Low Probability Of Success Research Articles

On prices and returns in commercial prediction markets

The Commodity Futures Trading Commission (CFTC) has recently licensed a commercial prediction market to operate in the US. With regulatory restrictions lifted, these markets can now play the important role that has been often envisaged for them. For example, investors can use them to hedge various event-related risks directly rather than indirectly via portfolios expected to move a certain way if events occur. Commercial prediction markets charge fees, an element that has not been incorporated into previous theoretical work on these markets. We examine the impact of fees on prediction market prices and returns by introducing them to a model in which the market price equals the true probability when there are no fees. We find that existing fee models mean contract prices for low probability outcomes are below the true probability but the impact of fees means prediction markets feature a form of favorite-longshot bias: Post-fee loss rates depend negatively on the probability of the event being backed. We show this result holds even if prediction market operators set a fee structure that is more generous to contracts with a low probability of success.

Vulnerability in in-vitro fertilisation transformative services: an interplay of individual and institutional factors

PurposeThe purpose of this paper is to empirically examine the factors driving and mitigating the experienced vulnerabilities of women undergoing the transformative service of in-vitro fertilisation (IVF), and how this influences women’s evaluations and intentions.Design/methodology/approachThe conceptual framework was tested using quantitative data collected via an online survey of Australian women who have undergone IVF treatment. Hayes’ PROCESS macro was used to analyse the data.FindingsThe results indicate that women’s persistent goal-striving alongside their perceived personal sacrifices influence the association between their need for parenthood and their experienced vulnerability. Institutional factors such as IVF clinic technical and interpersonal quality influence these consumers’ IVF experience evaluations and word-of-mouth (WoM) intentions.Research limitations/implicationsThis study’s results are limited to women who are undergoing IVF treatment. Further empirical work is needed to deepen the understanding of the role played by partners and other family members in women’s IVF experiences.Practical implicationsIVF clinics can reduce women’s experienced vulnerability by encouraging women who have a good probability of succeeding to persist in the pursuit of the goal of conceiving a child via IVF. This can be achieved by enabling and empowering them so that they give themselves the best chance during treatment, thus facilitating their control. Managing the expectations of those women with a lower probability of success is also recommended. The importance of the technical and interpersonal quality delivered by IVF clinics in influencing the positive evaluations and behavioural intentions of women experiencing vulnerabilities is further highlighted.Originality/valueThis study contributes to the transformative service research literature by: examining the IVF transformative experience, which has been largely overlooked; focussing on the intersection of transformative services and consumers experiencing vulnerability, which is an emerging research area; and testing a framework quantitatively that intermingles individual and institutional factors as antecedents and consequences of consumers’ experienced vulnerabilities, advancing the existing conceptual and qualitative work.

Abstract 2623: Investigation into factors influencing probability of success in oncology clinical trials and trends over time

Abstract The regulatory approval process for new therapies in oncology involves costly clinical trials that can span multiple years and historically have had a low probability of success. To derive estimates of the probability of success and other related risk characteristics in oncology clinical trials, we searched Informa Pharma Intelligence's Trialtrove and Pharmaprojects databases for oncology-specific drug-indication programs between 2001 and 2020. In total, we identified 10,083 oncology-specific drug-indication programs, which included 2,800 therapeutic agents (excluding biosimilars) tested across 98 indications. The features we considered included indication and indication group, clinical phase, follow-on indication status, presence and type of patient selection biomarker, drug modality, and accelerated approval status. In several cases, clinical success rates were higher than the benchmark oncology historical average of the phase 1 to approval success rate of 4.1% found in our sample set. For example, the use of pre-selection biomarkers in early clinical development was associated with a greater than two-fold increase in probability of approval from phase 1. Moreover, drugs with prior approvals in another indication were more than three times more likely to be successful from phase 1 than a candidate targeting a novel mechanism. In addition, we found that monoclonal antibodies were numerically more successful than other modalities in the historical data, while oncolytic viruses, vaccines, and bispecific antibodies have been less successful. In all cases, concomitant with the emergence of genomic technologies, an improved scientific understanding of cancer biology, and an evolving regulatory environment that includes a higher number of accelerated approvals, success rates in oncology have improved during the time period of this analysis and particularly in the past 5 years. Citation Format: Mary Jane Hinrichs, Shomesh E. Chaudhuri, Robert Bowden, Andrew W. Lo, David W. Jenkins. Investigation into factors influencing probability of success in oncology clinical trials and trends over time [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2623.

