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documentation:language_reference:objects:responsefunction:start [2024/10/04 17:26] – Sina Shokridocumentation:language_reference:objects:responsefunction:start [2024/10/07 10:00] (current) – Sina Shokri
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 One simple way to represent a spectrum, for example one that is calculated using the function //[[documentation:language_reference:functions:createspectra|CreateSpectra()]]//, is a sum over the poles multiplied by the residues: One simple way to represent a spectrum, for example one that is calculated using the function //[[documentation:language_reference:functions:createspectra|CreateSpectra()]]//, is a sum over the poles multiplied by the residues:
-$$ I(\omega) = \sum_{k} \frac{R_k}{\omega - \omega_k + i \gamma/2} $$ +\begin{equation} 
-A more compact way to store this spectrum is by just using two arrays for the values of $ \{R_k\} $ (residues) and $ \{\omega_k\} $ (poles). This is precicely the purpose of the object type Response Function. +    I(\omega) = \sum_{k} \frac{R_k}{\omega - \omega_k + i \gamma/2} \qquad \qquad \qquad    (1) 
 +\end{equation} 
 +A more compact way to store this spectrum, as a function of $\omega$ (and $\gamma$), is by just using two arrays for the values of $ \{R_k\} $ (residues) and $ \{\omega_k\} $ (poles). This is precicely the purpose of the object //Response Function//. In other words, response functions in Quanty are functions that, given a complex number as input ($\omega + i \gamma/2$) return a complex number (single valued functions). Additionally, the output could be a matrix (matrix functions) when the response function is defined using array of matrices, instead of array of numbers. Response functions fullfil the Kramers Kronig relations and "causality".
  
-===== Table of contents ===== +The response functions can also be defined by matrices such that the function is given by  
-{{indexmenu>.#2}}+$$ A_0 + B_0^* \frac{ 1 }{\omega - H + i \gamma / 2} \Bigg|_{[0,0]} B_0^{T} $$  
 +where $A_0$, $B_0$ and $H$ are matrices. Any unitary transformation that leaves the [0,0] element of $H$ unchanged results in the same spectrum. Hence $H$ can have different forms, whereby only a few elements/blocks are non-zero. In Quanty, there are 4 different forms (types) for the matrix $H$: 
 +  * list of poles (//ListOfPoles//) 
 +  * tri-diagonal (//Tri//) 
 +  * Anderson (//And//) 
 +  * natural impurity orbital (//NaturalImpurityOrbital//) 
 + 
 +These types are related to each other by unitary transformations and the Quanty function //[[documentation/language_reference/objects/responsefunction/functions/changetype|ChangeType()]]// can be used to transform between these types. List of poles is exactly the representation in Eq. (1). 
 + 
 +In order to define a response function, one needs to set the meta table to "ResponseFunctionMeta" in Lua. Note that there is no type-check, (i.e. setting the meta table is optional) for the functions acting on these tables. 
