{-# LANGUAGE MultiParamTypeClasses #-} -- | This module implements the specialized quantum operations required in stages 1 and 4 of Hallgren’s algorithm. -- -- The key operation for stage 1 is 'q_fN', implementing /f/[sub /N/], the quasi-periodic -- function used in approximating the regulator. This is the function /h/ of -- [Jozsa 2003], Sec. 9, discretized with precision 1\//N/ and translated by a -- specified jitter parameter. -- -- The key functions for stage 4 are not yet implemented. These essentially -- consist of the functions /f/[sub /I/,/N/], analogues of /f/[sub /N/] operating -- within the equivalence classes of possibly non-principal ideals /I/ (representing -- other elements of the class group), as described in [Hallgren 2006, Section 5]. module Quipper.Algorithms.CL.RegulatorQuantum where import Quipper import Quipper.Internal import Quipper.Libraries.Arith hiding (q_ext_euclid, q_add, q_mult, q_div_exact, q_add_in_place, q_add_param_in_place, q_div, q_mult_param, q_mod_unsigned, q_sub_in_place, q_increment) import qualified Quipper.Libraries.Arith as Arith import Quipper.Libraries.FPReal import Quipper.Algorithms.CL.Auxiliary import Quipper.Algorithms.CL.Types import Quipper.Algorithms.CL.RegulatorClassical import Control.Monad (foldM) -- ====================================================================== -- * Basic operations on ideals -- | Send /I/ = \</k/,/l/,/a/,/b/> to /l/\//ka/ /I/ = \<1,/a/,/a/,/b/>. -- -- On distances, send δ[sub /I/] to δ[sub /I/] - log (/l/\//ka/). -- Implementation note: is it more efficient to multply/divide and then -- take log, or take logs separately and then add/subtract? q_normalize :: IdDistQ -> Circ (IdDistQ,IdDistQ) q_normalize = box "q_normalize" $ \((Ideal bigD k l a b), dist) -> do let k_bits = qulist_of_qdint_bh k n = length k_bits k' <- qinit (intm n 1) (a,l') <- qc_copy_fun a (a,a') <- qc_copy_fun a (b,b') <- qc_copy_fun b ((k,l,a,dist), dist') <- with_computed_fun (k,l,a,dist) (\(k,l,a,dist) -> do (k,k_clreal) <- q_fromQDInt k (l,l_clreal) <- q_fromQDInt l (a,a_clreal) <- q_fromQDInt a (k_clreal,log_k) <- fprealq_log_with_shape dist k_clreal (l_clreal,log_l) <- fprealq_log_with_shape dist l_clreal (a_clreal,log_a) <- fprealq_log_with_shape dist a_clreal (log_k, dist) <- fprealq_sub_in_place log_k dist (log_l, dist) <- fprealq_add_in_place log_l dist (log_a, dist) <- fprealq_sub_in_place log_a dist return (((k,l,a),(k_clreal,l_clreal,a_clreal),(log_k,log_l,log_a)), dist)) (\(various, dist) -> do (dist,dist') <- qc_copy_fun dist return ((various,dist), dist')) return ((Ideal bigD k l a b, dist), (Ideal bigD k' l' a' b', dist')) -- | Apply the function ρ to an 'IdealQ' together with a distance. -- See [Jozsa 2003], Sect 6.2, preceding Prop. 21; compare 'rho_d'. -- Implementation note: not factored into q_rho plus action on distance, -- since the two share a bit of computation (c_num). q_rho_d :: IdDistQ -> Circ (IdDistQ,IdDistQ) q_rho_d = box "rho" $ \iid@(Ideal bigD m l a b, del) -> do rho_iid <- with_computed (do (_,_,b_sq) <- q_mult b b b_sq' <- q_sub_param_in_place (fromIntegral bigD) b_sq (_,c_num) <- q_abs b_sq' (_,c_denom) <- q_mult_param 4 a (_,_,c) <- q_div_exact c_num c_denom let a' = c (_,b_neg) <- q_negate b (_,_,b') <- q_tau bigD b_neg a' (_,_,m') <- q_mult m a (_,_,l') <- q_mult l a' (_,_,_,_,d) <- q_ext_euclid m' l' (_,_,m'') <- q_div_exact m' d (_,_,l'') <- q_div_exact l' d let ii' = Ideal bigD a' b' m'' l'' -- By definition, del_change = log $ abs $ gamma_bar / 2 * gamma, -- where gamma = b/2a + (1/2*a)*(sqrt bigD). -- -- A few lines of algebra gives: -- del_change = log $ (b - (sqrt bigD))^2 / (abs $ b^2 - bigD) -- = log (b - (sqrt bigD))^2 - log (abs $ b^2 - bigD) (_,b_fp) <- fprealq_of_QDInt_with_shape del b b_fp <- fprealq_add_param_in_place (negate $ sqrt $ fromIntegral bigD) b_fp (_,_,b_fp_sq) <- q_mult b_fp b_fp (_,del_change_1) <- fprealq_log_with_shape del b_fp_sq (_,del_change_2) <- fprealq_log_with_shape del (fprealx 0 c_num) del' <- qc_copy del (_,del') <- fprealq_add_in_place del_change_1 del' (_,del') <- fprealq_sub_in_place del_change_2 del' return (ii', del')) qc_copy return (iid, rho_iid) -- | Apply the function ρ[sup –1] to an 'IdealQ' together with a distance. -- See [Jozsa 2003], Sec 6.2, preceding Prop. 21, and Sec 6.4; compare 'rho_inv_d'. q_rho_inv_d :: IdDistQ -> Circ (IdDistQ, IdDistQ) q_rho_inv_d = box "rho_inv" $ \iid@(Ideal bigD m l a b, del) -> do rho_inv_iid <- with_computed (do -- b' = τ(Δ,-b,a): (_, b_neg) <- q_negate b (_, _, b') <- q_tau bigD b_neg a -- a'' = (Δ - b'^2) / (4*a): (_, b'_sq) <- q_square b' (_, a''_num) <- q_negate b'_sq a''_num <- q_add_param_in_place (fromIntegral bigD) a''_num (_, a''_denom) <- q_mult_param 4 a (_, _, a'') <- q_div_exact a''_num a''_denom (_, _, b'') <- q_tau bigD b' a'' -- m''/l'' = m*a / l*a'', reduced to lowest terms: (_, _, m') <- q_mult m a (_, _, l') <- q_mult l a'' (_,_,_,_, d) <- q_ext_euclid m' l' (_, _, m'') <- q_div_exact m' d (_, _, l'') <- q_div_exact l' d let ii' = Ideal bigD a'' b'' m'' l'' -- Compute del_change as in 'q_rho_d', -- but using coefficients from ii': (_,b_fp) <- fprealq_of_QDInt_with_shape del b'' b_fp <- fprealq_add_param_in_place (negate $ sqrt $ fromIntegral bigD) b_fp (_,_,b_fp_sq) <- q_mult b_fp b_fp (_,del_change_1) <- fprealq_log_with_shape del b_fp_sq (_,_,b_sq) <- q_mult b'' b'' b_sq' <- q_sub_param_in_place (fromIntegral bigD) b_sq (_,c_num) <- q_abs b_sq' (_,del_change_2) <- fprealq_log_with_shape del (fprealx 0 c_num) del' <- qc_copy del (_,del') <- fprealq_sub_in_place del_change_1 del' (_,del') <- fprealq_add_in_place del_change_2 del' return (ii', del')) qc_copy return (iid, rho_inv_iid) -- | As 'q_rho_d', but for reduced ideals. -- Implementation note: could be optimised a bit, since