Redshift-space Galaxy Research Articles

Estimation of line-of-sight velocities of individual galaxies using neural networks – I. Modelling redshift–space distortions at large scales

ABSTRACT We present a scheme based on artificial neural networks (ANNs) to estimate the line-of-sight velocities of individual galaxies from an observed redshift–space galaxy distribution. We find an estimate of the peculiar velocity at a galaxy based on galaxy counts and barycentres in shells around it. By training the network with environmental characteristics, such as the total mass and mass centre within each shell surrounding every galaxy in redshift space, our ANN model can accurately predict the line-of-sight velocity of each individual galaxy. When this velocity is used to eliminate the RSD effect, the two-point correlation function (TPCF) in real space can be recovered with an accuracy better than 1 per cent at s > 8 $\, h^{-1}\, \mathrm{Mpc}$, and 4 per cent on all scales compared to ground truth. The real-space power spectrum can be recovered within 3 per cent on k< 0.5 $\, \mathrm{Mpc}^{-1}\, h$, and less than 5 per cent for all k modes. The quadrupole moment of the TPCF or power spectrum is almost zero down to s = 10 $\, h^{-1}\, \mathrm{Mpc}$ or all k modes, indicating an effective correction of the spatial anisotropy caused by the RSD effect. We demonstrate that on large scales, without additional training with new data, our network is adaptable to different galaxy formation models, different cosmological models, and mock galaxy samples at high-redshifts and high biases, achieving less than 10 per cent error for scales greater than 15 $\, h^{-1}\, \mathrm{Mpc}$. As it is sensitive to large-scale densities, it does not manage to remove Fingers of God in large clusters, but works remarkably well at recovering real-space galaxy positions elsewhere. Our scheme provides a novel way to predict the peculiar velocity of individual galaxies, to eliminate the RSD effect directly in future large galaxy surveys, and to reconstruct the three-dimensional cosmic velocity field accurately.

The one-loop bispectrum of galaxies in redshift space from the Effective Field Theory of Large-Scale Structure

We derive the Effective Field Theory of Large-Scale Structure kernels and counterterms for the one-loop bispectrum of dark matter and of biased tracers in real and redshift space. This requires the expansion of biased tracers up to fourth order in fluctuations. In the process, we encounter several subtleties related to renormalization. One is the fact that, in renormalizing the momentum, a local counterterm contributes non-locally. A second subtlety is related to the renormalization of local products of the velocity fields, which need to be expressed in terms of the renormalized velocity in order to preserve Galilean symmetry. We check that the counterterms we identify are necessary and sufficient to renormalize the one-loop bispectrum at leading and subleading order in the derivative expansion. The kernels that we originally present here have already been used for the first analyses of the one-loop bispectrum in BOSS data [1,2].

Cosmological constraints from the redshift-space galaxy skew spectra

Extracting the non-Gaussian information of the cosmic large-scale structure (LSS) is vital in unlocking the full potential of the rich datasets from the upcoming stage-IV galaxy surveys. Galaxy skew spectra serve as efficient beyond-two-point statistics, encapsulating essential bispectrum information with computational efficiency akin to power spectrum analysis. This paper presents the first cosmological constraints from analyzing the full set of redshift-space galaxy skew spectra of the data from the SDSS-III BOSS, accessing cosmological information down to nonlinear scales. Employing the forward modeling framework and simulation-based inference via normalizing flows, we analyze the CMASS-SGC subsample, which constitute approximately 10% of the full BOSS data. Analyzing the scales up to kmax=0.5 h−1 Mpc, we find that the skew spectra improve the constraints on Ωm,Ωb,h, and ns by 34%, 35%, 18%, 10%, respectively, compared to constraints from previous power spectrum multipoles analysis, yielding Ωm=0.288−0.034+0.024, Ωb=0.043−0.007+0.005, h=0.759−0.050+0.104, ns=0.918−0.090+0.041 (at 68% confidence limit). On the other hand, the constraints on σ8 are weaker than from the power spectrum. Including the big bang nucleosynthesis (BBN) prior on baryon density reduces the uncertainty on the Hubble parameter further, achieving h=0.750−0.032+0.034, which is a 38% improvement over the constraint from the power spectrum with the same prior. Compared to the bispectrum (monopole) analysis, skew spectra offer comparable constraints on larger scales (kmax<0.3 h−1 Mpc) for most parameters except for σ8. Published by the American Physical Society 2024

