Scanning Near-field Optical Microscopies suffer from the low signal to noise ratio, due to the smallness of the diffracting probe used to get images. Therefore a lock-in amplifier is commonly used to perform homodyne detection. From the lock-in data, we reconstruct the near-field intensity diffracted by the probe-end in the case of approach curves. We show that the reconstructed and the detected signals can strongly differ. The reconstruction of the signal is necessary to give physical interpretation.
©2005 Optical Society of America
The advent of the near-field optical microscope successfully showed, in the early eighties, the possibility of beating the classical diffraction limit of conventional imaging systems . This new kind of microscopy is aimed at acquiring information about a nanostructure through the employment of a probe, located in the vicinity of the sample, to detect a non-propagating field through its conversion into an homogeneous one. The lateral resolution (or resolving power) of the Scanning Near-Field Optical Microscope (SNOM) is closely related to the size of the probe-end. Nevertheless, if it is too small, the detected signal would be buried in the noise [2, 3, 4]. Consequently, to increase the signal-to-noise ratio, a lock-in detection at the harmonics of the frequency of the vertical vibration of the probe must be used. The amplitude of the vertical vibration is a critical parameter as illustrated theoretically  and experimentally . Walford et al have demonstrated that a large modulation amplitude should be used to produce a realistic image of the field . On the other hand, a small modulation amplitude should be used if information on specific small details of the object are of interest. Moreover, to reproduce the experimental data with numerical computations, the vibration of the probe must be also included in the model of an a-SNOM [7, 8]. For a given amplitude of vibration, the data obtained through the lock-in detection are the Fourier harmonics of the signal diffracted by the probe. Therefore, this signal must be reconstructed from the lock-in data before physical interpretation.
In this study, we propose a general method for the reconstruction of this “ideal” signal as a function of the probe vertical position. In Sec. 2 we describe a general method for the demodulation of the lock-in detected signal. Then, in Sec. 3, the proposed method is applied to simulated experimental data, in the case of approach curves. We present our main conclusions in Sec. 4.
2. The lock-in demodulation
In the following paragraphs we expose the principles of the method that will be employed for the demodulation of the simulation of the detected signals in Sec. 3.
2.1. The method
The purpose of the experiment is to measure the variations of the detected signal along an approach curve. As the signal-to-noise ratio is too weak, a lock-in amplifier is necessary to get significative data. The lock-in amplifier is tuned on the frequency of the vertical vibration of the probe and gives therefore the harmonics of the signal. A physical interpretation cannot be achieved directly from these raw lock-in data without a comparison with the “ideal signal” that would be measured with a non-vibrating probe. In the following, we will introduce the notations used for the various parameters and signals involved in this study.
The ideal signal, as shown in Fig. 1(a), corresponds to the data that may be obtained without any probe vibration and without lock-in. Therefore it can be considered as a function of the mean position of the probe z 0: si(z 0). The corresponding experimental case is shown in Fig. 1(b), where the detected signal is obtained experimentally through the lock-in amplifier. It is in fact the harmonics Hn of the signal measured along a probe vibration period. In order to extract the physical information from the recorded data, it is necessary to reconstruct si from these harmonics Hn through a demodulation scheme .
Let us consider the experimental configuration shown in Fig 1(b). We will investigate the signal si(z tip(t)) that results from the interaction between the illuminating field and the involved materials, including those of the nanostructures and the time vibrating probe. If the probe vibrates at a frequency f, the detected signal varies periodically in time and, if the vibration is harmonic, the vertical position of the probe can be expressed as z tip(t) = z 0+A(z 0)(cos(2πft)), where A(z 0) is the amplitude of vibration of the probe about its mean position z 0, A(z 0) = A if z 0 > A and A(z 0) = z 0 if z 0 < A. With reference to Fig. 1(b), the position of the probe varies within the range [z 0-A, z 0+A] if z 0 > A and [0, 2z 0] elsewhere. The last case corresponds to the tapping mode . The harmonics H 0, H 1, …, HN of the signal si(z tip(t)) are provided by the lock-in detection and can be written as:
The signal si(z tip(t)) in Eq. (1) can be considered as an even function of time. Indeed it is dependent on the probe position but not on the fact that it is approached or removed from the surface of the sample. In the case of the approach curves it is convenient to consider z tip as the variable of interest instead of time t. Therefore, the integral in Eq. (1) can be written as a function of the probe vertical position z tip = z 0+A(z 0)cos(2πft):
where ζ= (z tip-z 0)/A(z 0) and Tn(ζ) = cos(narccos(ζ)) is the Chebyshev’s polynomial of the first kind (ζ ∈ [-1,1]) . Thus the ideal signal can be written:
From Eq. (4), it is clear that the detection of several harmonics of the signal would make possible its reconstruction. However, in an experimental situation, the number of harmonics is limited. Thus the reconstructed signal is given by:
The signal RN reconstructed from the harmonics H 0,…,HN is a function of the amplitude of the vibration A and the mean position z 0 of the probe. Also RN can be expressed as a function of the normalized position of the probe ζ = (z tip-z 0)/A(z 0). The relationship between si and RN is therefore straightforwardly established as:
This equation enables to reconstruct the “ideal” signal for each position of the probe in the range [z 0-A(z 0),z 0+A(z 0)] but in the following, we focuss our attention on approach curves and therefore, all the computations will be done for ζ = 0.