 + 
 +==== Definitions ==== 
 +<code Quanty Example.Quanty> 
 +-- Defining single-valued response functions 
 + 
 +a = {0, -1,-0.5, 0,   0.5,  1,  1.5} 
 +b = {  0.2, 0.1, 0.1, 0.1, 0.2, 0.3} 
 +GA_L = {a,b,mu=0,type="ListOfPoles", name="A"} 
 +setmetatable(GA_L, ResponseFunctionMeta) 
 + 
 +a = {0, 1,   1,   1,   1,   1,  1} 
 +b = {   1, 0.5, 0.5, 0.5, 0.5, 0.5} 
 +GB_T = {a,b,mu=0,type="Tri", name="B"} 
 +setmetatable(GB_T, ResponseFunctionMeta) 
 + 
 +a = {0, 1, 1.5,   2, 2.5,   3, 3.5} 
 +b = {   1, 0.5, 0.5, 0.5, 0.5, 0.5} 
 +GC_A = {a,b,mu=0,type="And", name="C"} 
 +setmetatable(GC_A, ResponseFunctionMeta) 
 + 
 +acon = {0,         1,   1,   1,   1,   1,  1} 
 +bcon = {   sqrt(1/2), 0.5, 0.5, 0.5, 0.5, 0.5} 
 +Gcon = {acon,bcon,mu=0,type="Tri"} 
 +setmetatable(Gcon, ResponseFunctionMeta) 
 +aval = {0,        -1,  -1,  -1,  -1,  -1, -1} 
 +bval = {   sqrt(1/2), 0.5, 0.5, 0.5, 0.5, 0.5} 
 +Gval = {aval,bval,mu=0,type="Tri"} 
 +setmetatable(Gval, ResponseFunctionMeta) 
 +a0=0 
 +b0=1 
 +GD_N = {{a0,b0},val=Gval,con=Gcon,mu=0,type="Nat", name="D"} 
 +setmetatable(GD_N, ResponseFunctionMeta) 
 + 
 +-- For a more efficient storage, one can convert from Table to Userdata 
 +GA_l = ResponseFunction.ToUserdata(GA_L) 
 +GB_t = ResponseFunction.ToUserdata(GB_T) 
 +GC_a = ResponseFunction.ToUserdata(GC_A) 
 +GD_n = ResponseFunction.ToUserdata(GD_N) 
 + 
 +print("GA_L:") 
 +print(GA_L) 
 +print("GA_l:") 
 +print(GA_l) 
 + 
 +print("GB_T:") 
 +print(GB_T) 
 +print("GB_t:") 
 +print(GB_t) 
 + 
 +print("GC_A:") 
 +print(GC_A) 
 +print("GC_a:") 
 +print(GC_a) 
 + 
 +print("GD_N:") 
 +print(GD_N) 
 +print("GD_n:") 
 +print(GD_n) 
 + 
 +-- response functions in Quanty are functions that, given  
 +-- a complex number as input w + I gamma/2 return a complex 
 +-- number (single valued functions) or a matrix (matrix functions) 
 +omega = 0.764 
 +gamma = 0.1 
 +print("omega = ", omega) 
 +print("gamma = ", gamma) 
 + 
 +print("") 
 +print("GA_L(omega, gamma) = ", GA_L(omega, gamma)) 
 +print("GA_l(omega, gamma) = ", GA_l(omega, gamma)) 
 + 
 +print("GB_T(omega, gamma) = ", GB_T(omega, gamma)) 
 +print("GB_t(omega, gamma) = ", GB_t(omega, gamma)) 
 + 
 +print("GC_A(omega, gamma) = ", GC_A(omega, gamma)) 
 +print("GC_a(omega, gamma) = ", GC_a(omega, gamma)) 
 + 
 +print("GD_N(omega, gamma) = ", GD_N(omega, gamma)) 
 +print("GD_n(omega, gamma) = ", GD_n(omega, gamma)) 
 + 
 + 
 +-- Defining matrix response functions 
 + 
 +A0 = {{0,0,0},{0,0,0},{0,0,0}} 
 +setmetatable(A0, MatrixMeta) 
 +A1 = {{1,2,3},{2,5,6},{3,6,9}} 
 +setmetatable(A1, MatrixMeta) 
 +A2 = {{2,2,3},{2,5,6},{3,6,9}} 
 +setmetatable(A2, MatrixMeta) 
 +A3 = {{3,2,3},{2,5,6},{3,6,9}} 
 +setmetatable(A3, MatrixMeta) 
 +a1 = -1 
 +a2 = 0 
 +a3 = 1 
 +av1 = -0.5 
 +av2 = -1.0 
 +av3 = -1.5 
 +ac1 = 0.5 
