schiff

Estimate the radiative properties of soft particless
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     20 .Dd May 15, 2026
     21 .Dt SCHIFF 1
     22 .Os
     23 .\""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
     24 .Sh NAME
     25 .Nm schiff
     26 .Nd estimate radiative properties of soft particles
     27 .\""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
     28 .Sh SYNOPSIS
     29 .Nm
     30 .Op Fl Dhqv
     31 .Op Fl a Ar nangles_phase_func
     32 .Op Fl A Ar nangles_phase_func_invcumul
     33 .Op Fl d Ar ninner_samples
     34 .Op Fl g Ar nrealisations
     35 .Op Fl G Ar nparticles
     36 .Op Fl i Ar distribution
     37 .Op Fl l Ar particles_length
     38 .Op Fl n Ar nthreads
     39 .Op Fl o Ar output
     40 .Op Fl w Ar wavelelength Ns Op : Ns Ar wavelelength No ...
     41 .Op Ar optical_props
     42 .\""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
     43 .Sh DESCRIPTION
     44 .Nm
     45 computes the radiative properties of soft particles with an
     46 .Dq Approximation Method for Short Wavelength or High Energy Scattering
     47 .Pq Schiff, 1956 .
     48 The implemented model is detailed in
     49 .Dq Monte Carlo Implementation of Schiff's Approximation for \
     50 Estimating Radiative Properties of Homogeneous, Simple-Shaped and \
     51 Optically Soft Particles: Application to Photosynthetic \
     52 Micro-Organisms
     53 .Pq Charon et al., 2015 .
     54 It relies on the Monte Carlo method to solve Maxwell's equations within
     55 Schiff's approximation; it estimates total cross sections
     56 .Pq extinction, absorption and scattering cross-sections
     57 in addition of the inverse cumulative phase function.
     58 .Pp
     59 The shapes of the soft particles are controlled by the
     60 .Xr schiff-geometry 5
     61 file submitted by the
     62 .Fl i
     63 option.
     64 The per wavelength optical properties
     65 of the soft particles are stored in
     66 .Ar optical_props
     67 where each line is formatted as
     68 .Dq W N K Ne
     69 with
     70 .Dq W
     71 is the wavelength in vacuum expressed in micron,
     72 .Dq N
     73 and
     74 .Dq K
     75 are the real and imaginary parts, respectively, of the refractive index,
     76 and
     77 .Dq Ne
     78 the refractive index of the medium.
     79 With no
     80 .Ar optical_props ,
     81 the optical properties are read from standard input.
     82 .Pp
     83 The estimated results follows the
     84 .Xr schiff-output 5
     85 format and are written to the
     86 .Ar output
     87 file or to standard ouptut whether
     88 the
     89 .Fl o
     90 is defined or not, respectively.
     91 .Pp
     92 The options are as follows:
     93 .Bl -tag -width Ds
     94 .\""""""""""""""""""""""""""""""""""
     95 .It Fl a Ar nangles_phase_func
     96 Number of phase function scattering angles to estimate.
     97 These angles are
     98 uniformaly distributed in
     99 .Bq 0,PI ,
    100 i.e. the value of the i^th angle
    101 .Pq i in Bq 0, Ns Ar nangles_phase_func
    102 is
    103 .No i*PI/ Ns Pq Ar nangles_phase_func Ns -1 .
    104 Default is @SCHIFF_ARGS_DEFAULT_NANGLES@.
    105 .\""""""""""""""""""""""""""""""""""
    106 .It Fl A Ar nangles_phase_func_invcumul
    107 Number of scattering angles computed from the inverse cumulative phase
    108 function.
    109 The value of the i^th angle
    110 .Pq i in Bq 0, Ns Ar nangles_phase_func_invcumul Ns -1
    111 is
    112 .No CDF^-1 Ns Po i/ Ns Po Ar nangles_phase_func_invcumul Ns -1 Pc Pc .
    113 Default is @SCHIFF_ARGS_DEFAULT_NANGLES_INV@.
    114 .\""""""""""""""""""""""""""""""""""
    115 .It Fl d Ar ninner_samples
    116 Number of conditioned integration variable sampling
    117 .Pq incident direction, volume, ray Ns Pq s
    118 for each sampled particle-shape.
    119 Calculation of optimal value is presented in
    120 .Dq Monte Carlo efficiency improvement by multiple sampling \
    121 of conditioned integration variables
    122 .Pq Weitz et al., 2016 .
    123 Default is @SCHIFF_ARGS_DEFAULT_NINSAMPLES@.
    124 .\""""""""""""""""""""""""""""""""""
    125 .It Fl D
    126 discard computations of the
    127 .Bq Ns Bo inverse- Bc Ns cumulative
    128 phase functions for large scattering angles.
    129 See the
    130 .Fl l
    131 option for the definition of large scattering angles.
    132 .\""""""""""""""""""""""""""""""""""
    133 .It Fl g Ar nrealisations
    134 Number of sampled particle-shapes.
    135 This the number of realisations of the Monte Carlo algorithm.
    136 Default is @SCHIFF_ARGS_DEFAULT_NREALISATIONS@.
    137 .\""""""""""""""""""""""""""""""""""
    138 .It Fl G Ar nparticles
    139 Sample
    140 .Ar nparticles
    141 soft particles with respect to the defined distribution, dump their
    142 geometric data and exit.
