25 papers · ranked by Valyu relevance
Yihui Quek, Daniel Stilck França, Sumeet Khatri, Johannes Jakob Meyer + 1 more
Quantum error mitigation has been proposed as a means to combat unwanted and unavoidable errors in near-term quantum computing without the heavy resource overheads required by fault-tolerant schemes. Recently, error mitigation has been successfully applied to reduce noise in near-term applications. In this work…
Manpreet Singh Jattana, Fengping Jin, Hans De Raedt, Kristel Michielsen
'Kristel Michielsen'] A general method to mitigate the effect of errors in quantum circuits is outlined. The method is developed in sight of characteristics that an ideal method should possess and to ameliorate an existing method which only mitigates state preparation and measurement errors. The method is tested on…
Rebecca Hicks, Bryce Kobrin, C. Bauer, Benjamin Nachman
Mitigating errors is a significant challenge for near term quantum computers. One of the most important sources of errors is related to the readout of the quantum state into a classical bit stream. A variety of techniques have been proposed to mitigate these errors with post-hoc corrections. We propose a complementary…
Zhendong Yin, Kai Cui, Zhilu Wu, Liang Yin + 2 more
'Sisi Zlatanova'] The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach of entropy-based TOA…
Madaline Kinlay, Wu Yi Zheng, Rosemary Burke, Ilona Juraskova + 4 more
'Lai Mun Ho' 'Hannah Turton' 'Jason Trinh' 'Melissa T. Baysari'] Background Electronic medical record (EMR) systems provide timely access to clinical information and have been shown to improve medication safety. However, EMRs can also create opportunities for error, including system-related errors or errors that were…
Jing Xin, Kaiyuan Gao, Mao Shan, Bo Yan + 1 more
Ultra-wideband (UWB) sensors have been widely used in multi-robot systems for cooperative tracking and positioning purposes due to their advantages such as high ranging accuracy and good real-time performance. In order to reduce the influence of non-line-of-sight (NLOS) UWB communication caused by the presence of…
Alistair W. R. Smith, Kiran E. Khosla, Chris N. Self, M. S. Kim
We present a scheme to characterize and mitigate readout errors on multi-qubit devices more efficiently using random bit-flips.
Tom Weber, Matthias Riebisch, K. Borras, Karl Jansen + 1 more
—While we expect quantum computers to surpass their classical counterparts in the future, current devices are prone to high error rates and techniques to minimise the impact of these errors are indispensable. There already exists a variety of error mitigation methods addressing this quantum noise that differ in…
Chinmay Hemant Joshi, Anna Dornhaus
The collective behavior of complex systems emerges from the actions and interactions of their individual components. But what if these individuals make mistakes, or deviate from behavior tuned to lead to collective success? Here, we explore the effects of individual errors on collective outcomes. We investigate in…
Authors not listed
This work provides a rigorous theoretical investigation of selective error correction strategies for variational quantum algorithms, with focus on understanding the interplay between error suppression, circuit trainability, and computational resource requirements. We develop a mathematical framework that characterizes…
Alexander M Sevy
Recent advances in DNA sequencing technology have allowed deep profiling of B- and T-cell receptor sequences on an unprecedented scale. However, sequencing errors pose a significant challenge in expanding the scope of these experiments. Errors can arise both by PCR during library preparation and by miscalled bases on…
Varun Totakura, Shayok Chakraborty
Due to the unprecedented success of deep learning, it has become an integral component in several multimedia computing applications in todays world. Unfortunately, deep learning systems are not perfect and can fail, sometimes abruptly, without prior warning or explanation. While reducing the error rate of deep neural…
Ehsan Ahsani-Estahbanati, Vladimir Sergeevich Gordeev, Leila Doshmangir
'Leila Doshmangir'] Background and aim Improving health care quality and ensuring patient safety is impossible without addressing medical errors that adversely affect patient outcomes. Therefore, it is essential to correctly estimate the incidence rates and implement the most appropriate solutions to control and reduce…
Mohammad Hadigol, Hossein Khiabanian
Rapid progress in high-throughput sequencing (HTS) has enabled the molecular characterization of mutational landscapes in heterogeneous populations and has improved our understanding of clonal evolution processes. Analyzing the sensitivity of detecting genomic mutations in HTS requires comprehensive profiling of…
Richard J. Wang, Predrag Radivojac, Matthew W. Hahn
Errors in genotype calling can have perverse effects on genetic analyses, confounding association studies and obscuring rare variants. Analyses now routinely incorporate error rates to control for spurious findings. However, reliable estimates of the error rate can be difficult to obtain because of their variance…
Authors not listed
Development of meta-generalized gradient approximations (meta-GGAs) has generally led to more accurate density-functional approximations, albeit ones that have more stringent requirements for the quadrature grids that are used to evaluate the exchange-correlation energy. Here, we demonstrate that grid-induced errors…
Pengyao Ping, Shuquan Su, Xinhui Cai, Tian Lan + 5 more
Although the per-base erring rate of NGS is very low at 0.1% to 0.5%, the percentage/probability of erroneous reads in a short-read sequencing dataset can be as high as 10% to 15% or in the number of millions. Correction of these wrongly sequenced reads to retrieve their huge missing value will improve many downstream…
Authors not listed
Material properties calculated using density functional theory (DFT) are often corrected to more closely match experimental values, but the most common correction method has flaws that lead to unphysical results and false positives in the material discovery process. In this work, we show that these flaws stem from the…
Surajit Nandi, Jonas Busk, Peter Bjørn Jørgensen, Tejs Vegge + 1 more
Workflows to predict chemical reaction networks based on density functional theory (DFT) are prone to systematic errors in reaction energy due to the extensive use of cheap DFT exchange-correlation functionals to limit computational cost. Recently, machine learning-based models are increasingly applied to mitigate this…
Mostafa Kishani, Reza Eftekhari, Hossein Asadi
—In this paper, we investigate the effect of incorrect disk replacement service on the availability of data storage systems. To this end, we first conduct Monte Carlo simulations to evaluate the availability of disk subsystem by considering disk failures and incorrect disk replacement service. We also propose a Markov…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Alireza Heidari, McGrath Joshua, Ihab F. Ilyas, Theodoros Rekatsinas
We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detection models that require minimal human involvement. Our framework consists of two parts: (1) an expressive model to learn rich representations…
Toshiki Kobayashi, Mitsuaki Takemi, Daichi Nozaki
Even experts can sometimes fail while performing fully learned movements. Do such failures suddenly arise, or are there any forecasting signs? It has been reported that the kinematics of the early phase of movements can predict the failure, and brain activity patterns specific to failures are observed just before the…
K.M. Meer, P.G. Nelson, K. Xiong, J. Masel
Errors in gene transcription can be costly, and organisms have evolved to prevent their occurrence or mitigate their costs. The simplest interpretation of the drift barrier hypothesis suggests that species with larger population sizes would have lower transcriptional error rates. However, Escherichia coli seems to have…
Mostafa Kishani, Hossein Asadi
—Data storage systems and their availability play a crucial role in contemporary datacenters. Despite using mechanisms such as automatic fail-over in datacenters, the role of human agents and consequently their destructive errors is inevitable. Due to very large number of disk drives used in exascale datacenters and…