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Results for “variational quantum algorithms”

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At least 19 recordsLinked to original sources

PubMed2025

Generating three-dimensional genome structures with a variational quantum algorithm.

Chromosome conformation capture experiments have revealed the underlying spatial interactions that govern three-dimensional (3D) genome organization and topology. Detecting 3D contacts between genomic loci considerably enhances our understanding of fundamental regulatory processes. Modeling 3D structures from experimental contact matrices can further contextualize the relationship between 3D genome organization and regulation. While classical algorithms have been successful in reconstructing genomic conformations, we investigate the prospect of quantum computation to aid in modeling the conformational space. In this context, we propose a novel variational quantum algorithm (VQA) to model the distribution of 3D genomic structures from experimental contact data. Through rigorous evaluations, we demonstrate the capability of our algorithm to sample ensembles of viable 3D conformations that agree well with experimental and simulated contact data. Furthermore, we extend our methodology to model the conformational space of a single cell or a population of cells. In the advent of sufficient quantum utility, the insights gained from this study can serve as a foundation for investigating high-resolution, large-scale ensembles of genomic conformations through generative VQAs.

Algorithms↗

PubMed1995

Quantum and biological computation.

Ubiquitous internal measurement of material origin and conservation laws, when combined together, uphold biological computation as a specific mode of quantum computation. Internal measurement supplemented by conservation laws can reproduce quantum mechanics or the uncertainty principle in particular. Furthermore, biological computation founded upon internal measurement provides an irreversible enhancement of organization and quantum coherency through non-algorithmic and non-programmable procedures of generating variations in accordance with the operation of the uncertainty principle.

Animals↗

PubMed2025

Q RadFusion: Hybrid Quantum Classical Radiogenomic Framework for Breast Cancer Diagnosis.

BACKGROUND AND PURPOSE: Breast cancer remains the most common cancer in women worldwide, with early and accurate diagnosis critical for patient survival. Radiogenomics integrates imaging phenotypes with genomic profiles, offering a pathway to precision diagnostics. However, existing classical machine learning models often struggle with the high dimensionality and heterogeneity of multimodal data, leading to issues in calibration and reproducibility. This study presents Q RadFusion, a hybrid quantum-classical framework designed to enhance breast cancer diagnosis by fusing mammography and genomics data. METHODS: Q RadFusion was implemented on two publicly available datasets: CBIS-DDSM (2,600 curated mammography cases, TCIA) and TCGA-BRCA (1,000 genomic profiles, GDC). Imaging preprocessing included bias-field correction, segmentation, and harmonization, while genomic data underwent normalization and imputation. Feature selection was performed using the Quantum Approximate Optimization Algorithm (QAOA), and features were mapped into a quantum Hilbert space using Variational Quantum Circuits (VQC). For multimodal fusion, ResNet encoded mammography features, and a Transformer encoded genomic features. Patient-level and site-held-out splits were used for evaluation. RESULTS: Q RadFusion achieved an AUC of 0.96 and accuracy of 94%, outperforming baselines including CNN-LSTM, ResNet + XGBoost, and multimodal Transformers. Ablation studies confirmed the contribution of quantum components, with optimal performance observed at circuit depth, qubits, and QAOA layers. The model also demonstrated improved calibration and ~ 80% fewer parameters compared to deep fusion networks. CONCLUSION: Q RadFusion demonstrates that hybrid quantum-classical radiogenomic integration can deliver accurate, reproducible, and clinically meaningful diagnostic support for breast cancer, with strong potential for future clinical translation.

Breast Cancer↗

PubMed2004

A diffusion quantum Monte Carlo study of geometries and harmonic frequencies of molecules.

