Abstract

This paper investigates, through simulation and experiment, the behavior of two dimensional foci arrays generated via phase-only holography where an iterative algorithm was used to produce the kinoforms. Specifically, we studied how aliasing of the signal on a spatial light modulator affects the quality of the foci array as the density and size of the array are varied. This study provides a reference for applications where it is important to understand how the fidelity and overall quality of the foci array changes as the number of foci increases and as the spacing between foci decreases.

© 2011 OSA

1. Introduction

Holograms are used in many areas, including three-dimensional image formation [1], wavefront correction [2], and optical interconnects [3]. More recently phase-only holograms, or kinoforms [4], have attracted much interest for use in microscopy-based techniques, including digital holographic microscopy [5], structured illumination [6], and optical manipulation [7]. For many of these applications, static kinoforms [8] have given way to dynamic implementations using spatial light modulators (SLMs) [9]. These devices enable real-time modulation of kinoforms and thus allow time varying processes to be implemented [10], such as forming and changing the positions of multiple optical traps in real time.

For many of these applications, it is important to understand what limits the complexity of the patterns that can be formed using kinoforms. In the context of parallel optical trapping, a body of work has been carried out with the aim of optimizing the generation of an array of laser foci for manipulating micro- and nanoparticles [11, 12]. For optical trapping, the number of foci is often limited by the amount of laser power that the SLM can tolerate, because each laser focus must have sufficient power for trapping. For imaging applications, such as in spatial patterning of illumination, the laser powers involved are typically much lower than in optical trapping. As a result, the number of laser foci is no longer constrained by laser power, but by the accuracy of the kinoform used to generate a large number of foci that are closely spaced.

Kinoforms displayed on SLMs are effectively discretized versions of the ideal solution used to form the foci array. Therefore, it is important to understand the effects any aliasing may have upon the arrays produced. As with any spatially varying signal, it must sample the original signal at or above the Nyquist frequency to prevent aliasing. Finding the solution from an iterative algorithm gives no analytical description of the kinoform, so it is impossible to predict when aliasing will degrade the resulting image. As such we decided to undertake an empirical study to understand how aliasing affects the quality of the 2D foci array, specifically when the foci become very dense and also large in number.

Figure 1 depicts the setup we used for this study. Here, the system uses the standard configuration of a Fourier transform lens placed one focal length from the kinoform to produce foci in the back focal plane of the lens [13]. In our experiments, this image is de-magnified onto the focal plane of a microscope. The array parameters are described by the inter-foci spacing, dx, the number of laser foci, Nfoci, and the maximum spatial frequency, fmax.

 

Fig. 1 The holography apparatus is constructed with a 4f system. L 1 is the Fourier transform lens, L 2 is a second lens, f 1 = 300 mm, f 2 = 500 mm. Inset shows our definitions of maximum spatial frequency, fmax, and inter-foci spacing, dx, within the microscope focal plane (MFP).

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In most applications, regardless of whether the intensity pattern is for optical trapping or fluorescence imaging, the desired foci array is known and the corresponding kinoform must be found, a classic inverse problem. Analytical solutions exist using superposition algorithms that allow foci to be placed < 10 nm apart [14], but this approach quickly produces poor kinoforms for foci number ≳ 10. For larger arrays, an iterative-type weighted Gerchberg-Saxton algorithm, with a superposition starting phase, provides the best result in terms of uniformity of the generated foci, efficiency, and relative standard deviation (rel. σ) of foci intensities [12]. However, this method limits the spacing between foci to δx=(λf1fobj)/(f2aNpix), where f 1 is the focal length of the transform lens, f 2 is the focal length of the second lens, λ is the wavelength of light, a is the pixel pitch of the SLM, and Npix is the number of pixels in the kinoform [15]. It is this iterative algorithm we concentrate on here.

De-coupling the inter-dependent parameters - density of foci, ρfoci, number of foci, Nfoci, maximum spatial frequency, fmax, and inter-foci spacing, dx - is not possible, so we approached the problem by asking two main questions that are pertinent to our aims. First, for a given dx, what effect does varying Nfoci have? Second, for a given fixed fmax, what effect does increasing ρfoci have?

