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diff --git a/.doctrees/autoapi/blackjax/mcmc/integrators/index.doctree b/.doctrees/autoapi/blackjax/mcmc/integrators/index.doctree
diff --git a/.doctrees/autoapi/blackjax/util/index.doctree b/.doctrees/autoapi/blackjax/util/index.doctree
diff --git a/.doctrees/bib.doctree b/.doctrees/bib.doctree
diff --git a/.doctrees/environment.pickle b/.doctrees/environment.pickle
diff --git a/.doctrees/examples/howto_custom_gradients.doctree b/.doctrees/examples/howto_custom_gradients.doctree
diff --git a/.doctrees/examples/howto_metropolis_within_gibbs.doctree b/.doctrees/examples/howto_metropolis_within_gibbs.doctree
diff --git a/.doctrees/examples/howto_other_frameworks.doctree b/.doctrees/examples/howto_other_frameworks.doctree
diff --git a/.doctrees/examples/howto_sample_multiple_chains.doctree b/.doctrees/examples/howto_sample_multiple_chains.doctree
diff --git a/.doctrees/examples/howto_use_aesara.doctree b/.doctrees/examples/howto_use_aesara.doctree
diff --git a/.doctrees/examples/howto_use_numpyro.doctree b/.doctrees/examples/howto_use_numpyro.doctree
diff --git a/.doctrees/examples/howto_use_oryx.doctree b/.doctrees/examples/howto_use_oryx.doctree
diff --git a/.doctrees/examples/howto_use_pymc.doctree b/.doctrees/examples/howto_use_pymc.doctree
diff --git a/.doctrees/examples/howto_use_tfp.doctree b/.doctrees/examples/howto_use_tfp.doctree
diff --git a/.doctrees/examples/quickstart.doctree b/.doctrees/examples/quickstart.doctree
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diff --git a/_modules/blackjax/_version.html b/_modules/blackjax/_version.html
@@ -350,8 +350,8 @@ <h1>Source code for blackjax._version</h1><div class="highlight"><pre>
 <span class="n">__version_tuple__</span><span class="p">:</span> <span class="n">VERSION_TUPLE</span>
 <div class="viewcode-block" id="version_tuple"><a class="viewcode-back" href="../../autoapi/blackjax/_version/index.html#blackjax._version.version_tuple">[docs]</a><span class="n">version_tuple</span><span class="p">:</span> <span class="n">VERSION_TUPLE</span></div>
 
-<span class="n">__version__</span> <span class="o">=</span> <span class="n">version</span> <span class="o">=</span> <span class="s1">&#39;0.1.dev1+g16df9a6&#39;</span>
-<span class="n">__version_tuple__</span> <span class="o">=</span> <span class="n">version_tuple</span> <span class="o">=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;dev1&#39;</span><span class="p">,</span> <span class="s1">&#39;g16df9a6&#39;</span><span class="p">)</span>
+<span class="n">__version__</span> <span class="o">=</span> <span class="n">version</span> <span class="o">=</span> <span class="s1">&#39;0.1.dev1+ge0f107f&#39;</span>
+<span class="n">__version_tuple__</span> <span class="o">=</span> <span class="n">version_tuple</span> <span class="o">=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;dev1&#39;</span><span class="p">,</span> <span class="s1">&#39;ge0f107f&#39;</span><span class="p">)</span>
 </pre></div>
 
                 </article>

diff --git a/_modules/blackjax/mcmc/integrators.html b/_modules/blackjax/mcmc/integrators.html
diff --git a/_modules/blackjax/util.html b/_modules/blackjax/util.html
@@ -420,6 +420,28 @@ <h1>Source code for blackjax.util</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">unravel_fn</span><span class="p">(</span><span class="n">mu</span> <span class="o">+</span> <span class="n">linear_map</span><span class="p">(</span><span class="n">sigma</span><span class="p">,</span> <span class="n">sample</span><span class="p">))</span></div>
 
 
+<div class="viewcode-block" id="generate_unit_vector"><a class="viewcode-back" href="../../autoapi/blackjax/util/index.html#blackjax.util.generate_unit_vector">[docs]</a><span class="k">def</span> <span class="nf">generate_unit_vector</span><span class="p">(</span>
+    <span class="n">rng_key</span><span class="p">:</span> <span class="n">PRNGKey</span><span class="p">,</span>
+    <span class="n">position</span><span class="p">:</span> <span class="n">ArrayLikeTree</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Array</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate a random unit vector with output structure that match a given PyTree.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    rng_key:</span>
+<span class="sd">        The pseudo-random number generator key used to generate random numbers.</span>
+<span class="sd">    position:</span>
+<span class="sd">        PyTree that the structure the output should to match.</span>
+
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    Random unit vector that match the structure of position.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">p</span><span class="p">,</span> <span class="n">unravel_fn</span> <span class="o">=</span> <span class="n">ravel_pytree</span><span class="p">(</span><span class="n">position</span><span class="p">)</span>
+    <span class="n">sample</span> <span class="o">=</span> <span class="n">normal</span><span class="p">(</span><span class="n">rng_key</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">p</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">p</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">unravel_fn</span><span class="p">(</span><span class="n">sample</span> <span class="o">/</span> <span class="n">jnp</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="n">sample</span><span class="p">))</span></div>
+
+
 <div class="viewcode-block" id="pytree_size"><a class="viewcode-back" href="../../autoapi/blackjax/util/index.html#blackjax.util.pytree_size">[docs]</a><span class="k">def</span> <span class="nf">pytree_size</span><span class="p">(</span><span class="n">pytree</span><span class="p">:</span> <span class="n">ArrayLikeTree</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;Return the dimension of the flatten PyTree.&quot;&quot;&quot;</span>
     <span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">jnp</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> <span class="k">for</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">tree_leaves</span><span class="p">(</span><span class="n">pytree</span><span class="p">))</span></div>

