Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
28,891
This Month
551
Today
0
Research Volume
13,849 papers in 12 months (-10% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Quantum algorithms for N-1 security in power grids
Niels M. P. Neumann, Stan van der Linde, Willem de Kok +7 more·May 1, 2024
In recent years, the supply and demand of electricity has significantly increased. As a result, the interconnecting grid infrastructure has required (and will continue to require) further expansion, while allowing for rapid resolution of unforeseen f...
Control landscapes for high-fidelity generation of C-NOT and C-PHASE gates with coherent and environmental driving
A. Pechen, V. Petruhanov, O. Morzhin +1 more·May 1, 2024
High-fidelity generation of two-qubit gates is important for quantum computation, since such gates are components of popular universal sets of gates. Here, we consider the problem of high-fidelity generation of two-qubit C-NOT and C-PHASE (with a det...
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...
QUACK: Quantum Aligned Centroid Kernel
Kilian Tscharke, Sebastian Issel, P. Debus·May 1, 2024
Quantum computing (QC) seems to show potential for application in machine learning (ML). In particular quantum kernel methods (QKM) exhibit promising properties for use in supervised ML tasks. However, a major disadvantage of kernel methods is their ...
Barren plateaus in variational quantum computing
Martín Larocca, Supanut Thanasilp, Samson Wang +7 more·May 1, 2024
Variational quantum computing offers a flexible computational approach with a broad range of applications. However, a key obstacle to realizing their potential is the barren plateau (BP) phenomenon. When a model exhibits a BP, its parameter optimizat...
Scaling Up the Quantum Divide and Conquer Algorithm for Combinatorial Optimization
I. Cameron, T. Tomesh, Zain Saleem +1 more·May 1, 2024
Quantum optimization as a field has largely been restricted by the constraints of current quantum computing hardware, as limitations on size, performance, and fidelity mean most non-trivial problem instances won't fit on quantum devices. Even propose...
What is Quantum Parallelism, Anyhow?
Stefano Markidis·May 1, 2024
Central to the power of quantum computing is the concept of quantum parallelism: quantum systems can explore and process multiple computational paths simultaneously. In this paper, we discuss the elusive nature of quantum parallelism, drawing paralle...
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...
Linearly simplified QAOA parameters and transferability
R. Sakai, Hiromichi Matsuyama, Wai-Hong Tam +2 more·May 1, 2024
Quantum Approximate Optimization Algorithm (QAOA) provides a way to solve combinatorial optimization problems using quantum computers. QAOA circuits consist of time evolution operators by the cost Hamiltonian and of state mixing operators, and embedd...
Experimental aspects of indefinite causal order in quantum mechanics
L. Rozema, T. Strömberg, Huan Cao +3 more·May 1, 2024
In the past decade, the toolkit of quantum information has been expanded to include processes in which the basic operations do not have definite causal relations. Originally considered in the context of the unification of quantum mechanics and genera...
Structure learning of Hamiltonians from real-time evolution
Ainesh Bakshi, Allen Liu, Ankur Moitra +1 more·Apr 30, 2024
We study the problem of Hamiltonian structure learning from real-time evolution: given the ability to apply $e^{-\mathrm{i} Ht}$ for an unknown local Hamiltonian $H = \sum_{a = 1}^m λ_a E_a$ on $n$ qubits, the goal is to recover $H$. This problem is ...
Quantum Cloud Computing: Trends and Challenges
Muhammed Golec, Emir Sahin Hatay, Mustafa Golec +3 more·Apr 30, 2024
Quantum computing (QC) is a new paradigm that will revolutionize various areas of computing, especially cloud computing. QC, still in its infancy, is a costly technology capable of operating in highly isolated environments due to its rapid response t...
Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent
Pingzhi Li, Junyu Liu, Hanrui Wang +1 more·Apr 30, 2024
Optimization techniques in deep learning are predominantly led by first-order gradient methodologies, such as SGD. However, neural network training can greatly benefit from the rapid convergence characteristics of second-order optimization. Newton's ...
A Simple Method for Compiling Quantum Stabilizer Circuits
B. Reid·Apr 30, 2024
Stabilizer circuits play an important role in quantum error correction protocols, and will be vital for ensuring fault tolerance in future quantum hardware. While stabilizer circuits are defined on the Clifford generating set, $\{H, S, CX\}$, not all...
Weighted Feedback-Based Quantum Algorithm for Excited States Calculation
Salahuddin Abdul Rahman, Özkan Karabacak, Rafael Wisniewski·Apr 30, 2024
Drawing inspiration from the Lyapunov control technique for quantum systems, feedback-based quantum al-gorithms have been proposed for calculating the ground states of Hamiltonians. In this work, we consider extending these algorithms to tackle calcu...
Entanglement-assisted phase-estimation algorithm for calculating dynamical response functions
Rei Sakuma, Shutaroh Kanno, Kenji Sugisaki +2 more·Apr 30, 2024
Dynamical response functions are fundamental quantities to describe the excited-state properties in quantum many-body systems. Quantum algorithms have been proposed to evaluate these quantities by means of quantum phase estimation (QPE), where the en...
Revealing the working mechanism of quantum neural networks by mutual information
Xin Zhang, Yuexian Hou·Apr 30, 2024
Quantum neural networks (QNNs) is a parameterized quantum circuit model, which can be trained by gradient-based optimizer, can be used for supervised learning, regression tasks, combinatorial optimization, etc. Although many works have demonstrated t...
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 ...
Light cone cancellation for variational quantum eigensolver in solving noisy Max-Cut
Xinwei Lee, Xinjian Yan, Ningyi Xie +5 more·Apr 30, 2024
Variational Quantum Eigensolver (VQE) is a quantum-classical hybrid algorithm used to estimate the ground energy of a given Hamiltonian. It consists of a parameterized quantum circuit, which the parameters are optimized using a classical optimizer. W...
Simple loss-tolerant protocol for Greenberger-Horne-Zeilinger-state distribution in a quantum network
Hikaru Shimizu, W. Roga, David Elkouss +1 more·Apr 30, 2024
Distributed quantum entanglement plays a crucial role in realizing networks that connect quantum devices. However, sharing entanglement between distant nodes by means of photons is a challenging process primary due to unavoidable losses in the linkin...