For our study the non-aliased ‘original’ kinoform was created through the iterative algorithm because an exact solution does not exist. We also chose to study symmetric square patterns centered on the 0th order. To determine the size of original kinoform that we needed in our studies, kinoforms were calculated with a fixed set of parameters and with increasing number of pixels in the result, Norig, after which consecutive original kinoforms were compared through the mean residual of their differences. As an example, Fig. 2 shows increasing Norig reduced the difference between consecutive kinoforms. For larger inter-foci spacing, convergence occurred for larger Norig. From this set of calculations, we determined kinoforms calculated with Norig=2000 should be sufficient to represent the true signal.

 

Fig. 2 Root mean square residual difference between original kinoforms with Norig=100P and Norig=100(P1) where P are integers between 1 and 21. Here Nfoci = 100 and dx is varied between 5δx and 30δx.

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Fourier transforming the kinoform with flat-top uniform incident light, normalized to an intensity of unity, simulates the optical system shown in Fig. 1, thereby allowing us to examine and compare the intensities of the foci with our experimental results. The quality of foci arrays produced are quantified using the rel. σ of foci intensities in the array, which has been shown to be a reliable metric of pattern quality [12]. The aliased kinoform was constructed by sampling every Norig/Nal_pix pixels while retaining the same size of the original kinoform (Fig. 3).

 

Fig. 3 Left panel: A 100 × 100 pixel section of original kinoform with Norig=2000. Right panel: Same section of the original kinoform aliased to Nal_pix=500pixels. One pixel in the right panel has the same physical dimension as 16 pixels in the left panel. Both white grids in the upper right corner of the panel display boxes that are 4 × 4 original pixels in size.

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In Fig. 4, with dx = 10δx, the quality of the simulated foci array is plotted as a function of Nfoci for several Nal_pix. It can be seen rel. σ increases with Nfoci, and the inset shows, for Nfoci = 400, aliasing the kinoform below 10002 pixels results in a rapid decrease in quality.

 

Fig. 4 Simulated relative standard deviation of foci intensities (rel. σ) versus increasing number of foci (Nfoci) for kinoforms with varying numbers of aliased pixels (Nal_pix) and dx = 10δx. The legend indicates Nal_pix for each curve. Inset shows the effect of aliasing on rel. σ for Nfoci = 400.

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Figure 5 plots the quality of the foci array as a function of ρfoci when the original kinoform was aliased to several Nal_pix and with fmax = 30δx. After an initial increase in rel. σ, counter-intuitively, there exists a threshold in density above which the quality of the kinoform remained approximately equal. The inset shows, for ρfoci = 0.071 foci μm−2, when aliased below 10002 pixels there was a rapid decrease in the quality of the kinoform.

 

Fig. 5 Simulated relative standard deviation of foci intensities (rel. σ) plotted as a function of the density of foci (ρfoci) for kinoforms with varying numbers of aliased pixels (Nal_pix) and for fmax (maximum spatial frequency) = 30δx. The legend indicates Nal_pix for each curve. Inset shows the effects of aliasing on pattern quality for a single ρfoci = 0.071 foci μm−2.

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To test the findings experimentally we constructed an optical system as in Fig. 1. A c.w. 1064 nm laser (YLD-10-LP, IPG Photonics Corp.), power controlled using a λ/2 plate and polarizing beam cube, was expanded to fill the short axis of an SLM (Holoeye PLUTO NIR). A second λ/2 plate was used to optimize the diffraction efficiency through varying the polarization incident on the SLM. To image the foci array, we placed a mirror at the focal plane of the objective to image the reflection of the formed foci. The SLM was imaged using a 4f system to slightly overfill the back aperture of a 40× NA=1.4 Nikon Plan Fluor objective. Images were taken using a GC1380 GigE camera (Allied Vision Technologies) and analysis carried out with custom written LabVIEW software (v8.6 National Instruments Corp.), which measured the intensities of each foci and calculated their standard deviation relative to the mean intensity.

The SLM was calibrated to give a linear phase retardation response up to a maximum of 2π as a function of gray value applied [16]. Any non-flatness in the device was removed by using Zernike polynomials to create a correction kinoform [17] encoded into the test kinoforms, which produced a 2.200 ± 0.002 fold increase in Strehl ratio.

The original kinoforms used for Fig. 4 were first aliased to Norig=1080 then test holograms were made for Nal_pix = 200 and 1080. These were displayed on the SLM and images taken of the resulting intensity patterns in the focal plane of the microscope. Figure 6 shows the measured rel. σ for several Nfoci; note only two differing Nal_pix are shown for clarity. Figure 6 indicates the same power-law trend is seen experimentally as in simulations. Experimentally we observed heavily aliased kinoforms performed comparably to the larger Nal_pix until Nfoci ≈ 50. The inset shows aliasing begins to severely affect pattern quality when Nal_pix ≲ 6002 pixels.

