Gavin S. Hartnett, Haoran Liao, Enrico Rinaldi • Published: 2026-04-15
Matrix models are an important class of systems in string theory and theoretical physics, with applications to random matrix theory, quantum chaos, and black holes. Hamiltonian Monte Carlo simulations and gauge/gravity duality have been used to study these systems at thermal equilibrium, and the bootstrap program has been used to efficiently determine operator expectation values by imposing positi...
Rahul Deshpande, Majid Kheirkhah, Chris Rich, Richard Harris, Jack Raymond, Emile Hoskinson, Pratik Sathe, Andrew J. Berkley, Stefan Paul, Brian Barch, Daniel A. Lidar, Markus Müller, Gabriel Aeppli, Andrew D. King, Mohammad H. Amin • Published: 2026-03-16
Quantum annealing processors typically control qubits in unison, attenuating quantum fluctuations uniformly until the applied system Hamiltonian is diagonal in the computational basis. This simplifies control requirements, allowing annealing QPUs to scale to much larger sizes than gate-based systems, but constraining the class of available operations. Here we expand the class by performing analog-...
Kenny Campbell • Published: 2026-04-15
Distributed quantum computing (DQC) is a promising proposal for overcoming the scalability challenges of quantum computing. However, the evaluation of DQC hardware and software is difficult due to the relative dearth of classical simulation tools available for DQC devices. In this work, we introduce dqc_simulator, a novel simulation toolkit, written in Python, which automates many of the most chal...
Theodoros Kapourniotis, Dominik Leichtle, Luka Music, Harold Ollivier • Published: 2025-10-03
With the advent of quantum cloud computing, the security of delegated quantum computation has become of utmost importance. While multiple statistically secure blind verification schemes in the prepare-and-send model have been proposed, none of them achieves full quantum fault-tolerance, a prerequisite for useful verification on scalable quantum computers. In this paper, we present the first fault-...
Zhushuo Liu, Jia-ai Shi, Bing-Nan Lu, Xiaosi Xu • Published: 2026-04-15
Nuclear lattice effective field theory has become an important framework for quantum many-body calculations in nuclear physics, yet its classical implementation remains increasingly challenging for more general interactions and larger systems. In this work, we develop a quantum-computing framework for a three-dimensional nuclear lattice model. We construct a variational quantum eigensolver framewo...
Vasilis Belis, Joseph Bowles, Rishabh Gupta, Evan Peters, Maria Schuld • Published: 2026-03-25
This article presents an argument for why quantum computers could unlock new methods for machine learning. We argue that spectral methods, in particular those that learn, regularise, or otherwise manipulate the Fourier spectrum of a machine learning model, are often natural for quantum computers. For example, if a generative machine learning model is represented by a quantum state, the Quantum Fou...
Sridhar Prabhu, Saeed A. Khan, Xingrui Song, Mathieu Ouellet, Ryotatsu Yanagimoto, Saswata Roy, Alen Senanian, Logan G. Wright, Valla Fatemi, Peter L. McMahon • Published: 2026-04-14
Quantum computational sensing (QCS) combines quantum sensing with quantum computing to extract task-relevant information from the physical world. QCS can in principle achieve an accuracy advantage for specific tasks versus the alternative of raw-signal estimation using conventional quantum sensing followed by task-specific classical postprocessing. Here we report the experimental demonstration of ...
Takumi Kanezashi, Daisuke Tsukayama, Jun-ichi Shirakashi, Tetsuo Shibuya, Hiroshi Imai • Published: 2026-04-14
Feedback-controlled electromigration (FCE) enables precise regulation of atomic migration by carefully optimizing multiple experimental parameters. However, manually fine-tuning these parameters poses significant challenges. This study investigated the feasibility of autonomously fabricating Au atomic junctions through gate-based quantum computing using a noisy intermediate-scale quantum (NISQ) de...
Chin-Yi Lin, Li-Chai Shih, Shin Sun, Yuan-Chung Cheng • Published: 2023-12-03
We study whether dissipative energy-transfer dynamics can be simulated on noisy near-term quantum hardware by treating device noise as a calibrated resource rather than purely as an error source. Focusing on a biased exciton dimer, we encode the single-excitation manifold into a two-qubit subspace and implement the coherent dynamics through a shallow Trotterized propagator, while repeated noisy id...
Hsiang-Wei Huang, Shen-Liang Yang, Chuan-Chi Huang, Yueh-Nan Chen, Hong-Bin Chen • Published: 2026-04-14
The quantum kernel method, a promising quantum machine learning algorithm, possesses substantial potential for demonstrating quantum advantage. Although the majority of the quantum kernel is constructed in the context of gate-based quantum circuits, inspired by the idea of analog quantum computing, here we construct an analog quantum kernel and a hybrid quantum kernel, and show their competitivene...