The Adjoint Is All You Need: Characterizing Barren Plateaus in Quantum Ans\" atze
Using tools from the representation theory of compact Lie groups we formulate a theory of
Barren Plateaus (BPs) for parameterized quantum circuits where the observable lies in the …
Barren Plateaus (BPs) for parameterized quantum circuits where the observable lies in the …
[PDF][PDF] Early fault-tolerant quantum computing
In recent years, research in quantum computing has largely focused on two approaches:
near-term intermediate-scale quantum (NISQ) computing and future fault-tolerant quantum …
near-term intermediate-scale quantum (NISQ) computing and future fault-tolerant quantum …
Quantum-classical tradeoffs and multi-controlled quantum gate decompositions in variational algorithms
The computational capabilities of near-term quantum computers are limited by the noisy
execution of gate operations and a limited number of physical qubits. Hybrid variational …
execution of gate operations and a limited number of physical qubits. Hybrid variational …
Convergence guarantee for linearly-constrained combinatorial optimization with a quantum alternating operator ansatz
B Goldstein-Gelb, PC Lotshaw - arxiv preprint arxiv:2409.18829, 2024 - arxiv.org
We present a quantum alternating operator ansatz (QAOA $^+ $) that solves a class of
linearly constrained optimization problems by evolving a quantum state within a Hilbert …
linearly constrained optimization problems by evolving a quantum state within a Hilbert …
Dual-step optimization for binary sequences with high merit factors
The problem of finding aperiodic low auto-correlation binary sequences (LABS) presents a
significant computational challenge, particularly as the sequence length increases. Such …
significant computational challenge, particularly as the sequence length increases. Such …
Quantum Algorithms for Nonconvex Optimization: Theory and Implementation
J Leng - 2024 - search.proquest.com
Continuous optimization problems arise in virtually all disciplines of quantitative research.
While convex optimization has been well-studied in recent decades, large-scale nonconvex …
While convex optimization has been well-studied in recent decades, large-scale nonconvex …