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Daily Quantum Computing Research & News • October 20, 2025 • 04:19 CST

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📊 Today's Data Collection

News items: 15 articles gathered
Technology papers: 10 papers fetched
Company papers: 8 papers from major players
Highlighted papers: 5 papers collected
Total sources: 5 data feeds processed

📰 News Items

📄 Technology Papers

A recipe for local simulation of strongly-correlated fermionic matter on quantum computers: the 2D Fermi-Hubbard model

Arash Jafarizadeh, Frank Pollmann, Adam Gammon-SmithPublished: 2024-08-26
The simulation of quantum many-body systems, relevant for quantum chemistry and condensed matter physics, is one of the most promising applications of near-term quantum computers before fault-tolerance. However, since the vast majority of quantum computing technologies are built around qubits and discrete gate-based operations, the translation of the physical problem into this framework is a cruci...

Achieving Sub-Exponential Speedup in Gate-Based Quantum Computing for Quadratic Unconstrained Binary Optimization

Tseng Ying-Wei, Kao Yu-Ting, Chang Yeong-Jar, Ou Chia-Ho, Chang Wen-ChihPublished: 2025-10-17
Recent quantum-inspired methods based on the Simulated Annealing (SA) algorithm have shown strong potential for solving combinatorial optimization problems. However, Grover's algorithm [1] in gate-based quantum computing offers only a quadratic speedup, which remains impractical for large problem sizes. This paper proposes a hybrid approach that integrates SA with Grover's algorithm to achieve sub...

Quantum Computing Tools for Fast Detection of Gravitational Waves in the Context of LISA Space Mission

Maria-Catalina Isfan, Laurentiu-Ioan Caramete, Ana Caramete, Daniel Tonoiu, Alexandru Nicolin-ŻaczekPublished: 2025-09-16
The field of gravitational wave (GW) detection is progressing rapidly, with several next-generation observatories on the horizon, including LISA. GW data is challenging to analyze due to highly variable signals shaped by source properties and the presence of complex noise. These factors emphasize the need for robust, advanced analysis tools. In this context, we have initiated the development of a ...

Cryo-CMOS Antenna for Wireless Communications within a Quantum Computer Cryostat

Viviana Centritto, Ama Bandara, Heqi Deng, Masoud Babaie, Evgenii Vinogradov, Sergi Abadal, Eduard AlarconPublished: 2025-10-15
Scaling quantum computers from a few qubits to large numbers remains one of the critical challenges in realizing practical quantum advantage. Multi-core quantum architectures have emerged as a promising solution, enabling scalability through distributed quantum processing units (QPUs) interconnected via classical and quantum links. However, the bottleneck of wired connections persists, as densely ...

Emergent Discrete Time Crystals on Digital Quantum Computers: Boundary-Protected and Ancilla-Induced Disorder Mechanisms of Thermalization Slowdown

Kazuya Shinjo, Kazuhiro Seki, Seiji YunokiPublished: 2025-10-15
Periodically driven (Floquet) systems typically evolve toward an infinite-temperature thermal state due to continuous energy absorption. Before reaching equilibrium, however, they can transiently exhibit long-lived prethermal states that host exotic nonequilibrium phenomena, such as discrete time crystals (DTCs). In this study, we investigate the relaxation dynamics of periodically driven product ...

State-Specific Orbital Optimization for Enhanced Excited-States Calculation on Quantum Computers

Guorui Zhu, Joel Bierman, Jianfeng Lu, Yingzhou LiPublished: 2025-10-15
We propose a state-specific orbital optimization scheme for improving the accuracy of excited states of the electronic structure Hamiltonian for the use on near-term quantum computers, which can be combined with any overlap-based excited-state quantum eigensolver. We derived the gradient of the overlap term between different states generated by different orbitals with respect to the orbital rotati...

