diff --git a/README.md b/README.md
index 9b7e3b2826865dc537682ccf0acd66f9bfc6c7ee..e120b47f70aaa7ea7a4c238c1a999b61f1bf3188 100644
--- a/README.md
+++ b/README.md
@@ -39,7 +39,7 @@ The usage requires only four lines of code:
 ## Further options
 
 The behavior can be finely controlled by passing additional keyword arguments to the
-`gext.Extrapolator()` constructor. **Note: many options are not yet implemented.**
+`gext.Extrapolator()` constructor. **Note:** some options might be implemented in the future.
 
 This is an up to date list of available keyword options:
 
@@ -58,6 +58,6 @@ Some options can be piped to the fitting modules.
 
 This work is based on these papers:
 
-  1. F. Pes, È. Polack, P. Mazzeo, G. Dusson, B. Stamm, and F. Lipparini, “A Quasi Time-Reversible scheme based on density matrix extrapolation on the Grassmann manifold for Born-Oppenheimer Molecular Dynamics.” arXiv, 2023. doi: 10.48550/ARXIV.2307.05653.
+  1. F. Pes, É. Polack, P. Mazzeo, G. Dusson, B. Stamm, and F. Lipparini, “A Quasi Time-Reversible Scheme Based on Density Matrix Extrapolation on the Grassmann Manifold for Born–Oppenheimer Molecular Dynamics,” The Journal of Physical Chemistry Letters, vol. 14, no. 43. American Chemical Society (ACS), pp. 9720–9726, Oct. 25, 2023. doi: 10.1021/acs.jpclett.3c02098.
   2. É. Polack, G. Dusson, B. Stamm, and F. Lipparini, “Grassmann Extrapolation of Density Matrices for Born–Oppenheimer Molecular Dynamics,” Journal of Chemical Theory and Computation, vol. 17, no. 11. American Chemical Society (ACS), pp. 6965–6973, Oct. 08, 2021. doi: 10.1021/acs.jctc.1c00751. 
   3. É. Polack, A. Mikhalev, G. Dusson, B. Stamm, and F. Lipparini, “An approximation strategy to compute accurate initial density matrices for repeated self-consistent field calculations at different geometries,” Molecular Physics, vol. 118, no. 19–20. Informa UK Limited, p. e1779834, Jun. 22, 2020. doi: 10.1080/00268976.2020.1779834.
diff --git a/gext/fitting.py b/gext/fitting.py
index c72614289fc596063d53cf0ce0de13f56f15cadd..efd09f08e317ccd7e962b3dc7596ef2a9e1ab927 100644
--- a/gext/fitting.py
+++ b/gext/fitting.py
@@ -70,7 +70,7 @@ class LeastSquare(AbstractFitting):
 
 class QuasiTimeReversible(AbstractFitting):
 
-    """Quasi time reversible fitting scheme. Not yet implemented."""
+    """Quasi time reversible fitting scheme."""
 
     supported_options = {
         "regularization": 0.0,
@@ -85,7 +85,8 @@ class QuasiTimeReversible(AbstractFitting):
             raise ValueError("Unsupported value for regularization")
 
     def fit(self, vectors: List[np.ndarray], target: np.ndarray):
-        """Time reversible least square minimization fitting."""
+        """Given a set of vectors and a target return the fitting
+        coefficients in a quasi time reversible scheme."""
 
         past_target = vectors[0]
         matrix = np.array(vectors[1:]).T
diff --git a/gext/main.py b/gext/main.py
index 71de73a5488307de15cefb3360d7dc86c399f5fd..f1546f31afd2495d04a0214097222fba48e7c595 100644
--- a/gext/main.py
+++ b/gext/main.py
@@ -25,7 +25,8 @@ class Extrapolator:
 
     def __init__(self, nelectrons: int, nbasis: int, natoms: int, **kwargs):
 
-        if not (type(nelectrons) == int and type(nbasis) == int and type(natoms) == int):
+        if not (isinstance(nelectrons, int) and isinstance(nbasis, int) \
+                and isinstance(natoms, int)):
             raise ValueError("Dimensions are not integers")
 
         self.nelectrons = nelectrons
@@ -33,11 +34,13 @@ class Extrapolator:
         self.natoms = natoms
         self.set_options(**kwargs)
 
-        self.gammas = CircularBuffer(self.options["nsteps"], (self.nelectrons//2, self.nbasis))
+        self.gammas = CircularBuffer(self.options["nsteps"],
+            (self.nelectrons//2, self.nbasis))
         self.descriptors = CircularBuffer(self.options["nsteps"],
             ((self.natoms - 1)*self.natoms//2, ))
         if self.options["store_overlap"]:
-            self.overlaps = CircularBuffer(self.options["nsteps"], (self.nbasis, self.nbasis))
+            self.overlaps = CircularBuffer(self.options["nsteps"],
+                (self.nbasis, self.nbasis))
 
         self.tangent: Optional[np.ndarray] = None