. Two algorithms have been recently introduced to perform reconstructions from such data: the Bias Gaussian correction coupled with the Wiener filter (BGc/WF) and the Hamlet implementation of the Hamiltonian Monte Carlo forward modelling. The two methods are tested here against mock catalogues that mimic the Cosmicflows-3 data. Specifically the reconstructed cosmography and moments of the velocity field (monopole, dipole) are examined. A comparison is made to the ‘exact’ WF as well, namely, the WF in the unrealistic case of zero observational errors. This is to understand the limits of the WF method. The following is found. In the nearby regime ($d \lesssim 40 \, \mathrm{ \mathit{ h}}^{-1}\, {\rm Mpc}$), the two methods perform roughly equally well. Hamlet shows more contrast in the intermediate regime ($40 \lesssim d \lesssim 120 \, h^{-1}\, {\rm Mpc}$). The main differences between the two appear in the most distant regime ($d \gtrsim 120 \, h^{-1}\, {\rm Mpc}$), close to the edge of the data. Hamlet outperforms the BGc/WF in terms of contrast and tighter correlations of the density and velocity fields. Yet, close to the edge of the data, Hamlet yields a slightly biased reconstruction, which affects the multipoles of the velocity field. Such biases are missing from the BGc/WF reconstruction. In sum, both methods perform well and create reliable reconstructions with significant differences apparent when details are examined.

Influence of Synthetic Jets on Multiscale Features in Wall-Bounded Turbulence

This experimental research focuses on the impacts of submerged synthetic jets on a fully-developed turbulent boundary layer (TBL) under a drag reduction working case. Two-dimensional velocity vectors in the flow field are captured with the aid of a particle image velocimetry (PIV) system. Proper orthogonal decomposition (POD) analyses provide evidence that synthetic jets notably attenuate the induction effect of prograde vortex on the low-speed fluid in large-scale fluctuation velocity field, thereby weakening the bursting process of near-wall turbulent events. Furthermore, the introduced perturbance redistributes the turbulent kinetic energy (TKE) and concentrates the TKE onto small-scale coherent structures. Modal time coefficients in various orders of POD are divided into components of multiple frequency bands by virtue of complementary ensemble empirical mode decomposition (CEEMD). It is found that the turbulence signals are shifted from low-frequency to high-frequency bands thanks to synthetic jets, thus revealing the relationship between scales and frequency bands. One further method of scale decomposition is proposed, that is, the large-scale fluctuating flow field will be obtained after removing the high-frequency noise data with the help of continuous mean square error (CMSE) criterion.

Hamiltonian Monte Carlo reconstruction from peculiar velocities

ABSTRACTThe problem of the reconstruction of the large-scale density and velocity fields from peculiar velocity surveys is addressed here within a Bayesian framework by means of Hamiltonian Monte Carlo (HMC) sampling. The HAmiltonian Monte carlo reconstruction of the Local EnvironmenT (hamlet) algorithm is designed to reconstruct the linear large-scale density and velocity fields in conjunction with the undoing of lognormal bias in the derived distances and velocities of peculiar velocity surveys, such as the Cosmicflows (CF) data. The hamlet code has been tested against CF mock catalogues consisting of up to 3 × 104 data points with mock errors akin to those of the Cosmicflows-3 (CF3) data, within the framework of the Lambda cold dark matter standard model of cosmology. The hamlet code outperforms previous applications of Gibbs sampling Markov chain Monte Carlo reconstruction from the CF3 data by two to four orders of magnitude in CPU time. The gain in performance is due to the inherent higher efficiency of the HMC algorithm and due to parallel computing on GPUs rather than CPUs. This gain will enable an increase in the reconstruction of the large-scale structure from the upcoming CF4 data and the setting of constrained initial conditions for cosmological high-resolution simulations.

Relationship between the base pressure and the velocity in the near-wake of an Ahmed body

We investigate the joint dynamics of the near-wake velocity and the base pressure of a square back Ahmed body. We identify two modes that are responsible for most of the pressure drag variations. We show that the turbulent large-scale velocity field in the wake can be recovered from base pressure measurements.

