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Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
The experimental optimization of Hamiltonian problems with up to six qubits and more than one hundred Pauli terms is demonstrated, determining the ground-state energy for molecules of increasing size, up to BeH2.
Tapering off qubits to simulate fermionic Hamiltonians
It is shown that encodings with a given filling fraction $\nu=N/M$ and a qubit-per-mode ratio $\eta=Q/M<1$ can be constructed from efficiently decodable classical LDPC codes with the relative distance $2\nu$ and the encoding rate $1-\eta$.
Quantum optimization using variational algorithms on near-term quantum devices
The quantum volume as a metric to compare the power of near-term quantum devices is discussed and simple error-mitigation schemes are introduced that could improve the accuracy of determining ground-state energies.
Error mitigation extends the computational reach of a noisy quantum processor
This work applies the error mitigation protocol to mitigate errors in canonical single- and two-qubit experiments and extends its application to the variational optimization of Hamiltonians for quantum chemistry and magnetism.
Digitized adiabatic quantum computing with a superconducting circuit.
The demonstration of digitized adiabatic quantum computing in the solid state opens a path to synthesizing long-range correlations and solving complex computational problems.
Digital quantum simulation of spin models with circuit quantum electrodynamics
Systems of interacting quantum spins show a rich spectrum of quantum phases and display interesting many-body dynamics. Computing characteristics of even small systems on conventional computers poses
Quantum algorithms for electronic structure calculations: Particle-hole Hamiltonian and optimized wave-function expansions
In this work we investigate methods to improve the efficiency and scalability of quantum algorithms for quantum chemistry applications. We propose a transformation of the electronic structure
Universal Gate for Fixed-Frequency Qubits via a Tunable Bus
The authors address a critical scalability issue in quantum computer design by activating a resonant exchange interaction. They achieve this by coupling two fixed-frequency superconducting qubits
From transistor to trapped-ion computers for quantum chemistry
This work presents an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling.
Fermionic neural-network states for ab-initio electronic structure
An extension of neural-network quantum states to model interacting fermionic problems and use neural-networks to perform electronic structure calculations on model diatomic molecules to achieve chemical accuracy.