arXiv subjects

M. A. Fernandez

Publications and source records attributed to M. A. Fernandez.

11 recordsLinked to original sources

arXiv2026

Multi-Year-to-Decadal Temperature Prediction using a Machine Learning Model-Analog Framework

Multi-year-to-decadal climate predictions are a key tool in understanding the range of potential regional climate futures. Here, we present a framework that combines machine learning and analog forecasting for regional predictions on these timescales. A neural network is used to learn a mask of weights that highlights important global precursors to the evolution of a specific prediction target (region, variable, and lead time). A library of mask-weighted model states, or potential analogs, are then compared to a mask-weighted observational state. The known future of the best matching potential analogs serve as the prediction for the future of the observational state. We predict 2-meter temperature using the Berkeley Earth Surface Temperature dataset for observations, with a multi-model potential analog library of CMIP6 simulations. Using a 30-year climatology reference, we compare our analog method to two other analog prediction methods and the CMIP6 library using the continuous ranked probability score to assess the quality of predicted distributions, and mean squared error to assess the quality of predicted ensemble means. For nearly all cases explored, our analog method produces skillful predictions. We find higher distribution skill over the CMIP6 library in all cases, which is due to improved prediction of the distribution spread. We find overall higher skill than other analog methods in the predicted distributions and ensemble means. Finally, we find broadly similar skill to an ensemble of bias-corrected initialized Earth system models. Benefits of our analog method include low computational cost, ensemble size flexibility, and interpretability.

physics.ao-ph↗

arXiv2026

Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra

We present a new cosmological analysis of the small-scale Lyman alpha forest 1D flux power spectrum (P1D) using high-resolution quasar spectra from XQ100 and KODIAQ-SQUAD, interpreted through the PRIYA emulator. PRIYA is a suite of galaxy formation simulations spanning a range of cosmological and inhomogeneous HeII reionization parameters, enabling few-percent-level predictions of the P1D. These datasets, probing down to $k \sim 6\,h\,\mathrm{Mpc}^{-1}$ at $z = 2-5$, offer access to non-linear scales inaccessible to large-volume surveys like eBOSS. We find that the XQ100 P1D yields constraints on the primordial power spectrum parameters $(A_P, n_P)$ at pivot scale $k_0 = 0.78\,\mathrm{Mpc}^{-1}$ that are consistent with PRIYA results from eBOSS DR14 and Planck CMB, albeit with broader uncertainties. Notably, this is achieved without external IGM temperature data, showing that XQ100 alone provides stronger constraints on thermal history than eBOSS DR14. In contrast, the KODIAQ-SQUAD P1D favors a significantly higher $A_P$ value, driven by the selection bias toward high-column density absorbers (HCDs). We also find that the P1D at $k > 0.045\,\mathrm{s/km}$ is more sensitive to Lyman limit system contamination and thermal history. When imposing a prior on $(A_P, n_P)$, the reduced $χ^2$ remains unchanged and the inferred mean IGM temperature is unaffected, suggesting that cosmological and thermal parameters are largely sensitive to different scales. The XQ100 P1D therefore provides complementary information on thermal nuisance parameters, which can be jointly fit with eBOSS or DESI P1D measurements to improve cosmological constraints.

astro-ph.CO↗

arXiv2025

Predicting Tropical Cyclone Track Forecast Errors using a Probabilistic Neural Network

A new method for estimating tropical cyclone track uncertainty is presented and tested. This method uses a neural network to predict a bivariate normal distribution, which serves as an estimate for track uncertainty. We train the network and make predictions on forecasts from the National Hurricane Center (NHC), which currently uses static error distributions based on forecasts from the past five years for most applications. The neural network-based method produces uncertainty estimates that are dynamic and probabilistic. Further, the neural network-based method allows for probabilistic statements about tropical cyclone trajectories, including landfall probability, which we highlight. We show that our predictions are well calibrated using multiple metrics, that our method produces better uncertainty estimates than current NHC approaches, and that our method achieves similar performance to the Global Ensemble Forecast System. Once trained, the computational cost of predictions using this method is negligible, making it a strong candidate to improve the NHC's operational estimations of tropical cyclone track uncertainty.

physics.ao-ph↗

arXiv2024

Cosmological Constraints from the eBOSS Lyman-$α$ Forest using the PRIYA Simulations