The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with AbacusSummit

ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 < z < 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

Galaxy clustering multi-scale emulation

Simulation-based inference has seen increasing interest in the past few years as a promising approach to modelling the non-linear scales of galaxy clustering. The common approach, using the Gaussian process, is to train an emulator over the cosmological and galaxy–halo connection parameters independently for every scale. We present a new Gaussian process model that allows the user to extend the input parameter space dimensions and to use a non-diagonal noise covariance matrix. We use our new framework to simultaneously emulate every scale of the non-linear clustering of galaxies in redshift space from the ABACUSSUMMITN-body simulations at redshift z = 0.2. The model includes nine cosmological parameters, five halo occupation distribution (HOD) parameters, and one scale dimension. Accounting for the limited resolution of the simulations, we train our emulator on scales from 0.3 h−1 Mpc to 60 h−1 Mpc and compare its performance with the standard approach of building one independent emulator for each scale. The new model yields more accurate and precise constraints on cosmological parameters compared to the standard approach. As our new model is able to interpolate over the scale space, we are also able to account for the Alcock-Paczynski distortion effect, leading to more accurate constraints on the cosmological parameters.

FkPT: constraining scale-dependent modified gravity with the full-shape galaxy power spectrum

Modified gravity models with scale-dependent linear growth typically exhibit an enhancement in the power spectrum beyond a certain scale. The conventional methods for extracting cosmological information usually involve inferring modified gravity effects via Redshift Space Distortions (RSD), particularly through the time evolution of fσ 8. However, classical galaxy RSD clustering analyses encounter difficulties in accurately capturing the spectrum's enhanced power, which is better obtained from the broad-band power spectrum. In this sense, full-shape analyses aim to consider survey data using comprehensive and precise models of the whole power spectrum. Yet, a major challenge in this approach is the slow computation of non-linear loop integrals for scale-dependent modified gravity, precluding the estimation of cosmological parameters using Markov Chain Monte Carlo methods. Based on recent studies, in this work we develop a perturbation theory tailored for Modified Gravity, or analogous scenarios introducing additional scales, such as in the presence of massive neutrinos. Our approach only needs the calculation of the scale-dependent growth rate f(k,t) and the limit of the perturbative kernels at large scales. We called this approximate technique as fk-Perturbation Theory and implemented it into the code fkpt, capable of computing the redshift space galaxy power spectrum in a fraction of a second. We validate our modeling and code with the f(R) theory MG-GLAM and General Relativity NSeries sets of simulations. The code is available at https://github.com/alejandroaviles/fkpt.

Cosmic Tidal Reconstruction in Redshift Space

Gravitational coupling between large- and small-scale density perturbations leads to anisotropic distortions to local small-scale matter fluctuations. Such local anisotropic distortions can be used to reconstruct large-scale matter distribution, known as tidal reconstruction. In this paper, we apply the tidal reconstruction methods to simulated galaxies in redshift space. We find that redshift-space distortions (RSDs) lead to anisotropic reconstruction results. While the reconstructed radial modes are more noisy mainly due to the small-scale velocity dispersion, the transverse modes are still reconstructed with high fidelity, and well correlated with the original large-scale density modes. The bias of the reconstructed field at large scales shows a simple angular dependence, which can be described by a form similar to that of the linear RSD. The noise power spectrum is nearly isotropic and scale independent on large scales. This makes the reconstructed tide fields an ideal tracer for cosmic variance cancellation and multi-tracer analysis and has profound implications for future 21 cm intensity mapping surveys.

