Low Probability Of Success Research Articles

A Hybrid GNN Approach for Improved Molecular Property Prediction.

The development of new drugs is a vital effort that has the potential to improve human health, well-being and life expectancy. Molecular property prediction is a crucial step in drug discovery, as it helps to identify potential therapeutic compounds. However, experimental methods for drug development can often be time-consuming and resource-intensive, with a low probability of success. To address such limitations, deep learning (DL) methods have emerged as a viable alternative due to their ability to identify high-discriminating patterns in molecular data. In particular, graph neural networks (GNNs) operate on graph-structured data to identify promising drug candidates with desirable molecular properties. These methods represent molecules as a set of node (atoms) and edge (chemical bonds) features to aggregate local information for molecular graph representation learning. Despite the availability of several GNN frameworks, each approach has its own shortcomings. Although, some GNNs may excel in certain tasks, they may not perform as well in others. In this work, we propose a hybrid approach that incorporates different graph-based methods to combine their strengths and mitigate their limitations to accurately predict molecular properties. The proposed approach consists in a multi-layered hybrid GNN architecture that integrates multiple GNN frameworks to compute graph embeddings for molecular property prediction. Furthermore, we conduct extensive experiments on multiple benchmark datasets to demonstrate that our hybrid approach significantly outperforms the state-of-the-art graph-based models. The data and code scripts to reproduce the results are available in the repository, https://github.com/pedro-quesado/HybridGNN.

Optimal attempt scheduling and aborting in heterogenous system performing asynchronous multi-attempt mission

Multi-attempt mission aborting systems have recently received significant attention from the reliability community. Existing models mostly assume parallel or sequential execution of multiple attempts, incurring great cost or low mission success probability (MSP), respectively. This paper advances the state of the art by considering a new model, where system components may be activated with certain delay allowing to activate next one before the previous component leaves the operation, balancing the expected cost of lost components (ECC) and MSP. Each component may abort its attempt according to an individual aborting policy defined by two parameters (the number of survived shocks and an operation time threshold) or upon receiving a common abort command. Because components may have different shock resistances and performance rates, their activation order can affect both MSP and ECC. Thus, we formulate and solve the optimal attempt scheduling and aborting policy (SAP) problem, which determines the vector of component activation times and the individual attempt aborting policy for each component to minimize the expected mission losses (EML). The EML, a function of MSP and ECC, is evaluated using a new numerical procedure. A detailed case study of a cloud data processing system is provided to demonstrate the proposed model.

Selling Bonus Actions in Video Games

In the mobile video games industry, a common in-app purchase is for additional “moves” or “time” in single-player puzzle games. We call these in-app purchases bonus actions. In some games, bonus actions can only be purchased in advance of attempting a level of the game (pure advance sales (PAS)), yet in other games, bonus actions can only be purchased in a “spot” market that appears when an initial attempt to pass the level fails (pure spot sales). Some games offer both advance and spot purchases (hybrid advance sales). This paper studies these selling strategies for bonus actions in video games. Such a question is novel to in-app tools selling in video games, and it cannot be answered by previous advance selling studies focusing on end goods. We model the selling of bonus actions as a stochastic extensive form game. We show how the distribution of skill among players (i.e., their inherent ability to pass the level) and the inherent randomness of the game influence selling strategies. For casual games, where low-skill players have a sufficiently high probability of success in each attempt, if the proportion of high-skill players is either sufficiently large or sufficiently small, firms should adopt PAS and shut down the “spot” market. Furthermore, the player welfare-maximizing selling strategy is to sell only in the spot market. Hence, no “win-win” strategy exists for casual games. However, PAS can be a win-win for hardcore games, where low-skill players have a sufficiently low success probability for each attempt. This paper was accepted by Hemant Bhargava, information systems. Funding: C. T. Ryan received funding from NSERC Discovery [Grant RGPIN-2020-06488]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.02348 .

Deterministic Preparation of Optical Squeezed Cat and Gottesman-Kitaev-Preskill States.

Large-amplitude squeezed cat states and high-quality Gottesman-Kitaev-Preskill (GKP) states are essential for effective quantum error correction, yet their optical preparation has been hindered by challenges such as low success probabilities, small amplitudes, and insufficient squeezing. Addressing these limitations, our research introduces scalable optical schemes for the deterministic preparation of large-amplitude squeezed cat states from photon-number states. Fock states have the benefit of producing consistent cat states across all measurement outcomes and intrinsically provides a degree of squeezing. Notably, these squeezed cat states facilitate the deterministic generation of high-quality approximate GKP states via "breeding," showing that GKP error correction in optics is technically feasible in near-term experiments. Our schemes allow fault-tolerant quantum computation through the use of GKP error correction.

