Related references
Note: Only part of the references are listed.Fisher Information in Noisy Intermediate-Scale Quantum Applications
Johannes Jakob Meyer
QUANTUM (2021)
Measuring Analytic Gradients of General Quantum Evolution with the Stochastic Parameter Shift Rule
Leonardo Banchi et al.
QUANTUM (2021)
Local, expressive, quantum-number-preserving VQE ansatze for fermionic systems
Gian-Luca R. Anselmetti et al.
NEW JOURNAL OF PHYSICS (2021)
Quantum circuits with many photons on a programmable nanophotonic chip
J. M. Arrazola et al.
NATURE (2021)
Quantum approximate optimization of non-planar graph problems on a planar superconducting processor
Matthew P. Harrigan et al.
NATURE PHYSICS (2021)
Structure optimization for parameterized quantum circuits
Mateusz Ostaszewski et al.
QUANTUM (2021)
Analytic gradients in variational quantum algorithms: Algebraic extensions of the parameter-shift rule to general unitary transformations
Artur F. Izmaylov et al.
PHYSICAL REVIEW A (2021)
Generalized quantum circuit differentiation rules
Oleksandr Kyriienko et al.
PHYSICAL REVIEW A (2021)
Variational quantum algorithm for molecular geometry optimization
Alain Delgado et al.
PHYSICAL REVIEW A (2021)
Variational quantum algorithms
M. Cerezo et al.
NATURE REVIEWS PHYSICS (2021)
Hardware-efficient variational quantum algorithms for time evolution
Marcello Benedetti et al.
PHYSICAL REVIEW RESEARCH (2021)
Universal discriminative quantum neural networks
H. Chen et al.
QUANTUM MACHINE INTELLIGENCE (2021)
Layerwise learning for quantum neural networks
Andrea Skolik et al.
QUANTUM MACHINE INTELLIGENCE (2021)
Effect of data encoding on the expressive power of variational quantum-machine-learning models
Maria Schuld et al.
PHYSICAL REVIEW A (2021)
Abrupt transitions in variational quantum circuit training
Ernesto Campos et al.
PHYSICAL REVIEW A (2021)
A feasible approach for automatically differentiable unitary coupled-cluster on quantum computers
Jakob S. Kottmann et al.
CHEMICAL SCIENCE (2021)
Estimating the gradient and higher-order derivatives on quantum hardware
Andrea Mari et al.
PHYSICAL REVIEW A (2021)
Input Redundancy for Parameterized Quantum Circuits
Francisco Javier Gil Vidal et al.
FRONTIERS IN PHYSICS (2020)
Quantum Approximate Optimization Algorithm: Performance, Mechanism, and Implementation on Near-Term Devices
Leo Zhou et al.
PHYSICAL REVIEW X (2020)
On the universality of the quantum approximate optimization algorithm
M. E. S. Morales et al.
QUANTUM INFORMATION PROCESSING (2020)
Stochastic gradient descent for hybrid quantum-classical optimization
Ryan Sweke et al.
QUANTUM (2020)
Transfer learning in hybrid classical-quantum neural networks
Andrea Mari et al.
QUANTUM (2020)
Avoiding local minima in variational quantum eigensolvers with the natural gradient optimizer
David Wierichs et al.
PHYSICAL REVIEW RESEARCH (2020)
Sequential minimal optimization for quantum-classical hybrid algorithms
Ken M. Nakanishi et al.
PHYSICAL REVIEW RESEARCH (2020)
Supervised learning with quantum-enhanced feature spaces
Vojtech Havlicek et al.
NATURE (2019)
Quantum Machine Learning in Feature Hilbert Spaces
Maria Schuld et al.
PHYSICAL REVIEW LETTERS (2019)
An adaptive variational algorithm for exact molecular simulations on a quantum computer
Harper R. Grimsley et al.
NATURE COMMUNICATIONS (2019)
Variational quantum state diagonalization
Ryan LaRose et al.
NPJ QUANTUM INFORMATION (2019)
Quantum optical neural networks
Gregory R. Steinbrecher et al.
NPJ QUANTUM INFORMATION (2019)
Variational ansatz-based quantum simulation of imaginary time evolution
Sam McArdle et al.
NPJ QUANTUM INFORMATION (2019)
Parameterized quantum circuits as machine learning models
Marcello Benedetti et al.
QUANTUM SCIENCE AND TECHNOLOGY (2019)
Efficient variational simulation of non-trivial quantum states
Wen Wei Ho et al.
SCIPOST PHYSICS (2019)
Continuous-variable quantum neural networks
Nathan Killoran et al.
PHYSICAL REVIEW RESEARCH (2019)
Subspace-search variational quantum eigensolver for excited states
Ken M. Nakanishi et al.
PHYSICAL REVIEW RESEARCH (2019)
Variational quantum algorithms for discovering Hamiltonian spectra
Tyson Jones et al.
PHYSICAL REVIEW A (2019)
Quantum-assisted quantum compiling
Sumeet Khatri et al.
QUANTUM (2019)
Methodology for replacing indirect measurements with direct measurements
Kosuke Mitarai et al.
PHYSICAL REVIEW RESEARCH (2019)
Evaluating analytic gradients on quantum hardware
Maria Schuld et al.
PHYSICAL REVIEW A (2019)
Hierarchical quantum classifiers
Edward Grant et al.
NPJ QUANTUM INFORMATION (2018)
Differentiable learning of quantum circuit Born machines
Jin-Guo Liu et al.
PHYSICAL REVIEW A (2018)
Quantum approximate optimization algorithm for MaxCut: A fermionic view
Zhihui Wang et al.
PHYSICAL REVIEW A (2018)
Hybrid Quantum-Classical Approach to Quantum Optimal Control
Jun Li et al.
PHYSICAL REVIEW LETTERS (2017)
Efficient Variational Quantum Simulator Incorporating Active Error Minimization
Ying Li et al.
PHYSICAL REVIEW X (2017)
Quantum autoencoders for efficient compression of quantum data
Jonathan Romero et al.
QUANTUM SCIENCE AND TECHNOLOGY (2017)
A variational eigenvalue solver on a photonic quantum processor
Alberto Peruzzo et al.
NATURE COMMUNICATIONS (2014)
Automated conjectures on upper bounds for the largest Laplacian eigenvalue of graphs
V Brankov et al.
LINEAR ALGEBRA AND ITS APPLICATIONS (2006)
A tight semidefinite relaxation of the MAX CUT problem
HW Liu et al.
JOURNAL OF COMBINATORIAL OPTIMIZATION (2003)
Geometry of semidefinite Max-Cut relaxations via matrix ranks
MF Anjos et al.
JOURNAL OF COMBINATORIAL OPTIMIZATION (2002)