ABSTRACT
Abstract
The present disclosure provides methods and systems for using a hybrid architecture of classical and non-classical (e.g., quantum) computing to compute the quantum mechanical energy and/or electronic structure of a chemical system, as well as to identify stable conformations of a chemical system (e.g., a molecule) and/or to perform an ab initio molecular dynamics calculation or simulation on the chemical system.
Description
CROSS-REFERENCE
This application is a continuation of International Application No. PCT/CA2020/050641, filed May 12, 2020, which claims the benefit of U.S. Provisional Application Ser. No. 62/949,263, filed Dec. 17, 2019, and U.S. Provisional Application Ser. No. 62/847,141, filed May 13, 2019, each of which is entirely incorporated herein by reference for all purposes.
BACKGROUND
In chemistry and biology, the identification and the prediction of the electronic structure and the most energetically stable conformers of a molecule have significant importance as molecular function is inherently embedded in molecular conformation. For example, the reaction rate in a catalyzed reaction can vary significantly based on which of several different conformations of the catalyst are used. As another example, a protein is more functional or functional at all when it forms a certain tertiary structure.
In order to accurately identify and predict the electronic structure and the most stable conformers, highly accurate quantum chemistry methods, such as Coupled-Cluster theory (CC) or Full Configuration Interaction (Full CI), may be performed. However, the computational costs of such methods can exponentially increase with the size of a molecule, and they often become intractable in cases where the size of a molecule exceeds about 50 atoms for CC, and about 10 atoms for Full CI, even when performed on some current state-of-the-art classical computers. Therefore, a highly efficient and accurate computational framework is needed to identify the most stable conformers of industry-relevant chemical compounds and biologically-relevant large molecules.
Quantum computing (QC) technology may be capable of computing the quantum mechanical energy and/or electronic structure of a molecule with exponentially less computational resources compared to classical computing. Thus, high-accuracy quantum chemistry calculations that are intractable using classical computing may become tractable using the QC approaches. However, QC approaches may face challenges, such as the high expense and rarity of QC resources. In addition, increasing the number of qubits in a quantum computer is a technologically challenge, which has limited the size of quantum computing devices. In addition, qubits are very sensitive to noise and environmental effects, which may cause them to decohere in a very short amount of time, thereby providing a relatively small window for running meaningful calculations.
SUMMARY
Recognized herein is the need for quantum algorithms and circuits that efficiently leverage current and near-term quantum computing systems to solve complex quantum chemistry problems. One approach is to decompose an industry-sized problem into subproblems, identify the more complex subproblems, and then use quantum computers to process a subset of problems, for example, those subproblems that are challenging for classical computers.
Systems and methods provided herein utilize problem decomposition (PD) techniques in quantum chemistry toward identification and prediction of the electronic structure and a set of the most energetically stable conformers of a molecule. Such PD techniques may include the fragment molecular orbital (FMO) method, the divide-and-conquer (DC) method, the density matrix embedding theory (DMET) method, the density matrix renormalization group (DMRG) method, tensor networks, the method of increments, and others, as described herein.
In quantum chemistry, PD techniques have been developed to efficiently compute molecular energies and/or electronic structures with reasonable accuracy using classical computing. In PD techniques, the molecule may be decomposed into smaller fragments such that the quantum mechanical energy and/or electronic structure computation becomes tractable for each fragment. The quantum mechanical energy and/or electronic structure computation may then be performed individually for each fragment. The quantum mechanical energy and/or electronic structure computations resulting from each fragment may be recombined into a solution for the original molecule.
Systems and methods provided herein to perform PD techniques on a QC platform may enable quantum mechanical energy and/or electronic structure computations to be performed with a high level of accuracy for each fragment. Further, the small size of each fragment may allow highly accurate computations to be performed on QC devices on which the scale of computations is rather restricted, thereby obtaining the energies and/or electronic structures of complex, industry-relevant molecules efficiently and accurately.
The identification of the electronic structure and the most energetically stable conformers of a molecule is a fundamental process in chemistry- and biology-related research and development. While such processes may be performed by actually synthesizing the molecule and using a variety of physicochemical measurements to identify its electronic structure and conformations, such experimental processes may require a very large amount of resources, such as human effort and time. Thus, highly efficient, and accurate computational methods and systems, such as those provided by the present disclosure, may significantly reduce the need for such resources and render common R&D processes more efficient. Further, methods and systems described herein can be applied not simply to single chemical systems structures (e.g., chemical compounds and biomolecules) but also to molecular aggregates with different associations. For example, methods and systems disclosed herein may be applied toward the identification of the most stable binding orientation of a drug candidate, relative to a target protein, determined from an ensemble of possible binding orientations.