In the next subsection, we illustrate the reconstruction in the case of a pure exponential decay.
2.2. The example of the pure exponential decay
To illustrate the foundations of our method, we will consider the case of the study of the evanescent decay Dp of a Fresnel wave, generated in total internal reflection of a laser beam, above a glass prism. For this purpose, the ideal signal should be the square modulus of an evanescent Fresnel field :
To clarify the interpretation of our results, the underlying hypothesis is that the probe is passive. Nevertheless, the method previously described would be also valid for the case when the probe perturbs the near-field. The measured data is the signal diffracted by the probe and recorded by the detector. In this numerical simulation, we have chosen Et = 2.4, Dp = 0.1874μm in order to be close to the experimental conditions described in . The Fourier harmonics given by the lock-in can be calculated analytically:
where In(x) is the modified Bessel function of the first kind and A(z 0) = A is the amplitude of vibration of the probe if z 0 > A. For z 0 < A, in tapping mode, A(z 0) = z 0. Figure 2 shows the influence of the amplitude of vibration A(z 0) on the first harmonic |H 1| comparatively to the ideal signal si(z 0). For a small amplitude of vibration, the first harmonic of the signal is weak. When the probe approaches the sample, in the case of the experimental “tapping” mode, the amplitude of vibration is equal to z 0. In this zone, the first harmonic |H 1| decreases toward 0 therefore the variations of |H 1| are far from the ideal signal (Eq. (7)).
In Fig. 3, we show the ideal signal si(z 0), the modulus of the first harmonic |H 1| that is directly obtained from the lock-in amplifier, the reconstructions R 1(z 0) and R 2(z 0) for A = 70nm (close to the experimental value ). In this case, only two harmonics are necessary to reconstruct the ideal signal si(z 0) along the approach curve but the shape of the first harmonic |H 1| differs strongly from the si(z 0). This example shows that the reconstruction is necessary to get a signal close to the ideal one that should be obtained without the lock-in. It is clear that in a more general case of experiments, if we have no “ab initio” information on the detected signal, its interpretation may be hazardous before reconstruction.
In the Sec. 3, we illustrate the behavior of the lock-in detection by considering simulated near-field signals.
3. Reconstruction of the ASNOM signal from harmonics
This section is devoted to the application of the reconstruction scheme proposed in this work to the case of an approach of the probe above an interference pattern. The ideal signal si(z) results from the interferences between an evanescent wave with amplitude Et and a background homogeneous wave Eg. The corresponding experiment has been described by Aubert et al . In that paper, the detected signal is supposed to be independent of the characteristics of the probe, which also is supposed to be passive. Therefore it does not modify the interference fringes that would exist without its presence in the experiment. This assumption seems to be valid in this particular case; however, in the general case, the method of reconstruction of the ideal signal takes into account the interaction with the probe.
The ideal signal along the approach curve can be written as:
where Dp is the decay of the evanescent wave [6, 10] and ϕ the phase between the two waves. The purpose of the experiment is to measure this ideal signal. The lock-in furnishes harmonics of this signal deduced from the vertical vibration of the probe around z 0. The amplitude of vibration is A(z 0). In this example, we can calculate analytically the harmonics of the ideal signal as:
where δ n0 is the Kronecker delta. Equation (11) shows that the two terms with exponential decay are modulated by modified Bessel functions of the first kind In. To illustrate the difference between the first harmonic data |H 1| (given by Aubert et al ) and the ideal signal si(z 0) we show in Fig. 4 the associated maps as functions of the approach distance z 0 and the phase ϕ. From this map, it appears that it may be hazardous to do physical interpretation from the first harmonic as it can differ strongly from the ideal signal. At this stage, we may conclude that the discrepancy between the recorded signal |H 1| and the ideal signal Si may be mainly due to the amplitude of the vibration of the probe A = 70nm.