    143 The data are written to
    144 .Ar output
    145 or the standard output whether the
    146 .Fl o
    147 option is defined or not, respectively.
    148 The outputted data followed the Alias Wavefront obj file format.
    149 .\""""""""""""""""""""""""""""""""""
    150 .It Fl h
    151 Display short help and exit.
    152 .\""""""""""""""""""""""""""""""""""
    153 .It Fl i Ar distribution
    154 Define the
    155 .Xr schiff-geometry 5
    156 file that controls the geometry distribution of the soft particles.
    157 .\""""""""""""""""""""""""""""""""""
    158 .It Fl l Ar particles_length
    159 Characteristic length in micron of the soft particles.
    160 Used for the definition of the angle that sets the limit between small
    161 and large scattering angles
    162 .Po
    163 see equation 7 in
    164 .Dq  Approximation for Estimating Radiative Properties of Homogeneous, \
    165 Simple-Shaped and Optically Soft Particles: Application to \
    166 Photosynthetic Micro-Organisms ,
    167 Charon et al. 2015
    168 .Pc .
    169 .\""""""""""""""""""""""""""""""""""
    170 .It Fl n Ar nthreads
    171 Hint on the number of threads to use during the integration.
    172 Advice on the number of threads to use.
    173 By default,
    174 .Nm
    175 uses as many threads as processor cores.
    176 .\""""""""""""""""""""""""""""""""""
    177 .It Fl o Ar output
    178 Output file.
    179 If not defined, the results are written to standard output.
    180 .\""""""""""""""""""""""""""""""""""
    181 .It Fl q
    182 Do not print the helper message when no
    183 .Ar optical_props
    184 is submitted.
    185 .\""""""""""""""""""""""""""""""""""
    186 .It Fl w Ar wavelelength Ns Op : Ns Ar wavelelength No ...
    187 List of wavelengths in vacuum
    188 .Pq expressed in micron
    189 to integrate.
    190 .\""""""""""""""""""""""""""""""""""
    191 .It Fl v
    192 Display version information and exit.
    193 .El
    194 .Sh EXIT STATUS
    195 .Ex -std
    196 .\""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
    197 .Sh EXAMPLES
    198 Estimate the radiative properties of soft particles whose shape is
    199 described in the
    200 .Pa geometry.yaml
    201 file and its optical properties in the
    202 .Pa properties
    203 file.
    204 The characteristic length of the soft particle shapes is  2.3 microns
    205 and the estimations is performed for the wavelengths 0.45 and 0.6
    206 microns.
    207 The results are written to the standard output:
    208 .Bd -literal -offset Ds
    209 schiff -i geometry.yaml -l 2.3 -w 0.45:0.6 properties
    210 .Ed
    211 .\""""""""""""""""""""""""""""""""""
    212 .Pp
    213 The soft particles have a characteristic length of 1 and their shape is
    214 controlled by the
    215 .Pa my_geom.yaml
    216 file.
    217 Their optical properties are read from the standard input.
    218 The estimated wavelelength is 0.66 microns and the results are written
    219 to the
    220 .Pa my_result
    221 file:
    222 .Bd -literal -offset Ds
    223 schiff -w 0.66 -l 1.0 -i my_geom.yaml -o my_result
    224 .Ed
    225 .\""""""""""""""""""""""""""""""""""
    226 .Pp
    227 Sample 10
    228 soft particles whose shape is defined by the
    229 .Pa geometry.yaml
    230 file and write their triangulated geometric data to the
    231 .Pa output
    232 file.
    233 Use the
    234 .Xr csplit 1
    235 command to split the
    236 .Pa output
    237 file in 10 files named
    238 .No particle Ns Ar N ,
    239 with
    240 .Ar N
    241 in
    242 .Bq 0,9 ,
    243 each storing the geometric data of a sampled soft particle:
    244 .Bd -literal -offset Ds
    245 schiff -i geometry.yaml -G 10 -o output
    246 N="$(grep -ce "^g " output)"
    247 csplit -f particle -k -n1 output %^g\e % /^g\e / {$((N-2))}
    248 .Ed
    249 .\""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
    250 .Sh SEE ALSO
    251 .Xr csplit 1 ,
    252 .Xr schiff-geometry 5 ,
    253 .Xr schiff-output 5
    254 .Rs
    255 .%A Leonard Isaac Schiff
    256 .%T Approximation Method for Short Wavelength or High-Energy Scattering
    257 .%J Physical Review
    258 .%V 104
    259 .%P pp. 1481\(en1485
    260 .%D 1956
    261 .Re
    262 .Rs
    263 .%A Julien Charon et al.
    264 .%T Approximation for Estimating Radiative Properties of Homogeneous, \
    265 Simple-Shaped and Optically Soft Particles: Application to \
    266 Photosynthetic Micro-Organisms
    267 .%J Journal of Quantitative Spectroscopy and Radiative Transfer
    268 .%V 172
    269 .%P pp. 3\(en23
    270 .%D 2015
    271 .Re
    272 .Rs
    273 .%A Sebastian Weitz et al.
    274 .%T Monte Carlo efficiency improvement by multiple sampling of \
    275 conditioned integration variables
    276 .%J Journal of Computational Physics
    277 .%V 326
    278 .%P pp. 30\(en34
    279 .%D 2016
    280 .Re
    281 .\""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
    282 .Sh HISTORY
    283 .Nm
    284 has been developed as part of
    285 .Li ANR-11-IDEX-0002-02
    286 ALGUE project.