Inverse Quantum Simulation for Quantum Material Design

• URL: http://arxiv.org/abs/2601.12239v1
• Date: Sun, 18 Jan 2026 03:28:09 GMT
• Title: Inverse Quantum Simulation for Quantum Material Design
• Authors: Christian Kokail, Pavel E. Dolgirev, Rick van Bijnen, Daniel Gonzalez-Cuadra, Mikhail D. Lukin, Peter Zoller,
• Abstract summary: We present a framework for inverse quantum simulation, enabling material design with desired properties.<n>Hamiltonian learning is used to reconstruct a low-energy Hamiltonian for which this state is an approximate ground state.<n>Results extend the scope of quantum simulators from exploring quantum many-body systems to designing and discovering new quantum materials.
• Score: 0.38312604216679147
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum simulation provides a powerful route for exploring many-body phenomena beyond the capabilities of classical computation. Existing approaches typically proceed in the forward direction: a model Hamiltonian is specified, implemented on a programmable quantum platform, and its phase diagram and properties are explored. Here we present a quantum algorithmic framework for inverse quantum simulation, enabling quantum material design with desired properties. Target material characteristics are encoded as a cost function, which is minimized on quantum hardware to prepare a many-body state with the desired properties in quantum memory. Hamiltonian learning is then used to reconstruct a low-energy Hamiltonian for which this state is an approximate ground state, yielding a physically interpretable model that can guide experimental synthesis. As illustrative applications, we outline how the method can be used to search for high-temperature superconductors within the fermionic Hubbard model, enhancing $d$-wave correlations over a broad range of dopings and temperatures, design quantum phases by stabilizing a topological order through continuous Hamiltonian modifications, and optimize dynamical properties relevant for photochemistry and frequency- and momentum-resolved condensed-matter data. These results extend the scope of quantum simulators from exploring quantum many-body systems to designing and discovering new quantum materials.

Related papers

• Programmable Exploration of Magnetic States in Lieb-Kagome Interpolated Lattices [44.99833362998488]
  A quantum annealer is used to simulate magnetic interactions in molecular qubit lattices inspired by experimentally realizable systems.<n>The annealer provides access to observables such as the static structure factor and magnetization over a wide parameter space.<n>This framework defines a modular and scalable paradigm for probing the limits of engineered quantum matter across chemistry, condensed matter, and quantum information science.
  arXiv  Detail & Related papers  (2025-07-24T21:47:54Z)
• VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning [50.95799256262098]
  Variational quantum circuits (VQCs) hold promise for quantum machine learning but face challenges in expressivity, trainability, and noise resilience.<n>We propose VQC-MLPNet, a hybrid architecture where a VQC generates the first-layer weights of a classical multilayer perceptron during training, while inference is performed entirely classically.
  arXiv  Detail & Related papers  (2025-06-12T01:38:15Z)
• Variational Quantum Simulation of the Interacting Schwinger Model on a Trapped-Ion Quantum Processor [26.47874938214435]
  In this work, we explore the multi-flavor lattice Schwinger model - a toy model inspired by quantum chromodynamics.<n>We employ a parametric quantum circuit executed on our quantum processor to identify ground states in different parameter regimes of the model.<n>The resulting states are analyzed via quantum state tomography, to reveal how characteristic properties such as correlations in the output state change.
  arXiv  Detail & Related papers  (2025-04-29T14:43:57Z)
• Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity [0.0]
  Equilibrium propagation (EP) is a procedure that has been introduced and applied to classical energy-based models which relax to an equilibrium. Here, we show a direct connection between EP and Onsager reciprocity and exploit this to derive a quantum version of EP. This can be used to optimize loss functions that depend on the expectation values of observables of an arbitrary quantum system.
  arXiv  Detail & Related papers  (2024-06-10T17:22:09Z)
• Programmable Simulations of Molecules and Materials with Reconfigurable Quantum Processors [0.3320294284424914]
  We introduce a simulation framework for strongly correlated quantum systems that can be represented by model spin Hamiltonians. Our approach leverages reconfigurable qubit architectures to programmably simulate real-time dynamics. We show how this method can be used to compute key properties of a polynuclear transition-metal catalyst and 2D magnetic materials.
  arXiv  Detail & Related papers  (2023-12-04T19:00:01Z)
• Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
  We explore the applicability of quantum-data learning to practical problems in high-energy physics. We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states. The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
  arXiv  Detail & Related papers  (2023-06-29T18:00:01Z)
• Quantum Neural Architecture Search with Quantum Circuits Metric and Bayesian Optimization [2.20200533591633]
  We propose a new quantum gates distance that characterizes the gates' action over every quantum state. Our approach significantly outperforms the benchmark on three empirical quantum machine learning problems.
  arXiv  Detail & Related papers  (2022-06-28T16:23:24Z)
• Recompilation-enhanced simulation of electron-phonon dynamics on IBM Quantum computers [62.997667081978825]
  We consider the absolute resource cost for gate-based quantum simulation of small electron-phonon systems. We perform experiments on IBM quantum hardware for both weak and strong electron-phonon coupling. Despite significant device noise, through the use of approximate circuit recompilation we obtain electron-phonon dynamics on current quantum computers comparable to exact diagonalisation.
  arXiv  Detail & Related papers  (2022-02-16T19:00:00Z)
• Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits at Exascale [57.84751206630535]
  We present a modernized version of the Quantum Virtual Machine (TNQVM) which serves as a quantum circuit simulation backend in the e-scale ACCelerator (XACC) framework. The new version is based on the general purpose, scalable network processing library, ExaTN, and provides multiple quantum circuit simulators. By combining the portable XACC quantum processors and the scalable ExaTN backend we introduce an end-to-end virtual development environment which can scale from laptops to future exascale platforms.
  arXiv  Detail & Related papers  (2021-04-21T13:26:42Z)
• Preparing random states and benchmarking with many-body quantum chaos [48.044162981804526]
  We show how to predict and experimentally observe the emergence of random state ensembles naturally under time-independent Hamiltonian dynamics. The observed random ensembles emerge from projective measurements and are intimately linked to universal correlations built up between subsystems of a larger quantum system. Our work has implications for understanding randomness in quantum dynamics, and enables applications of this concept in a wider context.
  arXiv  Detail & Related papers  (2021-03-05T08:32:43Z)
• Quantum Phases of Matter on a 256-Atom Programmable Quantum Simulator [41.74498230885008]
  We demonstrate a programmable quantum simulator based on deterministically prepared two-dimensional arrays of neutral atoms. We benchmark the system by creating and characterizing high-fidelity antiferromagnetically ordered states. We then create and study several new quantum phases that arise from the interplay between interactions and coherent laser excitation.
  arXiv  Detail & Related papers  (2020-12-22T19:00:04Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.