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Quantum supremacy using a programmable superconducting processor
Quantum supremacy is demonstrated using a programmable superconducting processor known as Sycamore, taking approximately 200 seconds to sample one instance of a quantum circuit a million times, which would take a state-of-the-art supercomputer around ten thousand years to compute.
Bayesian Sampling Using Stochastic Gradient Thermostats
This work shows that one can leverage a small number of additional variables to stabilize momentum fluctuations induced by the unknown noise inynamics-based sampling methods.
Characterizing quantum supremacy in near-term devices
A critical question for quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of
Scalable Quantum Simulation of Molecular Energies
We report the first electronic structure calculation performed on a quantum computer without exponentially costly precompilation. We use a programmable array of superconducting qubits to compute the
Barren plateaus in quantum neural network training landscapes
It is shown that for a wide class of reasonable parameterized quantum circuits, the probability that the gradient along any reasonable direction is non-zero to some fixed precision is exponentially small as a function of the number of qubits.
Encoding Electronic Spectra in Quantum Circuits with Linear T Complexity
We construct quantum circuits which exactly encode the spectra of correlated electron models up to errors from rotation synthesis. By invoking these circuits as oracles within the recently introduced
What is the Computational Value of Finite Range Tunneling
It is demonstrated how finite range tunneling can provide considerable computational advantage over classical processors for a crafted problem designed to have tall and narrow energy barriers separating local minima, the D-Wave 2X quantum annealer achieves significant runtime advantages relative to Simulated Annealing.
OpenFermion: the electronic structure package for quantum computers
The key motivations behind design choices in OpenFermion are outlined and some basic OpenFermanion functionality is discussed which are believed to aid the community in the development of better quantum algorithms and tools for this exciting area of research.
Quantum approximate optimization of non-planar graph problems on a planar superconducting processor
The application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA) is demonstrated and an approximation ratio is obtained that is independent of problem size and for the first time, that performance increases with circuit depth.
The theory of variational hybrid quantum-classical algorithms
This work develops a variational adiabatic ansatz and explores unitary coupled cluster where it is shown how the use of modern derivative free optimization techniques can offer dramatic computational savings of up to three orders of magnitude over previously used optimization techniques.