Papers
Live trends in quantum computing research, updated daily from arXiv.
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13,522 papers in 12 months (-19% vs prior quarter)
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Optimization of Functional Materials Design with Optimal Initial Data in Surrogate-Based Active Learning
Seongmin Kim, In-Saeng Suh·Jun 3, 2025
The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships be...
Quantum correlation beyond entanglement: Holographic discord and multipartite generalizations
Takato Mori·Jun 2, 2025
While entanglement is a cornerstone of quantum theory and holography, quantum correlations arising from superposition, such as quantum discord, offer a broader perspective that has remained largely unexplored in holography. We construct gravity duals...
Quantum Complexity and Chaos in Many-Qudit Doped Clifford Circuits
Beatrice Magni, Xhek Turkeshi·Jun 2, 2025
We investigate the emergence of quantum complexity and chaos in doped Clifford circuits acting on qudits of odd prime dimension $d$. Using doped Clifford Weingarten calculus and a replica tensor network formalism, we derive exact results and perform ...
The Motzkin Spaghetto
Zhao Zhang, Olai B. Mykland·Jun 2, 2025
While highly entangled ground states of gapless local Hamiltonians have been known to exist in one dimension, their two-dimensional counterparts were only recently found, with rather sophisticated interactions involving at least four neighboring degr...
Flux-trapping characterization for superconducting electronics using a cryogenic widefield N-$V$ diamond microscope
Rohan T. Kapur, Pauli Kehayias, Sergey K. Tolpygo +12 more·Jun 2, 2025
Magnetic flux trapping is a significant hurdle limiting the reliability and scalability of superconducting electronics, yet tools for imaging flux vortices remain slow or insensitive. We present a cryogenic widefield NV-diamond magnetic microscope ca...
Learning thermodynamic master equations for open quantum systems
Peter Sentz, Stanley Nicholson, Yujin Cho +3 more·Jun 2, 2025
The characterization of Hamiltonians and other components of open quantum dynamical systems plays a crucial role in quantum computing and other applications. Scientific machine learning techniques have been applied to this problem in a variety of way...
Bayesian and Markovian classical feedforward for discriminating qubit channels
Milajiguli Rexiti, Stefano Mancini·Jun 2, 2025
We address the issue of multishot discrimination between two qubit channels by invoking a simple adaptive protocol that employs Helstrom measurement at each step and classical information feedforward, beside separable inputs. We contrast the performa...
Quantum Circuit Encodings of Polynomial Chaos Expansions
Junaid Aftab, Christoph Schwab, Haizhao Yang +1 more·Jun 2, 2025
This work investigates the expressive power of quantum circuits in approximating high-dimensional, real-valued functions. We focus on countably-parametric holomorphic maps $u:U\to \mathbb{R}$, where the parameter domain is $U=[-1,1]^{\mathbb{N}}$. We...
Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
Florian Fürrutter, Zohim Chandani, Ikko Hamamura +2 more·Jun 2, 2025
Efficiently compiling quantum operations remains a major bottleneck in scaling quantum computing. Today's state-of-the-art methods achieve low compilation error by combining search algorithms with gradient-based parameter optimization, but they incur...
New aspects of quantum topological data analysis: Betti number estimation, and testing and tracking of homology and cohomology classes
Nhat A. Nghiem·Jun 2, 2025
We introduce several new quantum algorithms for estimating homological invariants, specifically Betti numbers and persistent Betti numbers, of a simplicial complex given via a structured classical input. At the core of our algorithm lies the ability ...
Quantum Ensembling Methods for Healthcare and Life Science
Kahn Rhrissorrakrai, Kathleen E. Hamilton, Prerana Bangalore Parthsarathy +4 more·Jun 2, 2025
Learning on small data is a challenge frequently encountered in many real-world applications. In this work we study how effective quantum ensemble models are when trained on small data problems in healthcare and life sciences. We constructed multiple...
State Similarity in Modular Superconducting Quantum Processors with Classical Communications
Bujiao Wu, Changrong Xie, Peng Mi +20 more·Jun 2, 2025
As quantum devices continue to scale, distributed quantum computing emerges as a promising strategy for executing large-scale tasks across modular quantum processors. A central challenge in this paradigm is verifying the correctness of computational ...
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications
Rong Chen, Quanxin Mei, Wending Zhao +5 more·Jun 2, 2025
AlphaFold has achieved groundbreaking advancements in protein structure prediction, exerting profound influence across biology, medicine, and drug discovery. However, its reliance on multiple sequence alignment (MSA) is inherently time-consuming due ...
Optimization Strategies for Variational Quantum Algorithms in Noisy Landscapes
Vojtech Novák, Ivan Zelinka, V. Snásel·Jun 2, 2025
Variational Quantum Algorithms (VQAs) are a leading approach for near-term quantum computing but face major optimization challenges from noise, barren plateaus, and complex energy landscapes. We benchmarked more than fifty metaheuristic algorithms fo...
Self-attention U-Net decoder for toric codes
Wei-Wei Zhang, Zhu Xia, Wei Zhao +2 more·Jun 2, 2025
In the NISQ era, one of the most important bottlenecks for the realization of universal quantum computation is error correction. Stabiliser code is the most recognizable type of quantum error correction code. A scalable efficient decoder is most desi...
Workflow decomposition algorithm for scheduling with quantum annealer-based hybrid solver
Marcin Kroczek, Justyna Zawalska, Katarzyna Rycerz·Jun 2, 2025
We introduce the Series-Parallel Workflow Decomposition (SP\-WD) heuristic algorithm for the Workflow Scheduling Problem (WSP) decomposition. We demonstrate that the SPWD algorithm facilitates the scheduling of large WSP instances with the hybrid D-W...
Improved belief propagation is sufficient for real-time decoding of quantum memory
Tristan Muller, Thomas Alexander, M. Beverland +4 more·Jun 2, 2025
We introduce a new heuristic decoder, Relay-BP, targeting real-time quantum circuit decoding for large-scale quantum computers. Relay-BP achieves high accuracy across circuit-noise decoding problems: significantly outperforming BP+OSD+CS-10 for bivar...
Demonstrating magnetic field robustness and reducing temporal T1 noise in transmon qubits through magnetic field engineering
Bektur Abdisatarov, Tanay Roy, D. Bafia +10 more·Jun 2, 2025
The coherence of superconducting transmon qubits is often disrupted by fluctuations in the energy relaxation time (T1), limiting their performance for quantum computing. While background magnetic fields can be harmful to superconducting devices, we d...
Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments
Umberto Gonccalves de Sousa·Jun 2, 2025
This paper presents Q-ARDNS-Multi, an advanced multi-agent quantum reinforcement learning (QRL) framework that extends the ARDNS-FN-Quantum model, where Q-ARDNS-Multi stands for"Quantum Adaptive Reward-Driven Neural Simulator - Multi-Agent". It integ...
Quantum Machine Learning for Predicting Anastomotic Leak: A Clinical Study
V. Nov'ak, Ivan Zelinka, Lenka Pvribylov'a +2 more·Jun 2, 2025
Anastomotic leak (AL) is a life-threatening complication following colorectal surgery, and its accurate prediction remains a significant clinical challenge. This study explores the potential of Quantum Neural Networks (QNNs) for AL prediction, presen...