Nest survival of black-backed water tyrant Fluvicola albiventer in relation to nest morphometry and nest site features

ABSTRACT Understanding the relationship between nest site features and the breeding biology of wetland birds is crucial, as these ecosystems are significantly threatened. Particularly, studies assessing Neotropical bird breeding success are sparse. During three consecutive breeding seasons (2016–2019), we monitored 66 nests of the black-backed water tyrant Fluvicola albiventer in central Argentina. We described basic nesting parameters and analysed the relationship between breeding parameters (nest survival, clutch, and brood size), nest site features, and nest morphometry. Breeding season lasted from early September to the end of January, with a peak in October and November. Nests were placed 136.81 ± 60.44 cm above the ground or water. Clutch size was 2.70 ± 0.47 eggs (n = 30 nests), and brood size was 2.11 ± 0.60 chicks (n = 10 nests). We found a positive relationship between external nest width and both clutch and brood size. Conversely, there was a negative relationship between nest concealment and brood size. Daily nest survival rate (DSR) was 0.92, and the cumulative probability of nest survival in a 28 day nesting cycle was 9%. We found a positive influence of external nest width on DSR. We also found a negative relationship between nest concealment and DSR. The low success probability found in this species raises uncertainties about the future of its populations. Moreover, the availability of suitable nesting sites may be affected by wetland degradation. This study could provide valuable insights into the consequences of wetland loss and design strategies for wetlands conservation.

Special issue.: The role of whole genome duplication in evolutionary ecology

Polyploid organisms are common and can be found across the tree of life. A key question is to understand how and why these polyploid lineages become established and persist in populations, particularly since they are predicted to have a low probability of success. While the collection of papers in this special issue addresses broad questions on the evolutionary ecology of polyploids, ultimately, these studies also highlight the myriad ways that we are examining what drives the success of polyploid lineages. In this paper we consider where we've been and the challenges that we face, and then propose several directions that will allow us to continue to propel the field towards our ultimate goal of understanding the rules that govern the establishment and persistence of polyploid populations. We conclude that developing this rule set will require a combination of model systems for which we have detailed knowledge of the phylogenetic and population genetic history, expanding our perspective beyond plants to include greater taxonomic breadth, and conducting studies in ecologically relevant settings. Additionally, we argue that future research on the evolutionary ecology of polyploidy should focus on integrating theory and empirical research, providing mechanistic linkages between the effects of whole genome duplication and population demography, and build a predictive framework to understand how anthropogenic change will impact polyploid organisms.

EFFECTIVENESS OF THE INNOVATION PORTFOLIO IN POLISH ENTERPRISES – RESEARCH RESULTS

A single innovation project has a low probability of success, while the company’s chances of gaining a competitive advantage are low. Only a properly diversified innovation portfolio gives a chance for market success. The aim of the article is to analyze the issue of the effectiveness of innovation portfolio management in Polish enterprises, due to various external and internal factors, and also to identify clues determining the success of the innovation portfolio among enterprises in the future. For this purpose, a literature review in the area of the innovation portfolio was conducted. Also the method of analysis and criticism of the literature was applied. In the research process, empirical articles and Statistics Poland reports were analyzed. As a result of the analyses, effective ways to build innovation portfolio efficiency were identified by pointing out factors that can contribute to key optimization decisions (e.g., proper planning and diversification of the innovation project portfolio). Enterprises, in order to achieve innovation portfolio efficiency in difficult market conditions, should reallocate their resources to less risky innovation projects, and at the same time accepting the risks associated with introducing a transformational innovation.

Creating a place for open innovation among diverse players - a perspective from practitioners at a science park

Twenty years after the concept of open innovation was first proposed, entrepreneurship and horizontal division of labor have become popular in Japan, following the global trend. However, in the life science field, the foundation for open innovation is still in its infancy due to the high degree of specialization, large scale of required investment, and low probability of success. For the five years since its opening in 2018, Shonan Health Innovation Park (Shonan iPark) has taken on the challenge of building an ecosystem to create a place where a diverse range of players can realize open innovation. The key points of the efforts are the multifaceted approach taken by the governing body, which is well versed in life sciences, and on the other hand, the fostering of a mutually supportive mechanism and culture by actively borrowing the strength of the community's constituent members. In this article, we introduce the efforts to support diverse players, including venture companies, from the perspective of a science park that creates a place for open innovation.

