diff --git a/Proof of Leadership/generate_inputs.py b/Proof of Leadership/generate_inputs.py new file mode 100755 index 0000000..0cfb01c --- /dev/null +++ b/Proof of Leadership/generate_inputs.py @@ -0,0 +1,1348 @@ +#!/usr/bin/sage +# -*- mode: python ; -*- + + +from sage.all import * +import hashlib +import itertools +from hashlib import sha256 + +p = 52435875175126190479447740508185965837690552500527637822603658699938581184513 +F = FiniteField(p) + + + + + +# anemoi is from their repo +COST_ALPHA = { + 3 : 2, 5 : 3, 7 : 4, 9 : 4, + 11 : 5, 13 : 5, 15 : 5, 17 : 5, + 19 : 6, 21 : 6, 23 : 6, 25 : 6, + 27 : 6, 29 : 7, 31 : 7, 33 : 6, + 35 : 7, 37 : 7, 39 : 7, 41 : 7, + 43 : 7, 45 : 7, 47 : 8, 49 : 7, + 51 : 7, 53 : 8, 55 : 8, 57 : 8, + 59 : 8, 61 : 8, 63 : 8, 65 : 7, + 67 : 8, 69 : 8, 71 : 9, 73 : 8, + 75 : 8, 77 : 8, 79 : 9, 81 : 8, + 83 : 8, 85 : 8, 87 : 9, 89 : 9, + 91 : 9, 93 : 9, 95 : 9, 97 : 8, + 99 : 8, 101 : 9, 103 : 9, 105 : 9, + 107 : 9, 109 : 9, 111 : 9, 113 : 9, + 115 : 9, 117 : 9, 119 : 9, 121 : 9, + 123 : 9, 125 : 9, 127 : 10, +} + +ALPHA_BY_COST = { + c : [x for x in range(3, 128, 2) if COST_ALPHA[x] == c] + for c in range(2, 11) +} + +PI_0 = 1415926535897932384626433832795028841971693993751058209749445923078164062862089986280348253421170679 +PI_1 = 8214808651328230664709384460955058223172535940812848111745028410270193852110555964462294895493038196 + +def get_prime(N): + result = (1 << N) - 1 + while not is_prime(result): + result -= 2 + return result + + +def get_n_rounds(s, l, alpha): + r = 0 + complexity = 0 + kappa = {3:1, 5:2, 7:4, 9:7, 11:9} + assert alpha in kappa + while complexity < 2**s: + r += 1 + complexity = binomial( + 4*l*r + kappa[alpha], + 2*l*r + )**2 + r += 2 # considering the second model + r += min(5,l+1) # security margin + + return max(8, r) + + +# Linear layer generation + +def is_mds(m): + # Uses the Laplace expansion of the determinant to calculate the (m+1)x(m+1) minors in terms of the mxm minors. + # Taken from https://github.com/mir-protocol/hash-constants/blob/master/mds_search.sage. + + # 1-minors are just the elements themselves + if any(any(r == 0 for r in row) for row in m): + return False + + N = m.nrows() + assert m.is_square() and N >= 2 + + det_cache = m + + # Calculate all the nxn minors of m: + for n in range(2, N+1): + new_det_cache = dict() + for rows in itertools.combinations(range(N), n): + for cols in itertools.combinations(range(N), n): + i, *rs = rows + + # Laplace expansion along row i + det = 0 + for j in range(n): + # pick out c = column j; the remaining columns are in cs + c = cols[j] + cs = cols[:j] + cols[j+1:] + + # Look up the determinant from the previous iteration + # and multiply by -1 if j is odd + cofactor = det_cache[(*rs, *cs)] + if j % 2 == 1: + cofactor = -cofactor + + # update the determinant with the j-th term + det += m[i, c] * cofactor + + if det == 0: + return False + new_det_cache[(*rows, *cols)] = det + det_cache = new_det_cache + return True + +def M_2(x_input, b): + x = x_input[:] + x[0] += b*x[1] + x[1] += b*x[0] + return x + +def M_3(x_input, b): + x = x_input[:] + t = x[0] + b*x[2] + x[2] += x[1] + x[2] += b*x[0] + x[0] = t + x[2] + x[1] += t + return x + + +def M_4(x_input, b): + x = x_input[:] + x[0] += x[1] + x[2] += x[3] + x[3] += b*x[0] + x[1] = b*(x[1] + x[2]) + x[0] += x[1] + x[2] += b*x[3] + x[1] += x[2] + x[3] += x[0] + return x + +def lfsr(x_input, b): + x = x_input[:] + l = len(x) + for r in range(0, l): + t = sum(b**(2**i) * x[i] for i in range(0, l)) + x = x[1:] + [t] + return x + +def circulant_mds_matrix(field, l, coeff_upper_limit=None): + if coeff_upper_limit == None: + coeff_upper_limit = l+1 + assert(coeff_upper_limit > l) + for v in itertools.combinations_with_replacement(range(1,coeff_upper_limit), l): + mat = matrix.circulant(list(v)).change_ring(field) + if is_mds(mat): + return(mat) + # In some cases, the method won't return any valid matrix, + # hence the need to increase the limit further. + return circulant_mds_matrix(field, l, coeff_upper_limit+1) + +def get_mds(field, l): + if l == 1: + return identity_matrix(field, 1) + if l <= 4: # low addition case + a = field.multiplicative_generator() + b = field.one() + t = 0 + while True: + # we construct the matrix + mat = [] + b = b*a + t += 1 + for i in range(0, l): + x_i = [field.one() * (j == i) for j in range(0, l)] + if l == 2: + mat.append(M_2(x_i, b)) + elif l == 3: + mat.append(M_3(x_i, b)) + elif l == 4: + mat.append(M_4(x_i, b)) + mat = Matrix(field, l, l, mat).transpose() + if is_mds(mat): + return mat + else: # circulant matrix case + return circulant_mds_matrix(field, l) + +# AnemoiPermutation class + +class AnemoiPermutation: + def __init__(self, + q=None, + alpha=None, + mat=None, + n_rounds=None, + n_cols=1, + security_level=128): + if q == None: + raise Exception("The characteristic of the field must be specified!") + self.q = q + self.prime_field = is_prime(q) # if true then we work over a + # prime field with + # characteristic just under + # 2**N, otherwise the + # characteristic is 2**self + self.n_cols = n_cols # the number of parallel S-boxes in each round + self.security_level = security_level + + # initializing the other variables in the state: + # - q is the characteristic of the field + # - g is a generator of the multiplicative subgroup + # - alpha is the main exponent (in the center of the Flystel) + # - beta is the coefficient in the quadratic subfunction + # - gamma is the constant in the second quadratic subfunction + # - QUAD is the secondary (quadratic) exponent + # - from_field is a function mapping field elements to integers + # - to_field is a function mapping integers to field elements + self.F = GF(self.q) + if self.prime_field: + if alpha != None: + if gcd(alpha, self.q-1) != 1: + raise Exception("alpha should be co-prime with the characteristic!") + else: + self.alpha = alpha + else: + self.alpha = 3 + while gcd(self.alpha, self.q-1) != 1: + self.alpha += 1 + self.QUAD = 2 + self.to_field = lambda x : self.F(x) + self.from_field = lambda x : Integer(x) + else: + self.alpha = 3 + self.QUAD = 3 + self.to_field = lambda x : self.F.fetch_int(x) + self.from_field = lambda x : x.integer_representation() + self.g = self.F.multiplicative_generator() + self.beta = self.g + self.delta = self.g**(-1) + self.alpha_inv = inverse_mod(self.alpha, self.q-1) + + # total number of rounds + if n_rounds != None: + self.n_rounds = n_rounds + else: + self.n_rounds = get_n_rounds(self.security_level, + self.n_cols, + self.alpha) + + # Choosing constants: self.C and self.D are built from the + # digits of pi using an open butterfly + self.C = [] + self.D = [] + pi_F_0 = self.to_field(PI_0 % self.q) + pi_F_1 = self.to_field(PI_1 % self.q) + for r in range(0, self.n_rounds): + pi_0_r = pi_F_0**r + self.C.append([]) + self.D.append([]) + for i in range(0, self.n_cols): + pi_1_i = pi_F_1**i + pow_alpha = (pi_0_r + pi_1_i)**self.alpha + self.C[r].append(self.g * (pi_0_r)**2 + pow_alpha) + self.D[r].append(self.g * (pi_1_i)**2 + pow_alpha + self.delta) + self.mat = get_mds(self.F, self.n_cols) + + + def __str__(self): + result = "Anemoi instance over F_{:d} ({}), n_rounds={:d}, n_cols={:d}, s={:d}".format( + self.q, + "odd prime field" if self.prime_field else "characteristic 2", + self.n_rounds, + self.n_cols, + self.security_level + ) + result += "\nalpha={}, beta={}, \ndelta={}\nM_x=\n{}\ninv_alpha={}\n".format( + self.alpha, + self.beta, + self.delta, + self.mat, + self.alpha_inv + ) + result += "C={}\nD={}".format( + [[self.from_field(x) for x in self.C[r]] for r in range(0, self.n_rounds)], + [[self.from_field(x) for x in self.D[r]] for r in range(0, self.n_rounds)], + ) + return result + + + # !SECTION! Sub-components + + def evaluate_sbox(self, _x, _y): + x, y = _x, _y + x -= self.beta*y**self.QUAD + y -= x**self.alpha_inv + x += self.beta*y**self.QUAD + self.delta + return x, y + + def linear_layer(self, _x, _y): + x, y = _x[:], _y[:] + x = self.mat*vector(x) + y = self.mat*vector(y[1:] + [y[0]]) + + # Pseudo-Hadamard transform on each (x,y) pair + y += x + x += y + return list(x), list(y) + + + # !SECTION! Evaluation + + def eval_with_intermediate_values(self, _x, _y): + x, y = _x[:], _y[:] + result = [[x[:], y[:]]] + for r in range(0, self.n_rounds): + for i in range(0, self.n_cols): + x[i] += self.C[r][i] + y[i] += self.D[r][i] + x, y = self.linear_layer(x, y) + for i in range(0, self.n_cols): + x[i], y[i] = self.evaluate_sbox(x[i], y[i]) + result.append([x[:], y[:]]) + # final call to the linear layer + x, y = self.linear_layer(x, y) + result.append([x[:], y[:]]) + return result + + + def input_size(self): + return 2*self.n_cols + + + def __call__(self, _x): + if len(_x) != self.input_size(): + raise Exception("wrong input size!") + else: + x, y = _x[:self.n_cols], _x[self.n_cols:] + u, v = self.eval_with_intermediate_values(x, y)[-1] + return u + v # concatenation, not a sum + + + # !SECTION! Writing full system of equations + + def get_polynomial_variables(self): + x_vars = [] + y_vars = [] + all_vars = [] + for r in range(0, self.n_rounds+1): + x_vars.append(["X{:02d}{:02d}".format(r, i) for i in range(0, self.n_cols)]) + y_vars.append(["Y{:02d}{:02d}".format(r, i) for i in range(0, self.n_cols)]) + all_vars += x_vars[-1] + all_vars += y_vars[-1] + pol_ring = PolynomialRing(self.F, (self.n_rounds+1)*2*self.n_cols, all_vars) + pol_gens = pol_ring.gens() + result = {"X" : [], "Y" : []} + for r in range(0, self.n_rounds+1): + result["X"].append([]) + result["Y"].append([]) + for i in range(0, self.n_cols): + result["X"][r].append(pol_gens[self.n_cols*2*r + i]) + result["Y"][r].append(pol_gens[self.n_cols*2*r + i + self.n_cols]) + return result + + + def verification_polynomials(self, pol_vars): + equations = [] + for r in range(0, self.n_rounds): + # the outputs of the open flystel are the state variables x, y at round r+1 + u = pol_vars["X"][r+1] + v = pol_vars["Y"][r+1] + # the inputs of the open flystel are the state variables + # x, y at round r after undergoing the constant addition + # and the linear layer + x, y = pol_vars["X"][r], pol_vars["Y"][r] + x = [x[i] + self.C[r][i] for i in range(0, self.n_cols)] + y = [y[i] + self.D[r][i] for i in range(0, self.n_cols)] + x, y = self.linear_layer(x, y) + for i in range(0, self.n_cols): + equations.append( + (y[i]-v[i])**self.alpha + self.beta*y[i]**self.QUAD - x[i] + ) + equations.append( + (y[i]-v[i])**self.alpha + self.beta*v[i]**self.QUAD + self.delta - u[i] + ) + return equations + + + def print_verification_polynomials(self): + p_vars = self.get_polynomial_variables() + eqs = self.verification_polynomials(p_vars) + variables_string = "" + for r in range(0, self.n_rounds+1): + variables_string += str(p_vars["X"][r])[1:-1] + "," + str(p_vars["Y"][r])[1:-1] + "," + print(variables_string[:-1].replace(" ", "")) + print(self.q) + for f in eqs: + print(f) + + + +# !SECTION! Modes of operation + + +def jive(P, b, _x): + if b < 2: + raise