Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Impact of control signal phase noise on qubit fidelity
Agata Barsotti, Paolo Marconcini, Gregorio Procissi +1 more·Jan 13, 2026
As qubit decoherence times are increased and readout technologies are improved, nonidealities in the drive signals, such as phase noise, are going to represent a crucial limitation to the fidelity achievable at the end of complex control pulse sequen...
Quantifying the Relationship Between Strain and Bandgap in Thin Ga$_2$Se$_2$
Lottie L. Murray, Eric Herrmann, Igor Evangelista +3 more·Jan 13, 2026
We present a rigorous analysis that combines theory, simulation, and experimental measurements to quantify the relationship between strain and bandgap in two dimensional gallium selenide (Ga$_2$Se$_2$). Experimentally, we transfer thin Ga$_2$Se$_2$ f...
Enhancing classical simulation with noisy quantum devices
Ruiqi Zhang, Fuchuan Wei, Zhaohui Wei·Jan 13, 2026
As quantum devices continue to improve in scale and precision, a central challenge is how to effectively utilize noisy hardware for meaningful computation. Most existing approaches aim to recover noiseless circuit outputs from noisy ones through erro...
Local Magnetometry from Measurement-Induced Dissipation
Rishith Reddy, Parveen Kumar, Ankur Das·Jan 13, 2026
Magnetic phases are commonly identified through macroscopic magnetization, yet many ordered states, including antiferromagnets and altermagnets, possess a vanishing net moment despite distinct local spin structure. We show that such an order can be a...
Attosecond quantum optics
Mohamed Sennary, Javier Rivera-Dean, Yihe Wange +2 more·Jan 13, 2026
Modern quantum optics primarily operates in the quasistationary regime, isolated from the intrinsic timescales of ultrafast optical fields. Pushing these boundaries into the femtosecond and attosecond domains is a critical frontier. Here, we generate...
Open quantum spin chains with non-reciprocity: a theoretical approach based on the time-dependent generalized Gibbs ensemble
Alice Marché, Hironobu Yoshida, Alberto Nardin +2 more·Jan 13, 2026
We study an open quantum spin chain with non-reciprocal dissipation using a theoretical approach known as time-dependent generalized Gibbs ensemble. In the regime of weak dissipation the system is fully characterized by its rapidity distribution and ...
Symmetry-Adapted State Preparation for Quantum Chemistry on Fault-Tolerant Quantum Computers
Viktor Khinevich, Wataru Mizukami·Jan 13, 2026
We present systematic and resource-efficient constructions of continuous symmetry projectors, particularly $U(1)$ particle number and $SU(2)$ total spin, tailored for fault-tolerant quantum computations. Our approach employs a linear combination of u...
Toolchain for shuttling trapped-ion qubits in segmented traps
Andreas Conta, Santiago Bogino, Frodo Köhncke +2 more·Jan 13, 2026
Scalable trapped-ion quantum computing requires fast and reliable transport of ions through complex, segmented radiofrequency trap architectures without inducing excessive motional excitation. We present a numerical toolchain for the systematic gener...
Dissipative ground-state preparation of a quantum spin chain on a trapped-ion quantum computer
Kazuhiro Seki, Yuta Kikuchi, Tomoya Hayata +1 more·Jan 13, 2026
We demonstrate a dissipative protocol for ground-state preparation of a quantum spin chain on a trapped-ion quantum computer. As a first step, we derive a Kraus representation of a dissipation channel for the protocol recently proposed by Ding et al....
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...
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...
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...
Phase transition, phase separation and mode softening of a two-component Bose-Einstein condensate in an optical cavity
Jia-Ying Lin, Wei Qin, Renyuan Liao·Jan 12, 2026
We investigate the superradiant phase transition in a two-component Bose-Einstein condensate with distinct atomic detunings, confined in an optical cavity and driven by a transverse pump laser. By combining perturbation theory and numerical simulatio...
Bias-Aware BP Decoding of Quantum Codes via Directional Degeneracy
Mohammad Rowshan·Jan 12, 2026
We study directionally informed belief propagation (BP) decoding for quantum CSS codes, where anisotropic Tanner-graph structure and biased noise concentrate degeneracy along preferred directions. We formalize this by placing orientation weights on T...
Reply to Comment on "Properties and dynamics of generalized squeezed states"
Sahel Ashhab, Mohammad Ayyash·Jan 12, 2026
In our paper [1], our numerical simulations showed that, unlike displacement and conventional squeezing, higher-order squeezing exhibits oscillatory dynamics. Subsequently, Gordillo and Puebla pointed out that simulation results depend on whether the...
Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach
Ratun Rahman, Shaba Shaon, Dinh C. Nguyen·Jan 11, 2026
Quantum federated learning (QFL) emerges as a powerful technique that combines quantum computing with federated learning to efficiently process complex data across distributed quantum devices while ensuring data privacy in quantum networks. Despite r...
XBTorch: A Unified Framework for Modeling and Co-Design of Crossbar-Based Deep Learning Accelerators
Osama Yousuf, Andreu L. Glasmann, Martin Lueker-Boden +2 more·Jan 11, 2026
Emerging memory technologies have gained significant attention as a promising pathway to overcome the limitations of conventional computing architectures in deep learning applications. By enabling computation directly within memory, these technologie...
Stochastic phase-space simulation of multimode cat states via the positive-P representation
Yi Shi, Alex Ferrier, Piotr Deuar +2 more·Jan 11, 2026
We present a comprehensive study of the transient dynamics of multimode Schrödinger cat states in dissipatively coupled resonator arrays using the positive-P phase-space method. By employing the positive-P representation, we derive the exact stochast...
Extending the Handover-Iterative VQE to Challenging Strongly Correlated Systems: $N_2$ and Fe-S Cluster
Pilsun Yoo, Kyungmin Kim, Eyuel E. Elala +10 more·Jan 11, 2026
Accurately describing strongly correlated electronic systems remains a central challenge in quantum chemistry, as electron-electron interactions give rise to complex many-body wavefunctions that are difficult to capture with conventional approximatio...
High-capacity dual degrees of freedom quantum secret sharing protocol beyond the linear rate-distance bound
Meng-Dong Zhu, Cheng Zhang, Shi-Pu Gu +5 more·Jan 11, 2026
Quantum secret sharing (QSS) is the multipartite cryptographic primitive. Most of existing QSS protocols are limited by the linear rate-distance bound, and cannot realize the long-distance and high-capacity multipartite key distribution. This paper p...