Number count of gravitational waves and supernovae in luminosity distance space for ΛCDM and scalar-tensor theories

The clustering of gravitational waves in luminosity distance space is emerging as a promising probe of the growth of structure. Just like for galaxies, its observation is subject to a number of relativistic corrections that affect the measured signal and need to be accounted for when fitting theoretical models to the data. We derive the full expression for the number count of gravitational waves in luminosity distance space, including all relativistic corrections, in ΛCDM and in scalar-tensor theories with luminal propagation of tensors. We investigate the importance of each relativistic effect and the detectability of the total signal by current and planned GW detectors. We consider also supernovae in luminosity distance space, highlighting the differences with gravitational waves in the case of scalar-tensor theories. We carry out a thorough comparison among the number count of gravitational waves and supernovae in luminosity distance space, and that of galaxies in redshift space. We show how the relativistic corrections contain useful complementary information on the growth of perturbations and on the underlying theory of gravity, highlighting the synergy with other cosmological probes.

Efficiently evaluating loop integrals in the EFTofLSS using QFT integrals with massive propagators

We develop a new way to analytically calculate loop integrals in the Effective Field Theory of Large Scale-Structure. Previous available methods show severe limitations beyond the one-loop power spectrum due to analytical challenges and computational and memory costs. Our new method is based on fitting the linear power spectrum with cosmology-independent functions that resemble integer powers of quantum field theory massive propagators with complex masses. A remarkably small number of them is sufficient to reach enough accuracy. Similarly to former approaches, the cosmology dependence is encoded in the coordinate vector of the expansion of the linear power spectrum in our basis. We first produce cosmology-independent tensors where each entry is the loop integral evaluated on a given combination of basis vectors. For each cosmology, the evaluation of a loop integral amounts to contracting this tensor with the coordinate vector of the linear power spectrum. The 3-dimensional loop integrals for our basis functions can be evaluated using techniques familiar to particle physics, such as recursion relations and Feynman parametrization. We apply our formalism to evaluate the one-loop bispectrum of galaxies in redshift space. The final analytical expressions are quite simple and can be evaluated with little computational and memory cost. We show that the same expressions resolve the integration of all one-loop N-point function in the EFTofLSS. This method, which is originally presented here, has already been applied in the first one-loop bispectrum analysis of the BOSS data to constraint ΛCDM parameters and primordial non-Gaussianities [1, 2].

Cosmology inference at the field level from biased tracers in redshift-space

Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while robustly marginalizing over any astrophysical uncertainties. A pipeline in this spirit is implemented in the LEFTfield code, which we extend in this work to describe the clustering of galaxies in redshift space. Our main additions are: the computation of the velocity field in the LPT gravity model, the fully nonlinear displacement of the evolved, biased density field to redshift space, and a systematic expansion of velocity bias. We test the resulting analysis pipeline by applying it to synthetic data sets with a known ground truth at increasing complexity: mock data generated from the perturbative forward model itself, sub-sampled matter particles, and dark matter halos in N-body simulations. By fixing the initial-time density contrast to the ground truth, while varying the growth rate f, bias coefficients and noise amplitudes, we perform a stringent set of checks. These show that indeed a systematic higher-order expansion of the velocity bias is required to infer a growth rate consistent with the ground truth within errors. Applied to dark matter halos, our analysis yields unbiased constraints on f at the level of a few percent for a variety of halo masses at redshifts z = 0, 0.5, 1 and for a broad range of cutoff scales 0.08 h/Mpc≤ Λ ≤ 0.20 h/Mpc. Importantly, deviations between true and inferred growth rate exhibit the scaling with halo mass, redshift and cutoff that one expects based on the EFT of Large Scale Structure. Further, we obtain a robust detection of velocity bias through its effect on the redshift-space density field and are able to disentangle it from higher-derivative bias contributions.

