arXiv subjects

Ryan S. Bennink

Publications and source records attributed to Ryan S. Bennink.

At least 19 recordsLinked to original sources

arXiv2026

Large-scale quantum simulations of dissipative spin-1/2 Heisenberg chains

A quantum many-body system coupled to an environment relaxes to a nonequilibrium steady state that can sustain order with no equilibrium counterpart. Computing such steady states is harder than closed-system dynamics as the density matrix problem squares the Hilbert-space dimension, and no free energy selects the steady state. The dissipative spin-1/2 Heisenberg chain is a benchmark example for nonequilibrium steady state physics; various methods have each calculated its phase diagram but do not agree, and a controlled determination at large system size has remained out of reach. Here we simulate the Lindblad dynamics of chains of up to 50 sites on the superconducting processor ibm_kingston -- 100 simultaneously active qubits at up to 1700 entangling-gate depths -- realizing the dissipation via Stinespring dilation. The system's dissipative evolution is a self-correcting mechanism that effectively erases errors, so hardware noise enters only as a weak competing dissipator. We measure static structure factors and resolve ferromagnetic, antiferromagnetic, spin-density-wave, and paramagnetic steady states, mapping the phase diagram with 117 quantum hardware data points across the $J_x$--$J_y$ plane. We uncover a rich non-equilibrium phase diagram of ordered phases with only remnants of the mean-field order, and where sharp transitions give way to the crossovers expected in one dimension. We also find the existence of an incipient (Trotter-induced) spin density wave phase, highlighting the potential of controlled Trotterization as a tool to engineer various magnetic phases in dissipative spin systems. Our quantum simulations largely settle the lingering uncertainty regarding the correct phase diagram of this benchmark system. Moreover, they show that quantum computers are now a feasible tool for addressing scientific questions involving dissipative quantum systems.

quant-ph↗

arXiv2026

Quantum Resource Comparison for Two Leading Surface Code Lattice Surgery Approaches

Hamiltonian simulation is one of the most promising candidates for the demonstration of quantum advantage within the next ten years, and several studies have proposed end-to-end resource estimates for executing such algorithms on fault-tolerant quantum processors. Usually, these resource estimates are based upon the assumption that quantum error correction is implemented using the surface code, and that the best surface code compilation scheme involves serializing input circuits by eliminating all Clifford gates. This transformation is thought to make best use of the native multi-body measurement (lattice surgery) instruction set available to surface codes. Some work, however, has suggested that direct compilation from Clifford+T to lattice surgery operations may be beneficial for circuits that have high degrees of logical parallelism. In this study, we analyze the resource costs for implementing Hamiltonian simulation using example approaches from each of these leading surface code compilation families. The Hamiltonians whose dynamics we consider are those of the transverse-field Ising model in several geometries, the Kitaev honeycomb model, and the $\mathrm{α-RuCl_3}$ complex under a time-varying magnetic field. We show, among other things, that the optimal scheme depends on whether Hamiltonian simulation is implemented using the quantum signal processing or Trotter-Suzuki algorithms, with Trotterization benefiting by orders of magnitude from direct Clifford+T compilation for these applications. Our results suggest that surface code quantum computers should not have a one-size-fits-all compilation scheme, but that smart compilers should predict the optimal scheme based upon high-level quantities from logical circuits such as average circuit density, numbers of logical qubits, and T fraction.

quant-ph↗

arXiv2025

Logical Error Rates for the Surface Code Under a Mixed Coherent and Stochastic Circuit-Level Noise Model Inspired by Trapped Ions

With fault-tolerant quantum computing (FTQC) on the horizon, it is critical to understand sources of logical error in plausible hardware implementations of quantum error-correcting codes (QECC). In this work, we consider logical error rates for the surface code implemented on a hypothetical grid-based trapped-ion quantum charge-coupled device (QCCD) architecture. Specifically, we construct logical channels for the idling surface code and examine its diamond error under a mixed coherent and stochastic circuit-level noise model inspired by trapped ions. We include the coherent dephasing noise that is known to accumulate during physical qubit idling and transport in these systems, determining idling and transport durations using the time-resolved output of the trapped-ion surface code compiler (TISCC). To estimate expectation values of logical Pauli observables following hardware circuits containing non-Clifford sources of noise, we utilize a Monte Carlo technique to sample from an underlying quasi-probability distribution of Clifford circuits that we independently simulate in a phase-sensitive fashion. We verify error suppression up to code distance $d=11$ at coherent dephasing rates near and below those of current-generation trapped-ion quantum computers and find that logical error rates align with those of analogous fully stochastic simulations in this regime. Exploring higher dephasing rates at $d=3-5$, we find evidence for growing coherent rotations about all three logical Pauli axes, increased diagonal logical error process matrix elements relative to those of stochastic simulations, and a reduced dephasing rate threshold. Overall, our work paves a way toward realistic hardware emulation of small fault-tolerant quantum processes, e.g., members of a FTQC instruction set.

