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R. Zhou

Publications and source records attributed to R. Zhou.

At least 109 records · Page 6Linked to original sources

Fully-gapped superconductivity with rotational symmetry breaking in pressurized kagome metal CsV$_3$Sb$_5$

The discovery of the kagome metal CsV$_3$Sb$_5$ has generated significant interest in its complex physical properties, particularly its superconducting behavior under different pressures, though its nature remains debated. Here, we performed low-temperature, high-pressure $^{121/123}$Sb nuclear quadrupole resonance (NQR) measurements to explore the superconducting pairing symmetry in CsV$_3$Sb$_5$. At ambient pressure, we found that the spin-lattice relaxation rate 1/$T_1$ exhibits a kink at $T \sim$ 0.4 $T_\textrm{c}$ within the superconducting state and follows a $T^3$ variation as temperature further decreases. This suggests the presence of two superconducting gaps with line nodes in the smaller one. As pressure increases beyond $P_{\rm c} \sim 1.85$ GPa, where the charge-density wave phase is completely suppressed, 1/$T_1$ shows no Hebel-Slichter peak just below $T_\textrm{c}$, and decreases rapidly, even faster than $T^5$, indicating that the gap is fully opened for pressures above $P_{\rm c}$. In this high pressure region, the angular dependence of the in-plane upper critical magnetic field $H_{\rm c2}$ breaks the $C_6$ rotational symmetry. We propose the $s+id$ pairing at $P > P_{\rm c}$ which explains both the 1/$T_1$ and $H_{\rm c2}$ behaviors. Our findings indicate that CsV$_3$Sb$_5$ is an unconventional superconductor and its superconducting state is even more exotic at high pressures.

cond-mat.supr-con↗

Validation of the DESI DR2 Ly$α$ BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-$α$ (Ly$α$) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the Baryonic Acoustic Oscillation (BAO) analysis using Ly$α$ forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Ly$α$ mocks that use a quasi-linear input power spectrum to incorporate the non-linear broadening of the BAO peak. We have also increased the number of realisations used in the validation to 400, compared to the 150 realisations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask Damped Lyman-$α$ Absorbers (DLAs) in our spectra. The BAO measurement from the Ly$α$ dataset of DESI DR2 is presented in a companion publication.

astro-ph.IM↗

Antiferromagnetic Spin Fluctuations and Structural Transition in Cluster Mott Insulator Candidate Nb3Cl8 Revealed by 93Nb- and 35Cl-NMR

Motivated by recent studies of the cluster Mott insulator candidate compound Nb3Cl8, this study performs 93Nb and 35Cl nuclear magnetic resonance (NMR) measurements to investigate the electron correlations. Below the structural transition temperature Ts ~ 97 K, all satellites of the 93Nb NMR spectra split into three distinct peaks, which suggests symmetry lowering due to the structural transition and could be attributed to the change in the Nb-Nb bond-lengths of the Nb3 clusters. The spin-lattice relaxation rate 1/T1 divided by the temperature T, 1/T1T, increases upon cooling to Ts for all Cl sites, whereas only the Knight shift K of Cl located at the center of the Nb3 clusters exhibits a temperature dependence similar to that observed in magnetic susceptibility. These findings collectively demonstrate the existence of strong spin correlations between the Nb atoms in Nb3Cl8, which are closely associated with Mottness.

cond-mat.str-el↗

Signatures of two gaps in the spin susceptibility of a cuprate superconductor

A major obstacle to understanding high-Tc cuprates is that superconductivity precludes observing normal-state properties at low temperatures. One prime example is the normal-state spin susceptibility \c{hi}spin: although its decrease upon cooling far above Tc typifies pseudogap behavior, its behavior at low temperatures is generally unknown. Here, our measurements in high magnetic fields expose \c{hi}spin of YBa2Cu3Oy down to low temperatures. Even though superconductivity is suppressed by the field, we uncover two thermally-activated contributions alongside a residual \c{hi}spin(T=0) due to gapless excitations. We relate these two distinct gaps to short-range charge-density waves and to the formation of singlets as in certain quantum spin systems. Both phenomena thus contribute to the pseudogap at low temperature, supplementing short-lived antiferromagnetism that initiates pseudogap behavior at high temperatures. We therefore propose that the pseudogap ought to be regarded as a composite property and that, when not undergoing spin-stripe ordering, underdoped cuprates tend to form short-ranged spin singlets.