Prioritizing restoration areas to conserve multiple sagebrush-associated wildlife species

Strategic restoration of altered habitat is one method for addressing worldwide biodiversity declines. Within the sagebrush steppe of western North America, habitat degradation has been linked to declines in many species, making restoration a priority for managers; however, limited funding, spatiotemporal variation in restoration success, and the need to manage for diverse wildlife species make decision-making regarding restoration actions challenging. To address the challenge of spatial conservation prioritization, we developed the Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET). This decision support tool utilizes the prioritizr package in program R and an integer linear programming algorithm to select parcels representing both high biodiversity value and high probability of restoration success. We tested PReSET on a sagebrush steppe system within southwestern Wyoming using distributional data for six species with diverse life histories and a spatial layer of predicted sagebrush recovery times to identify restoration targets at both broad and local scales. While the broad-scale portion of our tool outputs can inform policy, the local-scale results can be applied directly to on-the-ground restoration. We identified restoration priority areas with greater precision than existing spatial prioritizations and incorporated range differences among species. We noted tradeoffs, including that restoring for habitat connectivity may require restoration actions in areas with lower probability of success. Future applications of PReSET will draw from emerging datasets, including spatially-varying economic costs of restoration, animal movement data, and additional species, to further improve our ability to target effective sagebrush restoration.

The American Society of Colon and Rectal Surgeons Clinical Practice Guidelines for the Management of Colonic Volvulus and Acute Colonic Pseudo-Obstruction.

The American Society of Colon and Rectal Surgeons Clinical Practice Guidelines for the Management of Colonic Volvulus and Acute Colonic Pseudo-Obstruction.

GPCR-Based Bioactive Peptide Screening Using Phage-Displayed Peptides and an Insect Cell System for Insecticide Discovery.

The discovery of new insecticides improves integrated pest management (IPM), but is usually a long high-risk process with a low probability of success. For over two decades, insect neuropeptides (NPs) and their G-protein coupled receptors (GPCRs) have been considered as biological targets for insect pest control, because they are involved in almost all physiological processes associated with insect life stages. A key roadblock to success has been the question of how large volume chemical libraries can be efficiently screened for active compounds. New genomic and proteomic tools have advanced and facilitated the development of new approaches to insecticide discovery. In this study, we report a novel GPCR-based screening technology that uses millions of short peptides randomly generated by bacteriophages, and a method using an insect Sf9 cell expression system. The fire ant is a good model system, since bioactive peptides have been identified for a specific GPCR. The novel small peptides could interfere with the target GPCR-ligand functions. Therefore, we refer to this new mechanism as “receptor interference” (RECEPTORi). The GPCR-based bioactive peptide screening method offers multiple advantages. Libraries of phage-displayed peptides (~109 peptides) are inexpensive. An insect cell-based screening system rapidly leads to target specific GPCR agonists or antagonists in weeks. Delivery of bioactive peptides to target pests can be flexible, such as topical, ingestion, and plant-incorporated protectants. A variety of GPCR targets are available, thus minimizing the development of potential insecticide resistance. This report provides the first proof-of-concept for the development of novel arthropod pest management strategies using neuropeptides, and GPCRs.

Prediction of extubation outcome in mechanically ventilated patients: Development and validation of the Extubation Predictive Score (ExPreS).

