Abstract
Quantum comparators and modular arithmetic are fundamental in many quantum algorithms. Current research mainly focuses on operations between two quantum states. However, various ...applications, such as integer factorization, optimization, and financial risk analysis, commonly require one of the inputs to be classical. It requires many ancillary qubits, especially when subsequent computations are involved. In this paper, we propose a quantum–classical comparator based on the quantum Fourier transform. Then we extend it to compare two quantum integers and modular arithmetic. Proposed operators only require up to one ancilla qubit, which is optimal for qubit resources. We analyze limitations in the current modular addition circuit and develop it to process arbitrary quantum states in the entire
n
-qubit space. The proposed algorithms reduce computing resources and make them valuable for noisy intermediate-scale quantum computers.
Abstract
Quantitative trading is an integral part of financial markets with high calculation speed requirements, while no quantum algorithms have been introduced into this field yet. We propose ...quantum algorithms for high-frequency statistical arbitrage trading by utilizing variable time condition number estimation and quantum linear regression. The algorithm complexity has been reduced from the classical benchmark
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, where
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is the desired precision. Moreover, two tool algorithms for condition number estimation and cointegration test are developed.
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Classical simulations of quantum circuits are limited in both space and time when the qubit count is above 50, the realm where quantum supremacy reigns. However, recently, for the low ...depth circuit with more than 50 qubits, there are several methods of simulation proposed by teams at Google and IBM. Here, we present a scheme of simulation which can extract a large amount of measurement outcomes within a short time, achieving a 64-qubit simulation of a universal random circuit of depth 22 using a 128-node cluster, and 56- and 42-qubit circuits on a single PC. We also estimate that a 72-qubit circuit of depth 23 can be simulated in about 16 h on a supercomputer identical to that used by the IBM team. Moreover, the simulation processes are exceedingly separable, hence parallelizable, involving just a few inter-process communications. Our work enables simulating more qubits with less hardware burden and provides a new perspective for classical simulations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The quantum-classical hybrid algorithm is a promising algorithm with respect to demonstrating the quantum advantage in noisy-intermediate-scale quantum (NISQ) devices. When running such algorithms, ...effects due to quantum noise are inevitable. In our work, we consider a well-known hybrid algorithm, the quantum approximate optimization algorithm (QAOA). We study the effects on QAOA from typical quantum noise channels, and produce several numerical results. Our research indicates that the output state fidelity, i.e., the cost function obtained from QAOA, decreases exponentially with respect to the number of gates and noise strength. Moreover, we find that when noise is not serious, the optimized parameters will not deviate from their ideal values. Our result provides evidence for the effectiveness of hybrid algorithms running on NISQ devices.
Abstract Background Pathogenesis and diagnostic biomarkers for diseases can be discovered by metabolomic profiling of human fluids. If the various types of coronary artery disease (CAD) can be ...accurately characterized by metabolomics, effective treatment may be targeted without using unnecessary therapies and resources. Objectives The authors studied disturbed metabolic pathways to assess the diagnostic value of metabolomics-based biomarkers in different types of CAD. Methods A cohort of 2,324 patients from 4 independent centers was studied. Patients underwent coronary angiography for suspected CAD. Groups were divided as follows: normal coronary artery (NCA), nonobstructive coronary atherosclerosis (NOCA), stable angina (SA), unstable angina (UA), and acute myocardial infarction (AMI). Plasma metabolomic profiles were determined by liquid chromatography–quadrupole time-of-flight mass spectrometry and were analyzed by multivariate statistics. Results We made 12 cross-comparisons to and within CAD to characterize metabolic disturbances. We focused on comparisons of NOCA versus NCA, SA versus NOCA, UA versus SA, and AMI versus UA. Other comparisons were made, including SA versus NCA, UA versus NCA, AMI versus NCA, UA versus NOCA, AMI versus NOCA, AMI versus SA, significant CAD (SA/UA/AMI) versus nonsignificant CAD (NCA/NOCA), and acute coronary syndrome (UA/AMI) versus SA. A total of 89 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism, increased amino acid metabolism, increased short-chain acylcarnitines, decrease in tricarboxylic acid cycle, and less biosynthesis of primary bile acid. For differential diagnosis, 12 panels of specific metabolomics-based biomarkers provided areas under the curve of 0.938 to 0.996 in the discovery phase (n = 1,086), predictive values of 89.2% to 96.0% in the test phase (n = 933), and 85.3% to 96.4% in the 3-center external sets (n = 305). Conclusions Plasma metabolomics are powerful for characterizing metabolic disturbances. Differences in small-molecule metabolites may reflect underlying CAD and serve as biomarkers for CAD progression.