Invisible Stripes? A Field Experiment on the Disclosure of a Criminal Record in the British Labour Market and the Potential Effects of Introducing Ban-The-Box Policies

Abstract Labour market discrimination against individuals with criminal records may be unfair, ineffective and counterproductive. This article describes a field experiment designed to indicate whether job applicants disclosing a criminal record in the British labour market have a lower probability of success than equivalent applicants not disclosing criminal records. The research also provides insights into the potential effects of introducing a Ban-The-Box (BTB) policy in the United Kingdom, which would prohibit questions on prior convictions in the first stages of the recruitment process. The results confirm the existence of criminal record discrimination and suggest that introducing a BTB policy would increase job prospects for White applicants with criminal records, but not for members of ethnic minorities.

A HOME FOR THE POLITICALLY HOMELESS? THE AMERICAN SOLIDARITY PARTY, CATHOLICS, AND THIRD PARTIES IN U.S. POLITICS

U.S. Catholics in recent decades have been given the choice between Republicans and Democrats, representing two parties whose platforms diverge significantly from Catholic social teaching (CST). The American Solidarity Party (ASP) was founded on the same principles as CST, particularly consistent respect for the dignity of human life, including safeguards and support for the poor, vulnerable, and oppressed. Thus, it offers U.S. Catholic voters, as well as many other constituencies, an alternative that can greatly reduce their cognitive dissonance regarding CST in the voting process. However, this reduction in cognitive dissonance is balanced by the low probability of immediate electoral success. 71 ASP supporters were interviewed at length to ascertain why they support the party, how they view the party’s internal dynamics, and what they hope to see the party achieve. The ASP attracts supporters committed to upholding human dignity. While members appreciate having finally a found a political home that respects their commitment, their characteristically principled stances often discord with other supporters’ stances. They have developed novel strategies, perhaps shaped by their Christian Democratic ideologies, to navigate their differences to form a united front as they strive to promote, in conventional and unconventional ways, greater protection for human dignity.

Age, brood fate, and territory quality affect nest-site fidelity in white stork Ciconia ciconia

BackgroundA particular type of site fidelity is faithfulness to the nest site, where birds are not only reoccupying breeding territories but also reusing nests built in previous breeding seasons. Staying faithful to the nest site is believed to be an adaptive strategy, and based on the ability to predict an individual's own breeding success, a hypothesis of “win-stay:loose-switch” was proposed. In this study, we aimed to resolve which factors affect the nest-site fidelity of white stork Ciconia ciconia, species known for reusing nests available in the breeding sites. Basing on ring recoveries from 31 years of studies in Western and Southern Poland, we analysed the impact of intrinsic and extrinsic factors on nest-site fidelity.ResultsWe found that increasing age and breeding success (i.e. producing any fledglings or not) increased the probability of reusing the nest, but in the oldest individuals, the probability decreased. In turn, the probability of breeding success increased with age, the increasing number of reproductive events on the particular nest, and the presence on the nest in the previous year. However, the oldest individuals had lower probability of success, as the relationship was curvilinear. The number of fledglings, however, was influenced only by an individual's age. The number of reproductive events on the nest was, in turn, affected by age, with the youngest and oldest individuals using the current nest for the least number of years.ConclusionsOur study shows that the decision process of whether to stay faithful to the nest or switch is based on the experience from the previous breeding event, consistently with the “win-stay:loose-switch” hypothesis. Our results also show that site fidelity benefits white storks, as the probability of breeding success increases if the nest is reused. Results also show the senescence effect that lowers breeding success and site fidelity probabilities.

Socio-economic predictors of Inuit hunting choices and their implications for climate change adaptation.

