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ELECTRON–ION SCATTERING IN DENSE MULTI-COMPONENT PLASMAS: APPLICATION TO THE OUTER CRUST OF AN ACCRETING NEUTRON STAR

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Published 2009 September 3 © 2009. The American Astronomical Society. All rights reserved.
, , Citation J. Daligault and S. Gupta 2009 ApJ 703 994 DOI 10.1088/0004-637X/703/1/994

0004-637X/703/1/994

ABSTRACT

The thermal conductivity of a dense multi-component plasma (MCP) is critical to the modeling of accreting neutron stars. To this end, we perform large-scale molecular dynamics simulations to calculate the static structure factor of the dense MCP in the neutron star crust from near the photosphere-ocean boundary to the vicinity of the neutron drip point. The structure factors are used to validate a microscopic linear mixing rule that is valid for arbitrarily complex plasmas over a wide range of Coulomb couplings. The microscopic mixing rule in turn implies and validates the linear mixing rule (LMR) for the equation of state properties and also the LMR for the electrical and thermal conductivities of dense MCPs. To make our result as useful as possible, for the specific cases of electrical and thermal conductivities, we provide a simple analytic fit that is valid for arbitrarily complex MCPs over a wide range of Coulomb couplings. We compute the thermal conductivity for a representative compositional profile of the outer crust of an accreting neutron star in which hundreds of nuclear species can be present. We utilize our results to re-examine the so-called impurity parameter formalism as used to characterize impure plasmas.

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1. INTRODUCTION

The thermal conductivity of a dense multi-component plasma (MCP) is critical to the modeling of the quiescent and explosive emission from the surface of accreting neutron stars. Much effort has been expended in accurately calculating the magnitude and location of crustal heating from nuclear reactions using modern nuclear models for energetics and reaction rates such as those in Haensel & Zdunik (1990), Haensel & Zdunik (2003), Gupta et al. (2007), Haensel & Zdunik (2008), and Gupta et al. (2008). However, crust thermal conductivity is of equal importance in determining the thermal structure of an accreting neutron star and the uncertainty in this quantity is compounded by the difficulties in understanding the phase diagram of a dense plasma with hundreds of nuclear species spread over several mass chains.

For illustration of the importance of thermal conductivity, we now describe two phenomena that have attracted much attention in the observational community: (1) superbursts and (2) quasi-persistent transients.

  • 1.  
    Long-term monitoring of low-mass X-ray binaries (LMXBs) by instruments on board BeppoSAX and RXTE has yielded a wealth of phenomena on accreting neutron stars. For example, superbursts, lasting roughly a thousand times as long as Type I X-ray bursts and recurring on timescales of a year, have energies ∼103 times that of a typical X-ray burst. For the source 4U 1636 − 53 three superbursts were observed within 4.7 yr (Wijnands 2001; Kuulkers et al. 2004). These still mysterious explosions are thought to result from unstable 12C burning (Cumming & Bildsten 2001) at column depths ∼1012 g cm−2 (see Kuulkers et al. 2004 for a review). The crust thermal gradient dictates whether a temperature conducive to unstable 12C burning can exist at an ignition depth inferred from observations of superburst recurrence times. A critical ingredient in predicting the thermal gradient that a neutron star crust can support is the thermal conductivity of the impure crust that is expected when Type I X-ray bursts drive a rapid-proton-capture, or "rp-process" on the neutron star surface. Models that treat the crust thermal conductivity as uncertain also have to grapple with the large uncertainties in core neutrino luminosity from URCA processes. In this work we show that if the composition of the crust can be accurately computed, then so can crust thermal conductivity.
  • 2.  
    Another exciting application of accurate conductivities appears in modeling the cooling light curves of transiently accreting neutron stars. In the case of transients with accretion episodes of sufficient duration to heat the crust by deep crustal nuclear reactions (quasi-persistent transients), the thermal relaxation behavior gives us a new observational window into the physics of matter at very high density. Recently, Shternin et al. (2007) and Cackett et al. (2006) have presented detailed analyses of two such quasi-persistent transients, namely KS 1731 − 260 and MXB 1659 − 29. Since a critical determinant of the time evolution of surface flux is the thermal diffusion timescale as a function of depth in the neutron star, the conductivity plays an important role in modeling the cooling light curve of transients.

To reduce the uncertainties in modeling the thermal profiles of persistent and transient accretors, we have begun a program of accurately computing the microphysical quantities that influence thermal structure. For the impure ashes from an X-ray burst, it is crucial to ascertain the composition evolution of these ashes with increasing depth in the neutron star crust. It is upon this composition profile that all other thermal structure determinants depend, most notably

  • 1.  
    nuclear heating due to non-equilibrium electron captures, neutron reactions, and pycnonuclear fusion,
  • 2.  
    the thermal conductivity κ, and
  • 3.  
    the neutrino emissivity epsilonν from neutrino-pair bremsstrahlung (NPB).

The compositional profile of the outer crust (where there is negligible free neutron abundance) starting with a realistic MCP of XRB ashes was calculated for the first time using global nuclear structure and reaction rate inputs to a large reaction network in Gupta et al. (2007). By a "composition profile" we refer to the changing composition from the top of the crust (X-ray burst ashes) all the way to neutron-drip. This spans four orders of magnitude in density (roughly ∼107.5 to ∼1011.5 g cm−3) allowing for a large range in Coulomb coupling. It is this compositional profile that we employ in the present work to investigate the resulting crustal microphysics since it has tens to hundreds of abundant species at each depth. Thus, we have an ideal site to explore the physics of strongly coupled MCPs.

In this paper, we perform large-scale molecular dynamics (MD) simulations to calculate the structure factor of the dense MCP in the neutron star crust from near the photosphere-ocean boundary to the vicinity of the neutron drip point. The structure factors are used to validate a microscopic linear mixing rule (MLMR) that is valid for arbitrarily complex MCPs over a wide range of Coulomb couplings. The MLMR in turn implies and validates the mixing rule for the equation of state properties recently proposed for MCPs by Potekhin et al. (2009), and a mixing rule for the electrical and thermal conductivities of MCPs. These mixing rules provide a simple recipe to compute the physical properties of plasma mixtures, such as would be found in terrestrial experiments (e.g., inertial confinement fusion (ICF) plasmas.) In general, the MLMR implies a LMR for any quantity that is an integral of the structure factor, such as the neutrino pair-Bremsstrahlung emissivity. To make our result as useful as possible for the compact object modeling community, for the specific cases of electrical and thermal conductivities, we provide a simple analytic fit that is valid for arbitrarily complex MCPs over a wide range of Coulomb couplings.

In addition, we comment on the standard characterization of crust impurity in terms of the impurity parameter Qimp, the mean-square deviation in species charge, and show that this is inadequate for the amorphous outer crust. We compare the similarities and differences characterizing electron–ion scattering in the crust of neutron stars and in terrestrial solid and liquid metals—we also comment on the controversy regarding the behavior of the electron–ion scattering at the solid–liquid phase boundary. We use the mixing rule to compute the thermal conductivity of the outer crust of an accreting neutron star as a function of depth. Since the X-ray burst ashes (initial crust composition) used to determine the crust composition profile are obtained from a model that has accretion rate $\sim 0.1 \dot{M}_{\rm Edd}$, where $\dot{M}_{\rm Edd} \approx 10^{18}$ g s−1 is the Eddington accretion rate for a 10 km radius neutron star accreting a roughly solar hydrogen fraction, our results for crust conductivity are immediately applicable to superburst progenitors.