 +ac2 = 1.0 
 +ac3 = 1.5 
 +B0s = {{1,0,0},{0,1,0},{0,0,1}} 
 +setmetatable(B0s, MatrixMeta) 
 +t=sqrt(0.5) 
 +B0vs = {{t,0,0},{0,t,0},{0,0,t}} 
 +setmetatable(B0vs, MatrixMeta) 
 +B0cs = {{t,0,0},{0,t,0},{0,0,t}} 
 +setmetatable(B0cs, MatrixMeta) 
 +B0 = B0s * B0s 
 +B0v = B0vs * B0vs 
 +B0c = B0cs * B0cs 
 +B1s = {{1,I,3},{-I,5,6},{3,6,9}} 
 +setmetatable(B1s, MatrixMeta) 
 +B1 = B1s * B1s 
 +B2s = {{2,0,3},{0,5,6},{3,6,9}} 
 +setmetatable(B2s, MatrixMeta) 
 +B2 = B2s * B2s 
 +B3s = {{3,0,3},{0,5,6},{3,6,9}} 
 +setmetatable(B3s, MatrixMeta) 
 +B3 = B3s * B3s 
 + 
 +MA_L = { {A0,a1,a2,a3}, {B1,B2,B3}, mu=0, type="ListOfPoles", name="A"} 
 +setmetatable(MA_L, ResponseFunctionMeta) 
 + 
 +MB_T = { {A0,A1,A2,A3}, {B0,B1,B2}, mu=0, type="Tri", name="B"} 
 +setmetatable(MB_T, ResponseFunctionMeta) 
 + 
 +MC_A = { {A0,A1,A2,A3}, {B0,B1,B2}, mu=0, type="And", name="C"} 
 +setmetatable(MC_A, ResponseFunctionMeta) 
 + 
 +MD_Nv = { {A0,av1,av2,av3}, {B1,B2,B3}, mu=0, type="ListOfPoles", name="Dv"} 
 +setmetatable(MD_Nv, ResponseFunctionMeta) 
 + 
 +MD_Nc = { {A0,ac1,ac2,ac3}, {B1,B2,B3}, mu=0, type="ListOfPoles", name="Dc"} 
 +setmetatable(MD_Nc, ResponseFunctionMeta) 
 + 
 +MD_N = {{A0,B0},val=MD_Nv,con=MD_Nc,mu=0,type="Nat", name="D"} 
 +setmetatable(MD_N, ResponseFunctionMeta) 
 + 
 +-- For a more efficient storage, one can convert from Table to Userdata 
 +MA_l = ResponseFunction.ToUserdata(MA_L) 
 +MB_t = ResponseFunction.ToUserdata(MB_T) 
 +MC_a = ResponseFunction.ToUserdata(MC_A) 
 +MD_n = ResponseFunction.ToUserdata(MD_N) 
 + 
 + 
 +print("MA_L:") 
 +print(MA_L) 
 +print("MA_l:") 
 +print(MA_l) 
 + 
 +print("MB_T:") 
 +print(MB_T) 
 +print("MB_t:") 
 +print(MB_t) 
 + 
 +print("MC_A:") 
 +print(MC_A) 
 +print("MC_a:") 
 +print(MC_a) 
 + 
 +print("MD_N:") 
 +print(MD_N) 
 +print("MD_n:") 
 +print(MD_n) 
 + 
 + 
 +-- response functions in Quanty are functions that, given  
 +-- a complex number as input w + I gamma/2 return a complex 
 +-- number (single valued functions) or a matrix (matrix functions) 
 +omega = 0.764 
 +gamma = 0.1 
 +print("omega = ", omega) 
 +print("gamma = ", gamma) 
 + 
 +print("") 
 +print("MA_L(omega, gamma) = ") 
 +print(MA_L(omega, gamma)) 
 +print("MA_l(omega, gamma) = ") 
 +print(MA_l(omega, gamma)) 
 + 
 +print("") 
 +print("MB_T(omega, gamma) = ") 
 +print(MB_T(omega, gamma)) 
 +print("MB_t(omega, gamma) = ") 
 +print(MB_t(omega, gamma)) 
 + 
 +print("") 
 +print("MC_A(omega, gamma) = ") 
 +print(MC_A(omega, gamma)) 
 +print("MC_a(omega, gamma) = ") 
 +print(MC_a(omega, gamma)) 
 + 
 +print("") 
 +print("MD_N(omega, gamma) = ") 
 +print(MD_N(omega, gamma)) 
 +print("MD_n(omega, gamma) = ") 
 +print(MD_n(omega, gamma)) 
 +</code>
  
-==== Result ==== 
 <file Quanty_Output> <file Quanty_Output>
-text produced as output+GA_L: 
