Search

Conformation generation, also known as molecular unfolding (MU), is a crucial step in structure-based drug design, remaining a challenging combinatorial optimization problem. Quantum annealing (QA) has shown great potential for solving certain combinatorial optimization problems over traditional classical methods such as simulated annealing (SA). However, a recent study showed that a 2000-qubit QA hardware was still unable to outperform SA for the MU problem. Here, we propose the use of quantum-inspired algorithm to solve the MU problem, in order to go beyond traditional SA. We introduce a highly-compact phase encoding method which can exponentially reduce the representation space, compared with the previous one-hot encoding method. For benchmarking, we tested this new approach on the public QM9 dataset generated by density functional theory (DFT). The root-mean-square deviation between the conformation determined by our approach and DFT is negligible (less than about 0.5 Angstrom), which underpins the validity of our approach. Furthermore, the median time-to-target metric can be reduced by a factor of five compared to SA. Additionally, we demonstrate a simulation experiment by MindQuantum using quantum approximate optimization algorithm (QAOA) to reach optimal results. These results indicate that quantum-inspired algorithms can be applied to solve practical problems even before quantum hardware become mature.

Molecular docking (MD) is a crucial task in drug design, which predicts the position, orientation, and conformation of the ligand when bound to a target protein. It can be interpreted as a combinatorial optimization problem, where quantum annealing (QA) has shown promising advantage for solving combinatorial optimization. In this work, we propose a novel quantum molecular docking (QMD) approach based on QA-inspired algorithm. We construct two binary encoding methods to efficiently discretize the degrees of freedom with exponentially reduced number of bits and propose a smoothing filter to rescale the rugged objective function. We propose a new quantum-inspired algorithm, hopscotch simulated bifurcation (hSB), showing great advantage in optimizing over extremely rugged energy landscapes. This hSB can be applied to any formulation of objective function under binary variables. An adaptive local continuous search is also introduced for further optimization of the discretized solution from hSB. Concerning the stability of docking, we propose a perturbation detection method to help ranking the candidate poses. We demonstrate our approach on a typical dataset. QMD has shown advantages over the search-based Autodock Vina and the deep-learning DIFFDOCK in both re-docking and self-docking scenarios. These results indicate that quantum-inspired algorithms can be applied to solve practical problems in the drug discovery even before quantum hardware become mature.

Molecular docking is an important tool for structure-based drug design, accelerating the efficiency of drug development. Complex and dynamic binding processes between proteins and small molecules require searching and sampling over a wide spatial range. Traditional docking by searching for possible binding sites and conformations is computationally complex and results poorly under blind docking. Quantum-inspired algorithms combining quantum properties and annealing show great advantages in solving combinatorial optimization problems. Inspired by this, we achieve an improved in blind docking by using quantum-inspired combined with gradients learned by deep learning in the encoded molecular space. Numerical simulation shows that our method outperforms traditional docking algorithms and deep learning-based algorithms over 10\%. Compared to the current state-of-the-art deep learning-based docking algorithm DiffDock, the success rate of Top-1 (RMSD<2) achieves an improvement from 33\% to 35\% in our same setup. In particular, a 6\% improvement is realized in the high-precision region(RMSD<1) on molecules data unseen in DiffDock, which demonstrates the well-generalized of our method.

Quantum measurements based on mutually unbiased bases (MUB) play crucial roles in foundational studies and quantum information processing. It is known that there exist inequivalent MUB, but little is known about their operational distinctions, not to say experimental demonstration. In this work, by virtue of a simple estimation problem we experimentally demonstrate the operational distinctions between inequivalent triples of MUB in dimension 4 based on high-precision photonic systems. The experimental estimation fidelities coincide well with the theoretical predictions with only 0.16$\%$ average deviation, which is 25 times less than the difference (4.1$\%$) between the maximum estimation fidelity and the minimum estimation fidelity. Our experiments clearly demonstrate that inequivalent MUB have different information extraction capabilities and different merits for quantum information processing.