Consequently, to complete the discussion, we show in Figures 5, the influence of the amplitude of vibration on the discrepancy between the recorded signal |H 1|, the reconstructed signal R 1 and the ideal signal si. Figures 5(a-b) show the case of constructive interference (ϕ = 0) and Figs. 5(c-d) show the case of destructive interference (ϕ = π) for various amplitudes of vibration A ∈ [40nm, 200nm]. As expected, the influence of the amplitude of vibration is visible on the reconstructed signal even if A is much smaller than Dp. Moreover, the first harmonic amplitude differs strongly from the useful ideal signal. Therefore, the aim of the following is to reconstruct the ideal signal when the probe is above a bright fringe and a dark fringe.
Finally, we show in Figs. 6(a) and 6(b) the simulated first harmonic |H 1| (Eq. (11)), the reconstructed signals R 0(z), R 1(z), R 2(z) from computed harmonics (Eq. (5)) and the ideal signal that should be measured without probe vibration along the approach curve si(z 0) (Eq. (9)), for ϕ= 0 (bright fringe) and ϕ=π(dark fringe), respectively. The other parameters are A = 70 nm, Dp = 187.4 nm, Et = 2.4 and Eg = 1.28. They are either deduced from the experimental setup  or from a non linear fit using evolutionary algorithm . The field amplitude are in arbitrary units because they are deduced from the experimental curve, which is measured in arbitrary units. Again, a first visual inspection reveals that |H 1| is far from the expected (or ideal) signal si(z 0). For this example, we may conclude that the reconstruction of the signal may be considered as satisfactory by using only three harmonics H 0, H 1 and H 2.
We have demonstrated that the SNOM recorded signal, if a lock-in detection is used, cannot be interpreted directly. In order to get information on the electromagnetic interaction between the light, the nanostructures and the probe along an approach curve, we have presented a method to reconstruct the “ideal” signal, from the harmonics of the lock-in detection. The use of the Chebyshev polynomials enables a versatile reconstruction that could permit to deduce a physically meaningful signal from the lock-in experimental data. In principle, there are no visible restrictions to extend the application of the proposed method to the case of scanned maps. In the future, the use of near-field intensity data obtained from heterodyne setups will open the possibility of using this method for a more general application than for approach curves.
Authors are grateful to D. Macias and A. Vial for fruitful discussion on the improvement of this paper.
References and links
1. D. Courjon and C. Bainier, “Near field microscopy and near field optics,” Rep. Prog. Phys. 57, 989–1027 (1994). [CrossRef]
2. J.J. Greffet and R. Carminati, “Image formation in near-field optics,” Prog. Surf. Sci. 56, 133–237 (1997). [CrossRef]
3. C. Girard, C. Joachim, and S. Gauthier, “The physics of the near-field,” Rep. Prog. Phys. 63, 893–938 (2000). [CrossRef]
4. A. Dereux, C. Girard, and J.C. Weeber, “Theoretical principles of near-field optical microscopies and spectroscopies,” J. Chem. Phys. 112, 7775–7789 (2000). [CrossRef]
5. J.N. Walford, J.A. Porto, R. Carminati, J.J. Greffet, P.M. Adam, S. Hudlet, J.L. Bijeon, A. Stashkevitch, and P. Royer, “Influence of tip modulation on image formation in scanning near-field optical microscopy,” J. Appl. Phys. 89, 5159–5169 (2001). [CrossRef]
6. S. Aubert, A. Bruyant, S. Blaize, R. Bachelot, G. Lerondel, S. Hudlet, and P. Royer, “Analysis of the interferometric effect of the background light in apertureless scanning near-field optical microscopy,” J. Opt. Soc. Am. B 20, 2117–2124 (2003). [CrossRef]
8. R. Fikri, T. Grosges, and D. Barchiesi, “Apertureless scanning near-field optical microscopy: Numerical modeling of the lock-in detection,” Opt. Commun. 232, 15–23 (2004). [CrossRef]
9. I.S. Gradshteyn and I.M. Ryzhik, Table of Integrals, Series, and Products. (Academic Press Inc., London, 1994).
10. M. Born and E. Wolf, Principle of Optics (Pergamon Press, Oxford, 1993).
11. D. Macías, A. Vial, and D. Barchiesi, “Application of evolution strategies for the solution of an inverse problem in near-field optics,” J. Opt. Soc. Am. A 21, 1465–1471 (2004). [CrossRef]