The present invention provides a method for forming a history of natural gas accumulation by using carbon isotopes by a pyrolysis experiment. The method includes: obtaining activation energy distribution and a frequency factor of light carbon methane; carrying out carbon isotope kinetics simulation of natural gas in a study area by using a spreadsheet function of Excel to obtain activation energy, a mass fraction and a frequency factor of heavy carbon methane; establishing a burial history and a thermal history of the study area based on geological data; and combining the activation energy distribution and frequency factor of the heavy carbon methane with the burial history and thermal history of the study area, and establishing an instantaneous curve, a cumulative curve and a stage cumulative curve of natural gas under geological conditions on a geologic time scale.

The present invention provides a method for forming a history of natural gas accumulation by using carbon isotopes by a pyrolysis experiment. The method includes: obtaining activation energy distribution and a frequency factor of light carbon methane; carrying out carbon isotope kinetics simulation of natural gas in a study area by using a spreadsheet function of Excel to obtain activation energy, a mass fraction and a frequency factor of heavy carbon methane; establishing a burial history and a thermal history of the study area based on geological data; and combining the activation energy distribution and frequency factor of the heavy carbon methane with the burial history and thermal history of the study area, and establishing an instantaneous curve, a cumulative curve and a stage cumulative curve of natural gas under geological conditions on a geologic time scale.

A method for simulating a quantum chemistry system comprises determining a hard-core bosonic Hamiltonian describing the quantum chemistry system, the Hamiltonian model restricting the electronic states to electron singlet state configurations; determining a “paired-electron unitary coupled cluster with double excitations” (pUCCD) ansatz, the ansatz being restricted to paired-electron configurations; mapping the pUCCD ansatz to qubit operations of a quantum circuit that comprises a set of qubits and gates for enabling pairs of qubits to interact with each other: and, determining a trial state on the quantum circuit by applying the qubit operations defined by the mapped pUCCD ansatz to the qubits; and, determining an energy of the quantum chemistry system based on the trial state and the restricted Hamiltonian, grouping the Hamiltonian terms into three sets of operators which can be measured simultaneously; and, an error-mitigation technique, based on post-selection of the quantum measurements with the known particle number.

A method for simulating a quantum chemistry system comprises determining a hard-core bosonic Hamiltonian describing the quantum chemistry system, the Hamiltonian model restricting the electronic states to electron singlet state configurations; determining a “paired-electron unitary coupled cluster with double excitations” (pUCCD) ansatz, the ansatz being restricted to paired-electron configurations; mapping the pUCCD ansatz to qubit operations of a quantum circuit that comprises a set of qubits and gates for enabling pairs of qubits to interact with each other: and, determining a trial state on the quantum circuit by applying the qubit operations defined by the mapped pUCCD ansatz to the qubits; and, determining an energy of the quantum chemistry system based on the trial state and the restricted Hamiltonian, grouping the Hamiltonian terms into three sets of operators which can be measured simultaneously; and, an error-mitigation technique, based on post-selection of the quantum measurements with the known particle number.

The disclosure provides a process of designing and optimizing supramolecular therapeutics. The disclosure also provides a method for designing and optimizing antibody drug conjugates.

The disclosure provides a process of designing and optimizing supramolecular therapeutics. The disclosure also provides a method for designing and optimizing antibody drug conjugates.

Techniques regarding determining a three-dimensional structure of a heteropolymer are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a polymer folding component that can generate a course-grained model to determine a three-dimensional structure of a heteropolymer based on a first qubit registry that encodes a conformation of the heteropolymer on a lattice and a second qubit registry that encodes an interaction distance between monomers comprised within the heteropolymer.

Techniques regarding determining a three-dimensional structure of a heteropolymer are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a polymer folding component that can generate a course-grained model to determine a three-dimensional structure of a heteropolymer based on a first qubit registry that encodes a conformation of the heteropolymer on a lattice and a second qubit registry that encodes an interaction distance between monomers comprised within the heteropolymer.

Provided is a simulation method that represents an elastic analysis object as an aggregate of a plurality of virtual particles, and the method includes, when solving the equation of motion for each particle, regarding the analysis object as a rigid body, and calculating a force acting on the analysis object and a velocity of the analysis object, based on the force acting on each particle obtained at each time step and the velocity and the position of each particle, applying FIRE to a motion of the analysis object to calculate a force to be applied to the analysis object, obtaining a force to be additionally applied to each particle, by distributing the force to be applied to the analysis object to the plurality of particles, and solving the equation of motion, by adding the force to be additionally applied, to the force acting on each particle.

A computer-implemented method for a generative adversarial approach for conformational space modeling of molecules is provided. The method can include obtaining molecule graph data for a molecule and inputting the molecule graph data into a machine learning platform. The machine learning platform can include architecture of a molecular graph generator, conformation discriminator, stochastic encoder, and latent variables discriminator. The method can include generating a plurality of conformations for the molecule with the machine learning platform. The plurality of conformations are specific to the molecule. Each conformation can have internal coordinates defining positions of atoms of the molecule. At least one conformation for the molecule can be selected based on at least one parameter related to molecular conformations. A report can be prepared that includes the selected at least one conformation for the molecule.