Nuclear Geometry Research Articles

Monte Carlo damage models of different complexity levels predict similar trends in radiation induced DNA damage

Ion therapies have an increased relative biological effectiveness (RBE) compared to X-rays, but this remains poorly quantified across different radiation qualities. Mechanistic models that simulate DNA damage and repair after irradiation could be used to help better quantify RBE. However, there is large variation in model design with the simulation detail and number of parameters required to accurately predict key biological endpoints remaining unclear. This work investigated damage models with varying detail to determine how different model features impact the predicted DNA damage.

Methods: Damage models of reducing detail were designed in TOPAS-nBio and Medras investigating the inclusion of chemistry, realistic nuclear geometries, single strand break damage, and track structure. The nucleus models were irradiated with 1 Gy of protons across a range of linear energy transfers (LETs). Damage parameters in the models with reduced levels of simulation detail were fit to proton double strand break (DSB) yield predicted by the most detailed model. Irradiation of the optimised models with a range of radiation qualities was then simulated, before undergoing repair in the Medras biological response model.

Results: Simplified damage models optimised to proton exposures predicted similar trends in DNA damage across radiation qualities. On average across radiation qualities, the simplified models experienced an 8% variation in double strand break (DSB) yield but a larger 28% variation in chromosome aberrations. Aberration differences became more prominent at higher LETs, with model features having an increasing impact on the distribution and therefore misrepair of DSBs. However, overall trends remained similar with better agreement likely achievable through repair model optimisation. 

Conclusion: Several model simplifications could be made without compromising key damage yield predictions, although changes in damage complexity and distribution were observed. This suggests simpler, more efficient models may be sufficient for initial radiation damage comparisons, if validated against experimental data.&#xD.

X-ray AGNs with SRG/eROSITA: multiwavelength observations reveal merger triggering and post-coalescence circumnuclear blowout

ABSTRACT Major mergers between galaxies are predicted to fuel their central supermassive black holes (SMBHs), particularly after coalescence. However, determining the prevalence of active galactic nuclei (AGNs) in mergers remains a challenge, because AGN diagnostics are sensitive to details of the central structure (e.g. nuclear gas clouds, geometry, and orientation of a dusty torus) that are partly decoupled from SMBH accretion. X-rays, expected to be ubiquitous among accreting systems, are detectable through non-Compton-thick screens of obscuring material, and thus offer the potential for a more complete assessment of AGNs in mergers. But extant statistical X-ray studies of AGNs in mergers have been limited by either sparse, heterogeneous, or shallow on-sky coverage. We use new X-ray observations from the first SRG/eROSITA all-sky data release to characterize the incidence, luminosity, and observability of AGNs in mergers. Combining machine learning and visual classification, we identify 923 post-mergers in Dark Energy Camera Legacy Survey (DECaLS) imaging and select 4565 interacting galaxy pairs (with separations <120 kpc and mass ratios within 1:10) from the Sloan Digital Sky Survey. We find that galaxies with X-ray AGNs are 2.0$\pm$0.24 times as likely to be identified as post-mergers compared to non-AGN controls, and that post-mergers are 1.8$\pm$0.1 times as likely to host an X-ray AGN as non-interacting controls. A multiwavelength census of X-ray, optical, and mid-IR-selected AGNs suggests a picture wherein the underlying AGN fraction increases during pair-phase interactions, that galaxy pairs within ~20 kpc become heavily obscured, and that the obscuration often clears post-coalescence.

Performant automatic differentiation of local coupled cluster theories: Response properties and ab initio molecular dynamics

In this work, we introduce a differentiable implementation of the local natural orbital coupled cluster (LNO-CC) method within the automatic differentiation framework of the PySCFAD package. The implementation is comprehensively tuned for enhanced performance, which enables the calculation of first-order static response properties on medium-sized molecular systems using coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)]. We evaluate the accuracy of our method by benchmarking it against the canonical CCSD(T) reference for nuclear gradients, dipole moments, and geometry optimizations. In addition, we demonstrate the possibility of property calculations for chemically interesting systems through the computation of bond orders and Mössbauer spectroscopy parameters for a [NiFe]-hydrogenase active site model, along with the simulation of infrared spectra via ab initio LNO-CC molecular dynamics for a protonated water hexamer.

