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J. Jimenez

Publications and source records attributed to J. Jimenez.

16 recordsLinked to original sources

Sizing the Universe with DESI Galaxy Sizes: Plain Fundamentals of Fundamental-Plane Lensing

Weak gravitational lensing provides a powerful way to map cosmic structure, but most current measurements rely on galaxy shape distortions from deep imaging surveys and are affected by systematics such as intrinsic alignments, photometric-redshift uncertainties and shape-measurement biases. Here we present a spectroscopic galaxy-galaxy lensing magnification measurement using Fundamental-Plane (FP) size residuals, $\delta_r\equiv\Delta\log_{10}R_\mathrm{e}$, from 3.26 million DESI luminous red galaxy (LRG) sources behind DESI Bright Galaxy Survey lenses. The FP-like relation predicts the intrinsic sizes of LRGs from lensing-invariant quantities, including velocity dispersion $\sigma_0$ and surface brightness $I_\mathrm{e}$, with a scatter of about 0.06-0.07 dex. Lensing magnifies LRG sizes, giving the direct convergence response $\delta_r(\kappa)=\kappa/\ln 10$, but we show that the full lensing response is modified by magnification bias, because fitting $R_\mathrm{e}$ with $I_\mathrm{e}$ inevitably induces a magnitude dependence in $\bar{\delta}_r(m)$. After calibrating this response, we recover surface-density profiles with uncertainties comparable to those from individual Stage-III shear surveys using 5-20 million higher-redshift sources. The corresponding excess surface-density profiles agree with shear-based measurements. We further show that the estimator is robust to size-measurement uncertainties, with a convergence multiplicative bias only $\simeq -0.2$ times the size bias. FP lensing therefore provides a clean, spectroscopic and complementary probe of cosmic structure.

astro-ph.CO

Unveiling Hidden Lyman Alpha Emitters in the DESI DR1 Data

We present an automatic method based on machine-learning convolutional neural network (CNN) architecture to detect Lyman alpha emitters (LAE) hidden in the Data Release 1 spectroscopic dataset of the Dark Energy Spectroscopic Instrument (DESI). Those LAEs mostly have incorrect redshift estimations because the current DESI pipeline is not designed to detect and measure the redshifts of galaxies at $z>2$. To uncover those sources, we first visually inspect thousands of DESI spectra and construct a sample, consisting of both LAEs and non-LAEs, for training and testing the CNN-based model to (1) detect LAEs in DESI spectra and (2) determine their Ly$\alpha$ redshifts. The final model yields $95.2\%$ purity and $95.9\%$ completeness for detecting LAEs. We apply this model to approximately $2\times10^{6}$ spectra of sources targeted as emission-line galaxies and detect 19,685 LAEs from $z\sim2$ to $3.5$ within 12 minutes with a single GPU, illustrating the high efficiency of this model for identifying LAEs. The detected LAEs are mostly at the bright end of the luminosity function with Ly$\alpha$ luminosity $L_{\rm Ly\alpha} \gtrsim 10^{43}$ erg/s. The high signal-to-noise composite spectrum of the detected LAEs further shows various spectral features, including P-Cygni profiles of metal lines and MgII emission lines, possible indicators of Lyman continuum escape fraction, revealing the rich astrophysical information in this LAE sample. Finally, this sample can be used to train and validate the pipelines for redshift determination of LAEs for the preparation of the DESI-II survey.

astro-ph.GA

Cosmological constraints from the DESI DR1 joint power spectrum and bispectrum analysis

We derive cosmological parameter constraints from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) galaxy clustering data, based on a joint full-shape analysis of the power spectrum multipoles and the bispectrum monopole using the ShapeFit framework. This is the follow-up of our previous work, in which we obtained for the first time constraints on the ShapeFit parameters using the bispectrum of DESI DR1. Here we present the first ShapeFit cosmological inference results using the bispectrum of DESI DR1. We recover values for the matter density parameter and Hubble constant of respectively $\Omega_m=0.310\pm0.012$ and $H_0=[68.92\pm0.97]\,\mathrm{km\, s^{-1} Mpc^{-1}}$, consistent with previous results from the full DESI DR1 dataset that did not use the bispectrum signal. The inclusion of the bispectrum significantly tightens the constraints on the amplitude of fluctuations, reducing the error-bars in $\ln(A_s\times10^{10})$ by approximately 20\%, compared to using the power spectrum alone. We also explore extended cosmological models by performing fits for the evolving dark energy equation of state $w_0w_a$, and the sum of neutrino masses $\sum m_\nu$. In these cases, we obtain constraints slightly larger than the ones from previous works from the DESI collaboration, due to not combining the full-shape results with other probes in all tracers. We find no strong evidence of deviations from standard $\Lambda$CDM, with the dark energy equation-of-state remaining within 2$\sigma$ from a cosmological constant $\Lambda$, and the neutrino mass being consistent with the normal hierarchy, $\sum m_\nu<0.1\,[eV]$ at 95\% confidence limit. These constraints are broadly consistent with other DESI DR1 analyses, thus validating the robustness of the ShapeFit compression approach and the inclusion of the bispectrum for cosmological inference.