Despite the best efforts of intensive care units (ICUs) professionals, the extubation failure rates in mechanically ventilated patients remain in the range of 5%–30%. Extubation failure is associated with increased risk of death and longer ICU stay. This study aimed to identify respiratory and non-respiratory parameters predictive of extubation outcome, and to use these predictors to develop and validate an “Extubation Predictive Score (ExPreS)” that could be used to predict likelihood of extubation success in patients receiving invasive mechanical ventilation (IMV). Derivation cohort was composed by patients aged ≥18 years admitted to the ICU and receiving IMV through an endotracheal tube for >24 hours. The weaning process followed the established ICU protocol. Clinical signs and ventilator parameters of patients were recorded during IMV, in the end phase of weaning in pressure support ventilation (PSV) mode, with inspiratory pressure of 7 cm H2O over the PEEP (positive end expiratory pressure). Patients who tolerated this ventilation were submitted to spontaneous breathing trial (SBT) with T-tube for 30 minutes. Those who passed the SBT and a subsequent cuff-leak test were extubated. The primary outcome of this study was extubation success at 48 hours. Parameters that showed statistically significant association with extubation outcome were further investigated using the receiver operating characteristics (ROC) analysis to assess their predictive value. The area under the curve (AUC) values were used to select parameters for inclusion in the ExPreS. Univariable logistic regression analysis and ROC analysis were performed to evaluate the performance of ExPreS. Patients’ inclusion and statistical analyses for the prospective validation cohort followed the same criteria used for the derivation cohort and the decision to extubate was based on the ExPreS result. In the derivation cohort, a total of 110 patients were extubated: extubation succeeded in 101 (91.8%) patients and failed in 9 (8.2%) patients. Rapid shallow-breathing index (RSBI) in SBT, dynamic lung compliance, duration of IMV, muscle strength, estimated GCS, hematocrit, and serum creatinine were significantly associated with extubation outcome. These parameters, along with another parameter—presence of neurologic comorbidity—were used to create the ExPreS. The AUC value for the ExPreS was 0.875, which was higher than the AUCs of the individual parameters. The total ExPreS can range from 0 to 100. ExPreS ≥59 points indicated high probability of success (OR = 23.07), while ExPreS ≤44 points indicated low probability of success (OR = 0.82). In the prospective validation cohort, 83 patients were extubated: extubation succeeded in 81 (97.6%) patients and failed in 2 (2.4%) patients. The AUC value for the ExPreS in this cohort was 0.971. The multiparameter score that we propose, ExPreS, shows good accuracy to predict extubation outcome in patients receiving IMV in the ICU. In the prospective validation, the use of ExPreS decreased the extubation failure rate from 8.2% to 2.4%, even in a cohort of more severe patients.

Strategic introduction of a new product under uncertainty: A duopoly case

We present a continuous‐game of two symmetric firms competing strategically to launch a new product, simultaneously or sequentially. In the timing game, where each firm decides when to launch, we consider the uncertainty of profits and that the launch is successful with a probability that can be less than one. We find that when the first‐mover advantage (FMA) is large, even with a low probability of success, one firm preempts the other deteriorating the leader's value function. The simultaneous investment dominates the sequential one when the FMA is small or when the probability is almost zero.

Adding essential oils to emergence tents has taxon-specific effects on trapping efficiency of ground-nesting bees

Soil emergence tents (e-tents) are a new tool for studying the nesting biology of ground-nesting bees. E-tents allow us to link nests with specific soil conditions; however, low success probabilities (≤ 20% of e-tents capture at least one bee) and long deployment times (> 72 h) limit their efficiency. We examined if adding scents—spearmint and lemongrass essential oils—increases how quickly e-tents capture bees actively nesting in the soil directly covered by the trap (“capture rate”), letting e-tents be moved more frequently to sample more area. Adding essential oils did not have a significant effect on the overall capture rate. However, in e-tents with spearmint essential oil, bees in the family Halictidae were captured 1.80× faster, and there was a trend for reduced capture rate for the family Andrenidae. The efficacy of adding scents to e-tents appears to be taxon-specific. Researchers interested in halictid nesting biology may increase the efficacy of e-tents with spearmint essential oil, but further work is needed to find a suitable attractant for other groups or whole communities.

R15 Long-term Outcome Following Mitral Valve Repair in Rheumatic Heart Disease

Mitral valve repair (MVr) for rheumatic heart disease (RHD) is considered to have a low probability of success. This retrospective study evaluates the efficacy of MVr in RHD.

BMP and TGFβ use and release in bone regeneration

A fracture that does not unite in nine months is defined as nonunion. Nonunion is common in fragmented fractures and large bone defects where vascularization is impaired. The distal third of the tibia, the scaphoid bone or the talus fractures are furthermore prone to nonunion. Open fractures and spinal fusion cases also need special monitoring for healing. Bone tissue regeneration can be attained by autografts, allografts, xenografts and synthetic materials, however their limited availability and the increased surgical time as well as the donor site morbidity of autograft use, and lower probability of success, increased costs and disease transmission and immunological reaction probability of allografts oblige us to find better solutions and new grafts to overcome the cons. A proper biomaterial for regeneration should be osteoinductive, osteoconductive, biocompatible and mechanically suitable. Cytokine therapy, where growth factors are introduced either exogenously or triggered endogenously, is one of the commonly used method in bone tissue engineering. Transforming growth factor β (TGFβ) superfamily, which can be divided structurally into two groups as bone morphogenetic proteins (BMPs), growth differentiation factors (GDFs) and TGFβ, activin, Nodal branch, Mullerian hormone, are known to be produced by osteoblasts and other bone cells and present already in bone matrix abundantly, to take roles in bone homeostasis. BMP family, as the biggest subfamily of TGFβ superfamily, is also reported to be the most effective growth factors in bone and development, which makes them one of the most popular cytokines used in bone regeneration. Complications depending on the excess use of growth factors, and pleiotropic functions of BMPs are however the main reasons of why they should be approached with care. In this review, the Smad dependent signaling pathways of TGFβ and BMP families and their relations and the applications in preclinical and clinical studies will be briefly summarized.