 

Fig. 6 Experimentally measured relative standard deviation of foci intensities (rel. σ) plotted as a function of the number of foci (Nfoci) for Nal_pix (number of aliased pixels) = 200 and 1080; dx = 10δx. Inset shows the effect of aliasing on rel. σ for Nfoci = 400. Error bars represent standard deviation; n = 20.

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Finally kinforms of Fig. 5 were aliased in a similar fashion and placed on the SLM to generate the experimental measurements shown in Fig. 7. Again, only two different Nal_pix are shown for clarity. Here, we observed rel. σ increased consistently with ρfoci. Kinoforms with less aliasing performed better overall with performance again rapidly decreasing for Nal_pix ≲ 6002.

 

Fig. 7 Experimentally measured relative standard deviation of foci intensities (rel. σ) for varying foci density (ρfoci); Nal_pix (number of aliased pixels) = 200 and 1080; fmax (maximum spatial frequency) = 30δx. Inset shows the effect of aliasing on rel. σ for ρfoci = 0.071 foci μm−2. Error bars represent standard deviation; n = 20.

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Experimentally the measurements indicate a poorer performance than that expected from simulation. We believe this is partly attributed to an increasing amount of speckle, known to occur in kinoform reconstruction [18], as the pattern complexity increases. Future studies should investigate the effectiveness of utilising a dummy area to improve precision [15].

Through simulations and experiments, we have characterized and given the first reference on how iteratively generated kinoforms perform at producing large or dense 2D arrays of laser foci. There are no limits on Nfoci and dx (above δx) per se, but as we have shown here, one must carefully balance the quality of the intensity pattern needed for the application with Nfoci and dx. Finally, our studies show kinoforms need at least ≈ 6002 pixels to accurately represent the kinoform desired. This study should serve as a useful reference for applications, such as parallel confocal imaging or patterned illumination, in which it is important to understand how aliasing affects the degradation of the quality of the arrayed laser foci as the number or density of the foci is increased.

Acknowledgments

We thank Xudong Chen for many useful discussions. We are grateful to the NIH ( GM 085485) for support of this work.

References and links

1. D. Gabor, “Microscopy by reconstructed wave-fronts,” Proc. R. Soc. London Ser. A 197, 454–487 (1949). [CrossRef]  

2. G. D. Love, “Wave-front correction and production of Zernike modes with a liquid-crystal spatial light modulator,” Appl. Opt. 36, 1517–1524 (1997). [CrossRef]   [PubMed]  

3. K. L. Tan, W. A. Crossland, and R. J. Mears, “Dynamic holography for optical interconnections. I. Noise floor of low-cross-talk holographic switches,” J. Opt. Soc. Am. A 18, 195–204 (2001). [CrossRef]  

4. L. B. Lesem, P. M. Hirsch, and J. A. Jordan Jr, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969). [CrossRef]  

5. W. Xu, M. H. Jericho, I. A. Meinertzhagen, and H. J. Kreuzer, “Digital in-line holography of microspheres,” Appl. Opt. 41, 5367–5375 (2002). [CrossRef]   [PubMed]  

6. B. Chang, L. Chou, Y. Chang, and S. Chiang, “Isotropic image in structured illumination microscopy patterned with a spatial light modulator,” Opt. Express 17, 14710–14721 (2009). [CrossRef]   [PubMed]  

7. G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008). [CrossRef]  

8. W. H. Lee, “Sampled Fourier transform hologram generated by computer,” Appl. Opt. 9, 639–643 (1970). [CrossRef]   [PubMed]  

9. G. Whyte and J. Courtial, “Experimental demonstration of holographic three-dimensional light shaping using a Gerchberg-Saxton algorithm,” N. J. Phys. 7, 117 (2005). [CrossRef]  

10. G. Sinclair, P. Jordan, J. Courtial, M. Padgett, J. Cooper, and Z. J. Laczik, “Assembly of 3-dimensional structures using programmable holographic optical tweezers,” Opt. Express 12, 5475–5480 (2004). [CrossRef]   [PubMed]  