Exception("b must be at least equal to 2") + if P.input_size() % b != 0: + raise Exception("b must divide the input size!") + c = P.input_size()/b # length of the compressed output + # Output size check: we allow the output size to be 3 bits shorter than + # the theoretical target, as commonly used finite fields usually have a + # characteristic size slightly under 2**256. + if c * P.F.cardinality().nbits() < 2 * P.security_level - 3: + raise Exception(f"digest size is too small for the targeted security level!") + x = _x[:] + u = P(x) + compressed = [] + for i in range(0, int(c)): + compressed.append(sum(x[int(i+c*j)] + u[int(i+c*j)] + for j in range(0, int(b)))) + return compressed + +A_2 = AnemoiPermutation(q=p, alpha=5, n_rounds=None, n_cols=1, security_level=128) +A_4 = AnemoiPermutation(q=p, alpha=5, n_rounds=None, n_cols=2, security_level=128) +A_16 = AnemoiPermutation(q=p, alpha=5, n_rounds=None, n_cols=8, security_level=128) + +def anemoi(state): + if len(state) == 2: + return jive(A_2,2,state)[0] + if len(state) == 4: + return jive(A_4,4,state)[0] + if len(state) == 16: + return jive(A_16,16,state)[0] + +def poseidon(state): + if len(state) == 2: + original_state = state + cst = poseidon_round_constant_2_to_1() + state = poseidon_linear_layer_2_to_1(state) + for i in range(4): + for j in range(2): + state[j] += cst[2*i+j] + state[j] = state[j]**5 + state = poseidon_linear_layer_2_to_1(state) + for i in range(56): + state[0] += cst[i + 8] + state[0] = state[0]**5 + state = poseidon_linear_layer_2_to_1(state) + for i in range(4): + for j in range(2): + state[j] += cst[64 + i*2 + j] + state[j] = state[j]**5 + state = poseidon_linear_layer_2_to_1(state) + return state[0] + state[1] + original_state[0] + original_state[1] + if len(state) == 4: + original_state = state + cst = poseidon_round_constant_4_to_1() + state = poseidon_external_linear_layer_4_to_1(state) + for i in range(4): + for j in range(4): + state[j] += cst[4*i+j] + state[j] = state[j]**5 + state = poseidon_external_linear_layer_4_to_1(state) + for i in range(56): + state[0] += cst[i + 16] + state[0] = state[0]**5 + state = poseidon_internal_linear_layer_4_to_1(state) + for i in range(4): + for j in range(4): + state[j] += cst[72 + i*4 + j] + state[j] = state[j]**5 + state = poseidon_external_linear_layer_4_to_1(state) + h = F(0) + for i in range(4): + h += state[i] + original_state[i] + return h + if len(state) == 16: + original_state = state + cst = poseidon_round_constant_16_to_1() + state = poseidon_external_linear_layer_16_to_1(state) + for i in range(4): + for j in range(16): + state[j] += cst[16*i+j] + state[j] = state[j]**5 + state = poseidon_external_linear_layer_16_to_1(state) + for i in range(57): + state[0] += cst[i + 64] + state[0] = state[0]**5 + state = poseidon_internal_linear_layer_16_to_1(state) + for i in range(4): + for j in range(16): + state[j] += cst[121 + i*16 + j] + state[j] = state[j]**5 + state = poseidon_external_linear_layer_16_to_1(state) + h = F(0) + for i in range(16): + h += state[i] + original_state[i] + return h + +def poseidon_linear_layer_2_to_1(state): + M = Matrix(F,[[2,1],[1,2]]) + return [2*state[0]+state[1],state[0]+2*state[1]] + +def poseidon_external_linear_layer_4_to_1(state): + M_4 = [[5,7,1,3],[4,6,1,1],[1,3,5,7],[1,1,4,6]] + new_state = [0 for i in range(4)] + for i in range(4): + for j in range(4): + new_state[i] += M_4[i][j] * state[j] + return new_state + +def poseidon_external_linear_layer_16_to_1(state): + M_E = [[10,14,2,6,5,7,1,3,5,7,1,3,5,7,1,3], + [ 8,12,2,2,4,6,1,1,4,6,1,1,4,6,1,1], + [ 2,6,10,14,1,3,5,7,1,3,5,7,1,3,5,7], + [ 2,2,8,12,1,1,4,6,1,1,4,6,1,1,4,6], + [ 