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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def step(self, x):
 r"""perform a single Brownian dynamics step"""

        return x - self.coeff_A * self.gradient(x) \
               + self.coeff_B * np.random.normal(size=self.dim)