quant-ph↗

arXiv2025

Optimizing State Preparation for Variational Quantum Regression on NISQ Hardware

The execution of quantum algorithms on modern hardware is often constrained by noise and qubit decoherence, limiting the circuit depth and the number of gates that can be executed. Circuit optimization techniques help mitigate these limitations, enhancing algorithm feasibility. In this work, we implement, optimize, and execute a variational quantum regression algorithm using a novel state preparation method. By leveraging ZX-calculus-based optimization techniques, such as Pauli pushing, phase folding, and Hadamard pushing, we achieve a more efficient circuit design. Our results demonstrate that these optimizations enable the successful execution of the quantum regression algorithm on current hardware. Furthermore, the techniques presented are broadly applicable to other quantum circuits requiring arbitrary real-valued state preparation, advancing the practical implementation of quantum algorithms.

quant-ph↗

arXiv2024

Realistic Cost to Execute Practical Quantum Circuits using Direct Clifford+T Lattice Surgery Compilation

We report a resource estimation pipeline that explicitly compiles quantum circuits expressed using the Clifford+T gate set into a surface code lattice surgery instruction set. The cadence of magic state requests from the compiled circuit enables the optimization of magic state distillation and storage requirements in a post-hoc analysis. To compile logical circuits into lattice surgery operations, we build upon the open-source Lattice Surgery Compiler. The revised compiler operates in two stages: the first translates logical gates into an abstract, layout-independent instruction set; the second compiles these into local lattice surgery instructions that are allocated to hardware tiles according to a specified resource layout. The second stage retains logical parallelism while avoiding resource contention in the fault-tolerant layer, aiding realism. Additionally, users can specify dedicated tiles at which magic states are replenished, enabling resource costs from the logical computation to be considered independently from magic state distillation and storage. We demonstrate the applicability of our pipeline to large, practical quantum circuits by providing resource estimates for the ground state estimation of molecules. We find that variable magic state consumption rates in real circuits can cause the resource costs of magic state storage to dominate unless production is varied to suit.

quant-ph↗

arXiv2023

TISCC: A Surface Code Compiler and Resource Estimator for Trapped-Ion Processors

We introduce the Trapped-Ion Surface Code Compiler (TISCC), a software tool that generates circuits for a universal set of surface code patch operations in terms of a native trapped-ion gate set. To accomplish this, TISCC manages an internal representation of a trapped-ion system where a repeating pattern of trapping zones and junctions is arranged in an arbitrarily large rectangular grid. Surface code operations are compiled by instantiating surface code patches on the grid and using methods to generate transversal operations over data qubits, rounds of error correction over stabilizer plaquettes, and/or lattice surgery operations between neighboring patches. Beyond the implementation of a basic surface code instruction set, TISCC contains corner movement functionality and a patch translation that is implemented using ion movement alone. Except in the latter case, all TISCC functionality is extensible to alternative grid-like hardware architectures. TISCC output has been verified using the Oak Ridge Quasi-Clifford Simulator (ORQCS).

quant-ph↗

arXiv2022

Counting Abelian Squares for a Problem in Quantum Computing

In a recent work I developed a formula for efficiently calculating the number of abelian squares of length $t+t$ over an alphabet of size $d$, where $d$ may be very large. Here I show how the expressiveness of a certain class of parameterized quantum circuits can be reduced to the problem of counting abelian squares over a large alphabet, and use the recently developed formula to efficiently calculate this quantity.

quant-ph↗

arXiv2022

Counting Abelian Squares More Efficiently

I present a recursive formula for calculating the number of abelian squares of length $n+n$ over an alphabet of size $d$. The presented formula is similar to a previously known formula but has substantially lower complexity when $d\gg n$.

math.CO↗

arXiv2022

Bayesian tomography of high-dimensional on-chip biphoton frequency combs with randomized measurements