Galaxy Clustering in the Mira-Titan Universe. I. Emulators for the Redshift Space Galaxy Correlation Function and Galaxy–Galaxy Lensing

We construct accurate emulators for the projected and redshift space galaxy correlation functions and excess surface density as measured by galaxy–galaxy lensing, based on halo occupation distribution modeling. Using the complete Mira-Titan suite of 111 N-body simulations, our emulators vary over eight cosmological parameters and include the effects of neutrino mass and dynamical dark energy. We demonstrate that our emulators are sufficiently accurate for the analysis of the Baryon Oscillation Spectroscopic Survey DR12 CMASS galaxy sample over the range 0.5 ≤ r ≤ 50 h −1 Mpc. Furthermore, we show that our emulators are capable of recovering unbiased cosmological constraints from realistic mock catalogs over the same range. Our mock catalog tests show the efficacy of combining small-scale galaxy–galaxy lensing with redshift space clustering and that we can constrain the growth rate and σ 8 to 7% and 4.5%, respectively, for a CMASS-like sample using only the measurements covered by our emulator. With the inclusion of a cosmic microwave background prior on H 0, this reduces to a 2% measurement of the growth rate.

The bacco simulation project: bacco hybrid Lagrangian bias expansion model in redshift space

ABSTRACT We present an emulator that accurately predicts the power spectrum of galaxies in redshift space as a function of cosmological parameters. Our emulator is based on a second-order Lagrangian bias expansion that is displaced to Eulerian space using cosmological N-body simulations. Redshift space distortions are then imprinted using the non-linear velocity field of simulated particles and haloes. We build the emulator using a forward neural network trained with the simulations of the BACCO project, which covers an eight-dimensional parameter space including massive neutrinos and dynamical dark energy. We show that our emulator provides unbiased cosmological constraints from the monopole, quadrupole, and hexadecapole of a mock galaxy catalogue that mimics the BOSS-CMASS sample down to non-linear scales ($k\sim 0.6{h\, {\rm Mpc}^{-1}}$). This work opens up the possibility of robustly extracting cosmological information from small scales using observations of the large-scale structure of the universe.

Consistent and simultaneous modelling of galaxy clustering and galaxy–galaxy lensing with subhalo abundance matching

ABSTRACT The spatial distribution of galaxies and their gravitational lensing signal offer complementary tests of galaxy formation physics and cosmology. However, their synergy can only be fully exploited if both probes are modelled accurately and consistently. In this paper, we demonstrate that this can be achieved using an extension of Sub-Halo Abundance Matching extended model (SHAMe), dubbed SHAMe. Specifically, we use mock catalogues built from the TNG300 hydrodynamical simulation to show that SHAMe can simultaneously model the multipoles of the redshift–space galaxy correlation function and galaxy–galaxy lensing, without noticeable bias within the statistical sampling uncertainties of a SDSS volume and on scales r ∈ [0.6 − 30]h−1 Mpc. Modelling the baryonic processes in galaxy–galaxy lensing with a baryonification scheme allows SHAMe’s range of validity to be extended to r ∈ [0.1 − 30] h−1 Mpc. Remarkably, our model achieves this level of precision with just five free parameters beyond those describing the baryonification model. At fixed cosmology, we find that galaxy–galaxy lensing provides a general consistency test but little additional information on galaxy modelling parameters beyond that encoded in the redshift-space multipoles. It does, however, improve constraints if only the projected correlation function is available, as in surveys with only photometric redshifts. We expect SHAMe to have a higher fidelity across a wider range of scales than more traditional methods such as Halo Occupation Distribution modelling. Thus it should provide a significantly more powerful and more robust tool for analysing next-generation large-scale surveys.

On Low Hubble Expansion Rate from Planck Data Anomalies

From the linear perturbations of Nash–Greene fluctuations of a background metric, we obtain profiles of Hubble function evolution H(z) and fσ8(z) measurements as compared with the ΛCDM results at intermediate redshifts 0.1<z<1. For parameter estimation, we use joint data from Planck Cosmic Microwave Background (CMB) likelihoods of CMB temperature and polarization angular power spectra, Barionic Acoustic Oscillations (BAO) and local measurements of Hubble constant H0 from the Hubble Space Telescope (HST). We analyze the stability of the effective Newtonian constant Geff and its agreement with Big Bang Nucleosynthesis (BBN) constraints. We show that our results are highly compatible with the ΛCDM paradigm, rather extending the perspective for further studies on redshift-space galaxy clustering data. Moreover, we obtain the CMB TT angular spectra with the Integrated Sachs–Wolfe (ISW) effect, which is weakened on low-l scales. The resulting linear matter power spectrum P(k) profile is also compatible with ΛCDM results but somewhat degenerate with an early dark energy (DE) contribution. Finally, posing a dilemma to the solution of Hubble tension, our results indicate a low Hubble expansion rate suggesting possible anomalies in Planck data in consonance with the recent South Pole Telescope (SPT-3G) data.

