Alexander Soiguine [soi

1
Alexander Soiguine soigin(Sasha standard
Russian nickname for Alexander)

• Physicist, Mathematician, Computer Modeling
  Scientist
• PhD in Applied Mathematics, MS in Mathematical
  Physics
• 20 years of hands-on software development in
  computer simulation
• Former professor of Mathematics and Mechanics
• Enthusiast of naturally parallelizable simulation
  algorithms

2

• Physical Department of St. Petersburg University,
  Russia.
• MS in Mathematical Physics.

Major Courses

• Higher Mathematics - General Physics- Atomic
  Physics - Theoretical Mechanics
• - Thermodynamics and Statistical Physics -
  Optics- Electrodynamics - Quantum Mechanics

- Mathematical Hydrodynamics - Methods of
Mathematical Physics - Advanced Mathematical
Analysis - Theory of Scattering - Operator
Theory - Nonlinear Problems of Mathematical
Physics- Spectral Theory of Operators -
Generalized Functions - Wave Propagation in
Random Media

• PhD in Applied Mathematics - Numerical Methods
  for
• Stochastically Disturbed PDEs (Definitions of
  stochastic
• solutions, existence/uniqueness theorems,
  propagated
• variance estimations)

3

• Professor of Mathematics and Mechanics at Naval
  Academy of Russia (St. Petersburg) top level
  institution preparing senior officers for Russian
  Navy.

Taught

• Linear Algebra - Probability Theory -
  Differential Equations - Vector Analysis -
  Numerical Methods- Coding Theory - Stochastic
  Processes

- Partial Differential Equations - Control
Theory - Theory of Optimized Filtration and
Estimation- Equations of Mathematical Physics-
Electrodynamics - Heat Transfer Processes

• Participated in multiple research projects,
  particularly
• - submarine nuclear power plant numerical
  simulation algorithms
• - relativistic particle beam dynamics simulation
  (star war challenge)
• - acoustic emission simulation in metal
  construction
• Beginning of object-oriented programming

4

• January 1997 first USA job as software
  developer at International Metrology Systems - a
  company producing coordinate measuring machines.
  Wrote C/C code to geometric surface/shape/solid
  modeling

Programming was mainly around

• implementation of Levenberg-Marquardt best fit
  approximation method for predefined geometrical
  shapes and spline-type curves/surfaces
• creating effective iteration algorithms to
  accurate and in real-time construction of
  tangents/normals to curves/surfaces
• integration of Matra Datavision Cascade
  geometrical object library into existing software
  tool
• OpenInventor/VRML 3D visualization routines
• implementation of interprocess dynamical data
  exchange multithreading mechanism

5

• August 1999 took offer from Cadence to work on
  math simulation engine for integrated electronic
  circuits. Architectural, data structure
  modifications, matrix solver and integration
  algorithms on-fly switching optimization.

Programming issues

• Restructuring circuit matrix nodes data
  fromlinked list of doubles type into single
  double values, rewriting device load member
  functions
• Rewriting class member function interfaces for
  compatibility with NIST SparseLib package
• Restructuring circuit matrix load bypass
  algorithms for new architecture
• Creating algorithms to optimize switching between
  different matrix decomposition and integration
  schemes

The result
Electronic circuit simulation speed increased up
to 15 times simulation began to converge with
circuits where it never did before.
6

• 2003 2004 Principal Analyst/Engineer at JRM
  Technologies. Software simulation of physical
  signatures appeared due to optical,
  electromagnetic, thermal, chemical phenomena.
  Implemented both on Windows and Linux platforms.

What was done

• Algorithms to transform stellar brightness data
  into irradiation approaching earth surface
• Algorithms to calculate spectra of a city site
  illumination based on given distribution of light
  sources
• Simulation algorithm of radiation propagation
  from missile plumes
• Simulation algorithms of thermal irradiation from
  vehicles, tanks, detection by phase antennas
• Terrain scene material identification algorithms
  based on satellite hypespectral images

7

• Since August 2004 computational scientist at
  Tinsley. Two from a scratch huge projects -
  software tool to visualize/analyze/process
  optical surface data collected from coordinate
  measuring machines and interferometers, and
  software package to interactively control optics
  processing machines.

Some of the first tool numerical blocks

• Algorithms to convert scattered point Cartesian
  data into regular grid surface data
• Algorithms to convert interferometer phase data
  into regular grid surface data
• Algorithms for surface profile analysis
• Algorithms to filter regular grid data through
  cutting off 2D rectangular/circle frequency
  domains

8

• Algorithms to approximate data through Zernike
  polynomials
• Algorithms for polynomial, moving average,
  weighted Gaussian, other types of smoothing
• Image cropping, clipping, stitching algorithms
• Algorithms to create regular surface grid from
  given aspheric equation
• Algorithms to best fit metrology data to
  analytically predefined aspheric surface
• Algorithms to define pixels height/slope
  statistics in areas close to optics edges
• Algorithms of manual and scenario automated pixel
  editing
• Image algebra

9
The following slides are a few screen shots of
the software tool to visualize/analyze/process
optical surface data collected from coordinate
measuring machines and interferometers.Live
demonstration will be available.
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How it works. Main data visualization/analysis box
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Profile analysis
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Zernike approximation interface
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Comparing profiles
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Interface to create aspherics
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We can show how the tool can be used to estimate
power losses in one reflection due to dust
particles. Typical dust pike effect in phase data
16
Profile of disturbance in interferometer phase
intensity measurement
17
To get power loss estimation lets remove
Zernikes up to 8th order. The rms decreases to
2.668nm.
18
If we consider this Zernike residual as a sample
of two-dimensional centered stationary random
process with and
assume that HeNe wavelength 632.8nm is much
bigger than the Zernike residual PV 39.37nm
then the Fourier transform expansion of the
reflected wave from normally impinging beam
can be used just up to the first
power of . Then we
get scattering losses from the power spectrum
density that in this case is 0.05. It
would be interesting to get detailed information
about field spectral variations depending on dust
pike position and its shape parameters, though it
is doubtful if the Fresnel diffraction or PDE
will work at all. More direct involvement of the
Kirchhoff equation looks necessary.
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I would be happy to answer your questions if you
have some.Thank you.