We restrict our study to the outer crust of the neutron star. In the vicinity of neutron drip, Gupta et al. (2008) showed that a large number of reactions involving neutrons can remove compositional memory, and the complexity can be drastically reduced in the inner crust. We plan to follow up on the nucleosynthesis results of Gupta et al. (2008) with a simple model of how an MCP evolves in the inner crust—this will serve as an analytic model of crust composition evolution on either side of neutron-drip without invoking large reaction networks. Even in the scenario of unsuppressed photodissociation as investigated recently by Shternin & Yakovlev (2009), the impurity of the outer crust is preserved from X-ray burst ashes on the surface to the rather high depth of 1011 g cm−3. Between this depth and the neutron-drip point at ∼4 × 1011 g cm−3, temperature-driven (n, γ) − (γ, n) equilibria along isotopic chains will reduce the impurity to roughly Qimp ∼ 40. Beyond neutron-drip (between ∼4 × 1011 and 3 × 1012 g cm−3) the density-dependent electron-capture-delayed neutron emissions, (EC,xn), as described in Gupta et al. (2008), will be the primary drivers of abundance re-arrangement and crust impurity will be reduced very quickly with increasing depth. Between ∼3 × 1012 and ∼1013 g cm−3 pycnonuclear reactions will change the composition using the few remaining nuclides to determine the compositional trajectory. Finally, at densities greater than 1013 g cm−3 proton-tunneling reactions will play a role, and may be instrumental in driving the composition to a single species (Jones 2005) without diverse metastable state populations spread out over different proton shell closures. The abrupt change in composition and resulting change in the phase diagram at neutron drip will be addressed in a later paper. Therefore this paper is restricted to the highly impure liquid metallic and amorphous phases of the neutron star crust which exist at depths shallower than neutron drip.

2. ELECTRONIC PROPERTIES OF IONIC MIXTURES

The section is organized as follows.

  • 1.  
    First, we briefly discuss the principal characteristics of the MCPs found in the crust of accreting neutron star.
  • 2.  
    We then recall the link between the electronic transport properties and NPB emissivity with the charge–charge structure factor.
  • 3.  
    We discuss the standard treatments of mixtures, namely the impurity parameter formalism and the LMR.
  • 4.  
    Finally, we compare electron scattering in terrestrial metals and neutron star crusts, and comment on the model of electron–ion scattering at the solid–liquid phase boundary as proposed by Baiko et al. (1998).

All the formulae below are expressed in natural (SI) units (in particular e2 = q2/4πepsilon0 where q is the electronic charge.) Also, the words "nucleus (nuclei)" and "ion (ions)" are used interchangeably.

2.1. Characterizing the Ionic Mixtures

We consider an unmagnetized, neutral MCP in a volume V at temperature T consisting of a mixture of Nsp atomic species of charge Zj and mass number Aj, j = 1, ..., Nsp. The number and mass densities of species j are nj and ρj, respectively. The total number density and mass density are $n=\sum _{j=1}^{N_{\rm sp}}{n_{j}}$ and $\rho =\sum _{j=1}^{N_{\rm sp}}{\rho _{j}}$, respectively. The total electron density is $n_{\rm e}=\sum _{j}^{N_{\rm sp}}{Z_{j}n_{j}}=\langle Z\rangle n$, where $\langle Z\rangle =\sum _{j}^{N_{\rm sp}}{x_{j}Z_{j}}$ is the mean ionic charge. We use

Equation (1)

to denote the number fraction of the jth species. Note that the number fraction is related to the species "abundances" Yj as traditionally used in the astrophysics literature; therefore the number fraction xj differs from the usual "mass fraction" Xj. Thus

Equation (2)

where Aj is the mass number of species j, NA is Avogadro's number, and

Equation (3)

where the index k denotes summation over all nuclear species in the MCP, including free nucleons. The average inter-particle distance between nuclei is denoted by a = (3/4πn)1/3, whereas the mean distance between electrons is ae = (3/4π ne)1/3. We will occasionally use the compact notations $\vec{Z}=(Z_{1},\dots,Z_{\rm N_{\rm sp}})$ and $\vec{x}=(x_{1},\dots,x_{\rm N_{\rm sp}})$ to denote the composition. When Nsp = 1, the system is referred to as a one-component plasma (OCP) and we drop the subscript referring to the particles' species.

We define several dimensionless parameters to characterize the system, namely:

  • 1.  
    the relativistic parameter xr = pF/mec,
  • 2.  
    the degeneracy parameter Θ = T/TF,
  • 3.  
    the electron coupling parameter Γe = e2/aekBT,

where pF = ℏkF is the Fermi momentum, kF = (3π2ne)1/3 is the Fermi wavevector and TF is the Fermi temperature of electrons.

For the typical physical conditions of interest in this paper, the density is in the range 106 g cm-3 ⩽ ρ ⩽ 1012 g cm-3, the temperature is T ∼ 0.5 GK, and the number of species Nsp varies from a few to several hundreds. As illustrated in Figure 1, at these densities and temperatures, xr > 1, Θ ≪ 1, and a/aB ≪ 1 where aB is the Bohr radius. As a consequence, atoms are completely pressure-ionized and matter is a dense, MCP composed of bare nuclei neutralized by a relativistic and strongly degenerate gas of delocalized electrons. This paper deals with the scattering of those electrons off the multi-component ionic mixture.

Figure 1.

Figure 1. Evolution with depth of dimensionless parameters obtained using the crustal composition profile of Gupta et al. (2007). Γeff is the effective ion coupling parameter defined in Equation (4), a/aB is the ratio of the mean interionic distance to the electronic Bohr radius, xr is the relativity parameter, Θ = T/TF is the degeneracy parameter. The vertical dashes indicate the compositions studied with MD and listed in Table 2. The dots show the ratio between the impurity parameter Qimp defined in Equation (24) and 〈Z2〉. As discussed in Section 5, 〈Z2〉 is less sensitive than Qimp to composition changes at densities ∼107, 2 × 108, 1010, and 1011 g cm−3.

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The ions are in general nonrelativistic; we shall also assume hereafter that the ions behave as classical entities, thereby neglecting the quantum nature of the ionic density fluctuations that may occur in the regions where T > Tp = ℏωp/kB, where ωp is the (kinetic) ion plasma frequency.

The nuclei are "strongly coupled" in the sense that their properties are primarily governed by their mutual interactions rather than by purely thermal effects as in an ideal gas.

In the OCP, electron–ion scattering is fairly well understood. The degree of coupling of an OCP is usually characterized by the so-called Coulomb coupling parameter ΓOCP = Z2e2/akBT, the ratio of the mean interaction energy Z2e2/a to the thermal energy kBT of the particles. Neglecting electronic screening, the OCP is known to crystallize into a bcc lattice at ΓOCP = Γc ≈ 175. Below Γc the OCP is in a fluid state whose properties vary from gas-like at small ΓOCP < 0.1 to liquid-like when 50 < ΓOCP < Γc (Daligault 2006); in the intermediate regime, 0.1 < ΓOCP < 50, both potential and kinetic effects play a comparable role in a non-trivial way. As a consequence, models of neutron star crusts based on the OCP usually treat the electron–ion scattering as follows.

  • 1.  
    When Γ>Γc, electrons travel in a bcc crystal and electron–ion scattering is interpreted as the scattering of Bloch electrons off the thermal vibrations (phonons) of the ions with respect to the bcc lattice sites.
  • 2.  
    When Γ < Γc, electrons scatter off the disordered ionic background characteristic of the fluid state.

Recently Baiko et al. (1998) called into question this canonical picture because it yields discontinuities in the electronic transport properties at melting. In Section 2.2.4, we comment on this controversy regarding the behavior of the electron–ion scattering at the solid–liquid phase boundary of an OCP.

The state of affairs for multi-component mixtures is much less known, and especially for mixtures composed of Nsp ⩾ 3 species as encountered in the crust of accreting neutron stars. A common approach used to infer the properties of a mixture is to map the latter onto an effective OCP of coupling Γeff, thereby disregarding the (poorly understood) complexities of the phase diagram and dynamic properties of a true mixture. A suitable definition of the effective coupling is

Equation (4)

where

Equation (5)

is the coupling parameter for species j, aj = (3/4πnj)1/3 being the average inter-particle distance of particles of species j, and $\langle Z^{5/3}\rangle =\sum _{j}^{N_{\rm sp}}{x_{j}Z_{j}^{5/3}}$. This choice for Γeff is motivated by the inequality (written here for pure Coulomb interactions; Rosenfeld 1993)

Equation (6)

which provides a very good lower bound of the ratio of mean excess (interaction) energy per particle Uex/nV to the thermal energy kBT, and therefore is a lower bound on the effective Coulomb coupling in the MCP.

