Resonance Detection Research Articles

Controlling 229Th isomeric state population in a VUV transparent crystal

The radioisotope thorium-229 (229Th) is renowned for its extraordinarily low-energy, long-lived nuclear first-excited state. This isomeric state can be excited by vacuum ultraviolet (VUV) lasers and 229Th has been proposed as a reference transition for ultra-precise nuclear clocks. To assess the feasibility and performance of the nuclear clock concept, time-controlled excitation and depopulation of the 229Th isomer are imperative. Here we report the population of the 229Th isomeric state through resonant X-ray pumping and detection of the radiative decay in a VUV transparent 229Th-doped CaF2 crystal. The decay half-life is measured to 447(25) s, with a transition wavelength of 148.18(42) nm and a radiative decay fraction consistent with unity. Furthermore, we report a new “X-ray quenching” effect which allows to de-populate the isomer on demand and effectively reduce the half-life. Such controlled quenching can be used to significantly speed up the interrogation cycle in future nuclear clock schemes.

Quantum gravity signatures in gravitational wave detectors placed inside a harmonic trap potential

In this work, we consider a general gravitational wave detector of gravitational waves interacting with an incoming gravitational wave carrying plus polarization only placed inside a harmonic trap. This model can be well acquainted with the description of a resonant detector of gravitational waves as well. The well-known detector-gravitational wave interaction scenario uses the method of a semiclassical approach where the detector is treated quantum mechanically but the gravitational wave is considered at a classical level. In our analysis, we use a discrete mode decomposition of the gravitational wave perturbation which results in a Hamiltonian involving the position and momentum operators corresponding to the gravitational wave and the harmonic oscillator. We have then calculated the transition probability for the harmonic oscillator-gravitational wave tensor product state for going from an initial state to some unknown final state. Using the energy flux relation of the gravitational waves, we observe that if we consider the total energy as a combination of the number of gravitons in the initial state of the detector then the transition probability for the resonant absorption case scenario takes the analytical form which is exactly similar to the semiclassical absorption case. In the case of the emission scenario, we observe a spontaneous emission of a single graviton which was completely absent in the semiclassical analog of this model. This therefore gives a direct signature of linearized quantum gravity. Published by the American Physical Society 2024

Distributed estimation cascade second-order tri-stable stochastic resonance method for random noise suppression in continuous-wave mud pulse telemetry

The extraction of high-quality useful signals in downhole environments has perennially posed a technical challenge for continuous wave mud pulse transmission systems. Traditional denoising methods, such as adaptive filtering and wavelet transform, inevitably compromise the integrity of the original signal's useful components while removing noise. Different from the traditional denoising methods, stochastic resonance (SR) is capable of transferring the energy of noise to the signal, thereby accomplishing the objective of noise suppression. In this paper, based on the second-order tri-stable stochastic resonance detection method combined with the estimation of distribution algorithm (EDA), a distributed estimation cascade second-order tri-stable stochastic resonance (EDA- CSTSR) detection method is proposed for the first time. By constructing 5 groups of simulation signals with different signal-to-noise ratios (SNRs), the denoising performance of distributed estimation CSTSR, Langevin SR, and Duffing SR is analyzed in detail. The results show that compared with Langevin SR and Duffing SR, the EDA-CSTSR can increase the SNR of the input simulation signal by at least 17 dB and significantly increase the amplitude of the useful pulse signal. Moreover, the EDA-CSTSR is applied to process actual data obtained from a drilling site, enabling the recognition of weak signals amidst strong background noise, which highlights the method's excellent practical application value and underscores its potential for further enhancement.

Influence of water vapor concentration on photoacoustic spectroscopy‐based characteristic gas analysis of transformer faults

AbstractThe water vapor in the ambient air affects the accuracy of the photoacoustic (PA) dissolved gas analysis system for transformer health monitoring. A laser PA system was evaluated by dry and humidified standard gases to study the influence of water vapor concentration on PA gas detection. Theoretical analysis was conducted on the effect of gas molecule relaxation on PA signal detection. A high‐frequency resonant PA cell and a low‐frequency nonresonant PA cell were used to detect acetylene (C2H2) and carbon monoxide (CO), respectively. The experimental results show that the PA signal of humidified CO is about 12 times higher than PA signal of dry gas for the resonant PA detection system, respectively. In addition, as the frequency is increased from 30 to 980 Hz, the PA signals of humidified and dry CO attenuate by 1.5 and 6.9 times, respectively.