some of the algebra -- needed for ρ in the general case is redundant for reduced ideals. q_rho_red_d :: IdRedDistQ -> Circ (IdRedDistQ,IdRedDistQ) q_rho_red_d (ii,del) = do ii <- q_forget_reduced ii ((ii,del), (ii',del')) <- q_rho_d (ii,del) ii <- q_assert_reduced ii ii' <- q_assert_reduced ii' return ((ii,del), (ii',del')) -- | As 'q_rho_inv_d', but for reduced ideals. -- Implementation note: could be optimised, like 'q_rho_red_d'. q_rho_inv_red_d :: IdRedDistQ -> Circ (IdRedDistQ,IdRedDistQ) q_rho_inv_red_d (ii,del) = do ii <- q_forget_reduced ii ((ii,del), (ii',del')) <- q_rho_inv_d (ii,del) ii <- q_assert_reduced ii ii' <- q_assert_reduced ii' return ((ii,del), (ii',del')) -- ====================================================================== -- * Products of ideals -- | Compute the ordinary (not necessarily reduced) product of two reduced -- fractional ideals. -- -- This is /I/⋅/J/ of [Jozsa 2003], Sec 7.1, following the description -- given in Prop. 34. q_dot_prod :: IdealRedQ -> IdealRedQ -> Circ (IdealRedQ,IdealRedQ,IdealQ) q_dot_prod = box "q_dot_prod" $ \(IdealRed bigD1 a1 b1) (IdealRed bigD2 a2 b2) -> do assertM (all_eq [bigD1,bigD2]) "Error: mismatched Δ’s in q_dot_prod." let bigD = bigD1 n = qdint_length a1 label (a1,b1,a2,b2) ("a1","b1","a2","b2") ((a1,a2,b1,b2),(k,l,a3,b3)) <- with_computed_fun (a1,a2,b1,b2) (\(a1,a2,b1,b2) -> do comment "q_dot_prod, step 1: (khat,uhat,vhat) <- ExtendedEuclid(a1,a2)" (a1,a2,khat,uhat,vhat) <- q_ext_euclid a1 a2 label (khat,uhat,vhat) ("khat","uhat","vhat") comment "q_dot_prod, step 2: (k,u,v) <- ExtendedEuclid(khat,(b1+b2)/2)" (b1,b2,b1b2) <- q_add b1 b2 b1b2 <- q_div2 b1b2 label (b1b2) ("(b1 + b2)/2") (khat,b1b2,k,x,w) <- q_ext_euclid khat b1b2 label (k,x,w) ("k","x","w") comment "q_dot_prod, step 3: a3 := a1a2/k^2. [This should always be an integer.]" (a1,a2,a1a2) <- q_mult a1 a2 label (a1a2) ("a1*a2") (k,k_sq) <- q_square k label (k_sq) ("k^2") (a1a2,k_sq,a3) <- q_div_exact a1a2 k_sq label (a1a2,k_sq,a3) ("a3") comment "q_dot_prod, step 4: t = (long formula, requiring many intermediate calculations)" (((a1,b1,a2,b2),(uhat,vhat,k,x,w)),t) <- with_computed_fun ((a1,b1,a2,b2),(uhat,vhat,k,x,w)) (\((a1,b1,a2,b2),(uhat,vhat,k,x,w)) -> do comment "q_dot_prod, step 4, first summand: x * uhat * a1 * b2" (x,uhat,x_uhat) <- q_mult x uhat label x_uhat "x * uhat" (x_uhat,a1,x_uhat_a1) <- q_mult x_uhat a1 label x_uhat_a1 "x * uhat * a1" (x_uhat_a1,b2,x_uhat_a1_b2) <- q_mult x_uhat_a1 b2 label x_uhat_a1_b2 "x * uhat * a1 * b2" comment "q_dot_prod, step 4, second summand: x * vhat * a2 * b1" (x,vhat,x_vhat) <- q_mult x vhat label x_vhat "x * vhat" (x_vhat,a2,x_vhat_a2) <- q_mult x_vhat a2 label x_vhat_a2 "x * vhat * a2" (x_vhat_a2,b1,x_vhat_a2_b1) <- q_mult x_vhat_a2 b1 label x_vhat_a2_b1 "x * vhat * a2 * b1" comment "q_dot_prod, step 4, third summand: w * (b1 * b2 + Delta) / 2" (b1,b2,b1_b2) <- q_mult