📊 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
−Scalable modular architecture for universal quantum computation
Fernando Gago-Encinas, Christiane P. Koch • Published: 2025-07-19
Universal quantum computing requires the ability to perform every unitary
operation, i.e., evolution operator controllability. In view of developing
resource-efficient quantum processing units (QPUs), it is important to
determine how many local controls and qubit-qubit couplings are required for
controllability. Unfortunately, assessing the controllability of large qubit
arrays is a difficult task...
Benchmarking Quantum Computers: Towards a Standard Performance Evaluation Approach
Arturo Acuaviva, David Aguirre, Rubén Peña, Mikel Sanz • Published: 2024-07-15
The technological development of increasingly larger quantum processors on
different quantum platforms raises the problem of how to fairly compare their
performance, known as quantum benchmarking of quantum processors. This is a
challenge that computer scientists have already faced when comparing classical
processors, leading to the development of various mathematical tools to address
it, but also...
Bridging Quantum Computing and Nuclear Structure: Atomic Nuclei on a Trapped-Ion Quantum Computer
Sota Yoshida, Takeshi Sato, Takumi Ogata, Masaaki Kimura • Published: 2025-09-25
We report accurate quantum simulations of medium-mass atomic nuclei
-including oxygen, calcium, and nickel- on the RIKEN-Quantinuum Reimei
trapped-ion quantum computer, achieving sub-percent accuracy. Using a
symmetry-aware pair-unitary coupled-cluster doubles (pUCCD) ansatz implemented
with a hard-core-boson mapping, and with particle-number-restoring
post-selection, our ground-state energy estim...
(2+1)D Quantum Electrodynamics at Finite Density on a Quantum Computer
Emil Otis Rosanowski, Arianna Crippa, Lena Funcke, Paulo Vitor Itaborai, Karl Jansen, Simran Singh • Published: 2025-09-24
In this paper, we explore (2+1)D quantum electrodynamics (QED) at finite
density on a quantum computer, including two fermion flavors. Our method
employs an efficient gauge-invariant ansatz together with a quantum circuit
structure that enforces Gauss's law. As a proof of principle, we benchmark our
simulation protocol on a small lattice system, demonstrating the identification
of phase transition...
Quantum computing on encrypted data with arbitrary rotation gates
Mohit Joshi, Manoj Kumar Mishra, S. Karthikeyan • Published: 2025-08-26
An efficient technique of computing on encrypted data allows a client with
limited capability to perform complex operations on a remote fault-tolerant
server without leaking anything about the input or output. Quantum computing
provides information-theoretic security to solve such a problem, and many such
techniques have been proposed under the premises of half-blind quantum
computation. However, ...
Efficient Preparation of Resource States for Hamiltonian Simulation and Universal Quantum Computation
Thierry N. Kaldenbach, Isaac D. Smith, Hendrik Poulsen Nautrup, Matthias Heller, Hans J. Briegel • Published: 2025-09-05
The direct compilation of algorithm-specific graph states in
measurement-based quantum computation (MBQC) can lead to resource reductions in
terms of circuit depth, entangling gates, and even the number of physical
qubits. In this work, we extend previous studies on algorithm-tailored graph
states to periodic sequences of generalized Pauli rotations, which commonly
appear in, e.g., Trotterized Ham...
Quantum circuit compilation with quantum computers
Davide Rattacaso, Daniel Jaschke, Marco Ballarin, Ilaria Siloi, Simone Montangero • Published: 2024-07-31
Compilation optimizes quantum algorithms performances on real-world quantum
computers. To date, it is performed via classical optimization strategies. We
introduce a class of quantum algorithms to perform compilation via quantum
computers, paving the way for a quantum advantage in compilation. We
demonstrate the effectiveness of this approach via Quantum and Simulated
Annealing-based compilation: ...
A Taxonomy of Data Risks in AI and Quantum Computing (QAI) - A Systematic Review
Grace Billiris, Asif Gill, Madhushi Bandara • Published: 2025-09-24
Quantum Artificial Intelligence (QAI), the integration of Artificial
Intelligence (AI) and Quantum Computing (QC), promises transformative advances,
including AI-enabled quantum cryptography and quantum-resistant encryption
protocols. However, QAI inherits data risks from both AI and QC, creating
complex privacy and security vulnerabilities that are not systematically
studied. These risks affect t...
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-Zaczek • Published: 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 ...
Quantum Computing Beyond Ground State Electronic Structure: A Review of Progress Toward Quantum Chemistry Out of the Ground State
Alan Bidart, Prateek Vaish, Tilas Kabengele, Yaoqi Pang, Yuan Liu, Brenda M. Rubenstein • Published: 2025-09-24
Quantum computing offers the promise of revolutionizing quantum chemistry by
enabling the solution of chemical problems for substantially less computational
cost. While most demonstrations of quantum computation to date have focused on
resolving the energies of the electronic ground states of small molecules, the
field of quantum chemistry is far broader than ground state chemistry; equally
import...