An Anti-migration Self-expandable and Removable Metal Stent for Crohn's Disease Strictures: A Nationwide Study From GETAID and SFED.

In Crohn's disease, strictures are frequent and may require surgical resection or endoscopic balloon dilation. An anti-migration, removable and shaped self-expandable metal stent is available. We evaluated its effectiveness and safety in a real-life setting. All centres were asked to collect retrospectively or prospectively all data on patients who had a stent for a stricture. The anti-migration stent [Hanarostent HRC-20-080-230-MITech, Seoul, South Korea] was maintained 7 days before its extraction during a second colonoscopy. Short- and long-term efficacy and safety outcomes were evaluated. A total of 46 patients were enrolled. Strictures were anastomotic in 73.9% of cases. The median length of the stricture evaluated by cross-sectional imaging and during colonoscopy was 3.1 ± 1.7 and 2.7 ± 1.4 cm, respectively. Immediate success [no obstructive symptom at Day 30] was reported in 93.5% of cases (95% confidence interval [CI] = [86.3; 99.9]). Sixteen patients needed a new balloon dilation [n = 8] or surgery [n = 8]. The overall success rate [obstruction-free without any intervention] was 58.7% [n = 27] after a median follow-up of 26 months [8-41 months]. No perforation occurred and three migrations were observed [6.5%]. Perianal disease (hazard ratio [HR] = 0.1 [0.02; 0.58]) and discontinuation of an immunosuppressant (0.12 [0.02; 0.86]), were associated with a lower probability of success, whereas performing imaging (HR = 5.3 [1.2; 23.5]) before stent placement was associated with success. The anti-migration stent is safe and effective in about half of patients, with no perforation reported in this study, and has an extremely low migration rate.

Simulation Informed Design and Performance of In Vitro Bioequivalence Trials for Particle Size Distributions.

This study used statistical simulations to investigate the performance of the population bioequivalence test applied to image-based particle size measurements (such as morphologically directed Raman spectroscopy) and methods for designing in vitro bioequivalence trials using prior information. Simulations of in vitro population bioequivalence trials were conducted across a range of representative D50 (number-weighted median particle diameter from a log-normal particle size distribution) and span (which is defined as [Formula: see text] where D90 and D10 are the number-weighted 90th and 10th percentiles in particle diameters sampled from a log-normal particle size distribution) values respectively. The performance of the population bioequivalence test in the simulations was driven by an interplay between overall test variability and the widening or narrowing of the bioequivalence region due to variance terms in the test statistic definition. These findings were dependent upon differences in the variability of D50 and span and may generalise to a wider range of in vitro metrics. Trial design optimisation using power and assurance approaches followed patterns consistent with these findings. As more novel scientific methods are applied to the development of complex generic drug products, the procedures outlined in this study may be used at the inception stage of future in vitro bioequivalence trials to reduce the risk of conducting costly trials with low probabilities of success.

Efficient two-stage sequential arrays of proof of concept studies for pharmaceutical portfolios.

Previous work has shown that individual randomized "proof-of-concept" (PoC) studies may be designed to maximize cost-effectiveness, subject to an overall PoC budget constraint. Maximizing cost-effectiveness has also been considered for arrays of simultaneously executed PoC studies. Defining Type III error as the opportunity cost of not performing a PoC study, we evaluate the common pharmaceutical practice of allocating PoC study funds in two stages. Stage 1, or the first wave of PoC studies, screens drugs to identify those to be permitted additional PoC studies in Stage 2. We investigate if this strategy significantly improves efficiency, despite slowing development. We quantify the benefit, cost, benefit-cost ratio, and Type III error given the number of Stage 1 PoC studies. Relative to a single stage PoC strategy, significant cost-effective gains are seen when at least one of the drugs has a low probability of success (10%) and especially when there are either few drugs (2) with a large number of indications allowed per drug (10) or a large portfolio of drugs (4). In these cases, the recommended number of Stage 1 PoC studies ranges from 2 to 4, tracking approximately with an inflection point in the minimization curve of Type III error.

