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At least 469 records · Page 26

Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions

Abstract The ability to efficiently load functions on quantum computers with high fidelity is essential for many quantum algorithms, including those for solving partial differential equations and Monte Carlo estimation. In this work, we introduce the Fourier series loader (FSL) method for preparing quantum states that exactly encode multi-dimensional Fourier series using linear-depth quantum circuits. Specifically, the FSL method prepares a (Dn)-qubit state encoding the 2 Dn -point uniform discretization of aD-dimensional function specified by aD-dimensional Fourier series. A free parameter,m, which must be less thann, determines the number of Fourier coefficients, 2 D ( m + 1 ) , used to represent the function. The FSL method uses a quantum circuit of depth at most 2 ( n − 2 ) + ⌈ log 2 ( n − m ) ⌉ + 2 D ( m + 1 ) + 2 − 2 D ( m + 1 ) , which is linear in the number of Fourier coefficients, and linear in the number of qubits (Dn) despite the fact that the loaded function’s discretization is over exponentially many (2 Dn ) points. The FSL circuit consists of at most D n + 2 D ( m + 1 ) + 1 − 1 single-qubit and D n ( n + 1 ) / 2 + 2 D ( m + 1 ) + 1 − 3 D ( m + 1 ) − 2 two-qubit gates; we present a classical compilation algorithm with runtime O ( 2 3 D ( m + 1 ) ) to determine the FSL circuit for a given Fourier series. The FSL method allows for the highly accurate loading of complex-valued functions that are well-approximated by a Fourier series with finitely many terms. We report results from noiseless quantum circuit simulations, illustrating the capability of the FSL method to load various continuous 1D functions, and a discontinuous 1D function, on 20 qubits with infidelities of less than 10 −6 and 10 −3 , respectively. We also demonstrate the practicality of the FSL method for near-term quantum computers by presenting experiments performed on the Quantinuum H1-1 and H1-2 trapped-ion quantum computers: we loaded a complex-valued function on 3 qubits with a fidelity of over 95 % , as well as various 1D real-valued functions on up to 6 qubits with classical fidelities ≈99%, and a 2D function on 10 qubits with a classical fidelity ≈94%.

Physics↗

Binary operations on neuromorphic hardware with application to linear algebraic operations and stochastic equations

Abstract Non-von Neumann computational hardware, based on neuron-inspired, non-linear elements connected via linear, weighted synapses—so-called neuromorphic systems—is a viable computational substrate. Since neuromorphic systems have been shown to use less power than CPUs for many applications, they are of potential use in autonomous systems such as robots, drones, and satellites, for which power resources are at a premium. The power used by neuromorphic systems is approximately proportional to the number of spiking events produced by neurons on-chip. However, typical information encoding on these chips is in the form of firing rates that unarily encode information. That is, the number of spikes generated by a neuron is meant to be proportional to an encoded value used in a computation or algorithm. Unary encoding is less efficient (produces more spikes) than binary encoding. For this reason, here we present neuromorphic computational mechanisms for implementing binary two’s complement operations. We use the mechanisms to construct a neuromorphic, binary matrix multiplication algorithm that may be used as a primitive for linear differential equation integration, deep networks, and other standard calculations. We also construct a random walk circuit and apply it in Brownian motion simulations. We study how both algorithms scale in circuit size and iteration time.

97 MATHEMATICS AND COMPUTING↗

EpitopeVec: linear epitope prediction using deep protein sequence embeddings

Motivation: B-cell epitopes (BCEs) play a pivotal role in the development of peptide vaccines, immuno-diagnostic reagents and antibody production, and thus in infectious disease prevention and diagnostics in general. Experimental methods used to determine BCEs are costly and time-consuming. Therefore, it is essential to develop computational methods for the rapid identification of BCEs. Although several computational methods have been developed for this task, generalizability is still a major concern, where cross-testing of the classifiers trained and tested on different datasets has revealed accuracies of 51–53%. Results: We describe a new method called EpitopeVec, which uses a combination of residue properties, modified antigenicity scales, and protein language model-based representations (protein vectors) as features of peptides for linear BCE predictions. Extensive benchmarking of EpitopeVec and other state-of-the-art methods for linear BCE prediction on several large and small datasets, as well as cross-testing, demonstrated an improvement in the performance of EpitopeVec over other methods in terms of accuracy and area under the curve. As the predictive performance depended on the species origin of the respective antigens (viral, bacterial and eukaryotic), we also trained our method on a large viral dataset to create a dedicated linear viral BCE predictor with improved cross-testing performance.

