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N-Dimensional Scanning and Data Acquisition

IP.com Disclosure Number: IPCOM000107714D
Original Publication Date: 1992-Mar-01
Included in the Prior Art Database: 2005-Mar-22
Document File: 3 page(s) / 100K

Publishing Venue

IBM

Related People

Duerig, UT: AUTHOR [+2]

Abstract

Up to the present time, scanning tunneling microscope data were usually acquired in the form of Z = f(x, y), where Z represents the topography and x and y are the scan deflections of the tunnel tip in two orthogonal directions. Alternatively, one has acquired spectroscopic data in the form of I = f(V) or I = f(d), where I is the tunneling current, V is the voltage across the tunnel gap, and d is the distance of the tunnel tip from the scanned surface. Usually, such spectroscopies have been implemented using an additional function generator and an additional storage oscilloscope to acquire the data.

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N-Dimensional Scanning and Data Acquisition

       Up to the present time, scanning tunneling microscope
data were usually acquired in the form of Z = f(x, y), where Z
represents the topography and x and y are the scan deflections of the
tunnel tip in two orthogonal directions. Alternatively, one has
acquired spectroscopic data in the form of I = f(V) or I = f(d),
where I is the tunneling current, V is the voltage across the tunnel
gap, and d is the distance of the tunnel tip from the scanned
surface. Usually, such spectroscopies have been implemented using an
additional function generator and an additional storage oscilloscope
to acquire the data.

      The situation is more complicated in the case of experiments
where the tunneling current and the topography are recorded as a
function of x, y and the tunnel voltage, for example. Typically, two
independent data acquisition systems must be synchronized to perform
the task, involving special setups for hardware and software. Such an
implementation is time-consuming and applicable only to one type of
experiment and does not permit on-line changes while tunneling.

      Described herein is a software architecture which enables the
configuring of different types of experiments having the general
form: o1, o2,... =  f(p1, p2, ... pn).  The observables o1, o2 are
measured as a function of p1  ... pn, mutually orthogonal parameters
spanning an n-dimensional parameter space Pn . Each parameter
dimension consists of a discrete set of kj values. Hence, the
parameter space contains a total number of    points and is
isomorphous to the direct product

                            (Image Omitted)

                           where         denotes a subset of   .
For each point in Pn', m observables o1  ... om are measured. Hence,
the dimension of the data space is

      The crucial features of the architecture are:
1.   The flexible allocation of functions to the dimensions of the
parameter space. This is especially powerful in that new experiments
can be set up with the analog input and output...