 +{ { 0 , -1 , -0.5 , 0 , 0.5 , 1 , 1.5 } ,  
 +  { 0.2 , 0.1 , 0.1 , 0.1 , 0.2 , 0.3 } , 
 +  type = ListOfPoles , 
 +  mu = 0 , 
 +  name = A } 
 +GA_l: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +GB_T: 
 +{ { 0 , 1 , 1 , 1 , 1 , 1 , 1 } ,  
 +  { 1 , 0.5 , 0.5 , 0.5 , 0.5 , 0.5 } , 
 +  type = Tri , 
 +  mu = 0 , 
 +  name = B } 
 +GB_t: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +GC_A: 
 +{ { 0 , 1 , 1.5 , 2 , 2.5 , 3 , 3.5 } ,  
 +  { 1 , 0.5 , 0.5 , 0.5 , 0.5 , 0.5 } , 
 +  type = And , 
 +  mu = 0 , 
 +  name = C } 
 +GC_a: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +GD_N: 
 +{ { 0 , 1 } , 
 +  type = Nat , 
 +  val = { { 0 , -1 , -1 , -1 , -1 , -1 , -1 } ,  
 +  { 0.70710678118655 , 0.5 , 0.5 , 0.5 , 0.5 , 0.5 } , 
 +  mu = 0 , 
 +  type = Tri } , 
 +  con = { { 0 , 1 , 1 , 1 , 1 , 1 , 1 } ,  
 +  { 0.70710678118655 , 0.5 , 0.5 , 0.5 , 0.5 , 0.5 } , 
 +  mu = 0 , 
 +  type = Tri } , 
 +  name = D , 
 +  mu = 0 } 
 +GD_n: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +omega = 0.764 
 +gamma = 0.1 
 + 
 +GA_L(omega, gamma) = (-0.52850742098896 - 0.28351791776891 I) 
 +GA_l(omega, gamma) = (-0.52850742098896 - 0.28351791776891 I) 
 +GB_T(omega, gamma) = (-1.6762624946074 - 5.2043002596032 I) 
 +GB_t(omega, gamma) = (-1.6762624946074 - 5.2043002596032 I) 
 +GC_A(omega, gamma) = (1.5075603166492 - 0.20713674761056 I) 
 +GC_a(omega, gamma) = (1.5075603166492 - 0.20713674761056 I) 
 +GD_N(omega, gamma) = (-0.52770560643508 - 2.61282805234 I) 
 +GD_n(omega, gamma) = (-0.52770560643508 - 2.61282805234 I) 
 +MA_L: 
 +{ { { { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } } , -1 , 0 , 1 } ,  
 +  { { { 11 , (18 + 6 I) , (30 + 6 I) } ,  
 +  { (18 - 6 I) , 62 , (84 - 3 I) } ,  
 +  { (30 - 6 I) , (84 + 3 I) , 126 } } ,  
 +  { { 13 , 18 , 33 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 33 , 84 , 126 } } ,  
 +  { { 18 , 18 , 36 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 36 , 84 , 126 } } } , 
 +  type = ListOfPoles , 
 +  mu = 0 , 
 +  name = A } 
 +MA_l: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +MB_T: 
 +{ { { { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } } ,  
 +  { { 1 , 2 , 3 } ,  
 +  { 2 , 5 , 6 } ,  
 +  { 3 , 6 , 9 } } ,  
 +  { { 2 , 2 , 3 } ,  
 +  { 2 , 5 , 6 } ,  
 +  { 3 , 6 , 9 } } ,  
 +  { { 3 , 2 , 3 } ,  
 +  { 2 , 5 , 6 } ,  
 +  { 3 , 6 , 9 } } } ,  
 +  { { { 1 , 0 , 0 } ,  
 +  { 0 , 1 , 0 } ,  
 +  { 0 , 0 , 1 } } ,  
 +  { { 11 , (18 + 6 I) , (30 + 6 I) } ,  
 +  { (18 - 6 I) , 62 , (84 - 3 I) } ,  
 +  { (30 - 6 I) , (84 + 3 I) , 126 } } ,  
 +  { { 13 , 18 , 33 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 33 , 84 , 126 } } } , 
 +  type = Tri , 
 +  mu = 0 , 
 +  name = B } 
 +MB_t: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +MC_A: 