59 BASIC BIOLOGICAL SCIENCES↗

The effect of non-linear mutual friction on pulsar glitch sizes and rise times

ABSTRACT Observations of pulsar glitches have the potential to provide constraints on the dynamics of the high density interior of neutron stars. However, to do so, realistic glitch models must be constructed and compared to the data. We take a step towards this goal by testing non-linear models for the mutual friction force, which is responsible for the exchange of angular momentum between the neutron superfluid and the observable normal component in a glitch. In particular, we consider a non-linear dependence of the drag force on the relative velocity between superfluid vortices and the normal component, in which the contributions of both kelvin and phonon excitations are included. This non-linear model produces qualitatively new features, and is able to reproduce the observed bimodal distribution of glitch sizes in the pulsar population. The model also suggests that the differences in size distributions in individual pulsars may be due to the glitches being triggered in regions with different pinning strengths, as stronger pinning leads to higher vortex velocities and a qualitatively different mutual friction coupling with respect to the weak pinning case. Glitches in pulsars that appear to glitch quasi-periodically with similar sizes may thus be due to the same mechanisms as smaller events in pulsars that have no preferred glitch size, but simply originate in stronger pinning regions, possibly in the core of the star.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantum algorithm for the linear Vlasov equation with collisions

The Vlasov equation is a nonlinear partial differential equation that provides a first-principles description of the dynamics of plasmas. Its linear limit is routinely used in plasma physics to investigate plasma oscillations and stability. In this paper, we present a quantum algorithm that simulates the linearized Vlasov equation with and without collisions, in the one-dimensional electrostatic limit. Rather than solving this equation in its native spatial and velocity phase space, we adopt an efficient representation in the dual space yielded by a Fourier-Hermite expansion. For a given simulation time, the Fourier-Hermite representation is exponentially more compact, thus yielding a classical algorithm that can match the performance of a previously proposed quantum algorithm for this problem. Further, this representation results in a system of linear ordinary differential equations (ODEs) which can be solved with well-developed quantum algorithms: a Hamiltonian simulation in the collisionless case, and quantum ODE solvers in the collisional case. In particular, we demonstrate that a quadratic speedup in system size is attainable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comprehensive anisotropic linear optical properties of the Weyl semimetals TaAs and NbAs

We report that TaAs and NbAs are two of the earliest identified Weyl semimetals that possess many intriguing optical properties, such as chirality-dependent optical excitations and giant second harmonic generation (SHG). Linear and nonlinear optics have been employed as tools to probe the Weyl physics in these crystals. Here, we extend these studies to address two important aspects: determining the complete anisotropic dielectric response and exploring if and how they can reveal essential Weyl physics. We determine the complete anisotropic dielectric functions of TaAs and NbAs by combining spectroscopic ellipsometry and density functional theory (DFT). Parameterized Lorentz oscillators are reported from 1.2 - 6 eV (experiment) and 0 - 6 eV (DFT), and good agreement is shown between them. Both linear and nonlinear optical properties have been previously reported to reveal Weyl physics. We suggest that strong optical resonances from trivial bands are the likely origin of the large optical SHG previously reported at these energies. Furthermore, by comparing the contribution of a small k -space centered around the Weyl cones with the total linear dielectric function, we find that these contributions are highly anisotropic and are < 25% of the total dielectric function below 0.5 eV; abov1 eV, these contributions are negligible. Thus, the study of Weyl physics using optical techniques requires very low energies, and even there, a careful assessment is required in distinguishing the much smaller contributions of the Weyl bands from the dominant contributions of the trivial bands and Drude response to the total dielectric function.