We present new cosmological parameter constraints from the eBOSS Lyman-$α$ forest survey. We use a new theoretical model and likelihood based on the PRIYA simulation suite. PRIYA is the first suite to resolve the Lyman-$α$ forest in a ($120$~Mpc/h~)$^3$ volume, using a multi-fidelity emulation technique. We use PRIYA to predict Lyman-$α$ forest observables with $\lesssim 1\%$ interpolation error over an $11$ dimensional ($9$ simulated, $2$ in post-processing) parameter space. We identify an internal tension within the flux power spectrum data. Once the discrepant data is removed, we find the primeval scalar spectral index measured at a pivot scale of $k_0 = 0.78$ Mpc$^{-1}$ to be $n_P = 1.009^{+0.027}_{-0.018}$ at 68\% confidence. This measurement from the Lyman-$α$ forest flux power spectrum alone is in reasonable agreement with Planck, and in tension with earlier eBOSS analyses. The amplitude of matter fluctuations is $σ_8 = 0.733^{+0.026}_{-0.029}$ at 68\% confidence, in agreement with Dark Energy Survey weak lensing measurements and other small-scale structure probes and in tension with CMB measurements from Planck and ACT. The effective optical depth to Lyman-$α$ photons from our pipeline is in good agreement with earlier high resolution measurements. We find a linear power at $z=3$ and $k = 0.009$ s/km of $Δ_L^2 = 0.302^{+0.024}_{-0.027}$ with a slope $n_\mathrm{eff} = -2.264^{+0.026}_{-0.018}$. Our flux power spectrum only chains prefer a low level of heating during helium reionization. When we add IGM temperature data we find $n_P = 0.983\pm 0.020$ and $σ_8 = 0.703^{+0.023}_{-0.027}$. Our chains prefer an early and long helium reionization event, as suggested by measurements from the helium Lyman-$α$ forest. In the near future we will use our pipeline to infer cosmological parameters from the DESI Lyman-$α$ data.

astro-ph.CO↗

arXiv2022

A Multi-Fidelity Emulator for the Lyman-$α$ Forest Flux Power Spectrum

In this work we extend our recently developed multi-fidelity emulation technique to the simulated Lyman-$α$ forest flux power spectrum. Multi-fidelity emulation allows interpolation of simulation outputs between cosmological parameters using many cheap low-fidelity simulations and a few expensive high-fidelity simulations. Using a test suite of small box (30 Mpc/h) simulations, we show that multi-fidelity emulation is able to reproduce the Lyman-$α$ forest flux power spectrum well, achieving an average accuracy when compared to a test suite of $0.8\%$. We further show that it has a substantially increased accuracy over single-fidelity emulators, constructed using either the high or low-fidelity simulations only. In particular, it allows the extension of an existing simulation suite to smaller scales and higher redshifts.

astro-ph.CO↗

arXiv2021

Effect of Separate Initial Conditions on the Lyman-$α$ Forest in Simulations

Using a set of high resolution simulations, we quantify the effect of species specific initial transfer functions on probes of the IGM via the Lyman-$α$ forest. We focus on redshifts $2-6$, after H~{\sc i} reionization. We explore the effect of these initial conditions on measures of the thermal state of the low density IGM: the curvature, Doppler width cutoff, and Doppler width distribution. We also examine the matter and flux power spectrum, and potential consequences for constraints on warm dark matter models. We find that the curvature statistic is at most affected at the $\approx2\%$ level at $z=6$. The Doppler width cutoff parameters are affected by $\approx5\%$ for the intercept, and $\approx8\%$ for the fit slope, though this is subdominant to sample variation. The Doppler width distribution shows a $\approx30\%$ effect at $z=3$, however the distribution is not fully converged with simulation box size and resolution. The flux power spectrum is at most affected by $\approx5\%$ at high redshift and small scales. We discuss numerical convergence with simulation parameters.

astro-ph.CO↗

arXiv2020

Cosmic Filaments from Cosmic Strings

Cosmic strings are generically predicted in many extensions of the Standard Model of particle physics. We propose a new avenue for detecting cosmic strings through their effect on the filamentary structure in the cosmic web. Using cosmological simulations of the density wake from a cosmic string, we examine a variety of filament structure probes. We show that the largest effect of the cosmic string is an overdensity in the filament distribution around the string wake. The signal from the overdensity is stronger at higher redshift, and more robust with a wider field. We analyze the spatial distribution of filaments from a publicly available catalog of filaments built from SDSS galaxies. With existing data, we find no evidence for the presence of a cosmic string wake with string tension parameter $Gμ$ above $5\times 10^{-6}$. However, we project WFIRST will be able to detect a signal from such a wake at the $99\%$ confidence level at redshift $z=2$, with significantly higher confidence and the possibility of probing lower tensions ($Gμ\sim 10^{-6}$), at $z=10$. The sensitivity of this method is not competitive with constraints derived from the CMB. However, it provides an independent discovery channel at low redshift, which could be a smoking-gun in scenarios where the CMB bound can be weakened.

