Synchrotron radiation from radio galaxies is known to be linearly polarized. Even unresolved sources show mea-surable linear polarization. Using this linear polarization property, I can measure the fractional polarization and the polarization angle of the radiation after traversing the Faraday medium (e.g. a magnetized thermal plasma be-tween the polarized source and us). First investigations of the galactic Faraday medium were made by Simard-Normandin et al. (1981) and others using the integrated polarization of extragalactic sources. With increased sen-sitivity and angular resolution of radio telescopes and telescope arrays, the investigation of the Faraday medi-um of radio galaxies has become one of the main inter-ests of this field. Burn (1966) and Laing (1984) have shown that deciphering the geometry of the Faraday medium is very complex. In general, there are two basic geometric configurations.

- The Faraday medium is 'internal' to the source, and physically mixed with the emitting volume (e.g. a thermal cloud surrounded by a shell of relativistic electrons).

- A foreground Faraday medium (in front of the syn-chrotron source) has a fine structure that is unresolved by the telescope.

Decades of multi-frequency observations have shown that the Faraday rotation is highly linear in λ² when the spatial resolution is good enough. This linearity is the property of the resolved slab and the external (resolved)Faraday medium (Burn 1966). The difference between the internal slab geometry and the external medium be-comes evident in the fractional polarization. In the inter-nal case, I will see the secondary maxima of the fractional polarization in the low-frequency regime. In the exter-nal case, I will see no depolarization at low frequencies.The observational results seem to be 'in between.' The achievement of full frequency-sampled data is virtually impossible. While a depolarization trend is seen, it is not easy to distinguish between the internal slab and the un-resolved external component.

The Faraday rotation of supernova remnants and spiral galaxies is an example of the first case. In this case, the Faraday rotation profile is non-linear in λ². On the other hand, the observational results of radio galaxies over the last decades, especially multi-frequency observations with high angular resolution, have proven that Faraday rotation in radio galaxies does follow a λ² law. Therefore, it must be concluded that the Faraday-rotating media do not permeate the lobes of radio galaxies. Recently ob-tained sensitive X-ray images (e.g. with ROSAT, Chandra) exhibit cavities in the hot gas towards the lobes of radio galaxies. This confirms that the thermal electrons of the X-ray halos and the relativistic electrons of the radio lobes are not mixed. Physically, this could imply pressure bal-ance between the thermal and the relativistic electrons. Alternatively, it could mean rapid acceleration of the thermal electrons in the radio lobes and rapid cooling of the relativistic electrons in the X-ray halo. In any case, the λ² behavior of the Faraday rotation of radio galaxies in-dicates that the differential depolarization (DP) and the rotation measure (RM) of radio galaxies are due to an 'ex-ternal' Faraday medium. It also implies that the Faraday media are almost or even fully resolved. This should lead to a low differential de-polarization.

In the case of fully resolved Faraday cells and assum-ing that radio galaxies reside in the center of X-ray halos with King profiles, I expect an RM asymmetry instead of a depolarization asymmetry. Although the scale length of the Faraday cells is not definitely known yet, the λ² be-havior suggests that I do resolve the Faraday screen. On the other hand, the asymmetry of the DP (i.e. the -'Laing-Garrington effect' Laing [1988], Garrington et al. [1988]) is known to be the best proof of the relativistic beaming effect of jets in radio galaxies. The Laing-Garrington ef-fect means that a non-negligible amount of (magnetic) energy is contained in small-scale (unresolved) magnetic field structures. In that case, Faraday rotation will deviate from the λ² behavior and will be saturated at ？χ < π / 3 (Burn 1966).

The fractional polarization of a radio source is deter-mined by the pitch angle distribution of the relativistic electrons, the geometry of the magnetic field, and by the energy distribution function of the relativistic electrons

The general power-law distribution is known from radio observations, cosmic-ray experiments, and from theory. The theoretical fractional polarization of the ra-dio intensity is (almost) independent of frequency. On the other hand, the measured fractional polarization of the flux density is additionally dependent on the depolariza-tion due to differential Faraday rotation, i.e. on the dis-tribution of thermal electrons along the line-of-sight, as well as the line-of-sight component of the magnetic field. This way, the polarized component of the radiation under-going Faraday rotation becomes frequency dependent.

