1,664 research outputs found
Relativistic calculations of charge transfer probabilities in U92+ - U91+(1s) collisions using the basis set of cubic Hermite splines
A new approach for solving the time-dependent two-center Dirac equation is
presented. The method is based on using the finite basis set of cubic Hermite
splines on a two-dimensional lattice. The Dirac equation is treated in rotating
reference frame. The collision of U92+ (as a projectile) and U91+ (as a target)
is considered at energy E_lab=6 MeV/u. The charge transfer probabilities are
calculated for different values of the impact parameter. The obtained results
are compared with the previous calculations [I. I. Tupitsyn et al., Phys. Rev.
A 82, 042701 (2010)], where a method based on atomic-like Dirac-Sturm orbitals
was employed. This work can provide a new tool for investigation of quantum
electrodynamics effects in heavy-ion collisions near the supercritical regime
On the meteor trail spectra
Meteor radiation appears as a result of collisions between meteoroid atoms and air molecules. Depending on duration, this radiation is usually divided into the following types: radiation of the meteor head; radiation of a coma surrounding or immediately following the meteor head; radiation of a trail formed as a result of fragments lagging behind or by the afterglow; and radiation of a meteor train forming from a tail as a result of various chemical and dynamical processes. To investigate physical processes caused by each of the above types, it is necessary to obtain the corresponding experimental data. The physical processes of the radiation and the measurement of the experimental data is discussed
Relativistic calculations of the U91+(1s)-U92+ collision using the finite basis set of cubic Hermite splines on a lattice in coordinate space
A new method for solving the time-dependent two-center Dirac equation is
developed. The approach is based on the using of the finite basis of cubic
Hermite splines on a three-dimensional lattice in the coordinate space. The
relativistic calculations of the excitation and charge-transfer probabilities
in the U91+(1s)-U92+ collisions in two and three dimensional approaches are
performed. The obtained results are compared with our previous calculations
employing the Dirac-Sturm basis sets [I.I. Tupitsyn et al., Phys. Rev. A 82,
042701 (2010)]. The role of the negative-energy Dirac spectrum is investigated
within the monopole approximation
Relativistic calculations of the K-K charge transfer and K-vacancy production probabilities in low-energy ion-atom collisions
The previously developed technique for evaluation of charge-transfer and
electron-excitation processes in low-energy heavy-ion collisions [I.I. Tupitsyn
et al., Phys. Rev. A 82, 042701(2010)] is extended to collisions of ions with
neutral atoms. The method employs the active electron approximation, in which
only the active electron participates in the charge transfer and excitation
processes while the passive electrons provide the screening DFT potential. The
time-dependent Dirac wave function of the active electron is represented as a
linear combination of atomic-like Dirac-Fock-Sturm orbitals, localized at the
ions (atoms). The screening DFT potential is calculated using the overlapping
densities of each ions (atoms), derived from the atomic orbitals of the passive
electrons. The atomic orbitals are generated by solving numerically the
