Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data
Abstract Not Provided
Astrophysics,ASTRO↗
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A Visual Comparison of Silent Error Propagation
High-performance computing (HPC) systems play a critical role in facilitating scientific discoveries. Their scale and complexity (e.g., the number of computational units and software stack) continue to grow as new systems are expected to process increasingly more data and reduce computing time. However, with more processing elements, the probability that these systems will experience a random bit-flip error that corrupts a program's output also increases, which is often recognized as silent data corruption. Analyzing the resiliency of HPC applications in extreme-scale computing to silent data corruption is crucial but difficult. An HPC application often contains a large number of computation units that need to be tested, and error propagation caused by error corruption is complex and difficult to interpret. Here, to accommodate this challenge, we propose an interactive visualization system that helps HPC researchers understand the resiliency of HPC applications and compare their error propagation. Our system models an application's error propagation to study a program's resiliency by constructing and visualizing its fault tolerance boundary. Coordinating with multiple interactive designs, our system enables domain experts to efficiently explore the complicated spatial and temporal correlation between error propagations. At the end, the system integrated a nonmonotonic error propagation analysis with an adjustable graph propagation visualization to help domain experts examine the details of error propagation and answer such questions as why an error is mitigated or amplified by program execution.
97 MATHEMATICS AND COMPUTING↗
Combining compositional data sets introduces error in covariance network reconstruction
Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.
59 BASIC BIOLOGICAL SCIENCES↗
Monte Carlo-Based Method for Parallelizing Quasi-Static Time-Series Power System Simulations: Preprint
Both commercial and open source power system simulators run quasi-static time-series (QSTS) simulations sequentially. For yearlong high-resolution load profiles this sequential execution of load flows incurs long computation times. Parallelizing QSTS simulations on multiple processors is one possible way to reduce the computation time. Parallelization however introduces errors in the simulation results as the initial state of the system at the beginning of each parallelized time period is not known. In this work a Monte Carlo-based approach has been proposed to estimate the initial state of the system for each parallel simulation run to mitigate the errors in the final results. Classical sequential QSTS simulation is the chosen base case against which all other methods have been compared. Results presented in this paper show that the proposed method improves the simulation results considerably. This paper also discusses possible sensitivities of the proposed method to a number of tunable parameters. Additionally, sensitivity analysis results for a number of parameters have also been presented in the results section.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A Hierarchical OPF Algorithm with Improved Gradient Evaluation in Three-Phase Networks
Linear approximation commonly used in solving alternating-current optimal power flow (AC-OPF) simplifies the system models but incurs accumulated voltage errors in large power networks. Such errors will make the primal-dual type gradient algorithms converge to solutions with voltage violation. In this paper, we improve a recent hierarchical OPF algorithm that rested on primal-dual gradients evaluated with a linearized distribution power flow model. Specifically, we propose a more accurate gradient evaluation method based on an unbalanced three-phase nonlinear distribution power flow model to mitigate the errors arising from linearization. The resultant gradients feature a blocked structure that enables our development of an improved hierarchical primal-dual algorithm to solve the OPF problem. Numerical results on the IEEE 123-bus test feeder and a 4,518-node test feeder show that the proposed method can enhance voltage safety at comparable computational efficiency with the linearized algorithm.
approximation algorithms↗
Leveraging Randomized Compiling for the QITE Algorithm
The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary Time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary Time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1\%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.
Ville, Jean-Loup↗
Mitigation of Cosmic Rays-Induced Errors in Superconducting Quantum Processors
Environmental radioactivity and cosmic-rays have recently been identified as a source of decoherence in super-conducting quantum bits (qubits). In particular, the absorption of cosmic-ray muons and gamma rays emitted by naturally occurring radioactive isotopes in the qubit substrate leads to correlated errors in superconducting quantum processors, posing significant challenges to quantum error correction. To enable quantum computing to scale, it is therefore necessary the devel-opment of mitigation strategies to prevent, or keep under control, error bursts due to particle impacts in the chip. While most environmental radioactive sources can be effectively suppressed using dedicated shielding, cosmic-ray muons, with their high penetration capability, can only be mitigated by moving the entire facility in a deep underground laboratory. This work explores the potential for developing a novel class of quantum processors equipped with an active veto system to protect superconducting-based quantum computers from the detrimental effects of atmospheric muons. Such a device would enable the identification of an atmospheric muon interaction within the processor and veto all operations performed during the occurrence of such an interaction. By demonstrating high detection efficiency and negligible dead time, we aim to establish that the future of quantum processors can be envisioned in above-around facilities.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Quantum optimization algorithms: Energetic implications
Since the dawn of quantum computing (QC), theoretical developments like Shor's algorithm proved the conceptual superiority of QC over traditional computing. However, such quantum supremacy claims are difficult to achieve in practice because of the technical challenges of realizing noiseless qubits. In the near future, QC applications will need to rely on noisy quantum devices that offload part of their work to classical devices. One way to achieve this is by using parameterized quantum circuits in optimization or even in machine learning tasks. The energy requirements of quantum algorithms have not yet been studied extensively. Here in this article, we explore several optimization algorithms using both theoretical insights and numerical experiments to understand their impact on energy consumption. Specifically, we highlight why and how algorithms like quantum natural gradient descent, simultaneous perturbation stochastic approximations or circuit learning methods, are at least 2x to 4x more energy efficient than their classical counterparts; why feedback-based quantum optimization is energy-inefficient; and how techniques like Rosalin can improve the energy efficiency of other algorithms by a factor of ≥2 0 x. Finally, we use the NchooseK high-level programming model to run optimization problems on both gate-based quantum computers and quantum annealers. Empirical data indicate that these optimization problems run faster, have better success rates, and consume less energy on quantum annealers than on their gate-based counterparts.