In the astrophysical literature related to dense plasmas, often a mixture is assumed to crystallize at Γeff = 175 as in the OCP. Several questions can be raised with regard to the onset of periodic ordering in a true MCP that have not been satisfactorily addressed to date. For instance:

  • 1.  
    Does the system crystallize in a regular, periodic lattice as has often been assumed in the literature?
  • 2.  
    Do the most abundant species make a lattice and the less abundant species contribute to defects in the structure?
  • 3.  
    Is it amorphous with a liquid-like frozen-in structure?

An affirmative answer to questions 1 and 2 above is assumed rather commonly in the literature and consequently, beyond Γeff > Γc, the total electron–ion scattering cross-section is split into two contributions: (1) the electron–phonon contribution due to the lattice structure and (2) the electron–impurity contribution. We believe that the phase diagram of mixtures such as those existing in the crust of accreting neutron stars is still too poorly known to make any definite statements such as 1 and 2 above. The local composition may also be changed due to phase-separation (demixing) and sedimentation effects, which are still not well understood and are being investigated (Horowitz et al. 2008). Given the complexity of the mixtures, it is, however, not unreasonable to think that, even when Γeff > Γc, the system will most likely be amorphous, or at the very least be comprised of many defects, and that the existence of Bloch states is questionable. In the following, we shall assume that the composition at any depth in the outer crust of the accreting neutron star is known; in practice, we shall use the outer crust composition from Gupta et al. (2007). In all cases that we considered, when starting from an amorphous structure, the MD simulations performed did not show any evidence for demixing or crystallization over the timescale of the simulations.

2.2. Electron–Ion Scattering in MCPs

We shall focus on electron–ion scattering and ignore the effect of electron–electron (ee) scattering. It was shown in (Potekhin et al. 1999) that ee scattering contributes to conductivity only for very light nuclei with Z ≲ 6 and under non-degenerate conditions. For a pure 56Fe composition in a degenerate plasma at densities ≈108.5–1011.5 g cm−3 (Potekhin et al. 1999) showed that ee collisions could be neglected.

Many of the basic formulae in the following sections can be found, for instance, in Flowers & Itoh (1976).

2.2.1. Thermal and Electrical Conductivities

Electron–ion scattering impedes the transport of electronic momentum and energy. The resulting electrical conductivity σ and the thermal conductivity κ can generally be expressed in terms of the collision frequencies νσ and νκ:

Equation (7)

Equation (8)

where $m_{\rm e}^{*}=m_{\rm e}\sqrt{1+x_{\rm r}^{2}}$ is the effective electron mass, vF = pF/m*e is the Fermi velocity, and CV is the heat capacity of the free relativistic electron gas.

The quantities τσ and τκ describe the typical timescale over which electron–ion collisions degrade the electric and thermal currents. Their inverses, the frequencies νσ,κ = 1/τσ.κ, can conveniently be written as the product of a "fundamental" frequency ν0:

Equation (9)

multiplied by a dimensionless quantity ln Λσ,κ known as the Coulomb logarithm:

Equation (10)

In Equation (9), 〈Z2〉 results form the appropriate normalization Szz(k) → 1 of the structure factor discussed below in Equation (15), α = e2/ℏc is the fine-structure constant, and EF = m*ec2 is the electron Fermi energy. The fundamental frequency ν0 can be seen as a frequency of Coulomb collisions associated with the transfer of momentum between electrons and ions; it can be written as

Equation (11)

in which the bracketed term can be interpreted as the cross-section for momentum transfer in a binary collision between an electron of velocity vF and charge −e and a massive ion of charge $\langle Z^{2}\rangle ^{\frac{1}{2}}e$. The dimensionless Coulomb logarithm contains all the fine details of electron–ion collisions in a plasma, such as charge screening, collective modes, and quantum diffraction effects. In general, ln Λσ ≠ ln Λκ since the two transport coefficients measure different mechanisms, namely momentum and energy transport. However, when the dominant source of electron–ion scattering is elastic, as in the disordered fluid phase or the high-temperature crystalline phase, the two Coulomb logarithms are equal and the Wiedemann–Franz relation

Equation (12)

is satisfied.

A calculation of the Coulomb logarithm that self-consistently treats all the many-body effects occurring in a MCP is in general rather complicated. However, because of the high electron density in neutron stars, the typical electron kinetic energy is very large compared to the electron–ion interaction energy and the average electron–ion correlations are weak. Accordingly, a good approximation can be made by considering the ions and electrons in the plasma as two weakly interacting subsystems, namely an MCP neutralized by a homogeneous negatively charged background and an homogeneous interacting electron gas (i.e., relativistic quantum electronic jellium.) Electrons scatter off the electrostatic potential created by the ionic charge distribution,

Equation (13)

where Rl(t) is the position of the lth nuclei of the jth species at time t, and Nj = njV is the number of particles of species j. In the (first) Born approximation1 of the electron–ion interaction and using the fact that the electrons are much heavier than the ions, we obtain (Flowers & Itoh 1976)

Equation (14)

with v(k) = 1/k2 and epsilone(k) is the static dielectric function of the electron jellium.

Equation (14) can be interpreted as follows. The Coulomb logarithm ln Λσ,κ sums all the contributions of collisions characterized by momentum transfer k. The range of integration is limited to 2kF because the electrons are degenerate and only those electrons near the Fermi surface take part in exchanges of momentum and energy. The electrons behave as if they were scattered independently of each other by the electronically screened electron–ion potential. Because the electrons are much lighter than the nuclei, the energy exchanges ℏω in inelastic collisions occur in a range over which epsilone(k, ω) ≈ epsilone(k, 0) = epsilone(k). For relativistic, degenerate electrons, an analytical expression for epsilone was obtained by Jancovici (1962) within the random-phase approximation (see Appendix B).

The bracketed term, which describes the kinematic suppression of backward scattering of relativistic electrons, $\big[ 1-\frac{x_{\rm r}^{2}}{1+x_{\rm r}^{2}}\big(\frac{k}{2k_{\rm F}}\big)^{2} \big]$, varies between unity for xr → 0 and [1 − (k/2kF)2] for xr.

The many-body physics of the ionic subsystem is encapsulated in the function ${\cal {S}_{\sigma,\kappa }}(k)$. ${\cal {S}_{\sigma,\kappa }}(k)$ is a functional of the spectrum of charged fluctuations δnz(k, t) = nz(k, t) − 〈nz(k)〉eq in the ionic system

Equation (15)

where 〈 〉eq denotes the average of a canonical ensemble at temperature T. In other words, ${\cal {S}_{\sigma,\kappa }}(k)$ self-consistently takes into account all of the separate electron–ion relaxation mechanisms at the level of the Born approximation; it is really an umbrella term for electron–ion, electron–impurity, electron–phonon scattering, and includes multi-phonon processes. We have, from Flowers & Itoh (1976),

where n(z) = 1/1 − ez.

In the special case of a periodic, crystalline structure, the term 〈nz(k)〉eq peaks at values of the wavevector k commensurate with the periodicity of the lattice and subtracts out the elastic Bragg peaks: electron–ion scattering involves Bloch electrons and Equation (14) is obtained by approximating their behavior by means of free particle wave functions.

When the scattering is predominantly elastic in nature, as is expected in the fluid and solid phases at T > Tp or in a disordered (non-periodic) lattice, we have

Equation (16)

Equation (17)

Equation (18)

where Szz(k) is the (charge–charge) structure factor. This leads to

Equation (19)

In this limit, σ and κ are insensitive to the details of the spectrum of ionic charge fluctuations. These details (ion collective modes and single-particle effects) are present implicitly but in an integrated form via the sum-rule (18).