one-center Dirac-Fock and Dirac-Fock-Sturm equations by means of a
finite-difference approach with the potential taken as the sum of the exact
reference ion (atom) Dirac-Fock potential and of the Coulomb potential from the
other ion within the monopole approximation. The method developed is used to
calculate the K-K charge transfer and K-vacancy production probabilties for the
Ne -- F collisions at the F projectile
energies 130 keV/u and 230 keV/u. The obtained results are compared with
experimental data and other theoretical calculations. The K-K charge transfer
and K-vacancy production probabilities are also calculated for the Xe --
Xe collision.Comment: 16 pages, 4 figure
Weakly-nonlocal Symplectic Structures, Whitham method, and weakly-nonlocal Symplectic Structures of Hydrodynamic Type
We consider the special type of the field-theoretical Symplectic structures
called weakly nonlocal. The structures of this type are in particular very
common for the integrable systems like KdV or NLS. We introduce here the
special class of the weakly nonlocal Symplectic structures which we call the
weakly nonlocal Symplectic structures of Hydrodynamic Type. We investigate then
the connection of such structures with the Whitham averaging method and propose
the procedure of "averaging" of the weakly nonlocal Symplectic structures. The
averaging procedure gives the weakly nonlocal Symplectic Structure of
Hydrodynamic Type for the corresponding Whitham system. The procedure gives
also the "action variables" corresponding to the wave numbers of -phase
solutions of initial system which give the additional conservation laws for the
Whitham system.Comment: 64 pages, Late
Quasiperiodic functions theory and the superlattice potentials for a two-dimensional electron gas
We consider Novikov problem of the classification of level curves of
quasiperiodic functions on the plane and its connection with the conductivity
of two-dimensional electron gas in the presence of both orthogonal magnetic
field and the superlattice potentials of special type. We show that the
modulation techniques used in the recent papers on the 2D heterostructures
permit to obtain the general quasiperiodic potentials for 2D electron gas and
consider the asymptotic limit of conductivity when . Using the
theory of quasiperiodic functions we introduce here the topological
characteristics of such potentials observable in the conductivity. The
corresponding characteristics are the direct analog of the "topological
numbers" introduced previously in the conductivity of normal metals.Comment: Revtex, 16 pages, 12 figure
Π£ΡΠΈΠ»ΠΈΠ·Π°ΡΠΈΡ ΡΡΠ»ΡΡΠΈΠ΄Π½ΠΎ-ΠΌΡΡΡΡΠΊΠΎΠ²ΠΈΡΡΠΎΠ³ΠΎ ΠΊΠ΅ΠΊΠ°
When processing sulfide copper-zinc concentrates at copper smelters, sulfide-arsenic cakes are formed, which are subject to disposal. To solve the global environmental problem of arsenic in the metallurgical and mining industries, it must be reliably concentrated and fixed in technological flows with subsequent waste disposal. The fusion of arsenic cake with elemental sulfur leads to the formation of vitreous sulfides, which are less toxic in comparison with dispersed powdered cake, homogeneous and compact in shape. The fusion product is represented by non-stoichiometric arsenic sulfide, similar in composition to As2S5. The high chemical stability of glassy arsenic sulfides is confirmed by the results of