5,7,1,3,10,14,2,6,5,7,1,3,5,7,1,3], + [ 4,6,1,1,8,12,2,2,4,6,1,1,4,6,1,1], + [ 1,3,5,7,2,6,10,14,1,3,5,7,1,3,5,7], + [ 1,1,4,6,2,2,8,12,1,1,4,6,1,1,4,6], + [ 5,7,1,3,5,7,1,3,10,14,2,6,5,7,1,3], + [ 4,6,1,1,4,6,1,1,8,12,2,2,4,6,1,1], + [ 1,3,5,7,1,3,5,7,2,6,10,14,1,3,5,7], + [ 1,1,4,6,1,1,4,6,2,2,8,12,1,1,4,6], + [ 5,7,1,3,5,7,1,3,5,7,1,3,10,14,2,6], + [ 4,6,1,1,4,6,1,1,4,6,1,1,8,12,2,2], + [ 1,3,5,7,1,3,5,7,1,3,5,7,2,6,10,14], + [ 1,1,4,6,1,1,4,6,1,1,4,6,2,2,8,12]] + new_state = [0 for i in range(16)] + for i in range(16): + for j in range(16): + new_state[i] += M_E[i][j] * state[j] + return new_state + +def poseidon_internal_linear_layer_4_to_1(state): + M_I = [[2,1,1,1],[1,2,1,1],[1,1,4,1],[1,1,1,8]] + new_state = [0 for i in range(4)] + for i in range(4): + for j in range(4): + new_state[i] += M_I[i][j] * state[j] + return new_state + +def poseidon_internal_linear_layer_16_to_1(state): + M_I = [[68,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1], + [1,85,1,1,1,1,1,1,1,1,1,1,1,1,1,1], + [1,1,81,1,1,1,1,1,1,1,1,1,1,1,1,1], + [1,1,1,95,1,1,1,1,1,1,1,1,1,1,1,1], + [1,1,1,1,58,1,1,1,1,1,1,1,1,1,1,1], + [1,1,1,1,1,90,1,1,1,1,1,1,1,1,1,1], + [1,1,1,1,1,1,93,1,1,1,1,1,1,1,1,1], + [1,1,1,1,1,1,1,40,1,1,1,1,1,1,1,1], + [1,1,1,1,1,1,1,1,35,1,1,1,1,1,1,1], + [1,1,1,1,1,1,1,1,1,25,1,1,1,1,1,1], + [1,1,1,1,1,1,1,1,1,1,2,1,1,1,1,1], + [1,1,1,1,1,1,1,1,1,1,1,96,1,1,1,1], + [1,1,1,1,1,1,1,1,1,1,1,1,22,1,1,1], + [1,1,1,1,1,1,1,1,1,1,1,1,1,74,1,1], + [1,1,1,1,1,1,1,1,1,1,1,1,1,1,69,1], + [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,53]] + new_state = [0 for i in range(16)] + for i in range(16): + for j in range(16): + new_state[i] += M_I[i][j] * state[j] + return new_state + + + +def anemoi_C_2_to_1(): + return [ + 39, + 41362478282768062297187132445775312675360473883834860695283235286481594490621, + 9548818195234740988996233204400874453525674173109474205108603996010297049928, + 25365440569177822667580105183435418073995888230868180942004497015015045856900, + 34023498397393406644117994167986720327178154686105264833093891093045919619309, + 38816051319719761886041858113129205506758421478656182868737326994635468402951, + 35167418087531820804128377095512663922179887277669504047069913414630376083753, + 25885868839756469722325652387535232478219821850603640827385444642154834700231, + 8867588811641202981080659274007552529205713737251862066053445622305818871963, + 36439756010140137556111047750162544185710881404522379792044818039722752946048, + 7788624504122357216765350546787885309160020166693449889975992574536033007374, + 3134147137704626983201116226440762775442116005053282329971088789984415999550, + 50252287380741824818995733304361249016282047978221591906573165442023106203143, + 48434698978712278012409706205559577163572452744833134361195687109159129985373, + 32960510617530186159512413633821386297955642598241661044178889571655571939473, + 12850897859166761094422335671106280470381427571695744605265713866647560628356, + 14578036872634298798382048587794204613583128573535557156943783762854124345644, + 21588109842058901916690548710649523388049643745013696896704903154857389904594, + 35731638686520516424752846654442973203189295883541072759390882351699754104989, + 34141830003233180772153845227433233456603143306530920011579259084215824391544, + 30272543670850635882116596228256005460817517173808721139136515002908946750291 + ] + +def anemoi_D_2_to_1(): + return [ + 14981678621464625851270783002338847382197300714436467949315331057125308909900, + 28253420209785428420233456008091632509255652343634529984400816700490470131093, + 51511939407083344002778208487678590135577660247075600880835916725469990319313, + 