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Variational Quantum Algorithms
TLDR
An overview of the field of Variational Quantum Algorithms is presented and strategies to overcome their challenges as well as the exciting prospects for using them as a means to obtain quantum advantage are discussed. Expand
Cost function dependent barren plateaus in shallow parametrized quantum circuits
TLDR
This work rigorously proves two results, assuming V(θ) is an alternating layered ansatz composed of blocks forming local 2-designs, that establish a connection between locality and trainability. Expand
Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks
TLDR
Two results are rigorously proved that establish a connection between locality and trainability in VQAs and illustrate these ideas with large-scale simulations of a particular VQA known as quantum autoencoders. Expand
Variational Quantum Linear Solver: A Hybrid Algorithm for Linear Systems
TLDR
This paper presents a parallel version of the Celada–Seiden cellular automaton that simulates the dynamic response of the immune system tozman, a type of “spatially aggregating” disease. Expand
Noise resilience of variational quantum compiling
TLDR
A surprising form of noise resilience for variational hybrid quantum-classical algorithms is reported, finding one often learns the correct gate sequence $V$ despite various sources of incoherent noise acting during the cost-evaluation circuit. Expand
Connecting ansatz expressibility to gradient magnitudes and barren plateaus
TLDR
This paper presents a probabilistic simulation of the response of the immune system to x-ray diffraction and shows clear patterns in response to the proton-proton collision. Expand
Impact of Barren Plateaus on the Hessian and Higher Order Derivatives.
The Barren Plateau (BP) phenomenon is an issue for certain quantum neural networks and variational quantum algorithms, whereby the gradient vanishes exponentially in the system size $n$. The questionExpand
Noise-induced barren plateaus in variational quantum algorithms
TLDR
This work rigorously proves a serious limitation for noisy VQAs, in that the noise causes the training landscape to have a barren plateau (i.e., vanishing gradient), and implements numerical heuristics that confirm the NIBP phenomenon for a realistic hardware noise model. Expand
Effect of barren plateaus on gradient-free optimization
TLDR
It is shown that gradient-free optimizers do not solve the barren plateau problem, and the main result proves that cost function differences, which are the basis for making decisions in a gradient- free optimization, are exponentially suppressed in a barren plateau. Expand
Variational Quantum Fidelity Estimation
TLDR
The novel lower and upper bounds for the fidelity of F(\rho,\sigma) based on the "truncated fidelity" are proposed, which are often tighter than previously known computable bounds for realistic situations and can detect quantum phase transitions. Expand
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