11. J. E. Curtis, C. H. J. Schmitz, and J. P. Spatz, “Symmetry dependence of holograms for optical trapping,” Opt. Lett. 30, 2086–2088 (2005). [CrossRef]   [PubMed]  

12. R. di Leonardo, F. Ianni, and G. Ruocco, “Computer generation of optimal holograms for optical trap arrays,” Opt. Express 15, 1913–1922 (2007). [CrossRef]   [PubMed]  

13. J. W. Goodman, Introduction to Fourier Optics, 3rd Ed. (Roberts and Company Publishers, 2005).

14. C. H. J. Schmitz, J. P. Spatz, and J. E. Curtis, “High-precision steering of multiple holographic optical traps,” Opt. Express 13, 8678–8685 (2005). [CrossRef]   [PubMed]  

15. Y. Takaki and J. Hojo, “Computer-generated holograms to produce high-density intensity patterns,” Appl. Opt. 38, 2189–2195 (1999). [CrossRef]  

16. C. Kohler, X. Schwab, and W Osten, “Optimally tuned spatial light modulators for digital holography,” Appl. Opt. 45, 960–967 (2006). [CrossRef]   [PubMed]  

17. K. D. Wulff, D. G. Cole, R. L. Clark, R. Di Leonardo, J. Leach, J. Cooper, G. Gibson, and M. J. Padgett, “Aberration correction in holographic optical tweezers,” Opt. Express 14, 4169–4174 (2006). [CrossRef]   [PubMed]  

18. J. Amako, H. Miura, and T. Sonehara, “Speckle-noise reduction on kinoform reconstruction using phase-only spatial light modulator,” Appl. Opt. 34, 3165–3171 (1995). [CrossRef]   [PubMed]  

References

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  1. D. Gabor, “Microscopy by reconstructed wave-fronts,” Proc. R. Soc. London Ser. A 197, 454–487 (1949).
    [CrossRef]
  2. G. D. Love, “Wave-front correction and production of Zernike modes with a liquid-crystal spatial light modulator,” Appl. Opt. 36, 1517–1524 (1997).
    [CrossRef] [PubMed]
  3. K. L. Tan, W. A. Crossland, and R. J. Mears, “Dynamic holography for optical interconnections. I. Noise floor of low-cross-talk holographic switches,” J. Opt. Soc. Am. A 18, 195–204 (2001).
    [CrossRef]
  4. L. B. Lesem, P. M. Hirsch, and J. A. Jordan, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969).
    [CrossRef]
  5. W. Xu, M. H. Jericho, I. A. Meinertzhagen, and H. J. Kreuzer, “Digital in-line holography of microspheres,” Appl. Opt. 41, 5367–5375 (2002).
    [CrossRef] [PubMed]
  6. B. Chang, L. Chou, Y. Chang, and S. Chiang, “Isotropic image in structured illumination microscopy patterned with a spatial light modulator,” Opt. Express 17, 14710–14721 (2009).
    [CrossRef] [PubMed]
  7. G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
    [CrossRef]
  8. W. H. Lee, “Sampled Fourier transform hologram generated by computer,” Appl. Opt. 9, 639–643 (1970).
    [CrossRef] [PubMed]
  9. G. Whyte and J. Courtial, “Experimental demonstration of holographic three-dimensional light shaping using a Gerchberg-Saxton algorithm,” N. J. Phys. 7, 117 (2005).
    [CrossRef]
  10. G. Sinclair, P. Jordan, J. Courtial, M. Padgett, J. Cooper, and Z. J. Laczik, “Assembly of 3-dimensional structures using programmable holographic optical tweezers,” Opt. Express 12, 5475–5480 (2004).
    [CrossRef] [PubMed]
  11. J. E. Curtis, C. H. J. Schmitz, and J. P. Spatz, “Symmetry dependence of holograms for optical trapping,” Opt. Lett. 30, 2086–2088 (2005).
    [CrossRef] [PubMed]
  12. R. di Leonardo, F. Ianni, and G. Ruocco, “Computer generation of optimal holograms for optical trap arrays,” Opt. Express 15, 1913–1922 (2007).
    [CrossRef] [PubMed]
  13. J. W. Goodman, Introduction to Fourier Optics, 3rd Ed. (Roberts and Company Publishers, 2005).
  14. C. H. J. Schmitz, J. P. Spatz, and J. E. Curtis, “High-precision steering of multiple holographic optical traps,” Opt. Express 13, 8678–8685 (2005).
    [CrossRef] [PubMed]
  15. Y. Takaki and J. Hojo, “Computer-generated holograms to produce high-density intensity patterns,” Appl. Opt. 38, 2189–2195 (1999).
    [CrossRef]
  16. C. Kohler, X. Schwab, and W Osten, “Optimally tuned spatial light modulators for digital holography,” Appl. Opt. 45, 960–967 (2006).
    [CrossRef] [PubMed]
  17. K. D. Wulff, D. G. Cole, R. L. Clark, R. Di Leonardo, J. Leach, J. Cooper, G. Gibson, and M. J. Padgett, “Aberration correction in holographic optical tweezers,” Opt. Express 14, 4169–4174 (2006).
    [CrossRef] [PubMed]
  18. J. Amako, H. Miura, and T. Sonehara, “Speckle-noise reduction on kinoform reconstruction using phase-only spatial light modulator,” Appl. Opt. 34, 3165–3171 (1995).
    [CrossRef] [PubMed]