leaching by TCLP method. The fusion products have 100 times lower solubility compared to the initial cake. Achieving the solubility of arsenic in the alloy below the threshold concentration (5 mg/dm3 ) makes it possible to recommend the disposal of arsenic cake by fusing it with elemental sulfur. The fusion products belong to non-hazardous waste and are suitable for long-term storage. The composition and structure of cake fusions with iron powder have been studied. New compounds of variable composition were identified in the fused samples: arsenides and sulfides of iron, arsenic sulfides and arsenopyrites. Studies have shown that the products of fusion with iron have a solubility 10β15 times lower than the arsenic compounds in the initial cake but above the threshold concentration as per TCLP method. Therefore, fusion with iron cannot be recommended for practical use for the disposal of arsenic cakes.ΠΡΠΈ ΠΏΠ΅ΡΠ΅ΡΠ°Π±ΠΎΡΠΊΠ΅ ΡΡΠ»ΡΡΠΈΠ΄Π½ΡΡ
ΠΌΠ΅Π΄Π½ΠΎ-ΡΠΈΠ½ΠΊΠΎΠ²ΡΡ
ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΎΠ² Π½Π° ΠΌΠ΅Π΄Π΅ΠΏΠ»Π°Π²ΠΈΠ»ΡΠ½ΡΡ
Π·Π°Π²ΠΎΠ΄Π°Ρ
ΠΎΠ±ΡΠ°Π·ΡΡΡΡΡ ΡΡΠ»ΡΡΠΈΠ΄Π½ΠΎΠΌΡΡΡΡΠΊΠΎΠ²ΠΈΡΡΡΠ΅ ΠΊΠ΅ΠΊΠΈ, ΠΏΠΎΠ΄Π»Π΅ΠΆΠ°ΡΠΈΠ΅ ΡΡΠΈΠ»ΠΈΠ·Π°ΡΠΈΠΈ. ΠΠ»Ρ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΌΡΡΡΡΠΊΠ° Π² ΠΌΠ΅ΡΠ°Π»Π»ΡΡΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈ Π³ΠΎΡΠ½ΠΎΠ΄ΠΎΠ±ΡΠ²Π°ΡΡΠ΅ΠΉ ΠΎΡΡΠ°ΡΠ»ΡΡ
ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ ΠΎΠ½ Π΄ΠΎΠ»ΠΆΠ΅Π½ Π±ΡΡΡ Π½Π°Π΄Π΅ΠΆΠ½ΠΎ ΡΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠΈΡΠΎΠ²Π°Π½ ΠΈ ΠΈΠΌΠΌΠΎΠ±ΠΈΠ»ΠΈΠ·ΠΎΠ²Π°Π½ Π² ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΡΠΎΠΊΠ°Ρ
Ρ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠΈΠΌ ΡΠ΄Π°Π»Π΅Π½ΠΈΠ΅ΠΌ ΠΎΡΡ
ΠΎΠ΄ΠΎΠ². Π‘ΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΠ΅ ΠΌΡΡΡΡΠΊΠΎΠ²ΠΈΡΡΠΎΠ³ΠΎ ΠΊΠ΅ΠΊΠ° Ρ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠΎΠΉ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠ΅ΠΊΠ»ΠΎΠ²ΠΈΠ΄Π½ΡΡ
ΡΡΠ»ΡΡΠΈΠ΄ΠΎΠ², ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠ΅Π½Π΅Π΅ ΡΠΎΠΊΡΠΈΡΠ½Ρ Π² ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΈ Ρ Π΄ΠΈΡΠΏΠ΅ΡΡΠ½ΡΠΌ ΠΏΠΎΡΠΎΡΠΊΠΎΠΎΠ±ΡΠ°Π·Π½ΡΠΌ ΠΊΠ΅ΠΊΠΎΠΌ, ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½Ρ ΠΈ ΠΎΠ±Π»Π°Π΄Π°ΡΡ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ ΡΠΎΡΠΌΠΎΠΉ. ΠΡΠΎΠ΄ΡΠΊΡ ΡΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ Π½Π΅ΡΡΠ΅Ρ
ΠΈΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΡΠ»ΡΡΠΈΠ΄ΠΎΠΌ ΠΌΡΡΡΡΠΊΠ°, Π±Π»ΠΈΠ·ΠΊΠΈΠΌ ΠΏΠΎ ΡΠΎΡΡΠ°Π²Ρ ΠΊ As2S5. ΠΡΡΠΎΠΊΠ°Ρ Ρ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡ ΡΡΠ΅ΠΊΠ»ΠΎΠΎΠ±ΡΠ°Π·Π½ΡΡ
ΡΡΠ»ΡΡΠΈΠ΄ΠΎΠ² ΠΌΡΡΡΡΠΊΠ° ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π°Π΅ΡΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌΠΈ Π²ΡΡΠ΅Π»Π°ΡΠΈΠ²Π°Π½ΠΈΡ ΠΏΠΎ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ΅ TCLP. ΠΡΠΎΠ΄ΡΠΊΡΡ ΡΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΡ ΠΈΠΌΠ΅ΡΡ Π² 100 ΡΠ°Π· ΠΌΠ΅Π½ΡΡΡΡ ΡΠ°ΡΡΠ²ΠΎΡΠΈΠΌΠΎΡΡΡ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΈΡΡ
ΠΎΠ΄Π½ΡΠΌ ΠΊΠ΅ΠΊΠΎΠΌ. ΠΠΎΡΡΠΈΠΆΠ΅Π½ΠΈΠ΅ ΡΠ°ΡΡΠ²ΠΎΡΠΈΠΌΠΎΡΡΠΈ ΠΌΡΡΡΡΠΊΠ° Π² ΡΠΏΠ»Π°Π²Π΅ Π½ΠΈΠΆΠ΅ ΠΏΠΎΡΠΎΠ³ΠΎΠ²ΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ (5 ΠΌΠ³/Π΄ΠΌ3 ) ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°ΡΡ ΡΡΠΈΠ»ΠΈΠ·Π°ΡΠΈΡ ΠΌΡΡΡΡΠΊΠΎΠ²ΠΈΡΡΠΎΠ³ΠΎ ΠΊΠ΅ΠΊΠ° ΡΠΏΠΎΡΠΎΠ±ΠΎΠΌ ΡΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΡ Π΅Π³ΠΎ Ρ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠΎΠΉ. ΠΡΠΎΠ΄ΡΠΊΡΡ ΡΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΡ ΠΎΡΠ½ΠΎΡΡΡΡΡ ΠΊ Π½Π΅ΠΎΠΏΠ°ΡΠ½ΡΠΌ ΠΎΡΡ