diff --git a/_sources/autoapi/blackjax/mcmc/integrators/index.rst b/_sources/autoapi/blackjax/mcmc/integrators/index.rst
@@ -12,60 +12,41 @@
 Module Contents
 ---------------
 
-
-Functions
-~~~~~~~~~
-
-.. autoapisummary::
-
-   blackjax.mcmc.integrators.velocity_verlet
-   blackjax.mcmc.integrators.mclachlan
-   blackjax.mcmc.integrators.yoshida
-
-
-
-.. py:function:: velocity_verlet(logdensity_fn: Callable, kinetic_energy_fn: blackjax.mcmc.metrics.EuclideanKineticEnergy) -> Integrator
-
-   The velocity Verlet (or Verlet-Störmer) integrator.
-
-   The velocity Verlet is a two-stage palindromic integrator :cite:p:`bou2018geometric` of the form
-   (a1, b1, a2, b1, a1) with a1 = 0. It is numerically stable for values of
-   the step size that range between 0 and 2 (when the mass matrix is the
-   identity).
-
-   While the position (a1 = 0.5) and velocity Verlet are the most commonly used
-   in samplers, it is known in the numerical computation literature that the value
-   $a1 pprox 0.1932$ leads to a lower integration error :cite:p:`mclachlan1995numerical,schlick2010molecular`. The authors of :cite:p:`bou2018geometric`
-   show that the value $a1 pprox 0.21132$ leads to an even higher step acceptance
-   rate, up to 3 times higher than with the standard position verlet (p.22, Fig.4).
-
-   By choosing the velocity verlet we avoid two computations of the gradient
-   of the kinetic energy. We are trading accuracy in exchange, and it is not
-   clear whether this is the right tradeoff.
-
-
-
-.. py:function:: mclachlan(logdensity_fn: Callable, kinetic_energy_fn: Callable) -> Integrator
+.. py:data:: velocity_verlet
 
    Two-stage palindromic symplectic integrator derived in :cite:p:`blanes2014numerical`.
 
    The integrator is of the form (b1, a1, b2, a1, b1). The choice of the parameters
    determine both the bound on the integration error and the stability of the
    method with respect to the value of `step_size`. The values used here are
-   the ones derived in :cite:p:`mclachlan1995numerical`; note that :cite:p:`blanes2014numerical` is more focused on stability
-   and derives different values.
+   the ones derived in :cite:p:`mclachlan1995numerical`; note that :cite:p:`blanes2014numerical`
+   is more focused on stability and derives different values.
 
+   Also known as the minimal norm integrator.
 
-
-.. py:function:: yoshida(logdensity_fn: Callable, kinetic_energy_fn: Callable) -> Integrator
+.. py:data:: mclachlan
 
    Three stages palindromic symplectic integrator derived in :cite:p:`mclachlan1995numerical`
 
    The integrator is of the form (b1, a1, b2, a2, b2, a1, b1). The choice of
    the parameters determine both the bound on the integration error and the
    stability of the method with respect to the value of `step_size`. The
-   values used here are the ones derived in :cite:p:`mclachlan1995numerical` which guarantees a stability
-   interval length approximately equal to 4.67.
+   values used here are the ones derived in :cite:p:`mclachlan1995numerical` which
+   guarantees a stability interval length approximately equal to 4.67.
+
+.. py:data:: yoshida
+
+   
+
+.. py:data:: noneuclidean_leapfrog
+
+   
+
+.. py:data:: noneuclidean_mclachlan
+
+   
 
+.. py:data:: noneuclidean_yoshida
 
+   
 
diff --git a/_sources/autoapi/blackjax/util/index.rst b/_sources/autoapi/blackjax/util/index.rst
@@ -22,6 +22,7 @@ Functions
 
    blackjax.util.linear_map
    blackjax.util.generate_gaussian_noise
+   blackjax.util.generate_unit_vector
    blackjax.util.pytree_size
    blackjax.util.index_pytree
 
@@ -63,6 +64,16 @@ Functions
    :rtype: Gaussian noise following N(mu, sigma) that match the structure of position.
 
 
+.. py:function:: generate_unit_vector(rng_key: blackjax.types.PRNGKey, position: blackjax.types.ArrayLikeTree) -> blackjax.types.Array
+
+   Generate a random unit vector with output structure that match a given PyTree.
+
+   :param rng_key: The pseudo-random number generator key used to generate random numbers.
+   :param position: PyTree that the structure the output should to match.
+
+   :rtype: Random unit vector that match the structure of position.
+
+
 .. py:function:: pytree_size(pytree: blackjax.types.ArrayLikeTree) -> int
 
    Return the dimension of the flatten PyTree.