Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Generalized geometric speed limits for quantum observables
J. Bringewatt, Zach Steffen, Martin Ritter +6 more·Sep 6, 2024
Leveraging quantum information geometry, we derive generalized quantum speed limits on the rate of change of the expectation values of observables. These bounds subsume and, for Hilbert space dimension $\geq 3$, tighten existing bounds -- in some cas...
Geometrical Approach to Logical Qubit Fidelities of Neutral Atom CSS Codes
Jasper J. Postema, S. Kokkelmans·Sep 6, 2024
Encoding quantum information in a quantum error correction (QEC) code enhances protection against errors. Imperfection of quantum devices due to decoherence effects will limit the fidelity of quantum gate operations. In particular, neutral atom quant...
Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems
Freya Shah, Taylor L. Patti, Julius Berner +3 more·Sep 5, 2024
Fourier Neural Operators (FNOs) excel on tasks using functional data, such as those originating from partial differential equations. Such characteristics render them an effective approach for simulating the time evolution of quantum wavefunctions, wh...
Enhancing the performance of variational quantum classifiers with hybrid autoencoders
Georgios Maragkopoulos, Aikaterini Mandilara, Antonia Tsili +1 more·Sep 5, 2024
Variational quantum circuits (VQC) lie at the forefront of quantum machine learning research. Still, the use of quantum networks for real data processing remains challenging as the number of available qubits cannot accommodate a large dimensionality ...
Predicting quantum channels over general product distributions
Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh +3 more·Sep 5, 2024
We investigate the problem of predicting the output behavior of unknown quantum channels. Given query access to an $n$-qubit channel $E$ and an observable $O$, we aim to learn the mapping \begin{equation*} \rho \mapsto \mathrm{Tr}(O E[\rho]) \end{equ...
Splitting and connecting singlets in atomic quantum circuits
Zijie Zhu, Yann Kiefer, Samuel Jele +4 more·Sep 4, 2024
Gate operations composed in quantum circuits form the basis for digital quantum simulation and quantum processing. While two-qubit gates generally operate on nearest neighbours, many circuits require nonlocal connectivity and necessitate some form of...
QHDOPT: A Software for Nonlinear Optimization with Quantum Hamiltonian Descent
Samuel Kushnir, J. Leng, Yuxiang Peng +2 more·Sep 4, 2024
We develop an open-source, end-to-end software (named QHDOPT), which can solve nonlinear optimization problems using the quantum Hamiltonian descent (QHD) algorithm. QHDOPT offers an accessible interface and automatically maps tasks to various suppor...
Learning out-of-time-ordered correlators with classical kernel methods
John Tanner, J. Pye, Jingbo B. Wang·Sep 3, 2024
Out-of-Time Ordered Correlators (OTOCs) are widely used to investigate information scrambling in quantum systems. However, directly computing OTOCs with classical computers is an expensive procedure. This is due to the need to classically simulate th...
An almost-linear time decoding algorithm for quantum LDPC codes under circuit-level noise
Antonio deMarti iOlius, Imanol Martinez, Joschka Roffe +1 more·Sep 2, 2024
Fault-tolerant quantum computers must be designed in conjunction with classical co-processors that decode quantum error correction measurement information in real-time. In this work, we introduce the belief propagation plus ordered Tanner forest (BP+...
Optimal training of finitely sampled quantum reservoir computers for forecasting of chaotic dynamics
Osama Ahmed, Felix Tennie, Luca Magri·Sep 2, 2024
In the current Noisy Intermediate Scale Quantum (NISQ) era, the presence of noise deteriorates the performance of quantum computing algorithms. Quantum reservoir computing (QRC) is a type of quantum machine learning algorithm, which, however, can ben...
Optimal displacement detection of arbitrarily-shaped levitated dielectric objects using optical radiation
Shaun Laing, Shelby Klomp, George Winstone +6 more·Sep 1, 2024
Optically-levitated dielectric objects are promising for precision force, acceleration, torque, and rotation sensing due to their extreme environmental decoupling. While many levitated opto-mechanics experiments employ spherical objects, for some app...
Resource state generation for a multispin register in a hybrid matter-photon quantum information processor
Yu Liu, Martin B. Plenio·Aug 30, 2024
Hybrid quantum architectures that integrate matter and photonic degrees of freedom present a promising pathway toward scalable, fault-tolerant quantum computing. This approach needs to combine well-established entangling operations between distant re...
Diagnosing crosstalk in large-scale QPUs using zero-entropy classical shadows
J. A. Montañez-Barrera, G. Beretta, K. Michielsen +1 more·Aug 30, 2024
As quantum processing units (QPUs) scale toward hundreds of qubits, diagnosing noise-induced correlations (crosstalk) becomes critical for reliable quantum computation. In this work, we introduce Zero-Entropy Classical Shadows (ZECS), a diagnostic to...
Optimal Trace Distance and Fidelity Estimations for Pure Quantum States
Qisheng Wang·Aug 29, 2024
Measuring the distinguishability between quantum states is a basic problem in quantum information theory. In this paper, we develop optimal quantum algorithms that estimate both the trace distance and the (square root) fidelity between pure states to...
Quantum sieving for code-based cryptanalysis and its limitations for ISD
Lynn Engelberts, Simona Etinski, Johanna Loyer·Aug 29, 2024
Sieving using near-neighbor search techniques is a well-known method in lattice-based cryptanalysis, yielding the current best runtime for the shortest vector problem in both the classical and quantum setting. Recently, sieving has also become an imp...
Engineering squeezed thermal reservoirs via passive linear coupling
Cheng-Lin Lee, Chiao-Hsuan Wang·Aug 28, 2024
Squeezed thermal reservoirs, characterized by thermal noise with anisotropic fluctuations, have profound implications in quantum thermodynamics and serve as powerful resources for quantum information. However, their experimental realizations remain c...
Beating the Ramsey limit on sensing with deterministic qubit control
M. Hecht, Kumar Saurav, E. Vlachos +2 more·Aug 28, 2024
Qubit frequency shifts, which often contain information about a target environment variable, are detected with Ramsey interference measurements. Unfortunately, the sensitivity of this protocol is limited by decoherence. We introduce a new protocol to...
Probing the Page transition via approximate quantum error correction
Haocheng Zhong·Aug 27, 2024
In recent years, there is a huge progress in understanding the black hole information problem, and the key is that the black hole entropy of radiation should be calculated by the island formula, which describes the Page curve to ensure the unitarity ...
Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform
Yuan Liu, John M. Martyn, Jasmine Sinanan-Singh +3 more·Aug 27, 2024
Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) ...
Artificially intelligent Maxwell’s demon for optimal control of open quantum systems
P. A. Erdman, Robert Czupryniak, Bibek Bhandari +4 more·Aug 27, 2024
Feedback control of open quantum systems is of fundamental importance for practical applications in various contexts, ranging from quantum computation to quantum error correction and quantum metrology. Its use in the context of thermodynamics further...