Until now, we have assumed that the ions are point particles. In this "point-charge" approximation, the only species-dependent term in the integrand of Equation (14) is the charge–charge structure factor Szz(k). In order to allow for finite nuclear size, one can replace the density (13) with

Equation (20)

where Fj(k) is the nuclear form factor, which reflects the charge distribution within a nucleus of species j. For instance, assuming uniform proton density in the nuclei,

Equation (21)

where Rj the charge radius of the nuclear species j which has mass number Aj; we use Rj = 1.15A1/3j fm as in Kaminker et al. (1999). Direct MD calculation of the structure factor Szz(k) with and without the nuclear form factor (21) shows that the finite nuclear size corrections are completely negligible in the outer crust of interest in this paper. (Note that for instance (Fj(k))2 = 0.9766 at the peak of Szz(k), i.e. at (k/2kF) ≈ 0.33, for a typical heavy nucleus having mass number Aj ≈ 64–100 or A1/3j ≈ 4–4.6). Accordingly, we neglect finite nuclear size effects in the remainder of this paper.

2.2.2. Neutrino-pair Bremsstrahlung (NPB) Emissivity

In NPB, the electrons are accelerated by the Coulomb field of the crust as in photon Bremsstrahlung but with the emission of a neutrino–antineutrino pair instead of a photon. In the first Born approximation, the neutrino emissivity is

Equation (22)

with the Coulomb logarithm for NPB,

Equation (23)

where k = kt + kr, GF is the Fermi weak coupling constant, C2+ ≈ 1.675 from the vector and axial-vector constants of the weak interaction, and $a(k)= \left[ 1-\frac{2k^{2}}{4k_{\rm F}^{2}-k^{2}}\ln \left(\frac{k}{2k_{\rm F}}\right) \right]$. The function RT describes the thermal broadening of the electron Fermi surface and from Equation (20) of Haensel et al. (1996) this can be approximated as unity for T ≲ 0.6 GK typical of models of the neutron star crust at accretion rates characteristic of superburst progenitors (Kaminker et al 1999).

Thus, in both Equations (14) and (23) the only dependence on the nuclear species present (i.e., on the composition) enters via Szz(k). Therefore, to tabulate fits to both κ and epsilonν for every nuclear species prior to application of a mixing rule is extremely cumbersome (note that the papers Itoh et al. 2008, 1996 tabulate fit coefficients for only 11 species for conductivities and NPB emissivities, respectively) and also unnecessary from a computational standpoint. The fits to OCP structure factors in Young et al. (1991) are sufficient to cover every one of the Nsp > 100 species encountered in the neutron star crust. They can also be used to compute both κ and epsilonν for an MCP of arbitrary complexity using the microscopic mixing rule (MLMR) described in Section 4 which involves only the OCP structure factors and species abundances. For higher values of Γ>225 in the neutron star crust we present a simple model for the behavior of the Coulomb logarithm that reduces the evaluation of thermal and electrical conductivity to an analytic formula incorporating crust impurity in a very simple way. We do not present calculations of the NPB neutrino emissivity in this paper, rather we point it out to demonstrate that all such "integral" determinants (i.e., summations over momenta) of crust thermal profile are related to the crust composition via the quantity Szz(k).

2.2.3. The Standard Treatment of Mixtures in the Crust

For simplicity, we drop the σ, κ, and ν subscripts in what follows.

The most common approach of electron–ion scattering in the neutron star crust relies on the belief that the MCP is fluid in the upper part of the crust where Γeff < 175 and consist of a solid, i.e. a crystalline lattice with impurities, in the lower part where Γeff > 175. Accordingly, in the solid phase, the collision frequency ν = νe-ph + νe-imp is split into the sum of the electron–phonon and the electron–impurity scattering contributions; in the liquid state ν = νei where νei is the electron–ion scattering inverse relaxation time discussed in the next section.

The splitting ν = νe-ph + νe-imp was initially introduced in Flowers & Itoh (1976) to deal with periodic crystals with a small fraction of the lattice sites occupied by impurities. The idea is illustrated in Figure 2. The case of binary mixtures (Nsp = 2) was discussed in detail in Itoh & Kohyama (1993) for a small concentration of impurity ions (say species "2"): the contribution of the impurity to electron–ion scattering is equal to its concentration times the binary electron–ion collision frequency between an electron and a "residual" ion of charge (Z2Z1). This idea was extended to deal with more complex MCPs containing Nsp ⩾ 3 species, in which case the system is treated as a perfect crystal of charge 〈Z〉 plus the contribution of uncorrelated impurities of charge (Zi − 〈Z〉).

Figure 2.

Figure 2. Impurity parameter formalism illustrated. Top panel: a perfect crystal with a low concentration of impurities substituted at lattice sites can be approximated as being made of two uncorrelated parts: the perfect lattice and the residual charge. The total electron–ion scattering cross section is the sum of the Bloch electron-lattice scattering cross section plus the sum of uncorrelated binary electron-residual impurity collisional cross section. Lower panel: as the concentration of impurities increases, this splitting is less and less justifiable.

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Within this approximation and defining the impurity parameter as

Equation (24)

the relaxation frequency can be written as

Equation (25)

where

Equation (26)

and

Equation (27)

ln Λimp corresponds to Equation (20) with Szz set to unity to correspond to independent (uncorrelated) electron–impurity collisions.

While the impurity parameter formalism was developed to treat small impurity concentration in an otherwise almost perfect crystal lattice (see Figure 2), it has also been used to characterize electron–ion scattering in complex fluid and amorphous MCPs when Qimp is large, say Qimp ∼ 100. Such is usually the case when electron–impurity scattering is used to set a lower bound on conductivity for the entire crust. However, since Λimp is of the order of magnitude as Λ, we have

Equation (28)

Equation (29)

over the whole outer crust as shown in Figure 1, the impurity parameter can lead to conductivities much higher than the those that would be obtained using the actual structure factors employed in Equation (20). We thus anticipate that Qimp is inappropriate for the outer crust (impure liquid metal approaching heterogeneous amorphous solid at high density), and instead we shall justify the usage of 〈Z2〉 from its presence in our expression for the fundamental frequency ν0 in Equation (9). The differences in crust conductivity that would result from these differing prescriptions are discussed in Section 5.

In the liquid state, Potekhin et al. (1999) proposed a different approach to deal with mixtures. In this formalism, one writes

Equation (30)

where Γj = Z5/3jΓe, xj refers to the number fraction as defined in Equation (1), and ln ΛOCPj, Zj, xr) is the Coulomb logarithm (20) for an OCP of charge Zj at coupling Γj and relativistic parameter xr. This prescription for mixtures was also recommended recently in the works of Cassisi et al. (2007) and Itoh et al. (2008) and we corroborate its efficacy in Section 4.

In Sections 4 and 5, we propose and validate with MD simulations a mixing rule for |ln Λ that is slightly modified from Equation (30). We also show that the impurity parameter formalism is inappropriate at large Qimp.

2.2.4. Discontinuities in Transport Coefficients at Crystallization

The previous expressions tell us that the conductivities and NPB emissivity depend on the scattering of electrons off the fluctuations δnz(k, t) in the ionic charge density about the average value 〈nz(k)〉eq. However, this average charge density is dependent upon the thermodynamic phase of the system.

  • 1.  
    If the system is fluid, the averaged charge density 〈nz(k)〉eq = ne δ(k) is uniform.
  • 2.  
    If the system is in a crystalline solid state, i.e., comprised of a periodic (Bravais) lattice with the same physical unit, electrons are in Bloch states and 〈nz(k)〉 = e−2W(k)neVKδk,K depends on k, where, assuming Nsp = 1, K are reciprocal lattice vectors and W(k) is the Debye–Waller factor: Bloch electrons do not scatter off the static, wavevector-dependent charge fluctuations (Bragg peak).