 +{ { { { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } } ,  
 +  { { 1 , 2 , 3 } ,  
 +  { 2 , 5 , 6 } ,  
 +  { 3 , 6 , 9 } } ,  
 +  { { 2 , 2 , 3 } ,  
 +  { 2 , 5 , 6 } ,  
 +  { 3 , 6 , 9 } } ,  
 +  { { 3 , 2 , 3 } ,  
 +  { 2 , 5 , 6 } ,  
 +  { 3 , 6 , 9 } } } ,  
 +  { { { 1 , 0 , 0 } ,  
 +  { 0 , 1 , 0 } ,  
 +  { 0 , 0 , 1 } } ,  
 +  { { 11 , (18 + 6 I) , (30 + 6 I) } ,  
 +  { (18 - 6 I) , 62 , (84 - 3 I) } ,  
 +  { (30 - 6 I) , (84 + 3 I) , 126 } } ,  
 +  { { 13 , 18 , 33 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 33 , 84 , 126 } } } , 
 +  type = And , 
 +  mu = 0 , 
 +  name = C } 
 +MC_a: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +MD_N: 
 +{ { { { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } } ,  
 +  { { 1 , 0 , 0 } ,  
 +  { 0 , 1 , 0 } ,  
 +  { 0 , 0 , 1 } } } , 
 +  type = Nat , 
 +  val = { { { { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } } , -0.5 , -1 , -1.5 } ,  
 +  { { { 11 , (18 + 6 I) , (30 + 6 I) } ,  
 +  { (18 - 6 I) , 62 , (84 - 3 I) } ,  
 +  { (30 - 6 I) , (84 + 3 I) , 126 } } ,  
 +  { { 13 , 18 , 33 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 33 , 84 , 126 } } ,  
 +  { { 18 , 18 , 36 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 36 , 84 , 126 } } } , 
 +  type = ListOfPoles , 
 +  mu = 0 , 
 +  name = Dv } , 
 +  con = { { { { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } ,  
 +  { 0 , 0 , 0 } } , 0.5 , 1 , 1.5 } ,  
 +  { { { 11 , (18 + 6 I) , (30 + 6 I) } ,  
 +  { (18 - 6 I) , 62 , (84 - 3 I) } ,  
 +  { (30 - 6 I) , (84 + 3 I) , 126 } } ,  
 +  { { 13 , 18 , 33 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 33 , 84 , 126 } } ,  
 +  { { 18 , 18 , 36 } ,  
 +  { 18 , 61 , 84 } ,  
 +  { 36 , 84 , 126 } } } , 
 +  type = ListOfPoles , 
 +  mu = 0 , 
 +  name = Dc } , 
 +  name = D , 
 +  mu = 0 } 
 +MD_n: 
 +ResponseFunction in userdata format use ToTable() in order to get a table form 
 +omega = 0.764 
 +gamma = 0.1 
 + 
 +MA_L(omega, gamma) =  
 +{ { (-49.82074737235 - 16.750435144161 I) , (-39.242754250336 - 13.890672203015 I) , (-85.890426598686 - 30.827754261851 I) } ,  
 +  { (-39.435420350993 - 20.687932234176 I) , (-132.74935751632 - 58.607579693628 I) , (-183.63057392827 - 82.382725361235 I) } ,  
 +  { (-86.083092699343 - 37.625014293012 I) , (-183.53424087794 - 78.984095345655 I) , (-275.37361110465 - 121.02511553017 I) } } 
 +MA_l(omega, gamma) =  
 +{ { (-49.82074737235 - 16.750435144161 I) , (-39.242754250336 - 13.890672203015 I) , (-85.890426598686 - 30.827754261851 I) } ,  
 +  { (-39.435420350993 - 20.687932234176 I) , (-132.74935751632 - 58.607579693628 I) , (-183.63057392827 - 82.382725361235 I) } ,  
 +  { (-86.083092699343 - 37.625014293012 I) , (-183.53424087794 - 78.984095345655 I) , (-275.37361110465 - 121.02511553017 I) } } 