Drag decomposition of laminar channel flows developing over convergent–divergent riblets

Convergent–divergent (C–D) riblets are known to induce large-scale secondary flow motion in laminar flow that may point to their potential for flow separation control and heat transfer enhancement. In this paper, a fully-developed pressure-driven laminar channel flow with C–D riblets is studied numerically. The effects of Reynolds number, riblet wavelength and riblet cross-sectional shape on the secondary flow and drag characteristics are investigated. An exact expression for the drag coefficient of this flow is derived based on the balance of kinetic energy principle for a rough-wall channel. Furthermore, the triple decomposition technique is used to identify the contribution to drag production from the mean velocity field, the small- and large-scale dispersive flow field. Our results show that the normalized drag increment starts to rise when the secondary flow begins to alter the velocity field across the span as the Reynolds number based on the channel height (ReH) increases above 100, a behavior which is very different from that of a laminar channel flow developing over homogeneous roughness in which the normalized drag increment is found to remain constant up to a much greater Reynolds number due to an absence of secondary flow. It is found that the drag produced by C–D riblets is predominantly caused by the wall-normal gradient of streamwise velocity. In addition, while the drag increment is predominantly caused by the mean and small-scale dispersive velocity at ReH≤100, the contribution from the large-scale dispersive velocity field increases rapidly with the Reynolds number and becomes dominant as ReH exceeds 400. It is also observed that the secondary flow scales with the riblet wavelength Λ, and its swirling strength peaks around Λ=1.25H, which is accompanied by a drag maxima at ReH≥400. Finally, among the three C–D riblet cross-sectional shape (rectangular, triangular and sinusoidal) examined here, the triangular riblet pattern is found to produce a secondary motion with a similar strength to the other two shapes but with less drag penalty.

Erratum: Prospects for detection and application of the alignment of galaxies with the large-scale velocity field [Phys. Rev. D 102 , 123507 (2020)

Received 12 August 2021DOI:https://doi.org/10.1103/PhysRevD.104.069902© 2021 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasCosmologyLarge scale structure of the UniversePhysical SystemsGalaxiesGravitation, Cosmology & Astrophysics

Correlation between Large-Scale Streamwise Velocity Features and the Height of Coherent Vortices in a Turbulent Boundary Layer

The preferential organisation of coherent vortices in a turbulent boundary layer in relation to local large-scale streamwise velocity features was investigated. Coherent vortices were identified in the wake region using the Triple Decomposition Method (originally proposed by Kolář) from 2D particle image velocimetry (PIV) data of a canonical turbulent boundary layer. Two different approaches, based on conditional averaging and quantitative statistical analysis, were used to analyze the data. The large-scale streamwise velocity field was first conditionally averaged on the height of the detected coherent vortices and a change in the sign of the average large scale streamwise fluctuating velocity was seen depending on the height of the vortex core. A correlation coefficient was then defined to quantify this relationship between the height of coherent vortices and local large-scale streamwise fluctuating velocity. Both of these results indicated a strong negative correlation in the wake region of the boundary layer between vortex height and large-scale velocity. The relationship between vortex height and full large-scale velocity isocontours was also studied and a conceptual model based on the findings of the study was proposed. The results served to relate the hairpin vortex model of Adrian et al. to the scale interaction results reported by Mathis et al., and Chung and McKeon.

Experimental investigation on drag reduction in a turbulent boundary layer with a submerged synthetic jet

This work investigates the active control of a fully developed turbulent boundary layer by a submerged synthetic jet actuator. The impacts of the control are explored by measuring the streamwise velocities using particle image velocimetry, and reduction of the skin-friction drag is observed in a certain range downstream of the orifice. The coherent structure is defined and extracted using a spatial two-point correlation function, and it is found that the synthetic jet can efficiently reduce the streamwise scale of the coherent structure. Proper orthogonal decomposition analysis reveals that large-scale turbulent kinetic energy is significantly attenuated with the introduction of a synthetic jet. The conditional averaging results show that the induction effect of the prograde vortex on the low-speed fluid in a large-scale fluctuation velocity field is deadened, thereby suppressing the bursting process near the wall.

Proca-stinated cosmology. Part II. Matter, halo, and lensing statistics in the vector Galileon

The generalised Proca (GP) theory is a modified gravity model in which the acceleration of the cosmic expansion rate can be explained by self interactions of a cosmological vector field. In this paper we study a particular sub-class of the GP theory, with up to cubic order Lagrangian, known as the cubic vector Galileon (cvG) model. This model is similar to the cubic scalar Galileon (csG) in many aspects, including a fifth force and the Vainshtein screening mechanism, but with the additional flexibility that the strength of the fifth force depends on an extra parameter — interpolating between zero and the full strength of the csG model — while the background expansion history is independent of this parameter. It offers an interesting alternative to ΛCDM in explaining the cosmic acceleration, as well as a solution to the tension between early- and late-time measurements of the Hubble constant H 0. To identify the best ways to test this model, in this paper we conduct a comprehensive study of the phenomenology of this model in the nonlinear regime of large-scale structure formation, using a suite of N-body simulations run with the modified gravity code ECOSMOG. By inspecting thirteen statistics of the dark matter field, dark matter haloes and weak lensing maps, we find that the fifth force in this model can have particularly significant effects on the large-scale velocity field and lensing potential at late times, which suggest that redshift-space distortions and weak lensing can place strong constraints on it.

