Quantum computing for high-energy physics: State of the art and challenges
Quantum computers offer an intriguing path for a paradigmatic change of computing in the
natural sciences and beyond, with the potential for achieving a so-called quantum …
natural sciences and beyond, with the potential for achieving a so-called quantum …
A Lie algebraic theory of barren plateaus for deep parameterized quantum circuits
Variational quantum computing schemes train a loss function by sending an initial state
through a parametrized quantum circuit, and measuring the expectation value of some …
through a parametrized quantum circuit, and measuring the expectation value of some …
A unified theory of barren plateaus for deep parametrized quantum circuits
AFV CoverSheet Page 1 LA-UR-23-30483 Accepted Manuscript A Lie algebraic theory of
barren plateaus for deep parameterized quantum circuits Cerezo de la Roca, Marco Vinicio …
barren plateaus for deep parameterized quantum circuits Cerezo de la Roca, Marco Vinicio …
A review of barren plateaus in variational quantum computing
Variational quantum computing offers a flexible computational paradigm with applications in
diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) …
diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) …
Quantum simulations of hadron dynamics in the Schwinger model using 112 qubits
Hadron wave packets are prepared and time evolved in the Schwinger model using 112
qubits of IBM's 133-qubit Heron quantum computer ibm_torino. The initialization of the …
qubits of IBM's 133-qubit Heron quantum computer ibm_torino. The initialization of the …
Quantum convolutional neural networks are (effectively) classically simulable
Quantum Convolutional Neural Networks (QCNNs) are widely regarded as a promising
model for Quantum Machine Learning (QML). In this work we tie their heuristic success to …
model for Quantum Machine Learning (QML). In this work we tie their heuristic success to …
Provably trainable rotationally equivariant quantum machine learning
Exploiting the power of quantum computation to realize superior machine learning
algorithms has been a major research focus of recent years, but the prospects of quantum …
algorithms has been a major research focus of recent years, but the prospects of quantum …
Towards large-scale quantum optimization solvers with few qubits
Quantum computers hold the promise of more efficient combinatorial optimization solvers,
which could be game-changing for a broad range of applications. However, a bottleneck for …
which could be game-changing for a broad range of applications. However, a bottleneck for …
Classically estimating observables of noiseless quantum circuits
We present a classical algorithm for estimating expectation values of arbitrary observables
on most quantum circuits across all circuit architectures and depths, including those with all …
on most quantum circuits across all circuit architectures and depths, including those with all …
Absence of barren plateaus in finite local-depth circuits with long-range entanglement
Ground state preparation is classically intractable for general Hamiltonians. On quantum
devices, shallow parametrized circuits can be effectively trained to obtain short-range …
devices, shallow parametrized circuits can be effectively trained to obtain short-range …