[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 …
Perspective on the current state-of-the-art of quantum computing for drug discovery applications
Computational chemistry is an essential tool in the pharmaceutical industry. Quantum
computing is a fast evolving technology that promises to completely shift the computational …
computing is a fast evolving technology that promises to completely shift the computational …
Measurement-induced entanglement phase transition on a superconducting quantum processor with mid-circuit readout
Quantum many-body systems subjected to unitary evolution with the addition of interspersed
measurements exhibit a variety of dynamical phases that do not occur under pure unitary …
measurements exhibit a variety of dynamical phases that do not occur under pure unitary …
Entanglement devised barren plateau mitigation
Hybrid quantum-classical variational algorithms are one of the most propitious
implementations of quantum computing on near-term devices, offering classical machine …
implementations of quantum computing on near-term devices, offering classical machine …
Entanglement phase transitions in measurement-only dynamics
Unitary circuits subject to repeated projective measurements can undergo an entanglement
phase transition (EPT) as a function of the measurement rate. This transition is generally …
phase transition (EPT) as a function of the measurement rate. This transition is generally …
Exponential separations between learning with and without quantum memory
We study the power of quantum memory for learning properties of quantum systems and
dynamics, which is of great importance in physics and chemistry. Many state-of-the-art …
dynamics, which is of great importance in physics and chemistry. Many state-of-the-art …
[HTML][HTML] Stochastic gradient descent for hybrid quantum-classical optimization
Within the context of hybrid quantum-classical optimization, gradient descent based
optimizers typically require the evaluation of expectation values with respect to the outcome …
optimizers typically require the evaluation of expectation values with respect to the outcome …
[HTML][HTML] Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers
Variational algorithms are a promising paradigm for utilizing near-term quantum devices for
modeling electronic states of molecular systems. However, previous bounds on the …
modeling electronic states of molecular systems. However, previous bounds on the …
Fermionic partial tomography via classical shadows
We propose a tomographic protocol for estimating any k-body reduced density matrix (k-
RDM) of an n-mode fermionic state, a ubiquitous step in near-term quantum algorithms for …
RDM) of an n-mode fermionic state, a ubiquitous step in near-term quantum algorithms for …
Quantum computation of finite-temperature static and dynamical properties of spin systems using quantum imaginary time evolution
Developing scalable quantum algorithms to study finite-temperature physics of quantum
many-body systems has attracted considerable interest due to recent advancements in …
many-body systems has attracted considerable interest due to recent advancements in …