🏢 Company Papers
−Clustering methods for Categorical Time Series and Sequences : A scoping review
Ottavio Khalifa, Viet-Thi Tran, Alan Balendran, François Petit • Published: 2025-09-09
Objective: To provide an overview of clustering methods for categorical time
series (CTS), a data structure commonly found in epidemiology, sociology,
biology, and marketing, and to support method selection in regards to data
characteristics.
Methods: We searched PubMed, Web of Science, and Google Scholar, from
inception up to November 2024 to identify articles that propose and evaluate
clusteri...
Scalable modular architecture for universal quantum computation
Fernando Gago-Encinas, Christiane P. Koch • Published: 2025-07-19
Universal quantum computing requires the ability to perform every unitary
operation, i.e., evolution operator controllability. In view of developing
resource-efficient quantum processing units (QPUs), it is important to
determine how many local controls and qubit-qubit couplings are required for
controllability. Unfortunately, assessing the controllability of large qubit
arrays is a difficult task...
What Do LLM Agents Do When Left Alone? Evidence of Spontaneous Meta-Cognitive Patterns
Stefan Szeider • Published: 2025-09-25
We introduce an architecture for studying the behavior of large language
model (LLM) agents in the absence of externally imposed tasks. Our continuous
reason and act framework, using persistent memory and self-feedback, enables
sustained autonomous operation. We deployed this architecture across 18 runs
using 6 frontier models from Anthropic, OpenAI, XAI, and Google. We find agents
spontaneously o...
Vision Transformers: the threat of realistic adversarial patches
Kasper Cools, Clara Maathuis, Alexander M. van Oers, Claudia S. Hübner, Nikos Deligiannis, Marijke Vandewal, Geert De Cubber • Published: 2025-09-25
The increasing reliance on machine learning systems has made their security a
critical concern. Evasion attacks enable adversaries to manipulate the
decision-making processes of AI systems, potentially causing security breaches
or misclassification of targets. Vision Transformers (ViTs) have gained
significant traction in modern machine learning due to increased 1) performance
compared to Convolut...
Byam: Fixing Breaking Dependency Updates with Large Language Models
Frank Reyes, May Mahmoud, Federico Bono, Sarah Nadi, Benoit Baudry, Martin Monperrus • Published: 2025-05-12
Application Programming Interfaces (APIs) facilitate the integration of
third-party dependencies within the code of client applications. However,
changes to an API, such as deprecation, modification of parameter names or
types, or complete replacement with a new API, can break existing client code.
These changes are called breaking dependency updates; It is often tedious for
API users to identify ...
Application of Audio Fingerprinting Techniques for Real-Time Scalable Speech Retrieval and Speech Clusterization
Kemal Altwlkany, Sead Delalić, Adis Alihodžić, Elmedin Selmanović, Damir Hasić • Published: 2024-10-29
Audio fingerprinting techniques have seen great advances in recent years,
enabling accurate and fast audio retrieval even in conditions when the queried
audio sample has been highly deteriorated or recorded in noisy conditions.
Expectedly, most of the existing work is centered around music, with popular
music identification services such as Apple's Shazam or Google's Now Playing
designed for indiv...
AnywhereVLA: Language-Conditioned Exploration and Mobile Manipulation
Konstantin Gubernatorov, Artem Voronov, Roman Voronov, Sergei Pasynkov, Stepan Perminov, Ziang Guo, Dzmitry Tsetserukou • Published: 2025-09-25
We address natural language pick-and-place in unseen, unpredictable indoor
environments with AnywhereVLA, a modular framework for mobile manipulation. A
user text prompt serves as an entry point and is parsed into a structured task
graph that conditions classical SLAM with LiDAR and cameras, metric semantic
mapping, and a task-aware frontier exploration policy. An approach planner then
selects vis...
Tracking spin qubit frequency variations over 912 days
Kenji Capannelli, Brennan Undseth, Irene Fernández de Fuentes, Eline Raymenants, Florian K. Unseld, Oriol Pietx-Casas, Stephan G. J. Philips, Mateusz T. Mądzik, Sergey V. Amitonov, Larysa Tryputen, Giordano Scappucci, Lieven M. K. Vandersypen • Published: 2025-09-25
Solid-state qubits are sensitive to their microscopic environment, causing
the qubit properties to fluctuate on a wide range of timescales. The sub-Hz end
of the spectrum is usually dealt with by repeated background calibrations,
which bring considerable overhead. It is thus important to characterize and
understand the low-frequency variations of the relevant qubit characteristics.
In this study, ...
📚 Highlighted Papers
−Quantum enhanced Monte Carlo simulation for photon interaction cross sections
Authors: Euimin Lee, Sangmin Lee, Shiho Kim • Submitted: Submitted • arXiv: arXiv:2502.14374
Abstract: â¦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 Sevior • Submitted: Submitted • arXiv: arXiv:2502.14225
Abstract: â¦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. Geller • Submitted: Submitted • arXiv: arXiv:2502.13910
Abstract: â¦-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...