Lattice surgery with Bell measurements: Modular fault-tolerant quantum computation at low entanglement cost

Trond Hjerpekjøn Haug, Timo Hillmann, Anton Frisk Kockum, Raphaël Van LaerPublished: 2025-10-15
Modular architectures are a promising approach to scaling quantum computers to fault tolerance. Small, low-noise quantum processors connected through relatively noisy quantum links are capable of fault-tolerant operation as long as the noise can be confined to the interface. Finding protocols that implement the quantum links between modules as efficiently as possible is essential because inter-mod...

Performance Comparison of Gate-Based and Adiabatic Quantum Computing for Power Flow Analysis

Zeynab Kaseb, Matthias Moller, Peter Palensky, Pedro P. VergaraPublished: 2025-10-15
In this paper, we present the first direct comparison between gate-based quantum computing (GQC) and adiabatic quantum computing (AQC) for solving the AC power flow (PF) equations. Building on the Adiabatic Quantum Power Flow (AQPF) algorithm originally designed for annealing platforms, we adapt it to the Quantum Approximate Optimization Algorithm (QAOA). The PF equations are reformulated as a com...

A low-circuit-depth quantum computing approach to the nuclear shell model

Chandan Sarma, Paul StevensonPublished: 2025-10-02
In this work, we introduce a new qubit mapping strategy for the Variational Quantum Eigensolver (VQE) applied to nuclear shell model calculations, where each Slater determinant (SD) is mapped to a qubit, rather than assigning qubits to individual single-particle states. While this approach may increase the total number of qubits required in some cases, it enables the construction of simpler quantu...

Privacy-Aware Framework of Robust Malware Detection in Indoor Robots: Hybrid Quantum Computing and Deep Neural Networks

Tan Le, Van Le, Sachin ShettyPublished: 2025-10-15
Indoor robotic systems within Cyber-Physical Systems (CPS) are increasingly exposed to Denial of Service (DoS) attacks that compromise localization, control and telemetry integrity. We propose a privacy-aware malware detection framework for indoor robotic systems, which leverages hybrid quantum computing and deep neural networks to counter DoS threats in CPS, while preserving privacy information. ...

🏢 Company Papers

Funky: Cloud-Native FPGA Virtualization and Orchestration

Atsushi Koshiba, Charalampos Mainas, Pramod BhatotiaPublished: 2025-10-17
The adoption of FPGAs in cloud-native environments is facing impediments due to FPGA limitations and CPU-oriented design of orchestrators, as they lack virtualization, isolation, and preemption support for FPGAs. Consequently, cloud providers offer no orchestration services for FPGAs, leading to low scalability, flexibility, and resiliency. This paper presents Funky, a full-stack FPGA-aware orch...

Generation of multipartite photonic entanglement using a trapped-ion quantum processing node

Marco Canteri, James Bate, Ida Mishra, Nicolai Friis, Victor Krutyanskiy, Benjamin P. LanyonPublished: 2025-10-17
The ability to establish entanglement between the nodes of future quantum networks is essential for enabling a wide range of new applications in science and technology. A promising approach involves the use of a powerful central node capable of deterministically preparing arbitrary multipartite entangled states of its matter-based qubits and efficiently distributing these states to surrounding end...

Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks

Lorenzo Pes, Bojian Yin, Sander Stuijk, Federico CorradiPublished: 2025-09-16
Spiking Neural Networks (SNNs) provide an efficient framework for processing dynamic spatio-temporal signals and for investigating the learning principles underlying biological neural systems. A key challenge in training SNNs is to solve both spatial and temporal credit assignment. The dominant approach for training SNNs is Backpropagation Through Time (BPTT) with surrogate gradients. However, BPT...

Balancing Fairness and Performance in Multi-User Spark Workloads with Dynamic Scheduling (extended version)

Dāvis Kažemaks, Laurens Versluis, Burcu Kulahcioglu Ozkan, Jérémie DecouchantPublished: 2025-10-17
Apache Spark is a widely adopted framework for large-scale data processing. However, in industrial analytics environments, Spark's built-in schedulers, such as FIFO and fair scheduling, struggle to maintain both user-level fairness and low mean response time, particularly in long-running shared applications. Existing solutions typically focus on job-level fairness which unintentionally favors user...

