Subspace Diagonalization on Quantum Computers using Eigenvector Continuation

Quantum subspace diagonalization (QSD) methods are quantum-classical hybrid
methods, commonly used to find ground and excited state energies by projecting
the Hamiltonian to a smaller subspace. In app ...

Symmetry breaking/symmetry preserving circuits and symmetry restoration on quantum computers: A quantum many-body perspective

We discuss here some aspects related to symmetries of a quantum many-body
problem when trying to treat it on a quantum computer. Several features related
to symmetry conservation, symmetry breaking an ...

Symmetry enhanced variational quantum eigensolver

The variational quantum-classical algorithms are the most promising approach
for achieving quantum advantage on near-term quantum simulators. Among these
methods, the variational quantum eigensolver h ...

Quantum Algorithms for Ground-State Preparation and Green's Function Calculation

We propose quantum algorithms for projective ground-state preparation and
calculations of the many-body Green's functions directly in frequency domain.
The algorithms are based on the linear combinati ...

Quantum Krylov subspace algorithms for ground and excited state energy estimation

Quantum Krylov subspace diagonalization (QKSD) algorithms provide a low-cost
alternative to the conventional quantum phase estimation algorithm for
estimating the ground and excited-state energies of ...

Many-Body Quantum States with Exact Conservation of Non-Abelian and Lattice Symmetries through Variational Monte Carlo

Optimization of quantum states using the variational principle has recently
seen an upsurge due to developments of increasingly expressive wave functions.
In order to improve on the accuracy of the an ...

Predicting ground state, excited states and long-time evolution of many-body systems from short-time evolution on a quantum computer

The generating function of a Hamiltonian $H$ is defined as $F(t)=\langle
e^{-itH}\rangle$, where $t$ is the time and where the expectation value is
taken on a given initial quantum state. This functio ...

Simulating Many-Body Systems with a Projective Quantum Eigensolver

We present a new hybrid quantum-classical algorithm for optimizing unitary
coupled-cluster (UCC) wave functions deemed the projective quantum eigensolver
(PQE), amenable to near-term noisy quantum har ...

Quantum Assisted Eigensolver

We propose a hybrid quantum-classical algorithm for approximating the ground
state and ground state energy of a Hamiltonian. Once the Ansatz has been
decided, the quantum part of the algorithm involve ...

Quantifying the efficiency of state preparation via quantum variational eigensolvers

Recently, there has been much interest in the efficient preparation of complex quantum states using low-depth quantum circuits, such as Quantum Approximate Optimization Algorithm (QAOA). While it has ...