For decades, one-sided jets of active galactic nuclei have been observed. The most successful explanation of this phenomenon is Doppler boosting caused by the relativistic bulk motion of the jet material. Since the radio lobes are connected to, and fed by, the jets, large efforts have been made in order to look for independent projec-tion effects which do or do not support the interpretation in terms of projection effects of the relativistic jets. As far as the radio lobes are concerned, the depolarization asymmetry, i.e. the Laing-Garrington effect, is the stron-gest support of this view. The other asymmetries of the radio lobes, the lobe length and the spectral index asym-metry, do not show any clear connection to the projection effect of the relativistic jets. To conclude, the Laing-Gar-rington effect is interpreted in terms of DP. In case of such an internal DP, the foreground medium should also have magnetic field reversals along the line-of-sight.

In this Section, I discuss the Ricean bias in the polar-ization intensity and suggest a new correction method. The linearly polarized intensity is obtained from Stokes parameters U and Q according to

It follows a Ricean distribution (Vinokur 1965):

where I_pobs is the observed polarized intensity, I_p is the in-trinsic polarized intensity, B₀ is the modified Bessel func-tion of zero order and σ_Ip is the noise level. For I_p ≫ σ _Ip and I_p ~ σ _Ip the Rice distribution is approximated by the well known statistical forms. In the case of I_p ≫ σ, the Rice distribution of I_pobs asymptotically approaches a Gaussian distribution (Fig. 1). Since the Gaussian is a symmetric distribution, the most probable value and the peak value, df / dI_P = 0 are the same. Therefore, the most probable I_pobs is the real I_p in this case (Fig. 1).

In the other case, I_p ~ σ_Ip, the Rice distribution of I_pobs is a Rayleigh distribution (Fig. 2). In this case, the most probable value is larger than the peak value, df / dI_P = 0,

The reason is that the Rayleigh distri-bution is an asymmetric distribution. This has become known as the Ricean bias in the literature, and is caused by the positivity of the noise in

Different from the polarized intensity, the distribution function of the polarization angles remains symmetric, and no Ricean bias correction is needed (Wardle & Kronberg 1974), since there is no positivity problem in χ = tan^-1 ( U /Q ).

In practice, two solutions of the Ricean bias correction are widely used.

Wardle & Kronberg (1974) have suggested a solution based on the mode of the equation, namely,

A good approximation of this solution is

Conventionally,

with c₁ = 1.2. As seen above,

is the Rayleigh distribution.

The other solution which is based on a more solid sta-tistical reasoning, viz. the maximum likelihood method,

was suggested by Killeen et al. (1986). With in-creasing signal-to-noise, the Maximum Likelihood esti-mate approaches the value of I_P more rapidly:

A good approximation of this solution is

which is implemented in the AIPS task POLCO as such.

The performance of the maximum likelihood estima-tion is better at high signal-to-noise, I_P / σ_IP > 5, but does not yield any significant effect, since the difference to the solution of Wardle & Kronberg (1974) is much less than 1% (Figs. 3 and 4). This is because the probability distri-bution of I_pobs becomes a (symmetric) Gaussian at high

signal-to-noise. On the contrary, the difference at low sig-nal-to-noise, i.e. the overestimate of the maximum like-lihood solution, is significant. As mentioned in the help tool to AIPS task POLCO, one should assume an underes-timate of up to about a factor of 2 of the noise level, due to the so-called 'magic blanking'. Therefore, if one wants to go down to a 3- σ_Ip level, the choices of the solution and of c₁ become critical.

