arXiv subjects

Andrew D. Baczewski

Publications and source records attributed to Andrew D. Baczewski.

At least 19 recordsLinked to original sources

arXiv2026

Machine learning quantum data to accelerate quantum Monte Carlo

Simulating strongly correlated electrons in molecules and materials remains a central goal for quantum computing. A promising strategy uses quantum processors to prepare trial wavefunctions that guide classical quantum Monte Carlo (QMC). However, the enormous computational cost of repeatedly processing quantum measurements has severely limited the practical scalability of this approach. Here, we overcome this bottleneck by compressing quantum measurement data into machine-learning models that efficiently provide the wavefunction overlaps needed by QMC. This accelerates quantum-classical QMC by orders of magnitude, enabling chemically accurate simulations on up to 40 qubits, more than doubling the scale of previous hardware demonstrations with comparable accuracy. We demonstrate our approach on hydrogen chains and strongly correlated iron-sulfur clusters using measurements from Google's Willow processor. By enabling efficient reuse of quantum-state information on the classical coprocessor, our framework addresses a fundamental bottleneck in hybrid quantum algorithms that will persist even into the fault-tolerant era.

quant-ph↗

arXiv2026

Below-threshold execution of fault-tolerant ripple-carry addition on a trapped-ion quantum computer

We deploy a universal fault-tolerant quantum computing (FTQC) architecture based on error-detecting $[\![8,3,2]\!]$ and $[\![4,2,2]\!]$ codes on Quantinuum's Helios-1 trapped-ion quantum computer. We compile and execute ripple-carry adder (RCA) circuits for classical inputs up to five bits on this architecture. Uncomputing a workspace qubit provides an additional ``algorithmic check'' to detect errors. While available at both the physical and logical levels, this check synergizes with our architecture by increasing the effective fault distance of many circuit locations from two to four. Combining this algorithmic check with the error-detecting codes, we observed only a single logical failure in one-bit addition after burst-error filtering, yielding an estimated logical failure rate of $(6.0 \pm 5.9) \times 10^{-5}$. This is well below the $(3.5 \pm 1.3) \times 10^{-3}$ failure probability observed for one-bit addition on the same hardware in unencoded form. Two- and three-bit adders also showed performance improvements, while the longer four- and five-bit adders executed just above threshold.

quant-ph↗

arXiv2026

Benchmarking the computational power of quantum computers

Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare routes to this goal, using different qubit technologies and logical architectures. Tracking progress toward quantum utility therefore requires rigorous benchmarks that measure computational capability relative to utility-scale challenge problems and enable fair comparison across disparate platforms. Here we demonstrate direct, cross-platform measurement of quantum computational capability using a new benchmark that quantifies the size of the largest computationally relevant quantum circuits that a machine can execute successfully and the speed at which it can execute them. We apply this quantum universal operation performance system (QUOPS) experimentally to leading processors from Quantinuum, Google, and IBM, computing directly on physical qubits. Translating state-of-the-art resource requirements for recognized challenge problems that represent useful quantum computation into effective QUOPS circuit sizes shows that computational capability must grow by 5 orders of magnitude, motivating fault-tolerant approaches. We use the same benchmark to assess the performance of a simple fault-tolerant logical-qubit processor implemented on up to eight [[7,1,3]]-encoded logical qubits using Quantinuum Helios-1, and project the growth of capability across successive generations of fault-tolerant quantum computers to show how QUOPS can track progress toward quantum scientific utility.

quant-ph↗

arXiv2026

An approach for calculating astrophysical opacities on quantum computers

We propose a quantum algorithmic protocol for calculating astrophysical opacities. Our implementation uses first- and second-quantized representations of interacting electronic and photonic subsystems and Hamiltonian simulation via the interaction picture. Inferring opacity from momentum-resolved measurements of the photonic register yields a direct relationship between qubit count and spectral range/resolution. Logical resource estimates for the classically challenging problem of solar iron opacity are comparable to another high-energy-density physics problem (Rubin et al., PNAS 121(3) (2024)).

quant-ph↗

arXiv2026

Capturing many-body effects in electrical conductivity of warm dense matter

Conductivity models for warm dense matter inform simulations of planetary structure and fusion experiments. State-of-the-art conductivity calculations based on density functional theory approximate many-body physics and neglect electron-electron scattering lifetimes. We introduce a many-body framework for electrical conductivity using the GW approximation of the electronic self-energy. For beryllium, improved transition energies yield a surprisingly large reduction in low-temperature DC conductivity, while electron-electron scattering primarily reduces high-temperature DC conductivity.