In the Arctic, seasonal variation in the accessibility of the land, sea ice and open waters influences which resources can be harvested safely and efficiently. Climate stressors are also increasingly affecting access to subsistence resources. Within Inuit communities, people differ in their involvement with subsistence activities, but little is known about how engagement in the cash economy (time and money available) and other socio-economic factors shape the food production choices of Inuit harvesters, and their ability to adapt to rapid ecological change. We analyse 281 foraging trips involving 23 Inuit harvesters from Kangiqsujuaq, Nunavik, Canada using a Bayesian approach modelling both patch choice and within-patch success. Gender and income predict Inuit harvest strategies: while men, especially men from low-income households, often visit patches with a relatively low success probability, women and high-income hunters generally have a higher propensity to choose low-risk patches. Inland hunting, marine hunting and fishing differ in the required equipment and effort, and hunters may have to shift their subsistence activities if certain patches become less profitable or less safe owing to high costs of transportation or climate change (e.g. navigate larger areas inland instead of targeting seals on the sea ice). Our finding that household income predicts patch choice suggests that the capacity to maintain access to country foods depends on engagement with the cash economy. This article is part of the theme issue 'Climate change adaptation needs a science of culture'.

Maze design: size and number of choices impact fish performance in cognitive assays.

Although studies on fish cognition are increasing, consideration of how methodological details influence the ability to detect and measure performance is lagging. Here, in two separate experiments the authors compared latency to leave the start position, latency to make a decision, levels of participation and success rates (whether fish entered the rewarded chamber as first choice) across different physical designs. Experiments compared fish performance across (a) two sizes of T-mazes, large and standard, and a plus-maze, and (b) open choice arenas with either two or four doors. Fish in T-mazes with longer arms took longer to leave the start chamber and were less likely to participate in a trial than fish in T-mazes with shorter arms. The number of options, or complexity, in a maze significantly impacted success but did not necessarily impact behavioural measures, and did not impact the number of fish that reached a chamber. Fish in the plus-maze had similar latencies to leave the start box and time to reach any chamber as fish in the same-sized T-maze but exhibited lower overall success. Similarly, in an open choice arena, increasing the number of options - doors to potential reward chambers - resulted in lower probability of success. There was an influence of reward position in the choice arena, with rewarded chambers closest to the sides of the arena resulting in lower latencies to enter and higher probability of decision success. Together the results allow the authors to offer practical suggestions towards optimal maze design for studies of fish cognition.

331-OR: Fasting Metabolic Flexibility in Prediabetes

Metabolic flexibility cannot be easily clinically assessed, but the respiratory exchange ratio (RER) measured via indirect calorimetry can indicate substrate utilization. When indirect calorimetry is performed to measure resting metabolic rate, a normal RER should reflect a lipolytic metabolism (close to 0.7). We aimed to describe fasting glucose metabolism in relation to RER in patients seeking a nutritional intervention. In 10175 patients (7,222 (71%) females, median (quartiles) age of 46 (36, 55) years, and BMI of 28.3 (25.0, 32.3) kg/m2) a greater RER was associated with higher fasting values of glucose, insulin and higher insulin resistance (HOMA-IR), controlling for sex, age, and BMI (differences going from a RER of 0.7 to 1 RER for glucose 1.7 (95% CI 0.66, 2.8; p=0.002), for insulin 1.9 (95% CI 1.3, 2.6; p=<0.001), and for HOMA-IR 0.49 (95% CI 0.32, 0.66; p=<0.001)). As an higher RER relates to an altered glucose metabolism, within the whole sample we selected patients with prediabetes with 1 year follow-up. We matched 86 patients having either a RER indicating a lipolytic metabolism (<0.775) or glycolytic metabolism (>0.925). Patients were matched for sex, age, BMI, waist circumference, and arm muscle area. The high RER group had a lower probability of normalizing fasting glucose level within 1 year (log(OR) -0.89 (95% CI -1.8, -0.03; p=0.046)), with higher fasting glucose levels at followup (5.4 (95% CI 0.98, 9.9; p=0.017)). Moreover, while losing similar weight than the low RER group (-0.55 (95% CI -3.7, 2.6; p=0.7)), they lost a lower amount of fat mass (1.2 (95% CI 0.02, 2.4; p=0.047)). Our results suggest than an higher RER relates to a dysfunctional glycolytic metabolism at rest. We also show that prediabetic patients with higher RER are more likely to not respond to a lifestyle intervention, warranting a more intensive treatment for this subgroup. This lower probability of success doesn’t seem related to a lower adherence to the proscription, as weight loss was similar across RER categories, but to a lower weight loss quality. Disclosure A.Foppiani: None. R.De amicis: None. A.Leone: None. S.Bertoli: None. A.Battezzati: None. Funding Italian National Recovery and Resilience Plan Mission 4 Component 2 Investment 1.3 - Call for Proposals (341) of 15 March 2022 of Italian Ministry of University and Research funded by the European Union - NextGenerationEU (PE00000003) Concession Decree (1550) of 11 October 2022 adopted by the Italian Ministry of University and Research (CUP D93C22000890001)