In the Wardle & Kronberg (1974) solution,

, c₁ should be carefully selected. As I am not interested in values of I_P as low as I_pobs ~ σ_Ip , c₁ should be lower than

for a better performance in the range 3 < I_pobs / σ_Ip < 6 ~ 10. Above 6σ_Ip ··· 10σ_Ip, I can expect the best performance using the ML solution. From our ex-periments, I conclude that c₁ = 0.9 is a reasonable choice (Figs. 3 and 4)

Our goal is to improve the performance of the Ricean correction such that

should be reliable down to 3σ_Ip and 3σ_Ip. In the next subsection, I will show the importance of the areal mean m' and the position infor-mation of DP. Our scheme is simple. I make a hybrid so-lution of the two solutions explained in the former sub-section. At high signal-to-noise, I will still use the scheme of Killeen et al. (1986). At low signal-to-noise, the solution of Wardle & Kronberg (1974) is better, but with c₁ = 0.9.

The selection of c₁ has been done numerically, consid-ering the fact that one should take account of the under-estimation of the noise by up to factor of 2 in the intensity (National Radio Astronomical Observatory 2011), due to the blanked values. Further minor estimation errors could be caused, for example, through a wrong selection of the noise estimation area, which could further under-estimate σ_Ip. I combine the two solutions (Wardle & Kro-nberg 1974, Killeen et al. 1986). Our solution accepts the Maximum Likelihood over I_pobs ~ 6σ_Ip ; below this, it uses

with c₁ = 0.9, which is a good choice for σ_Ip / I_pobs between 1.5 to 6. Using this new fractional polar-ization, I can estimate DP with the positional information and can study any correlation between RM and DP.

Before working out a new method to estimate the frac-tion of polarization, I discuss the integrated fractional po-larization as published in the literature, motivating this new correction method. There are two ways to estimate the fractional polarization of a region of interest. One can first integrate the polarized and the total intensity and di-vide them:

There are pros and cons to this integrated estimate. The pro is that the Ricean bias problems are largely removed by the integration. The obtained m' reflects the fractional polarization of bright source structures, such as cores, hot spots and jets. The con is the loss of the positional infor-mation. Conventionally, DP maps are presented after one of the Ricean bias corrections, i.e. (Wardle & Kronberg 1974, Killeen et al. 1986), down to 3σ_Ip of the total inten-sity. This will lead to significant over- and underestimates of the low - σ_I,P regions, such as the lobes. Therefore, in order to estimate the fractional polarization including the positional information, an estimate

is desirable.

In polarization studies, other important informations are the polarization angle and the RM. Since they are in-dependent of the brightness, the use of DP as obtained from

could lead to a wrong interpretation.

In this subsection, I discuss the propagation of the sys-tematic error as due to the insufficient Ricean bias cor-rection in published DP maps. The discussion is based on the solution of Killeen et al. (1986). For the solution of Wardle & Kronberg (1974), this should be interpreted in an opposite sense. In that case, the systematic error in regions with low polarization intensity is less important, unless the signal-to-noise is too low in the absence of any σ_Ip cut-off.

I consider the problem of underestimating σ_Ip for two cases, namely for well resolved and for unresolved sourc-es. I assume a power-law distribution for Iν. When the source and the Faraday medium are resolved, the over-estimate caused by the 3σ_Ip cut is serious at the highest frequencies. In this case, the fractional polarization of re-gions with low I_p could be overestimated. The other case is that of low angular resolution. Because of the Faraday rotation in the foreground medium, depolarization will be significant. In the most depolarized regions, a cut at 3σ_Ip is serious at the lowest frequencies. Then the frac-tional polarization of such regions is overestimated at the lowest compared to the highest frequencies. In effect, the depolarization trend will thus be reduced.

In depolarization studies, the integrated DP is rather in-dependent of the polarized and total intensity, but rather depends on

where S is the projected surface. The first case (resolved source) overestimates DP, while the second (unresolved source) underestimates it. Let us discuss this in the light of the Laing-Garrington effect. If one can assume that the jet side is brighter and more po-larized, the two arguments will be more important for the counter-jet lobe. In the first case, the Laing-Garrington effect will be emphasized through the overestimate of DP, whereas it will be reduced in the second case because of the under-estimation.

One more word of caution seems to be necessary re-garding DP structures. Patchy distributions of DP in re-gions with low I_p which are frequently seen should be interpreted with utter care. One can mis-interpret such a patchy structure as real turbulence or fluctuations. Un-less such patchy structures are confirmed independently, e.g. also in RM maps, they could be solely statistical.