The Schwinger model (quantum electrodynamics in 1+1 dimensions) is a testbed for the study of quantum gauge field theories. We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings. In particular, we perform a tight analysis of low-order Trotter formula simulations of the Schwinger model, using recently derived commutator bounds, and give upper bounds on the resources needed for simulations in both scenarios. 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 / 2 Λ can be simulated on a quantum computer for time 2 x T using a number of T -gates or CNOTs in O ~ ( N 3 / 2 T 3 / 2 x Λ ) for fixed operator error. This scaling with the truncation Λ is better than that expected from algorithms such as qubitization or QDRIFT. Furthermore, we give scalable measurement schemes and algorithms to estimate observables which we cost in both the NISQ and fault-tolerant settings by assuming a simple target observable–the mean pair density. Finally, we bound the root-mean-square error in estimating this observable via simulation as a function of the diamond distance between the ideal and actual CNOT channels. This work provides a rigorous analysis of simulating the Schwinger model, while also providing benchmarks against which subsequent simulation algorithms can be tested.
The Schwinger model (quantum electrodynamics in 1+1 dimensions) is a testbed for the study of quantum gauge field theories. We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings. In particular, we perform a tight analysis of low-order Trotter formula simulations of the Schwinger model, using recently derived commutator bounds, and give upper bounds on the resources needed for simulations in both scenarios. 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 / 2 Λ can be simulated on a quantum computer for time 2 x T using a number of T -gates or CNOTs in O ~ ( N 3 / 2 T 3 / 2 x Λ ) for fixed operator error. This scaling with the truncation Λ is better than that expected from algorithms such as qubitization or QDRIFT. Furthermore, we give scalable measurement schemes and algorithms to estimate observables which we cost in both the NISQ and fault-tolerant settings by assuming a simple target observable–the mean pair density. Finally, we bound the root-mean-square error in estimating this observable via simulation as a function of the diamond distance between the ideal and actual CNOT channels. This work provides a rigorous analysis of simulating the Schwinger model, while also providing benchmarks against which subsequent simulation algorithms can be tested.
Abstract U(1) lattice gauge theories (LGTs) offer a way to simulate quantum electrodynamics, one of the three forces unified by the Standard Model of particles physics. Here we provide complete, quantum-gate-by-quantum-gate algorithms to simulate U(1) LGTs on a fault-tolerant quantum computer. We further perform rigorous error analysis in order to derive concrete estimates of the quantum computational resources required for an accurate simulation of U(1) LGTs using a second-order product formula. We show that U(1) LGTs in any spatial dimension can be simulated using O ˜ ( T 3 2 N 3 2 Λ ϵ − 1 2 ) non-Clifford T gates, where T is the simulation time, N is the number of lattice sites, Λ is the truncation parameter for the bosonic gauge fields, and ε is the simulation error. This work paves the way towards fault-tolerant quantum simulations of physical models closely related to the Standard Model of particle physics.
Computing vacuum states of lattice gauge theories (LGTs) containing fermionic degrees of freedom can present significant challenges for classical computation using Monte-Carlo methods. Quantum algorithms may offer a pathway towards more scalable computation of groundstate properties of LGTs. However, a comprehensive understanding of the quantum computational resources required for such a problem is thus far lacking. In this work, we investigate using the quantum subspace expansion (QSE) algorithm to compute the groundstate of the Schwinger model, an archetypal LGT describing quantum electrodynamics in one spatial dimension. We perform numerical simulations, including the effect of measurement noise, to extrapolate the resources required for the QSE algorithm to achieve a desired accuracy for a range of system sizes. Using this, we present a full analysis of the resources required to compute LGT vacuum states using a quantum algorithm using qubitization within a fault tolerant framework. We develop of a novel method for performing qubitization of a LGT Hamiltonian based on a 'linear combination of unitaries' (LCU) approach. The cost of the corresponding block encoding operation scales as O ~ ( N ) with system size N . Including the corresponding prefactors, our method reduces the gate cost by multiple orders of magnitude when compared to previous LCU methods for the QSE algorithm, which scales as O ~ ( N 2 ) when applied to the Schwinger model. While the qubit and single circuit T-gate cost resulting from our resource analysis is appealing to early fault-tolerant implementation, we find that the number of shots required to avoid numerical instability within the QSE procedure must be significantly reduced in order to improve the feasibility of the methodology we consider and discuss how this might be achieved.
Quantum simulation of lattice gauge theories offers a path to first-principles calculations of real-time dynamics and finite-density phenomena that are inaccessible to classical Euclidean Monte Carlo methods. Realizing this potential requires a pipeline of controlled approximations---lattice discretization, truncation, digitization, state preparation, time evolution, measurement, and continuum extrapolation---each contributing errors and computational costs. General algorithmic asymptotic complexity arguments capture only part of the cost picture: the practical resources required for end-to-end simulation depend on numerical pre-factors, the cost of the subroutines that various algorithms call, and structural features of the lattice theory, all of which the asymptotic scaling leaves unspecified. This thesis develops contributions that aim to make such dependencies explicit and quantitative. We begin with a rigorous analysis of the asymptotic gate complexity of product formulas and Quantum Signal Processing (QSP) for the time evolution of general classes of lattice Hamiltonians, identifying the parameter regimes in which each method is favorable and estimating the associated pre-factors numerically. Since the cost of QSP-based simulation is dominated (in regimes of practical interest) by the block-encoding subroutine it calls, we also develop several novel block-encoding constructions tailored to bosonic lattice field theories and show that signal-processing techniques can be repurposed as highly efficient block-encoding subroutines. We then turn to the problem of truncating the Kogut--Susskind electric-field Hilbert space. Existing error bounds rely on energy-conservation arguments and require the truncation to grow with simulation time. By exploiting Hilbert space fragmentation we derive the tightest error bounds known to date: they decay factorially in the truncation parameter and are independent of simulation time. We validate them numerically for U(1) pure gauge theory and the Schwinger model. Finally, we address the continuum limit in the presence of approximate time evolution. For product formulas, we show that Trotter errors correspond to irrelevant operators that vanish in the continuum limit, which yields a renormalization trajectory independent of the Trotter step size. More generally, we introduce the Statistically-Bounded Time Evolution (SBTE) protocol, an algorithm-independent framework that treats approximation errors as a systematic uncertainty to be driven below the working statistical precision. This decouples the continuum-limit prescription from the choice of time-evolution algorithm and provides a basis for end-to-end cost comparisons across simulation methods.
