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Found 8 papers, 5 papers with code
Quantum compression with classically simulatable circuits
As we continue to find applications where the currently available noisy devices exhibit an advantage over their classical counterparts, the efficient use of quantum resources is highly desirable.
Noisy intermediate-scale quantum (NISQ) algorithms
We additionally provide a comprehensive overview of various benchmarking and software tools useful for programming and testing NISQ devices.
A Feasible Approach for Automatically Differentiable Unitary Coupled-Cluster on Quantum Computers
We show that, within our framework, the gradient of an expectation value with respect to a parameterized n-fold fermionic excitation can be evaluated by four expectation values of similar form and size, whereas most standard approaches based on the direct application of the parameter-shift-rule come with an associated cost of O(2^(2n)) expectation values.
Quantum Physics Chemical Physics Computational Physics
Tequila: A platform for rapid development of quantum algorithms
As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in high demand for flexible and reliable ways to implement, test, and share new ideas.
Quantum Physics Chemical Physics Computational Physics
The Meta-Variational Quantum Eigensolver (Meta-VQE): Learning energy profiles of parameterized Hamiltonians for quantum simulation
We present the meta-VQE, an algorithm capable to learn the ground state energy profile of a parametrized Hamiltonian.
Quantum Physics
Reducing qubit requirements while maintaining numerical precision for the Variational Quantum Eigensolver: A Basis-Set-Free Approach
We present a basis-set-free approach to the variational quantum eigensolver using an adaptive representation of the spatial part of molecular wavefunctions.
Quantum Physics Chemical Physics Computational Physics
Quantum Computer-Aided design of Quantum Optics Hardware
It is not clear how the full potential of large quantum systems can be exploited.
Quantum Physics Computational Physics Optics
MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation
MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision based on multiresolution analysis and separated representations.
Mathematical Software Computational Engineering, Finance, and Science Numerical Analysis
