diff --git a/prob_laplace.m b/prob_laplace.m
index 86581027b46ae4d9a225257c1e91db4138e6615c..2f62d8585b42aabf03257b30b22bfd90076f10c8 100644
--- a/prob_laplace.m
+++ b/prob_laplace.m
@@ -240,32 +240,70 @@ params = {-5, b(7.7/3, 10^-6), 0.5, e(7.7/3), 'const', 0.5, 10, 7, 0,...
 t = [0, 0.05, 0.1];
 direc = 1;
 bp = [3, 5, 7];
+
 for j = 1:length(bp)
-x0 = sort(bp(j)-direc*(0:0.001:3.02));
-% Run simulations for 'delta' IC across outside
-T = {};
-parfor i = 1:length(x0)
+    x0 = sort(bp(j)-direc*(0:0.001:3.02));
+    % Run simulations for 'delta' IC across outside
+    T = {};
+    parfor i = 1:length(x0)
+        tic
+        T{i} = Ternary_model(0, 'Gauss', [params(1:7), {x0(i)},...
+                                          params(9:end)], t, 0.2);
+        T{i}.solve_tern_frap();
+        toc
+    end
+    % Calculate probabilities for each jump length in ls.
+    l_max = 3;
+    t_ind = 3;
+    ls = -direc*(0.000:0.005:l_max);
+    p = nan(1, length(ls));
     tic
-    T{i} = Ternary_model(0, 'Gauss', [params(1:7), {x0(i)}, params(9:end)], t, 0.2);
-    T{i}.solve_tern_frap();
+    parfor i = 1:length(ls)
+        tic
+        p(i) = int_prob(ls(i), T, x0, direc, t_ind, bp(j), 0, 0);
+        toc
+    end
     toc
+    save(['prob_7_7_bp', num2str(bp(j))]);
+    pa = '/Users/hubatsch/Nextcloud/Langevin_vs_MeanField/data/constD/';
+    csvwrite([pa, 'jump_length_7_7_bp', num2str(bp(j)), '.csv'], ls)
+    csvwrite([pa, 'prob_7_7_bp', num2str(bp(j)), '.csv'], p);
 end
-% Calculate probabilities for each jump length in ls.
-l_max = 3;
-t_ind = 3;
-ls = -direc*(0.000:0.005:l_max);
-p = nan(1, length(ls));
-tic
-parfor i = 1:length(ls)
+
+%% Now for d = 0.5 across the entire domain bp=0, lb=0.02
+params = {-5, b(7.7/3, 10^-6), 0.5, e(7.7/3), 'const', 0.5, 10, 7, 0,...
+          'Constituent', 0};
+t = [0, 0.05, 0.1];
+direc = 1;
+bp = [3, 5, 7];
+
+for j = 1:length(bp)
+    x0 = sort(bp(j)-direc*(0:0.001:3.02));
+    % Run simulations for 'delta' IC across outside
+    T = {};
+    parfor i = 1:length(x0)
+        tic
+        T{i} = Ternary_model(0, 'Gauss', [params(1:7), {x0(i)},...
+                                          params(9:end)], t, 0.2);
+        T{i}.solve_tern_frap();
+        toc
+    end
+    % Calculate probabilities for each jump length in ls.
+    l_max = 3;
+    t_ind = 3;
+    ls = -direc*(0.000:0.005:l_max);
+    p = nan(1, length(ls));
     tic
-    p(i) = int_prob(ls(i), T, x0, direc, t_ind, bp(j), 0);
+    parfor i = 1:length(ls)
+        tic
+        p(i) = int_prob(ls(i), T, x0, direc, t_ind, bp(j), 0, 0.02);
+        toc
+    end
     toc
-end
-toc
-save(['prob_7_7_bp', num2str(bp(j))]);
-pa = '/Users/hubatsch/Nextcloud/Langevin_vs_MeanField/data/constD/';
-csvwrite([pa, 'jump_length_7_7_bp', num2str(bp(j)), '.csv'], ls)
-csvwrite([pa, 'prob_7_7_bp', num2str(bp(j)), '.csv'], p);
+    save(['prob_7_7_lb002_bp', num2str(bp(j))]);
+    pa = '/Users/hubatsch/Nextcloud/Langevin_vs_MeanField/data/constD/';
+    csvwrite([pa, 'jump_length_7_7_lb002_bp', num2str(bp(j)), '.csv'], ls)
+    csvwrite([pa, 'prob_7_7_lb002_bp', num2str(bp(j)), '.csv'], p);
 end
 %% Mean cross jump length chi 7/3
 run_jump_lengths(-5, 1, 7/3, 1, 4, '73_1_01', 10^-6, 3, 0.5);