Abstract. We present a validated computational testbed for studying product-formula errorin a lattice gauge theory. For the lattice Schwinger model (1+1D QED, Kogut–Susskindstaggered fermions, gauge field eliminated via Gauss’s law) we construct three references —exact diagonalization, classical second-order Trotter evolution, and a gate-level Qiskit circuit— and cross-check them against each other and against published conventions. The firsttwo are independent; the second and third share the Hamiltonian construction and Paulidecomposition, so their agreement verifies the gate decomposition and circuit implementationrather than the physics, which is validated against the exact solution instead. The gate-levelcircuit reproduces the classical Trotter propagator to 7.6×10−14 after accumulated repetitions,so that the residual difference from exact evolution isolates the physical Trotter error cleanly;the Hamiltonian is verified term-by-term against Nguyen et al., and the Pauli decompositionagainst direct matrix construction, in both cases to machine precision.We then demonstrate the testbed on three questions from the existing literature. First, thecommutator-scaling bound of Childs et al. (2021), evaluated with prefactors derived numerically rather than assumed, overestimates the measured operator-norm error by a factor between1.5 and 6.8 across nine parameter points (median 2.0), rising with system size and coupling;at the reference point the ratio is 1.74, constant to three significant figures over the testedrange ∆t ∈ [1/512, 1/16]. Second, operator-norm, state, and observable errors all give fittedexponents statistically consistent with p = 2 but markedly different prefactors; we introduce anormalisation-independent gap factor G to quantify this, finding G numerically constant overthe tested ∆t range and increasing across the four accessible system sizes. We show that thisgrowth reflects the growth of the state error while the local-observable error stays constantto five significant figures — the local-versus-global robustness established by Heyl, Hauke andZoller (2019), for which we claim no priority. Third, the ordering heuristics of Tranter et al.(2019), established on 44 molecular Hamiltonians, reproduce all four of their reported trendsat the parameter point tested here — the fourth in sharpened form, the norm-based estimatorranking orderings slightly backwards (ρ = −0.292) rather than merely failing to rank them.The contribution is the validated testbed and its convention bookkeeping rather than newtheory: all three demonstrations are measurements of known results, and in the case of theobservable gap, a re-derivation of a known result in a different language. Reference [5] studiesthe same model with the same decomposition and initial state, using a first-order formula inthe long-time limit; the present work uses the second-order symmetric formula at short timeand compares against the 2021 commutator-scaling bound, which postdates that study. Codefor all reported figures and tables is provided.
We discuss a method to efficiently compute energy spectra in quantum field theories by digital quantum simulation. We utilize a quantum algorithm called coherent imaging spectroscopy which quenches the ground state with a perturbation oscillating periodically in time for various frequencies and then reads off excited energy levels from values of frequencies having loss of the vacuum-to-vacuum probability by the quench. We demonstrate this method in the Schwinger model which is the (1+1)-dimensional quantum electrodynamics with a topological term. In particular, the ground state of the Schwinger model on lattice is prepared by adiabatic state preparation and then we apply various types of quenches to the approximate ground state via Suzuki-Trotter time evolution. We benchmark the types of quenches and argue their (dis)advantages especially in the context of studying quantum field theories. We also estimate the computational complexity to obtain physically reasonable results which likely implies efficiency of the method in the early fault-tolerant quantum computer era
Quantum computing offers a paradigm shift in efficiently simulating quantum field theories (QFTs). In this review, we outline two new techniques for the simulation of QFTs on quantum devices. The first technique employs Hamiltonian Truncation (HT) for nonperturbative real-time QFT simulations on Noisy Intermediate-Scale Quantum (NISQ) devices. As a use case, we apply the HT approach to the Schwinger model. For the observables studied, HT avoids complex state preparation, reducing circuit depth and making the algorithm well suited for NISQ devices. Validated on the ibm_brisbane quantum computer with results showing good agreement with numerical simulations, HT presents an efficient alternative to lattice models. The second approach introduces a continuous-variable quantum computing (CVQC) framework for simulating the real-time dynamics of QFTs, where quantum field values are encoded directly into photonic qumodes. By avoiding the overhead of field digitization, CVQC enables scalable simulations using significantly fewer quantum resources than traditional qubit-based approaches. Classical emulation of the qumode lattice successfully reproduces scattering processes in [Formula: see text]-dimensional [Formula: see text] theory. Together, these methods demonstrate viable paths toward near-term quantum simulations of interacting field theories, offering complementary strategies to address challenges in nonperturbative studies in high-energy physics.