Owing in large part to the advent of integrated biphoton frequency combs (BFCs), recent years have witnessed increased attention to quantum information processing in the frequency domain for its inherent high dimensionality and entanglement compatible with fiber-optic networks. Quantum state tomography (QST) of such states, however, has required complex and precise engineering of active frequency mixing operations, which are difficult to scale. To address these limitations, we propose a novel solution that employs a pulse shaper and electro-optic phase modulator (EOM) to perform random operations instead of mixing in a prescribed manner. We successfully verify the entanglement and reconstruct the full density matrix of BFCs generated from an on-chip Si$_{3}$N$_{4}$ microring resonator(MRR) in up to an $8\times8$-dimensional two-qudit Hilbert space, the highest dimension to date for frequency bins. More generally, our employed Bayesian statistical model can be tailored to a variety of quantum systems with restricted measurement capabilities, forming an opportunistic tomographic framework that utilizes all available data in an optimal way.

quant-ph↗

arXiv2020

A Bayesian analysis of classical shadows

The method of classical shadows heralds unprecedented opportunities for quantum estimation with limited measurements [H.-Y. Huang, R. Kueng, and J. Preskill, Nat. Phys. 16, 1050 (2020)]. Yet its relationship to established quantum tomographic approaches, particularly those based on likelihood models, remains unclear. In this article, we investigate classical shadows through the lens of Bayesian mean estimation (BME). In direct tests on numerical data, BME is found to attain significantly lower error on average, but classical shadows prove remarkably more accurate in specific situations -- such as high-fidelity ground truth states -- which are improbable in a fully uniform Hilbert space. We then introduce an observable-oriented pseudo-likelihood that successfully emulates the dimension-independence and state-specific optimality of classical shadows, but within a Bayesian framework that ensures only physical states. Our research reveals how classical shadows effect important departures from conventional thinking in quantum state estimation, as well as the utility of Bayesian methods for uncovering and formalizing statistical assumptions.

quant-ph↗

arXiv2020

Efficient Verification of Anticoncentrated Quantum States

A promising use of quantum computers is to prepare quantum states that model complex domains, such as correlated electron wavefunctions or the underlying distribution of a complex dataset. Such states need to be verified in view of algorithmic approximations and device imperfections. As quantum computers grow in size, however, verifying the states they produce becomes increasingly problematic. Relatively efficient methods have been devised for verifying sparse quantum states, but dense quantum states have remained costly to verify. Here I present a novel method for estimating the fidelity $F(μ,τ)$ between a preparable quantum state $μ$ and a classically specified target state $τ$, using simple quantum circuits and on-the-fly classical calculation (or lookup) of selected amplitudes of $τ$. Notably, in the targeted regime the method demonstrates an exponential quantum advantage in sample efficiency over any classical method. The simplest version of the method is efficient for anticoncentrated quantum states (including many states that are hard to simulate classically), with a sample cost of approximately $4ε^{-2}(1-F)dp_{\text{coll}}$ where $ε$ is the desired precision of the estimate, $d$ is the dimension of the Hilbert space in which $μ$ and $τ$ reside, and $p_{\text{coll}}$ is the collision probability of the target distribution. I also present a more sophisticated version of the method, which uses any efficiently preparable and well-characterized quantum state as an importance sampler to further reduce the number of copies of $μ$ needed. Though some challenges remain, this work takes a significant step toward scalable verification of complex states produced by quantum processors.

quant-ph↗

arXiv2020

Scalable quantum processor noise characterization

Measurement fidelity matrices (MFMs) (also called error kernels) are a natural way to characterize state preparation and measurement errors in near-term quantum hardware. They can be employed in post processing to mitigate errors and substantially increase the effective accuracy of quantum hardware. However, the feasibility of using MFMs is currently limited as the experimental cost of determining the MFM for a device grows exponentially with the number of qubits. In this work we present a scalable way to construct approximate MFMs for many-qubit devices based on cumulant expansion. Our method can also be used to characterize various types of correlation error.

quant-ph↗

arXiv2019

Quantum Process Identification: A Method for Characterizing Non-Markovian Quantum Dynamics

Established methods for characterizing quantum information processes do not capture non-Markovian (history-dependent) behaviors that occur in real systems. These methods model a quantum process as a fixed map on the state space of a predefined system of interest. Such a map averages over the system's environment, which may retain some effect of its past interactions with the system and thus have a history-dependent influence on the system. Although the theory of non-Markovian quantum dynamics is currently an active area of research, a systematic characterization method based on a general representation of non-Markovian dynamics has been lacking. In this article we present a systematic method for experimentally characterizing the dynamics of open quantum systems. Our method, which we call quantum process identification (QPI), is based on a general theoretical framework which relates the (non-Markovian) evolution of a system over an extended period of time to a time-local (Markovian) process involving the system and an effective environment. In practical terms, QPI uses time-resolved tomographic measurements of a quantum system to construct a dynamical model with as many dynamical variables as are necessary to reproduce the evolution of the system. Through numerical simulations, we demonstrate that QPI can be used to characterize qubit operations with non-Markovian errors arising from realistic dynamics including control drift, coherent leakage, and coherent interaction with material impurities.

