diff --git a/benchmarks/zdc_pi0/analysis/zdc_pi0_plots.py b/benchmarks/zdc_pi0/analysis/zdc_pi0_plots.py
index c2b4acff..92973109 100644
--- a/benchmarks/zdc_pi0/analysis/zdc_pi0_plots.py
+++ b/benchmarks/zdc_pi0/analysis/zdc_pi0_plots.py
@@ -44,7 +44,7 @@ def gauss(x, A,mu, sigma):
     if len(Etot)<25:
         continue
     #print(p, res, mrecon)
-    if p==100:
+    if p==60:
         plt.sca(axs[0])
         y, x, _=plt.hist(Etot, bins=100, range=(p*.5, p*1.5), histtype='step')
         plt.ylabel("events")
@@ -61,7 +61,7 @@ def gauss(x, A,mu, sigma):
     #print(list(y), list(x))
     coeff, var_matrix = curve_fit(fnc, list(bc[slc]), list(y[slc]), p0=p0,
                                  sigma=list(np.sqrt(y[slc])+(y[slc]==0)), maxfev=10000)
-    if p==100:
+    if p==60:
         xx=np.linspace(p*0.5,p*1.5, 100)
         plt.plot(xx, fnc(xx,*coeff))
     pvals.append(p)
@@ -120,7 +120,7 @@ def gauss(x, A,mu, sigma):
     
     Etot=np.sum(E, axis=-1)
     #print(p, res, mrecon)
-    if p==100:
+    if p==60:
         plt.sca(axs[0])
         y, x, _=plt.hist(1000*(theta_recon-theta_truth), bins=100, range=(-0.5, 0.5), histtype='step')
         plt.ylabel("events")
@@ -137,7 +137,7 @@ def gauss(x, A,mu, sigma):
     #print(list(y), list(x))
     coeff, var_matrix = curve_fit(fnc, list(bc[slc]), list(y[slc]), p0=p0,
                                  sigma=list(np.sqrt(y[slc])+(y[slc]==0)), maxfev=10000)
-    if p==100:
+    if p==60:
         xx=np.linspace(-0.5,0.5, 100)
         plt.plot(xx, fnc(xx,*coeff))
     pvals.append(p)
@@ -187,11 +187,11 @@ def gauss(x, A,mu, sigma):
         continue
     
     #print(p, res, mrecon)
-    if p==100:
+    if p==60:
         plt.sca(axs[0])
         y, x, _=plt.hist(mrecon, bins=100, range=(0, 0.2), histtype='step')
         plt.ylabel("events")
-        plt.title(f"$p_{{\pi^0}}$={p} GeV")
+        plt.title(f"$p_{{\\pi^0}}$={p} GeV")
         plt.xlabel("$m^{\\pi^{0}}_{recon}$ [GeV]")
     else:
         #y, x, _=plt.hist(mrecon, bins=100, range=(0, 0.2), histtype='step')#y, x =np.histogram(mrecon, bins=100, range=(0, 0.2))
@@ -201,11 +201,11 @@ def gauss(x, A,mu, sigma):
     from scipy.optimize import curve_fit
     slc=abs(bc-.135)<.1
     fnc=gauss
-    p0=[100, .135, 0.2]
+    p0=[60, .135, 0.2]
     #print(list(y), list(x))
     coeff, var_matrix = curve_fit(fnc, list(bc[slc]), list(y[slc]), p0=p0,
                                  sigma=list(np.sqrt(y[slc])+(y[slc]==0)), maxfev=10000)
-    if p==100:
+    if p==60:
         xx=np.linspace(0,0.2)
         plt.plot(xx, fnc(xx,*coeff))
     pvals.append(p)
@@ -224,7 +224,7 @@ def gauss(x, A,mu, sigma):
                                  sigma=dresvals, maxfev=10000)
 xx=np.linspace(55, 200, 100)
 #plt.plot(xx, fnc(xx, *coeff), label=f'fit:  ${coeff[0]*1000:.1f}+{coeff[1]*1000:.4f}\\times E$ MeV')
-plt.plot(xx, fnc(xx, *coeff), label=f'fit:  $({coeff[0]*1000:.1f}+{coeff[1]*1000:.4f}\\times [E\,in\,GeV])$ MeV')
+plt.plot(xx, fnc(xx, *coeff), label=f'fit:  $({coeff[0]*1000:.1f}+{coeff[1]*1000:.4f}\\times [E\\,in\\,GeV])$ MeV')
 plt.legend()