36 MATERIALS SCIENCE↗

Extended linear-in- T resistivity due to electron-phason scattering in moiré superlattices

Due to its incommensurate nature, moiré superlattices host not only acoustic phonons but also another type of soft collective modes called phasons. Here, we investigate the impact of electron-phason scattering on the transport properties of moiré systems. We show that the resistivity can scale linearly with temperature down to temperatures much lower than the Bloch-Grüneisen scale defined by electron kinematics on the Fermi surface. This result stems from the friction between layers, which transfers phason spectral weight to a broad diffusive low-energy peak in the mechanical response of the system. As a result, phason scattering becomes a very efficient channel for entropy production at low temperatures. We also consider the contributions of phasons to thermodynamic properties at low temperatures and find a “metallic-like” linear-in-T behavior for the specific heat, despite the fact that this behavior is due to mechanical and not electronic degrees of freedom. Finally, we discuss the implications of this finding to reports of linear-in-T resistivity in the phase diagram of twisted bilayer graphene.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Neutron-induced fission fragment angular distributions, anisotropy, and linear momentum transfer measured with the NIFFTE fission time projection chamber

The Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) collaboration has performed measurements with a fission time projection chamber (fissionTPC) to study the fission process by reconstructing full three-dimensional tracks of fission fragments and other ionizing radiation. The amount of linear momentum imparted to the fissioning nucleus by the incident neutron can be inferred by measuring the opening angle between the fission fragments. Using this measured linear momentum, fission fragment angular distributions can be converted to the center-of-mass frame for anisotropy measurements. Angular anisotropy is an important experimental observable for understanding the quantum mechanical state of the fissioning nucleus and vital to determining detection efficiency for cross section measurements. Neutron linear momentum transfer to fissioning 235 U, 238 U, and 239Pu and fission fragment angular anisotropy of 235 U and 238 U as a function of neutron energies in the range 130 keV–250 MeV are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cosmological forecasts for future galaxy surveys with the linear point standard ruler: Toward consistent BAO analyses far from a fiducial cosmology

The linear point (LP) standard ruler was identified as the basis of a purely geometric method for exploiting the baryon acoustic oscillations (BAO). The LP exploits the BAO feature imprinted in the galaxy two-point correlation function to measure cosmological distances independent of any specific cosmological model. We forecast the expected precision of future and ongoing spectroscopic galaxy surveys to measure distances leveraging the linear point. We investigate the cosmological implications of our forecasted results. We focus in particular on a relevant working example: the detection of the late-time cosmic acceleration independent of other cosmological probes. Further, our findings show that, even within the Λ⁢CDM standard cosmological paradigm, estimated distances need to be reliable over a very wide parameter range in order to realize their maximum utility. This is particularly relevant if we aim to properly characterize cosmological tensions. The LP is a promising candidate approach to achieve this reliability. In contrast, widely employed procedures in BAO analysis estimate distances keeping fixed cosmological parameters to fiducial values close to cosmic-microwave-background constraints in flat-Λ⁢CDM. It is unclear whether they are purely geometric methods. Moreover, they rely on untested extrapolations to explore the parameter space away from those fiducial flat-Λ⁢CDM values. We recommend that all BAO methodologies be validated across the full range of models and parameters over which their results are quoted, first by means of linear predictions and then N -body simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Counting linearly polarized gluons with lattice QCD

We outline an approach to calculate the transverse-momentum-dependent distribution of linearly polarized gluons inside an unpolarized hadron on the lattice with the help of large momentum effective theory. To achieve this purpose, we propose calculating a Euclidean version of the degree of polarization for a fast-moving hadron on the lattice, which is ultraviolet finite, and no soft function subtraction is needed. It indicates a practical way to explore the distribution of the linearly polarized gluons in a proton and the linearly polarized gluon effects in hadron collisions on the lattice.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sparse Linear Solvers for Large-scale Electromagnetic Transient Simulations

Linear solvers form the basis for electromagnetic transient (EMT) simulations. There is a need to speed up EMT simulations as larger regions are analyzed using EMT simulations. For the same, the performance of linear solvers plays an important role. Exploiting the sparsity of the matrices generated in EMT simulations could assist with speed-up. Scalability is also crucial as power grids expand, demanding solutions capable of accommodating the increasing system size. Recent studies from the North American Electric Reliability Corporation (NERC) increasingly emphasize that EMT simulation models of the power grid will grow larger with the inclusion of power electronics components. Parallelisms in sparsity patterns exploit modern central processing units (CPUs), multi-core CPUs, and graphics processing units (GPUs) architectures in sparse solver designs. Therefore, this paper explores publicly available existing linear solvers and investigates their efficiency in large-scale power grid simulations. A large-scale power grid is developed by increasing the size of the IEEE 39 bus test system to up to 39000 bus systems.

