Dreaming of atmospheres

Here we introduce the RobERt (Robotic Exoplanet Recognition) algorithm for the classification of exoplanetary emission spectra. Spectral retrievals of exoplanetary atmospheres frequently requires the preselection of molecular/atomic opacities to be defined by the user. In the era of open-source, automated and self-sufficient retrieval algorithms, manual input should be avoided. User dependent input could, in worst case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is based on deep belief neural (DBN) networks trained to accurately recognise molecular signatures for a wide range of planets, atmospheric thermal profiles and compositions. Reconstructions of the learned features, also referred to as `dreams' of the network, indicate good convergence and an accurate representation of molecular features in the DBN. Using these deep neural networks, we work towards retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.Comment: ApJ accepte

Q-dependence of the inelastic neutron scattering cross section for molecular spin clusters with high molecular symmetry

For powder samples of polynuclear metal complexes the dependence of the inelastic neutron scattering intensity on the momentum transfer Q is known to be described by a combination of so called interference terms. They reflect the interplay between the geometrical structure of the compound and the spatial properties of the wave functions involved in the transition. In this work, it is shown that the Q-dependence is strongly interrelated with the molecular symmetry of molecular nanomagnets, and, if the molecular symmetry is high enough, is actually completely determined by it. A general formalism connecting spatial symmetry and interference terms is developed. The arguments are detailed for cyclic spin clusters, as experimentally realized by e.g. the octanuclear molecular wheel Cr8, and the star like tetranuclear cluster Fe4.Comment: 8 pages, 1 figures, REVTEX

A new approach to analysing HST spatial scans: the transmission spectrum of HD 209458 b

The Wide Field Camera 3 (WFC3) on Hubble Space Telescope (HST) is currently one of the most widely used instruments for observing exoplanetary atmospheres, especially with the use of the spatial scanning technique. An increasing number of exoplanets have been studied using this technique as it enables the observation of bright targets without saturating the sensitive detectors. In this work we present a new pipeline for analyzing the data obtained with the spatial scanning technique, starting from the raw data provided by the instrument. In addition to commonly used correction techniques, we take into account the geometric distortions of the instrument, whose impact may become important when combined to the scanning process. Our approach can improve the photometric precision for existing data and also push further the limits of the spatial scanning technique, as it allows the analysis of even longer spatial scans. As an application of our method and pipeline, we present the results from a reanalysis of the spatially scanned transit spectrum of HD 209458 b. We calculate the transit depth per wavelength channel with an average relative uncertainty of 40 ppm. We interpret the final spectrum with T-Rex, our fully Bayesian spectral retrieval code, which confirms the presence of water vapor and clouds in the atmosphere of HD 209458 b. The narrow wavelength range limits our ability to disentangle the degeneracies between the fitted atmospheric parameters. Additional data over a broader spectral range are needed to address this issue.Comment: 13 pages, 15 figures, 7 tables, Accepted for publication in Ap

Field-induced level crossings in spin clusters: Thermodynamics and magneto-elastic instability

Quantum spin clusters with dominant antiferromagnetic Heisenberg exchange interactions typically exhibit a sequence of field-induced level crossings in the ground state as function of magnetic field. For fields near a level crossing, the cluster can be approximated by a two-level Hamiltonian at low temperatures. Perturbations, such as magnetic anisotropy or spin-phonon coupling, sensitively affect the behavior at the level-crossing points. The general two-level Hamiltonian of the spin system is derived in first-order perturbation theory, and the thermodynamic functions magnetization, magnetic torque, and magnetic specific heat are calculated. Then a magneto-elastic coupling is introduced and the effective two-level Hamilitonian for the spin-lattice system derived in the adiabatic approximation of the phonons. At the level crossings the system becomes unconditionally unstable against lattice distortions due to the effects of magnetic anisotropy. The resultant magneto-elastic instabilities at the level crossings are discussed, as well as the magnetic behavior.Comment: 13 pages, 8 figures, REVTEX

Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series Transformer

Astrophysical light curves are particularly challenging data objects due to the intensity and variety of noise contaminating them. Yet, despite the astronomical volumes of light curves available, the majority of algorithms used to process them are still operating on a per-sample basis. To remedy this, we propose a simple Transformer model –called Denoising Time Series Transformer (DTST)– and show that it excels at removing the noise and outliers in datasets of time series when trained with a masked objective, even when no clean targets are available. Moreover, the use of self-attention enables rich and illustrative queries into the learned representations. We present experiments on real stellar light curves from the Transiting Exoplanet Space Satellite (TESS), showing advantages of our approach compared to traditional denoising techniques1

Low temperature magnetization and the excitation spectrum of antiferromagnetic Heisenberg spin rings

Accurate results are obtained for the low temperature magnetization versus magnetic field of Heisenberg spin rings consisting of an even number N of intrinsic spins s = 1/2, 1, 3/2, 2, 5/2, 3, 7/2 with nearest-neighbor antiferromagnetic (AF) exchange by employing a numerically exact quantum Monte Carlo method. A straightforward analysis of this data, in particular the values of the level-crossing fields, provides accurate results for the lowest energy eigenvalue E(N,S,s) for each value of the total spin quantum number S. In particular, the results are substantially more accurate than those provided by the rotational band approximation. For s <= 5/2, data are presented for all even N <= 20, which are particularly relevant for experiments on finite magnetic rings. Furthermore, we find that for s > 1 the dependence of E(N,S,s) on s can be described by a scaling relation, and this relation is shown to hold well for ring sizes up to N = 80 for all intrinsic spins in the range 3/2 <= s <= 7/2. Considering ring sizes in the interval 8 <= N <= 50, we find that the energy gap between the ground state and the first excited state approaches zero proportional to 1/N^a, where a = 0.76 for s = 3/2 and a = 0.84 for s = 5/2. Finally, we demonstrate the usefulness of our present results for E(N,S,s) by examining the Fe12 ring-type magnetic molecule, leading to a new, more accurate estimate of the exchange constant for this system than has been obtained heretofore.Comment: Submitted to Physical Review B, 10 pages, 10 figure