Enhancing Chemistry on Quantum Computers with Fermionic Linear Optical Simulation
- URL: http://arxiv.org/abs/2511.12416v2
- Date: Wed, 19 Nov 2025 16:48:20 GMT
- Title: Enhancing Chemistry on Quantum Computers with Fermionic Linear Optical Simulation
- Authors: Zack Hassman, Oliver Reardon-Smith, Gokul Subramanian Ravi, Frederic T. Chong, Kevin J. Sung,
- Abstract summary: We present and open source a quantum circuit simulator tailored to chemistry applications.<n>Our simulator can compute the Born-rule probabilities of samples obtained from circuits containing passive fermionic linear optical elements and controlled-phase gates.
- Score: 2.7065118141722455
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We present and open source a quantum circuit simulator tailored to chemistry applications. More specifically, our simulator can compute the Born-rule probabilities of samples obtained from circuits containing passive fermionic linear optical elements and controlled-phase gates. We support both approximate and exact calculation of probabilities, and for approximate probability calculation, our simulator's runtime is exponential only in the magnitudes of the circuit's controlled-phase gate angles. This makes our simulator useful for simulating certain systems that are beyond the reach of conventional state vector methods. We demonstrate our simulator's utility by simulating the local cluster unitary Jastrow (LUCJ) ansatz and integrating it with sample-based quantum diagonalization (SQD) to improve the accuracy of molecular ground-state energy estimates. Applied to a 52-qubit $N_2$ system, we observe accuracy improvements of up to $46\%$ over the baseline SQD implementation with negligible computational overhead. More generally, we highlight a regime in which our simulator achieves substantially superior latency scaling and exponentially superior memory scaling over a tensor network simulator and a state vector simulator. As an efficient and flexible tool for simulating quantum chemistry circuits, our simulator enables new opportunities for enhancing near-term quantum algorithms in chemistry and related domains.
Related papers
- TensorCircuit-NG: A Universal, Composable, and Scalable Platform for Quantum Computing and Quantum Simulation [33.05172028111655]
We presentCircuit-NG, a next-generation quantum software platform designed to bridge the gap between quantum physics, artificial intelligence, and high-performance computing.<n>Circuit-NG establishes a unified, tensor-native programming paradigm where quantum circuits, tensor networks, and neural networks fuse into a single, end-to-end differentiable computational graph.
arXiv Detail & Related papers (2026-02-15T14:37:37Z) - Simulation of Charge Stability Diagrams for Automated Tuning Solutions (SimCATS) [0.0]
Quantum dots must be tuned precisely to provide a suitable basis for quantum computation.<n>One crucial step is to trap the appropriate number of electrons in the quantum dots.<n>This article introduces a new approach to the realistic simulation of such measurements.
arXiv Detail & Related papers (2025-08-11T14:36:33Z) - TQml Simulator: Optimized Simulation of Quantum Machine Learning [0.0]
We benchmark universal and gate-specific techniques for simulating the action of layers of gates on quantum state vectors.<n>We develop a numerical simulator, named TQml Simulator, that employs the most efficient simulation method for each layer in a given circuit.
arXiv Detail & Related papers (2025-06-05T11:19:05Z) - phase2: Full-State Vector Simulation of Quantum Time Evolution at Scale [0.8223023312645978]
Large-scale classical simulation of quantum computers is crucial for benchmarking quantum algorithms.<n>We present a full-state vector simulation algorithm and software implementation designed to perform HPC simulation of layers of rotations around a string of Pauli operators.
arXiv Detail & Related papers (2025-04-24T18:41:23Z) - Programming optical-lattice Fermi-Hubbard quantum simulators [39.58317527488534]
We develop ground-state preparation algorithms for different fermionic models.<n>In particular, we first design variational, pre-compiled quantum circuits to prepare the ground state of the native Fermi-Hubbard model.<n>We discuss how to approximate the imaginary-time evolution using variational fermionic circuits.
