Update description of chemistry ansatz on landing pages (#159) (#160)

(cherry picked from commit f28bbc0)

Co-authored-by: Caleb Johnson <caleb.johnson@ibm.com>

README.md

@@ -37,7 +37,7 @@ SQD-based workflows involve first preparing one or more quantum states on a quan
 
 SQD can be used in various ways in practice. For example, we can use two categories of quantum circuits to sample from:
 
-  1. A single ansatz is prepared that is believed to be a good representation of an eigenstate (e.g., ground state) of the target Hamiltonian. This is appealing for chemistry applications where Hamiltonians can have millions of interaction terms [1]. For an example of this approach applied to chemistry see the [tutorial for approximating the ground state energy of the N2 molecule](https://qiskit.github.io/qiskit-addon-sqd/tutorials/01_chemistry_hamiltonian.html).
+  1. A variational circuit ansatz with parameters chosen such that sampling the circuit produces electronic configurations on which the target wavefunction (i.e., the ground state) has significant support. This is appealing for chemistry applications where Hamiltonians can have millions of interaction terms [1]. For an example of this approach applied to chemistry see the [tutorial for approximating the ground state energy of the N2 molecule](https://qiskit.github.io/qiskit-addon-sqd/tutorials/01_chemistry_hamiltonian.html).
 
   2. A set of Krylov basis states are prepared over increasing time intervals. Assuming a good initial state and sparsity of the ground state, this approach is proven to converge efficiently. As one needs to prepare Trotterized time evolution circuits on a quantum device, this approach is best for applications to lattice models [2]. For an example of this approach applied to Fermionic lattice Hamiltonians, see the [tutorial for approximating the ground state energy of a simplified single-impurity Anderson model](https://qiskit.github.io/qiskit-addon-sqd/tutorials/02_fermionic_lattice_hamiltonian.html).
 

docs/index.rst

@@ -10,7 +10,7 @@ SQD-based workflows involve first preparing one or more quantum states on a quan
 
 SQD can be used in various ways in practice. For example, we can use two categories of quantum circuits to sample from:
 
-    1. A single ansatz is prepared that is believed to be a good representation of an eigenstate (e.g., ground state) of the target Hamiltonian. This is appealing for chemistry applications where Hamiltonians can have millions of interaction terms [1]. For an example of this approach applied to chemistry see the `tutorial for approximating the ground state energy of the N2 molecule <https://qiskit.github.io/qiskit-addon-sqd/tutorials/01_chemistry_hamiltonian.html>`_.
+    1. A variational circuit ansatz with parameters chosen such that sampling the circuit produces electronic configurations on which the target wavefunction (i.e., the ground state) has significant support. This is appealing for chemistry applications where Hamiltonians can have millions of interaction terms [1]. For an example of this approach applied to chemistry see the `tutorial for approximating the ground state energy of the N2 molecule <https://qiskit.github.io/qiskit-addon-sqd/tutorials/01_chemistry_hamiltonian.html>`_.
 
     2. A set of Krylov basis states are prepared over increasing time intervals. Assuming a good initial state and sparsity of the ground state, this approach is proven to converge efficiently. As one needs to prepare Trotterized time evolution circuits on a quantum device, this approach is best for applications to lattice models [2]. For an example of this approach applied to Fermionic lattice Hamiltonians, see the `tutorial for approximating the ground state energy of a simplified single-impurity Anderson model <https://qiskit.github.io/qiskit-addon-sqd/tutorials/02_fermionic_lattice_hamiltonian.html>`_.