Enhanced Degradation of Micropollutants in a Peracetic Acid/Mn(II) System with EDDS: An Investigation of the Role of Mn Species.

Extensive research has been conducted on the utilization of a metal-based catalyst to activate peracetic acid (PAA) for the degradation of micropollutants (MPs) in water. Mn(II) is a commonly employed catalyst for homogeneous advanced oxidation processes (AOPs), but its catalytic performance with PAA is poor. This study showed that the environmentally friendly chelator ethylenediamine-N,N'-disuccinic acid (EDDS) could greatly facilitate the activation of Mn(II) in PAA for complete atrazine (ATZ) degradation. In this process, the EDDS enhanced the catalytic activity of manganese (Mn) and prevented disproportionation of transient Mn species, thus facilitating the decay of PAA and mineralization of ATZ. By employing electron spin resonance detection, quenching and probe tests, and 18O isotope-tracing experiments, the significance of high-valent Mn-oxo species (Mn(V)) in the Mn(II)-EDDS/PAA system was revealed. In particular, the involvement of the Mn(III) species was essential for the formation of Mn(V). Mn(III) species, along with singlet oxygen (1O2) and acetyl(per)oxyl radicals (CH3C(O)O•/CH3C(O)OO•), also contributed partially to ATZ degradation. Mass spectrometry and density functional theory methods were used to study the transformation pathway and mechanism of ATZ. The toxicity assessment of the oxidative products indicated that the toxicity of ATZ decreased after the degradation reaction. Moreover, the system exhibited excellent interference resistance toward various anions and humid acid (HA), and it could selectively degrade multiple MPs.

Enhanced degradation of emerging contaminants by Far-UVC photolysis of peracetic acid: Synergistic effect and mechanisms

Krypton chloride (KrCl*) excimer lamps (222 nm) are used as a promising irradiation source to drive ultraviolet-based advanced oxidation processes (UV-AOPs) in water treatment. In this study, the UV222/peracetic acid (PAA) process is implemented as a novel UV-AOPs for the degradation of emerging contaminants (ECs) in water. The results demonstrate that UV222/PAA process exhibits excellent degradation performance for carbamazepine (CBZ), with a removal rate of 90.8 % within 45 min. Notably, the degradation of CBZ in the UV222/PAA process (90.8 %) was significantly higher than that in the UV254/PAA process (15.1 %) at the same UV dose. The UV222/PAA process exhibits superior electrical energy per order (EE/O) performance while reducing resource consumption associated with the high-energy UV254/PAA process. Quenching experiments and electron paramagnetic resonance (EPR) detection confirm that HO• play a dominant role in the reaction. The contributions of direct photolysis, HO•, and other active species (RO• and 1O2) are estimated to be 5 %, 88 %, and 7 %, respectively. In addition, the effects of Cl−, HCO3−, and humic acid (HA) on the degradation of CBZ are evaluated. The presence of relatively low concentrations of Cl−, HCO3−, and HA can inhibit CBZ degradation. The UV222/PAA oxidation process could also effectively degrade several other ECs (i.e., iohexol, sulfamethoxazole, acetochlor, ibuprofen), indicating the potential application of this process in pollutant removal. These findings will propel the development of the UV222/PAA process and provide valuable insights for its application in water treatment.

High-field/high-frequency electron spin resonances of Fe-doped β−Ga2O3 by terahertz generalized ellipsometry: Monoclinic symmetry effects