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Lysine acetylation regulates many eukaryotic cellular processes, but its function in prokaryotes is largely unknown. We demonstrated that central metabolism enzymes in Salmonella were acetylated ...extensively and differentially in response to different carbon sources, concomitantly with changes in cell growth and metabolic flux. The relative activities of key enzymes controlling the direction of glycolysis versus gluconeogenesis and the branching between citrate cycle and glyoxylate bypass were all regulated by acetylation. This modulation is mainly controlled by a pair of lysine acetyltransferase and deacetylase, whose expressions are coordinated with growth status. Reversible acetylation of metabolic enzymes ensure that cells respond environmental changes via promptly sensing cellular energy status and flexibly altering reaction rates or directions. It represents a metabolic regulatory mechanism conserved from bacteria to mammals.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Understanding ecological niches of major tick species and prevalent tick-borne pathogens is crucial for efficient surveillance and control of tick-borne diseases. Here we provide an up-to-date review ...on the spatial distributions of ticks and tick-borne pathogens in China. We map at the county level 124 tick species, 103 tick-borne agents, and human cases infected with 29 species (subspecies) of tick-borne pathogens that were reported in China during 1950-2018. Haemaphysalis longicornis is found to harbor the highest variety of tick-borne agents, followed by Ixodes persulcatus, Dermacentor nutalli and Rhipicephalus microplus. Using a machine learning algorithm, we assess ecoclimatic and socioenvironmental drivers for the distributions of 19 predominant vector ticks and two tick-borne pathogens associated with the highest disease burden. The model-predicted suitable habitats for the 19 tick species are 14‒476% larger in size than the geographic areas where these species were detected, indicating severe under-detection. Tick species harboring pathogens of imminent threats to public health should be prioritized for more active field surveillance.
Enteric bacteria use up to 15% of their cellular energy for ammonium assimilation via glutamine synthetase (GS)/glutamate synthase (GOGAT) and glutamate dehydrogenase (GDH) in response to varying ...ammonium availability. However, the sensory mechanisms for effective and appropriate coordination between carbon metabolism and ammonium assimilation have not been fully elucidated. Here, we report that in Salmonella enterica, carbon metabolism coordinates the activities of GS/GDH via functionally reversible protein lysine acetylation. Glucose promotes Pat acetyltransferase‐mediated acetylation and activation of adenylylated GS. Simultaneously, glucose induces GDH acetylation to inactivate the enzyme by impeding its catalytic centre, which is reversed upon GDH deacetylation by deacetylase CobB. Molecular dynamics (MD) simulations indicate that adenylylation is required for acetylation‐dependent activation of GS. We show that acetylation and deacetylation occur within minutes of “glucose shock” to promptly adapt to ammonium/carbon variation and finely balance glutamine/glutamate synthesis. Finally, in a mouse infection model, reduced S. enterica growth caused by the expression of adenylylation‐mimetic GS is rescued by acetylation‐mimicking mutations. Thus, glucose‐driven acetylation integrates signals from ammonium assimilation and carbon metabolism to fine‐tune bacterial growth control.
Synopsis
In Salmonella enterica, metabolic enzyme acetylation regulates carbon metabolism. Here, glucose availability is shown to regulate ammonium assimilation and virulence in Salmonella.
Acetylation of glutamine synthetase (GS) and glutamate dehydrogenase (GDH) is regulated by acetyltransferase Pat and deacetylase CobB.
Glucose promotes acetylation to activate adenylylated GS and inactivate GDH by impeding its catalytic centre.
Acetylation of GS and GDH occurs within minutes to adapt to the ammonium/carbon variation and balance glutamate/glutamine synthesis.
GS acetylation‐mimicking mutations enhance Salmonella survival in infected mice.
Glucose regulates acetylation of glutamate and glutamine biosynthesis enzymes to enhance bacterial survival in infected mice.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Untangling the complex variations of microbiome associated with large-scale host phenotypes or environment types challenges the currently available analytic methods. Here, we present tmap, an ...integrative framework based on topological data analysis for population-scale microbiome stratification and association studies. The performance of tmap in detecting nonlinear patterns is validated by different scenarios of simulation, which clearly demonstrate its superiority over the most commonly used methods. Application of tmap to several population-scale microbiomes extensively demonstrates its strength in revealing microbiome-associated host or environmental features and in understanding the systematic interrelations among their association patterns. tmap is available at https://github.com/GPZ-Bioinfo/tmap.
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