quant-ph↗

arXiv2018

Scalar Quantum Field Theories as a Benchmark for Near-Term Quantum Computers

Quantum field theory (QFT) simulations are a potentially important application for noisy intermediate scale quantum (NISQ) computers. The ability of a quantum computer to emulate a QFT, therefore, constitutes a natural application-centric benchmark. Foundational quantum algorithms to simulate QFT processes rely on fault-tolerant computational resources, but to be useful on NISQ machines, error-resilient algorithms are required. Here we outline and implement a hybrid algorithm to calculate the lowest energy levels of the paradigmatic 1+1--dimensional interacting scalar QFT. We calculate energy splittings and compare results with experimental values obtained on currently available quantum hardware. We show that the accuracy of mass-renormalization calculations represents a useful metric with which near-term hardware may be benchmarked. We also discuss the prospects of scaling the algorithm to full simulation of interacting QFTs on future hardware.

quant-ph↗

arXiv2018

Quantum Computing Circuits and Devices

The development of quantum computing technologies builds on the unique features of quantum physics while borrowing familiar principles from the design of conventional devices. We introduce the fundamental concepts required for designing and operating quantum computing devices by reviewing state of the art efforts to fabricate and demonstrate quantum gates and qubits. We summarize the near-term challenges for devices based on semiconducting, superconducting, and trapped ion technologies with an emphasis on design tools as well as methods of verification and validation. We then discuss the generation and synthesis of quantum circuits for higher-order logic that can be carried out using quantum computing devices.

quant-ph↗

arXiv2017

Unbiased Simulation of Near-Clifford Quantum Circuits

Modeling and simulation is essential for predicting and verifying the behavior of fabricated quantum circuits, but existing simulation methods are either impractically costly or require an unrealistic simplification of error processes. We present a method of simulating noisy Clifford circuits that is both accurate and practical in experimentally relevant regimes. In particular, the cost is weakly exponential in the size and the degree of non-Cliffordness of the circuit. Our approach is based on the construction of exact representations of quantum channels as quasiprobability distributions over stabilizer operations, which are then sampled, simulated, and weighted to yield unbiased statistical estimates of circuit outputs and other observables. As a demonstration of these techniques we simulate a Steane [[7,1,3]]-encoded logical operation with non-Clifford errors and compute its fault tolerance error threshold. We expect that the method presented here will enable studies of much larger and more realistic quantum circuits than was previously possible.

quant-ph↗

arXiv2014

Heralding efficiency and correlated-mode coupling of near-IR fiber coupled photon pairs

We report on a systematic experimental study of heralding efficiency and generation rate of telecom-band infrared photon pairs generated by spontaneous parametric down-conversion and coupled to single mode optical fibers. We define the correlated-mode coupling efficiency--an inherent source efficiency--and explain its relation to heralding efficiency. For our experiment, we developed a reconfigurable computer controlled pump-beam and collection-mode optical apparatus which we used to measure the generation rate and correlated-mode coupling efficiency. The use of low-noise, high-efficiency superconducting nanowire single-photon detectors in this setup allowed us to explore focus configurations with low overall photon flux. The measured data agree well with theory and we demonstrated a correlated-mode coupling efficiency of $97 \pm 2\%$, which is the highest efficiency yet achieved for this type of system. These results confirm theoretical treatments and demonstrate that very high overall heralding efficiencies can, in principle, be achieved in quantum optical systems. It is expected that these results and techniques will be widely incorporated into future systems that require, or benefit from, a high heralding efficiency.

quant-ph↗

arXiv2014

An Integrated Programming and Development Environment for Adiabatic Quantum Optimization

Adiabatic quantum computing is a promising route to the computational power afforded by quantum information processing. The recent availability of adiabatic hardware has raised challenging questions about how to evaluate adiabatic quantum optimization programs. Processor behavior depends on multiple steps to synthesize an adiabatic quantum program, which are each highly tunable. We present an integrated programming and development environment for adiabatic quantum optimization called JADE that provides control over all the steps taken during program synthesis. JADE captures the workflow needed to rigorously specify the adiabatic quantum optimization algorithm while allowing a variety of problem types, programming techniques, and processor configurations. We have also integrated JADE with a quantum simulation engine that enables program profiling using numerical calculation. The computational engine supports plug-ins for simulation methodologies tailored to various metrics and computing resources. We present the design, integration, and deployment of JADE and discuss its potential use for benchmarking adiabatic quantum optimization programs by the quantum computer science community.

quant-ph↗