Hybrid Method of Efficient Simulation of Physics Applications for a Quantum Computer
- URL: http://arxiv.org/abs/2602.09020v1
- Date: Mon, 09 Feb 2026 18:59:30 GMT
- Title: Hybrid Method of Efficient Simulation of Physics Applications for a Quantum Computer
- Authors: Carla Rieger, Albert T. Schmitz, Gehad Salem, Massimiliano Incudini, Sofia Vallecorsa, Anne Y. Matsuura, Michele Grossi, Gian Giacomo Guerreschi,
- Abstract summary: We present a novel hybrid simulation approach, forming a hybrid of a fullstate and a Clifford simulator.<n>Our method focuses on the efficient emulation of multi-qubit rotations, a critical component of Trotterized Hamiltonian evolution.
- Score: 0.19674381684480702
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum chemistry and materials science are among the most promising areas for demonstrating algorithmic quantum advantage and quantum utility due to their inherent quantum mechanical nature. Still, large-scale simulations of quantum circuits are essential for determining the problem size at which quantum solutions outperform classical methods. In this work, we present a novel hybrid simulation approach, forming a hybrid of a fullstate and a Clifford simulator, specifically designed to address the computational challenges associated with the time evolution of quantum chemistry Hamiltonians. Our method focuses on the efficient emulation of multi-qubit rotations, a critical component of Trotterized Hamiltonian evolution. By optimizing the representation and execution of multi-qubit operations leveraging the Pauli frame, our approach significantly reduces the computational cost of simulating quantum circuits, enabling more efficient simulations. Beyond its impact on chemistry applications, our emulation strategy has broad implications for any computational workload that relies heavily on multi-qubit rotations. By increasing the efficiency of quantum simulations, our method facilitates more accurate and cost-effective studies of complex quantum systems. We quantify the performance improvements and computational savings for this emulation strategy, and we obtain a speedup of a factor $\approx 18$ ($\approx 22$ with MPI) for our evaluated chemistry Hamiltonians with 24 qubits. Thus, we evaluate our integration of this emulation strategy into the Intel Quantum SDK, further bridging the gap between theoretical algorithm development and practical quantum software implementations.
Related papers
- 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) - hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications [4.529849615658088]
We present the largest-scale implementation of digital simulation using up to 16 qubits on a trapped-ion quantum computer for life science problem.<n>Our work paves the way towards large-scale simulations of life science tasks on real quantum processors.
arXiv Detail & Related papers (2025-06-02T11:36:30Z) - Experimental Quantum Simulation of Chemical Dynamics [0.0]
Quantum computers promise efficient chemical simulation, but the existing quantum algorithms require many logical qubits and gates.<n>Here, we carry out the first quantum simulations of chemical dynamics by employing a more hardware-efficient encoding scheme.<n>Our trapped-ion device accurately simulates the dynamics of non-adiabatic chemical processes.
arXiv Detail & Related papers (2024-09-06T06:28:05Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [62.46800898243033]
Recent progress in quantum learning theory prompts a question: can linear properties of a large-qubit circuit be efficiently learned from measurement data generated by varying classical inputs?<n>We prove that the sample complexity scaling linearly in $d$ is required to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.<n>We propose a kernel-based method leveraging classical shadows and truncated trigonometric expansions, enabling a controllable trade-off between prediction accuracy and computational overhead.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Parallel Quantum Computing Simulations via Quantum Accelerator Platform Virtualization [44.99833362998488]
We present a model for parallelizing simulation of quantum circuit executions.
The model can take advantage of its backend-agnostic features, enabling parallel quantum circuit execution over any target backend.
arXiv Detail & Related papers (2024-06-05T17:16:07Z) - Quantum Tunneling: From Theory to Error-Mitigated Quantum Simulation [49.1574468325115]
This study presents the theoretical background and the hardware aware circuit implementation of a quantum tunneling simulation.
We use error mitigation techniques (ZNE and REM) and multiprogramming of the quantum chip for solving the hardware under-utilization problem.
arXiv Detail & Related papers (2024-04-10T14:27:07Z) - Quantum Simulation of Dissipative Energy Transfer via Noisy Quantum
Computer [0.40964539027092917]
We propose a practical approach to simulate the dynamics of an open quantum system on a noisy computer.
Our method leverages gate noises on the IBM-Q real device, enabling us to perform calculations using only two qubits.
In the last, to deal with the increasing depth of quantum circuits when doing Trotter expansion, we introduced the transfer tensor method(TTM) to extend our short-term dynamics simulation.
arXiv Detail & Related papers (2023-12-03T13:56:41Z) - Deep Quantum Circuit Simulations of Low-Energy Nuclear States [51.823503818486394]
We present advances in high-performance numerical simulations of deep quantum circuits.
circuits up to 21 qubits and more than 115,000,000 gates can be efficiently simulated.
arXiv Detail & Related papers (2023-10-26T19:10:58Z) - A Herculean task: Classical simulation of quantum computers [4.12322586444862]
This work reviews the state-of-the-art numerical simulation methods that emulate quantum computer evolution under specific operations.
We focus on the mainstream state-vector and tensor-network paradigms while briefly mentioning alternative methods.
arXiv Detail & Related papers (2023-02-17T13:59:53Z) - 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) - Quantum algorithms for quantum dynamics: A performance study on the
spin-boson model [68.8204255655161]
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator.
variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware.
We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
arXiv Detail & Related papers (2021-08-09T18:00:05Z) - Variational Quantum Optimization with Multi-Basis Encodings [62.72309460291971]
We introduce a new variational quantum algorithm that benefits from two innovations: multi-basis graph complexity and nonlinear activation functions.
Our results in increased optimization performance, two increase in effective landscapes and a reduction in measurement progress.
arXiv Detail & Related papers (2021-06-24T20:16:02Z) - Randomizing multi-product formulas for Hamiltonian simulation [2.2049183478692584]
We introduce a scheme for quantum simulation that unites the advantages of randomized compiling on the one hand and higher-order multi-product formulas on the other.
Our framework reduces the circuit depth by circumventing the need for oblivious amplitude amplification.
Our algorithms achieve a simulation error that shrinks exponentially with the circuit depth.
arXiv Detail & Related papers (2021-01-19T19:00:23Z)
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.