Because of this fundamental difference, the formulae of the previous section predict significant (by a factor of 3–5) discontinuities of the electric and thermal conductivities at the melting point (Itoh et al. 1993). Recently, Baiko et al. (1998) argued that this jump in the OCP electronic transport properties upon crystallization is not physical and that the electron transport properties in strongly coupled plasmas should be fairly insensitive to the thermodynamic state of the plasma. Accordingly, they advance that strongly coupled Coulomb liquids are characterized locally by the same long-range order as present in the crystalline solid and although the long-range order does not persist forever as in a solid (the liquid state is fluid), electrons keep traveling in those local crystal-like structures without any significant degradation of their mean velocity. Thus, Baiko et al. (1998) advocate that, in the liquid state, the contribution corresponding to elastic scattering off the incipient crystalline structure must be subtracted from the static structure factor. As intended, this prescription removes the jump in the conductivities at the solid–liquid transition—this prescription was later used in a series of papers to redefine practical fitting formulae for the electron conductivities and NPB (e.g., Cassisi et al. 2007 and references therein; also Horowitz et al. 2008).

The prescription of Baiko et al. (1998) contradicts our current understanding of solid and liquid metals. We instead agree with Itoh et al. (2008) since we believe that the disordered positions and the oscillating and diffusive movement of the ions cannot be ignored in a liquid.

The arguments and conclusions of Baiko et al. (1998) contradict both experimental findings and the contemporary theoretical understanding of liquids: for example, it has been known for a long time that the electrical resistance of most metals in the liquid state just above their melting points are about 1.5–2.3 times larger than those of solid metals (Cusak & Enderby 1960). Even the simplest metals, whose electronic structure do not change appreciably upon melting, show a discontinuity in transport properties at melting, e.g., for sodium σsl ≈ 1.45 and for aluminum σsl ≈ 2.2. Interestingly, similar to Baiko et al.'s approach but with the opposite purpose in mind, early theoretical attempts to explain the increase of electrical resistivity upon melting relied heavily on ideas that had proved successful for solid metals. These approaches overlooked the effect of disorder inherent to liquids: for instance, in the "quasi-crystalline" models, the local coordination just above the melting point was treated very similar to that which prevails in the solid phase just below. It was also believed that, as in a solid metal, the resistivity of liquid metals could be divided into two parts: (1) a thermal term, proportional to the mean square amplitude of vibration of the ions, and hence dependent on the temperature T and (2) a residual term, independent of T due to defects (e.g., vacancies, dislocations). In 1934, Mott (1934) presented an elegant theory to reconcile these solid-like picture to the increase of electrical resistivity on melting in terms of the entropy change on melting per particle Δs = (SlSs)/nV,

Equation (31)

Using the latent heat of fusion to evaluate Δs, Mott's model yields surprisingly good values of σsl (1.68 for sodium instead of 1.45.) It was later realized that Mott's assumptions do not hold in the light of other facts. Hence Mott's theory assumes that all the melting entropy is connected with the thermal agitation of the ions and ignored the configurational entropy arising from disorder in the rest positions about which ions are instantaneously vibrating (the so-called "cage effect"). Unfortunately, this argument does not hold: it is indeed known that for all simple metals, the experimental Δs is approximately a universal constant, Δs ≈ 0.8 ± 0.1 (rms), and is chiefly due to the change in configurational entropy (Wallace 1997). The entropy change due to the thermal agitation, the anharmonicities in ionic motions, and the electronic structure are responsible for the small scattering in the universal value. As illustrated in Table 1, similar findings apply the OCP over a wide range of electronic screening, namely Δs ≈ 0.85.

Table 1. Entropy Variation Δs = ΔS/nVkBT on Melting (i.e., from BCC to Fluid) of the OCP as a Function of the Inverse Dimensionless Screening Length κ = aksc

κ Γm Δs
0 171.8 0.8516
0.2 173.5 0.8526
0.4 178.6 0.8551
0.6 187.1 0.8580
0.8 199.6 0.8599
1.0 217.4 0.8591

Notes. Γm is the coupling paramater ΓOCP at melting. The data were calculated using the equation of state of Hamaguchi et al. (1997).

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Finally, we would like to add another argument in disfavor of Baiko et al.'s prescription. If crystallites do indeed exist in the liquid phase as assumed by Baiko et al. (1998), they must be extremely small, smaller than required for a local band structure to be established, because the presence of nuclei would make it impossible for a liquid to supercool. However, all liquid metals can be persuaded to supercool through as much as 20% of their melting temperature (Turnbull & Cech 1950) and MD simulations of the OCP show the same trend (Daligault 2007).

Interestingly, for the multi-component systems found in the crusts of accreting neutron stars, the jump may be much less important than suggested by the calculations of Itoh et al. (1993). However, this is likely not due to the reason proposed by Baiko et al. but because of the lack of long-range order for those complex mixtures and the high degree of impurity-like disorder that those systems possess.

2.2.5. Terrestrial Liquid Metal Compared to the Neutron Star Crust Plasma

In this section we continue the comparison of electron–ion scattering as occurring in terrestrial liquid metals as opposed to the crust of a neutron star. To make this comparison as quantitative as possible, we shall discuss the different components of the Coulomb logarithm in Equation (14). While this expression applies to both terrestrial liquid metals and to the crusts of accreting neutron stars (under the assumption of the first Born approximation), there are several interesting differences between both systems which we enumerate below.

  • 1.  
    While in the former the number of species is typically of order unity (Nsp = 1 in simple metals; Nsp = 2–3 in alloys), the number of species in the latter can be several hundred (see Section 3.1) Nevertheless, as shall see, the charge–charge structure factors Szz(k) is similar in both cases, i.e., characterized by damped oscillations originating from the short-range order of strongly coupled systems. The heights of the peaks increase with the strength of the coupling parameter Γeff and therefore with depth.
  • 2.  
    While in terrestrial liquid metals electrons are nonrelativistic, electrons in an accreting neutron star crust are relativistic. The main effects of relativity are encapsulated in $\big[1-\frac{x_{\rm r}^{2}}{1+x_{\rm r}^{2}}\big(\frac{k}{2k_{\rm F}}\big)^{2}\big]$, which varies from 1 when xr → 0 and 1 − (k/2kF)2 when xr and describes kinematic suppression of backward scattering of relativistic electrons. Relativity also modifies the electronic screening of the ions (see Equation (B2)). The overall effects of relativistic corrections is illustrated in Figures 3 and 4. Figure 3 shows the integrand of Equation (14) for both relativistic and nonrelativistic electrons (xr = 0 in Equation (14)). Relativistic effects are noticeable in large momentum transfer collisions (close encounters) and, as a consequence of the suppression of back-scattering, result in lower scattering cross-sections and consequently higher conductivities. Figure 4 compares the relativistic versus nonrelativistic Coulomb logarithm as a function of depth using the compositional profile of Gupta et al. (2007) discussed in Section 3.1.
  • 3.  
    While in the neutron star crust, ions are fully stripped and all electrons are delocalized electrons and participate in the electronic conduction, ne = 〈Zn with 〈Z〉 ∼ 40, most electrons in a liquid metal are bound to the nuclei, ne = 〈Zeffn where Zeff is the effective charge of the ions and Zeff = 1–3. As a consequence, in Equation (14), vie(k) must, in principle, be replaced by a pseudopotential that mimics the effect of bound electrons on free-electron ion scattering (this is a major difficulty in condensed matter physics). In contrast, for neutron star crusts, vie is known: it is the pure Coulomb potential, slightly corrected with a form factor to describe the finite size of the nuclei and very close electron–ion collisions.
  • 4.  
    A final effect of major importance arises from the magnitude of the electron Fermi wavevector kF = (3π2ne)1/3, which increases like Z1/3eff in terrestrial liquid metals as opposed to 〈Z1/3 in the neutron star crust. Therefore the ranges of integration 0 ⩽ k ⩽ 2kF in Equation (14) greatly vary between the two cases. The situation is illustrated in Figure 3: the limit of integration 2kF lies just to the left of the main peak in S(k) for monovalent liquid metals, just to its right for divalent ones, and progressively further to the right for metals which have a valency greater that two and three. In neutron stars, 2kF can be quite large (and increases with depth), i.e., large momentum transfer collisions (close encounters) become much more important in determining the electron–ion scattering cross section.
Figure 3.