cond-mat.supr-con↗

Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements

The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper (Yu et al., 2024). We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by $<15\%$ of their statistical errors, and thus contribute negligibly to the overall DESI error budget.

astro-ph.CO↗

Mitigation of DESI fiber assignment incompleteness effect on two-point clustering with small angular scale truncated estimators

We present a method to mitigate the effects of fiber assignment incompleteness in two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys, by truncating small angular scales from estimators. We derive the corresponding modified correlation function and power spectrum windows to account for the small angular scale truncation in the theory prediction. We validate this approach on simulations reproducing the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show that we recover unbiased cosmological constraints using small angular scale truncated estimators from simulations with fiber assignment incompleteness, with respect to standard estimators from complete simulations. Additionally, we present an approach to remove the sensitivity of the fits to high $k$ modes in the theoretical power spectrum, by applying a transformation to the data vector and window matrix. We find that our method efficiently mitigates the effect of fiber assignment incompleteness in two-point correlation function and power spectrum measurements, at low computational cost and with little statistical loss.

astro-ph.CO↗

Mitigating Imaging Systematics for DESI 2024 Emission Line Galaxies and Beyond

Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as imaging systematics. We present the imaging systematics mitigation applied to the DESI Data Release 1 (DR1) large-scale structure catalogs used in the DESI 2024 cosmological analyses. We also explore extensions of the fiducial treatment. This includes a combined approach, through forward image simulations in conjunction with neural network-based regression, to obtain an angular selection function that mitigates the imaging systematics observed in the DESI DR1 ELGs target density. We further derive a line-of-sight selection function from the forward model that removes the strong redshift dependence between imaging systematics and low redshift ELGs. Combining both angular and redshift-dependent systematics, we construct a 3D selection function and assess the impact of all selection functions on clustering statistics. We quantify differences between these extended treatments and the fiducial treatment in terms of the measured 2-point statistics. We find that the results are generally consistent with the fiducial treatment and conclude that the differences are far less than the imaging systematics uncertainty included in DESI 2024 full-shape measurements. We extend our investigation to the ELGs at $0.6<z<0.8$, i.e., beyond the redshift range ($0.8<z<1.6$) adopted for the DESI clustering catalog, and demonstrate that determining the full 3D selection function is necessary in this redshift range. Our tests showed that all changes are consistent with statistical noise for BAO analyses indicating they are robust to even severe imaging systematics. Specific tests for the full-shape analysis will be presented in a companion paper.

astro-ph.CO↗

Not all lensing is low: An analysis of DESI$\times$DES using the Lagrangian Effective Theory of LSS

In this work we use Lagrangian perturbation theory to analyze the harmonic space galaxy clustering signal of Bright Galaxy Survey (BGS) and Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI), combined with the galaxy--galaxy lensing signal measured around these galaxies using Dark Energy Survey Year 3 source galaxies. The BGS and LRG galaxies are extremely well characterized by DESI spectroscopy and, as a result, lens galaxy redshift uncertainty and photometric systematics contribute negligibly to the error budget of our ``$2\times2$-point'' analysis. On the modeling side, this work represents the first application of the \texttt{spinosaurus} code, implementing an effective field theory model for galaxy intrinsic alignments, and we additionally introduce a new scheme (\texttt{MAIAR}) for marginalizing over the large uncertainties in the redshift evolution of the intrinsic alignment signal. Furthermore, this is the first application of a hybrid effective field theory (HEFT) model for galaxy bias based on the $\texttt{Aemulus}\, ν$ simulations. Our main result is a measurement of the amplitude of the lensing signal, $S_8=σ_8 \left(Ω_m/0.3\right)^{0.5} = 0.850^{+0.042}_{-0.050}$, consistent with values of this parameter derived from the primary CMB. This constraint is artificially improved by a factor of $51\%$ if we assume a more standard, but restrictive parameterization for the redshift evolution and sample dependence of the intrinsic alignment signal, and $63\%$ if we additionally assume the nonlinear alignment model. We show that when fixing the cosmological model to the best-fit values from Planck PR4 there is $> 5 σ$ evidence for a deviation of the evolution of the intrinsic alignment signal from the functional form that is usually assumed in cosmic shear and galaxy--galaxy lensing studies.

