Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2009.13485 · Physical Review C

Preparation of excited states for nuclear dynamics on a quantum computer

Alessandro Roggero, Chenyi Gu, Alessandro Baroni, T. Papenbrock

Published Dec 28, 2020• 55 citations
arXivHTMLPDF

Abstract

The authors explore methods for developing excited states for a nuclear system in a quantum computer and apply them to the thermal neutron-proton capture reaction, $n+p\ensuremath{\rightarrow}d+\ensuremath{\gamma}$. The applications of this work are a step toward computing nuclear reactions on quantum devices and hold promise for low-energy nuclear theory problems that are hard to solve on classical computers.

DOI
10.1103/physrevc.102.064624

Related papers

Preparation of excited states on a quantum computer

Alessandro Roggero, Chenyi Gu, Alessandro Baroni +1 more

We study two different methods to prepare excited states on a quantum computer, a key initial step to study dynamics within linear response theory. The first method uses unitary evolution for a short time $T=\mathcal{O}(\sqrt{1-F})$ to approximate the action of an excitation operator $\hat{O}$ with fidelity $F$ and success probability $P\approx1-F$. The second method probabilistically applies the excitation operator using the Linear Combination of Unitaries (LCU) algorithm. We benchmark these techniques on emulated and real quantum devices, using a toy model for thermal neutron-proton capture. Despite its larger memory footprint, the LCU-based method is efficient even on current generation noisy devices and can be implemented at a lower gate cost than a naive analysis would suggest. These findings show that quantum techniques designed to achieve good asymptotic scaling on fault tolerant quantum devices might also provide practical benefits on devices with limited connectivity and gate fidelity.

•Sep 28, 2020•0 citations

Simulation of nuclear processes by a quantum computer

Luca Nigro, C. Barbieri, Enrico Prati

Abstract Quantum computers have shown promise in simulating complex quantum systems, including nuclear processes that challenge even supercomputers. We summarize the key ingredients to demonstrate the feasibility of a full nuclear transition simulation, covering also ground and excited state preparation. The tritium nucleus has been used to model strong interactions between nucleons, with quantum circuits used to represent the initial and final states. Variational quantum algorithms aid in preparing such states, requiring four qubits to describe spin-isospin states. Our results show low relative errors in the energy estimation for the obtained eigenstates. Additionally, the transition probability between these states has been estimated as a function of dipole polarization angle. We also study the transition for the neutron capture d(n, γ)t and compare the result with the tritium de-excitation.

Journal of Physics Conference Series•Jun 1, 2025•0 citations

Quantum computing for nuclear reactions

Ionel Stetcu

Description of quantum many-body dynamics is extremely challenging on classical computers, as it requires taking into account many degrees of freedom. In nuclear physics, this translates on a large number of break up channels that have to be taken into account depending on available energy. Even using classical computing exascale capabilities will not allow a full description of dynamical processes starting from internucleon interactions beyond drastic approximations. On the other hand, the dynamics can be naturally implemented on quantum hardware that is designed to easily handle unitary transformations, and hence the hope that in the future we will be able to obtain reaction observables from first principles. In this contribution, I describe the main steps involved in quantum algorithms and review our efforts to apply quantum computing to the nuclear many-body problem using realistic inter-nucleon interactions.

EPJ Web of Conferences•Jan 1, 2025•1 citation

Neural-network quantum states for the nuclear many-body problem

Alessandro Lovato, Giuseppe Carleo, Bryce Fore +4 more

A long-standing goal of nuclear theory is to explain how the structure and dynamics of atomic nuclei and neutron-star matter emerge from the underlying interactions among protons and neutrons. Achieving this goal requires solving the nuclear quantum many-body problem with high accuracy across a wide range of length scales and density regimes. In this review, we discuss how artificial neural network representations of the nuclear many-body wave function have significantly extended the capabilities of continuum quantum Monte Carlo methods. In particular, neural network quantum states enable calculations of larger systems than were previously accessible and provide a flexible framework for capturing phenomena that challenge conventional approaches, including the emergence of nuclear clusters and superfluid phases in dense matter. We highlight recent applications to finite nuclei, infinite nuclear and neutron matter, and dynamical processes relevant to lepton-nucleus and nucleus-nucleus scattering. We also discuss conceptual and methodological connections with condensed matter physics, emphasizing developments in neural network quantum states that bridge strongly correlated systems across disciplines. Together, these developments demonstrate how neural-network methods open new avenues toward unified and accurate descriptions of nuclear structure, matter, and reactions.