Hsu, Kuan-Chieh↗

A Linear Programming Approach to Backtracking for Single-Axis Trackers on Rolling Terrain

In this article, we present a computationally efficient method for determining optimal backtracking rotations for single-axis solar trackers on nonuniform terrain. The method allows for ganged tracking, mechanical rotation constraints, uneven row spacing, and arbitrary maximum allowable shaded fractions (to enable “fractional backtracking”). As with previous 2-D approaches, the method is suitable for terrain that varies in the transverse direction with respect to the rotation axis of the trackers. The novelty of the method lies in formulating the problem of shade avoidance as a linear problem, which is achieved by using the row interception width as the optimization variable instead of rotation angles. Formulating backtracking as a linear problem enables the use of extremely efficient linear programming algorithms, making the method highly scalable, requiring less than 1 min to compute optimal rotation schedules for hundreds of trackers. It also produces more effective backtracking rotations, reducing the frequency of shading by 4× and improving system energy output by 1%–2%.

Optimization↗

Early Exploration of a Flexible Framework for Efficient Quantum Linear Solvers in Power Systems

The rapid integration of renewable energy resources presents formidable challenges in managing power grids. While advanced computing and machine learning techniques offer some solutions for accelerating grid modeling and simulation, there remain complex problems that classical computers cannot effectively address. Quantum computing, a promising technology, has the potential to fundamentally transform how we manage power systems, especially in scenarios with a higher proportion of renewable energy sources. One critical aspect is solving linear systems of equations, crucial for power system applications like power flow analysis, for which the Harrow-Hassidim-Lloyd (HHL) algorithm is a well-known quantum solution. However, HHL quantum circuits often exhibit excessive depth, making them impractical for current Noisy-Intermediate-Scale-Quantum (NISQ) devices. In this paper, we introduce a versatile framework, powered by NWQSim, that bridges the gap between power system applications and quantum linear solvers available in Qiskit. This framework empowers researchers to efficiently explore power system applications using quantum linear solvers. Through innovative gate fusion strategies, reduced circuit depth, and GPU acceleration, our simulator significantly enhances resource efficiency. Power flow case studies have demonstrated up to a eight-fold speedup compared to Qiskit Aer, all while maintaining comparable levels of accuracy.

quantum computing, Harrow-Hassidim-Lloyd, high-per↗

Learning Canonical Embeddings for Unsupervised Shape Correspondence With Locally Linear Transformations

We present a new approach to unsupervised shape correspondence learning between pairs of point clouds. We make the first attempt to adapt the classical locally linear embedding algorithm (LLE)-originally designed for nonlinear dimensionality reduction-for shape correspondence. The key idea is to find dense correspondences between shapes by first obtaining high-dimensional neighborhood-preserving embeddings of low-dimensional point clouds and subsequently aligning the source and target embeddings using locally linear transformations. We demonstrate that learning the embedding using a new LLE-inspired point cloud reconstruction objective results in accurate shape correspondences. More specifically, the approach comprises an end-to-end learnable framework of extracting high-dimensional neighborhood-preserving embeddings, estimating locally linear transformations in the embedding space, and reconstructing shapes via divergence measure-based alignment of probability density functions built over reconstructed and target shapes. Our approach enforces embeddings of shapes in correspondence to lie in the same universal/canonical embedding space, which eventually helps regularize the learning process and leads to a simple nearest neighbors approach between shape embeddings for finding reliable correspondences. Comprehensive experiments show that the new method makes noticeable improvements over state-of-the-art approaches on standard shape correspondence benchmark datasets covering both human and nonhuman shapes.