We demonstrate detection and measurement of electron paramagnetic spin resonances (EPR) of iron defects in β−Ga2O3 utilizing generalized ellipsometry at frequencies between 110 and 170 GHz. The experiments are performed on an Fe-doped single crystal in a free-beam configuration in reflection at 45∘ and magnetic fields between 3 and 7 T. In contrast with low-field, low-frequency EPR measurements, we observe all five transitions of the s=5/2 high-spin state Fe3+ simultaneously. We confirm that ferric Fe3+ is predominantly found at octahedrally coordinated Ga sites. We obtain the full set of fourth-order monoclinic zero-field splitting parameters for both octahedrally and tetrahedrally coordinated sites by employing measurements at multiple sample azimuth rotations. The capability of high-field EPR allows us to demonstrate that simplified second-order orthorhombic spin Hamiltonians are insufficient, and fourth-order terms as well as consideration of the monoclinic symmetry are needed. These findings are supported by computational approaches based on density-functional theory for second-order and on ligand-field theory for fourth-order parameters of the spin Hamiltonian. Terahertz ellipsometry is a way to measure spin resonances in a cavity-free setup. Its possibility of varying the probe frequency arbitrarily without otherwise changing the experimental setup offers unique means of truly disentangling different components of highly anisotropic spin Hamiltonians. Published by the American Physical Society 2024

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

The classical bistable stochastic resonance algorithm has an inherent output saturation defect that restricts the amplitude of the output signal. This paper examines the causes of this phenomenon and its negative impact on the detection of weak signals. Proposing the Unsaturated Bistable Stochastic Resonance (UBSR) detection algorithm involves constructing a segmented potential function using a linear function to eliminate the effect of higher-order terms in the classical stochastic resonance algorithm. A new type of segmented potential function has been created by combining exponential and linear functions. This new function helps to eliminate the impact of higher-order terms in classical algorithms while also improving the noise immunity of the stochastic resonance system. This results in the development of the accelerated stochastic resonance (ASR) detection algorithm. In this paper, the Kramers escape rate and output signal-to-noise ratio of two improved stochastic resonance algorithms are theoretically derived and compared with the classical bistable stochastic resonance algorithms, and the proposed algorithms are able to effectively avoid the output saturation phenomenon and have more excellent detection performance under strong background noise.

Rapid Non-Destructive Detection Technology in the Field of Meat Tenderness: A Review.

Traditionally, tenderness has been assessed through shear force testing, which is inherently destructive, the accuracy is easily affected, and it results in considerable sample wastage. Although this technology has some drawbacks, it is still the most effective detection method currently available. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into applying five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of the quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations to guide the future direction of non-destructive, AI-enhanced meat tenderness detection.

Enhanced photocatalytic degradation of oxytetracycline by Z-scheme heterostructure ZIF-8/Bi4O5Br2

Semiconductor photocatalysis technology has a wide range of application in the treatment of environmental pollution. In this study, the Z-scheme heterojunction photocatalyst ZIF-8/Bi4O5Br2 was synthesized by hydrothermal method. The morphology, structure, mechanism and photocatalytic performance of the materials were studied. Under simulated sunlight illumination for 60 minutes, the degradation efficiency of oxytetracycline (15 mg·L−1) reached 94.2 %. In light of density functional theory calculation and liquid chromatography-mass spectrometry, the attack sites and degradation pathways of OTC were determined. The consequence of free radical capture test and electron paramagnetic resonance detection showed that ·O2-, ·OH and h+ were the primary active substances. Based on the analysis above, the charge transfer principle of Z-scheme heterojunction was further elucidation. It inhibited the recombination of photo carriers and improved the photocatalytic performance. This work provides a hopeful measure for photocatalytic degradation of OTC by Z-scheme heterojunction composite.

Prognostic Value and Determinants of High-Sensitivity Cardiac Troponin T in Patients With a Systemic Right Ventricle: Insights From the SERVE Trial.