Startup and Multiphysics Analysis of a Compact kW-Class Thermal Spectrum Microreactor

Self-regulating compact nuclear microreactor concepts are being developed for use in space and at terrestrial remote sites. The current emphasis is on the development of high-assay low-enriched uranium–fueled reactors that rely on metal hydrides to achieve size, specific weight, and power parity with the legacy highly enriched uranium systems. In the case of terrestrial applications, metal hydride–moderated systems can also improve economic feasibility. The neutronic design of metal hydride–moderated high-temperature reactor cores is complicated by the need to optimize and synchronize delayed spatial and temporal reactivity feedback from outer reflectors. Zebra is a thermal spectrum proof-of-principle core designed for demonstrating the reactor dynamics of hydride-moderated spectrum reactors, which is studied in this work. The reactor, including the fuel, yttrium hydride moderator, heat pipes, central control rod, structural supports, and the beryllium reflector, weighs ~425 kg. The design shares several features common with nuclear criticality test geometries routinely used in National Criticality Experiments Research Center (NCERC) experiments such that a prototype of the reactor can be readily assembled and tested. Additional features, such as heat pipes and hydrogen barrier clads, were added to minimize the potential for large thermal gradients that in turn could induce hydrogen loss or structural deformation during extended periods of operation at ~1000 K. In this work, normal and off-normal state performance of the Zebra rector core was analyzed using MCNP and Abaqus-based Reactor Multiphysics (MARM) software. Up-to-date nuclear, thermal, and mechanical performance data were used to characterize the performance of the yttrium hydride moderator. Steady-state analyses established that at a postulated power between 20 and 50 kW(thermal), the reactor core is nearly isothermal irrespective of quality of conduction coupling between heat pipes and fuel plates. Additionally, heat pipe failure modes, including simultaneous failure of all heat pipes in a quadrant of a reactor, were examined to bound the maximum credible temperature spike in the reactor core for extreme off-normal operating conditions. Finally, we detail the startup design challenges for the hydride-moderated thermal core, and analyze load-following cases to achieve “self-regulation” using the Dynamic Analysis of Reactor Transients module of MARM. The reactor is self-regulating with a reactivity temperature coefficient of ~−1 pcm/K at the operating point based solely on nuclear cross-section feedback. It can be further strengthened using additional spectral shift neutron absorbers and incorporating design features that enhance core expansion. This work captures that hydride-moderated systems are feasible for various self-regulating applications once systematic checks are verified in order to achieve a well-engineered core design.

Salinity and flow pattern independent flow rate measurement in a gas-liquid flow with optimum feature selection and novel detection geometry using ANNs

This paper presents a study on the salinity determination and flow rate estimation in a two-phase air-water system. For this purpose, an automated air-water test loop capable of generating different flow patterns in a horizontal pathway was utilized to do numerous experiments at varying flow rates. A nuclear measuring setup, comprising Cs-137 and Am-241 as radiation sources, one NaI (Tl) scintillation detector to register transmission counts of Cs and three scintillator detectors for registering transmission and scattering counts from Am, was prepared. A pressure drop pipe was also employed for flow rate measurement, with MLPs were selected as the processing element. Notable innovations of this paper can be considered from two perspectives. Firstly, a novel paradigm in nuclear measurement geometry. This novelty uses the benefits of three scintillator detectors to extract features with the maximum potential for classifying and determining salinity. Secondly, there is a new method in data processing and utilizing optimum features to achieve the best performance in predicting flow rates. Results in flow rate prediction independent of salinity and flow regime indicate that the proposed paradigm and method are reliable for using in industrial fields related to multi-phase metering.

Exploring Alternate Methods for the Calculation of High-Level Vibrational Corrections of NMR Spin-Spin Coupling Constants.