astro-ph.CO

The DESI Single Fiber Lens Search. I. Four Thousand Spectroscopically Selected Galaxy-Galaxy Gravitational Lens Candidates

We present 4,110 strong gravitational lens candidates, 3,887 of which are new discoveries, selected from a sample of 5,837,154 luminous red galaxies (LRGs) observed with the Dark Energy Spectroscopic Instrument (DESI). Candidates are identified via the presence of background ionized oxygen [O II] nebular emission lines in the foreground LRG spectra which may originate from the lensing of higher redshift star-forming galaxies. Using the measured foreground redshift, background redshift, and integrated flux of the background [O II] doublet, we integrate over impact parameters to compute the probability that each candidate is a lens. We expect 53% of candidates to be true lenses with Einstein radii ranging from 0.1'' to 4'', which can be confirmed with high-resolution imaging. Confirmed strong lenses from this sample will form a valuable cosmological dataset, as strong gravitational lensing is the only method to directly measure dark matter halo substructure at cosmological distances. We independently recover the host of the multiply imaged gravitationally lensed type Ia supernova iPTF16geu. Monitoring these lenses for future multiply lensed transients will enable (a) H0 measurements via time-delay cosmography and (b) substructure measurements via flux ratios.

astro-ph.GA

DESI DR1 Ly$\alpha$ 1D power spectrum: Validation of estimators

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Ly$\alpha$ forest cosmology, accessed through its one-dimensional power spectrum ($P_{\mathrm{1D}}$). The Ly$\alpha$ forest $P_{\mathrm{1D}}$ is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure $P_{\mathrm{1D}}$: the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest $k$ values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 $P_{\mathrm{1D}}$ on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

astro-ph.CO

The Compilation and Validation of the Spectroscopic Redshift Catalogs for the DESI-COSMOS and DESI-XMMLSS Fields

Over several dedicated programs that include targets beyond the main cosmological samples, the Dark Energy Spectroscopic Instrument (DESI) collected spectra for 304,970 unique objects in two fields centered on the COSMOS and XMM-LSS fields. In this work, we develop spectroscopic redshift robustness criteria for those spectra, validate these criteria using visual inspection, and provide two custom Value-Added Catalogs with our redshift characterizations. With these criteria, we reliably classify 212,935 galaxies below z < 1.6, 9,713 quasars and 35,222 stars. As a critical element in characterizing the selection function, we provide the description of 70 different algorithms that were used to select these targets from imaging data. To facilitate joint imaging/spectroscopic analyses, we provide row-matched photometry from the Dark Energy Camera, Hyper-Suprime Cam, and public COSMOS2020 photometric catalogs. Finally, we demonstrate example applications of these large catalogs to photometric redshift estimation, cluster finding, and completeness studies.