The determinants and prognostic value of high-sensitivity cardiac troponin T (hs-cTnT) among patients with a systemic right ventricle are largely unknown. Ninety-eight patients from the randomized controlled SERVE (Effect of Phosphodiesterase-5 Inhibition With Tadalafil on Systemic Right Ventricular Size and Function) trial were included. The correlation between baseline hs-cTnT concentrations and biventricular volumes and function quantified by cardiac magnetic resonance or cardiac multirow detector computed tomography was assessed by adjusted linear regression models. The prognostic value of hs-cTnT was assessed by adjusted Cox proportional hazards models, survival analysis, and concordance statistics. The primary outcome was time to the composite of clinically relevant arrhythmia, hospitalization for heart failure, or all-cause death. Median age was 39 (interquartile range, 32-48) years, and 32% were women. Median hs-cTnT concentration was 7 (interquartile range, 4-11) ng/L. Coefficients of determination for the relationship between hs-cTnT concentrations and right ventricular end-systolic volume index and right ventricular ejection fraction (RVEF) were +0.368 (P=0.046) and -0.381 (P=0.018), respectively. The sex- and age-adjusted hazard ratio for the primary outcome of hs-cTnT at 2 and 4 times the reference level (5 ng/L) were 2.89 (95% CI, 1.14-7.29) and 4.42 (95% CI, 1.21-16.15), respectively. The prognostic performance quantified by the concordance statistics for age- and sex-adjusted models based on hs-cTnT, right ventricular ejection fraction, and peak oxygen uptake predicted were comparable: 0.71% (95% CI, 0.61-0.82), 0.72% (95% CI, 0.59-0.84), and 0.71% (95% CI, 0.59-0.83), respectively. Hs-cTnT concentration was significantly correlated with right ventricular ejection fraction and right ventricular end-systolic volume index in patients with a systemic right ventricle. The prognostic accuracy of hs-cTnT was comparable to that of right ventricular ejection fraction and peak oxygen uptake predicted. URL: https://www.clinicaltrials.gov; Unique identifier: NCT03049540.

Evaluating lumbar disc degeneration by MRI quantitative metabolic indicators: the perspective of factor analysis

PurposeThis study aimed to investigate an early diagnostic method for lumbar disc degeneration (LDD) and improve its diagnostic accuracy.MethodsQuantitative biomarkers of the lumbar body (LB) and lumbar discs (LDs) were obtained using nuclear magnetic resonance (NMR) detection technology. The diagnostic weights of each biological metabolism indicator were screened using the factor analysis method.ResultsThrough factor analysis, common factors such as the LB fat fraction, fat content, and T2* value of LDs were identified as covariates for the diagnostic model for the evaluation of LDD. This model can optimize the accuracy and reliability of LDD diagnosis.ConclusionThe application of biomarker quantification methods based on NMR detection technology combined with factor analysis provides an effective means for the early diagnosis of LDD, thereby improving diagnostic accuracy and reliability.

Resonance Detection Method of AC-DC Hybrid Micro-grid Based on Wavelet Transform and Fast Fourier Transform

The grid connection of a mass of distributed power sources in the AC/DC hybrid micro-grid will cause harmonics, voltage sags, voltage fluctuations, and flicker in the grid, which seriously affects the power quality of the grid. Therefore, the power quality problems such as the resonance generated by the AC/DC hybrid micro-grid need to be studied urgently. In this paper, a resonance detection technology based on the combination of wavelet transform (WT) and fast Fourier transform (FFT) is proposed. This method uses wavelet transform to process the high-frequency and low-frequency parts of the signal separately, and eliminates part of the interference signal. The method then uses the FFT to obtain the resonance content. The AC/DC hybrid micro-grid resonance detection method based on WT and FFT can not only determine the time and amplitude of the resonance signal, but also filter the interference signal and improve the accuracy of frequency domain analysis. It is verified by simulation that the algorithm can detect the resonance of the AC/DC hybrid micro-grid.

An image-based spatiotemporal approach for detecting coherence resonance in annular model gas-turbine combustor

When exposed to an intermediate level of noise, dynamical systems near a Hopf bifurcation can reveal deterministic information about the impending oscillatory mode. Known as the coherence resonance, this phenomenon can be used as a precursor to thermoacoustic instability, which is detrimental to practical combustors. In this study, we apply a spatiotemporal dimensionality reduction method, namely the sparsity-promoting dynamic mode decomposition, to detect coherence resonance in a combustor that exhibits a transition toward thermoacoustic instability. We stochastically excite the annular model gas-turbine combustor and acquire its high-speed image for spatiotemporal analysis. As a result, we find that the impending mode of instability is best identified with a maximum clustering level at the intermediate noise amplitude, implying the existence of coherence resonance. To the best of our knowledge, this is the first time that an image-based method has been used for the detection of coherence resonance, opening new possibilities for the prediction of combustion instability without requiring embedded sensors.