Drug development in oncology and devices-lessons for heart failure drug development and approval? a review.

Heart failure (HF) and cancer are of the most common diseases globally, both associated with significant adverse outcomes and greatly impaired quality of life. Despite those similarities, over the last 15 years, the United States (USA) and European authorities have approved only 5 and 3 new drugs for HF respectively, none using an accelerated process and none for patients with either acute HF (AHF) or with HF and preserved ejection fraction (HFpEF). During the same period, more than 100 new drugs were approved for treatment of various cancers, several receiving accelerated approval. HF drugs in the last 15 years were mostly approved for reduction in mortality, whereas most approved cancer drugs addressed disease progression and surrogate markers. Consequently, the size of the trials in HF were far greater than those in oncology which was associated with lower probability of success. Given the larger study size and smaller probability of approval, pharma progressively reduces the necessary investments in new HF drugs. We suggest for HF drugs be developed, especially those used to treat patients with HFpEF and AHF, consideration of approval based beyond morbidity and mortality on improvements in symptoms and functional capacity and, like oncology, based on measures of disease progression and end organ damage. At the same time, HF drug development should adopt some approaches used in other diseases (such as oncology) focusing on better defining specific phenotypes and defining specific disease-related targets for new drugs.

The CTo-aBCDE score: A new predictor of success in chronic total occlusions

IntroductionPatient selection for percutaneous coronary intervention (PCI) in chronic total occlusions (CTOs) is crucial to procedural success. Our aim was to identify independent predictors of success in CTO PCI in order to create an accurate score. MethodsIn a single-center observational registry of CTO PCI, demographic and clinical data and anatomical characteristics of coronary lesions were recorded. Linear and logistic regression analysis were used to identify predictors of success. A score to predict success was created and its accuracy was measured by receiver operating curve analysis. ResultsA total of 377 interventions were performed (334 patients, age 68±11 years, 75% male). The success rate was 65% per patient and 60% per procedure. Predictors of success in univariate analysis were absence of active smoking (OR 2.02, 95% CI 1.243-3.29; p=0.005), presence of tapered stump (OR 5.2, 95% CI 2.7-10.2; p<0.001), absence of tortuosity (OR 6.44; 95% CI 3.02-13.75; p<0.001), absence of bifurcation (OR 1.95; 95% CI 1.08-3.51; p=0.026), absence of calcification (OR 3.1; 95% CI 3.10-5.41; p<0.001), LAD as target vessel (OR 1.9, 95% CI 1.0-3.5; p=0.048), and CTO length <20 mm (OR 3.00, 95% CI 1.69-5.3; p<0.001). Only anatomical factors were independent predictors of success, and an anatomical score (0-11 points) with high accuracy (area under the curve 0.831) was subsequently created. A score <3 was associated with low probability of success (15%), 3-8 with intermediate probability (55%), and >8 with high probability (95%). ConclusionIn our sample only anatomical characteristics were predictors of success. The creation of a score to predict success, with good accuracy, may enable selection of cases that can be treated by any operator, those in which a dedicated operator will be desirable, and those with an extremely low probability of success, which should be considered individually for conservative management, surgical revascularization or PCI by a team experienced in CTO.

Application of Interpretable Machine-Learning Workflows To Identify Brittle, Fracturable, and Producible Rock in Horizontal Wells Using Surface Drilling Data

Summary In this study, we demonstrate the application of an interpretable (or explainable) machine-learning workflow using surface drilling data to identify fracturable, brittle, and productive rock intervals along horizontal laterals in the Marcellus Shale. The results are supported by a thorough model-agnostic interpretation of the input/output relationships to make the model explainable to users. The methodology described here can easily be generalized to real-time processing of surface drilling data for optimal landing of laterals, placing of fracture stages, optimizing production, and minimizing fracture hits. In practice, this information is rarely available in real time and requires tedious and time-consuming processing of logs (including image logs), core, microseismic data, and fiber-optic-sensor data to provide post-job validation of fracture and well placement. Post-completion analyses are generally too late for corrective action, leading to wells with a low probability of success and increasing risk of fracture hits. Our workflow involves identifying geomechanical facies from core and well-log data. We verify that the geomechanical facies derived using core and well-log data have characteristically different brittleness, fracturability, and production characteristics. We test and investigate several different supervised classifiers to relate surface drilling data to the geomechanical facies. The data were divided into training and test data sets, with supervised classification techniques being able to accurately predict the geomechanical facies with 75% accuracy on the test data set. The clusters predicted on test well (unseen data) were qualitatively verified using the microseismic interpretation. The use of Shapley additive explanations (SHAP) helps explain the predictive models, rank the importance of various inputs in the prediction of the facies, and provides both local and global sensitivities. Our study demonstrates that pre-existing natural-fracture networks control both the hydraulic-fracture geometry as well as the production. Natural fractures promote the formation of complex fracture networks with shorter half-lengths, which increase well productivity while minimizing fracture hits and neighboring-well interactions. The natural-fracture network is itself controlled by the geomechanical properties of the rock. The ability of the surface drilling data to reliably predict the geomechanical rock facies provides a powerful tool for real-time optimization of wellbore trajectory and completions.