This article describes an approach in determination of equilibrium geometries and harmonic frequencies of molecules by the Ornstein-Uhlenbeck diffusion quantum Monte Carlo method based on the floating spherical Gaussians. In conjunction with a projected and renormalized Hellmann-Feynman gradient and an electronic energy at variational Monte Carlo and diffusion quantum Monte Carlo, respectively, the quasi-Newton algorithm implemented with the Broyden-Fletcher-Goldfarb-Shanno updated Hessian was used to find the optimized molecular geometry. We applied this approach to N2 and H2O molecules. The geometry and harmonic frequencies calculated were consistent with some sophisticated ab initio calculated values within reasonable statistical uncertainty.

Journal Article↗

PubMed2006

Quantum Monte Carlo method using a stochastic Poisson solver.

The quantum Monte Carlo (QMC) technique is an extremely powerful method to treat many-body systems. Usually the quantum Monte Carlo method has been applied in cases where the interaction potential has a simple analytic form, like the 1/r Coulomb potential. However, in a complicated environment as in a semiconductor heterostructure, the evaluation of the interaction itself becomes a nontrivial problem. Obtaining the potential from any grid-based finite-difference method for every walker and every step is infeasible. We demonstrate an alternative approach of solving the Poisson equation by a classical Monte Carlo calculation within the overall quantum Monte Carlo scheme. We have developed a modified "walk on spheres" algorithm using Green's function techniques, which can efficiently account for the interaction energy of walker configurations, typical of quantum Monte Carlo algorithms. This stochastically obtained potential can be easily incorporated with variational, diffusion, and other Monte Carlo techniques. We demonstrate the validity of this method by studying a simple problem, the polarization of a helium atom in the electric field of an infinite capacitor.

Journal Article↗

PubMed2001

A cone beam filtered backprojection (CB-FBP) reconstruction algorithm for a circle-plus-two-arc orbit.

The circle-plus-arc orbit possesses advantages over other "circle-plus" orbits for the application of x-ray cone beam (CB) volume CT in image-guided interventional procedures requiring intraoperative imaging, in which movement of the patient table is to be avoided. A CB circle-plus-two-arc orbit satisfying the data sufficiency condition and a filtered backprojection (FBP) algorithm to reconstruct longitudinally unbounded objects is presented here. In the circle suborbit, the algorithm employs Feldkamp's formula and another FBP implementation. In the arc suborbits, an FBP solution is obtained originating from Grangeat's formula, and the reconstruction computation is significantly reduced using a window function to exclude redundancy in Radon domain. The performance of the algorithm has been thoroughly evaluated through computer-simulated phantoms and preliminarily evaluated through experimental data, revealing that the algorithm can regionally reconstruct longitudinally unbounded objects exactly and efficiently, is insensitive to the variation of the angle sampling interval along the arc suborbits, and is robust over practical x-ray quantum noise. The algorithm's merits include: only 1D filtering is implemented even in a 3D reconstruction, only separable 2D interpolation is required to accomplish the CB backprojection, and the algorithm structure is appropriate for parallel computation.

Algorithms↗

PubMed2004

Linear scaling computation of the Fock matrix. VII. Parallel computation of the Coulomb matrix.

We present parallelization of a quantum-chemical tree-code for linear scaling computation of the Coulomb matrix. Equal time partition is used to load balance computation of the Coulomb matrix. Equal time partition is a measurement based algorithm for domain decomposition that exploits small variation of the density between self-consistent-field cycles to achieve load balance. Efficiency of the equal time partition is illustrated by several tests involving both finite and periodic systems. It is found that equal time partition is able to deliver 91%-98% efficiency with 128 processors in the most time consuming part of the Coulomb matrix calculation. The current parallel quantum chemical tree code is able to deliver 63%-81% overall efficiency on 128 processors with fine grained parallelism (less than two heavy atoms per processor).

Journal Article↗

PubMed1995

Rational design of anticonvulsants: a quantum pharmacologic study of the ion channel-modulating FMRFamide tetrapeptide as an endogenous anticonvulsant.