arXiv Detail & Related papers (2025-02-07T16:40:58Z) - Harnessing CUDA-Q's MPS for Tensor Network Simulations of Large-Scale Quantum Circuits [0.0]
Current largest quantum computers feature more than one thousand qubits.<n>A more appealing approach for simulating quantum computers is adopting the network approach.<n>We show that network-based methods provide a significant opportunity to simulate large-qubit circuits.
arXiv Detail & Related papers (2025-01-27T10:36:05Z) - 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) - TANQ-Sim: Tensorcore Accelerated Noisy Quantum System Simulation via QIR on Perlmutter HPC [16.27167995786167]
TANQ-Sim is a full-scale density matrix based simulator designed to simulate practical deep circuits with both coherent and non-coherent noise.
To address the significant computational cost associated with such simulations, we propose a new density-matrix simulation approach.
To optimize performance, we also propose specific gate fusion techniques for density matrix simulation.
arXiv Detail & Related papers (2024-04-19T21:16:29Z) - Importance sampling for stochastic quantum simulations [68.8204255655161]
We introduce the qDrift protocol, which builds random product formulas by sampling from the Hamiltonian according to the coefficients.
We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage.
Results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.
arXiv Detail & Related papers (2022-12-12T15:06:32Z) - Differentiable matrix product states for simulating variational quantum
computational chemistry [6.954927515599816]
We propose a parallelizable classical simulator for variational quantum eigensolver(VQE)
Our simulator seamlessly integrates the quantum circuit evolution into the classical auto-differentiation framework.
As applications, we use our simulator to study commonly used small molecules such as HF, LiH and H$$O, as well as larger molecules CO$$, BeH$ and H$_4$ with up to $40$ qubits.
arXiv Detail & Related papers (2022-11-15T08:36:26Z) - Efficient Mean-Field Simulation of Quantum Circuits Inspired by Density
Functional Theory [1.3561290928375374]
Exact simulations of quantum circuits (QCs) are currently limited to $sim$50 qubits.
Here we show simulations of QCs with a method inspired by density functional theory (DFT)
Our calculations can predict marginal single-qubit probabilities with over 90% accuracy in several classes of QCs with universal gate sets.
arXiv Detail & Related papers (2022-10-29T02:12:15Z) - Probing finite-temperature observables in quantum simulators of spin
systems with short-time dynamics [62.997667081978825]
We show how finite-temperature observables can be obtained with an algorithm motivated from the Jarzynski equality.
We show that a finite temperature phase transition in the long-range transverse field Ising model can be characterized in trapped ion quantum simulators.
arXiv Detail & Related papers (2022-06-03T18:00:02Z) - Parallel Simulation of Quantum Networks with Distributed Quantum State
Management [56.24769206561207]
We identify requirements for parallel simulation of quantum networks and develop the first parallel discrete event quantum network simulator.
Our contributions include the design and development of a quantum state manager that maintains shared quantum information distributed across multiple processes.
We release the parallel SeQUeNCe simulator as an open-source tool alongside the existing sequential version.
arXiv Detail & Related papers (2021-11-06T16:51:17Z) - 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) - Efficient calculation of gradients in classical simulations of
variational quantum algorithms [0.0]
We present a novel derivation of an emulation strategy to precisely calculate the gradient in O(P) time.
Our strategy is very simple, uses only 'apply gate', 'clone state' and 'inner product' primitives.
It is compatible with gate parallelisation schemes, and hardware accelerated and distributed simulators.
arXiv Detail & Related papers (2020-09-06T21:39:44Z) - Quantum Algorithms for Simulating the Lattice Schwinger Model [63.18141027763459]
We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings.
In lattice units, we find a Schwinger model on $N/2$ physical sites with coupling constant $x-1/2$ and electric field cutoff $x-1/2Lambda$.
We estimate observables which we cost in both the NISQ and fault-tolerant settings by assuming a simple target observable---the mean pair density.
arXiv Detail & Related papers (2020-02-25T19:18:36Z)
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.