97 MATHEMATICS AND COMPUTING↗
Enhancing scalability and accuracy of quantum poisson solver
The Poisson equation has many applications across the broad areas of science and engineering. Most quantum algorithms for the Poisson solver presented so far either suffer from lack of accuracy and/or are limited to very small sizes of the problem and thus have no practical usage. In this regard, our previous work showed a proof-of-concept demonstration in advancing quantum Poisson solver algorithm and validated preliminary results for a simple case of 3 x 3 problem. In this work, we delve into comprehensive research details, presenting the results on up to 15 x 15 problems that include step-by-step improvements in Poisson equation solutions, scaling performance, and experimental exploration. In particular, we demonstrate the implementation of eigenvalue amplification by a factor of up to 2 8 , achieving a significant improvement in the accuracy of our quantum Poisson solver and comparing that to the exact solution. Additionally, we present success probability results, highlighting the reliability of our quantum Poisson solver. Moreover, we explore the scaling performance of our algorithm against the circuit depth and width, demonstrating how our approach scales with larger problem sizes and thus further solidifies the practicality of easy adaptation of this algorithm in real-world applications. We also discuss a multilevel strategy for how this algorithm might be further improved to explore much larger problems with greater performance. Finally, through our experiments on the IBM quantum hardware, we conclude that though overall results on the existing NISQ hardware are dominated by the error in the CNOT gates, this work opens a path to realizing a multidimensional Poisson solver on near-term quantum hardware.
97 MATHEMATICS AND COMPUTING↗
Optimized Auxiliary Functions for Robust Mitigation of Finite-Size Errors in Periodic Hybrid Density Functional Theory
When calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a slowly converging quadrature error when approximating an integral in the reciprocal space by a finite sum. The singularity subtraction (SS) method offers a systematic approach for reducing this quadrature error and thus the FSE. Here, in this work, we first investigate the performance of the SS method in the simplest setting, aiming at reducing the FSE in exact exchange calculations by subtracting the Coulomb contribution with a single, adjustable Gaussian auxiliary function. We demonstrate that a simple fitting method can robustly estimate the optimal Gaussian width and leads to rapid convergence toward the TDL. Furthermore, we suggest new forms of the auxiliary function, whose optimal parameters could also be determined through least-squares fitting. For a range of semiconductors and insulators, the proposed auxiliary functions achieve robust, millihartree-level accuracy in hybrid density functional theory calculations, including cases with sparse k-meshes and large basis sets.
Quiton, Stephen Jon [University of California, Ber↗
Symplectic machine learning model for fast simulation of space-charge effects
Symplectic simulation of space-charge effects is crucial for the design and operation of high-intensity particle accelerators. Traditional methods for simulating these effects are often computationally expensive, resulting in significant overhead. In this work, we introduce a generative model based on a U-Net architecture within a generative adversarial network framework to efficiently simulate space-charge effects. The model is trained to predict the transverse multiparticle space-charge Hamiltonian, which can be physically computed using a gridless spectral method. The one-step symplectic transverse transfer map for the particles is then obtained by differentiating the predicted Hamiltonian. Benchmarking results demonstrate that this generative model achieves an order of magnitude higher computational efficiency compared to the spectral method, providing a highly efficient alternative for simulating space-charge effects with a large number of particles. By maintaining symplecticity, the model effectively preserves the phase-space structure and mitigates nonphysical errors in long-term simulations. This model has been integrated into jutrack, a novel autodifferentiable accelerator modeling code developed in the julia programming language.