Optimizing the properties of molecules (materials or drugs) for stronger toughness, lower toxicity, or better bioavailability has been a long-standing challenge. In this context, we propose a molecular optimization framework called Q-Drug (Quantum-inspired optimization algorithm for Drugs) that leverages quantum-inspired algorithms to optimize molecules on discrete binary domain variables. The framework begins by encoding the molecules into binary embeddings using a discrete VAE. The binary embeddings are then used to construct an Ising energy-like objective function, over which the state-of-the-art quantum-inspired optimization algorithm is adopted to find the optima. The binary embeddings corresponding to the optima are decoded to obtain the optimized molecules. We have tested the framework for optimizing drug molecule properties and have found that it outperforms other molecular optimization methods, finding molecules with better properties in 1/20th to 1/10th of the time previously required. The framework can also be deployed directly on various quantum computing equipment, such as laser pulses CIMs, FPGA Ising Machines, and quantum computers based on quantum annealing, among others. Our work demonstrates a new paradigm that leverages the advantages of quantum computing and AI to solve practically useful problems.

Affleck-Kennedy-Lieb-Tasaki (AKLT) states are an important class of many-body quantum states that are useful in quantum information processing, including measurement-based quantum computation in particular. Here we propose a general approach for constructing efficient verification protocols for AKLT states on arbitrary graphs with local spin measurements. Our verification protocols build on bond verification protocols and matching covers (including edge coloring) of the underlying graphs, which have a simple geometric and graphic picture. We also provide rigorous performance guarantee that is required for practical applications. With our approach, most AKLT states of wide interest, including those defined on 1D and 2D lattices, can be verified with a constant sample cost, which is independent of the system size and is dramatically more efficient than all previous approaches. As an illustration, we construct concrete verification protocols for AKLT states on various lattices and on arbitrary graphs up to five vertices., Comment: 18+7 pages, 15 figures, and 4+1 tables; see also the companion paper on the verification of ground states. Comments and suggestions are very welcome!

Ground states of local Hamiltonians are of key interest in many-body physics and also in quantum information processing. Efficient verification of these states are crucial to many applications, but very challenging. Here we propose a simple, but powerful recipe for verifying the ground states of general frustration-free Hamiltonians based on local measurements. Moreover, we derive rigorous bounds on the sample complexity by virtue of the quantum detectability lemma (with improvement) and quantum union bound. Notably, the number of samples required does not increase with the system size when the underlying Hamiltonian is local and gapped, which is the case of most interest. As an application, we propose a general approach for verifying Affleck-Kennedy-Lieb-Tasaki (AKLT) states on arbitrary graphs based on local spin measurements, which requires only a constant number of samples for AKLT states defined on various lattices. Our work is of interest not only to many tasks in quantum information processing, but also to the study of many-body physics., Comment: 17+5 pages and 2 figures; accepted by Quantum

Efficient verification of quantum states and gates is crucial to the development of quantum technologies. Although the sample complexities of quantum state verification and quantum gate verification have been studied by many researchers, the number of experimental settings has received little attention and is poorly understood. In this work we study systematically quantum state verification and quantum gate verification with a focus on the number of experimental settings. We show that any bipartite pure state can be verified by only two measurement settings based on local projective measurements. Any bipartite unitary in dimension $d$ can be verified by $2d$ experimental settings based on local operations. In addition, we introduce the concept of entanglement-free verification and clarify its connection with minimal-setting verification. Finally, we show that any two-qubit unitary can be verified with at most five experimental settings; moreover, a generic two-qubit unitary (except for a set of measure zero) can be verified by an entanglement-free protocol based on four settings. In the course of study we clarify the properties of Schmidt coefficients of two-qubit unitaries, which are of independent interest., Comment: 12+4 pages and 2 figures

Electromagnetic waves carrying orbital angular momentum (OAM) have found many applications. This work reports a broadband millimeter wave OAM generator applying a dielectric metasurface with high-refractive-index dielectric elements distributed on a low-refractive-index substrate. Proper adjustment of the dimensions of the dielectric elements can make a broadband OAM generator from 53 to 70 GHz. OAM generators with different mode numbers are designed and validated by simulation. Such structures can find potential applications in high-capacity communications and imaging., Comment: 8 pages, 6 figures