Difference between revisions of "Rlx scalar.m"

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{{DISPLAYTITLE:rlx_scalar.m}}
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{{DISPLAYTITLE:rlx_scalar.m}} __NOTOC__
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Scalar relaxation superoperator using Redfield theory.
 
Scalar relaxation superoperator using Redfield theory.
  
 
==Syntax==
 
==Syntax==
  
    R=rlx_scalar(spin_system,H0,H1,tau_c)
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R=rlx_scalar(spin_system,H0,H1,tau_c_array)
  
==Description==
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==Arguments==
Computes Redfield superoperator in situations when the system has a static background Hamiltonian and a perturbation with a scalar stochastic function in front of it. Scalar hyperfine relaxation is a common example. This function is called by Spinach relaxation theory module, but may also be invoked directly.
 
  
==Arguments==
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H0 - background Hamiltonian
  
    H0 - background Hamiltonian
 
 
 
     H1 - the stochastically modulated interaction operator
 
     H1 - the stochastically modulated interaction operator
 
           multiplied by its root mean square modulation depth
 
           multiplied by its root mean square modulation depth
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     tau_c - the correlation time of the stochastic modulation
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     tau_c_array - a cell array of the following format:
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 +
                      {[weight_a,tau_a],[weight_b,tau_b],...}
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 +
                  giving weights of the exponential components
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                  of the correlation function and the associa-
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                  ted correlation times, e.g. {[1.0,1e-12]}
  
 
==Outputs==
 
==Outputs==
  
    R  - relaxation superoperator as a negative definite matrix
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R  - relaxation superoperator as a negative definite matrix
  
 
==Notes==
 
==Notes==
 +
 
If H1(t) has a non-zero average value, it must be subtracted out and put into H0.
 
If H1(t) has a non-zero average value, it must be subtracted out and put into H0.
  
 
==See also==
 
==See also==
 +
 
[[relaxation.m]], [[expmint.m]], [[lindbladian.m]], [[rlx_t1_t2.m]]
 
[[relaxation.m]], [[expmint.m]], [[lindbladian.m]], [[rlx_t1_t2.m]]
  
  
 
''Version 2.1, authors: [[Ilya Kuprov]]''
 
''Version 2.1, authors: [[Ilya Kuprov]]''
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 +
==Description==
 +
 +
Computes Redfield superoperator in situations when the system has a static background Hamiltonian and a perturbation with a scalar stochastic function in front of it. Scalar hyperfine relaxation is a common example. This function is called by Spinach relaxation theory module, but may also be invoked directly.

Revision as of 15:04, 5 April 2026


Scalar relaxation superoperator using Redfield theory.

Syntax

R=rlx_scalar(spin_system,H0,H1,tau_c_array)

Arguments

H0 - background Hamiltonian

    H1 - the stochastically modulated interaction operator
         multiplied by its root mean square modulation depth
    tau_c_array - a cell array of the following format:
                     {[weight_a,tau_a],[weight_b,tau_b],...}
                  giving weights of the exponential components
                  of the correlation function and the associa-
                  ted correlation times, e.g. {[1.0,1e-12]}

Outputs

R - relaxation superoperator as a negative definite matrix

Notes

If H1(t) has a non-zero average value, it must be subtracted out and put into H0.

See also

relaxation.m, expmint.m, lindbladian.m, rlx_t1_t2.m


Version 2.1, authors: Ilya Kuprov

Description

Computes Redfield superoperator in situations when the system has a static background Hamiltonian and a perturbation with a scalar stochastic function in front of it. Scalar hyperfine relaxation is a common example. This function is called by Spinach relaxation theory module, but may also be invoked directly.