NbTiN Nanowire Resonators for Spin-Photon Coupling on Solid Neon

Y. Tian, I. Grytsenko, A. Jennings, J. Wang, H. Ikegami, X. Zhou, S. Tamate, H. Terai, H. Kutsuma, D. Jin, M. Benito, E. KawakamiPublished: 2025-05-30
Electrons floating on a solid neon exhibit long charge coherence times, making them attractive for hybrid quantum systems. When combined with high-quality, high-impedance superconducting resonators and a local magnetic field gradient, this platform enables strong charge--photon and spin--charge coupling-key ingredients for scalable spin qubit architectures. In this work, we demonstrate that NbTiN ...

ASBI: Leveraging Informative Real-World Data for Active Black-Box Simulator Tuning

Gahee Kim, Takamitsu MatsubaraPublished: 2025-10-17
Black-box simulators are widely used in robotics, but optimizing their parameters remains challenging due to inaccessible likelihoods. Simulation-Based Inference (SBI) tackles this issue using simulation-driven approaches, estimating the posterior from offline real observations and forward simulations. However, in black-box scenarios, preparing observations that contain sufficient information for ...

Capturing Protein Free Energy Landscape using Efficient Quantum Encoding

Ashwini Kannan, Jaya Vasavi Pamidimukkala, Avinash Dakshinamoorthy, Soham Bopardikar, Kalyan Dasgupta, Sanjib SenapatiPublished: 2025-10-17
Protein folding is one of the age-old biological problems that refers to the mechanism of understanding and predicting how a protein's linear sequence of amino acids folds into its specific three dimensional structure.This structure is critical, as a protein's functionality is inherently linked to its final folded form. Misfolding can lead to severe diseases such as Alzheimer's and cystic fibrosis...

Fundamental Limits to Cat-Code Qubits from Chaos-Assisted Tunneling

Lionel E. Martínez, Ignacio García-Mata, Diego A. WisniackiPublished: 2025-10-16
We show that chaos-assisted tunneling (CAT) imposes an intrinsic limit to the protection of Kerr-cat qubits. In the static effective description, tunneling between the quasi-degenerate cat states can be exponentially suppressed, ensuring long lifetimes. However, our Floquet analysis reveals that when the nonlinearities increase, chaotic states mediate tunneling between the cat states, producing la...

📚 Highlighted Papers

Quantum enhanced Monte Carlo simulation for photon interaction cross sections

Authors: Euimin Lee, Sangmin Lee, Shiho KimSubmitted: Submitted arXiv: arXiv:2502.14374
Abstract: …as the dominant attenuation mechanism, we demonstrate that our approach reproduces classical probability distributions with high fidelity. Simulation results obtained via the IBM Qiskit quantum simulator reveal a quadratic speedup in amplitude estimation compared to conventional Monte C...

Time-adaptive single-shot crosstalk detector on superconducting quantum computer

Authors: Haiyue Kang, Benjamin Harper, Muhammad Usman, Martin SeviorSubmitted: Submitted arXiv: arXiv:2502.14225
Abstract: …in two scenarios: simulation using an artificial noise model with gate-induced crosstalk and always-on idlings channels; and the simulation using noise sampled from an IBM quantum computer parametrised by the reduced HSA error model. The presented results show our method's efficacy hing...

Quantum simulation of a qubit with non-Hermitian Hamiltonian

Authors: Anastashia Jebraeilli, Michael R. GellerSubmitted: Submitted arXiv: arXiv:2502.13910
Abstract: …-broken regime surrounding an exceptional point. Quantum simulations are carried out using IBM superconducting qubits. The results underscore the potential for variational quantum circuits and machine learning to push the boundaries of quantum simulation, offering new methods for explor...

Comment on "Energy-speed relationship of quantum particles challenges Bohmian mechanics"

Aurélien Drezet, Dustin Lazarovici, Bernard Michael Nabet
In their recent paper [Nature 643, 67 (2025)], Sharaglazova et al. report an optical microcavity experiment yielding an "energy-speed relationship" for quantum particles in evanescent states, which they infer from the observed population transfer between two coupled waveguides. The authors argue tha...