Quantum neural networks (QNNs) have generated excitement around the possibility of
efficiently analyzing quantum data. But this excitement has been tempered by the existence …

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) …

A large amount of effort has recently been put into understanding the barren plateau
phenomenon. In this perspective article, we face the increasingly loud elephant in the room …

Scaling of variational quantum algorithms to large problem sizes requires efficient
optimization of random parameterized quantum circuits. For such circuits with uncorrelated …

Combinatorial optimization on near-term quantum devices is a promising path to
demonstrating quantum advantage. However, the capabilities of these devices are …

Barren plateaus have emerged as a pivotal challenge for variational quantum computing.
Our understanding of this phenomenon underwent a transformative shift with the recent …

Quantum compiling, where a parameterized quantum circuit is trained to learn a target
unitary, is an important primitive for quantum computing that can be used as a subroutine to …

Bosonic variational quantum circuits (VQCs) are crucial for information processing in
microwave cavities, trapped ions, and optical systems, widely applicable in quantum …

Variational quantum algorithms (VQAs) that estimate values of widely used physical
quantities such as the rank, the quantum entropies, the Bures fidelity, and the quantum …

We propose a continuous-variable (CV) SWAP test that requires no ancilla register, thereby
generalizing the ancilla-free SWAP test for qubits. In this ancilla-free CV SWAP test, the …