Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
28,188
This Month
0
Today
0
Research Volume
13,351 papers in 12 months (+7% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Chemistry beyond the scale of exact diagonalization on a quantum-centric supercomputer.
Javier Robledo-Moreno, Mario Motta, Holger Haas +14 more·May 8, 2024
A universal quantum computer can simulate diverse quantum systems, with electronic structure for chemistry offering challenging problems for practical use cases around the hundred-qubit mark. Although current quantum processors have reached this size...
Benchmarking Optimizers for Qumode State Preparation with Variational Quantum Algorithms
Shuwen Kan, Miguel Palma, Zefan Du +5 more·May 7, 2024
Quantum state preparation involves preparing a target state from an initial system, a process integral to applications such as quantum machine learning and solving systems of linear equations. A qumode is a quantum-mechanical harmonic oscillator repr...
Neural network based deep learning analysis of semiconductor quantum dot qubits for automated control
Jacob R. Taylor, S. Das Sarma·May 7, 2024
Machine learning offers a largely unexplored avenue for improving noisy disordered devices in physics using automated algorithms. Through simulations that include disorder in physical devices, particularly quantum devices, there is potential to learn...
Quantum-inspired clustering with light
Miguel Varga, Pablo Bermejo, Ruben Pellicer-Guridi +2 more·May 7, 2024
This article introduces a novel approach to perform the simulation of a single qubit quantum-inspired algorithm using laser beams. Leveraging the polarization states of photonic qubits, and inspired by variational quantum eigensolvers, we develop a v...
Progressive quantum algorithm for maximum independent set with quantum alternating operator ansatz
Xiao-Hui 晓慧 Ni 倪, L. Li 李, Y. Song 宋 +3 more·May 7, 2024
The quantum alternating operator ansatz algorithm (QAOA+) is widely used for constrained combinatorial optimization problems (CCOPs) due to its ability to construct feasible solution spaces. In this paper, we propose a progressive quantum algorithm (...
Logical Error Rates for a [[4,2,2]]-Encoded Variational Quantum Eigensolver Ansatz
Meenambika Gowrishankar, Daniel Claudino, Jerimiah Wright +1 more·May 5, 2024
Quantum computing offers a potential for algorithmic speedups for applications, such as large-scale simulations in chemistry and physics. However, these speedups must yield results that are sufficiently accurate to predict realistic outcomes of exper...
Validating large-scale quantum machine learning: efficient simulation of quantum support vector machines using tensor networks
Kuan-Cheng Chen, Tai-Yue Li, Yun-Yuan Wang +6 more·May 4, 2024
We present an efficient tensor-network-based approach for simulating large-scale quantum circuits exemplified by quantum support vector machines (QSVMs). Experimentally, leveraging the cuTensorNet library on multiple GPUs, our method effectively redu...
On computational complexity and average-case hardness of shallow-depth boson sampling
Byeongseon Go, Changhun Oh, Hyunseok Jeong·May 3, 2024
Boson sampling, a computational task believed to be classically hard to simulate, is expected to hold promise for demonstrating quantum computational advantage using near-term quantum devices. However, noise in experimental implementations poses a si...
Optimal Toffoli-Depth Quantum Adder
Siyi Wang, Ankit Mondal, Anupam Chattopadhyay·May 3, 2024
Efficient quantum arithmetic circuits are commonly found in numerous quantum algorithms of practical significance. To date, the logarithmic-depth quantum adders include a constant coefficient k ≥ 2 while achieving the Toffoli-Depth of k log n + 𝒪(1)...
Strategies for Enhancing Spin-Shuttling Fidelities in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:mi>Si</mml:mi></mml:math> / <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:mi>Si</mml:mi></mml:mat
Merritt P. Losert, Max Oberländer, J. Teske +5 more·May 3, 2024
Coherent coupling between distant qubits is needed for many scalable quantum computing schemes. In quantum dot systems, one proposal for long-distance coupling is to coherently transfer electron spins across a chip in a moving dot potential. Here, we...
Error-mitigated photonic quantum circuit Born machine
A. Salavrakos, Tigran Sedrakyan, James Mills +2 more·May 3, 2024
In this Letter, we study quantum circuit Born machines (QCBMs) in the context of photonic quantum computing. QCBMs are a popular choice of quantum generative machine learning models, and we present a QCBM designed for linear optics. We show that a re...
High-Frequency Tails in Spectral Densities
R. Korol, Xinxian Chen, Ignacio Franco·May 2, 2024
Recent advances in numerically exact quantum dynamics methods have brought the dream of accurately modeling the dynamics of chemically complex open systems within reach. Path-integral-based methods, hierarchical equations of motion, and quantum analo...
Driven multiphoton qubit-resonator interactions
M. Ayyash, Xicheng Xu, S. Ashhab +1 more·May 2, 2024
We develop a general theory for multiphoton qubit-resonator interactions enhanced by a qubit drive. The interactions generate qubit-conditional operations in the resonator when the driving is near $n$-photon cross-resonance, namely, the qubit drive i...
Generalising quantum imaginary time evolution to solve linear partial differential equations
Swagat Kumar, C. Wilmott·May 2, 2024
The quantum imaginary time evolution (QITE) methodology was developed to overcome a critical issue as regards non-unitarity in the implementation of imaginary time evolution on a quantum computer. QITE has since been used to approximate ground states...
Digital-analog counterdiabatic quantum optimization with trapped ions
Shubham Kumar, N. N. Hegade, Alejandro Gomez-Cadavid +3 more·May 2, 2024
We introduce a hardware-specific, problem-dependent digital-analog quantum algorithm of a counterdiabatic quantum dynamics tailored for optimization problems. Specifically, we focus on trapped-ion architectures, taking advantage from global Mølmer–Sø...
QSimPy: A Learning-centric Simulation Framework for Quantum Cloud Resource Management
H. T. Nguyen, Muhammad Usman, R. Buyya·May 2, 2024
Quantum cloud computing is an emerging computing paradigm that allows seamless access to quantum hardware as cloud-based services. However, effective use of quantum resources is challenging and necessitates robust simulation frameworks for effective ...
Classically Spoofing System Linear Cross Entropy Score Benchmarking
Andrew Tanggara, Mile Gu, Kishor Bharti·May 1, 2024
In recent years, several experimental groups have claimed demonstrations of ``quantum supremacy'' or computational quantum advantage. A notable first claim by Google Quantum AI revolves around a metric called the Linear Cross Entropy Benchmarking (Li...
High-dimensional graphs convolution for quantum walks photonic applications
Roman Abramov, Leonid Fedichkin, Dmitry V. Tsarev +1 more·May 1, 2024
Quantum random walks represent a powerful tool for the implementation of various quantum algorithms. We consider a convolution problem for the graphs which provide quantum and classical random walks. We suggest a new method for lattices and hypercycl...
A synthetic magnetic vector potential in a 2D superconducting qubit array
Ilan T. Rosen, Sarah E. Muschinske, Cora N. Barrett +14 more·May 1, 2024
Superconducting quantum processors are a compelling platform for analogue quantum simulation due to the precision control, fast operation and site-resolved readout inherent to the hardware. Arrays of coupled superconducting qubits natively emulate th...
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification
Sk Chan, Pranav Kulkarni, P. Yi +1 more·Apr 30, 2024
Quantum machine learning (QML) has the potential for improving the multi-label classification of rare, albeit critical, diseases in large-scale chest x-ray (CXR) datasets due to theoretical quantum advantages over classical machine learning (CML) in ...