We applied the computational techniques of quantum pharmacology to examine molecular conformations (shapes and geometries) of the tetrapeptide FMR-Famide (L-Phe-L-Met-L-Arg-L-Phe-NH2), determining the geometric features necessary for anticonvulsant activity. The rigorous tiered hierarchical approach used molecular mechanics, molecular dynamics, and semiempirical quantum mechanics calculational methods. Low-energy conformations showed pertinent conformational information to be considered in the rational design of novel anticonvulsants. The FMRFamide peptide backbone assumes a bent but primary planar geometry. Distinct polar and nonpolar regions are created as the two Phe residues occupy one "face" of the bent conformation, while the Met and Arg residues occupy the opposite face. The aromatic rings point away from each other along the backbone, and this separation is consistent among the low-energy conformations at approximately 11-12 A. The Met side chain interacts with neither the peptide backbone nor the side chains of other residues. Molecular mechanics and semiempirical quantum mechanics calculations predict limited variation in the orientation of the Arg side chain.

Algorithms↗

PubMed2004

Converged quantum dynamics calculations of vibrational energies of CH4 and CH3D using an ab initio potential.

Exact variational calculations of vibrational energies of CH4 and CH3D are carried out using a two-layer Lanczos algorithm based on the ab initio potential energy surface of D. W. Schwenke and H. Partridge, Spectrochim. Acta, Part A 57, 887 (2001). The convergence of the calculated vibrational energies is discussed in detail. In addition, we report all well converged vibrational energy levels up to 6600 cm(-1) for CH4, and those up to 5000 cm(-1) for CH3D, respectively. These results clearly outperform previous theoretical calculations. And a comparison with experimental results available is also made.

Journal Article↗

PubMed2004

Variational transition state theory calculations for the rate constants of the hydrogen scrambling and the dissociation of BH5 using the multiconfiguration molecular mechanics algorithm.

The BH5 molecule contains a weak two-electron-three-center bond and it requires extremely high level of theories to calculate the energy and structure correctly. The potential energy of the hydrogen scrambling in BH5 has been generated by the multiconfiguration molecular mechanics algorithm with 15 high-level Shepard interpolation points, which would be practically impossible to obtain otherwise. The high-level interpolation points were obtained from the multicoefficient correlated quantum mechanical methods. The more high-level points are used, the better the shape of the potential energy surface. The rate constants are calculated using the variational transition state theory including multidimensional tunneling approximation. The potential energy curve for the BH5 dissociation has also been calculated, and the variational transition state was located to obtain the dissociation rate constants. Tunneling is very important in the scrambling, and there is large variational effect on the dissociation. The rate constants for the scrambling and the dissociation are 2.1 x 10(9) and 2.3 x 10(12) s(-1) at 300 K, respectively, which suggests that the dissociation is three orders of magnitude faster than the scrambling.

Journal Article↗

PubMed2004

A novel algorithm for non-adiabatic direct dynamics using variational Gaussian wavepackets.

In a recent paper (G. Worth, P. Hunt and M. Robb, J. Phys. Chem. A, 2003, 107, 621), we used surface hopping direct dynamics calculations to study the molecular dynamics of the butatriene radical cation in the X/A manifold, which is coupled by a conical intersection. Here, we present the first direct dynamics calculations using a novel algorithm, again using this ideal test system. The algorithm, which is based on the powerful multi-configuration time-dependent Hartree (MCTDH) wavepacket propagation method, uses a variational basis of coupled frozen Gaussian functions that optimally represent the evolving nuclear wavepacket at all times. Each Gaussian function follows a "quantum trajectory", along which the potential surface is evaluated by quantum chemistry calculations. As far fewer Gaussian functions are needed than classical trajectories in a semi-classical method, the number of quantum chemical calculations is drastically reduced. A crucial point in direct dynamics. To validate the method, initial calculations have been made using an analytic model Hamiltonian, where it is shown to reproduce the main features of the state population transfer with 8-16 basis functions per state. Coupled to the GAUSSIAN quantum chemistry program, the method is then shown to provide a feasible direct dynamics algorithm for the description of this non-adiabatic process.