Target for campaign success: an empirical analysis of equity crowdfunding in Japan

This study investigates campaign success in equity crowdfunding, using campaigns listed on a leading Japanese equity crowdfunding platform with an all-or-nothing rule. We examine how campaign success depends on campaign- and firm-specific characteristics, including the campaign target amount. We find that patenting positively affects campaign success and the campaign target amount. The results indicate that innovative firms have a higher probability of campaign success, while they set a higher target amount. We also provide evidence that campaigns that have already provided services and products have a lower probability of success, although not always significant, and firms tend to set a lower target amount. Moreover, campaigns launched by venture capital-backed firms are more likely to succeed than others. Furthermore, campaigns launched by firms eligible for the Angel Tax System, introduced in Japan as a tax incentive for investment in young and small firms, have a higher tendency to succeed in equity crowdfunding. Our findings suggest that the Angel Tax System attract more crowd investors and such tax incentives help raise funds on equity crowdfunding platforms for new businesses.

Landscape context importance for predicting forest transition success in central Panama

ContextNaturally recovering secondary forests are frequently re-cleared before they can recover to pre-disturbance conditions. Identifying landscape factors associated with persistence success will help planning cost-efficient and effective forest restoration.ObjectivesThe ability of secondary forest to persist is an often undervalued requisite for long-term ecosystem restoration. Here we identify the landscape context for naturally regenerated forests to persist through time within central Panama.MethodsWe developed a random forest classification (RFC) calibration method to identify areas with high (≥ 90%) and low (< 90%) likelihood of forest persistence success based on their spatial relation with nine landscape explanatory variables.ResultsThe RFC model discriminated between secondary forests areas that persisted and did not persisted with an error rate of 2%. By tuning, we obtained a precision of 0.94 (94%) in the validation test. The two most important explanatory variables involved in the persistence dynamic were elevation and distance to the nearest rural area. Naturally regenerated forests lasted longer in patches that were closer to both Gatun and Alajuela Lakes as to protected areas, but further from rural communities, roads, urban areas and in patches with higher elevation and steeper slopes.ConclusionBy tracking remote sensed, landscape context metrics of easy collection, we developed a prediction map of central Panama areas with high (≥ 90%) and low (> 90%) probability of natural forest regeneration and persistence success within the next 30 years. This map represents a basis for management decisions and future investigations for effective, long-term forest-landscape restoration.

Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.

De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learning and deep learning technology have reduced the time and cost of the discovery process and therefore, improved pharmaceutical research and development. In this paper, we explore the combination of two rapidly developing fields with lead candidate discovery in the drug development process. First, artificial intelligence has already been demonstrated to successfully accelerate conventional drug design approaches. Second, quantum computing has demonstrated promising potential in different applications, such as quantum chemistry, combinatorial optimizations, and machine learning. This article explores hybrid quantum-classical generative adversarial networks (GAN) for small molecule discovery. We substituted each element of GAN with a variational quantum circuit (VQC) and demonstrated the quantum advantages in the small drug discovery. Utilizing a VQC in the noise generator of a GAN to generate small molecules achieves better physicochemical properties and performance in the goal-directed benchmark than the classical counterpart. Moreover, we demonstrate the potential of a VQC with only tens of learnable parameters in the generator of GAN to generate small molecules. We also demonstrate the quantum advantage of a VQC in the discriminator of GAN. In this hybrid model, the number of learnable parameters is significantly less than the classical ones, and it can still generate valid molecules. The hybrid model with only tens of training parameters in the quantum discriminator outperforms the MLP-based one in terms of both generated molecule properties and the achieved KL divergence. However, the hybrid quantum-classical GANs still face challenges in generating unique and valid molecules compared to their classical counterparts.