b1 b2 label b1_b2 "b1 * b2" b1_b2_D <- q_add_param_in_place (fromInteger $ toInteger bigD) b1_b2 label b1_b2_D "b1 * b2 + Delta" b1_b2_D_by2 <- q_div2 b1_b2_D label b1_b2_D_by2 "(b1 * b2 + Delta) / 2" (w,b1_b2_D_by2,w_b1_b2_D_by2) <- q_mult w b1_b2_D_by2 label b1_b2_D_by2 "w * (b1 * b2 + Delta) / 2" comment "q_dot_prod, step 4, sum of all summands:" (x_uhat_a1_b2,x_vhat_a2_b1,s) <- q_add x_uhat_a1_b2 x_vhat_a2_b1 (w_b1_b2_D_by2,s) <- q_add_in_place w_b1_b2_D_by2 s label s "big sum from step 4" return ((a1,b1,a2,b2), (uhat,vhat,k,x,w), (x_uhat,x_uhat_a1,x_uhat_a1_b2), (x_vhat,x_vhat_a2,x_vhat_a2_b1), (b1_b2_D_by2,w_b1_b2_D_by2), s)) (\(inputs, (uhat,vhat,k,x,w), subterm1, subterm2, subterm3, s) -> do comment "q_dot_prod, step 4, final division: t := (big sum) / k" (s,k,t) <- q_div s k label t "t" return ((inputs, (uhat,vhat,k,x,w), subterm1, subterm2, subterm3, s), t)) comment "q_dot_prod, step 5: set b3 <- (t mod 2a3) - (a3 - 1)." (a3,twice_a3) <- q_mult_param 2 a3 (t,twice_a3,b3) <- q_mod_unsigned t twice_a3 (a3,b3) <- q_sub_in_place a3 b3 b3 <- q_increment b3 label b3 "b3" comment "q_dot_prod, step 6: test if (a3 > root Delta), store result as case_a3" (a3,case_a3) <- q_gt_param a3 (floor (sqrt (fromIntegral bigD))) label case_a3 "case_a3" comment "q_dot_prod, step 7: if (a3 > root Delta), then b3 <- b3 + (floor root Delta) - a3" b3 <- q_add_param_in_place (floor (sqrt (fromIntegral bigD))) b3 `controlled` case_a3 (a3,b3) <- q_sub_in_place a3 b3 `controlled` case_a3 return ((a1,a2,b1,b2),(khat,uhat,vhat),(k,x,w),(a1a2,b1b2,k_sq,t,case_a3,twice_a3),(a3,b3))) (\(inputs,temp1,(k,x,w),temp3,(a3,b3)) -> do comment "q_dot_prod, step 8: copy computed values into place for I3 = I1.I2" (a3,a3_out) <- qc_copy_fun a3 (b3,b3_out) <- qc_copy_fun b3 (k,k_out) <- qc_copy_fun k l_out <- qinit (intm n 1) label (k_out,l_out,a3_out,b3_out) "I3" comment "q_dot_prod: uncompute garbage." return ((inputs,temp1,(k,x,w),temp3,(a3,b3)) ,(k_out,l_out,a3_out,b3_out))) return (IdealRed bigD1 a1 b1, IdealRed bigD1 a2 b2, Ideal bigD1 k l a3 b3) -- | Compute the dot-product of two reduced fractional ideals, all with distance. q_dot_prod_with_dist :: IdRedDistQ -> IdRedDistQ -> Circ (IdRedDistQ, IdRedDistQ, IdDistQ) q_dot_prod_with_dist = box "q_dot_prod_with_dist" $ \(ii,dist_ii) (jj,dist_jj) -> do (ii, jj, ii_jj) <- q_dot_prod ii jj (dist_ii, dist_jj, dist_ii_jj) <- q_mult dist_ii dist_jj return ( (ii,dist_ii), (jj,dist_jj), (ii_jj,dist_ii_jj) ) -- | Given two reduced ideals-with-distance, compute their star-product, with distance. -- -- This is /I/*/J/ of [Jozsa 2003], Sec. 7.1, defined as the first reduced -- ideal-with-distance following /I/⋅/J/. q_star_prod :: IdRedDistQ -> IdRedDistQ -> Circ (IdRedDistQ, IdRedDistQ, IdRedDistQ) q_star_prod = box "q_star_prod" $ \iid jjd -> do let bigD = bigD_of_IdealRed $ fst iid ((iid,jjd), kkd_out) <- with_computed_fun (iid,jjd) (\(iid,jjd) -> do comment "q_star_prod, step 1: K <- 1/ka (I . J)" label (iid,jjd) (("I","δ(I)"),("J","δ(J)")) (iid,jjd,ii_jjd) <- q_dot_prod_with_dist iid jjd label (ii_jjd) ("II.JJ") (ii_jjd,kkd) <- q_normalize ii_jjd label (kkd) ("1/ka (II.JJ)") comment "q_star_prod, step 2: while K not reduced, set K <- rho(K)" (kkd_initial,kkd_reduced) <- q_bounded_while_with_garbage (\(kk,dist) -> do comment "q_star_prod, step 2, loop conditional: is K reduced yet?" (kk,c) <- q_is_reduced kk c <- qnot c return ((kk,dist),c)) ((ceiling $ (logBase 2 $ fromIntegral bigD) / 2) + 1) -- Generally, reduction may require log_2 (a/√D) steps, -- but here a is a_3 from the dot-product I.J, -- so a = a_3 = (a1 * a2) / k^2 ≤ a1 * a2; -- but now a1, a2 ≤ √D since they come from reduced ideals, -- so a ≤ √D * √D = D, and the bound simplifies. kkd (\kkd_old -> do comment "q_star_prod, step 2, loop body: compute ρ(Κ)" (kkd_old,kkd_new) <- q_rho_d kkd_old return (kkd_new,kkd_old)) let (ii_jj,dist_ij) = ii_jjd (kk_reduced,dist_k) = kkd_reduced comment "q_star_prod, step 2c: assert that K is now reduced." kk <- q_assert_reduced kk_reduced comment "q_star_prod, step 3: pull K backwards or forwards to be as close as possible to I.J" -- NB: implementation of the conditional + whiles could almost certainly be improved. (dist_k, dist_ij, k_lt_ij) <- q_lt dist_k dist_ij label k_lt_ij "Initially, δ(K) ≤ δ(I.J)?" let ii_jjd = (ii_jj,dist_ij) kkd = (kk,dist_k) comment "q_star_prod, step 3a: pull-forwards loop" ((dist_ij, kkd), (dij', kkd_forwards)) <- q_bounded_while_with_garbage (\(dist_ij,(kk,dist_k)) -> do comment "q_star_prod, step 3a, loop condition: is δ(K) ≤ δ(II.JJ) still?" (dist_k, dist_ij, k_lt_ij) <- q_lt dist_k dist_ij return ((dist_ij,(kk,dist_k)),k_lt_ij)) (ceiling $ 3 * (logBase 2 $ fromIntegral bigD) / 2) (dist_ij,kkd) (\(dij,kkd_old) -> do comment "q_star_prod, step 3a, loop body: compute ρ(Κ)" (kkd_old,kkd_new) <- q_rho_red_d kkd_old return ((dij,kkd_new),kkd_old)) comment "q_star_prod, step 3b: pull-backwards loop" ((dist_ij, kkd), (dij'', kkd_too_far_back)) <- q_bounded_while_with_garbage (\(dist_ij,(kk,dist_k)) -> do comment "q_star_prod, step 3b, loop condition: is δ(K) ≥ δ(II.JJ) still?" (dist_k, dist_ij, k_gt_ij) <- q_gt dist_k dist_ij return ((dist_ij,(kk,dist_k)),k_gt_ij)) (ceiling $ 3 * (logBase 2 $ fromIntegral bigD) / 2) (dist_ij,kkd) (\(dij,kkd_old) -> do comment "q_star_prod, step 3b, loop body: compute ρ^-1(Κ)" (kkd_old,kkd_new) <- q_rho_inv_red_d kkd_old return ((dij,kkd_new),kkd_old)) comment "q_star_prod, step 3b, cleanup: apply ρ once to the output of this loop" (kkd_too_far_back, kkd_back) <- q_rho_red_d kkd_too_far_back return ((iid, jjd, ii_jjd, kkd_initial, kkd, dij', dij'', kkd_too_far_back), k_lt_ij, kkd_forwards, kkd_back)) (\(stuff, k_lt_ij, kkd_forwards, kkd_back) -> do comment "q_star_prod, step 4: Return the result of either first or second loop, depending on test." kkd_out <- qinit $ qc_false kkd_forwards (kkd_out,kkd_forwards) <- controlled_not kkd_out kkd_forwards `controlled` k_lt_ij .