ΠΎΠ΄Π°ΠΌ ΠΈ ΠΏΡΠΈΠ³ΠΎΠ΄Π½Ρ Π΄Π»Ρ Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ Ρ
ΡΠ°Π½Π΅Π½ΠΈΡ. ΠΠ·ΡΡΠ΅Π½Ρ ΡΠΎΡΡΠ°Π² ΠΈ ΡΡΡΡΠΊΡΡΡΠ° ΡΠΏΠ»Π°Π²ΠΎΠ² ΠΊΠ΅ΠΊΠ° Ρ ΠΆΠ΅Π»Π΅Π·Π½ΡΠΌ ΠΏΠΎΡΠΎΡΠΊΠΎΠΌ. Π ΡΠΏΠ»Π°Π²Π»Π΅Π½Π½ΡΡ
ΠΎΠ±ΡΠ°Π·ΡΠ°Ρ
Π²ΡΡΠ²Π»Π΅Π½Ρ Π½ΠΎΠ²ΡΠ΅ ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΡ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΠΎΡΡΠ°Π²Π°: Π°ΡΡΠ΅Π½ΠΈΠ΄Ρ ΠΈ ΡΡΠ»ΡΡΠΈΠ΄Ρ ΠΆΠ΅Π»Π΅Π·Π°, ΡΡΠ»ΡΡΠΈΠ΄Ρ ΠΌΡΡΡΡΠΊΠ° ΠΈ Π°ΡΡΠ΅Π½ΠΎΠΏΠΈΡΠΈΡΡ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ, ΡΡΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΡ ΡΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΡ Ρ ΠΆΠ΅Π»Π΅Π·ΠΎΠΌ ΠΎΠ±Π»Π°Π΄Π°ΡΡ ΡΠ°ΡΡΠ²ΠΎΡΠΈΠΌΠΎΡΡΡΡ Π² 10β15 ΡΠ°Π· ΠΌΠ΅Π½ΡΡΠ΅ΠΉ, ΡΠ΅ΠΌ ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΡ ΠΌΡΡΡΡΠΊΠ° Π² ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠΌ ΠΊΠ΅ΠΊΠ΅, Π½ΠΎ Π²ΡΡΠ΅ ΠΏΠΎΡΠΎΠ³ΠΎΠ²ΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ ΠΏΠΎ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ΅ TCLP. ΠΠΎΡΡΠΎΠΌΡ ΡΠΏΠ»Π°Π²Π»Π΅Π½ΠΈΠ΅ Ρ ΠΆΠ΅Π»Π΅Π·ΠΎΠΌ Π½Π΅ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°Π½ΠΎ ΠΊ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΌΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π΄Π»Ρ ΡΡΠΈΠ»ΠΈΠ·Π°ΡΠΈΠΈ ΠΌΡΡΡΡΠΊΠΎΠ²ΠΈΡΡΡΡ
ΠΊΠ΅ΠΊΠΎΠ²
Scalable stellar evolution forecasting: Deep learning emulation vs. hierarchical nearest neighbor interpolation
Many astrophysical applications require efficient yet reliable forecasts of
stellar evolution tracks. One example is population synthesis, which generates
forward predictions of models for comparison with observations. The majority of
state-of-the-art population synthesis methods are based on analytic fitting
formulae to stellar evolution tracks that are computationally cheap to sample
statistically over a continuous parameter range. Running detailed stellar
evolution codes, such as MESA, over wide and densely sampled parameter grids is
prohibitively expensive computationally, while stellar-age based linear
interpolation in-between sparsely sampled grid points leads to intolerably
large systematic prediction errors. In this work, we provide two solutions of
automated interpolation methods that find satisfactory trade-off points between
cost-efficiency and accuracy. We construct a timescale-adapted evolutionary
coordinate and use it in a two-step interpolation scheme that traces the
evolution of stars from zero age main sequence all the way to the end of core
helium burning while covering a mass range from to . The feedforward neural network regression model (first
solution) that we train to predict stellar surface variables can make millions
of predictions, sufficiently accurate over the entire parameter space, within
tens of seconds on a 4-core CPU. The hierarchical nearest neighbor
interpolation algorithm (second solution) that we hard-code to the same end
achieves even higher predictive accuracy, the same algorithm remains applicable
to all stellar variables evolved over time, but it is two orders of magnitude
slower. Our methodological framework is demonstrated to work on the MIST data
set. Finally, we discuss prospective applications and provide guidelines how to
generalize our methods to higher dimensional parameter spaces.Comment: Submitted to A&
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