Resonant detectors of gravitational wave in the linear and quadratic generalized uncertainty principle framework

In this work, we consider a resonant bar detector of gravitational waves in the generalized uncertainty principle (GUP) framework with linear and quadratic momentum uncertainties. The phonon modes in these detectors vibrate due to the interaction with the incoming gravitational wave. In this uncertainty principle framework, we calculate the resonant frequencies and transition rates induced by the incoming gravitational waves on these detectors. We observe that the energy eigenstates and the eigenvalues get modified by the GUP parameters. We also observe non-vanishing transition probabilities between two adjacent energy levels due to the existence of the linear order momentum correction in the generalized uncertainty relation which was not present in the quadratic GUP analysis (Class Quantum Gravity 37:195006, 2020). We finally obtain bounds on the dimensionless GUP parameters using the form of the transition rates obtained during this analysis.

Continuous Cardiac Magnetic Resonance Imaging after Coronary Revascularization for Left Ventricular Dysfunction

Objective: To determine the contribution of serial cardiac magnetic resonance imaging (MRI) following coronary revascularization (CR) to the clinical management of patients with left ventricular insufficiency. Methods: The study objects comprised the clinical data of 145 patients with CR undergoing CR surgery for left ventricular insufficiency in our hospital from January 2021 to January 2023. The patients were divided into the case (n = 35, left ventricular ejection fraction (LVEF) <50%) and control (n = 110, LVEF ≥50%) groups based on the LVEF recorded in the medical record system 6 months after surgery. Preoperative LVEF left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), left ventricular end-diastolic volume index (LVEDVI), left ventricular end-systolic volume index (LVESVI), cardiac index (CI), and other cardiac magnetic resonance detection parameters were compared. Logistic regression analysis was performed to analyze the prognostic factors of patients undergoing CR after CR surgery for left ventricular insufficiency. The receiver operating characteristic curve was drawn, the sensitivity, specificity, and area under curve (AUC) were calculated, and the best prediction threshold was determined. The prognostic value of cardiac MRI in CR surgery for left ventricular dysfunction was observed. Results: Cardiac MRI revealed that the case group had higher LVEDV, LVESV, LVEDVI, LVESVI, and CI than the control group. However, the LVEF index was lower than that in the control group (p < 0.05). Logistic regression analysis was conducted for indicators with differences, and the results indicate LVEF as a protective factor for the postoperative efficacy of the patients, with an odds ratio (OR) <1. LVEDV, LVESV, LVEDVI, LVESVI, and CI were all risk factors for the postoperative efficacy of the patients, with an OR >1. The AUC values of LVEF, LVEDV, LVESV, LVEDVI, LVESVI, and CI were 0.698, 0.674, 0.654, 0.700, 0.572, and 0.812, respectively. The optimal threshold values were 53.57%, 112.33 and 68.5 mL, and 205.51, 163.99, and 2.14 L/m2, and their corresponding sensitivities reached 0.618, 0.514, 0.654, 0.800, 0.371, and 0.829 for each index. The specificities were 0.800, 0.836, 0.771, 0.609, 0.836, and 0.645, which indicate that LVEF, LVEDV, LVESV, LVEDVI, LVESVI, and CI had a certain degree of predictive value for postoperative cardiac function recovery. Conclusion: LVEDV, LVESV, LVEDVI, LVESVI, CI, and LVEF are all factors affecting the clinical efficacy in patients undergoing CR after left ventricular insufficiency. In addition, cardiac MRI can effectively detect the above factors and effectively predict the postoperative efficacy among patients.

Underestimated role of hydroxyl radicals for bromate formation in persulfate-based advanced oxidation processes

In persulfate-based advanced oxidation processes (PS-AOPs), sulfate radicals (SO4•-) have been recognized to play more important roles in inducing bromate (BrO3−) formation rather than hydroxyl radicals (HO•) because of the stronger oxidation capacity of the former. However, this study reported an opposite result that HO• indeed dominated the formation of bromate instead of SO4•-. Quenching experiments were coupled with electron paramagnetic resonance (EPR) detection and chemical probe identification to elucidate the contributions of each radical species. The comparison of different thermal activated persulfates (PDS and PMS) demonstrated that the significant higher bromate formation in HEAT/PMS ([BrO3−]/[Br−]0 = 0.8), as compared to HEAT/PDS ([BrO3−]/[Br−]0 = 0.2), was attributable to the higher concentration of HO• radicals in HEAT/PMS. Similarly, the bromate formation in UV/PDS ([BrO3−]/[Br−]0 = 1.0), with a high concentration of HO•, further underscored the dominant role of HO•. As a result, we quantified that HO• and SO4•- radicals accounted 66.7% and 33.3% for bromate formation. This controversial result can be reconciled by considering the critical intermediate, hypobromic acid/hypobromate (HOBr/BrO−), involved in the transformation of Br− to BrO3−. HO• radicals have the chemical preference to induce the formation of HOBr/BrO− intermediates (contributing ∼ 60%) relative to SO4•- radicals (contributing ∼ 40%). This study highlighted the dominant role of HO• in the formation of bromate rather than SO4•- in PS-AOPs and potentially offered novel insights for reducing disinfection byproduct formation by controlling the radical species in AOPs.