Traditional nuclear magnetic resonance (NMR) calculations typically treat systems with a Born-Oppenheimer-derived electronic wave function that is solved for a fixed nuclear geometry. One can numerically account for this neglected nuclear motion by averaging over property values for all nuclear geometries with a vibrational wave function and adding this expectation value as a correction to an equilibrium geometry property value. Presented are benchmark coupled-cluster singles and doubles (CCSD) vibrational corrections to spin-spin coupling constants (SSCCs) computed at the level of vibrational second-order perturbation theory (VPT2) using the vibrational averaging driver of the CFOUR program. As CCSD calculations of vibrational corrections are very costly, cheaper electronic structure methods are explored via a newly developed Python vibrational averaging program within the Dalton Project. Namely, results obtained with the second-order polarization propagator approximation (SOPPA) and density functional theory (DFT) with the B3LYP and PBE0 exchange-correlation functionals are compared to the benchmark CCSD//CCSD(T) and experimental values. CCSD//CCSD(T) corrections are also combined with literature CC3 equilibrium geometry values to form the highest-order vibrationally corrected values available (i.e., CC3//CCSD(T) + CCSD//CCSD(T)). CCSD//CCSD(T) statistics showed favorable statistics in comparison to experimental values, albeit at an unfavorably high computational cost. A cheaper CCSD//CCSD(T) + B3LYP method showed quite similar mean absolute deviation (MAD) values as CCSD//CCSD(T), concluding that CCSD//CCSD(T) + B3LYP is optimal in terms of cost and accuracy. With reference to experimental values, a vibrational correction was not worth the cost for all of the other methods tested. Finally, deviation statistics showed that CC3//CCSD(T) + CCSD//CCSD(T) vibrational-corrected equilibrium values deteriorated in comparison to CCSD//CCSD(T) attributed to the use of a smaller basis set or lack of solvation effects for the CC3 equilibrium calculations.

Illuminating the link between nuclear geometry and chromatin structures through 4D nucleus modeling

Illuminating the link between nuclear geometry and chromatin structures through 4D nucleus modeling

Four-Dimensional Mesoscale Liquid Model of Nucleus Resolves Chromatin's Radial Organization.

Recent advances chromatin capture, imaging techniques, and polymer modeling have dramatically enhanced quantitative understanding of chromosomal folding. However, the dynamism inherent in genome architectures due to physical and biochemical forces and their impact on nuclear architecture and cellular functions remains elusive. While imaging of chromatin in four dimensions is becoming more common, there is a conspicuous lack of physics-based computational tools appropriate for revealing the forces that shape nuclear architecture and dynamics. To this end, we have developed a multiphase liquid model of the nucleus, which can resolve chromosomal territories, compartments, and nuclear lamina using a physics-based and data-informed free-energy function. The model enables rapid hypothesis-driven prototyping of nuclear dynamics in four dimensions, thereby facilitating comparison with whole nucleus imaging experiments. As an application, we model the Drosophila nucleus and map phase diagram of various possible nuclear morphologies. We shed light on the interplay of adhesive and cohesive interactions which give rise to distinct radial organization seen in conventional, inverted, and senescent nuclear architectures. The results also show the highly dynamic nature of the radial organization, the disruption of which leads to significant variability in domain coarsening dynamics and consequently variability of chromatin architecture. The model also highlights the impact of oblate nuclear geometry and heterochromatin-subtype interactions on the global chromatin architecture and local asymmetry of chromatin compartments.

Forward dijet production at the LHC within an impact parameter dependent TMD approach

We investigate possible signatures of gluon saturation using forward p + A → j + j + X di-jet production processes at the Large Hadron Collider. In the forward rapidity region, this is a highly asymmetric process where partons with large longitudinal momentum fraction x in the dilute projectile are used as a probe to resolve the small x partonic content of the dense target. Such dilute-dense processes can be described in the factorization framework of Improved Transverse Momentum Distributions (ITMDs). We present a new model for ITMDs where we explicitly introduce the impact parameter (b) dependence in the ITMDs, to properly account for the nuclear enhancement of gluon saturation effects, and discuss the phenomenological consequences for p − Pb, p − Xe and p − O collisions at the LHC. While the case of p − p and e − p collisions is used to fix the model parameters, we find that, on average, the nuclear enhancement of the saturation scale is noticeably weaker than expected from naive scaling with a simple dependence on the atomic number. Since our model explicitly accounts for event-by-event fluctuations of the nuclear geometry, it can also be applied to study forward central correlations in p − A collisions.