deformation↗

Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow

Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. Here, we investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new QPF solving algorithm but scrutinizes the end-to-end complexity of the QPF approach, providing a nuanced evaluation of the purported quantum speedup in this problem. Our analysis establishes a best-case bound for the HHL-based quantum power flow complexity, conclusively demonstrating that the HHL-based method has higher runtime complexity compared to the classical algorithm for solving the direct current power flow (DCPF) and fast decoupled load flow (FDLF) problem. Notably, our analysis and conclusions can be extended to any quantum linear system solver with rigorous performance guarantees, based on the known complexity lower bounds for this problem. Additionally, we establish that for potential practical quantum advantage (PQA) to exist it is necessary to consider DCPF-type problems with a very narrow range of condition number values and readout requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comparison of Rotary and Linear Cutting Methodology in Determining Specific Cutting Energy of Granite

Abstract Single polycrystalline diamond compact (PDC) cutting is a practical technique to understand the rock–tool interactions in drag-bit-type geothermal drilling operations. This paper introduces a rotary cutting method to determine specific cutting energy (SCE) and compares it with the conventional linear cutting method. In this work, granite is selected to represent hard rock formations in geothermal drilling. Cutting tests are conducted on a Computer Numerical Control (CNC) machine with a realistic cutting speed of 12.7 m/min and several chip loads ranging from 0.08 to 0.25 mm. The cutting force is measured using a dynamometer and then converted to specific cutting energy (SCE). The results show that the rotary method produces an inverse relationship between SCE and chip load, whereas the linear method shows the opposite. As a result, the produced SCE by the rotary method tends to be lower than that of the linear method at a higher chip load at and over 0.16 mm. The difference may be attributed to the cutting configuration and associated force components.

Engineering↗

High-resolution 3D microwave imaging using an optically tracked linear array

Active three-dimensional microwave or millimeter-wave imaging is typically performed using a linear array that is mechanically scanned over a uniform planar or cylindrical aperture. However, an image can also be formed with a linear array that is scanned over a non-uniform irregular aperture. This requires that the precise position of the array be known for each radar sample. This paper explores high-resolution 3D microwave imaging of stationary targets using an optically tracked manually scanned linear array. The image reconstruction techniques necessary to account for a non-uniform irregular aperture are also developed.

Clark, Richard T.↗

Data for Renewable Linear Alpha-Olefins by Base-Catalyzed Dehydration of Biologically-Derived Fatty Alcohols

Base catalysts were studied for the dehydration of fatty alcohols to linear alpha olefins (LAOs). For the gas phase dehydration of 1-octanol to 1-octene, 15% Cs/SiO2 catalyst was 56% selective at 10% conversion. Diluting a feed of C8, C10, and C14 fatty alcohols to 50% in undecane increased the selectivity to alpha olefins to 77–99%. 15% Cs/SiO2 was further investigated for the gas phase dehydration of a 4.2 g L−1 mixed C8–C14 fatty alcohol in tridecane feed and showed linear alpha olefin selectivities of 78–100% at initial conversions of 51–91% with the conversion lowering to 32–77% over 30 h. Catalytic activity was totally regenerated through calcination. A feed of biologically derived alcohols was produced with E. coli strain CM24 transformed with three plasmids (pBTRCk–pVHb–maACR, pACYC–pVHb–seFadBA, pTRC99A–pVHb–tdTER–fdh) which yielded a 5.5 g L−1 of C8–C14 fatty alcohol in tridecane. This biologically-derived feed was successfully dehydrated to linear alpha olefins over 15% Cs/SiO2 at selectivities of 60–100% with initial conversions of 35–75% which decreased to 22–55% over 30 h. Techno-economic analysis (TEA) of the integrated process for fatty alcohol production and subsequent dehydration to alpha olefins was conducted across the potential fermentation TRY (titer, rate, yield) landscape. Baseline fermentation performance resulted in a minimum product selling price (MPSP) double the market price for LAOs due to low titers and high costs associated with managing water and tridecane solvent flows through the system. However, targeted improvements in fermentation performance (e.g., achieving 40 g L−1 titer, 0.5 g L−1 h−1 productivity, 80% theoretical yield) can enable financially viable production of biologically derived LAOs.

Catalysis↗