Distance Calibration Research Articles

Carnegie Supernova Project I and II: Measurements of H 0 Using Cepheid, Tip of the Red Giant Branch, and Surface Brightness Fluctuation Distance Calibration to Type Ia Supernovae* *This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

We present an analysis of Type Ia supernovae (SNe Ia) from the Carnegie Supernova Project I and II and extend the Hubble diagram from optical to near-infrared wavelengths (uBgVriYJH). We calculate the Hubble constant, H 0, using various distance calibrators: Cepheids, the tip of the red giant branch (TRGB), and surface brightness fluctuations (SBFs). Combining all methods of calibration, we derive H 0 = 71.76 ± 0.58 (stat) ± 1.19 (sys) km s−1 Mpc−1 from the B band and H 0 = 73.22 ± 0.68 (stat) ± 1.28 (sys) km s−1 Mpc−1 from the H band. By assigning equal weight to the Cepheid, TRGB, and SBF calibrators, we derive the systematic errors required for consistency in the first rung of the distance ladder, resulting in a systematic error of 1.2 ∼ 1.3 km s−1 Mpc−1 in H 0. As a result, relative to the statistics-only uncertainty, the tension between the late-time H 0 we derive by combining the various distance calibrators and the early-time H 0 from the cosmic microwave background is reduced. The highest precision in SN Ia luminosity is found in the Y band (0.12 ± 0.01 mag), as defined by the intrinsic scatter (σ int). We revisit SN Ia Hubble residual-host mass correlations and recover previous results that these correlations do not change significantly between the optical and near-infrared wavelengths. Finally, SNe Ia that explode beyond 10 kpc from their host centers exhibit smaller dispersion in their luminosity, confirming our earlier findings. A reduced effect of dust in the outskirts of hosts may be responsible for this effect.

ECR Spotlight – Bharath Kumar A. K.

ECR Spotlight is a series of interviews with early-career authors from a selection of papers published in Journal of Experimental Biology and aims to promote not only the diversity of early-career researchers (ECRs) working in experimental biology but also the huge variety of animals and physiological systems that are essential for the ‘comparative’ approach. Bharath Kumar A K is an author on ‘ Tropical and montane Apis cerana show distinct dance–distance calibration curves’, published in JEB. Bharath Kumar is a Research Assistant in the lab of Dr Axel Brockmann at the National Centre for Biological Sciences, Tata Institute of Fundamental Research, India, investigating bee behavior and pollination biology.

Constraints on Bianchi-I type universe with SH0ES anchored Pantheon+ SNIa data

We study the Bianchi-I cosmological model motivated by signals of statistical isotropy violation seen in cosmic microwave background (CMB) observations and others. To that end, we consider various kinds of anisotropic matter that source anisotropy in our model, specifically Cosmic strings, Magnetic fields, Domain walls and Lorentz violation generated magnetic fields. These anisotropic matter sources, taking one at a time, are studied for their co-evolution with standard model (isotropic) sources viz., dust-like (dark/normal) matter, and dark energy modelled as cosmological constant. We constrain the Hubble parameter, density fractions of anisotropic matter, cold dark matter (CDM), and dark energy (Λ) in a Bianchi-I universe with planar symmetry i.e., which has a global ellipsoidal geometry, and try to find signatures of a cosmic preferred axis if any.The latest compilation of Type Ia Supernova (SNIa) data from Pantheon+SH0ES collaboration is used in our analysis to obtain constraints on cosmological parameters and any preferred axis for our universe.In our analysis, we found mild evidence for a cosmic preferred axis. It is interesting to note that this preferred axis lies broadly in the vicinity of other prominent cosmic anisotropy axes reported in the literature from diverse data sets.Also we find some evidence for non-zero (negative) cosmic shear and eccentricity that characterize different expansion rates in different directions and deviation from an isotropic scale factor respectively.The energy density fractions of two of the sources considered are found to be non-zero at a2σ confidence level.To be more conclusive, we require more SNIa host galaxy data for tighter constraints on distance and absolute magnitude calibration which are expected to be available from the future JWST observations and others.

Research on Measuring the Bodies of Underwater Fish with Inclined Positions Using the YOLOv8 Model and a Line-Laser System

Fish body measurement is essential for monitoring fish farming and evaluating growth. Non-destructive underwater measurements play a significant role in aquaculture management. This study involved annotating images of fish in aquaculture settings and utilized a line laser for underwater distance calibration and fish body inclined-angle calculation. The YOLOv8 model was employed for fish identification and key-point detection, enabling the determination of actual body dimensions through a mathematical model. The results show a root-mean-square error of 6.8 pixels for underwater distance calibration using the line laser. The pre-training YOLOv8-n, with its lower parameter counts and higher MAP values, proved more effective for fish identification and key-point detection, considering speed and accuracy. Average body length measurements within 1.5 m of the camera showed a minor deviation of 2.46% compared to manual measurements. The average relative errors for body length and width were 2.46% and 5.11%, respectively, with corresponding average absolute errors. This study introduces innovative techniques for fish body measurement in aquaculture, promoting the digitization and informatization of aquaculture processes.

Addressing wander effect in vehicle weight monitoring: An advanced hybrid weigh-in-motion system integrating computer vision and in-pavement sensors

The paper addressed the challenges of the two main weigh-in-motion (WIM) systems through a hybrid WIM system, which combines embedded in-pavement sensor systems and computer vision to enhance accuracy while minimizing human intervention. To establish a cost-effective system, this study employed a standard camera integrated with computer vision technique to improve the precision of identifying wheel location and automatically adjust distance calibration, particularly in response to variations in camera angle. In addition, the system achieved real-time vehicle weight detection efficiently by addressing the vehicle wander effect concerns of the in-pavement sensors through camera using computer vision. The system can achieve weight accuracy notably exceeding ASTM 1318E-09 standards, with over 90% accuracy for distances below 0.1 m, demonstrating its potential value in assisting traffic analysis and pavement maintenance by offering real-time, accurate WIM measurements at a low cost for instrumentation.

ΛCDM is alive and well

Despite its successes, the ΛCDM model faces several tensions with recent cosmological data and their increased accuracy. The mismatch between the values of the Hubble constant H0 obtained from {some} direct distance ladder measurements and from the cosmic microwave background (CMB) is the most statistically significant, but the amplitude of the matter fluctuations is also regarded as a serious concern, leading to the investigation of a plethora of {alternative} models. Here, we examine the situation from a different perspective. We first show that the combination of several recent measurements from local probes leads to a tight constraint on the present-day matter density Ωm as well as on the amplitude of the matter fluctuations, both acceptably consistent with the values inferred from the CMB. Secondly, we address the Hubble tension by assuming that some determinations of the value of H0 are possibly biased. We treat such a bias as a nuisance parameter within ΛCDM and we examine such `` ΛCDM + H0 bias’’ models on the same statistical grounds as alternative cosmological models. A bias in Planck or in SH0ES produces similar improvements. However we show that a bias in the Cepheids calibration produces improvements in terms of ΔAIC that supersede existing extended models proposed up to now. In a third step, we show that the value of Ωm we obtained from our RSD, Pantheon+ and 3×2pt from DES, combined with SH0ES determination of H0, leads to a precise determination of the density parameter of the Universe ωm=0.1753±0.0069. This measurement provides an additional low-redshift test for cosmological models by comparing it to the preferred value derived from the CMB. From this test, most ΛCDM extensions seem to be confronted with a new tension as many of them cluster around ωm=0.14, while there is no tension with a local $H_0 67 $ km/s/Mpc. We conclude that a standard ΛCDM model with an unknown bias in the Cepheids distance calibration represents a model that reaches a remarkable agreement, statistically better than previously proposed extensions without bias for which such a comparison can be performed.

The marine diesel engine exhaust gas temperature baseline model based on particle swarm optimised generalised regression neural network

ABSTRACT This study addresses limitations in traditional condition monitoring for marine diesel engine (MDE) reliability and stability by proposing a hybrid machine learning and deep learning (DL) model called Particle Swarm Optimization-Generalized Regression Neural Network (PSO-GRNN) for real-time exhaust gas temperature (EGT) monitoring. The model integrates Mahalanobis distance (MD) calibration, wavelet packet denoising, and Pearson correlation analysis for comprehensive data preprocessing. Validation is conducted using historical '6L34DF' diesel engine data. Particle Swarm Optimization (PSO) optimizes the spread value (σ) of the Generalized Regression Neural Network (GRNN) to establish an optimal baseline model for EGT prediction. Experimental results show that PSO-GRNN outperforms Backpropagation Neural Network (BPNN), GRNN, Bidirectional Gated Recurrent Unit (BiGRU), Genetic Algorithm- Generalized Regression Neural Network (GA-GRNN), and Deep Belief Network-Support Vector Regression (DBN-SVR) in terms of training time and accuracy, demonstrating its suitability for MDE baseline modeling.

Real-world application of a smartphone-based visual acuity test (WHOeyes) with automatic distance calibration

BackgroundTo develop and assess the usability of a smartphone-based visual acuity (VA) test with an automatic distance calibration (ADC) function, the iOS version of WHOeyes.MethodsThe WHOeyes was an upgraded version...

Flexible and universal autofocus based on amplitude difference of fractional Fourier transform

Autofocus technology is a crucial technique in computational optical imaging. The clarity evaluation function (CEF) serves as the criterion for autofocus, making it the core of the autofocus algorithm. In this paper, we propose a CEF based on amplitude differences of fractional Fourier transform (ADFrFT). ADFrFT extracts information from the fractional domain, which corresponds to the fusion of the spatial and frequency domains. This renders ADFrFT highly accurate and robust to noise, making it suitable for various types of sample images. Additionally, ADFrFT provides an added dimension of flexibility to address different autofocus requirements for distinct sample image types and focusing scenarios. Simulations and experiments confirmed the effectiveness of ADFrFT, and we improved the imaging resolution via distance calibration in the coaxial multi-distance coherent diffraction imaging (MDCDI) experiment.

Automated measurement of beef cattle body size via key point detection and monocular depth estimation

The measurement of beef cattle’s body size is the key problem to be solved in beef cattle breeding. Automatic body size measurement were still influenced due to the light, distance, and other factors. To achieve measurement of beef cattle’s oblique length, body height, chest depth, and hoof diameter under different distances and lighting conditions, an automatic measurement method based on key point detection and monocular depth estimation was proposed. Firstly, the cattle were detected by the YOLOv5s network, then, the key points were detected through the Lite-HRNet network and the pixel distance of the body size was calculated. Secondly, the monocular depth information was extracted through the Global-Local Path networks to obtain the relative depth value of the images. The relationship between the actual distance and the relative depth was obtained by using the actual distance calibration. Finally, the ratio between the pixel length and the actual length was obtained through the imaging principle of the RGB camera, and the beef cattle images in different scenarios were measured. It was concluded that the proposed system could complete the measurement work of beef cattle straight side images under no sky or small sky background. Thirty beef cattle images were measured and the average relative error of body height, body oblique length, chest depth and hoof diameter were 6.75 %, 7.55 %, 8.00 %, 8.97 %. The results showed that the proposed method could measure the body size of beef cattle at different distances and light conditions.

Supernova calibration by gravitational waves

Hubble tension is one of the most important problems in cosmology. Although the local measurements on the Hubble constant with Type Ia supernovae (SNe Ia) are independent of cosmological models, they suffer the problem of zero-point calibration of the luminosity distance. The observations of gravitational waves (GWs) with space-based GW detectors can measure the luminosity distance of the GW source with high precision. By assuming that massive binary black hole mergers and SNe Ia occur in the same host galaxy, we study the possibility of re-calibrating the luminosity distances of SNe Ia by GWs. Then we use low-redshift re-calibrated SNe Ia to determine the local Hubble constant. We find that we need at least 7 SNe Ia with their luminosity distances re-calibrated by GWs to reach a 2% precision of the local Hubble constant. The value of the local Hubble constant is free from the problems of zero-point calibration and model dependence, so the result can shed light on the Hubble tension.

Pantheon+ tomography and Hubble tension

The recently released Type Ia supernovae (SNe Ia) sample, Pantheon+, is an updated version of Pantheon and has very important cosmological implications. To explore the origin of the enhanced constraining power and internal correlations of datasets in different redshifts, we perform a comprehensively tomographic analysis of the Pantheon+ sample without and with the Cepheid host distance calibration, respectively. Specifically, we take two binning methods to analyze the Pantheon+ sample, i.e., equal redshift interval and equal supernovae number for each bin. For the case of equal redshift interval, after dividing the sample to 10 bins, the first bin in the redshift range zin [0.00122, , 0.227235] dominates the constraining power of the whole sample. For the case of equal supernovae number, the first three low redshift bins prefer a large matter fraction Omega _m and only the sixth bin gives a relatively low cosmic expansion rate H_0. For both binning methods, we find no obvious evidence of evolution of H_0 and Omega _m at the 2,sigma confidence level. The inclusion of the SH0ES calibration can significantly compress the parameter space of background dynamics of the universe in each bin. When not considering the calibration, combining the Pantheon+ sample with cosmic microwave background, baryon acoustic oscillations, cosmic chronometers, galaxy clustering and weak lensing data, we give the strongest 1,sigma constraint H_0=67.88pm 0.42 km hbox {s}^{-1}hbox {Mpc}^{-1}. However, the addition of the calibration leads to a global shift of the parameter space from the combined constraint and H_0=68.66pm 0.42 km hbox {s}^{-1}hbox {Mpc}^{-1}, which is inconsistent with the Planck-2018 result at about 2,sigma confidence level.

Obsessive-compulsive existential type: a dialectical-phenomenological approach.

The clinical presentation of obsessive-compulsive patients is characterized by unwanted, intrusive, nonsensical, self-related, and recurrent ideas, thoughts, images, or impulses associated with active compulsive compensations. Under the operational diagnostic criteria adopted by the biological- and cognitive-oriented neopositivist medical paradigm, it is known as "obsessive-compulsive disorder." However, this paradigm has been criticized for its controversial assumptions, limited methodologies, theoretic biases, and inconsistency in producing practical outcomes. To bypass some of these issues, we propose a complementary approach that draws on and further develops existing psychopathological studies of the obsessive-compulsive anthropological condition based on dialectical phenomenological psychopathology. As such, we refer to the global clinical configuration as the "obsessive-compulsive existential type." Our theoretical inspiration comes from the classical phenomenological work on obsessions undertaken by Straus and Gebsattel, which identified the negative transformation of the obsessive-compulsive life-world or the endogenous emergence of the anti-eidos (diluting existential force). We then propose to broaden the concept of anti-eidos, especially in its dialectical correlation with eidos (unifying existential force), representing the existential dialectic between transformation and permanence. Next, we detail the dynamics of anthropological disproportions in obsessive-compulsive existential type, essentially the supremacy of the anti-eidos over the eidos. This primary imbalance modifies the obsessive-compulsive existential structure, consisting of polymorphic temporality; weakened intentionality; maladjusted calibration of distance with the world and others; an integral, isolated, besieged self with dwindling self-agency, and tense and over-protecting embodiment. We also analyze compensatory hyperreflexivity and compulsive rituals as expressions of structural counterbalancing designed to contain the primary structural disproportions and derangements. The heterogeneous obsessive-compulsive clinical manifestations are the complex result of the primary structural alteration and subsequent phenomenological compensations. They tend to be variable in temporal span and rarely assume a fixed form, hindering diagnosis. We correlate structural frameworks with multiple clinical examples. Finally, we raise some insights on how our study may contribute to scientific research and therapeutic proposals.

Greater interpersonal distance in adults with autism.

Social interactions are often shaped by the space we prefer to maintain between us and others, that is, interpersonal distance. Being too distant or too close to a stranger can often be perceived as odd, and lead to atypical social interactions. This calibration of appropriate interpersonal distance thus constitutes an important social skill. Individuals with autism spectrum disorder (ASD, hereafter autism) often experience difficulties with this skill, and anecdotal accounts suggest atypical interpersonal distances in their social interactions. In the current study, we systematically measured interpersonal distance in individuals with autism using immersive virtual reality (IVR) to recreate a naturalistic interaction with a full body avatar of a similar age. Participants observed their own virtual body in first-person perspective, and the other avatar in two tasks: in the first task, they approached the other avatar (active), in the second one they were approached by the other avatar (passive). Two groups of neurotypical and autistic adults, performed both tasks. Autistic adults showed greater interpersonal distance when compared to non-autistic adults. Additionally, the difference between the passive and active conditions was smaller for non-autistic compared to autistic adults. Across the full sample, greater interpersonal distance was associated with higher autism-related traits. This study provides systematic evidence for greater interpersonal distance in autistic adults using a paradigm with high ecological validity and can be useful in informing the design of appropriate environmental adjustments for shared spaces.

Resolution-enhanced reflection ptychography with axial distance calibration

Reflection ptychography is a lens-free computational imaging technology that operates by a coherent beam illuminated to a specimen inclined to the optical axis, a set of distorted diffracted patterns is captured on the far-filed plane. This tilted distortion results from the tilt angle of illumination in a reflection mode as a non-coplanar scattering geometry, which mismatches the Fourier transformed distribution and blocks the operation of FFT (fast Fourier Transform) in standard ptychographic reconstruction algorithms. This distortion can be corrected by performing a coordinate transform from the tilted geometry combined with knowledge of the axial distance of diffraction and the radiation wavelength. However, practically the axial distance usually cannot be measured with accuracy instead of a rough estimate, which may disrupt the correction from distortion, and degrade the reconstructed quality significantly. Here, we propose and analyze for the first time a straightforward axial distance calibration approach to improve the reconstructed resolution in reflection ptychography. Firstly, a uniform Fraunhofer-shaped diffraction is transformed from the tilted distorted scatterings by a coordinate transform at a coarse estimate of axial distance. Then, the axial distance error can be precisely corrected from the periodic unwrapped phase of the retrieved probe by ptychography. Finally, a resolution-enhanced reconstruction is generated from the reflection ptychography with axial distance calibration. A group of proof-of-concept experiments was performed for verification. Results demonstrate that the axial distance can be precisely calibrated within a fraction of a millimeter. Moreover, the reconstructed resolution is remarkably improved (2 times improvement in our experimental tests) by utilizing the proposed approach in reflection ptychography.

Comparison of image quality of 3D ultrasound: motorized acquisition versus freehand navigated acquisition, a phantom study

PurposeIntra-operative assessment of resection margins during oncological surgery is a field that needs improvement. Ultrasound (US) shows the potential to fulfill this need, but this imaging technique is highly operator-dependent. A 3D US image of the whole specimen may remedy the operator dependence. This study aims to compare and evaluate the image quality of 3D US between freehand acquisition (FA) and motorized acquisition (MA).MethodsMultiple 3D US volumes of a commercial phantom were acquired in motorized and freehand fashion. FA images were collected with electromagnetic navigation. An integrated algorithm reconstructed the FA images. MA images were stacked into a 3D volume. The image quality is evaluated following the metrics: contrast resolution, axial and elevation resolution, axial and elevation distance calibration, stability, inter-operator variability, and intra-operator variability. A linear mixed model determined statistical differences between FA and MA for these metrics.ResultsThe MA results in a statistically significant lower error of axial distance calibration (p < 0.0001) and higher stability (p < 0.0001) than FA. On the other hand, the FA has a better elevation resolution (p < 0.003) than the MA.ConclusionMA results in better image quality of 3D US than the FA method based on axial distance calibration, stability, and variability. This study suggests acquiring 3D US volumes for intra-operative ex vivo margin assessment in a motorized fashion.

RadarPDR: Radar-Assisted Indoor Pedestrian Dead Reckoning

Pedestrian dead reckoning (PDR) is the critical component in indoor pedestrian tracking and navigation services. While most of the recent PDR solutions exploit in-built inertial sensors in smartphones for next step estimation, due to measurement errors and sensing drift, the accuracy of walking direction, step detection, and step length estimation cannot be guaranteed, leading to large accumulative tracking errors. In this paper, we propose a radar-assisted PDR scheme, called RadarPDR, which integrates a frequency-modulation continuous-wave (FMCW) radar to assist the inertial sensors-based PDR. We first establish a segmented wall distance calibration model to deal with the radar ranging noise caused by irregular indoor building layouts and fuse wall distance estimation with acceleration and azimuth signals measured by the inertial sensors of a smartphone. We also propose a hierarchical particle filter(PF) together with an extended Kalman filter for position and trajectory adjustment. Experiments have been conducted in practical indoor scenarios. Results demonstrate that the proposed RadarPDR is efficient and stable and outperforms the widely used inertial sensors-based PDR scheme.

Machine learning approach to residential valuation: a convolutional neural network model for geographic variation

Geographic location and neighbourhood attributes are major contributors to residential property values. Automated valuation models (AVM) often use hedonic pricing with location and neighbourhood attributes in the form of numeric and categorical variables. This paper proposed a novel approach to automated property valuation using a machine learning model with a convolutional neural network (CNN), fully connected neural network layers with numeric and categorical variables. In this study we compare the results of a fused model, which treat geographical data as an input with the performance of the baseline neural network model with only numerically or categorically represented data. Furthermore, the residential valuation by the proposed fused model was tested with actual sold price data in Greater Sydney, Australia. The study found that the fused model produced valuations with a significantly lower mean absolute percentage error (MAPE) (8.71%) than the MAPE of the baseline model (11.59%). The results show that the fused model with CNN significantly improves the accuracy for residential valuation, reducing spatial information loss by data manipulation and distance calibration.

