Giuseppe Buonaiuto, Antonio Marquez Romero, Brian Coyle, Annie E. Paine, Vicente P. Soloviev, Stefano Scali, Michal Krompiec • Published: 2026-03-26
We extend Quantum Computing Quantum Monte Carlo (QCQMC) beyond ground-state energy estimation by systematically constructing the quantum circuits used for state preparation. Replacing the original Variational Quantum Eigensolver (VQE) prescription with task-adapted unitaries, we show that QCQMC can address excited-state spectra via Variational Fast Forwarding and the Variational Unitary Matrix Pro...
Pierre-Luc Dallaire-Demers • Published: 2026-03-26
Bitcoin already faces a quantum threat through Shor attacks on elliptic-curve signatures. This paper isolates the other component that public discussion often conflates with it: mining. Grover's algorithm halves the exponent of brute-force search, promising a quadratic edge to any quantum miner of Bitcoin. Exactly how large that edge grows depends on fault-tolerant hardware. No prior study has cos...
Yang-Yang Xie, Zhao-Ming Wang, Lian-Ao Wu • Published: 2025-08-06
We propose a universal gate set for quantum computing that operates in the presence of decoherence without the overhead of active error correction. We show that a broad class of anisotropic system--bath couplings can be effectively decoupled by preparing an appropriate system--bath entangled initial state. The initially established entanglement serves as a resource to cancel out the dominant decoh...
Ryan Bennink, Olena Burkovska, Konstantin Pieper, Jorge Ramirez, Elaine Wong • Published: 2026-03-26
This review is designed to introduce mathematicians and computational scientists to quantum computing (QC) through the lens of uncertainty quantification (UQ) by presenting a mathematically rigorous and accessible narrative for understanding how noise and intrinsic randomness shape quantum computational outcomes in the language of mathematics. By grounding quantum computation in statistical infere...
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...
Jiunn-Wei Chen, Yu-Ting Chen, Ghanashyam Meher, Berndt Müller, Andreas Schäfer, Xiaojun Yao • Published: 2026-03-25
We simulate the thermalization dynamics for minimally truncated SU(2) pure gauge theory on linear plaquette chains with up to 151 plaquettes using IBM quantum computers. We study the time dependence of the entanglement spectrum, Rényi-2 entropy and anti-flatness on small subsystems. The quantum hardware results obtained after error mitigation agree with extrapolated classical simulator results for...
Yi-Ting Lee, Vijaya Begum-Hudde, Barbara A. Jones, André Schleife • Published: 2026-03-25
Quantum computers, currently in the noisy intermediate-scale quantum (NISQ) era, have started to provide scientists with a novel tool to explore quantum physics and chemistry. While several electronic systems have been extensively studied, Frenkel excitons, as prototypical optical excitations, remain among the less-explored applications. Here, we first use variational quantum deflation to calculat...
Chenyi Gu, Matthias Heinz, Oriel Kiss, Thomas Papenbrock • Published: 2025-07-19
We solve the nuclear two-body and three-body bound states via quantum simulations of pionless effective field theory on a lattice in position space. While the employed lattice remains small, the usage of local Hamiltonians including two- and three-body forces ensures that the number of Pauli terms scales linearly with increasing numbers of lattice sites. We use an adaptive ansatz grown from unitar...
Talal Ahmed Chowdhury, Vladimir Korepin, Vincent R. Pascuzzi, Kwangmin Yu • Published: 2025-09-17
The Fermi-Hubbard model is a fundamental model in condensed matter physics that describes strongly correlated electrons. On the other hand, quantum computers are emerging as powerful tools for exploring the complex dynamics of these quantum many-body systems. In this work, we demonstrate the quantum simulation of the one-dimensional Fermi-Hubbard model using IBM's superconducting quantum computers...
Edward H. Chen, Senrui Chen, Laurin E. Fischer, Andrew Eddins, Luke C. G. Govia, Brad Mitchell, Andre He, Youngseok Kim, Liang Jiang, Alireza Seif • Published: 2025-05-28
To successfully perform quantum computations, it is often necessary to first accurately characterize the noise in the underlying hardware. However, it is well known that fundamental limitations prevent the unique identification of the noise. This raises the question of whether these limitations impact the ability to predict noisy dynamics and mitigate errors. Here, we show, both theoretically and ...