Sinking microplastics in the water column: simulations in the Mediterranean Sea

Abstract. We study the vertical dispersion and distribution of negatively buoyant rigid microplastics within a realistic circulation model of the Mediterranean sea. We first propose an equation describing their idealized dynamics. In that framework, we evaluate the importance of some relevant physical effects (inertia, Coriolis force, small-scale turbulence and variable seawater density), and we bound the relative error of simplifying the dynamics to a constant sinking velocity added to a large-scale velocity field. We then calculate the amount and vertical distribution of microplastic particles on the water column of the open ocean if their release from the sea surface is continuous at rates compatible with observations in the Mediterranean. The vertical distribution is found to be almost uniform with depth for the majority of our parameter range. Transient distributions from flash releases reveal a non-Gaussian character of the dispersion and various diffusion laws, both normal and anomalous. The origin of these behaviors is explored in terms of horizontal and vertical flow organization.

Large-scale peculiar velocity fields: Newtonian vs relativistic treatment

We employ a perturbative analysis to study the evolution of large-scale peculiar velocity fields within the framework of Newtonian gravity and then compare our results to those of the corresponding relativistic treatment. In so doing, we use the same mathematical formalism and apply the same physical approach. This facilitates a direct and transparent comparison between the two treatments. Our study recovers and extends the familiar Newtonian results on the one hand, while on the other it shows that the Newtonian analysis leads to substantially weaker growth-rates for the peculiar velocity field, compared to the relativistic approach. This implies that, by using Newton's rather than Einstein's theory, one could seriously underestimate the overall kinematic evolution of cosmological peculiar motions. We are also in the position to identify the reason the two theories arrive at such considerably different results and conclusions.

Prospects for detection and application of the alignment of galaxies with the large-scale velocity field

Studies of intrinsic alignment effects mostly focus on the correlations between the shapes of galaxies with each other or with the underlying density field of the large scale structure of the Universe. Lately, the correlation between the shapes of galaxies and the large-scale velocity field has been proposed as an additional probe of the large scale structure. We use a Fisher forecast to make a prediction for the detectability of this velocity-shape correlation with a combination of redshifts and shapes from the $4\mathrm{MOST}+\mathrm{LSST}$ surveys, and radial velocity reconstruction from the Simons Observatory. The signal-to-noise ratio for the velocity-shape (dipole) correlation is 23, relative to 44 for the galaxy density-shape (monopole) correlation and for a maximum wave number of $0.2\text{ }\text{ }\text{Mp}{\mathrm{c}}^{\ensuremath{-}1}$. Increasing the signal-to-noise ratio for higher values of the maximum wave numbers (respectively, 56 and 69, for a maximum wave number of $1\text{ }\text{ }\text{Mp}{\mathrm{c}}^{\ensuremath{-}1}$) indicate potential gains in the nonlinear regime. Encouraged by these predictions, we discuss two possible applications for the velocity-shape correlation. Measuring the velocity-shape correlation could improve the mitigation of selection effects induced by intrinsic alignments on galaxy clustering. We also find that velocity-shape measurements could potentially aid in determining the scale dependence of intrinsic alignments when multiple shape measurements of the same galaxies are provided.

What Is the Price of Abandoning Dark Matter? Cosmological Constraints on Alternative Gravity Theories.

Any successful alternative gravity theory that obviates the need for dark matter must fit our cosmological observations. Measurements of microwave background polarization trace the large-scale baryon velocity field at recombination and show very strong O(1) baryon acoustic oscillations. Measurements of the large-scale structure of galaxies at low redshift show much weaker features in the spectrum. If the alternative gravity theory's dynamical equations for the growth rate of structure are linear, then the density field growth can be described by a Green's function: δ(x[over →],t)=δ(x[over →],t^{'})G(x,t,t^{'}). We show that the Green's function G(x,t,t^{'}) must have dramatic features that erase the initial baryon oscillations. This implies an acceleration law that changes sign on the ∼150 Mpc scale. On the other hand, if the alternative gravity theory has a large nonlinear term that couples modes on different scales, then the theory would predict large-scale non-Gaussian features in large-scale structure. These are not seen in the distribution of galaxies nor in the distribution of quasars. No proposed alternative gravity theory for dark matter seems to satisfy these constraints.