==. True (kkd_out,kkd_backwards) <- controlled_not kkd_out kkd_back `controlled` k_lt_ij .==. False label kkd_out "kkd_out" return ((stuff, k_lt_ij, kkd_forwards, kkd_back),kkd_out)) return (iid, jjd, kkd_out) -- | Compute /I/ * /I/, where /I/ is a reduced ideal/distance pair. q_star_square :: IdRedDistQ -> Circ (IdRedDistQ, IdRedDistQ) q_star_square = \iid -> with_computed_fun iid qc_copy_fun (\(iid, iid_copy) -> do (iid, iid_copy, iid_square) <- q_star_prod iid iid_copy return ((iid, iid_copy), iid_square)) -- ====================================================================== -- * The function f[sub /N/] -- | @'q_fN' Δ /s/ /n/ /l/ /qi/ /j/@: find the minimal ideal-with-distance (/J/,δ[sub /J/]) such that δ[sub /J/] > /x/, where /x/ = /i/\//N/ + /j/\//L/, where /N/ = 2[sup /n/], /L/ = 2[sup /l/]. /qi/ is quantum; other inputs are classical parameters. Return (/i/,/J/,δ[sub /J/]–/x/). Work under the assumption that /R/ < 2[sup /s/]. -- -- This is the function /h/ of [Jozsa 2003], Sec. 9, discretized with precision 1\//N/ = 2[sup −/n/], -- and perturbed by the jitter parameter /j/\//L/. q_fN :: CLIntP -> Int -> Int -> QDInt -> IntM -> Circ (QDInt,(IdealRedQ,FPRealQ)) q_fN bigD n l qi j = do let p = precision_for_fN bigD n l nn = 2^n ll = 2^l q = qdint_length qi -- Need to figure out a bound /p/ on the precision of the real arithmetic required. -- It’s tempting to take /p/ = max(/n/,/l/); but I [pll] think we need larger, since if -- I understand correctly, we want the /final output/ with precision of 2^-n, which -- requires higher precision in intermediate calculations. (qi, (jj, diff)) <- with_computed_fun qi (\qi -> do comment "q_fN, step 1: Precompute x := i/N + j/L, as it used many times." qi <- return $ fprealx (-n) qi qj <- qinit (fprealx (-l) j) (qi,qj,qx) <- fprealq_add_het (-p) (q - n + p) qi qj label qx "x := i/N + j/L" comment "q_fN, step 2: J <- ρ^2(O)." oo <- qinit $ fix_sizes_IdealRed $ unit_idealRed bigD dist_o <- qinit $ (fprealx (-p) (intm (q - n + p) 0)) let ood = (oo,dist_o) label ood ("O", "δ_O = 0") (ood,jjd0) <- q_rho_red_d ood label jjd0 ("J0", "δ_J0)") (jjd0,jjd1) <- q_rho_red_d jjd0 label jjd1 ("J1", "δ_J1)") comment "q_fN, step 3: compute the iterated squares of (J1,δ_J1)." -- Note: quantumly, it is cheaper to compute them all unconditionally, rather than -- using a conditional loop that stops early, as one might classically. jjds <- loop_with_indexM (ceiling $ (fromIntegral q) * (log 2) / (nn * (snd $ rho_d $ rho_d $ (unit_ideal bigD, 0)))) [jjd1] (\i (jjd_prev:jjds_earlier) -> do (jjd_prev,jjd_new) <- q_star_square jjd_prev label jjd_new ("J_" ++ show (i+2), "δ_" ++ show (i+2)) return (jjd_new:jjd_prev:jjds_earlier)) comment "q_fN, step 4: compute the greatest product of these ≤ x" -- Again, it is quantumly cheaper to start at the maximum possible bound, instead of k = M. let jjd_star = ood label jjd_star ("J_*, δ_*") (qx, jjd_star, garbage) <- foldM (\(qx, jjd_star_old, garbage) jjd_k -> do (jjd_star_old, jjd_k, jjd_star_candidate) <- q_star_prod jjd_star_old jjd_k let (jj_star_candidate, dist_candidate) = jjd_star_candidate (dist_candidate, qx, test) <- q_lt dist_candidate qx let jjd_star_candidate = (jj_star_candidate, dist_candidate) jjd_star_new <- qinit (qc_false jjd_star_old) (jjd_star_new, jjd_star_candidate) <- controlled_not jjd_star_new jjd_star_candidate `controlled` test .==. True (jjd_star_new, jjd_star_old) <- controlled_not jjd_star_new jjd_star_old `controlled` test .==. False label jjd_star_new ("J_*, δ(J_*)") return (qx, jjd_star_new, (jjd_star_old,jjd_star_candidate,jjd_k,test):garbage)) (qx, jjd_star, []) jjds label jjd_star ("J_*, δ_*)") comment "q_fN: (J_*,δ_*) is now the greatest ideal/distance pair ≤ x constructible from the iterated star-squares (J_k,δ_k)." comment "q_fN, step 5: apply ρ^2 to (J_*,δ_*) as long as δ_* ≤ x." ((jjd_star_initial, qx), (jjd_star, qx_copy)) <- q_bounded_while_with_garbage -- conditional test: (\((jj_star, dist_star), qx) -> do (dist_star, qx, test) <- q_le dist_star qx return (((jj_star, dist_star), qx), test)) -- bound (ceiling $ 3 * logBase 2 (fromIntegral bigD) / 2) -- starting value (jjd_star, qx) -- body of loop (\(jjd_star_old, qx) -> do (jjd_star_old, rho_jjd_star_old) <- q_rho_red_d jjd_star_old (rho_jjd_star_old, jjd_star_new) <- q_rho_red_d rho_jjd_star_old return ((jjd_star_new, qx), (jjd_star_old, rho_jjd_star_old))) qx <- qc_uncopy_fun qx qx_copy comment "q_fN, step 6: apply ρ^{-1} once more if necessary." (jjd_star_candidate1, jjd_star_candidate2) <- q_rho_inv_red_d jjd_star let (jj_star_candidate1, dist_star_candidate1) = jjd_star_candidate1 (dist_star_candidate1, qx, final_test) <- q_le dist_star_candidate1 qx let jjd_star_candidate1 = (jj_star_candidate1, dist_star_candidate1) -- End of the computation part of the 'with_computed_fun'. -- Pass on everything we’ve constructed, with the relevant stuff put first. return (qx, jjd_star_candidate1, jjd_star_candidate2, final_test, (qi, qj, garbage, jjd0, jjd1, jjd_star_initial, jjd_star_initial))) (\(qx, jjd_star_candidate1, jjd_star_candidate2, test, irrelevant) -> do jjd_star_out <- qinit (qc_false jjd_star_candidate1) (jjd_star_out, jjd_star_candidate1) <- controlled_not jjd_star_out jjd_star_candidate1 `controlled` test .==. False (jjd_star_out, jjd_star_candidate1) <- controlled_not jjd_star_out jjd_star_candidate2 `controlled` test .==. True let (jj_out, dist_jj) = jjd_star_out (qx,diff_out) <- fprealq_sub_in_place qx dist_jj return ((qx, jjd_star_candidate1, jjd_star_candidate2, test, irrelevant), (jj_out, diff_out))) return (qi, (jj, diff))