astro-ph.CO

Cosmological neutrino mass: a frequentist overview in light of DESI

We derive constraints on the neutrino mass using a variety of recent cosmological datasets, including DESI BAO, the full-shape analysis of the DESI matter power spectrum and the one-dimensional power spectrum of the Lyman-$\alpha$ forest (P1D) from eBOSS quasars as well as the cosmic microwave background (CMB). The constraints are obtained in the frequentist formalism by constructing profile likelihoods and applying the Feldman-Cousins prescription to compute confidence intervals. This method avoids potential prior and volume effects that may arise in a comparable Bayesian analysis. Parabolic fits to the profiles allow one to distinguish changes in the upper limits from variations in the constraining power $\sigma$ of the different data combinations. We find that all profiles in the $\Lambda$CDM model are cut off by the $\sum m_\nu \geq 0$ bound, meaning that the corresponding parabolas reach their minimum in the unphysical sector. The most stringent 95% C.L. upper limit is obtained by the combination of DESI DR2 BAO, Planck PR4 and CMB lensing at 53 meV, below the minimum of 59 meV set by the normal ordering. Extending $\Lambda$CDM to non-zero curvature and $w_0w_\mathrm{a}$CDM relaxes the constraints past 59 meV again, but only $w_0w_\mathrm{a}$CDM exhibits profiles with a minimum at a positive value. Using a combination of DESI DR1 full-shape, BBN and eBOSS Lyman-$\alpha$ P1D, we successfully constrain the neutrino mass independently of the CMB. This combination yields $\sum m_\nu \leq 285$ meV (95% C.L.). The addition of DESI full-shape or Lyman-$\alpha$ P1D to CMB and DESI BAO results in small but noticeable improvement of the constraining power of the data. Lyman-$\alpha$ free-streaming measurements especially improve the constraint. Since they are based on eBOSS data, this sets a promising precedent for upcoming DESI data.

astro-ph.CO

The Backup Program of the Dark Energy Spectroscopic Instrument's Milky Way Survey

The Milky Way Backup Program (MWBP), a survey currently underway with the Dark Energy Spectroscopic Instrument (DESI) on the Nicholas U. Mayall 4-m Telescope, works at the margins of the DESI Main surveys to obtain spectra of millions of additional stars from the Gaia catalog. Efficiently utilizing twilight times (<18 deg) and poor weather conditions, the MWBP extends the range of stellar sources studied to both brighter magnitudes and lower Galactic latitude and declination than the stars studied in DESI's Main Milky Way Survey. While the MWBP prioritizes candidate giant stars selected from the Gaia catalog (using color and parallax criteria), it also includes an unbiased sample of bright stars (i.e., 11.2 < G < 16 mag) as well as fainter sources (to G < 19 mag). As of March 1, 2025, the survey had obtained spectra of ~7 million stars, approximately 1.2 million of which are included in the DESI Data Release 1. The full survey, when completed, will cover an area of more than 21,000 square degrees and include approximately 10 million Gaia sources, roughly equal to the number of stellar spectra obtained through the DESI Main Survey, while only utilizing <9% of all DESI observing time.

astro-ph.SR

DESI Data Release 1: Stellar Catalogue

In this paper we present the stellar Value-Added Catalogue (VAC) based on the DESI Data Release 1. This VAC contains stellar parameter, abundance and radial velocity measurements for more than 4 million stars. It also contains, for the first time, measurements from individual epochs for more than a million stars with at least two observations. The main contribution to the catalogue comes from the bright program of the main survey, which includes $\sim $2.5 million stars, and the backup program, which includes $\sim $ 1 million stars. The combined magnitude range for the stars in the catalogue extends from ${\it Gaia}$ G $\sim 12$ to G $\sim 21$. For the magnitude range $17.5<G<21$ this catalogue represents a factor of 10 increase in the number of stars with radial velocity and abundance measurements compared to existing surveys. Despite DESI's resolution (R $\sim 2500-5000$), the median radial velocity uncertainty for stars in the catalogue is better than 1 km s$^{-1}$. The stellar parameters and abundances of stars in DESI are measured by two independent pipelines, and after applying a temperature-dependent calibration, [Fe/H] abundances of high signal-to-noise stars are accurate to better than $\sim$ 0.1 dex when compared to high-resolution surveys. The catalogue probes different Galactic components including a particularly large number of distant stars: tens of thousands of stars further than 10 kpc, and thousands further than 50 kpc. The catalogue also contains several thousand extremely metal-poor stars with ${\rm [Fe/H]}<-3$. The released sample of stars includes measurements for thousands of stars that are members of dwarf galaxies, open and globular clusters as well as members of several dozen stellar streams. The next public DESI data release is expected in less than two years and will contain three times as many stars as DR1.

astro-ph.GA

Measuring Fiber Positioning Accuracy and Throughput with Fiber Dithering for the Dark Energy Spectroscopic Instrument