astro-ph.CO↗

Baryon Acoustic Oscillation Theory and Modelling Systematics for the DESI 2024 results

This paper provides a comprehensive overview of how fitting of Baryon Acoustic Oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument's (DESI) 2024 results using its DR1 dataset, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic ($α_{\mathrm{iso}}$) and anisotropic ($α_{\mathrm{ap}}$) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement and validate a new model for the remaining smooth-broadband (i.e., without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best-practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than $0.1\%$ ($0.2\%$) for its isotropic (anisotropic) distance measurements. We expect the theory and best-practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond.

astro-ph.CO↗

CircleZ: Reliable Photometric redshifts for AGN computed using only photometry from Legacy Survey Imaging for DESI

(abridged)Photometric redshifts for AGN (galaxies hosting an accreting supermassive black hole in their center) are notoriously challenging and currently better computed via SED fitting, assuming that deep photometry for many wavelengths is available. However, for AGN detected all-sky, the photometry is limited and provided by different projects. This makes the task of homogenising the data challenging and is a dramatic drawback for the millions of AGN that wide surveys like SRG/eROSITA will detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGN using only one dataset that covers a large area: the 10th Data Release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures, thus avoids issues related to the cross-calibration of surveys. We present the results from CircleZ, a machine-learning algorithm based on a Fully Connected Neural Network. CircleZ uses training sample of 14,000 X-ray-detected AGN and utilizes multi-aperture photometry. The accuracy and the fraction of outliers reached in a test sample of 2913 AGN are 0.067 and 11.6%, respectively. The results are comparable to or better than those obtained previously for the same field but with much less effort. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching comparable accuracy as in eFEDS when limiting the magnitude of the counterparts with respect to the depth of LS10. The method applies to fainter samples of AGN using deeper optical data from future surveys (e.g., LSST, Euclid), granted LS10-like information on the light distribution beyond a morphological type is provided. With the paper, we release an updated version of the photometric redshifts (including errors and probability distribution function) for eROSITA/eFEDS.

astro-ph.GA↗

The Construction of Large-scale Structure Catalogs for the Dark Energy Spectroscopic Instrument

We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random' catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes.

astro-ph.CO↗

An analysis of parameter compression and full-modeling techniques with Velocileptors for DESI 2024 and beyond

In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within \texttt{velocileptors} modeling pipeline when fitting mock data from the \texttt{AbacusSummit} N-body simulations. We compare the constraints obtained from parameter compression methods to the direct fitting (Full-Modeling) approaches of modeling the galaxy power spectra, and show that the ShapeFit extension to the traditional template method is consistent with the Full-Modeling method within the standard $Λ$CDM parameter space. We show the dependence on scale cuts when fitting the different redshift bins using the ShapeFit and Full-Modeling methods. We test the ability to jointly fit data from multiple redshift bins as well as joint analysis of the pre-reconstruction power spectrum with the post-reconstruction BAO correlation function signal. We further demonstrate the behavior of the model when opening up the parameter space beyond $Λ$CDM and also when combining likelihoods with external datasets, namely the Planck CMB priors. Finally, we describe different parametrization options for the galaxy bias, counterterm, and stochastic parameters, and employ the halo model in order to physically motivate suitable priors that are necessary to ensure the stability of the perturbation theory.