CE-454610-3 VT STORM DUE TO HYPERTROPHIC CARDIOMYOPATHY TREATED WITH ALCOHOL SEPTAL ABLATION

Radiofrequency (RF) ablation is a guideline-recommended therapy for ventricular tachycardia (VT). However, certain locations can be inaccessible through endocardial or epicardial approach. There are several documented unconventional techniques in these cases where VT is either treatment-refractory to RF ablation, or ablation is unlikely to be successful due to deep intramural substrate. N/A N/A A 66-year-old gentleman with a history of coronary artery disease (CAD) presents with four days of palpitations and lightheadedness to the emergency department. An ECG was performed which showed monomorphic VT from a basal septal focus. He was hemodynamically stable and thus started on a lidocaine drip and intermittent metoprolol IV pushes with conversion to sinus rhythm. Given the history of CAD, primary differential concerns were ischemia-mediated or scar-mediated VT. Thus, the patient underwent a coronary angiogram which revealed stable non-obstructive CAD. The patient then underwent a cardiac MRI which revealed severe asymmetric left ventricular hypertrophy measuring up to 18 mm in the mid-basal interventricular septum with mid-myocardial late gadolinium enhancement in the same area. This was most consistent with hypertrophic cardiomyopathy (HCM) as the etiology for the patient’s VT. As the patient continued to have significant ventricular ectopy and recurrent bouts of sustained VT on medical management, options for VT ablation were discussed. Overall, given the deep intramural location of the suspected VT substrate, endocardial and epicardial approaches were thought to have a low probability of success. Transarterial coronary ethanol ablation (TCEA) of the septum was thought to have the highest likelihood of success at controlling the patient’s VT in the setting of HCM. The patient underwent successful TTE guided TCEA of the first septal branch. Left ventricular outflow tract (LVOT) gradient improved from 45 to 17 mmHg. The patient was observed for 24 hours without evidence of VT. An ICD was subsequently implanted for secondary prevention. The patient was discharged in stable condition on an oral beta blocker without any additional anti-arrhythmic medications. In patients with VT due to HCM where there is a deep intramural substrate not amenable to traditional RF catheter ablation, TCEA is a reasonable approach. We describe a case of successful TCEA in both decreasing a patient’s LVOT gradient as well as cessation of the patient’s treatment refractory VT.

Development and Evaluation of a Simulation-Based Algorithm to Optimize the Planning of Interim Analyses for Clinical Trials in ALS.

Late-phase clinical trials for neurodegenerative diseases have a low probability of success. In this study, we introduce an algorithm that optimizes the planning of interim analyses for clinical trials in amyotrophic lateral sclerosis (ALS) to better use the time and resources available and minimize the exposure of patients to ineffective or harmful drugs. A simulation-based algorithm was developed to determine the optimal interim analysis scheme by integrating prior knowledge about the success rate of ALS clinical trials with drug-specific information obtained in early-phase studies. Interim analysis schemes were optimized by varying the number and timing of interim analyses, together with their decision rules about when to stop a trial. The algorithm was applied retrospectively to 3 clinical trials that investigated the efficacy of diaphragm pacing or ceftriaxone on survival in patients with ALS. Outcomes were additionally compared with conventional interim designs. We evaluated 183-1,351 unique interim analysis schemes for each trial. Application of the optimal designs correctly established lack of efficacy, would have concluded all studies 1.2-19.4 months earlier (reduction of 4.6%-57.7% in trial duration), and could have reduced the number of randomized patients by 1.7%-58.1%. By means of simulation, we illustrate the efficiency for other treatment scenarios. The optimized interim analysis schemes outperformed conventional interim designs in most scenarios. Our algorithm uses prior knowledge to determine the uncertainty of the expected treatment effect in ALS clinical trials and optimizes the planning of interim analyses. Improving futility monitoring in ALS could minimize the exposure of patients to ineffective or harmful treatments and result in significant ethical and efficiency gains.

Optimization of parameter measurement precision with precoupling-assisted weak-value amplification

The weak-value amplification is extensively considered in precision metrology in order to achieve a higher sensitivity. Despite the practical benefits in amplifying small physical quantities, its metrological advantage still arouses a broad debate due to the low postselection probability of success. In this paper, by employing the quantum Fisher information metric, we show that the precision of estimating an unknown parameter can be improved by introducing a precoupling process with properly chosen interaction operators. We point out this result is credible for both real and imaginary weak values. By tracking the meter wave functions, we find this enhancement of estimation precision comes from a precoupling induced modulation of the meter wave function, thus the most sensitive regime with respect to the parameter is reached. In addition, the estimation error is investigated by considering the difference between the theoretical and estimated value. The analysis suggests that this kind of error can be effectively suppressed by averaging the estimations resulted from different initial meter states. These results are finally illustrated by an exact numerical simulation where the advantages of our proposal are displayed by the comparison to the standard weak-value amplification scheme.