Figure 3. Structure factor Szz(k) and the corresponding integrand for the Coulomb logarithm Equation (14) with (red line) and without (green line) the relativistic correction. The upper panel corresponds to composition 1 of Table 2 at T = 0, 27 GK (Γeff = 60 and 〈Z〉 = 37). The lower panel was obtained with composition 9 of Table 2 at T = 0.8 GK (Γeff = 153 and 〈Z〉 = 34). The vertical dashed lines mark the limit of integration 2kF in the Coulomb logarithm (14) for liquid metals with effective ionic charges Zeff = 1, 2, 3, and 4. Its position relative to the main peak in Szz(k) clearly depends on the valency of the metal ion. In the crust of a neutron star, 〈Z〉 ≫ Zeff, and consequently the range of integration encompasses all first peaks in Szz(k). Physically, in neutron star crusts, large momentum transfers (close encounters) significantly contribute to the Coulomb logarithm.

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Figure 4.

Figure 4. Contribution of the relativistic correction to the Coulomb logarithm (14) in the region 107 g cm−3 ⩽ ρ ⩽ 1010 g cm−3. ln Λcl corresponds to the nonrelativistic limit of Equation (14) obtained by setting the bracketed term $1-\frac{x_{\rm r}^{2}}{1+x_{\rm r}^{2}}\big(\frac{k}{2k_{\rm F}}\big)^{2}$ to 1.

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3. MOLECULAR DYNAMICS SIMULATIONS OF THE NEUTRON STAR CRUST

In this section, we discuss the MD simulations we performed in order to calculate the structure factors Szz(k) of MCPs representative of neutron star crust and to validate the LMR discussed in Section 4.

3.1. Input: A Representative Crust Composition Profile

To base our calculations of crustal κ and epsilonν on a realistic pre-neutron-drip crust compositional profile we have used the compositions of Gupta et al. (2007). Our choice was determined by a number of factors. First, the diversity of species in the starting composition (XRB ashes from Schatz et al. (2001) is characterized by the "impurity parameter" which has a high value Qimp ∼ 100, an ideal test-bed for validation of a mixing rule in an MCP. In the outer crust, prior to the onset of neutron reactions, electron captures preserve the high impurity. Only beyond neutron-drip in the inner crust, as demonstrated in the SEC-nucleosynthesis process described in Gupta et al. (2008), do electron-capture-delayed-neutron emissions rearrange abundances between very diverse mass chains. Finally, the accretion rate closely match those expected of X-ray superburst progenitors ($\sim 0.1 \dot{M}_{\rm Edd} \approx 10^{17}$ g s−1) and therefore we intend the numbers we compute to have practical relevance to the neutron star crust modeling and X-ray observational communities.

The mixtures we have simulated discard the less abundant species which would have had less than 10 particles in the simulations. Details for each of the compositions used at depth are given in Table 2 and the spread in Z is illustrated in Figure 5 for two compositions.

Figure 5.

Figure 5. Composition profile at two crustal depths corresponding to mixture 1 (upper panel) and 12 (lower panel) of Table 2. The figure shows the number concentration as a percentage as a function of the nuclear charge Z. At a given Z, the horizontal ticks indicate different nuclear masses A.

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Table 2. List of the Mixtures Considered in this Work Extracted from Gupta et al. (2007)

Mixture Norigsp Nsp ρ (g cm−3) EF (MeV) akF Γeff = 〈Z5/3〉Γe Z Z2
 1 450 55 8.59 × 106 0.45 6.44 32.3 37 1597
 2 419 50 1.01 × 108 1.38 6.46 71.3 37 1537
 3 451 52 2.49 × 108 2.00 6.44 97.9 38 1564
 4 432 52 4.33 × 108 2.49 6.52 118.4 38 1572
 5 405 50 7.08 × 108 3.00 6.42 137.4 38 1549
 6 400 53 1.00 × 109 3.42 6.41 153.2 38 1536
 7 398 53 2.87 × 109 5.00 6.37 179.5 35 1359
 8 406 52 4.85 × 109 6.01 6.31 236.4 36 1401
 9 411 49 1.00 × 1010 7.72 6.26 263.1 34 1275
10 404 49 2.17 × 1010 10.0 6.20 343.8 34 1171
11 372 52 3.74 × 1010 12.0 6.18 390.6 33 1113
12 355 50 4.26 × 1010 12.5 6.18 399.9 33 1090
13 363 54 4.81 × 1010 13.0 6.14 410.6 32 1073
14 341 50 5.99 × 1010 14.0 6.15 436.8 32 1119
15 344 49 7.37 × 1010 15.0 6.15 461.7 32 1103
16 341 46 9.13 × 1010 16.0 6.04 468.71 31 1041
17 206 24 1.75 × 1011 19.7 5.95 538.8 30 964

Notes. Norigsp is the original number of species in Gupta et al. (2007), Nsp is the number of species used in the MD simulations, ρ is the mass density, EF the Fermi energy, T the temperature, akTF the dimensionless TF screening length where a is the interparticle distance, akF is the dimensionless Fermi wavevector, Γ is the coupling parameter defined by Equation (4).

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We now use the composition profiles at various neutron star crust depths to validate the LMR. We adopt a fiducial temperature T = 0.5 GK, and vary the density as in Table 2. Thus, changes in Γeff with changing crust depth arise only from composition evolution and a decrease in inter-ionic spacing. At each depth a large number of mass chains A ≈ 20–100 enter the composition as expected from X-ray burst ashes evolving in the outer crust at depths shallower than the neutron-drip point.

3.2. The MD Procedure

We employ MD simulations to calculate the structure factor (18) at various depths of a neutron star crust. In order to deal with the impure multi-component ionic mixtures typical of neutron star crusts, we have developed a code that allows for the simulation of large charged systems (tens to a few hundred nuclear species) over the long timescales required for the equilibration of such impure MCPs. The code is based on a parallelized implementation of the Particle–Particle–Particle–Mesh (P3M) algorithm with periodic boundary conditions; high resolution for individual encounters is combined with rapid, mesh-based, long range force calculations. It simulates the classical dynamics of a mixture of nuclei described as point particles interacting through a screened Coulomb interaction. Thus the interaction potential between two nuclei of charge Zi and Zj is modeled by the screened Coulomb (Yukawa) potential,

Equation (32)

where ksc is the inverse screening length. The P3M algorithm can handle any value ksc ⩾ 0 to very high accuracy. In practice, we use the inverse of the relativistic Thomas–Fermi inverse screening length krTF for ksc given by krTFae = 0.185(1 + x−2r)1/4.

Several technical details of the MD calculations (simulation length, number of particles, time steps, etc) are collected in Appendix A. Here we briefly outline the procedure used to calculate Szz(k). Given a composition at a certain depth, the particles are initially randomly distributed in a cubic box of volume V = L3 with a Maxwellian velocity distribution at the prescribed temperature. After a long equilibration phase, a simulation is performed in which, at each time step n, the charge density nZ(k; n) as in Equation (13) is calculated for values of k commensurate with the simulation box size L, namely

Equation (33)

where nx,y,z are natural integers. The charge–charge structure factor (18) is calculated at the end of the run using

Equation (34)

3.3. Molecular Dynamics Structure Factors

MD results for the structure factor Szz(k) and corresponding to the crustal compositions of Gupta et al. (2007) listed in Table 2, all at temperature T = 0.5 GK, are shown in Figures 68 over the range 0 ⩽ k ⩽ 2kF. Additional data obtained from the MD simulations to test lower temperatures near the photosphere–ocean boundary and potentially high temperatures at different depths are provided in the Appendix C.

Figure 6.

Figure 6. Structure factor Szz(k) obtained with MD simulations (red lines) and with the mixing rule formula (40) (blue lines) for the mixtures 1–5 defined in Table 2.