2009 (1)

2008 (1)

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

2007 (1)

2006 (2)

2005 (3)

2004 (1)

2002 (1)

2001 (1)

1999 (1)

1997 (1)

1995 (1)

1970 (1)

1969 (1)

L. B. Lesem, P. M. Hirsch, and J. A. Jordan, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969).
[CrossRef]

1949 (1)

D. Gabor, “Microscopy by reconstructed wave-fronts,” Proc. R. Soc. London Ser. A 197, 454–487 (1949).
[CrossRef]

Amako, J.

Carberry, D. M.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

Chang, B.

Chang, Y.

Chiang, S.

Chou, L.

Clark, R. L.

Cole, D. G.

Cooper, J.

Courtial, J.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

G. Whyte and J. Courtial, “Experimental demonstration of holographic three-dimensional light shaping using a Gerchberg-Saxton algorithm,” N. J. Phys. 7, 117 (2005).
[CrossRef]

G. Sinclair, P. Jordan, J. Courtial, M. Padgett, J. Cooper, and Z. J. Laczik, “Assembly of 3-dimensional structures using programmable holographic optical tweezers,” Opt. Express 12, 5475–5480 (2004).
[CrossRef] [PubMed]

Crossland, W. A.

Curtis, J. E.

di Leonardo, R.

Gabor, D.

D. Gabor, “Microscopy by reconstructed wave-fronts,” Proc. R. Soc. London Ser. A 197, 454–487 (1949).
[CrossRef]

Gibson, G.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

K. D. Wulff, D. G. Cole, R. L. Clark, R. Di Leonardo, J. Leach, J. Cooper, G. Gibson, and M. J. Padgett, “Aberration correction in holographic optical tweezers,” Opt. Express 14, 4169–4174 (2006).
[CrossRef] [PubMed]

Goodman, J. W.

J. W. Goodman, Introduction to Fourier Optics, 3rd Ed. (Roberts and Company Publishers, 2005).

Hirsch, P. M.

L. B. Lesem, P. M. Hirsch, and J. A. Jordan, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969).
[CrossRef]

Hojo, J.

Ianni, F.

Jackson, J. C.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

Jericho, M. H.

Jordan, J. A.

L. B. Lesem, P. M. Hirsch, and J. A. Jordan, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969).
[CrossRef]

Jordan, P.

Kohler, C.

Kreuzer, H. J.

Laczik, Z. J.

Leach, J.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

K. D. Wulff, D. G. Cole, R. L. Clark, R. Di Leonardo, J. Leach, J. Cooper, G. Gibson, and M. J. Padgett, “Aberration correction in holographic optical tweezers,” Opt. Express 14, 4169–4174 (2006).
[CrossRef] [PubMed]

Lee, W. H.

Lesem, L. B.

L. B. Lesem, P. M. Hirsch, and J. A. Jordan, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969).
[CrossRef]

Love, G. D.

Mears, R. J.

Meinertzhagen, I. A.

Miles, M.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

Miura, H.

Osten, W

Padgett, M.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

G. Sinclair, P. Jordan, J. Courtial, M. Padgett, J. Cooper, and Z. J. Laczik, “Assembly of 3-dimensional structures using programmable holographic optical tweezers,” Opt. Express 12, 5475–5480 (2004).
[CrossRef] [PubMed]

Padgett, M. J.

