Quantum and molecular computing, quantum simulations

Jincheng Zhang

This research explores the potential of quantum simulation for tackling complex molecular dynamics problems that are currently intractable for classical computers. The core idea involves leveraging the principles of quantum mechanics to model molecular systems, specifically focusing on simulating the dynamic behavior of molecules and their interactions. We propose a framework for constructing a quantum simulator utilizing quantum bits (qubits) to represent and evolve molecular states. The theoretical framework presented herein outlines the methodology for mapping molecular dynamics problems onto a quantum computational platform, highlighting the advantages and challenges associated with this approach. Specifically, we examine the impact of quantum effects, such as superposition and entanglement, on the simulation accuracy and efficiency. This work contributes to the nascent field of quantum molecular dynamics and provides a foundation for future investigations into the development of practical quantum simulation tools. The key objective is to demonstrate that quantum simulation, when properly implemented, can significantly outperform classical methods for simulating complex molecular systems, particularly those involving significant quantum effects.

Jincheng Zhang

Quantum simulation offers a pathway to accurately model and understand complex molecular systems, a task often intractable using classical computational methods. However, the computational cost of simulating quantum systems, particularly those involving many particles and complex interactions, remains a significant barrier. This work presents a novel approach leveraging tensor network methods to achieve scalable quantum simulation of molecular dynamics. We demonstrate how tensor networks can efficiently represent the quantum state of a molecular system, allowing for the accurate calculation of its dynamics. The core idea is to utilize the tensor network representation to reduce the computational complexity associated with traditional quantum simulation algorithms. The presented method offers a promising route toward simulating larger and more realistic molecular systems, opening up new possibilities in fields such as drug discovery, materials science, and fundamental physics. This paper details the theoretical framework and provides a conceptual outline, emphasizing the scalability of the approach.

Mahn‐Soo Choi

Ryan J. MacDonell, Tomas Navickas, Tim F. Wohlers-Reichel +8 more

Spectroscopy is one of the most accurate probes of the molecular world. However, predicting molecular spectra accurately is computationally difficult because of the presence of entanglement between electronic and nuclear degrees of freedom. Although quantum computers promise to reduce this computational cost, existing quantum approaches rely on combining signals from individual eigenstates, an approach that is difficult to scale because the number of eigenstates grows exponentially with molecule size. Here, we introduce a method for scalable analog quantum simulation of molecular spectroscopy, by performing simulations in the time domain. Our approach can treat more complicated molecular models than previous ones, requires fewer approximations, and can be extended to open quantum systems with minimal overhead. We present a direct mapping of the underlying problem of time-domain simulation of molecular spectra to the degrees of freedom and control fields available in a trapped-ion quantum simulator. We experimentally demonstrate our algorithm on a trapped-ion device, exploiting both intrinsic electronic and motional degrees of freedom, showing excellent quantitative agreement for a single-mode vibronic photoelectron spectrum of SO$_2$.

Rüdiger Schack