Studying large-scale structure probes of modified gravity with COLA

We study the effect of two Modified Gravity (MG) theories, f(R) and nDGP, on three probes of large-scale structure, the real space power spectrum estimator Q 0, bispectrum and voids, and validate fast approximate COLA simulations against full N-body simulations for the prediction of these probes.We find that using the first three even multipoles of the redshift space power spectrum to estimate Q 0 is enough to reproduce the MG boost factors of the real space power spectrum for both halo and galaxy catalogues. By analysing the bispectrum and reduced bispectrum of Dark Matter (DM), we show that the strong MG signal present in the DM bispectrum is mainly due to the enhanced power spectrum. We warn about adopting screening approximations in simulations as this neglects non-linear contributions that can source a significant component of the MG bispectrum signal at the DM level, but we argue that this is not a problem for the bispectrum of galaxies in redshift space where the signal is dominated by the non-linear galaxy bias. Finally, we search for voids in our mock galaxy catalogues using the ZOBOV watershed algorithm.To apply a linear model for Redshift-Space Distortion (RSD) in the void-galaxy cross-correlation function, we first examine the effects of MG on the void profiles entering into the RSD model. We find relevant MG signals in the integrated-density, velocity dispersion and radial velocity profiles in the nDGP theory. Fitting the RSD model for the linear growth rate, we recover the linear theory prediction in an nDGP model, which is larger than the ΛCDM predictionat the 3σ level. In f(R) theory we cannot naively compare the results of the fit with the linear theory prediction as this is scale-dependent, but we obtain results that are consistent with the ΛCDM prediction.

Fast computation of non-linear power spectrum in cosmologies with massive neutrinos

We compute 1-loop corrections to the redshift space galaxy power spectrum in cosmologies containing additional scales, and hence kernels different from Einstein-de Sitter (EdS). Specifically, our method is tailored for cosmologies in the presence of massive neutrinos and some modified gravity models; in this article we concentrate on the former case. The perturbative kernels have contributions that we notice appear either from the logarithmic growth rate f(k,t), which is scale-dependent because of the neutrino free-streaming, or from the failure of the commonly used approximation f 2 = Ω m . The latter contributions make the computation of loop corrections quite slow, precluding full-shape analyses for parameter estimation. However, we identify that the dominant pieces of the kernels come from the growth factor, allowing us to simplify the kernels but retaining the characteristic free-streaming scale introduced by the neutrinos' mass. Moreover, with this simplification one can exploit FFTLog methods to speed up the computations even more. We validate our analytical modeling and numerical method with halo catalogs extracted from the Quijote simulations finding good agreement with the, a priori, known cosmological parameters. We make public our Python code FOLPSν to compute the redshift space power spectrum in a fraction of second. Code available at https://github.com/henoriega/FOLPS-nu.