DNA break clustering as a predictor of cell death across various radiation qualities: influence of cell size, cell asymmetry, and beam orientation

Abstract Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area—either because of a smaller size or a change in beam orientation—have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

Fast and accurate nonadiabatic molecular dynamics enabled through variational interpolation of correlated electron wavefunctions.

We build on the concept of eigenvector continuation to develop an efficient multi-state method for the rigorous and smooth interpolation of a small training set of many-body wavefunctions through chemical space at mean-field cost. The inferred states are represented as variationally optimal linear combinations of the training states transferred between the many-body bases of different nuclear geometries. We show that analytic multi-state forces and nonadiabatic couplings from the model enable application to nonadiabatic molecular dynamics, developing an active learning scheme to ensure a compact and systematically improvable training set. This culminates in application to the nonadiabatic molecular dynamics of a photoexcited 28-atom hydrogen chain, with surprising complexity in the resulting nuclear motion. With just 22 DMRG calculations of training states from the low-energy correlated electronic structure at different geometries, we infer the multi-state energies, forces and nonadiabatic coupling vectors at 12 000 geometries with provable convergence to high accuracy along an ensemble of molecular trajectories, which would not be feasible with a brute force approach. This opens up a route to bridge the timescales between accurate single-point correlated electronic structure methods and timescales of relevance for photo-induced molecular dynamics.

Illuminating the impact-parameter dependence of UPC dijet photoproduction

We present new NLO pQCD predictions for photoproduction of dijets in ultraperipheral PbPb collisions at 5.02 TeV with a realistic photon flux and up-to-date nuclear PDFs. Our calculation of the impact parameter dependence of the photon flux includes the effects of the nuclear form factor in the photon-emitting nucleus and the spatial dependence of nuclear PDFs of the target nucleus, which are estimated using theWood-Saxon nuclear density profile. We show that a significant portion of the measured dijets at large zγ originate from events with impact parameters of the order of a few nuclear radii, and that the cross section predictions therefore become sensitive to the modelling of the nuclear geometry and photon flux close to the source nucleus.

Theoretical developments on the initial state in relativistic particle collisions

We discuss recent progress towards developing accurate initial state descriptions for heavy ion collisions focusing on weak coupling based approaches, that enable one to constrain the high-energy structure of nuclei from deep inelastic scattering or proton-nucleus collisions. We review recent developments to determine the event-by-event fluctuating nuclear geometry, to describe gluon saturation phenomena at next-to-leading order accuracy, and to include longitudinal dynamics to the initial state descriptions.

Empowering nuclear reactor analysis: OpenNode for accurate 3D core simulation through nodal expansion neutron diffusion equations solving