46291121544435738125248657675097664742296276807186696922340332893747842754587, + 3650460179273129580093806058710273018999560093475503119057680216309578390988, + 45802223370746268123059159806400152299867771061127345631244786118574025749328, + 11798621276624967315721748990709309216351696098813162382053396097866233042733, + 42372918959432199162670834641599336326433006968669415662488070504036922966492, + 52181371244193189669553521955614617990714056725501643636576377752669773323445, + 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46030886964045328670650579467522042981756109464584907077434772786649263902996], + [48434698978712278012409706205559577163572452744833134361195687109159129985373, + 19216533213230709497947223526297848065365334472367022650183395435586190711770] + ] + +def anemoi_D_4_to_1(): + return [ + [14981678621464625851270783002338847382197300714436467949315331057125308909900, + 48720959343719104324739338388885839802998711550637402773896395605948383052052], + [28253420209785428420233456008091632509255652343634529984400816700490470131093, + 6257781313532096835800460747082714697295034136932481743077166200794135826591], + [51511939407083344002778208487678590135577660247075600880835916725469990319313, + 4386017178186728799761421274050927732938229436976005221436222062273391481632], + [46291121544435738125248657675097664742296276807186696922340332893747842754587, + 13820180736478645172746469075181304604729976364812127548341524461074783412926], + 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22462223600300108924276123720518708580622354327562062947406284488847554180931, + 40996278729170725855966064159584167091102415184996744640950022676164065046834, + 19430817579416357934148820670939901668848861606295052060308554899051486801548, + 12483379002100433076591219143638049458199676871775181258981956241115974881163] + ] + +def anemoi_D_16_to_1(): + return [ + [14981678621464625851270783002338847382197300714436467949315331057125308909900, + 48720959343719104324739338388885839802998711550637402773896395605948383052052, + 11709610427641952476226704950218052763560489079301307464225164120801969364960, + 3188799073106888901912065951229864304299742047220134499402570163601813730969, + 35055566170683830204685883433867693478135114051401583710007741398997412970579, + 41969389849183863090802087476567191363990360356945841340095187311995419576515, + 7556226394164164334481570938023506204252451033715203682883249970224239802922, + 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16026951337367383175610820246210183497734025720194433489132017234538604936414, + 33572475268799564642745000649407837861228346301126684294541252715366099579094, + 26220434981437976873498592303656146371158505657662010285451539733034399969825, + 31040488125858696173362986090795905945928951823554908571888900564555975057860, + 47286385036886749775224009536390346046643937618292722852399698152345906543537, + 20950917282535983122464307959293663918938997314569186126689031705635737272062, + 16685712499755301665281386819771726363157372904949135525550583883571962834528, + 18683291445525541017294795892345078328382688847480507122165708511223740177458, + 2608268839331669212463985078421319322001352992807108968314090990777368891770, + 40037105172855926626375817902131326490267684706159606232991633054381953553026, + 21626330967116418140505001603028197974177240574915763170077069271066169546158, + 35330469786033362269122965704661462637931218147681429112041541870602933338162, + 7959740499179483922969783988740981409045430979967212583073048384801003055527 + ] + + + +R = RealField(500) #Real numbers with precision 500 bits + +if len(sys.argv) != Integer(7): + print("Usage: