Alternative Operation Research Articles

Constrained quantum optimization for extractive summarization on a trapped-ion quantum computer

Realizing the potential of near-term quantum computers to solve industry-relevant constrained-optimization problems is a promising path to quantum advantage. In this work, we consider the extractive summarization constrained-optimization problem and demonstrate the largest-to-date execution of a quantum optimization algorithm that natively preserves constraints on quantum hardware. We report results with the Quantum Alternating Operator Ansatz algorithm with a Hamming-weight-preserving XY mixer (XY-QAOA) on trapped-ion quantum computer. We successfully execute XY-QAOA circuits that restrict the quantum evolution to the in-constraint subspace, using up to 20 qubits and a two-qubit gate depth of up to 159. We demonstrate the necessity of directly encoding the constraints into the quantum circuit by showing the trade-off between the in-constraint probability and the quality of the solution that is implicit if unconstrained quantum optimization methods are used. We show that this trade-off makes choosing good parameters difficult in general. We compare XY-QAOA to the Layer Variational Quantum Eigensolver algorithm, which has a highly expressive constant-depth circuit, and the Quantum Approximate Optimization Algorithm. We discuss the respective trade-offs of the algorithms and implications for their execution on near-term quantum hardware.

Diagnosing Barren Plateaus with Tools from Quantum Optimal Control

Variational Quantum Algorithms (VQAs) have received considerable attention due to their potential for achieving near-term quantum advantage. However, more work is needed to understand their scalability. One known scaling result for VQAs is barren plateaus, where certain circumstances lead to exponentially vanishing gradients. It is common folklore that problem-inspired ansatzes avoid barren plateaus, but in fact, very little is known about their gradient scaling. In this work we employ tools from quantum optimal control to develop a framework that can diagnose the presence or absence of barren plateaus for problem-inspired ansatzes. Such ansatzes include the Quantum Alternating Operator Ansatz (QAOA), the Hamiltonian Variational Ansatz (HVA), and others. With our framework, we prove that avoiding barren plateaus for these ansatzes is not always guaranteed. Specifically, we show that the gradient scaling of the VQA depends on the degree of controllability of the system, and hence can be diagnosed through the dynamical Lie algebragobtained from the generators of the ansatz. We analyze the existence of barren plateaus in QAOA and HVA ansatzes, and we highlight the role of the input state, as different initial states can lead to the presence or absence of barren plateaus. Taken together, our results provide a framework for trainability-aware ansatz design strategies that do not come at the cost of extra quantum resources. Moreover, we prove no-go results for obtaining ground states with variational ansatzes for controllable system such as spin glasses. Our work establishes a link between the existence of barren plateaus and the scaling of the dimension ofg.

Pluralizing measurement: Physical geodesy's measurement problem and its resolution

Derived measurements involve problems of coordination. Conducting them often requires detailed theoretical assumptions about their target, while such assumptions can lack sources of evidence that are independent from these very measurements. In this paper, I defend two claims about problems of coordination. I motivate both by a novel case study on a central measurement problem in the history of physical geodesy: the determination of the earth's ellipticity. First, I argue that the severity of problems of coordination varies according to scientists' predictive and experimental control over perturbations of the measurement process. Second, I identify a methodology by which scientists can solve hard problems of coordination and gradually increase their predictive control over perturbations. I dub this methodology ‘operational pluralism’ since it is driven by the introduction of alternative measurement operations that involve different physical indicators.

Hermitian operator of a Mach–Zehnder interferometer combined with parity detection and its applications

In quantum metrology, parity detection is often used to investigate the phase estimation based on optical interferometer. Different from previous work, we consider a Mach–Zehnder interferometer (MZI) and parity detection as a whole operation in Heisenberg picture, and obtain the corresponding Hermitian operator. By this alternative operator method, one can derive the parity signal directly in terms of input states. Our results clearly show that the phase sensitivity obtained by the parity detection is independent of both configurations of the estimated phases and the output ports of the MZI. As applications, we analytically demonstrate that the no-go theorem indeed holds for both parity detection and single-mode intensity detection. We also investigate the phase estimation of the MZI seeded by the two-mode squeezed coherent state, and obtain the more concise and illuminating results.

High Performance Broadcast Receiver Based on Obsolete Technology.

Since its inception, the electronics industry has mass-produced equipment. The fast evolution of electronic technologies made obsolete the entire generation of products and even technologies. Until the government issued regulations and guidelines on how to address the issue of reuse of obsolete electronic equipment, with special regard to the ones still operating (e.g., give it to family/friends, donate to charity, or sell to individuals or recycling companies), most of it was thrown out with usual rubbish, with a destructive effect on the environment. This paper presents the design techniques and methods for revaluation of obsolete vacuum tube analog receivers, with a focus on the manufacturing steps of a high-performance receiver. The choice of receiver type is not accidental at all, since tube technology is still a real success among audiophiles many providers offer vacuum tube amplifiers at considerably high prices. The redesign implied the original FM unit replacement with a DSP-based AM/FM tuner while the AM RF vacuum tube section has been preserved with the original architecture to allow the reception of the broadcast stations for the long-wave band and the alternative operation with the silicon tuner for the medium-wave and short-wave bands. The electrical performances of the modified receiver in terms of reliability, sensitivity, selectivity, and distortions on the reception chain are clearly superior to the original one, while the power consumption of the RF section is reduced more than 10 times from 11.5 W–15.5 W to 1 W. Last, but not least important, the proposed solution implied the use of few additional parts and resources and extended significantly the lifetime of the original vacuum tubes receiver. The work has been developed to serve as an example of how obsolete electronic equipment can be redesigned and reused avoiding its complete recycling or even worse, its disposal with usual rubbish. It has been imagined and performed as the initial step in launching a professional student contest on the reuse/redesign of obsolete equipment aimed at raising awareness regarding the issue of pollution with e-waste amongst students from the electronic departments of Romanian technical universities.

Fixing the rotating-wave approximation for strongly detuned quantum oscillators

Periodically-driven oscillators are commonly described in a frame co-rotating with the drive and using the rotating-wave approximation (RWA). This description, however, is known to induce errors for off-resonant driving. Here we show that the standard quantum description, using creation and annihilation of particles with the oscillator's natural frequency, necessarily leads to incorrect results when combined with the RWA. We demonstrate this on the simple harmonic oscillator and present an alternative operator basis which reconciles the RWA with off-resonant driving. The approach is also applicable to more complex models, where it accounts for known discrepancies. As an example, we demonstrate the advantage of our scheme on the driven quantum Duffing oscillator.

Time Fisher information associated with fluctuations in quantum geometry

As time is not an observable, we use Fisher information (FI) to address the problem of time. We demonstrate that although the Hamiltonian operator is the generator of time, the Hamiltonian constraint operator cannot observe the change that arises through the passage of time. This is because the Hamiltonian constraint does not contain time FI. As we also identify an alternative operator on the world-sheet which does contain time FI, we argue that the timelessness of quantum gravity occurs due to the use of an inappropriate operator. We propose that a criterion for a physically meaningful operator in any quantum gravitational process is that it should contain non-vanishing time FI. Although we explicitly derive these results on the world-sheet of bosonic strings, we argue that it holds for any quantum geometry associated with time-reparametrization–invariant classical geometry.

High Efficiency Hybrid Radiant and Heat Pump Heating Plants for Industrial Buildings: An Energy Analysis

A hybrid condensing radiant tubes system coupled to a heat pump to heat a typical industrial building was modeled in three climatic zones of Italy using dynamic simulation software. The heating system was set up by radiant tubes and an air heating system with terminals placed in the building supplied by hot water produced by the condensation of the exhausted of the radiant tubes and by a heat pump with external air heat source. An optimization of the main parameters (nominal power of the heat pump, bivalent temperature in alternative bivalent operation, and peak power of the photovoltaic system) was carried out on the basis of energy performance of the hybrid heating system. The optimal configuration of the hybrid heating system that minimizes the annual amount of total non-renewable primary energy and maximizes the non-renewable primary energy ratio was compared with traditional heating systems for industrial buildings. The energy savings of this innovative solution vary in the range of 40%-80% depending on the climate and the configuration of the system.

Multiarterial Phase Acquisition in Gadoxetic Acid-Enhanced Liver MRI for the Detection of Hypervascular Hepatocellular Carcinoma in High-Risk Patients: Comparison of Compressed Sensing Versus View Sharing Techniques.

The aim of this study was to compare compressed sensing (CS) and view sharing (VS) techniques for single breath-hold multiarterial phase imaging with respect to image quality and focal liver observation detectability during gadoxetic acid-enhanced magnetic resonance imaging in patients at high risk for hepatocellular carcinoma (HCC). A total of 385 patients who underwent gadoxetic acid-enhanced magnetic resonance imaging, including triple arterial phases using either CS (n = 224) or VS (n = 161) techniques, were retrospectively included. Among them, 117 patients had 171 focal liver observations (median diameter, 1.3 cm), which were classified according to Liver Imaging Reporting and Data System version 2018. The acquisition rate of optimally timed late arterial phase (LAP) was assessed, and image quality, including respiratory motion artifact and observation conspicuity, was rated on a 4-point scale by 3 radiologists. The Mann-Whitney U test and nonparametric test for repeated measures data were used for image quality and observation conspicuity analysis. The jackknife alternative free-response receiver operating characteristics method was used to compare the observation detectability between the 2 techniques. The CS technique showed significantly higher acquisition rate of optimally timed LAP without transient severe motion (82.1% [184/224] vs 71.4% [115/161]; P = 0.013) than the VS technique. The CS technique also demonstrated significantly improved overall image quality (3.42 ± 0.70 vs 2.97 ± 0.61; P < 0.001) compared with the VS technique. Regarding the detection of hyperenhancing observations, there was no significant difference between the figure of merits of CS and VS techniques (0.660 vs 0.665; P = 0.890). However, the CS technique showed a higher detection rate in Liver Imaging Reporting and Data System M (LR-M, probably or definitely malignant but not HCC specific) observations than the VS technique (100.0% [9/9] vs 44.4% [8/18]; P = 0.009). The CS technique tended to provide optimally timed LAP without transient severe motion and demonstrated greater detection rate of LR-M observations than the VS technique in patients at high risk of HCC.

MOCHA

The database systems course is offered in many major universities. A key learning goal of learners taking such a course is to understand how sql queries are processed in an RDBMS in practice. To this end, comprehension of the impact of various physical operators on the selected query execution plan (QEP) of a query is paramount. Unfortunately, off-the-shelf RDBMS typically only expose the QEP to users without revealing information about the impact of alternative choices of various physical operators on it in a user-friendly manner to aid learning. In this demonstration, we present a novel system called MOCHA that facilitates exploration and visualization of the impact of alternative physical operator choices on the QEP of a given SQL query. MOCHA accepts an SQL query as input, and compares and visualizes the QEP and alternative plans which are selected based on learner-specified operator preferences. Furthermore, it intuitively explains why the key operators in a QEP are chosen by connecting them to established knowledge in the literature.

Improve Product Quality and Production Process with Integration of Six Sigma and Quality Management System ISO 9001: A Case Study of Bakery Shop in France

This study highlights macarons product research conducted in a bakery shop in France. It is aims to optimize the quality of the macarons products via the integration of Six Sigma and Quality Management System, ISO 9001. To achieve the objective, the study first identifies the primary root cause of product defects. Besides, an alternative standard operating procedure is incorporated with the recommended improvements. The DMAIC approach is emphasized by the Six Sigma approach, which is Define-Measure-Analyze-Improve-Control. According to the data, the cost of poor quality for a month is 34,511.40 Euro. Cracked macarons (53.70%), hollow macarons (16.30%), and no feet macarons (16.10%) are three major critical defects. The macarons product has a Sigma level of 2.50. The parameters proposed in this study are low-level mixing at 80 rpm, 12 minutes of baking time, and 203°c oven temperature to improve the quality of macarons product using the Design of Experiment (DOE) of the Taguchi Method. When the major elements are controlled inside the processes, the company's chances of producing a high-quality product increase significantly. As a result of adopting Six Sigma with Quality Management System ISO 9001 into the macaron manufacturing process, defects costs and rate is expected to be lower.

Hartmann’s operation 100 years later: Time to think and stop?

When Henri Hartmann invented his operation in 1921, his intent was not for use in benign disease but as an alternative for Miles’ abdominoperineal resection which, at that period, had a high mortality rate. With advancements in medicine, Hartmann’s procedure was replaced by abdominoperineal resection which had a significant drop in mortality. In the 1980s to the 1990s, however, there was a renewed interest in Hartmann’s procedure as an alternative management for perforated diverticular disease leading to the formation of guidelines that advocated its use. Since then, resection with primary anastomosis has replaced Hartmann’s as the standard of care and with the alternative operations available for colorectal cancers, the place for Hartmann’s operation in medicine should be clearly defined.

Modeling, simulation, and experiments on waste kinetic energy utilization

Saving energy is as important as energy production. In systems like cars, trains, elevators, and machines that require frequent start/stop operation, a significant amount of kinetic energy is wasted during braking. It may be necessary to employ a sophisticated breaking mechanism to catch waste kinetic energy for later usage. Several criteria influence the proposed braking mechanism. A hydraulic test bench is developed and built to investigate how much kinetic energy can be absorbed and stored during braking using a hydraulic circuit. The test bench’s driving power is a variable voltage and variable frequency electric motor that drives a flywheel that constitutes the majority of the kinetic energy with speeds ranging from 876 to 2975 rpm. A positive displacement gear pump, flow control valve, non-return valve, on/off valve, direction control valve, and an accumulator are the major components of the hydraulic circuit. The use of an automated contactor and a magnetic clutch allows for alternate operations between the mechanical system and the hydraulic brake circuit. The entire system is theoretically modeled, and a MATLAB code is created to investigate the impact of various parameters on the braking mechanism’s performance. Four groups of experiments were conducted to investigate the features of the driving and braking systems, as well as the influence of various factors on the amount of energy that may be collected during braking. The results indicate that 18% to 55% of the kinetic energy may be absorbed and transformed into hydraulic power stored in the accumulator. The amount of hydraulic power gained is governed by the operating speed and restriction ratio (hydraulic system resistance). At certain rotational speeds and restriction ratios, maximum gain hydraulic power could well be produced. Not only can braking energy regeneration improve system efficiency, but it also provides environmental benefits. Alexandria, Egypt is used as a case study to investigate the economic and environmental benefits of employing this technology in cars.

Mixer-phaser Ansätze for quantum optimization with hard constraints

We introduce multiple parametrized circuit ansätze and present the results of a numerical study comparing their performance with a standard Quantum Alternating Operator Ansatz approach. The ansätze are inspired by mixing and phase separation in the QAOA, and also motivated by compilation considerations with the aim of running on near-term superconducting quantum processors. The methods are tested on random instances of a quadratic binary constrained optimization problem that is fully connected for which the space of feasible solutions has constant Hamming weight.For the parameter setting strategies and evaluation metric used, the average performance achieved by the QAOA is effectively matched by the one obtained by a ”mixer-phaser” ansatz that can be compiled in less than half-depth of standard QAOA on most superconducting qubit processors.

Expandable Lateral Lumbar Cages With Integrated Fixation: A Viable Option for Rostral Adjacent Segment Disease.