OpenNode is a sophisticated reactor core simulation tool, meticulously designed for educational purposes. Its main function is to solve the complex partial differential equation governing multi-group neutron diffusion in a Cartesian geometry. OpenNode relies on the second- and fourth-order Nodal Expansion Method (NEM) to provide accurate solutions to three-dimensional steady-state problems, encompassing both the direct and adjoint modes. At the heart of this method, the neutron balance equation serves as the fundamental framework for calculating the nodal neutron flux and the effective multiplication factor, enabling the complex evaluation of neutron flux distributions within individual nodes.The NEM methodology, carefully programmed in Fortran-90 in OpenNode, meticulously decomposes the reactor core into nodes of reasonable size. This approach balances computational efficiency and accuracy, achieving outstanding precision even when using a reduced number of computational meshes. To further increase the number of equations while maintaining the balance between unknowns, OpenNode judiciously incorporates two essential approximations: the Weighted Residual Method (WRM) and the Quadratic Transverse Leakage (QTL) approximation.OpenNode transcends simple computational prowess by adopting an intuitive Graphical User Interface (GUI), meticulously developed by combining Python 3, Qt Designer, and Blender software. This Python-powered graphical interface offers users a seamless, user-friendly experience, facilitating tasks such as data entry, execution of complex simulations, calculation of results, data visualization, 3D design of nuclear core geometry, and in-depth analysis of results. One of OpenNode’s key features is its innate flexibility, enabling it to solve problems in both 2D and 3D Cartesian geometries. This adaptability makes it a versatile tool suitable for a wide range of research and power reactor applications, offering users the ability to model and design reactors with unrivaled ease.To substantiate OpenNode’s reliability, comprehensive criticality calculations are carried out in various scenarios, including single-cell verification, BIBLIS, KOEBERG cores in two dimensions (2D), and IAEA cores in three dimensions (3D). The results clearly demonstrate OpenNode’s robustness and reliability in multidimensional criticality analysis. In particular, OpenNode adheres to an open-source philosophy, making it readily available for download. This commitment to open access fosters collaboration and paves the way for wider adoption within the education and research communities, nurturing a thriving ecosystem of shared knowledge and exploration.

Development and validation of a multivariable model for prediction of malignant transformation and recurrence of oral epithelial dysplasia

BackgroundOral epithelial dysplasia (OED) is the precursor to oral squamous cell carcinoma which is amongst the top ten cancers worldwide. Prognostic significance of conventional histological features in OED is not well established. Many additional histological abnormalities are seen in OED, but are insufficiently investigated, and have not been correlated to clinical outcomes.MethodsA digital quantitative analysis of epithelial cellularity, nuclear geometry, cytoplasm staining intensity and epithelial architecture/thickness is conducted on 75 OED whole-slide images (252 regions of interest) with feature-specific comparisons between grades and against non-dysplastic/control cases. Multivariable models were developed to evaluate prediction of OED recurrence and malignant transformation. The best performing models were externally validated on unseen cases pooled from four different centres (n = 121), of which 32% progressed to cancer, with an average transformation time of 45 months.ResultsGrade-based differences were seen for cytoplasmic eosin, nuclear eccentricity, and circularity in basal epithelial cells of OED (p < 0.05). Nucleus circularity was associated with OED recurrence (p = 0.018) and epithelial perimeter associated with malignant transformation (p = 0.03). The developed model demonstrated superior predictive potential for malignant transformation (AUROC 0.77) and OED recurrence (AUROC 0.74) as compared with conventional WHO grading (AUROC 0.68 and 0.71, respectively). External validation supported the prognostic strength of this model.ConclusionsThis study supports a novel prognostic model which outperforms existing grading systems. Further studies are warranted to evaluate its significance for OED prognostication.

A Discrete-Variable Local Diabatic Representation of Conical Intersection Dynamics.

Conical intersections (CIs) are ubiquitous in polyatomic molecules and are responsible for a wide range of phenomena in photochemistry and photophysics. Modeling the conical intersection dynamics with adiabatic electronic states is hindered by the divergence of the first- and second-order derivative couplings at CIs due to electronic degeneracy. We introduce and implement a novel diabatic representation for exact correlated electron-nuclear wave packet dynamics through conical intersections. It directly employs the adiabatic electronic states but avoids the singular first- and second-order derivative couplings and is robust to different gauge choices of the electronic wave function phases. The reference nuclear geometries defining the adiabatic electronic states are determined by a discrete-variable representation of the nuclear coordinates. The nonadiabatic effects are accounted for by the electronic overlap matrix instead of derivative couplings as in the adiabatic representation. Illustrated by a two-mode conical intersection model, this representation captures all nonadiabatic effects, including electronic transitions, electronic coherence, and geometric phases. Thus, this representation provides a singularity-free framework for modeling ab initio conical intersection wave packet dynamics.

Effects of clustered nuclear geometry on the anisotropic flow in O-O collisions at the LHC within a multiphase transport model framework

Effects of clustered nuclear geometry on the anisotropic flow in O-O collisions at the LHC within a multiphase transport model framework

Electronic Born-Oppenheimer approximation in nuclear-electronic orbital dynamics.

