[HTML][HTML] The variational quantum eigensolver: a review of methods and best practices
The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …
received significant attention from the research community in recent years. It uses the …
Variational-quantum-eigensolver–inspired optimization for spin-chain work extraction
The energy extraction from quantum sources is a key task to develop new quantum devices
such as quantum batteries (QB). In this context, one of the main figures of merit is the …
such as quantum batteries (QB). In this context, one of the main figures of merit is the …
The imitation game: Leveraging copycats for robust native gate selection in nisq programs
Quantum programs are written in high-level languages, whereas quantum hardware can
only execute low-level native gates. To run programs on quantum systems, each high-level …
only execute low-level native gates. To run programs on quantum systems, each high-level …
Alternating layered variational quantum circuits can be classically optimized efficiently using classical shadows
Variational quantum algorithms (VQAs) are the quantum analog of classical neural networks
(NNs). A VQA consists of a parameterized quantum circuit (PQC) which is composed of …
(NNs). A VQA consists of a parameterized quantum circuit (PQC) which is composed of …
VQE-inspired optimization for spin chains work extraction
The energy extraction from quantum sources is a key task to develop new quantum devices
such as Quantum Batteries (QB). In this context, one of the main figures of merit is the …
such as Quantum Batteries (QB). In this context, one of the main figures of merit is the …
SpacePulse: Combining Parameterized Pulses and Contextual Subspace for More Practical VQE
In this paper, we explore the integration of parameterized quantum pulses with the
contextual subspace method. The advent of parameterized quantum pulses marks a …
contextual subspace method. The advent of parameterized quantum pulses marks a …
Towards Efficient Quantum Computation of Molecular Ground State Energies using Bayesian Optimization with Priors over Surface Topology
Variational Quantum Eigensolvers (VQEs) represent a promising approach to computing
molecular ground states and energies on modern quantum computers. These approaches …
molecular ground states and energies on modern quantum computers. These approaches …
Shallow quantum circuits are robust hunters for quantum many-body scars
Presently, noisy intermediate-scale quantum computers encounter significant technological
challenges that make it impossible to generate large amounts of entanglement. We leverage …
challenges that make it impossible to generate large amounts of entanglement. We leverage …
An Empirical Analysis of Realistic Noise in Quantum Neural Networks for Medical Classifications of Tabular, Signal and Imaging Data
Quantum machine learning has gained significant momentum in recent years, particularly
with the use of parameterized quantum circuits that exhibit a certain level of resilience to …
with the use of parameterized quantum circuits that exhibit a certain level of resilience to …
Vertical Meaning: Interpersonal Data in Quantum Circuits via Japanese Honorifics
RD Walton - 2024 - preprints.org
This paper proposes a novel concept within Quantum Natural Language Processing (QNLP)
to encode the interpersonal metafunction of Systemic Functional Linguistics (SFL) …
to encode the interpersonal metafunction of Systemic Functional Linguistics (SFL) …