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Figure 7.

Figure 7. Structure factor Szz(k) obtained with MD simulations for the mixtures 7, 9, 10, and 11 defined in Table 2.

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Figure 8.

Figure 8. Structure factor Szz(k) obtained with MD simulations for the mixtures 12–17 defined in Table 2.

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The shape of the charge–charge structure factor Szz(k) is typical of the structure factor of liquids. The first peak, which systematically occurs at k/2kF ≈ 0.33 and which has a height increasing with the effective Coulomb coupling Γeff, reflects the existence of a dominant short-range order of the particles in real space. This is illustrated in Figure 9 that shows different pair-distribution functions gab(r) for several pairs of species a and b. The sharp decrease in the pair-distribution functions at small separation, originating from the repulsion between like charges, is responsible for the subsequent maxima and minima of Szz(k), whose oscillation is strongly damped as k increases. Eventually, at large k, Szz(k) approaches unity, in accordance with the normalization in Equation (18). At small k, Szz(k) probes the long-wavelength static fluctuations in the charge density and approaches zero (as k2) in the k → 0 limit as a consequence of charge neutrality and perfect screening.

Figure 9.

Figure 9. Upper panel: pair distribution function g(r) between particles of most abundant species of compositions 1, 3, 6, and 15 defined in Table 2. Lower panel: pair distribution function between the most abundant and another less abundant species for the same compositions of the upper panel.

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All the simulations at density larger than ∼1010 g cm−3 (compositions 9–17 of Table 2) and characterized by Γeff > 260 show pronounced short-range structure as seen in the shoulder of the second peak of Szz(k). Nevertheless, within the timescale of the simulations, we did not witness any clear-cut phase separation or crystallization.

4. VALIDATION OF THE LINEAR MIXING RULE AND PRACTICAL FIT

4.1. Validation of the LMR

A common approximation for the excess (non-ideal) energy Uex and free energy Fex of strongly coupled ion mixtures is the (empirical) LMR. In terms of the energy per particle and per unit of kBT, uex = Uex/NkBT and fex = Fex/NkBT, the LMR claims that

Equation (35)

Equation (36)

where Γj = Z5/3jΓe, and uLMRex and fLMRex are the excess free energy of an OCP at coupling Γj, and $\overrightarrow{\mathbf {x}}=\lbrace x_{i}\rbrace _{i=1}^{i=N_{\rm sp}}$ is the composition vector of species number fractions (see Equation (1)) for the MCP.

To the best of our knowledge, the mixing rules (35) and (36) were obtained empirically and there is no rigorous "derivation" of them. Equation (36) was shown to be very accurate for binary mixtures with both rigid (DeWitt & Slatery 2003) and polarizable background electrons (Chabrier & Ashcroft 1990). Recently, Potekhin et al. (2009) proposed to extend the LMR to calculation of the equation of state (EOS) of multi-component mixtures. The results derived in the following validate this recent prescription of Potekhin et al. (2009).

The LMRs (35) and (36) suggest a more fundamental, microscopic mixing rule that directly involves the structure factors. To this end, we recall that the excess energy of a screened MCP (i.e., with ions interaction via the screened Coulomb potential (32)) can be obtained from the charge–charge structure factor Szz(k) using (Rosenfeld 1993)

Equation (37)

The exact Equation (37) together with the accurate approximation Equation (36) suggest the following MLMR approximation for the MCP structure factor Szz(k),

Equation (38)

where SOCPj(k; Γ) is the structure factor of the OCP comprised of species j at coupling Γ. Indeed, introducing Equation (38) in Equation (37), we obtain the LMR (35) and (36). By introducing Equation (38) in Equation (14), we obtain the LMR for the Coulomb logarithm,

Equation (39)

where ln ΛOCPj, Zj, xr) is the Coulomb logarithm for an OCP of charge Zj at the coupling Γj and relativistic parameter xr (the explicit dependence on the charge Zj comes from the upper limit 2kF = 2(3π2ne)1/3 = 2(3π2Zjnj)1/3 of the integral in Equation (14)).

The validity of the MLMR (38) is confirmed by our MD simulations. The structure factors for compositions 1–8 of Table 2, corresponding to 8.6 × 106 g cm−3 ⩽ ρ ⩽ 4.8 × 109 g cm−3 and 70 ⩽ Γ ⩽ 140, are shown in Figures 1 and 2. The blue lines show the results obtained using MD simulations and the red lines show the results obtained with the mixing rule (38). The latter was evaluated with the structure factors for the OCPs obtained by solving the so-called HNC equations (see, e.g., Young et al. 1991) For all the compositions, Figures 1 and 2 show very good agreement between the MD and the mixing rule values. In each case, the position of the peaks is well reproduced and the mixing rule overestimates their heights by at most 10%. (The MLMR is also illustrated in the figures of Appendix C.)

When used in Equation (37) or Equation (14), however, these differences between the MD and MLMR structure factors barely affect the value of the Coulomb logarithm, and in turn the electronic transport properties are unaffected. This is illustrated in Figure 10 that shows the sum $\ln \Lambda (K)=\int _{0}^{K}{dkk^{3}\big |\frac{v(k)}{\epsilon (k)}\big |^{2}\big[1-\frac{x_{\rm r}^{2}}{1+x_{\rm r}^{2}}\big(\frac{k}{2k_{\rm F}}\big)^{2}\big]S_{\rm zz}(k)}$ with 0 ⩽ K ⩽ 2kF obtained with the MD and the mixing rule results. Thus the MLMR provides a very accurate and convenient way of calculating the electronic transport coefficients for complex ionic mixtures in the liquid phase. More generally, all quantities that are functionals of the structure factor such as (37), the electrical and thermal conductivity, and even the NPB emissivities can be obtained to high accuracy from the MLMR.

Figure 10.

Figure 10. Cumulative integral $\ln \Lambda (K)=\int _{0}^{K} dkk^{3}\big |\frac{v(k)}{\epsilon (k)}\big |^{2}\big[1-\frac{x_{\rm r}^{2}}{1+x_{\rm r}^{2}}\big(\frac{k}{2k_{\rm F}}\big)^{2}\big]S_{\rm zz}(k)$ obtained using the Szz(k) from MD simulations (solid blue line) and from the mixing rule Equation (38) (red dots). The Coulomb logarithm Equation (14) is ln Λ(2kF). The upper and lower curves correspond to the mixture 1 and 9 defined in Table 2, respectively.

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4.2. Practical Fit to the Coulomb Logarithm of a Mixture

Having validated the LMR, we now provide a simple practical fit to the Coulomb logarithm of an arbitrarily complex liquid or amorphous MCPs. The fit is valid for any effective Coulomb coupling Γj ⩾ 10 and relativistic parameter range 1 ⩽ xr ⩽ 1000. For the neutron star crust applications in the amorphous state, once the composition as function of depth is known, the conductivity can be calculated very accurately (when compared to numerical MD simulations) without resort to complicated tabulations of fit coefficients or decomposition of conductivity from different scattering processes.

Our prescription is as follows:

Equation (40)

where Γj = Z2je2/ajkBT and ln ΛOCP is fitted by the expression

Equation (41)

In Equation (27),

Equation (42)

is obtained by setting epsilon(k) = 1 + k2rTF/k2 in Equation (27), where

krTF is the relativistic Thomas–Fermi wavevector, and the functions a(xr) and b(xr) are given by

Equation (43)

Equation (44)

with the parameters an and bn as listed in Table 3.

Table 3. Fitting Parameters an and bn, n = 1, 2, 3, to be Used in Equations (43) and (44)

n an bn
1 48.12 1.95
2 29.23 11.74
3  0.77 92.18

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The species dependence is encapsulated in the function

Equation (45)

where

We fit the coefficients a0(xr), a1(xr), b0(xr), b1(xr) piecewise over disjoint Γj and xr ranges as follows. For 10 ⩽ Γj ⩽ 30,

whereas for 30 < Γj

This fit was obtained to match the OCP structure factors of Young et al. (1991) for the range 5 ⩽ Γj < 225. However, assuming that the system stays amorphous (no periodic lattice structure), the fit has not restriction on Γj as demonstrated in Figure 11.