Sensitivity and uncertainty analysis of a reduced-order model of nonlinear BWR dynamics. III: Uncertainty analysis results

This work presents a paradigm analysis of the standard deviations induced in the state functions of a reduced-order model of Boiling Water Reactor (BWR) dynamics by the standard deviations in this model’s imprecisely known parameters and initial conditions. This analysis is performed in the model’s stable region in phase-space, where the state functions converge asymptotically to finite, time-independent values, as well as in the regions in phase-space where the model’s state functions asymptotically evolve into periodic limit-cycle oscillations. The region in phase-space where the model’s state functions behave chaotically is also analyzed. The standard deviations of the state functions in the various regions in phase-space are computed using the first-order sensitivities of the state functions with respect to the model’s imprecisely known parameters and initial conditions. It is shown that in the stable region, the standard deviations induced by the imprecisely known model parameters and initial conditions in each of the BWR-model’s state functions are very large immediately after perturbing the initially critical reactor, reaching values that are about 10 times larger than the respective state functions themselves. Although these standard deviations decay to small values after about 140 s into the transient, the amplitudes of the oscillations of these standard deviations at the start of the transient are so large as to possibly cause the BWR-system to transit from the stable region into an oscillatory region in phase-space. In the limit-cycle oscillatory regions in phase space, as well as in the chaotic region, the standard deviations of the state functions are very large, so that an accurate prediction of the actual value of the respective state functions has a low probability of success. The results obtained in this work indicate that the methods used herein should be implemented into the models used for the design and routine analysis of BWRs, in order to quantify deterministically the uncertainties induced into the operational characteristics of BWRs by the imprecisely known parameters underlying these models, particularly when BWRs are operated close to the limits of their stability regions/maps.

Encryption scheme against eavesdropper collusion in wireless multi‐user network

In order to resist eavesdropper collusion attack in wireless multi-user network, the authors propose a distributed physical layer encryption (DPLE) scheme with energy-efficient design. The encryption is embedded into rateless coding at both user nodes and relay node. Meanwhile, data frame permutation is added at the relay for increasing randomness. It is noteworthy that the secret key is used as the seed of random number generator, which controls the encoding process and permutation. At receiver, the decryption is united with decoding process without any extra cost, which makes DPLE special in the field of lightweight security. There are two cases considered in security analysis for resisting collusion attack: without error and with error. Typical results are time complexity and attack success probability, respectively. Furthermore, the evaluation for algorithm implementation is investigated. The theoretic result and simulation show that the proposed scheme can combat colluding eavesdroppers by high complexity and very low attack success probability. Moreover, lower computation cost is achieved.

Ultra-high-rate nonclassical light source with 50 GHz-repetition-rate mode-locked pump pulses and multiplexed single-photon detectors.

Heralded single photons (HSPs) and entangled photon pairs (EPPs) via spontaneous parametric down-conversion are essential tools for the development of photonic quantum information technologies. In this paper, we report a novel ultra-high-rate nonclassical light source realized by developing 50 GHz-repetition-rate mode-locked pump pulses and multiplexed superconducting nanowire single-photon detectors. The presence of the single-photon state in the heralded photons with our setup was indicated by the second-order intensity correlation below 1/2 at the heralding rate over 20 Mcps. Even at the rate beyond 50 Mcps, the nonclassicality was still observed with the intensity correlation below unity. Moreover, our setup is also applicable to the polarization-EPP experiment, where we obtained the maximum coincidence rate of 1.6 Mcps with the fidelity of 0.881 ± (0.254 × 10-3) to the maximally entangled state. Our versatile source could be a promising tool to explore various large-scale quantum-photonic experiments with low success probability and heavy attenuation.