Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
27,548
This Month
1,041
Today
0
Research Volume
12,896 papers in 12 months (-5% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Unrolling SVT to Obtain Computationally Efficient SVT for N-Qubit Quantum State Tomography
S. Shanmugam, S. Kalyani·Dec 17, 2022
Quantum state tomography aims to estimate the state of a quantum mechanical system which is described by a trace one, Hermitian positive semidefinite complex matrix, given a set of measurements of the state. Existing works focus on estimating the den...
Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms
Mst. Shapna Akter, Md Jobair Hossain Faruk, Nafisa Anjum +6 more·Dec 17, 2022
The software supply chain (SSC) attack has become one of the crucial issues that are being increased rapidly with the advancement of the software development domain. In general, SSC attacks execute during the software development processes lead to vu...
Quantum Methods for Neural Networks and Application to Medical Image Classification
Jonas Landman, Natansh Mathur, Yun Li +4 more·Dec 14, 2022
Quantum machine learning techniques have been proposed as a way to potentially enhance performance in machine learning applications. In this paper, we introduce two new quantum methods for neural networks. The first one is a quantum orthogonal neural...
Category Theory for Quantum Natural Language Processing
Alexis Toumi·Dec 13, 2022
This thesis introduces quantum natural language processing (QNLP) models based on a simple yet powerful analogy between computational linguistics and quantum mechanics: grammar as entanglement. The grammatical structure of text and sentences connects...
NFNet: Non-interacting Fermion Network for Efficient Simulation of Large-scale Quantum Systems
Pengyuan Zhai, S. Yelin·Dec 12, 2022
We present NFNet, a PyTorch-based framework for polynomial-time simulation of large-scale, continuously controlled quantum systems, supporting parallel matrix computation and auto-differentiation of network parameters. It is based on the non-interact...
Scaling Qubit Readout with Hardware Efficient Machine Learning Architectures
Satvik Maurya, Chaithanya Naik Mude, W. Oliver +2 more·Dec 7, 2022
Reading a qubit is a fundamental operation in quantum computing. It translates quantum information into classical information enabling subsequent classification to assign the qubit states '0' or '1'. Unfortunately, qubit readout is one of the most er...
Deep quantum neural networks on a superconducting processor
Xiaoxuan Pan, Zhide Lu, Weiting Wang +10 more·Dec 5, 2022
Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of quantum machine learning. In this work, we report an experimental demo...
An exponentially-growing family of universal quantum circuits
Mohammad Kordzanganeh, Pavel Sekatski, Leonid Fedichkin +1 more·Dec 1, 2022
Quantum machine learning has become an area of growing interest but has certain theoretical and hardware-specific limitations. Notably, the problem of vanishing gradients, or barren plateaus, renders the training impossible for circuits with high qub...
Hybrid Quantum-Classical Autoencoders for End-to-End Radio Communication
Zsolt I. Tabi, Bence Bakó, Dániel Nagy +4 more·Dec 1, 2022
Quantum neural networks are emerging as poten-tial candidates to leverage noisy quantum processing units for applications. Here we introduce hybrid quantum-classical au-to encoders for end-to-end radio communication. In the physical layer of classica...
Quantum Neural Networks for a Supply Chain Logistics Application
R. Correll, Sean J. Weinberg, F. Sanches +2 more·Nov 30, 2022
Problem instances of a size suitable for practical applications are not likely to be addressed during the noisy intermediate‐scale quantum (NISQ) period with (almost) pure quantum algorithms. Hybrid classical‐quantum algorithms have potential, howeve...
A didactic approach to quantum machine learning with a single qubit
Elena Peña Tapia, G. Scarpa, Alejandro Pozas-Kerstjens·Nov 23, 2022
This paper presents, via an explicit example with a real-world dataset, a hands-on introduction to the field of quantum machine learning (QML). We focus on the case of learning with a single qubit, using data re-uploading techniques. After a discussi...
SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture
Han Zheng, Gokul Subramanian Ravi, Hanrui Wang +3 more·Nov 23, 2022
We propose SnCQA, a set of hardware-efficient variational circuits of equivariant quantum convolutional circuits respective to permutation symmetries and spatial lattice symmetries with the number of qubits n. By exploiting permutation symmetries of ...
Benchmarking Adversarially Robust Quantum Machine Learning at Scale
Maxwell T. West, S. Erfani, C. Leckie +3 more·Nov 23, 2022
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology and industry. Despite their accuracy and sophistication, neural networks can be easily fooled by carefully designed malicio...
Photonic Quantum Computing For Polymer Classification
A. Stoyanova, Taha Hammadia, Arno Ricou +1 more·Nov 22, 2022
We present a hybrid classical-quantum approach to the binary classification of polymer structures. Two polymer classes visual (VIS) and near-infrared (NIR) are defined based on the size of the polymer gaps. The hybrid approach combines one of the thr...
Improved Tomographic Estimates by Specialized Neural Networks
M. Guarneri, I. Gianani, M. Barbieri +1 more·Nov 21, 2022
Characterization of quantum objects, being states, processes, or measurements, complemented by previous knowledge about them is a valuable approach, especially as it leads to routine procedures for real‐life components. To this end, machine learning ...
Quantum approximate optimization algorithm parameter prediction using a convolutional neural network
Ningyi Xie, Xinwei Lee, DongSheng Cai +2 more·Nov 17, 2022
The Quantum approximate optimization algorithm (QAOA) is a quantum-classical hybrid algorithm aiming to produce approximate solutions for combinatorial optimization problems. In the QAOA, the quantum part prepares a quantum parameterized state that e...
Differentiable matrix product states for simulating variational quantum computational chemistry
Chu Guo, Yi Fan, Zhiqian Xu +1 more·Nov 15, 2022
Quantum Computing is believed to be the ultimate solution for quantum chemistry problems. Before the advent of large-scale, fully fault-tolerant quantum computers, the variational quantum eigensolver (VQE) is a promising heuristic quantum algorithm t...
Expressive quantum perceptrons for quantum neuromorphic computing
Rodrigo Araiza Bravo, T. Patti, K. Najafi +2 more·Nov 14, 2022
Quantum neuromorphic computing (QNC) is a sub-field of quantum machine learning (QML) that capitalizes on inherent system dynamics. As a result, QNC can run on contemporary, noisy quantum hardware and is poised to realize challenging algorithms in th...
An invitation to distributed quantum neural networks
Lirande Pira, C. Ferrie·Nov 14, 2022
Deep neural networks have established themselves as one of the most promising machine learning techniques. Training such models at large scales is often parallelized, giving rise to the concept of distributed deep learning. Distributed techniques are...
Hybrid Quantum Neural Network for Drug Response Prediction
A. Sagingalieva, Mohammad Kordzanganeh, Nurbolat Kenbayev +3 more·Nov 10, 2022
Simple Summary This work successfully employs a novel approach in processing patient and drug data to predict the drug response for cancer patients. The approach uses a deep quantum computing circuit as part of a machine learning architecture to simu...