paranoia fixes

nifty5/library/smooth_linear_amplitude.py

@@ -43,7 +43,7 @@ def CepstrumOperator(target, a, k0):
     and ceps is the so-called cepstrum:
 
     .. math::
-        \\mathrm{sqrt\_ceps}(k) = \\frac{a}{1+(k/k0)^2}
+        \\mathrm{sqrt\\_ceps}(k) = \\frac{a}{1+(k/k0)^2}
 
     These operators are combined in this fashion in order to generate:
 

nifty5/operators/energy_operators.py

@@ -325,7 +325,7 @@ class AveragedEnergy(EnergyOperator):
     drawn from the approximating Gaussian:
 
     .. math ::
-        \\text{KL}(m) = \\frac1{\\#\{v_i\}} \\sum_{v_i} H(m+v_i),
+        \\text{KL}(m) = \\frac1{\\#\\{v_i\\}} \\sum_{v_i} H(m+v_i),
 
     where :math:`v_i` are the residual samples and :math:`m` is the mean field
     around which the samples are drawn.

nifty5/probing.py

@@ -111,7 +111,7 @@ def probe_diagonal(op, nprobes, random_type="pm1"):
 
     The operator is called on a user-specified number of randomly generated
     input vectors :math:`v_i`, producing :math:`r_i`. The estimated diagonal
-    is the mean of :math:`r_i^\dagger v_i`.
+    is the mean of :math:`r_i^\\dagger v_i`.
 
     Parameters
     ----------