Papers
Live trends in quantum computing research, updated daily from arXiv.
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13,008 papers in 12 months (-3% vs prior quarter)
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Scalable Noise Characterization of Syndrome-Extraction Circuits with Averaged Circuit Eigenvalue Sampling
Evan T. Hockings, Andrew C. Doherty, Robin Harper·Apr 9, 2024
Characterizing the performance of noisy quantum circuits is central to the production of prototype quantum computers and can enable improved quantum error correction that exploits noise biases identified in a quantum device. We develop a scalable noi...
Single-qubit rotation algorithm with logarithmic Toffoli count and gate depth
Christoffer Hindlycke, Jan-AAke Larsson·Apr 8, 2024
Building generic gates from a restricted gate set is a difficult but important problem, especially in the noisy regime where only a limited set of noise-resistant gates are available, e.g., fault-tolerant Clifford gates (generated by Hadamard, phase,...
Distributing Arbitrary Quantum Graph States by Graph Transformation
Tingxiang Ji, Jianqing Liu, Zheshen Zhang·Apr 8, 2024
Quantum graph state is a special class of nonlocal state among multiple quantum particles, underpinning several nonclassical and promising applications such as quantum computing and quantum secret sharing. Recently, establishing quantum graph states ...
Portable diamond maser with reduced magnetic field through orientation
Wern Ng, Yongqiang Wen, N. Alford +1 more·Apr 7, 2024
Masers have the potential to transform medical sensing and boost qubit readout detection due to their superb low-noise amplification. The negatively-charged nitrogen vacancy (NV-) diamond maser is the only continuous-wave solid-state maser discovered...
Digital quantum simulation of cavity quantum electrodynamics: insights from superconducting and trapped ion quantum testbeds
Alex H. Rubin, Brian Marinelli, Victoria A. Norman +15 more·Apr 5, 2024
We explore the potential for hybrid development of quantum hardware where currently available quantum computers simulate open cavity quantum electrodynamical (CQED) systems for applications in optical quantum communication, simulation and computing. ...
Exploring Quantum-Enhanced Machine Learning for Computer Vision: Applications and Insights on Noisy Intermediate-Scale Quantum Devices
Purnachandra Mandadapu·Apr 1, 2024
As medium-scale quantum computers progress, the application of quantum algorithms across diverse fields like simulating physical systems, chemistry, optimization, and cryptography becomes more prevalent. However, these quantum computers, known as Noi...
Device-Independent Quantum Key Distribution Based on Routed Bell Tests
Tristan Le Roy-Deloison, Edwin Peter Lobo, Jef Pauwels +1 more·Apr 1, 2024
Photon losses are the main obstacle to fully photonic implementations of device-independent quantum key distribution (DIQKD). Motivated by recent work showing that routed Bell scenarios offer increased robustness to detection inefficiencies for the c...
Direct detection of quasiparticle tunneling with a charge-sensitive superconducting sensor coupled to a waveguide
Kazi Rafsanjani Amin, Axel Eriksson, Mikael Kervinen +3 more·Apr 1, 2024
Detecting quasiparticle tunneling events in superconducting circuits provides information about the population and dynamics of non-equilibrium quasiparticles. Such events can be detected by monitoring changes in the frequency of an offset-charge-sens...
Quantum circuit scheduler for QPUs usage optimization
J. Romero-Álvarez, J. Alvarado-Valiente, Jorge Casco-Seco +4 more·Apr 1, 2024
Progress in the realm of quantum technologies is paving the way for a multitude of potential applications across different sectors. However, the reduced number of available quantum computers, their technical limitations and the high demand for their ...
Solving reaction dynamics with quantum computing algorithms
Ronen Weiss, Alessandro Baroni, Joseph Carlson +1 more·Mar 30, 2024
The description of quantum many-body dynamics is extremely challenging on classical computers, as it can involve many degrees of freedom. On the other hand, the time evolution of quantum states is a natural application for quantum computers that are ...
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
Changwon Lee, Israel F. Araujo, Dongha Kim +4 more·Mar 28, 2024
Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This approach is particularly attractive due to the absence of the barren pl...
On the feasibility of quantum teleportation protocols implemented with silicon devices.
Junghee Ryu, Hoon Ryu·Mar 28, 2024
With recent experimental advancements demonstrating high-fidelity universal logic gates and basic programmability, silicon-based spin quantum bits (qubits) have emerged as promising candidates for scalable quantum computing. However, implementation o...
Lindblad-like quantum tomography for non-Markovian quantum dynamical maps
S. Varona, Markus Muller, A. Bermudez·Mar 28, 2024
We introduce Lindblad-like quantum tomography (LℓQT) as a quantum characterization technique of time-correlated noise in quantum information processors. This approach enables the estimation of time-local master equations, including their possible neg...
Theory of quantum error mitigation for non-Clifford gates
David Layden, Bradley Mitchell, Karthik Siva·Mar 27, 2024
Quantum error mitigation techniques mimic noiseless quantum circuits by running several related noisy circuits and combining their outputs in particular ways. How well such techniques work is thought to depend strongly on how noisy the underlying gat...
Benchmarking Quantum Generative Learning: A Study on Scalability and Noise Resilience using QUARK
Florian J. Kiwit, Maximilian A. Wolf, M. Marso +4 more·Mar 27, 2024
Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to scale quantum machine learning (QML) to industrial-level applications....
Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction.
Anthony M. Smaldone, Victor S. Batista·Mar 27, 2024
Toxicity is a roadblock that prevents an inordinate number of drugs from being used in potentially life-saving applications. Deep learning provides a promising solution to finding ideal drug candidates; however, the vastness of chemical space coupled...
Comment on “Recovering noise-free quantum observables”
Josu Etxezarreta Martinez, Olatz Sanz Larrarte, Javier Oliva del Moral +2 more·Mar 26, 2024
Zero-noise extrapolation (ZNE) stands as the most widespread quantum error mitigation technique used in the recovery of noise-free expectation values of observables of interest by means of noisy intermediate-scale quantum (NISQ) machines. Recently, O...
Molecular groundstate determination via short pulses on superconducting qubits
Noga Entin, Mor M. Roses, Reuven Cohen +2 more·Mar 26, 2024
Quantum computing is currently hindered by hardware noise. We present a freestyle superconducting pulse optimization method, incorporating two-qubit channels, which enhances flexibility, execution speed, and noise resilience. A minimal 0.22 ns pulse ...
Probing the limits of variational quantum algorithms for nonlinear ground states on real quantum hardware: The effects of noise
Muhammad Umer, Eleftherios Mastorakis, S. Evangelou +1 more·Mar 25, 2024
A recently proposed variational quantum algorithm has expanded the horizon of variational quantum computing to nonlinear physics and fluid dynamics. In this work, we probe the ability of such approaches to capture the ground state of the nonlinear Sc...
BeSnake: A Routing Algorithm for Scalable Spin-Qubit Architectures
Nikiforos Paraskevopoulos, C. G. Almudéver, Sebastian Feld·Mar 24, 2024
As quantum computing devices increase in size with respect to the number of qubits, two-qubit interactions become more challenging, necessitating innovative and scalable qubit routing solutions. In this work, we introduce beSnake, a novel algorithm s...