Coupling harmful algae derived nitrogen and sulfur co-doped carbon nanosheets with CeO2 to enhance the photocatalytic degradation of isothiazolinone biocide

Removing the algae from water bodies is an effective treatment toward the worldwide frequently occurred harmful algae blooms (HAB), but processing the salvaged algae waste without secondary pollution places another burden on the economy and environment. Herein, a green hydrothermal process without any chemical addition was developed to resource the HAB algae (Microcystis sp.) into autogenous nitrogen and sulfur co-doped carbon nanosheet materials C–CNS and W–CNS, whose alga precursors were collected from pure culture and a wild bloom pond, respectively. After coupling with CeO2, the obtained optimal C–CNS/CeO2 and W–CNS/CeO2 composites photocatalytically degraded 95.4% and 88.2% of the marine pollutant 4,5-Dichloro-2-n-octyl-4-isothiazolin-3-one (DCOIT) in 90 min, significantly higher than that of pure CeO2 (63.15%). DCOIT degradation on CNS/CeO2 was further conducted under different conditions, including pH value, coexisting cations and anions, and artificial seawater. Although different influences were observed, the removal efficiencies were all above 76%. Along with the ascertained good stability and reusability in five consecutive runs, the great potential of CNS/CeO2 for practical application was validated. UV–vis DRS showed the increased light absorption of CNS/CeO2 in comparison to pure CeO2. PL spectra and photoelectrochemical measurements suggested the lowered charge transfer resistance and thereby inhibited charge recombination of CNS/CeO2. Meanwhile, trapping experiments and electron paramagnetic resonance (EPR) detection verified the primary roles of hydroxyl radical (OH) and superoxide radical (O2−) in DCOIT degradation, as well as their notably augmented generation by CNS. Consequently, a mechanism of CNS enhanced photocatalytic degradation of DCOIT was proposed. The intermediates involved in the reaction were identified by LC-QTOF-MS, giving rise to a deduced degradation pathway for DCOIT. This study offers a new approach for resourceful utilization of the notorious HAB algae waste. Besides that, photocatalytic degradation has been explored as an effective measure to remove DCOIT from the ocean.

Graphene quantum dot bolometer for on-chip detection of organic radical

We present a proof-of-concept magnetic resonance detection of organic radical 2,2-diphenyl-1-picrylhydrazyl via a nanostructured on-chip graphene quantum dot bolometer. In a common electron paramagnetic resonance setup, the microwave propagates from a source into a sample and back to a detector. Yet, by using on-chip detection, it is possible to skip the whole detection arm and, thus, mitigate lab expenses on instrument and cooling costs. The bolometric detection was demonstrated at a frequency of 151 GHz and a temperature of 15 K.

The interplay of machine learning-based resonant anomaly detection methods

Machine learning-based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD methods that has received significant attention is resonant anomaly detection, where the BSM physics is assumed to be localized in at least one known variable. While there have been many methods proposed to identify such a BSM signal that make use of simulated or detected data in different ways, there has not yet been a study of the methods’ complementarity. To this end, we address two questions. First, in the absence of any signal, do different methods pick the same events as signal-like? If not, then we can significantly reduce the false-positive rate by comparing different methods on the same dataset. Second, if there is a signal, are different methods fully correlated? Even if their maximum performance is the same, since we do not know how much signal is present, it may be beneficial to combine approaches. Using the Large Hadron Collider (LHC) Olympics dataset, we provide quantitative answers to these questions. We find that there are significant gains possible by combining multiple methods, which will strengthen the search program at the LHC and beyond.