Kiril Maltsev

Massive stars undergoing iron core-collapse at the end of their evolution terminate their lives either in successful or failed supernovae (SNe). The most frequent outcomes are successful explosions, producing Type II or Type Ibc SNe. Though some stars fail to explode and continue to collapse until a black hole is formed. In this work, we formulate an explosion condition for the neutrino-heating driven SN mechanism (and for its failure) using multiple variables characterizing stellar structure at the onset of iron-core infall. We find that the final fates of massive stars are largely pre-determined already at the end of core-helium burning, and derive a simple SN recipe applicable at this stage. The SN recipe predicts the remnant type (neutron star vs. black hole) given the carbon-oxygen core mass and metallicity, while distinguishing hydrogen-rich envelope retaining vs. envelope-stripped stars. Our explodability formalism connects to theory of massive star evolution through the advanced burning phases, is in good agreement with 3D core-collapse SN simulation outcomes and consistent with a number of observational constraints from transient astronomy.
doi:10.1051/0004-6361/202554931

• binary black hole mergers and to compare with their gravitational wave observations from the latest GWTC-4 data release,
• the local, galactic and near-Earth SN explosion rates and the BH number count in the Milky Way (Quintana et al., in prep.),
• the dynamical SN feedback onto the chemical evolution of a low-metallicity dwarf galaxy (Lahén et al., in prep.), and
• the diffuse supernova neutrino background, filled by (anti)-neutrino emission from successful and failed SNe (Kresse et al., in prep.).

• Does the prediction of singularity formation in stellar gravitational collapse indicate the breakdown of General Relativity theory?
  doi:10.1142/9789811269776_0298
• Do classical-limit Schwarzschild black holes transcend the laws of thermodynamics?
  doi:10.1134/S1063772921100218

In-progress work. Details to follow.

The merger of two NSs results either in prompt collapse to a BH or in a quasi-stable hypermassive neutron star (HMNS). The HMNS is supported by differential rotation, thermal effects and repulsive nuclear forces, and continues to emit gravitational waves (GWs) until it either stabilizes or undergoes a delayed collapse to a BH. One of the methods for ground-based detection of GWs emitted from cosmic HMNSs is the matched-filtering technique. It requires efficient GW template models that predict gravitational waveforms in the time- or frequency-domain as a function of astrophysical source parameters. The templates are scanned through the interferometry data in order to identify GW signals in a noisy background. In this work, we constructed a template model for the GW emission from HMNSs remaining quasi-stable for at least 17 ms after the merger, as a function of astrophysical source parameters, using numerical relativity simulations and supervised learning techniques. The template model is fast, accurate and noise-robust enough to in future be used for signal searches in the interferometry data of the Advanced LIGO detector network at design sensitivity as well as of next-generation detectors. Under Advanced LIGO conditions, we confirmed the earlier prediction that the main GW properties (in particular, the dominant and subdominant peak oscillation frequencies) can be reliably reconstructed up to a source luminosity distance of approximately 12 Mpc, and further found that signal detection is achievable even in the case that the Equation-of-State (EoS) model adopted in the search template only crudely replicates the actual EoS at source.
doi:10.1103/PhysRevD.111.023002

In-progress work. Details to follow.

Many astrophysical studies require efficient but reliable predictive models of stellar evolution. Examples are stellar N-body dynamics, large-scale galactic evolution simulations, iterative optimization-based stellar parameter inference and rapid population synthesis. In this work, we constuct a deep-learning based surrogate model of stellar evolution, trained on evolutionary tracks pre-computed with the detailed stellar evolution code MESA while generalizing predictions over a continuous parameter space: it traces stellar evolution from the zero-age-main-sequence up to the end of core-helium burning while covering a mass range from red dwarves to 300 solar-mass star. Its main advantage over classical interpolation of stellar model grids is the speed-up, as it casts millions of predictions within tens of seconds on a 4-core CPU, while keeping the predictive errors orders of magnitude below typical observational uncertainties. In ongoing work, we use it to estimate the Initial-Mass-Function of observed solar-metallicity stellar populations.
doi:10.1051/0004-6361/202347118

In-progress work. Details to follow.