Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Cost scaling of MPS and TTNS simulations for 2D and 3D systems with area-law entanglement
Thomas Barthel·Jan 13, 2026
Tensor network states are an indispensable tool for the simulation of strongly correlated quantum many-body systems. In recent years, tree tensor network states (TTNS) have been successfully used for two-dimensional systems and to benchmark quantum s...
Quantum observers can communicate across multiverse branches
Maria Violaris·Jan 13, 2026
It is commonly thought that observers in distinct branches of an Everettian multiverse cannot communicate without violating the linearity of quantum theory. Here we show a counterexample, demonstrating that inter-branch communication is in fact possi...
Directional Electrical Spiking, Bursting, and Information Propagation in Oyster Mycelium Recorded with a Star-Shaped Electrode Array
Andrew Adamatzky·Jan 13, 2026
Electrical activity in fungal mycelium has been reported in numerous species and experimental contexts, yet its spatial organisation and propagation remain insufficiently characterised. In this study we investigate the spatiotemporal structure of ele...
Multi-level charge fluctuations in a Si/SiGe double quantum dot device
Dylan Albrecht, Feiyang Ye, N. Tobias Jacobson +1 more·Jan 13, 2026
Discrete charge fluctuations, routinely observed in semiconductor quantum dot devices, may contribute significantly to device drift and errors resulting from qubit miscalibration. Understanding the nature and origins of these discrete charge fluctuat...
Learning parameter curves in feedback-based quantum optimization algorithms
Vicente Peña Pérez, Matthew D. Grace, Christian Arenz +1 more·Jan 13, 2026
Feedback-based quantum algorithms (FQAs) operate by iteratively growing a quantum circuit to optimize a given task. At each step, feedback from qubit measurements is used to inform the next quantum circuit update. In practice, the sampling cost assoc...
A Differential Geometry and Algebraic Topology Based Public-Key Cryptographic Algorithm in Presence of Quantum Adversaries
Andrea Rondelli·Jan 13, 2026
In antiquity, the seal embodied trust, secrecy, and integrity in safeguarding the exchange of letters and messages. The purpose of this work is to continue this tradition in the contemporary era, characterized by the presence of quantum computers, cl...
Spin qubit shuttling between coupled quantum dots with inhomogeneous Landé <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>g</mml:mi> </mml:math> factors
Zhi-Hai Liu, Xiao-Fei Liu, H. Q. Xu +5 more·Jan 13, 2026
By utilizing the site-dependent spin quantization axis in semiconductor quantum dot (QD) arrays, shuttling-based spin qubit gates have become an appealing approach to realize scalable quantum computing due to the circumvention of using high-frequency...
Hierarchical Precision and Recursion for Accelerating Symmetric Linear Solves on MXUs
Vicki Carrica, Rabab Alomairy, Evelyne Ringoot +1 more·Jan 12, 2026
Symmetric linear solves are fundamental to a wide range of scientific and engineering applications, from climate modeling and structural analysis to machine learning and optimization. These workloads often rely on Cholesky (POTRF) decomposition and i...
Monte Carlo to Las Vegas for Recursively Composed Functions
Bandar Al-Dhalaan, Shalev Ben-David·Jan 12, 2026
For a (possibly partial) Boolean function $f\colon\{0,1\}^n\to\{0,1\}$ as well as a query complexity measure $M$ which maps Boolean functions to real numbers, define the composition limit of $M$ on $f$ by $M^*(f)=\lim_{k\to\infty} M(f^k)^{1/k}$. We s...
Quantum Energetic Advantage before Computational Advantage in Boson Sampling
Ariane Soret, Nessim Dridi, Stephen C. Wein +3 more·Jan 12, 2026
Understanding the energetic efficiency of quantum computers is essential for assessing their scalability and for determining whether quantum technologies can outperform classical computation beyond runtime alone. In this work, we analyze the energy r...
On measurement-dependent variance in quantum neural networks
Andrey Kardashin, Konstantin Antipin·Jan 12, 2026
Variational quantum circuits have become a widely used tool for performing quantum machine learning (QML) tasks on labeled quantum states. In some specific tasks or for specific variational ansätze, one may perform measurements on a restricted part o...
Learning Better Error Correction Codes with Hybrid Quantum-Assisted Machine Learning
Yariv Yanay·Jan 12, 2026
Quantum error correction is one of the fundamental building blocks of digital quantum computation. The Quantum Lego formalism has introduced a systematic way of constructing new stabilizer codes out of basic lego-like building blocks, which in previo...
Interferometric discrepancy between the non-relativistic solution to the Klein-Gordon and Schrödinger wave equations due to their dissimilar phase velocities
Frank Victor Kowalski·Jan 12, 2026
Adding a constant energy offset leaves classical dynamics unchanged. In quantum mechanics it changes the phase velocity of the wavefunction. The inclusion of the constant rest energy in the Klein-Gordon formulation leads to significantly higher phase...
Quantum automated theorem proving
Zheng-Zhi Sun, Qi Ye, Dong-Ling Deng·Jan 12, 2026
Automated theorem proving, or more broadly automated reasoning, aims at using computer programs to automatically prove or disprove mathematical theorems and logical statements. It takes on an essential role across a vast array of applications and the...
Attention in Krylov Space
Zihao Qi, Christopher Earls·Jan 12, 2026
The Universal Operator Growth Hypothesis formulates time evolution of operators through Lanczos coefficients. In practice, however, numerical instability and memory cost limit the number of coefficients that can be computed exactly. In response to th...
Data-driven learning of non-Markovian quantum dynamics
Samuel Goodwin, Brian K. McFarland, Manuel H. Muñoz-Arias +6 more·Jan 12, 2026
Fault-tolerant quantum computing requires extremely precise knowledge and control of qubit dynamics during the application of a gate. We develop a data-driven learning protocol for characterizing quantum gates that builds off previous work on learnin...
Bohmian mechanics: A legitimate hydrodynamic picture for quantum mechanics, and beyond
A. S. Sanz·Jan 12, 2026
Since its inception, Bohmian mechanics has been surrounded by a halo of controversy. Originally proposed to bypass the limitations imposed by von Neumann's theorem on the impossibility of hidden-variable models in quantum mechanics, it faced strong o...
Mechanical Resonator-based Quantum Computing
Yu Yang, Igor Kladaric, Martynas Skrabulis +11 more·Jan 12, 2026
Hybrid quantum systems combine the unique advantages of different physical platforms with the goal of realizing more powerful and practical quantum information processing devices. Mechanical systems, such as bulk acoustic wave resonators, feature a l...
Computing quantum magic of state vectors
Piotr Sierant, Jofre Vallès-Muns, Artur Garcia-Saez·Jan 12, 2026
Non-stabilizerness, also known as ``magic,'' quantifies how far a quantum state departs from the stabilizer set. It is a central resource behind quantum advantage and a useful probe of the complexity of quantum many-body states. Yet standard magic qu...
Measurement-based acceleration of optical computations
I. V. Vovchenko, A. A. Zyablovsky, A. A. Pukhov +1 more·Jan 12, 2026
Analog coprocessors are intensively developing nowadays with the aim to optimize energy computations of neural networks. In this work we focus on the possibility of using detection of collective oscillations in optical systems for computational purpo...