Journal Article↗

PubMed2007

The use of quantum molecular calculations to guide a genetic algorithm: a way to search for new chemistry.

The process of gene-based molecular evolution has been simulated in silico by using massively parallel density functional theory quantum calculations, coupled with a genetic algorithm, to test for fitness with respect to a target chemical reaction in populations of genetically encoded molecules. The goal of this study was the identification of transition-metal complexes capable of mediating a known reaction, namely the cleavage of N(2) to give the metal nitride. Each complex within the search space was uniquely specified by a nanogene consisting of an eight-digit number. Propagation of an individual nanogene into successive generations was determined by the fitness of its phenotypic molecule to perform the target reaction and new generations were created by recombination and mutation of surviving nanogenes. In its simplest implementation, the quantum-directed genetic algorithm (QDGA) quickly located a local minimum on the evolutionary fitness hypersurface, but proved incapable of progressing towards the global minimum. A strategy for progressing beyond local minima consistent with the Darwinian paradigm by the use of environmental variations coupled with mass extinctions was therefore developed. This allowed for the identification of nitriding complexes that are very closely related to known examples from the chemical literature. Examples of mutations that appear to be beneficial at the genetic level but prove to be harmful at the phenotypic level are described. As well as revealing fundamental aspects of molecular evolution, QDGA appears to be a powerful tool for the identification of lead compounds capable of carrying out a target chemical reaction.

Algorithms↗

PubMed2006

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results.

Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aPhi*) or the chlorophyll-a fluorescence quantum yield (eta) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. aPhi* appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient (bb,Phi) dominates the total backscattering, as is likely during algal blooms, variations in the specific bb,Phi may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as eta or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided.

Algorithms↗

PubMed2005

Four-dimensional quantum study on exothermic complex-forming reactions: Cl- + CH3Br-->ClCH3+Br-.

The exothermic gas-phase bimolecular nucleophilic substitution (S(N)2) reaction Cl(-)+CH(3)Br (upsilon1',upsilon2',upsilon3')-->ClCH(3) (upsilon1,upsilon2,upsilon3)+Br- and the corresponding endothermic reverse reaction have been studied by time-independent quantum scattering calculations in hyperspherical coordinates on a coupled-cluster potential-energy surface. The dimensionality-reduced model takes four degrees of freedom into account [Cl-C and C-Br stretching modes (quantum numbers upsilon3' and upsilon3); totally symmetric modes of the methyl group, i.e., C-H stretching (upsilon1' and upsilon1) and umbrella bending vibrations (upsilon2' and upsilon2)]. Diagonalization of the Hamiltonian was performed employing the Lanczos algorithm with a variation of partial reorthogonalization. A narrow grid in the total energy was employed so that long-living resonance states could be resolved and extracted. While excitation of the reactant umbrella bending mode already leads to a considerable enhancement of the reaction probability, its combination with vibrational excitation of the broken C-Br bond, (0, 1, 1), results in a strong synergic effect that can be rationalized by the similarity with the classical transitional normal mode. Exciting the C-H stretch has a non-negligible effect on the reaction probability, while for larger translational energies this mode follows the expected spectatorlike behavior. Combination of C-Br stretch and symmetric C-H, (1,0,1), stretch does not show a cooperative effect. Contrary to the spectator mode concept, energy originally stored in the C-H stretching mode is by no means conserved, but almost completely released in other modes of the reaction products. Products are most likely formed in states with a high degree of excitation in the new C-Cl bond, while the internal modes of the methyl group are less important. Reactants with combined umbrella/C-Br stretch excitation, (0, 1, 1), may yield products with two quanta in the umbrella mode.

Journal Article↗

PubMed2005

Computational methods in coupled electron-ion Monte Carlo simulations.