astro-ph.CO↗

arXiv2017

IN-SYNC VI. Identification and Radial Velocity Extraction for 100+ Double-Lined Spectroscopic Binaries in the APOGEE/IN-SYNC Fields

We present radial velocity measurements for 70 high confidence, and 34 potential binary systems in fields containing the Perseus Molecular Cloud, Pleiades, NGC 2264, and the Orion A star forming region. 18 of these systems have been previously identified as binaries in the literature. Candidate double-lined spectroscopic binaries (SB2s) are identified by analyzing the cross-correlation functions (CCFs) computed during the reduction of each APOGEE spectrum. We identify sources whose CCFs are well fit as the sum of two Lorentzians as likely binaries, and provide an initial characterization of the system based on the radial velocities indicated by that dual fit. For systems observed over several epochs, we present mass ratios and systemic velocities; for two systems with observations on eight or more epochs, and which meet our criteria for robust orbital coverage, we derive initial orbital parameters. The distribution of mass ratios for multi-epoch sources in our sample peaks at q=1, but with a significant tail toward lower q values. Tables reporting radial velocities, systemic velocities, and mass ratios are provided online. We discuss future improvements to the radial velocity extraction method we employ, as well as limitations imposed by the number of epochs currently available in the APOGEE database. The Appendix contains brief notes from the literature on each system in the sample, and more extensive notes for select sources of interest.

astro-ph.SR↗

arXiv2016

Young Stellar Clusters Containing Massive Young Stellar Objects in the VVV Survey

The purpose of this research is to study the connection of global properties of eight young stellar clusters projected in the Vista Variables in the Via Lactea (VVV) ESO Large Public Survey disk area and their young stellar object population. The analysis in based on the combination of spectroscopic parallax-based reddening and distance determinations with main sequence and pre-main sequence ishochrone fitting to determine the basic parameters (reddening, age, distance) of the sample clusters. The lower mass limit estimations show that all clusters are low or intermediate mass (between 110 and 1800 Mo), the slope Gamma of the obtained present-day mass functions of the clusters is close to the Kroupa initial mass function. On the other hand, the young stellar objects in the surrounding cluster's fields are classified by low resolution spectra, spectral energy distribution fit with theoretical predictions, and variability, taking advantage of multi-epoch VVV observations. All spectroscopically confirmed young stellar objects (except one) are found to be massive (more than 8 Mo). Using VVV and GLIMPSE color-color cuts we have selected a large number of new young stellar object candidates, which are checked for variability and 57% are found to show at least low-amplitude variations. In few cases it was possible to distinguish between YSO and AGB classification on the basis of the light curves.

astro-ph.GA↗

arXiv2015

Modeling contact formation between atomic-sized gold tips via molecular dynamics

The formation and rupture of atomic-sized contacts is modelled by means of molecular dynamics simulations. Such nano-contacts are realized in scanning tunnelling microscope and mechanically controlled break junction experiments. These instruments routinely measure the conductance across the nano-sized electrodes as they are brought into contact and separated, permitting conductance traces to be recorded that are plots of conductance versus the distance between the electrodes. One interesting feature of the conductance traces is that for some metals and geometric configurations a jump in the value of the conductance is observed right before contact between the electrodes, a phenomenon known as jump-to-contact. This paper considers, from a computational point of view, the dynamics of contact between two gold nano-electrodes. Repeated indentation of the two surfaces on each other is performed in two crystallographic orientations of face-centred cubic gold, namely (001) and (111). Ultimately, the intention is to identify the structures at the atomic level at the moment of first contact between the surfaces, since the value of the conductance is related to the minimum cross-section in the contact region. Conductance values obtained in this way are determined using first principles electronic transport calculations, with atomic configurations taken from the molecular dynamics simulations serving as input structures.

cond-mat.mes-hall↗

arXiv2005

Pairing Correlations in Finite Systems: From the weak to the strong fluctuations regime

The Particle Number Projected Generator Coordinate Method is formulated for the pairing Hamiltonian in a detailed way in the projection after variation and the variation after projection methods. The dependence of the wave functions on the generator coordinate is analyzed performing numerical applications for the most relevant collective coordinates. The calculations reproduce the exact solution in the weak, crossover and strong pairing regimes. The physical insight of the Ansatz and its numerical simplicity make this theory an excellent tool to study pairing correlations in complex situations and/or involved Hamiltonians.

cond-mat.supr-con↗