Dependence of Cosmological Constraints on Gray Photometric Zero-point Uncertainties of Supernova Surveys

Type Ia supernova (SN) measurements of the Hubble constant, H 0; cosmic mass density, Ω M ; and dark energy equation-of-state parameter, w, rely on heterogeneous SN surveys across three decades of observation. These distinct surveys may have undiagnosed, relative photometric zero-point errors. We determine the sensitivities of the SH0ES+Pantheon+ cosmological constraints to unknown gray systematics in the photometric zero-point calibration between the 19 surveys that comprise the Pantheon+ SN compendium. Varying the surveys’ gray zero-points simultaneously with cosmological parameters, we determine that the SH0ES+Pantheon+ measurement of H 0 is robust against gray intersurvey photometric miscalibration. Specifically, uncalibrated intersurvey systematics could represent a source of uncertainty no larger than 0.39 km s−1 Mpc−1 for H 0. This modest increase in H 0 uncertainty could not account for the 7 km s−1 Mpc−1 “Hubble tension” between the SH0ES measurement of H 0 and the Planck ΛCDM-based inference of H 0. However, the SH0ES+Pantheon+ best-fit values of Ω M and w are not robust against gray zero-point error, slipping by up to 0.16 and −0.63. Because measurements of Ω M and w depend on intrasurvey cross-band calibration, the hypothetical gray miscalibration underestimates the sensitivity of these measurements to zero-point miscalibration. Because the Pantheon+ compendium contains many surveys that share low-z Hubble flow (HF) and Cepheid-paired SNe, intersurvey photometric calibration errors do not significantly impede the joint use of SH0ES and Pantheon+ to measure H 0 to 1% accuracy. However, H 0 constraints that rely on one HF survey but numerous galactic distance calibration surveys are susceptible to intersurvey photometric miscalibration.

Constraining Coupling Constants’ Variation with Supernovae, Quasars, and GRBs

Dirac, in 1937, proposed the potential variation of coupling constants derived from his large numbers hypothesis. Efforts have continued since then to constrain their variation by various methods, including astrophysical and cosmological observations. We briefly discuss several methods used for the purpose while focusing primarily on the use of supernovae type 1a, quasars, and gamma-ray bursts as cosmological probes for determining cosmological distances. Supernovae type Ia (SNeIa) are considered the best standard candles since their intrinsic luminosity can be determined precisely from their light curves. However, they have only been observed up to about redshift z=2.3, mostly at z≤1.5. Quasars are the brightest non-transient cosmic sources in the Universe. They have been observed up to z=7.5. Certain types of quasars can be calibrated well enough for their use as standard candles but with a higher degree of uncertainty in their intrinsic luminosity than SNeIa. Gamma-ray bursts (GRBs) are even brighter than quasars, and they have been observed up to z=9.4. They are sources of highly transient radiation lasting from tens of milliseconds to several minutes and, in rare cases, a few hours. However, they are even more challenging to calibrate as standard candles than quasars. Both quasars and GRBs use SNeIa for distance calibration. What if the standard candles’ intrinsic luminosities are affected when the coupling constants become dynamic and depend on measured distances? Assuming it to be constant at all cosmic distances leads to the wrong constraint on the data-fitted model parameters. This paper uses our earlier finding that the speed of light c, the gravitational constant G, the Planck constant h, and the Boltzmann constant k vary in such a way that their variation is interrelated as G~c3~h3~k3/2 with G˙/G=3c˙/c=3h˙/h=1.5k˙/k =3.90±0.04×10−10 yr−1 and corroborates it with SNeIa, quasars, and GRBs observational data. Additionally, we show that this covarying coupling constant model may be better than the standard ΛCDM model for using quasars and GRBs as standard candles and predict that the mass of the GRBs scales with z as 1+z1/3−1. Noether’s symmetry on the coupling constants is now transferred effectively to the constant in the function relating to their variation.