Within the nuclear-electronic orbital (NEO) framework, the real-time NEO time-dependent density functional theory (RT-NEO-TDDFT) approach enables the simulation of coupled electronic-nuclear dynamics. In this approach, the electrons and quantum nuclei are propagated in time on the same footing. A relatively small time step is required to propagate the much faster electronic dynamics, thereby prohibiting the simulation of long-time nuclear quantum dynamics. Herein, the electronic Born-Oppenheimer (BO) approximation within the NEO framework is presented. In this approach, the electronic density is quenched to the ground state at each time step, and the real-time nuclear quantum dynamics is propagated on an instantaneous electronic ground state defined by both the classical nuclear geometry and the nonequilibrium quantum nuclear density. Because the electronic dynamics is no longer propagated, this approximation enables the use of an order-of-magnitude larger time step, thus greatly reducing the computational cost. Moreover, invoking the electronic BO approximation also fixes the unphysical asymmetric Rabi splitting observed in previous semiclassical RT-NEO-TDDFT simulations of vibrational polaritons even for small Rabi splitting, instead yielding a stable, symmetric Rabi splitting. For the intramolecular proton transfer in malonaldehyde, both RT-NEO-Ehrenfest dynamics and its BO counterpart can describe proton delocalization during the real-time nuclear quantum dynamics. Thus, the BO RT-NEO approach provides the foundation for a wide range of chemical and biological applications.

Structural dynamics upon photoinduced charge transfer in N,N,N′,N′-tetramethylmethylenediamine

The ultrafast structural motion linked to the charge transfer process in Rydberg excited N,N,N′,N′-tetramethylmethylenediamine (TMMDA) has been monitored in real time using femtosecond time-resolved photoelectron imaging coupled with quantum chemical calculations. Optical excitation to the 3 s Rydberg state initially populates the charge on one of the two amine groups, resulting in a charge-localized structure in the Franck-Condon (FC) region. As the wavepacket evolves on the 3 s potential surface, the molecular geometry changes with time, leading to the corresponding variation in the charge distribution. The ensuing structural evolution yields two distinct conformers GG+ and TT+ (see text for nomenclature), both with the charge delocalized between the two nitrogen atoms. By virtue of the sensitivity of the Rydberg electron binding energy (BE) on the nuclear geometry, the time-dependent BE spectrum offers an intuitive mapping of the charge transfer reaction that leads from the initially prepared charge-localized GG-FC structure to the fully charge-delocalized GG+ and TT+ structures. Complementary computations provide evidence that through-space interaction is responsible for the charge delocalization in the GG+ and TT+ structures.

Atomic mass, Bjorken variable, and scale dependence of quark transport coefficient in Drell-Yan process for proton incident on nucleus* *Supported in part by the National Natural Science Foundation of China (11975090, 11575052).

By means of the nuclear parton distributions determined without the fixed-target Drell-Yan experimental data and the analytic expression of quenching weight based on the BDMPS formalism, next-to-leading order analyses were performed on the Drell-Yan differential cross section ratios from the Fermilab E906 and E866 collaborations. It was found that the results calculated only with the nuclear effects of the parton distribution were not in agreement with the E866 and E906 experimental data. The incoming parton energy loss effect cannot be ignored in the nuclear Drell-Yan reactions. The predicted results indicate that, with the quark transport coefficient as a constant, the suppression due to the target nuclear geometry effect is approximately% for the quark transport coefficient. It was shown that we should consider the target nuclear geometry effect in studying the Drell-Yan reaction on nuclear targets. On the basis of the Bjorken variable and scale dependence of the quark transport coefficient, the atomic mass dependence was incorporated. The quark transport coefficient was determined as a function of the atomic mass, Bjorken variable, and scale by the global fit of the experimental data. The determined constant factor of the quark transport coefficient is GeV/fm. It was found that the atomic mass dependence has a significant impact on the constant factor in the quark transport coefficient in cold nuclear matter.