# Parallel quantum trajectories via forking for sampling without redundancy

## TL;DR

This paper introduces a quantum forking framework that enables parallel sampling from independent quantum processes, reducing redundant state preparations and accelerating quantum tasks like channel implementation and entanglement analysis.

## Contribution

The paper presents a novel quantum forking method that allows simultaneous sampling from multiple quantum trajectories, improving efficiency in quantum computations.

## Key findings

- Demonstrated quantum forking on IBM and Rigetti platforms.
- Achieved efficient implementation of non-unitary quantum channels.
- Enabled advanced studies of entanglement and quantum control.

## Abstract

The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find the answer, mandating reconstruction of the same input state for every execution of an algorithm. Thus, the advantage of quantum computation can diminish due to redundant state initialization. We present a framework based on quantum forking that bypasses this fundamental issue and expedites a family of tasks that require sampling from independent quantum processes. Quantum forking propagates an input state to multiple quantum trajectories in superposition, and a weighted power sum of individual results from each trajectories is obtained in one measurement via quantum interference. The significance of our work is demonstrated via applications to implementing non-unitary quantum channels, studying entanglement and benchmarking quantum control. A proof-of-principle experiment is implemented on the IBM and Rigetti quantum cloud platforms.