physics.plasm-ph↗

arXiv2026

Quantum simulation of electronic structure via quantum fast multipole method

Here we describe an approach for simulating electronic structure on quantum computers with significantly lower asymptotic complexity than prior work. The approach uses a real-space first-quantised representation of the molecular Hamiltonian which we propagate using high-order product formulae. Essential for this low complexity is the use of a technique similar to the fast multipole method for computing the Coulomb operator with $\widetilde{\cal O}(η)$ complexity for a simulation with $η$ particles. We show how to modify this algorithm so that it can be implemented on a quantum computer. We ultimately demonstrate an approach with $t(η^{4/3}N^{1/3} + η^{1/3} N^{2/3} ) (ηNt/ε)^{o(1)}$ gate complexity, where $N$ is the number of grid points, $ε$ is target precision, and $t$ is the duration of time evolution. This is roughly a speedup by ${\cal O}(η)$ over most prior algorithms. We provide lower complexity than all prior work for $N<η^7$ (the regime of practical interest), with only first-quantised interaction-picture simulations providing better performance for $N>η^7$. As with the classical fast multipole method, large particle numbers $η\gtrsim 10^3$ would be needed to realise this advantage.

quant-ph↗

arXiv2026

First principles band structure of interacting phosphorus and boron/aluminum $δ$-doped layers in silicon

Silicon can be heavily doped with phosphorus in a single atomic layer (a $δ$ layer), significantly altering the electronic structure of the conduction bands within the material. Recent progress has also made it possible to further dope silicon with acceptor-based $δ$ layers using either boron or aluminum, making it feasible to create devices with interacting $δ$ layers with opposite polarity. Using Density Functional Theory, we calculate the electronic structure of a phosphorus-based $δ$ layer interacting with a boron or aluminum $δ$ layer, varying the distances between the $δ$ layers. At separations 1 nm and smaller, the dopant potentials overlap and largely cancel each other out, leading to an electronic structure closely mimicking intrinsic silicon. At separations greater than 1 nm, the two $δ$ layers behave independently of one another, with an equivalent electronic structure to a p-n diode with an intrinsic layer taking the place of the depletion region. One mechanism for charge transfer between $δ$ layers at larger distances could be tunneling, where we see a tunneling probability exceeding what would be seen for a standard silicon 1.1 eV triangular barrier, indicating that the interaction between delta layers may enhance tunneling compared to a traditional junction.

cond-mat.mtrl-sci↗

arXiv2026

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the warm dense matter physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations \& experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments and contemporary challenges that are faced by theoretical methods, and experimental techniques needed to create and diagnose warm dense matter. A large part of this roadmap is dedicated to specific warm dense matter systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

physics.plasm-ph↗

arXiv2026

Benchmarking quantum computers

The rapid pace of development in quantum computing technology has sparked a proliferation of benchmarks for assessing the performance of quantum computing hardware and software. Good benchmarks empower scientists, engineers, programmers, and users to understand a computing system's power, but bad benchmarks can misdirect research and inhibit progress. In this Perspective, we survey the science of quantum computer benchmarking. We discuss the role of benchmarks and benchmarking, and how good benchmarks can drive and measure progress towards the long-term goal of useful quantum computations, i.e., "quantum utility". We explain how different kinds of benchmark quantify the performance of different parts of a quantum computer, survey existing benchmarks, examine recent trends in benchmarking, and highlight important open research questions in this field.

quant-ph↗

arXiv2025

Real-time time-dependent density functional theory for high-energy density physics

Electronic response properties of high-energy density (HED) systems influence planetary structure, drive evolution of fusion targets, and underpin diagnostics in laboratory astrophysics. Real-time time-dependent density functional theory (TDDFT) offers a versatile modeling framework capable of accurately predicting the dynamic response of HED materials -- including free-free, bound-free, and bound-bound contributions without requiring ad hoc state partitioning; capturing both collective and non-collective behavior; and applicable within the linear-response regime and beyond. We review the theoretical formalism of real-time TDDFT as applied to HED systems, provide a practical tutorial for computing relevant response properties (dynamic structure factors, conductivity, and stopping power), and comment on avenues for further development of this powerful computational method in service of HED science.

physics.plasm-ph↗

arXiv2025

Nonlinear effects in light-ion stopping powers within real-time time-dependent density functional theory

Electronic stopping power models describing fuel heating processes in inertial fusion energy concepts typically assume linear-response behavior through quadratic scaling with the projectile charge. We report the results of real-time time-dependent density functional theory (TDDFT) calculations indicating that even for low-Z ions, nonlinear processes modify stopping powers in warm dense matter by about 10% near and below the Bragg peak. By describing partial neutralization of slow ions, analytic effective charge models capture some qualitative aspects of the TDDFT results but do not always offer quantitative accuracy. Cases where the effective charge inferred from TDDFT exceeds the bare ion charge suggest that more complex nonlinear effects also contribute. These findings will inform future improvements to more efficient stopping power models.

physics.plasm-ph↗

arXiv2025

Benchmarking quantum computers with any quantum algorithm

Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale computations, these benchmarks currently test this hardware's performance on ``small'' problem instances that are not necessarily representative of utility-scale problems. Furthermore, these benchmarks often employ methods that are unscalable, limiting their ability to track progress towards utility-scale applications. In this work, we present a method for creating scalable and efficient benchmarks from any quantum algorithm or application. Our subcircuit volumetric benchmarking (SVB) method runs subcircuits of varied shape that are ``snipped out'' from some target circuit, which could implement a utility-scale algorithm. SVB is scalable and it enables estimating a capability coefficient that concisely summarizes progress towards implementing the target circuit. We demonstrate SVB with experiments on IBM Q systems using a Hamiltonian block-encoding subroutine from quantum chemistry algorithms.