Robert, D.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

Ruocco, G.

Schmitz, C. H. J.

Schwab, X.

Sinclair, G.

Sonehara, T.

Spatz, J. P.

Takaki, Y.

Tan, K. L.

Whyte, G.

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

G. Whyte and J. Courtial, “Experimental demonstration of holographic three-dimensional light shaping using a Gerchberg-Saxton algorithm,” N. J. Phys. 7, 117 (2005).
[CrossRef]

Wulff, K. D.

Xu, W.

Appl. Opt. (6)

IBM J. Res. and Dev. (1)

L. B. Lesem, P. M. Hirsch, and J. A. Jordan, “The kinoform: a new wavefront reconstruction device,” IBM J. Res. and Dev. 13, 150–155 (1969).
[CrossRef]

J. Opt. A, Pure Appl. Opt. (1)

G. Gibson, D. M. Carberry, G. Whyte, J. Leach, J. Courtial, J. C. Jackson, D. Robert, M. Miles, and M. Padgett, “Holographic assembly workstation for optical manipulation,” J. Opt. A, Pure Appl. Opt. 10, 044009 (2008).
[CrossRef]

J. Opt. Soc. Am. A (1)

N. J. Phys. (1)

G. Whyte and J. Courtial, “Experimental demonstration of holographic three-dimensional light shaping using a Gerchberg-Saxton algorithm,” N. J. Phys. 7, 117 (2005).
[CrossRef]

Opt. Express (5)

Opt. Lett. (1)

Proc. R. Soc. London Ser. A (1)

D. Gabor, “Microscopy by reconstructed wave-fronts,” Proc. R. Soc. London Ser. A 197, 454–487 (1949).
[CrossRef]

Other (1)

J. W. Goodman, Introduction to Fourier Optics, 3rd Ed. (Roberts and Company Publishers, 2005).

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Figures (7)

Fig. 1
Fig. 1

The holography apparatus is constructed with a 4f system. L 1 is the Fourier transform lens, L 2 is a second lens, f 1 = 300 mm, f 2 = 500 mm. Inset shows our definitions of maximum spatial frequency, fmax , and inter-foci spacing, dx , within the microscope focal plane (MFP).

Fig. 2
Fig. 2

Root mean square residual difference between original kinoforms with N o r i g = 100 P and N o r i g = 100 ( P 1 ) where P are integers between 1 and 21. Here Nfoci = 100 and dx is varied between 5δx and 30δx .

Fig. 3
Fig. 3

Left panel: A 100 × 100 pixel section of original kinoform with N o r i g = 2000 . Right panel: Same section of the original kinoform aliased to N a l _ p i x = 500 pixels . One pixel in the right panel has the same physical dimension as 16 pixels in the left panel. Both white grids in the upper right corner of the panel display boxes that are 4 × 4 original pixels in size.

Fig. 4
Fig. 4

Simulated relative standard deviation of foci intensities (rel. σ) versus increasing number of foci (Nfoci ) for kinoforms with varying numbers of aliased pixels (Nal_pix ) and dx = 10δx . The legend indicates Nal_pix for each curve. Inset shows the effect of aliasing on rel. σ for Nfoci = 400.

Fig. 5
Fig. 5

Simulated relative standard deviation of foci intensities (rel. σ) plotted as a function of the density of foci (ρfoci ) for kinoforms with varying numbers of aliased pixels (Nal_pix ) and for fmax (maximum spatial frequency) = 30δx . The legend indicates Nal_pix for each curve. Inset shows the effects of aliasing on pattern quality for a single ρfoci = 0.071 foci μm−2.

Fig. 6
Fig. 6

Experimentally measured relative standard deviation of foci intensities (rel. σ) plotted as a function of the number of foci (Nfoci ) for Nal_pix (number of aliased pixels) = 200 and 1080; dx = 10δx . Inset shows the effect of aliasing on rel. σ for Nfoci = 400. Error bars represent standard deviation; n = 20.

Fig. 7
Fig. 7

Experimentally measured relative standard deviation of foci intensities (rel. σ) for varying foci density (ρfoci ); Nal_pix (number of aliased pixels) = 200 and 1080; fmax (maximum spatial frequency) = 30δx . Inset shows the effect of aliasing on rel. σ for ρfoci = 0.071 foci μm−2. Error bars represent standard deviation; n = 20.

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