code: def chimera_elimination_order(m, n=None, t=None):
      
      if n is None:
          n = m
  
      if t is None:
          t = 4
  
      index_flip = m > n
      if index_flip:
          m, n = n, m
  
      def chimeraI(m0, n0, k0, l0):
          if index_flip:
              return m*2*t*n0 + 2*t*m0 + t*(1-k0) + l0
          else:
              return n*2*t*m0 + 2*t*n0 + t*k0 + l0
  
      order = []
  
      for n_i in range(n):
          for t_i in range(t):
              for m_i in range(m):
                  order.append(chimeraI(m_i, n_i, 0, t_i))
  
      for n_i in range(n):
          for m_i in range(m):
              for t_i in range(t):
                  order.append(chimeraI(m_i, n_i, 1, t_i))
  
      return order
docs: Provides a variable elimination order for a Chimera graph.
  
      A graph defined by chimera_graph(m,n,t) has treewidth max(m,n)*t.
      This function outputs a variable elimination order inducing a tree
      decomposition of that width.
  
      Parameters
      ----------
      m : int
          Number of rows in the Chimera lattice.
      n : int (optional, default m)
          Number of columns in the Chimera lattice.
      t : int (optional, default 4)
          Size of the shore within each Chimera tile.
  
  
      Returns
      -------
      order : list
          An elimination order that induces the treewidth of chimera_graph(m,n,t).
  
      Examples
      --------
      >>> G = dnx.chimera_elimination_order(1, 1, 4)  # a single Chimera tile