Search results for "signal processing"
showing 10 items of 2451 documents
Avoiding Boundary Effects in Wang-Landau Sampling
2003
A simple modification of the ``Wang-Landau sampling'' algorithm removes the systematic error that occurs at the boundary of the range of energy over which the random walk takes place in the original algorithm.
The chemical signature of jet-driven hypernovae
2020
Hypernovae powered by magnetic jets launched from the surface of rapidly rotating millisecond magnetars are one of the leading models to explain broad-lined Type Ic supernovae (SNe Ic-BL), and have been implicated as an important source of metal enrichment in the early Universe. We investigate the nucleosynthesis in such jet-driven hypernovae using a parameterised, but physically motivated, approach that analytically relates an artificially injected jet energy flux to the power available from the energy in differential rotation in the proto-neutron star. We find ejected $^{56}\mathrm{Ni}$ masses of $0.05\,\mathrm{M}_\odot - 0.45\,\mathrm{M}_\odot$ in our most energetic models with explosion…
Evidence for a resonant cyclotron line in IGR J16493-4348 from the Swift-BAT hard X-ray survey
2012
Resonant absorption cyclotron features are a key diagnostic tool to directly measure the strength of the magnetic field of accreting neutron stars. However, typical values for cyclotron features lie in the high-energy part of the spectrum between 20 keV and 50 keV, where detection is often damped by the low statistics from single pointed observations. We show that long-term monitoring campaign performed with Swift-BAT of persistently, but faint, accreting high-mass X-ray binaries is able to reveal in their spectra the presence of cyclotron features. We extracted the average Swift-BAT 15-150 keV spectrum from the 54 months long Swift-BAT survey of the high-mass X-ray source IGR J16493-4348. …
Testing reflection features in 4U 1705-44 with XMM-Newton, BeppoSAX, and RXTE in the hard and soft states
2012
We use data of the bright atoll source 4U 1705-44 taken with XMM-Newton, BeppoSAX and RXTE both in the hard and in the soft state to perform a self-consistent study of the reflection component in this source. Although the data from these X-ray observatories are not simultaneous, the spectral decomposition is shown to be consistent among the different observations, when the source flux is similar. We therefore select observations performed at similar flux levels in the hard and soft state in order to study the spectral shape in these two states in a broad band (0.1-200 keV) energy range, with good energy resolution, and using self-consistent reflection models. These reflection models provide…
Heavy sterile neutrinos in stellar core-collapse
2018
We perform spherically symmetric simulations of the core collapse of a single progenitor star of zero age main sequence mass $M_{\rm ZAMS} = 15 \, M_{\odot}$ with two models of heavy sterile neutrinos in the mass range of hundred MeV$/c^2$. According to both models, these hypothetical particles are copiously produced in the center, stream outwards a subsequently decay releasing energy into final states (including neutrinos) of the Standard Model. We find that they can lead to a successful explosion in otherwise non-exploding progenitors. Depending on their unknown parameters (e.g., mass and coupling constants with matter), we obtain either no explosion or an explosion of one of two types, i…
The damped harmonic oscillator in deformation quantization
2005
We propose a new approach to the quantization of the damped harmonic oscillator in the framework of deformation quantization. The quantization is performed in the Schr\"{o}dinger picture by a star-product induced by a modified "Poisson bracket". We determine the eigenstates in the damped regime and compute the transition probability between states of the undamped harmonic oscillator after the system was submitted to dissipation.
DEFORMATION QUANTIZATION OF COADJOINT ORBITS
2000
A method for the deformation quantization of coadjoint orbits of semisimple Lie groups is proposed. It is based on the algebraic structure of the orbit. Its relation to geometric quantization and differentiable deformations is explored.
Domain walls in supersymmetric QCD: The taming of the zoo
2000
We provide a unified picture of the domain wall spectrum in supersymmetric QCD with Nc colors and Nf flavors of quarks in the (anti-) fundamental representation. Within the framework of the Veneziano-Yankielowicz-Taylor effective Lagrangian, we consider domain walls connecting chiral symmetry breaking vacua, and we take the quark masses to be degenerate. For Nf/Ncm** there is no domain wall. We numerically determine m* and m** as a function of Nf/Nc, and we find that m** approaches a constant value in the limit that this ratio goes to one.
Bicoherent-State Path Integral Quantization of a non-Hermitian Hamiltonian
2020
We introduce, for the first time, bicoherent-state path integration as a method for quantizing non-hermitian systems. Bicoherent-state path integrals arise as a natural generalization of ordinary coherent-state path integrals, familiar from hermitian quantum physics. We do all this by working out a concrete example, namely, computation of the propagator of a certain quasi-hermitian variant of Swanson's model, which is not invariant under conventional $PT$-transformation. The resulting propagator coincides with that of the propagator of the standard harmonic oscillator, which is isospectral with the model under consideration by virtue of a similarity transformation relating the corresponding…
Machine learning for energy cost modelling in wastewater treatment plants.
2018
Understanding the energy cost structure of wastewater treatment plants is a relevant topic for plant managers due to the high energy costs and significant saving potentials. Currently, energy cost models are generally generated using logarithmic, exponential or linear functions that could produce not accurate results when the relationship between variables is highly complex and non-linear. In order to overcome this issue, this paper proposes a new methodology based on machine-learning algorithms that perform better with complex datasets. In this paper, machine learning was used to generate high-performing energy cost models for wastewater treatment plants, using a database of 317 wastewater…