Adjacent segment disease (ASD) above a previous posterior lumbar instrumented fusion can be managed with minimally invasive lateral lumbar interbody fusion. Earlier procedures with stand-alone lateral cages risked nonunion, and lateral cages with separate lateral plates risked lumbar plexus injury and vertebral fracture. We investigated clinical and radiographic outcomes of an expandable lateral titanium interbody cage with an integrated lateral fixation (eLLIFp) device as a stand-alone treatment for symptomatic ASD above a previous posterior lumbar fusion and performed a comparative cost analysis of eLLIFp to alternative operations for ASD. In this prospective, observational study, patients with ASD above 1-, 2-, 3-, or 4-level instrumented posterior fusions underwent surgery with lateral expandable titanium cage(s) with an integrated lateral plate with single screws into each adjacent vertebra from August 2017 to August 2019. Multimodality intraoperative neural monitoring was performed. Patient-reported outcomes, computed tomography outcomes, and total costs were analyzed. A total of 33 patients received 35 eLLIFp cages. All clinical outcomes improved significantly. The eLLIFp cages added 2.2° segmental lordosis and 2.7 mm posterior disc height. Interbody fusion rate was 94% at 12 months. There were 2 neurologic complications (6%): 1 patient reported transient anterior thigh numbness and 1 had mild persistent L4 radiculopathy. No cage subsidence, cage migration, screw loosening, or vertebral fracture occurred. No revision lateral surgery, posterior decompression, or supplemental posterior fixation was required. The total eLLIFp cost (AU$19,715) was lower than the cost for all other procedures. eLLIFp provided a minimally invasive, low morbidity, cost-effective, and robust alternative to traditional posterior construct extension surgery for rostral lumbar ASD in selected patients with 1- to 2-level stenosis and minimal deformity. Traditional ASD treatment involves substantial risks and expense. eLLIFp should be considered a safe, effective, and lower cost alternative to posterior construct extension surgery.

Graph Matching with Distance-Preserving Crossover

Graph models are fundamental to any kind of application on structured real-world problems. Any comparison between graphs by a graph distance measure requires the solution of the inexact graph matching problem, which constitutes a hard combinatorial optimization problem. An inexact matching problem includes in its formulation robustness to any type of perturbation, such as, for instance, noise, inherently present in real-world environments. In this paper, we introduce the concept of distance-preserving crossover operators for genetic algorithms for this task. For large graphs, our algorithm outperforms any state-of-the-art approximate algorithm—in particular, genetic algorithms with alternative crossover operators, which are to the best of our knowledge currently limited to no more than 50 nodes. We use a two-level local search heuristic to further enhance the results, pushing the limits to up to 300 nodes: a first local search step is directly integrated into the crossover operator; another one is applied independently during offspring generation.

Abstract LB533: TEtor: Improved machine learning approach unveils the clues of cancer lurking in individual TCR repertoire

Abstract T cell receptor (TCR) repertoires are formed by random recombination of genomic precursor elements, some of which mediate recognition of cancer-associated antigens. Identifying these cancer-associated TCRs (caTCRs) could facilitate the early detection of cancers and trace them back to their origins. Due to the complicated processes of T cell immune response, a practical strategy to obtain caTCRs is developing computational methods to identify caTCRs from population and/or individual TCR repertoires. Several machine learning-based methods have been proposed during the latest years and have promoted a series of interesting findings. However, these methods can be further improved by overcoming two vital weaknesses on the design of machine learning framework. First, to facilitate the computational processes, the existing machine learning frameworks prefer to decompose the original TCR sequences into length-fixed amino acid fragments, but the lengths of cancer-associated motifs vary from 3 to 10 amino acids. Second, the correlations among TCRs in the same repertoire should be considered, which are not supported in the existing machine learning frameworks. Thus, we developed a multi-instance learning framework incorporating a convolutional neural network (CNN) model, named TEtor, to solve the issues above. TEtor improves the predictions of caTCRs in pan-cancer TCR repertoires on two aspects. On one hand, the CNN model is adopted with the alternative convolutional filters and 1-max pooling operations. Such design of CNN model is able to handle the amino acid fragments with different lengths, and thus realizing the identification of cancer-associated motifs with various lengths. On the other hand, the multi-instance learning framework calculates the correlations among TCRs and assigns an adjusted weight for each TCR according to the prediction and training process. When training this machine learning model, to speed up the convergence, we adopted a filtering step, which only retains the top 500 abundant TCR sequences in each repertoire. To validate the performance of TEtor, we conducted a series of experiments on several cohorts of patients encompassing 11 different cancers. Compared to the existing machine learning methods, TEtor achieved better prediction performance on accuracy, sensitivity, specificity and areas under the curves (AUCs) on most of the cohorts. For all of the tested cancer types, TEtor obtained an AUC above 0.7 (e.g. thyroid cancer, 0.97; lung cancer, 0.90; gastrointestinal cancer, 0.9). In conclusion, TEtor is a reasonable and practical framework. It improves the caTCR prediction and could further support the accurate detection of early cancers from individual TCR repertoire data. Citation Format: Ying Xu, Xinyang Qian, Xuanping Zhang, Jiayin Wang. TEtor: Improved machine learning approach unveils the clues of cancer lurking in individual TCR repertoire [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB533.

Global time-optimal B-spline feedrate scheduling for a two-turret multi-axis NC machine tool based on optimization with genetic algorithm

Feedrate scheduling is of great significance in numerical control machining for the improvement of the surface finish and machining efficiency. For multi-axis machine tools with more than two rotary axes, the feedrate scheduling issue considering the geometry and drive constraints is highly complicated due to the nonlinear kinematic relationship between the cutter location and drive axes. In this paper, a general optimization-based time-optimal feedrate scheduling method for two-turret machine tools with three-rotary axes and one short linear axis is proposed. The closed-form solution for the inverse kinematics of the machine tool is developed to analytically determine the preferable motion of each drive axis for a desired motion of the cutter. By using the B-spline method to represent the feedrate profile, the optimization-based feedrate scheduling model is built, where the control points and knot vector are designated as the decision variables. Two alternative operations, namely the progressive knot insertion and genetic-algorithm-based optimization, are conducted to determine the knot vector and control points for a time-optimal feedrate, respectively. To improve the robustness and computational efficiency of the algorithm, a feedrate profile segmentation criteria is established for concurrent computing. Without any simplification of the constraints, the proposed method can be employed to produce a global time-optimal feedrate efficiently. Typical simulation cases and experiments are carried out to verify the effectiveness and time-optimality of the proposed method.

QuOp_MPI: A framework for parallel simulation of quantum variational algorithms

QuOp_MPI is a Python package designed for parallel simulation of quantum variational algorithms. It presents an object-orientated approach to quantum variational algorithm design and utilises MPI-parallelised sparse-matrix exponentiation, the fast Fourier transform and parallel gradient evaluation to achieve the highly efficient simulation of the fundamental unitary dynamics on massively parallel systems. In this article, we introduce QuOp_MPI and explore its application to the simulation of quantum algorithms designed to solve combinatorial optimisation algorithms, including the Quantum Approximation Optimisation Algorithm, the Quantum Alternating Operator Ansatz, and the Quantum Walk-assisted Optimisation Algorithm.

The chemistry insight: epoxy sealant as an alternative remedial operation for well integrity

Abstract Epoxy resin is commonly used in the oil and gas industry due to its excellent toughness, low shrinkage, good adhesive strength, and relatively good thermal resistance. It is used for water shutoff, zonal isolation, cementing, enhanced oil recovery, and preventing leakage in wells. This paper reviews the chemistry aspect of using an epoxy resin system as a sealant to prevent well leakage and it offers insights into the chemistry of the epoxy resin system, as applied in previous studies. The paper also unveils the reasons for the application of this system from the chemistry perspective, allowing this aspect to be better understood. Success in the investigated cases depended on the formulation design. The epoxide and hydroxyl functional groups have been found to contribute substantially to the excellent performance of the sealant system. Furthermore, the amine curing agent triggers the abrupt reaction of the oxirane ring to stabilise when the cured sealant is perfectly applied. Based on the findings, it is suggested that other types of epoxies, namely epoxidised oils, require further study. Finally, in terms of safety and sustainable energy, it is suggested that more curing agent and diluent studies are undertaken.