nucl-thCross-listedarXiv:2602.13826•Feb 17, 2026•0 citations

Ab initio nuclear structure via quantum adiabatic algorithm

Weijie Du, James P. Vary, Xingbo Zhao +1 more

Background: Solving nuclear many-body problems with an ab initio approach is widely recognized as a computationally challenging problem. Quantum computers offer a promising path to address this challenge. There are urgent needs to develop quantum algorithms for this purpose. Objective: In this work, we explore the application of the quantum algorithm of adiabatic state preparation with quantum phase estimation in ab initio nuclear structure theory. We focus on solving the low-lying spectra (including both the ground and excited states) of simple nuclear systems. Ideas: The efficiency of this algorithm is hindered by the emergence of small energy gaps (level crossings) during the adiabatic evolution. In order to improve the efficiency, we introduce techniques to avoid level crossings: 1) by suitable design of the reference Hamiltonian; 2) by insertions of perturbation terms to modify the adiabatic path. Results: We illustrate this algorithm by solving the deuteron ground state energy and the spectrum of the deuteron bounded in a harmonic oscillator trap implementing the IBM Qiskit quantum simulator. The quantum results agree well the classical results obtained by matrix diagonalization. Outlook: With our improvements to the efficiency, this algorithm provides a promising tool for investigating the low-lying spectra of complex nuclei on future quantum computers.

arXiv:2105.08910•May 19, 2021•2 citations

Polynomial-time quantum algorithm for the simulation of chemical dynamics

Ivan Kassal, Stephen P. Jordan, Peter J. Love +2 more

The computational cost of exact methods for quantum simulation using classical computers grows exponentially with system size. As a consequence, these techniques can be applied only to small systems. By contrast, we demonstrate that quantum computers could exactly simulate chemical reactions in polynomial time. Our algorithm uses the split-operator approach and explicitly simulates all electron-nuclear and interelectronic interactions in quadratic time. Surprisingly, this treatment is not only more accurate than the Born-Oppenheimer approximation but faster and more efficient as well, for all reactions with more than about four atoms. This is the case even though the entire electronic wave function is propagated on a grid with appropriately short time steps. Although the preparation and measurement of arbitrary states on a quantum computer is inefficient, here we demonstrate how to prepare states of chemical interest efficiently. We also show how to efficiently obtain chemically relevant observables, such as state-to-state transition probabilities and thermal reaction rates. Quantum computers using these techniques could outperform current classical computers with 100 qubits.