Highly multiplexed, fiber-fed spectroscopy is enabling surveys of millions of stars and galaxies. The performance of these surveys depends on accurately positioning fibers in the focal plane to capture target light. We describe a technique to measure the positioning accuracy of fibers by dithering fibers slightly around their ideal locations. This approach also enables measurement of the total system throughput and point spread function delivered to the focal plane. We then apply this technique to observations from the Dark Energy Survey Instrument (DESI), and demonstrate that DESI positions fibers to within 0.08" of their targets (5% of a fiber diameter) and achieves a system throughput within about 5% of expectations.

astro-ph.IM

Astrometric Calibration and Performance of the Dark Energy Spectroscopic Instrument Focal Plane

The Dark Energy Spectroscopic Instrument, consisting of 5020 robotic fiber positioners and associated systems on the Mayall telescope at Kitt Peak, Arizona, is carrying out a survey to measure the spectra of 40 million galaxies and quasars and produce the largest 3D map of the universe to date. The primary science goal is to use baryon acoustic oscillations to measure the expansion history of the universe and the time evolution of dark energy. A key function of the online control system is to position each fiber on a particular target in the focal plane with an accuracy of 11$\mu$m rms 2-D. This paper describes the set of software programs used to perform this function along with the methods used to validate their performance.

astro-ph.IM

Temperature Dependence of Spontaneous Switch-on and Switch-off of Laser Cavity Solitons in Vertical-Cavity Surface-Emitting Lasers with Frequency-Selective Feedback

A systematic experimental and numerical investigation of the conditions for the spontaneous formation of laser cavity solitons in broad-area vertical-cavity surface-emitting lasers with frequency-selective feedback by a volume Bragg grating is reported. It is shown that the switching thresholds are controlled by a combination of frequency shifts induced by ambient temperature and Joule heating. The gain level has only a minor influence on the threshold but controls mainly the power of the solitons. At large initial detuning and high threshold gain, the first observed structure can be a high order soliton. In real devices spatial disorder in the cavity length causes a pinning of solitons and a dispersion of thresholds. The experimental observations are in good agreement with numerical simulations taking into account disorder and the coupling of gain and cavity resonance due to Joule heating. In particular, we demonstrate that the existence of the traps explain the spontaneous switch on of the solitons,but do not modify the soliton shape significantly, i.e. the observed solitons are a good approximation of the ones expected in a homogenous system.

nlin.PS

Estimating financial risk using piecewise Gaussian processes

We present a computational method for measuring financial risk by estimating the Value at Risk and Expected Shortfall from financial series. We have made two assumptions: First, that the predictive distributions of the values of an asset are conditioned by information on the way in which the variable evolves from similar conditions, and secondly, that the underlying random processes can be described using piecewise Gaussian processes. The performance of the method was evaluated by using it to estimate VaR and ES for a daily data series taken from the S&P500 index and applying a backtesting procedure recommended by the Basel Committee on Banking Supervision. The results indicated a satisfactory performance.

q-fin.RM

Cropping Euler factors of modular L-functions

According to the Birch and Swinnerton-Dyer conjectures, if A/Q is an abelian variety then its L-function must capture substantial part of the arithmetic properties of A. The smallest number field L where A has all its endomorphisms defined must also have a role. This article deals with the relationship between these two objects in the specific case of modular abelian varieties A_f/Q associated to weight 2 newforms for the modular group Gamma_1(N). Specifically, our goal is to relate the order of L(A_f/Q,s) at s = 1 with Euler products cropped by the set of primes that split completely in L. The results we obtain for the case when f has complex multiplication are complete, while in the absence of CM, our results depend on the rate of convergence in Sato-Tate distributions.

math.NT

Information transfer and nontrivial collective behavior in chaotic coupled map networks

The emergence of nontrivial collective behavior in networks of coupled chaotic maps is investigated by means of a nonlinear mutual prediction method. The resulting prediction error is used to measure the amount of information that a local unit possesses about the collective dynamics. Applications to locally and globally coupled map systems are considered. The prediction error exhibits phase transitions at critical values of the coupling for the onset of ordered collective behavior in these networks. This information measure may be used as an order parameter for the characterization of complex behavior in extended chaotic systems.

nlin.CD

Coupled Map Networks as Communication Schemes

Networks of chaotic coupled maps are considered as string and language generators. It is shown that such networks can be used as encrypting systems where the ciphertext contains information about the evolution of the network and also about the way to select the plaintext symbols from the string associated to the network evolution. The secret key provides the network parameters, such as the coupling strengths.

nlin.CD