Tootfinder

Quantencomputer mit Fehlerkorrektur bis 2028: IBM mit ambitionierter Roadmap
IBM will bis 2028 einen Quantencomputer mit Fehlerkorrektur und deutlich höherer Rechenleistung bauen. Der soll über die Cloud verfügbar gemacht werden.

Quantum secret sharing in a triangular superconducting quantum network
Haoxiong Yan, Allen Zang, Joel Grebel, Xuntao Wu, Ming-Han Chou, Gustav Andersson, Christopher R. Conner, Yash J. Joshi, Shiheng Li, Jacob M. Miller, Rhys G. Povey, Hong Qiao, Eric Chitambar, Andrew N. Cleland
https://arxiv.org/abs/2506.10878

Quantum secret sharing in a triangular superconducting quantum network
We present a three-node quantum communication testbed with a triangular topology, each side of the triangle formed by a 1.3-meter-long transmission line. We demonstrate state transfer and entanglement generation between any two nodes, generate genuine multipartite entangled GHZ states, and implement quantum secret sharing (QSS) of classical information. Our experiments show that the QSS protocol can effectively detect eavesdropping, ensuring the secure sharing of secrets. This device forms a te…

Secure Data Access in Cloud Environments Using Quantum Cryptography
S. Vasavi Venkata Lakshmi, Ziaul Haque Choudhury
https://arxiv.org/abs/2506.10028 https…

Secure Data Access in Cloud Environments Using Quantum Cryptography
Cloud computing has made storing and accessing data easier but keeping it secure is a big challenge nowadays. Traditional methods of ensuring data may not be strong enough in the future when powerful quantum computers become available. To solve this problem, this study uses quantum cryptography to protect data in the cloud environment. Quantum Key Distribution (QKD) creates secure keys by sending information using quantum particles like photons. Specifically, we use the BB84 protocol, a simple …

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Waylon Luo (Kent State University), Jiapeng Zhao (Cisco), Tong Zhan (Meta), Qiang Guan (Kent State University)
https://arxiv.org/abs/2506.10889

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Present-day quantum systems face critical bottlenecks, including limited qubit counts, brief coherence intervals, and high susceptibility to errors-all of which obstruct the execution of large and complex circuits. The advancement of quantum algorithms has outpaced the capabilities of existing quantum hardware, making it difficult to scale computations effectively. Additionally, inconsistencies in hardware performance and pervasive quantum noise undermine system stability and computational accu…

Coherence monotones of quantum channels based on two generalized quantum relative entropies
Jiaorui Fan, Zhaoqi Wu, Shao-Ming Fei
https://arxiv.org/abs/2506.10810

Coherence monotones of quantum channels based on two generalized quantum relative entropies
By using the Choi-Jamiołkowski isomorphism, we propose two classes of coherence monotones of quantum channels based on the unified $(r,s)$-relative entropy and the sandwiched Rényi relative entropy. Elegant properties of the coherence monotones for quantum channels are explored. Moreover, we present the upper bounds of the coherence monotones and derive the explicit formulas of the coherence monotones for qubit unitary channels.

Ultrahigh threshold nonstabilizer nonlinear quantum error correcting code
Maga Grafe, Kaixuan Zhou, Zaman Tekin, Zhiyuan Lin, Sen Li, Fengquan Zhang, Valentin Ivannikov, Tim Byrnes
https://arxiv.org/abs/2506.10445

Ultrahigh threshold nonstabilizer nonlinear quantum error correcting code
We introduce a novel type of quantum error correcting code, called the spinor code, based on spaces defined by total spin. The code is a nonstabilizer code, and is also a nonlinear quantum error correcting code, meaning that quantum information is encoded in a parameterized family of quantum states, rather than a linear superposition of code words. Syndrome measurements are performed by projecting on states with differing total spin, with an associated correction to map states back to the maxim…

Unitary Scrambling and Collapse: A Quantum Diffusion Framework for Generative Modeling
Yihua Li, Jiayi Chen, Tamanna S. Kumavat, Kyriakos Flouris
https://arxiv.org/abs/2506.10571 …

Unitary Scrambling and Collapse: A Quantum Diffusion Framework for Generative Modeling
Quantum computing, with its promise of exponential speedups, is rapidly emerging as a powerful paradigm for advancing artificial intelligence. We propose QSC-Diffusion, the first fully quantum diffusion-based framework for image generation. Our method integrates classical Gaussian noise with quantum scrambling in the forward process, and employs parameterized quantum circuits with measurement-induced collapse for reverse denoising -- enabling end-to-end sampling without reliance on classical ne…

Kibble-Zurek dynamical scaling hypothesis in the Google analog-digital quantum simulator of the $XX$ model
Yintai Zhang, Francis A. Bayocboc Jr., Jacek Dziarmaga
https://arxiv.org/abs/2506.10771

Kibble-Zurek dynamical scaling hypothesis in the Google analog-digital quantum simulator of the $XX$ model
The state-of-the-art tensor networks are employed to simulate the Hamiltonian ramp in the analog-digital quantum simulation of the quantum phase transition to the quasi-long-range ordered phase of the 2D square-lattice $XX$ model [Nature 638, 79 (2025)]. We focus on the quantum Kibble-Zurek (KZ) mechanism near the quantum critical point. Using the infinite projected entangled pair state (iPEPS), we simulate an infinite lattice and demonstrate the KZ scaling hypothesis for the $XX$ correlations …

Majorana Signatures in the Tripartite Uncertainty Relations with Quantum Memory
D. Maroulakos (Doctoral School at the University of Rzeszow), C. Jasiukiewicz (Department of Physics and Medical Engineering Rzeszow University of Technology), A. Wal (Institute of Physics Faculty of Exact and Technical Sciences University of Rzeszow), A. Sinner (Institute of Physics University of Opole), I. Weymann (Institute of Spintronics and Quantum Information Faculty of Physics and Astronomy A. Mickie…

Majorana Signatures in the Tripartite Uncertainty Relations with Quantum Memory
Quantumness imposes a fundamental limit on measurement accuracy. The paradigmatic cases are Heisenberg's uncertainty relation in the original formulation, Robertson's formulation, and improved uncertainty relations. However, the more universal measures are given in terms of quantum entropies. Uncertainties of measurements done on one quantum system correlated with another quantum system constitute a more intriguing question. Quantum correlations can influence the lower bound of uncertainties, a…

Toward Scalable Quantum Compilation for Modular Architecture: Qubit Mapping and Reuse via Deep Reinforcement Learning
Sokea Sang, Leanghok Hour, Youngsun Han
https://arxiv.org/abs/2506.09323

Toward Scalable Quantum Compilation for Modular Architecture: Qubit Mapping and Reuse via Deep Reinforcement Learning
Modular quantum architectures have emerged as a promising approach for scaling quantum computing systems by connecting multiple Quantum Processing Units (QPUs). However, this approach introduces significant challenges due to costly inter-core operations between chips and quantum state transfers, which contribute to noise and quantum decoherence. This paper presents QARMA, a novel Qubit mapping using Attention-based deep Reinforcement learning (DRL) for Modular quantum Architectures, along with …