arXiv:0801.2986•Proceedings of the National Academy of Sciences•Nov 24, 2008•385 citations
The authors explore methods for developing excited states for a nuclear system in a quantum computer and apply them to the thermal neutron-proton capture reaction, n+p\ensuremath→d+\ensuremathγn+p\ensuremath{\rightarrow}d+\ensuremath{\gamma}n+p\ensuremath→d+\ensuremathγ. The applications of this work are a step toward computing nuclear reactions on quantum devices and hold promise for low-energy nuclear theory problems that are hard to solve on classical computers.
We study two different methods to prepare excited states on a quantum computer, a key initial step to study dynamics within linear response theory. The first method uses unitary evolution for a short time T=O(1−F)T=\mathcal{O}(\sqrt{1-F})T=O(1−F​) to approximate the action of an excitation operator O^\hat{O}O^ with fidelity FFF and success probability P≈1−FP\approx1-FP≈1−F. The second method probabilistically applies the excitation operator using the Linear Combination of Unitaries (LCU) algorithm. We benchmark these techniques on emulated and real quantum devices, using a toy model for thermal neutron-proton capture. Despite its larger memory footprint, the LCU-based method is efficient even on current generation noisy devices and can be implemented at a lower gate cost than a naive analysis would suggest. These findings show that quantum techniques designed to achieve good asymptotic scaling on fault tolerant quantum devices might also provide practical benefits on devices with limited connectivity and gate fidelity.
Abstract Quantum computers have shown promise in simulating complex quantum systems, including nuclear processes that challenge even supercomputers. We summarize the key ingredients to demonstrate the feasibility of a full nuclear transition simulation, covering also ground and excited state preparation. The tritium nucleus has been used to model strong interactions between nucleons, with quantum circuits used to represent the initial and final states. Variational quantum algorithms aid in preparing such states, requiring four qubits to describe spin-isospin states. Our results show low relative errors in the energy estimation for the obtained eigenstates. Additionally, the transition probability between these states has been estimated as a function of dipole polarization angle. We also study the transition for the neutron capture d(n, γ)t and compare the result with the tritium de-excitation.
Description of quantum many-body dynamics is extremely challenging on classical computers, as it requires taking into account many degrees of freedom. In nuclear physics, this translates on a large number of break up channels that have to be taken into account depending on available energy. Even using classical computing exascale capabilities will not allow a full description of dynamical processes starting from internucleon interactions beyond drastic approximations. On the other hand, the dynamics can be naturally implemented on quantum hardware that is designed to easily handle unitary transformations, and hence the hope that in the future we will be able to obtain reaction observables from first principles. In this contribution, I describe the main steps involved in quantum algorithms and review our efforts to apply quantum computing to the nuclear many-body problem using realistic inter-nucleon interactions.
A long-standing goal of nuclear theory is to explain how the structure and dynamics of atomic nuclei and neutron-star matter emerge from the underlying interactions among protons and neutrons. Achieving this goal requires solving the nuclear quantum many-body problem with high accuracy across a wide range of length scales and density regimes. In this review, we discuss how artificial neural network representations of the nuclear many-body wave function have significantly extended the capabilities of continuum quantum Monte Carlo methods. In particular, neural network quantum states enable calculations of larger systems than were previously accessible and provide a flexible framework for capturing phenomena that challenge conventional approaches, including the emergence of nuclear clusters and superfluid phases in dense matter. We highlight recent applications to finite nuclei, infinite nuclear and neutron matter, and dynamical processes relevant to lepton-nucleus and nucleus-nucleus scattering. We also discuss conceptual and methodological connections with condensed matter physics, emphasizing developments in neural network quantum states that bridge strongly correlated systems across disciplines. Together, these developments demonstrate how neural-network methods open new avenues toward unified and accurate descriptions of nuclear structure, matter, and reactions.
Background: Solving nuclear many-body problems with an ab initio approach is widely recognized as a computationally challenging problem. Quantum computers offer a promising path to address this challenge. There are urgent needs to develop quantum algorithms for this purpose. Objective: In this work, we explore the application of the quantum algorithm of adiabatic state preparation with quantum phase estimation in ab initio nuclear structure theory. We focus on solving the low-lying spectra (including both the ground and excited states) of simple nuclear systems. Ideas: The efficiency of this algorithm is hindered by the emergence of small energy gaps (level crossings) during the adiabatic evolution. In order to improve the efficiency, we introduce techniques to avoid level crossings: 1) by suitable design of the reference Hamiltonian; 2) by insertions of perturbation terms to modify the adiabatic path. Results: We illustrate this algorithm by solving the deuteron ground state energy and the spectrum of the deuteron bounded in a harmonic oscillator trap implementing the IBM Qiskit quantum simulator. The quantum results agree well the classical results obtained by matrix diagonalization. Outlook: With our improvements to the efficiency, this algorithm provides a promising tool for investigating the low-lying spectra of complex nuclei on future quantum computers.
The computational cost of exact methods for quantum simulation using classical computers grows exponentially with system size. As a consequence, these techniques can be applied only to small systems. By contrast, we demonstrate that quantum computers could exactly simulate chemical reactions in polynomial time. Our algorithm uses the split-operator approach and explicitly simulates all electron-nuclear and interelectronic interactions in quadratic time. Surprisingly, this treatment is not only more accurate than the Born-Oppenheimer approximation but faster and more efficient as well, for all reactions with more than about four atoms. This is the case even though the entire electronic wave function is propagated on a grid with appropriately short time steps. Although the preparation and measurement of arbitrary states on a quantum computer is inefficient, here we demonstrate how to prepare states of chemical interest efficiently. We also show how to efficiently obtain chemically relevant observables, such as state-to-state transition probabilities and thermal reaction rates. Quantum computers using these techniques could outperform current classical computers with 100 qubits.