Figure 11.

Figure 11. OCP Coulomb logarithm ln ΛOCP as a function of Γ at xr = 1 and xr = 10, with Z = 1. The red solid lines are obtained from Equation (19) with the OCP structure factors of Young et al. (1991) valid for 5 ⩽ Γ ⩽ 225. The blue dotted lines are from our prescription Equation (41) and fit the values obtained with Young et al. (1991) very well and smoothly extend into the Γ>225 regime.

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5. APPLICATION OF THE MLMR TO OBTAIN THERMAL AND ELECTRICAL CONDUCTIVITIES OF SUPERBURST PROGENITORS

Figure 12 shows the thermal conductivity calculated from numerical MD simulations in this paper and accurately reproduced by using the mixing rule prescription of Equation (39). The conductivity of the amorphous outer crust is lower by an order of magnitude from estimates obtained using the impurity parameter formalism, Equation (25). Figure 12 (see also Figure 1) also show that 〈Z2〉, and as a consequence the conductivity, are less sensitive than Qimp to reaction processes that reduce crust impurity abruptly in the outer crust, such as (1) electron captures on very proton-rich nuclei produced in the rp-process (and therefore far away from beta-stability at the top of the crust), (2) charge particle capture and fusion reactions destroying lighter nuclei, and (3) (γ, n)- and (n, γ)-driven rearrangement of abundances in mass chains.

Figure 12.

Figure 12. Thermal conductivity as a function of density in the crust of an accreting neutron star with $\dot{M}\approx 0.1\dot{M}_{\rm Edd}$. The MD calculations (squares) which are accurately reproduced by the LMR (39) (red line) are contrasted with the electron–impurity scattering conductivity as calculated using Equation (25) over a range of four orders of magnitude in crust density. As discussed in Section 5, 〈Z2〉, and as a consequence the conductivity, is less sensitive than Qimp to composition changes at densities ∼107, 2 × 108, 1010, and 1011 g cm−3.

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We note that in the limit of a classical amorphous solid, the Coulomb logarithms for electrical and thermal conductivity are equal, i.e., ln Λσ = ln Λκ; therefore σ and κ are related by the Wiedemann–Franz law, Equation (12). Thus while we only show a plot of the outer crust thermal conductivity as function of density in Figure 12, the composition-dependent electrical conductivity is related very simply to it.

X-ray burst ash composition differences will exist between one-zone models (Schatz et al. 2001) of an X-ray Burst as opposed to a multi-zone model (Woosley et al. 2004). Our purpose here is not to study all possible compositions in a superburst progenitor, but rather to show the applicability of the MLMR to an arbitrarily complex composition with the heterogeneity expected of X-ray burst ashes. Once composition is known, MD permits us to determine the physical state and the conductivity of crust matter. Since the thermal conductivity is a critical ingredient setting the crust thermal gradient, an uncertainty in this quantity makes it difficult to predict whether shallow crust conditions ∼109 g cm−3 are conducive to superburst ignition. We will leave the full thermal profile calculation to a later work, but we point out here that a conductivity significantly lowered by impurities, such as the MD results show for the outer crust which is in the amorphous outer crust can foster a steep thermal gradient such as would be required for superburst ignition. In Brown (2004) a local stability analysis for accretion rate $\dot{M}=3 \times 10^{17}$ g s−1 shows that superburst ignition at column depth y ≈ 1012 g cm−2 is favored by an amorphous crust. Further, such a crust renders the thermal profile relatively insensitive to the core neutrino luminosity, whether from modified URCA processes (inefficient core cooling) or enhanced due to direct URCA or pionic reactions (efficient core cooling). These results were confirmed by the global stability analysis of Cooper & Narayan (2005).

A complete analysis of thermal structure requires an understanding of conductivity in the inner crust and therefore of nuclear processes at neutron drip which may reduce impurity significantly (but not completely) from that of X-ray burst ashes. We are currently performing these detailed studies and will publish the results shortly.

We thank Sanjay Reddy and Dany Page for stimulating discussions. This work was performed for the U.S. Department of Energy by Los Alamos National Laboratory under contract DE-AC52-06NA25396.

APPENDIX A: DETAILS OF MD SIMULATIONS

Some technical details of the MD simulations are collected in Table 4, namely

  • 1.  
    Nsp = number of nuclear species;
  • 2.  
    N = total number of particles in the MD simulations;
  • 3.  
    Neq = number of time steps used initially to let the system equilibrate;
  • 4.  
    Nrun = number time steps of the MD run after equilibration;
  • 5.  
    Nk = total number of wave-vector norms used to calculated Szz(k) with a1k ⩽ 22; see Equations (33) and (34).

Table 4. Simulation Parameters Used for the Mixtures Defined in Table 2

Mixture Nsp N Neq Nrun Nk
 1 55 9718 105 105 1441
 2 50 19864 105 105 2464
 3 52 19851 105 105 2497
 4 52 19840 105 105 2503
 5 50 19851 105 105 2497
 6 53 14862 105 105 2107
 7 53 19849 105 105 2517
 8 52 19857 105 105 2517
 9 49 14847 105 105 2107
10 49 19859 105 105 2506
11 52 19870 105 105 2869
12 50 19875 105 105 3095
13 54 19871 105 105 3287
14 50 19898 105 105 3350
15 49 29888 105 105 4299
16 46 39903 105 105 4972
17 24 19937 105 105 2143

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In all the simulations, the time step δt is chosen such that δt = 0.01/ωp, where ωp is the mean ion plasma frequency. The total energy is very well conserved during the simulation (better than one part in 107).

APPENDIX B: RELATIVISTIC DIELECTRIC FUNCTION

The random-phase approximation static dielectric function of the relativistic electron gas in its ground state is (Jancovici 1962)

Equation (B1)

Equation (B2)

where x = k/2kF and kTF is the (nonrelativistic) Thomas–Fermi (TF) inverse screening length

Equation (B3)

APPENDIX C: ADDITIONAL STRUCTURE FACTORS

Figures 13 and 14 shows the charge–charge structure factors Szz(k) and their mixing rule approximation for some of the compositions of Table 2 but temperatures different than 0.5 GK, as listed in Table 5.

Figure 13.

Figure 13. Structure factor Szz(k) obtained with MD simulations (blue lines) and with the mixing rule formula (38) (red line) for the mixtures 1–4 defined in Table 5.

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Figure 14.

Figure 14. Same as Figure 13 for composition 5–8 listed in Table 5.

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Table 5. Compositions Used for the MD Calculations Shown in Figures 13 and 14

Mixture T (GK) Γeff = 〈Z5/3〉Γe
1 0.27 60
2 0.73 49
3 0.81 60
4 0.84 70
5 0.85 81
6 0.85 90
7 0.84 106
8 0.83 142

Notes. For a given mixture, the composition is the same as the one given in Table 1. The only difference is in the temperature, and therefore Γeff.

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Footnotes

  • Extensions to higher-order approximations are difficult. An approximate treatment proposed by Yakovlev et al. (1987) prescribes usage of the exact binary cross-section instead of the Born approximation in the integrand of Equation (14). This introduces an additional factor in Equation (14), namely R(k) = σ(k)/σB(k) where σ is the exact differential cross section for a momentum transfer k and σB is its Born approximation. A similar procedure can be applied verbatim to our calculations since the MCP structure factor is not affected. Recently, a similar averaging procedure was used by Itoh et al. (2008); however, the title of that paper is somewhat misleading since it is not actually the second-Born approximation that is performed therein. Such a calculation would involve the higher-order correlation functions of the ionic density Equation (13). However, these higher-order correlations are noticeably absent in the equations of Itoh et al. (2008) for the transport coefficients.

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10.1088/0004-637X/703/1/994