quant-ph↗

arXiv2025

A small and interesting architecture for early fault-tolerant quantum computers

We present an architecture for early fault-tolerant quantum computers based on the smallest interesting colour code (Earl Campbell, 2016). It realizes a universal logical gate set consisting of single-qubit measurements and preparations in the X and Z bases, single-qubit Hadamard (H) gates, and three-qubit controlled-controlled-Z (CCZ) gates. State teleportations between [[4, 2, 2]] (2D) and [[8, 3, 2]] (3D) error-detecting color codes allow one to make use of the respective transversal H and CCZ gates that these codes possess. As such, minimizing the number of logical quantum teleportation operations, not the number of logical quantum non-Clifford gates, is the relevant optimization goal. To help hardware developers characterize this architecture, we also provide an experimental protocol tailored to testing logical quantum circuits expressed in it.

quant-ph↗

arXiv2024

Statistical inference of collision frequencies from x-ray Thomson scattering spectra

Thomson scattering spectra measure the response of plasma particles to incident radiation. In warm dense matter, which is opaque to visible light, x-ray Thomson scattering (XRTS) enables a detailed probe of the electron distribution and has been used as a diagnostic for electron temperature, density, and plasma ionization. In this work, we examine the sensitivities of inelastic XRTS signatures to modeling details including the dynamic collision frequency and the electronic density of states. Applying verified Monte Carlo inversion methods to dynamic structure factors obtained from time-dependent density functional theory, we assess the utility of XRTS signals as a way to inform the dynamic collision frequency, especially its direct-current (DC) limit, which is directly related to the electrical conductivity.

physics.plasm-ph↗

arXiv2024

Using a high-fidelity numerical model to infer the shape of a few-hole Ge quantum dot

The magnetic properties of hole quantum dots in Ge are sensitive to their shape due to the interplay between strong spin-orbit coupling and confinement. We show that the split-off band, surrounding SiGe layers, and hole-hole interactions have a strong influence on calculations of the effective $g$ factor of a lithographic quantum dot in a Ge/SiGe heterostructure. Comparing predictions from a model including these effects to raw magnetospectroscopy data, we apply maximum-likelihood estimation to infer the shape of a quantum dot with up to four holes. We expect that methods like this will be useful in assessing qubit-to-qubit variability critical to further scaling quantum computing technologies based on spins in semiconductors.

cond-mat.mes-hall↗

arXiv2024

X-ray Thomson scattering absolute intensity from the f-sum rule in the imaginary-time domain

We present a formally exact and simulation-free approach for the normalization of X-ray Thomson scattering (XRTS) spectra based on the f-sum rule of the imaginary-time correlation function (ITCF). Our method works for any degree of collectivity, over a broad range of temperatures, and is applicable even in nonequilibrium situations. In addition to giving us model-free access to electronic correlations, this new approach opens up the intriguing possibility to extract a plethora of physical properties from the ITCF based on XRTS experiments.

physics.plasm-ph↗

arXiv2024

Requirements for building effective Hamiltonians using quantum-enhanced density matrix downfolding

Density matrix downfolding (DMD) is a technique for regressing low-energy effective Hamiltonians from quantum many-body Hamiltonians. One limiting factor in the accuracy of classical implementations of DMD is the presence of difficult-to-quantify systematic errors attendant to sampling the observables of quantum many-body systems on an approximate low-energy subspace. We propose a hybrid quantum-classical protocol for circumventing this limitation, relying on the prospective ability of quantum computers to efficiently prepare and sample from states in well-defined low-energy subspaces with systematically improvable accuracy. We introduce three requirements for when this is possible, including a notion of compressibility that quantifies features of Hamiltonians and low-energy subspaces thereof for which quantum DMD might be efficient. Assuming that these requirements are met, we analyze design choices for our protocol and provide resource estimates for implementing quantum-enhanced DMD on both the doped 2-D Fermi-Hubbard model and an ab initio model of a cuprate superconductor.

quant-ph↗

arXiv2024

An assessment of quantum phase estimation protocols for early fault-tolerant quantum computers

We compare several quantum phase estimation (QPE) protocols intended for early fault-tolerant quantum computers (EFTQCs) in the context of models of their implementations on a surface code architecture. We estimate the logical and physical resources required to use these protocols to calculate the ground state energy of molecular hydrogen in a minimal basis with error below $10^{-3}$ atomic units in the presence of depolarizing logical errors. Accounting for the overhead of rotation synthesis and magic state distillation, we find that the total $T$-gate counts do not vary significantly among the EFT QPE protocols at fixed state overlap. In addition to reducing the number of ancilla qubits and circuit depth, the noise robustness of the EFT protocols can be leveraged to reduce resource requirements below those of textbook QPE, realizing approximately a 300-fold reduction in computational volume in some cases. Even so, our estimates are well beyond the scale of existing early fault-tolerance demonstrations.

quant-ph↗