We describe an optical tweezers experiment suitable for a third-year undergraduate laboratory course. Compared to previous designs, it may be set up in about half the time and at one-third the cost. The experiment incorporates several features that increase safety. We also discuss how to use stochastic methods to characterize the trap’s strength and shape.

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Beth’s experiment using optical tweezers
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). Note that the Gaussian form for the beam shape [Eq. (4)] is inaccurate in that it assumes a Gaussian fall-off along the beam axis, whereas the actual intensity decreases asymptotically as z −2 . But both the true form and the assumed form vary quadratically about the focus, and the behavior there dominates in the calculation of trapping forces.
13.
Because of typographical errors in their version of our Eqs. (6) and (7), the formulas for trapping constants given in Ref. 12 were incorrect. The correct formulas, however, were used in calculating the results given in Ref. 12. [A. Meller and T. Tlusty (private communication).]
14.
Power Technology, PMP (LD1240) laser diode module, LDCU5 power supply, and PM–ACS–HS heat sink ($500). The setup is based on a Blue Sky Research circu-laser module. Note that although the laser itself is advertized as producing 35 mW, the feedback loop used to stabilize the optical power reduces this somewhat. We measured 23 mW for our module.
15.
The design of Moothoo et al. (Ref. 8) uses the infrared Blue-Sky laser.
16.
The breadboard and kinematic lens and mirror mounts are standard grade parts from Thorlabs, Inc. We used a 24-by-36 inch breadboard, which is larger than needed for this experiment. One could use an 18-by-24 inch board, but the extra space makes the layout easier and makes the board more useful for other experiments. The breadboard and kinematic mounts are available from a wide range of suppliers, almost all of which will be suitable.
17.
Ikea Expressivo lamp ($8). We modified the commercial lamp by replacing the two metal rods that connect base to lamp head with a two-wire cable. The head was attached to a standard post for mounting to the table and extra slots were cut to ensure cooling. We also added a light shield to block stray light.
18.
Thorlabs, Model MT3. Note that their 1 in. stage (Model PT3) was much less rigid and had a movement that was much more prone to stick-slip motion.
19.
Edmund Scientific, 100X Achromat, K43-905 ($95).
20.
Edmund Scientific, high-viscosity immersion oil, CR38-503 ($9).
21.
Pulnix, model TM-7CN ($550).
22.
Irez Corp., Kritter USB ($100). A Firewire version costs $200.
23.
Scion Corp., LG-3 ($900). The Macintosh PCI-bus version can digitize up to 30 frames (60 fields) per second directly into memory.
24.
Interfacial Dynamics Corp, http://www.idclatex.com, NIST-size-standard spheres. Adding a small amount of surfactant (for example, 1% TWEEN) can help prevent spheres from sticking to each other. A similar amount of sodium azide will prevent bacterial growth if samples are going to be used over long periods of time (months). Note that microspheres available from other suppliers (Duke, Bangs, etc.) will be equally satisfactory.
25.
NIH Image is a freely available image-processing software package for Macintosh computers. (http://rsb.info.nih.gov/nih-image/index.html) A Windows version, Scion Image, is also freely available (http://www.scioncorp.com/). The macro routines we use in processing the images are also available in EPAPAS Document No. EPAPS-AJPIAS-70-009203.
This document may be retrieved via the EPAPS homepage (http://www.aip.org/pubservs/epaps.html) or from ftp.aip.org in the directory /epaps/. See the EPAPS homepage for more information.
The basic strategy we use is to threshold the image so that the selected pixels lie entirely in the bead image and move along with it. The position is extracted by computing the x and y centers of mass of the pixels. A weakness of this method is that variations in the background intensity can produce spurious position shifts. We thus include a routine that normalizes each image by the average intensity of all pixels. A rule of thumb is that the better the original image, the better these routines work. Also, as shown in Fig. 3(a), there are residual fluctuations observed even for stationary objects. These are due to shot-noise fluctuations, which produce apparent positional fluctuations.
26.
Note that although it is easy to get relative power measurements, it is quite difficult to measure accurately the power actually delivered to the trap. The beam spreads out extremely rapidly from the trap, so much so that another objective would be required to collimate the beam. However, there are significant losses from each objective and the first objective may block an unknown fraction of the beam. The power measured at the output of the second objective is thus not a reliable measurement of the power at the trap. Another approach is to measure the portion of the power that falls on the light-meter detector as a function of the distance of the active surface from the objective and to extrapolate back to zero distance. However, this method is sensitive to misalignments of the detector’s center from the optical axis and, in practice, is difficult to do well. In our lab, we have merely asked students to try to place upper and lower bounds on estimates for the actual power delivered to the trap.
27.
The normalization of a finite-depth potential is tricky. The naive thing to do is to calculate the partition function Z as lim X→∞  ∫ −X X d(δx) ρ(δx), but taking this limit just gives a uniform distribution, with the particle equally likely to be in any particular range of δx. (The “bump” of extra probability at the center disappears as the limit is taken.) The problem is that in equilibrium, essentially all particles will have escaped the potential and will wander over the real axis. What one wants is the probability distribution of a particle that stays trapped in the potential and does not escape. In other words, we suppose a separation of time scales, so that the time to thermalize within the potential trap is much shorter than the observation time and also than the time to escape. For traps deeper than a few k B T, this condition will hold.
28.
G. Cowan, Statistical Data Analysis (Oxford University Press, New York, 1998), Chap. 11.
29.
F. Reif, Statistical and Thermal Physics (McGraw-Hill, New York, 1965), Chap. 15, especially Secs. 6 and 10.
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