Beam code development & simulation techniques↗
Solovay-Kitaev algorithm and randomized compilation
This paper discusses a technique for randomizing over synthesized one-qubit gate sequences in order to mitigate coherent errors in fault-tolerant circuits. We present simulated and experimental data showing that randomization can reduce the trace distance to the target state.
Widzowski Maupin, Oliver Gabriel [Sandia National ↗
Minimally entangled state preparation of localized wave functions on quantum computers
Initializing a single site of a lattice scalar field theory into an arbitrary state with support throughout the quantum register requires $O(2^{nQ})$ entangling gates on a quantum computer with $n_Q$ qubits per site. It is conceivable that instead initializing to functions that are good approximations to states may have utility in reducing the number of required entangling gates. In the case of a single site of a noninteracting scalar field theory, initializing to a symmetric exponential wave function requires $n_Q – 1$ entangling gates, the minimal number necessary to create an entangled state of all $n_Q$ qubits. This is compared with the $2^{nQ – 1} + n_Q – 3 + δ_{nQ, 1}$ required for a symmetric Gaussian wave function. In this work, we explore the initialization of one-site $(n_Q = 4)$, two-site $(n_Q = 3)$, and three-site ( n Q = 3 ) noninteracting scalar field theories with symmetric exponential wave functions using IBM's quantum simulators and quantum devices (Poughkeepsie and Tokyo). With the digitizations attainable with $n_Q = 3,4$, these tensor-product wave functions are found to have large overlap with a Gaussian wave function and provide a suitable low-noise initialization for improvement and Somma inflation. Further, in performing these simulations, we have employed a workflow that interleaves calibrations to mitigate systematic errors in production. The calibrations allow tolerance cuts on gate performance including the fidelity of the symmetrizing Hadamard gate, both in vacuum $(|\textbf{0}\gg^{\bigotimes nQ})$ and in medium ($n_Q –1$ qubits initialized to an exponential function). The results obtained in this work are relevant to systems beyond scalar field theories, such as the deuteron radial wave function, two- and three-dimensional Cartesian-space wave functions, and nonrelativistic multinucleon systems built on a localized eigenbasis.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Quancorde: Boosting fidelity with Quantum Canary Ordered Diverse Ensembles
On today's noisy imperfect quantum devices, execution fidelity tends to collapse dramatically for most applications beyond a handful of qubits. It is therefore imperative to employ novel techniques that can boost quantum fidelity in new ways. Here, this paper aims to boost quantum fidelity with Clifford canary circuits by proposing Quancorde: Quantum Canary Ordered Diverse Ensembles, a fundamentally newapproach to identifying the correct outcomes of extremely low-fidelity quantum applications. It is based on the key idea of diversity in quantum devices - variations in noise sources, make each (portion of a) device unique, and therefore, their impact on an application's fidelity, also unique. Quancorde utilizes Clifford canary circuits (which are classically simulable, but also resemble the target application structure and thus suffer similar structural noise impact) to order a diverse ensemble of devices or qubits/mappings approximately along the direction of increasing fidelity of the target application. Quancorde then estimates the correlation of the ensemble-wide probabilities of each output string of the application, with the canary ensemble ordering, and uses this correlation to weight the application's noisy probability distribution. The correct application outcomes are expected to have higher correlation with the canary ensemble order, and thus their probabilities are boosted in this process. Doing so, Quancorde improves the fidelity of evaluated quantum applications by a mean of 8.9x/4.2x (wrt. different baselines) and up to a maximum of 34x.