In the last few years, we have been developing a Monte Carlo simulation method to cope with systems of many electrons and ions in the Born-Oppenheimer approximation: the coupled electron-ion Monte Carlo method (CEIMC). Electronic properties in CEIMC are computed by quantum Monte Carlo rather than by density functional theory (DFT) based techniques. CEIMC can, in principle, overcome some of the limitations of the present DFT-based ab initio dynamical methods. The new method has recently been applied to high-pressure metallic hydrogen. Herein, we present a new sampling algorithm that we have developed in the framework of the reptation quantum Monte Carlo method chosen to sample the electronic degrees of freedom, thereby improving its efficiency. Moreover, we show herein that, at least for the case of metallic hydrogen, variational estimates of the electronic energies lead to an accurate sampling of the proton degrees of freedom.

Computer Simulation↗

PubMedDate not supplied

Computer modeling of three-dimensional reconstruction algorithm of cathodoluminescence material properties, analysis of errors, and optimization of variable parameters.

Three-dimensional (3-D) reconstruction of cathodoluminescence (CL) properties of materials (Saparin et al. 1997) is a new nondestructive technique that measures quantum yield information of subsurface layers as a set of two-dimensional image sections. This technique is able to synthesize a 3-D image without destroying the sample. The basis for this technique is the fact that the electrons in scanning electron microscopy penetrate the sample at different depths with a variation of accelerating voltage. The detected CL emission integrates the information from the full volume occupied by the charge carriers. Estimating the errors that occur during the reconstruction process is complex since these errors are caused by necessary approximations, noise, and the imperfection of the 3-D reconstruction algorithm that is employed. An analysis of the factors that affect the accuracy of the technique has been made. The estimation of systematic errors and the optimization of variable parameters were calculated by computer modeling.

Journal Article↗

PubMed2006

Comparison of clinical and physical measures of image quality in chest and pelvis computed radiography at different tube voltages.

The aim of this work was to study the dependence of image quality in digital chest and pelvis radiography on tube voltage, and to explore correlations between clinical and physical measures of image quality. The effect on image quality of tube voltage in these two examinations was assessed using two methods. The first method relies on radiologists' observations of images of an anthropomorphic phantom, and the second method was based on computer modeling of the imaging system using an anthropomorphic voxel phantom. The tube voltage was varied within a broad range (50-150 kV), including those values typically used with screen-film radiography. The tube charge was altered so that the same effective dose was achieved for each projection. Two x-ray units were employed using a computed radiography (CR) image detector with standard tube filtration and antiscatter device. Clinical image quality was assessed by a group of radiologists using a visual grading analysis (VGA) technique based on the revised CEC image criteria. Physical image quality was derived from a Monte Carlo computer model in terms of the signal-to-noise ratio, SNR, of anatomical structures corresponding to the image criteria. Both the VGAS (visual grading analysis score) and SNR decrease with increasing tube voltage in both chest PA and pelvis AP examinations, indicating superior performance if lower tube voltages are employed. Hence, a positive correlation between clinical and physical measures of image quality was found. The pros and cons of using lower tube voltages with CR digital radiography than typically used in analog screen-film radiography are discussed, as well as the relevance of using VGAS and quantum-noise SNR as measures of image quality in pelvis and chest radiography.

Algorithms↗

PubMed2004

Cooperating or fighting with control noise in the optimal manipulation of quantum dynamics.

This paper investigates the impact of control field noise on the optimal manipulation of quantum dynamics. Simulations are performed on several multilevel quantum systems with the goal of population transfer in the presence of significant control noise. The noise enters as run-to-run variations in the control amplitude and phase with the observation being an ensemble average over many runs as is commonly done in the laboratory. A genetic algorithm with an improved elitism operator is used to find the optimal field that either fights against or cooperates with control field noise. When seeking a high control yield it is possible to find fields that successfully fight with the noise while attaining good quality stable results. When seeking modest control yields, fields can be found which are optimally shaped to cooperate with the noise and thereby drive the dynamics more efficiently. In general, noise reduces the coherence of the dynamics, but the results indicate that population transfer objectives can be met by appropriately either fighting or cooperating with noise, even when it is intense.

Journal Article↗