Cosmology with the redshift-space galaxy bispectrum monopole at one-loop order

We study the cosmological information content of the redshift-space galaxy bispectrum monopole at one-loop order in perturbation theory. We incorporate all effects necessary for comparison to data: fourth-order galaxy bias, infrared resummation (accounting for the nonlinear evolution of baryon acoustic oscillations), ultraviolet counterterms, nonlinear redshift-space distortions, stochastic contributions, projection, and binning effects. The model is implemented using FFTLog, and validated with the PT Challenge suite of $N$-body simulations, whose large volume allows for high-precision tests. Focusing on the mass fluctuation amplitude, ${\ensuremath{\sigma}}_{8}$, and galaxy bias parameters, we find that including one-loop corrections allow us to significantly extend the range of scales over which the bispectrum can be modeled, and greatly tightens constraints on bias parameters. However, this does not lead to noticeable improvements in the ${\ensuremath{\sigma}}_{8}$ error bar due to the necessary marginalization over a large number of nuisance parameters with conservative priors. Analyzing a BOSS-volume likelihood, we find that the addition of the one-loop bispectrum may lead to improvements on primordial non-Gaussianity constraints by $\ensuremath{\lesssim}30%$ and on ${\ensuremath{\sigma}}_{8}$ by $\ensuremath{\approx}10%$, though we caution that this requires pushing the analysis to short scales where the galaxy bias parameters may not be correctly recovered; this may lead to biases in the recovered parameter values. We conclude that restrictive priors from simulations or higher-order statistics such as the bispectrum multipoles will be needed in order to realize the full information content of the galaxy bispectrum.

Modal compression of the redshift-space galaxy bispectrum

ABSTRACT We extend the modal decomposition method, previously applied to compress the information in the real-space bispectrum to the anisotropic redshift-space galaxy bispectrum. In the modal method approach, the bispectrum is expanded on a basis of smooth functions of triangles and their orientations, such that a set of modal expansion coefficients can capture the information in the bispectrum. We assume a reference survey and compute Fisher forecasts for the compressed modal bispectrum and two other basis decompositions of the redshift-space bispectrum in the literature, one based on (single) spherical harmonics and another based on tripolar spherical harmonics. In each case, we compare the forecasted constraints from the compressed statistic with forecasted constraints from the full uncompressed bispectrum which includes all triangles and orientations. Our main result is that all three compression methods achieve good recovery of the full information content of the bispectrum, but the modal decomposition approach achieves this the most efficiently: only 14 (42) modal expansion coefficients are necessary to obtain constraints that are within 10 (2) per cent of the full bispectrum result. The next most efficient decomposition is the one based on tripolar spherical harmonics, while the spherical harmonic multipoles are the least efficient.

Constraints on multifield inflation from the BOSS galaxy survey

We use redshift-space galaxy clustering data from the BOSS survey to constrain local primordial non-Gaussianity (LPNG). This is of particular importance due to the consistency relations, which imply that a detection of LPNG would rule out all single-field inflationary models. Our constraints are based on the consistently analyzed redshift-space galaxy power spectra and bispectra, extracted from the public BOSS data with optimal window-free estimators. We use a complete perturbation theory model including all one-loop power spectrum corrections generated by LPNG. Our constraint on the amplitude of the local non-Gaussian shape is $f_{\rm NL}^{\rm local}=-33\pm 28$ at 68\%\,CL, yielding no evidence for primordial non-Gaussianity. The addition of the bispectrum tightens the $f_{\rm NL}^{\rm local}$ constraints from BOSS by $20\%$, and allows breaking of degeneracies with non-Gaussian galaxy bias. These results set the stage for the analysis of future surveys, whose larger volumes will yield significantly tighter constraints on LPNG.

Constraints on Single-Field Inflation from the BOSS Galaxy Survey.

Nonlocal primordial non-Gaussianity (NLPNG) is a smoking gun of interactions in single-field inflationary models and can be written as a combination of the equilateral and orthogonal templates. We present the first constraints on these from the redshift-space galaxy power spectra and bispectra of the BOSS data. These are the first such measurements independent of the cosmic microwave background fluctuations. We perform a consistent analysis that includes all necessary nonlinear corrections generated by NLPNG and vary all relevant cosmological and nuisance parameters in a global fit to the data. Our conservative analysis yields joint limits on the amplitudes of the equilateral and orthogonal shapes, f_{NL}^{equil}=940±600 and f_{NL}^{ortho}=-170±170 (both at 68%CL). These can be used to derive constraints on coefficients of the effective single-field inflationary Lagrangian; in particular, we find that the sound speed of inflaton fluctuations has the bound c_{s}≥0.013 at 95%CL. Fixing the quadratic galaxy bias and cosmological parameters, the constraints can be tightened to f_{NL}^{equil}=260±300 and f_{NL}^{ortho}=-23±120 (68%CL).