 + 
 +MB_T(omega, gamma) =  
 +{ { (0.99841211757801 - 0.4318886700871 I) , (-0.92217346376056 - 0.59364349550167 I) , (0.33618642304746 + 0.56252370645231 I) } ,  
 +  { (-0.51999398150154 + 0.87279523667066 I) , (0.69431808205569 - 0.1748977600005 I) , (-0.34355189835894 - 0.03809026037919 I) } ,  
 +  { (0.13982839704936 - 0.53101630282404 I) , (-0.25718128095213 + 0.17938506335344 I) , (0.080137084707226 - 0.049212538037938 I) } } 
 +MB_t(omega, gamma) =  
 +{ { (0.99841211757801 - 0.4318886700871 I) , (-0.92217346376056 - 0.59364349550167 I) , (0.33618642304746 + 0.56252370645231 I) } ,  
 +  { (-0.51999398150154 + 0.87279523667066 I) , (0.69431808205569 - 0.1748977600005 I) , (-0.34355189835894 - 0.03809026037919 I) } ,  
 +  { (0.13982839704936 - 0.53101630282404 I) , (-0.25718128095213 + 0.17938506335344 I) , (0.080137084707226 - 0.049212538037938 I) } } 
 + 
 +MC_A(omega, gamma) =  
 +{ { (0.0033404740201663 - 0.049014208032374 I) , (-0.0092579857609902 - 0.018133779674219 I) , (0.0041464743284782 + 0.021581712320061 I) } ,  
 +  { (0.001131475130102 - 0.019625764066449 I) , (-0.006620607647268 - 0.0094591143626733 I) , (0.0044705980344151 + 0.010254424901895 I) } ,  
 +  { (0.0018776712535675 + 0.024036826455971 I) , (0.0083397043445284 + 0.01003150710377 I) , (-0.0056913744700838 - 0.011590149052798 I) } } 
 +MC_a(omega, gamma) =  
 +{ { (0.0033404740201663 - 0.049014208032374 I) , (-0.0092579857609902 - 0.018133779674219 I) , (0.0041464743284782 + 0.021581712320061 I) } ,  
 +  { (0.001131475130102 - 0.019625764066449 I) , (-0.006620607647268 - 0.0094591143626733 I) , (0.0044705980344151 + 0.010254424901895 I) } ,  
 +  { (0.0018776712535675 + 0.024036826455971 I) , (0.0083397043445284 + 0.01003150710377 I) , (-0.0056913744700838 - 0.011590149052798 I) } } 
 + 
 +MD_N(omega, gamma) =  
 +{ { (-12.839446772164 - 21.169048830916 I) , (5.1855777994224 - 3.9320983625761 I) , (-10.184899840804 - 27.575394683943 I) } ,  
 +  { (-3.5000860033155 - 57.291484603566 I) , (7.3025877301526 - 104.46376534286 I) , (1.7613982402315 - 156.19487348125 I) } ,  
 +  { (-18.870563643542 - 80.934780924933 I) , (6.1042301416005 - 129.51518036075 I) , (5.8992212863723 - 214.2825403815 I) } } 
 +MD_n(omega, gamma) =  
 +{ { (-12.839446772164 - 21.169048830916 I) , (5.1855777994224 - 3.9320983625761 I) , (-10.184899840804 - 27.575394683943 I) } ,  
 +  { (-3.5000860033155 - 57.291484603566 I) , (7.3025877301526 - 104.46376534286 I) , (1.7613982402315 - 156.19487348125 I) } ,  
 +  { (-18.870563643542 - 80.934780924933 I) , (6.1042301416005 - 129.51518036075 I) , (5.8992212863723 - 214.2825403815 I) } }
 </file> </file>
  
 ===== Table of contents ===== ===== Table of contents =====
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