Catching a star before explosion: the luminous blue variable progenitor of SN 2015bh

In this paper we analyse the pre-explosion spectrum of SN2015bh by performing radiative transfer simulations using the CMFGEN code. This object has attracted significant attention due to its remarkable similarity to SN2009ip in both its pre- and post-explosion behaviour. They seem to belong to a class of events for which the fate as a genuine core-collapse supernova or a non-terminal explosion is still under debate. Our CMFGEN models suggest that the progenitor of SN2015bh had an effective temperature between 8700 and 10000 K, luminosity in the range ~ 1.8-4.74e6 Lsun, contained at least 25% H in mass at the surface, and half-solar Fe abundances. The results also show that the progenitor of SN 2015bh generated an extended wind with a mass-loss rate of ~ 6e-4 to 1.5e-3 Msun/yr and a velocity of 1000 km/s. We determined that the wind extended to at least 2.57e14 cm and lasted for at least 30 days prior to the observations, releasing 5e-5 Msun into the circumstellar medium. In analogy to 2009ip, we propose that this is the material that the explosive ejecta could interact at late epochs, perhaps producing observable signatures that can be probed with future observations. We conclude that the progenitor of SN 2015bh was most likely a warm luminous blue variable of at least 35 Msun before the explosion. Considering the high wind velocity, we cannot exclude the possibility that the progenitor was a Wolf-Rayet star that inflated just before the 2013 eruption, similar to HD5980 during its 1994 episode. If the star survived, late-time spectroscopy may reveal either a similar LBV or a Wolf-Rayet star, depending on the mass of the H envelope before the explosion. If the star exploded as a genuine SN, 2015bh would be a remarkable case of a successful explosion after black-hole formation in a star with a possible minimum mass 35 Msun at the pre-SN stage.Comment: 13 pages, 10 figures, accepted for publication in A&

The diversity of supernovae and impostors shortly after explosion

Observational surveys are now able to detect an increasing number of transients, such as core-collapse supernovae (SN) and powerful non-terminal outbursts (SN impostors). Dedicated spectroscopic facilities can follow up these events shortly after detection. Here we investigate the properties of these explosions at early times. We use the radiative transfer code CMFGEN to build an extensive library of spectra simulating the interaction of supernovae and their progenitor's winds/circumstellar medium (CSM). We consider a range of progenitor mass-loss rates (Mdot = 5e-4 to 1e-2 Msun/yr), abundances (solar, CNO-processed, and He-rich), and SN luminosities (L = 1.9e8 to 2.5e10 Lsun). The models simulate events ~1 day after explosion, and we assume a fixed location of the shock front as Rin=8.6e13 cm. We show that the large range of massive star properties at the pre-SN stage causes a diversity of early-time interacting SN and impostors. We identify three main classes of early-time spectra consisting of relatively high-ionisation (e.g. Ovi), medium-ionisation (e.g. Ciii), and low-ionisation lines (e.g. Feii/iii). They are regulated by L and the CSM density. Given a progenitor wind velocity Vinf, our models also place a lower limit of Mdot > 5e-4 (Vinf/150 km/s) Msun/yr for detection of CSM interaction signatures in observed spectra. Early-time SN spectra should provide clear constraints on progenitors by measuring H, He, and CNO abundances if the progenitors come from single stars. The connections are less clear considering the effects of binary evolution. Yet, our models provide a clear path for linking the final stages of massive stars to their post-explosion spectra at early times, and guiding future observational follow-up of transients with facilities such as the Zwicky Transient Facility.Comment: Accepted for publication in A&A. 14 pages, 7 figure

Nonnegative/binary matrix factorization with a D-Wave quantum annealer

D-Wave quantum annealers represent a novel computational architecture and have attracted significant interest, but have been used for few real-world computations. Machine learning has been identified as an area where quantum annealing may be useful. Here, we show that the D-Wave 2X can be effectively used as part of an unsupervised machine learning method. This method can be used to analyze large datasets. The D-Wave only limits the number of features that can be extracted from the dataset. We apply this method to learn the features from a set of facial images

Sum of Three Cubes via Optimisation

By first solving the equation $x^3+y^3+z^3=k$ with fixed $k$ for $z$ and then considering the distance to the nearest integer function of the result, we turn the sum of three cubes problem into an optimisation one. We then apply three stochastic optimisation algorithms to this function in the case with $k=2$, where there are many known solutions. The goal is to test the effectiveness of the method in searching for integer solutions. The algorithms are a modification of particle swarm optimisation and two implementations of simulated annealing. We want to compare their effectiveness as measured by the running times of the algorithms. To this end, we model the time data by assuming two underlying probability distributions -- exponential and log-normal, and calculate some numerical characteristics for them. Finally, we evaluate the statistical distinguishability of our models with respect to the geodesic distance in the manifold with the corresponding Fisher information metric.Comment: 21 pages without the appendices. Any comments will be greatly appreciated

Simulation of Mobile Ambients by P Systems. Part 2

Ambient calculus is a theory which deals with mobile computing and computation and encompasses such notions as mobile agents, the ambients where the agents interact and the mobility of the ambients themselves. P systems is a formalism which abstracts from the structure and functioning of living cells and describes distributed parallel computing devices with multiset of objects processing. Ambient calculus and membrane computing are based on the same concepts and structures though they are developed in di®erent areas of computer science. The purpose of our work now is to express ambient calculus by means of P systems, namely by tissue P systems with dynamic network of membranes