Low-rank quantum state preparation

Abstract

Ubiquitous in quantum computing is the step to encode data into a quantum state. This process is called quantum state preparation, and its complexity for non-structured data is exponential on the number of qubits. Several works address this problem, for instance, by using variational methods that train a fixed depth circuit with manageable complexity. These methods have their limitations, as the lack of a back-propagation technique and barren plateaus. This work proposes an algorithm to reduce state preparation circuit depth by offloading computational complexity to a classical computer. The initialized quantum state can be exact or an approximation, and we show that the approximation is better on today's quantum processors than the initialization of the original state. Experimental evaluation demonstrates that the proposed method enables more efficient initialization of probability distributions in a quantum state.

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Cited by in corpus (14)

• Sparse Quantum State Preparation for Strongly Correlated Systems
• A Quantum Simulation Approach to Implementing Nuclear Density Functional Theory via Imaginary Time Evolution
• Efficient Quantum Circuits based on the Quantum Natural Gradient
• Quantum Multiplexer Simplification for State Preparation
• Efficient explicit circuit for quantum state preparation of piecewise continuous functions
• Parallel Quantum Signal Processing Via Polynomial Factorization
• Stabilization of symmetry-protected long-range entanglement in stochastic quantum circuits
• Sublinear Classical-to-Quantum Data Encoding using $n$-Toffoli Gates
• DisQu: Investigating the Impact of Disorder in Quantum Generative Models
• Solving coupled Non-linear Schrödinger Equations via Quantum Imaginary Time Evolution
• T-Count Optimizing Genetic Algorithm for Quantum State Preparation
• Quantum Framework for Simulating Linear PDEs with Robin Boundary Conditions
• Tucker iterative quantum state preparation
• Schmidt quantum compressor