astro-ph.CO↗

Archetype-Based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of PCA-derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive dataset derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by $10-30\%$. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates ($0.5-0.8\%$ higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false positive redshift estimation by $5-40\%$ for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

astro-ph.CO↗

A comparison of effective field theory models of redshift space galaxy power spectra for DESI 2024 and future surveys

In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation theory. These models are employed in the pipelines \texttt{velocileptors}, \texttt{PyBird}, and \texttt{Folps$ν$}. While these models have been validated independently, a detailed comparison with consistent choices has not been attempted. After briefly discussing the theoretical differences between the models we describe how to provide a more apples-to-apples comparison between them. We present the results of fitting mock spectra from the \texttt{AbacusSummit} suite of N-body simulations provided in three redshift bins to mimic the types of dark time tracers targeted by the DESI survey. We show that the theories behave similarly and give consistent constraints in both the forward-modeling and ShapeFit compressed fitting approaches. We additionally generate (noiseless) synthetic data from each pipeline to be fit by the others, varying the scale cuts in order to show that the models agree within the range of scales for which we expect 1-loop perturbation theory to be applicable. This work lays the foundation of Full-Shape analysis with DESI Y1 galaxy samples where in the tests we performed, we found no systematic error associated with the modeling of the galaxy redshift space power spectrum for this volume.

astro-ph.CO↗

Validation of the DESI 2024 Ly$α$ forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$α$ (Ly$α$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Ly$α$ forest BAO measurement. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Ly$α$ forest. The synthetic data sets span a redshift range $1.8<z<3.8$, and are analysed using the same framework and pipeline used for the DESI 2024 Ly$α$ forest BAO measurement. To measure BAO, we use both the Ly$α$ auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Ly$α$ forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Ly$α$ forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

astro-ph.CO↗

Optimal Reconstruction of Baryon Acoustic Oscillations for DESI 2024

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs.

astro-ph.CO↗

HOD-Dependent Systematics in Emission Line Galaxies for the DESI 2024 BAO analysis

The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this work, we focus on the robustness of the BAO analysis against the Halo Occupation Distribution (HOD) modeling for the Emission Line Galaxy (ELG) tracer. Based on a common dark matter simulation, our analysis relies on HOD mocks tuned to early DESI data, namely the One-Percent survey data. To build the mocks, we use several HOD models for the ELG tracer as well as extensions to the baseline HOD models. Among these extensions, we consider distinct recipes for galactic conformity and assembly bias. We perform two independent analyses in the Fourier space and in the configuration space. We recover the BAO signal from two-point measurements after performing reconstruction on our mocks. Additionally, we also apply the control variates technique to reduce sample variance noise. Our BAO analysis can recover the isotropic BAO parameter $α_\text{iso}$ within 0.1\% and the Alcock Paczynski parameter $α_\text{AP}$ within 0.3\%. Overall, we find that our systematic error due to the HOD dependence is below 0.17\%, with the Fourier space analysis being more robust against the HOD systematics. We conclude that our analysis pipeline is robust enough against the HOD systematics for the ELG tracer in the DESI 2024 BAO analysis.

astro-ph.CO↗

Survey Operations for the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) survey is a spectroscopic survey of tens of millions of galaxies at $0 < z < 3.5$ covering 14,000 square degrees of the sky. In its first 1.1 years of survey operations, it has observed more than 14 million galaxies and 4 million stars. We describe the processes that govern DESI's observations of the 15,000 fields composing the survey. This includes the planning of each night's observations in the afternoon; automatic selection of fields to observe during the night; real-time assessment of field completeness on the basis of observing conditions during each exposure; reduction, redshifting, and quality assurance of each field of targets in the morning following observation; and updates to the list of future targets to observe on the basis of these results. We also compare the performance of the survey with historical expectations and find good agreement. Simulations of the weather and of DESI observations using the real field-selection algorithm show good agreement with the actual observations. After accounting for major unplanned shutdowns, the dark time survey is progressing about 7% faster than forecast, which is good agreement given approximations made in the simulations.

astro-ph.CO↗