clifford↗
Quantum Electromagnetic Transients Program
This work devises a quantum electromagnetic transients program (QEMTP) which is the first attempt to tackle the computational challenges in solving EMTP through quantum computing. The main contributions lie in: (1) A quantum-enabled EMTP formulation with Dommel's model encoded in quantum states; 2) An Harrow-Hassidim-Lloyd (HHL)-based QEMTP to solve the discrete-time nodal equations; 3) An iteration-based HHL revision for mitigating temporal errors to achieve high accuracy of QEMTP with limited quantum resources. Case studies verify the correctness and efficacy of QEMTP in simulating both fast and slow dynamics.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Critical assessment of intramodality 3D ultrasound imaging for prostate IGRT compared to fiducial markers
Purpose: A quantitative 3D intramodality ultrasound (US) imaging system was verified for daily in-room prostate localization, and compared to prostate localization based on implanted fiducial markers (FMs).Methods: Thirteen prostate patients underwent multiple US scans during treatment. A total of 376 US-scans and 817 matches were used to determine the intra- and interoperator variability. Additionally, eight other patients underwent daily prostate localization using both US and electronic portal imaging (EPI) with FMs resulting in 244 combined US-EPI scans. Scanning was performed with minimal probe pressure and a correction for the speed of sound aberration was performed. Uncertainties of both US and FM methods were assessed. User variability of the US method was assessed.Results: The overall US user variability is 2.6 mm. The mean differences between US and FM are: 2.5 {+-} 4.0 mm (LR), 0.6 {+-} 4.9 mm (SI), and -2.3 {+-} 3.6 mm (AP). The intramodality character of this US system mitigates potential errors due to transducer pressure and speed of sound aberrations.Conclusions: The overall accuracy of US (3.0 mm) is comparable to our FM workflow (2.2 mm). Since neither US nor FM can be considered a gold standard no conclusions can be drawn on the superiority of either method. Because US imaging captures the prostate itself instead of surrogates no invasive procedure is required. It requires more effort to standardize US imaging than FM detection. Since US imaging does not involve a radiation burden, US prostate imaging offers an alternative for FM EPI positioning.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
SU-E-P-03: The Australian Clinical Dosimetry Service, a Bespoke National Solution
Purpose: The Australian Clinical Dosimetry Service, (ACDS) was a pilot program to enable the Australian Government to determine whether a locally designed audit program was suitable for mitigating dosimetric error risk to radiotherapy patients within Australia. The outcomes from four years of operations will be presented and discussed with a focus why and how the pilot requirements were met. The consequnces of success will be considered, the lessons learnt from the pilot program and how they are impacting the future ACDS design, operation and engagement with stakeholders. Methods: The ACDS was designed over 2010/11 by experts drawn from the three professions in consultation with the national Department of Health. The list of outcomes required over a three year pilot was expressed in a Memorandum of Understanding, (MoU) between Health and the Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) which hosted the ACDS. Results: The ACDS has achieved all the MoU requirements. This paper describes how the staff within the ACDS engaged with the professional clinical workforce and provided a successful and functioning audit service. It identifies the strengths and weaknesses within the MoU and the ACDS structure and how the ACDS resolved a number of conflicting issues. It identifies the successes within the ACDS and how these were achieved. It provides details to assist and advise those seeking to design or modify national or regional auditing programs. Finally the paper reviews potential futures for the ACDS. Conclusion: The raw number of audits and outcomes indicate that the ACDS has met the MoU auditing requirements. The reasons for the ACDS’ success are highly dependent on: attracting quality staff who can respond with agility to changing situations, a high level of communication with the professional community, a high level of engagement by the community and an interested and engaged Federal Department. The Australian Clinical Dosimetry Service is a joint initiative between the Australian Department of Health and the Australian Radiation Protection and Nuclear Safety Agency.
60 APPLIED LIFE SCIENCES↗
MO-D-213-02: Quality Improvement Through a Failure Mode and Effects Analysis of Pediatric External Beam Radiotherapy
Purpose: To conduct a failure mode and effects analysis (FMEA) as per AAPM Task Group 100 on clinical processes associated with teletherapy, and the development of mitigations for processes with identified high risk. Methods: A FMEA was conducted on clinical processes relating to teletherapy treatment plan development and delivery. Nine major processes were identified for analysis. These steps included CT simulation, data transfer, image registration and segmentation, treatment planning, plan approval and preparation, and initial and subsequent treatments. Process tree mapping was utilized to identify the steps contained within each process. Failure modes (FM) were identified and evaluated with a scale of 1–10 based upon three metrics: the severity of the effect, the probability of occurrence, and the detectability of the cause. The analyzed metrics were scored as follows: severity – no harm = 1, lethal = 10; probability – not likely = 1, certainty = 10; detectability – always detected = 1, undetectable = 10. The three metrics were combined multiplicatively to determine the risk priority number (RPN) which defined the overall score for each FM and the order in which process modifications should be deployed. Results: Eighty-nine procedural steps were identified with 186 FM accompanied by 193 failure effects with 213 potential causes. Eighty-one of the FM were scored with a RPN > 10, and mitigations were developed for FM with RPN values exceeding ten. The initial treatment had the most FM (16) requiring mitigation development followed closely by treatment planning, segmentation, and plan preparation with fourteen each. The maximum RPN was 400 and involved target delineation. Conclusion: The FMEA process proved extremely useful in identifying previously unforeseen risks. New methods were developed and implemented for risk mitigation and error prevention. Similar to findings reported for adult patients, the process leading to the initial treatment has an associated high risk.
60 APPLIED LIFE SCIENCES↗