Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Fusing matrix-product states with quantum Monte Carlo: reducing entanglement and sign problem at the same time
Gunnar Bollmark, Sam Mardazad, Johannes S. Hofmann +1 more·Nov 1, 2024
Systems of correlated quantum matter can be a steep challenge to any would-be method of solution. Matrix-product state (MPS)-based methods can describe 1D systems quasiexactly, but often struggle to retain sufficient bipartite entanglement to accurat...
Hybrid cat-transmon architecture for scalable, hardware-efficient quantum error correction
Connor T. Hann, Kyungjoo Noh, Harald Putterman +6 more·Oct 30, 2024
Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. In this work we theoretically study the long-term prospects of a hybrid cat-tran...
A fast hybrid classical-quantum algorithm based on block successive over-relaxation for the heat differential equation
Azim Farghadan, M. Farahani, Mohsen Akbari·Oct 29, 2024
The numerical solution of partial differential equations (PDEs) is essential in computational physics. Over the past few decades, various quantum-based methods have been developed to formulate and solve PDEs. Solving PDEs incur high time complexity f...
Designing Majorana Quasiparticles in InAsP Quantum Dots in InP Nanowires with Variational Quantum Eigenvalue Solver
Mahan Mohseni, Iann Cunha, D. Miravet +5 more·Oct 29, 2024
This work presents steps toward the design of Majorana zero modes (MZM) in InAsP quantum dots embedded in an InP semiconducting nanowire in contact with a p‐type superconductor described by the Kitaev Hamiltonian. The single‐particle spectrum is obta...
Hybrid quantum-classical approach for combinatorial problems at hadron colliders
Jacob L. Scott, Zhongtian Dong, Taejoon Kim +2 more·Oct 29, 2024
In recent years, quantum computing has drawn significant interest within the field of high-energy physics. We explore the potential of quantum algorithms to resolve the combinatorial problems in particle physics experiments. As a concrete example, we...
Machine Learning and Quantum Intelligence for Health Data Scenarios
S. Naguleswaran·Oct 28, 2024
The advent of quantum computing has opened new possibilities in data science, offering unique capabilities for addressing complex, data-intensive problems. Traditional machine learning algorithms often face challenges in high-dimensional or limited-q...
Approaches to Simultaneously Solving Variational Quantum Eigensolver Problems
A. Hutchings, Eric Yarnot, Xinpeng Li +4 more·Oct 28, 2024
The variational quantum eigensolver (VQE), a type of variational quantum algorithm, is a hybrid quantum-classical algorithm to find the lowest-energy eigenstate of a particular Hamiltonian. We investigate ways to optimize the VQE solving process on m...
Deep Optimizer States: Towards Scalable Training of Transformer Models Using Interleaved Offloading
Avinash Maurya, Jie Ye, M. Mustafa Rafique +2 more·Oct 26, 2024
Transformers and large language models~(LLMs) have seen rapid adoption in all domains. Their sizes have exploded to hundreds of billions of parameters and keep increasing. Under these circumstances, the training of transformers is very expensive and ...
Characterizing Conical Intersections of Nucleobases on Quantum Computers.
Yuchen Wang, Cameron Cianci, Irma Avdic +7 more·Oct 24, 2024
Hybrid quantum-classical computing algorithms offer significant potential for accelerating the calculation of the electronic structure of strongly correlated molecules. In this work, we present the first quantum simulation of conical intersections (C...
Adiabatic training for Variational Quantum Algorithms
Ernesto Acosta, C. C. Gutierrez, Guillermo Botella Juan +1 more·Oct 24, 2024
This paper presents a new hybrid Quantum Machine Learning (QML) model composed of three elements: a classical computer in charge of the data preparation and interpretation; a Gate-based Quantum Computer running the Variational Quantum Algorithm (VQA)...
Fast classical simulation of qubit-qudit hybrid systems
Haemanth Velmurugan, Arnav Das, Turbasu Chatterjee +3 more·Oct 23, 2024
Simulating quantum circuits is a computationally intensive task that relies heavily on tensor products and matrix multiplications, which can be inefficient. Recent advancements, eliminate the need for tensor products and matrix multiplications, offer...
Quantum Convolutional Neural Network: A Hybrid Quantum-Classical Approach for Iris Dataset Classification
S. Yousuf, Iqbal Tomal, Abdullah Al Shafin +2 more·Oct 21, 2024
This paper presents a hybrid quantum-classical machine learning model for classification tasks, integrating a 4-qubit quantum circuit with a classical neural network. The quantum circuit is designed to encode the features of the Iris dataset using an...
Hybrid Quantum-HPC Solutions for Max-Cut: Bridging Classical and Quantum Algorithms
Ishan Patwardhan, Akhil Akkapelli·Oct 21, 2024
This research explores the integration of the Quantum Approximate Optimization Algorithm (QAOA) into Hybrid Quantum-HPC systems for solving the Max-Cut problem, comparing its performance with classical algorithms like brute-force search and greedy he...
Projective Quantum Eigensolver with Generalized Operators
D. Mondal, Chayan Patra, Dipa Halder +1 more·Oct 21, 2024
Determination of molecular energetics and properties is one of the core challenges in the near-term quantum computing. To this end, hybrid quantum-classical algorithms are preferred for Noisy Intermediate Scale Quantum (NISQ) architectures. The Proje...
A Hybrid Quantum Solver for the Lorenz System
S. F. Hafshejani, D. Gaur, Arundhati Dasgupta +3 more·Oct 20, 2024
We develop a hybrid classical–quantum method for solving the Lorenz system. We use the forward Euler method to discretize the system in time, transforming it into a system of equations. This set of equations is solved by using the Variational Quantum...
Quantum-Classical Computing via Tensor Networks
Nathaniel Tornow, C. Mendl, Pramod Bhatotia·Oct 19, 2024
Circuit knitting offers a promising path to the scalable execution of large quantum circuits by breaking them into smaller sub-circuits whose output is recombined through classical postprocessing. However, current techniques face excessive overhead d...
Quantum Boltzmann machine learning of ground-state energies
Dhrumil Patel, Dan Koch, Saahil Patel +1 more·Oct 16, 2024
Estimating the ground-state energy of Hamiltonians is a fundamental task for which it is believed that quantum computers can be helpful. Several approaches have been proposed toward this goal, including algorithms based on quantum phase estimation an...
An Efficient Error Estimation Method in Quantum Key Distribution
Yingjian Wang, Yilun Hai, Buniechukwu Njoku +3 more·Oct 15, 2024
Error estimation is an important step for error correction in quantum key distribution. Traditional error estimation methods require sacrificing a part of the sifted key, forcing a trade-off between the accuracy of error estimation and the size of th...
Low-noise Optomechanical Single Phonon-photon Conversion for Quantum Networks
Liu Chen, Alexander Rolf Korsch, Cauê Moreno Kersul +4 more·Oct 14, 2024
Nano-structured optomechanical crystals (OMC) form an interface between mechanical modes with long coherence times and telecom optical photons, ideal for long-distance distribution of quantum information. However, the implementation of scalable quant...
Quantum Neural Network for Accelerated Magnetic Resonance Imaging
Shuo Zhou, Yihang Zhou, Congcong Liu +4 more·Oct 12, 2024
Magnetic resonance image reconstruction starting from undersampled k-space data requires the recovery of many potential nonlinear features, which is very difficult for algorithms to recover these features. In recent years, the development of quantum ...