The present disclosure provides methods and systems for using a hybrid architecture of quantum and classical computing processors to efficiently identify the electronic structure and the stable conformations of a chemical system (e.g., a molecule). A method may comprise obtaining an indication of a molecule; calculating or obtaining an ensemble of conformations of the molecule; and decomposing the chemical system into fragments (subsystems) for each conformation (which may be optionally stored in a list). The method may further comprise calculating the fermionic Hamiltonian (molecular Hamiltonian or electronic Hamiltonian) of each fragment of each conformation of the molecule; transforming each fermionic Hamiltonian to an equivalent qubit Hamiltonian; transforming the qubit Hamiltonian into a quantum circuit; calculating an initial state for qubits involved in the calculation of the total quantum mechanical energy and/or electronic structure; generating (e.g., through computational simulation) molecular quantum mechanical energy and/or electronic structure on a quantum hardware or classical simulator of a quantum circuit; and combining the energies and/or electronic structures for the plurality of the fragments to obtain an estimation of the total energy of the chemical system. The method may further comprise repeating these operations for all conformations in the ensemble of conformations and sorting the conformations in the ensemble of conformations based on the estimated total quantum mechanical energy and/or electronic structure. The method may further comprise providing an indication of the sorted conformation ensemble (e.g., in a list).
In one aspect, the present disclosure provides a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method being implemented by a hybrid computing unit comprising a classical computer and a distributed computing system comprising a plurality of one non-classical computers, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining, using the hybrid computing unit, quantum mechanical energies or electronic structures of each of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structure determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structure combined in (c).
In some embodiments, the plurality of non-classical computers comprises at least one quantum computer. In some embodiments, the at least one quantum computer comprises one or more members selected from the group consisting of a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, a quantum mechanical energy of the quantum mechanical energies comprises nuclear-nuclear repulsion energy.
In some embodiments, the method further comprises providing an input to the hybrid computing unit, the input comprising a set of atomic coordinates for the chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within the ensemble of conformations of the chemical system. In some embodiments, the method further comprises sorting the combined quantum mechanical energies or electronic structures of the at least the subset of the plurality of molecular fragments.
In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
In some embodiments, (d) comprises: determining a fermionic Hamiltonian (molecular Hamiltonian or electronic Hamiltonian) of a molecular fragment of the at least the subset of the plurality of molecular fragments; transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming the qubit Hamiltonian into a quantum circuit; and determining, using the quantum circuit, the quantum mechanical energy or electronic structure of the molecular fragment. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing ab initio molecular dynamics (AIMD) simulation of the chemical system. In some embodiments, the AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, the indication comprising coordinates of each particle of a plurality of particles in the chemical system and velocities of each particle in the chemical system; and subsequent to (c): (i) determining, from the combined energy or electronic structure, a force on each particle in the systems; (ii) updating the coordinates of each particles in the chemical system and the velocities of each particle in the chemical system; and (iii) electronically outputting a report indicative of the coordinates or velocities. In some embodiments, (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to the quantum mechanical energy or electronic structure. In some embodiments, (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
In another aspect, a system for performing a quantum mechanical energy or electronic structure calculation for a chemical system may comprise: memory comprising instructions for performing the quantum mechanical energy or electronic structure calculation for the chemical system; and a hybrid computing unit operatively coupled to the memory, wherein the hybrid computing unit comprises at least one classical computer and a distributed computing system comprising a plurality of non-classical computers, wherein the hybrid computing unit is configured to execute the instructions to at least: (a) decompose at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determine quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combine the quantum mechanical energies or electronic structures determined in (b); and (d) electronically output a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In another aspect, a non-transitory computer readable medium may comprise machine-executable code that upon execution by a hybrid computing unit comprising at least one classical computer and a distributed computing system comprising a plurality of non-classical computers, implements a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In another aspect, the present disclosure provides a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method being implemented by a hybrid computing unit comprising a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining, using the hybrid computing unit, quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In some embodiments, the at least one non-classical computer comprises at least one quantum computer. In some embodiments, the at least one quantum computer comprises one or more members selected from the group consisting of a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, a quantum mechanical energy of the quantum mechanical energies comprises nuclear-nuclear repulsion energy.
In some embodiments, the method further comprises providing an input to the hybrid computing unit, the input comprising a set of atomic coordinates for the chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within the ensemble of conformations of the chemical system. In some embodiments, the method further comprises sorting the combined quantum mechanical energies or electronic structures of the at least the subset of the plurality of molecular fragments.
In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
In some embodiments, (b) comprises: determining a fermionic Hamiltonian (molecular Hamiltonian or electronic Hamiltonian) of a molecular fragment of the at least the subset of the plurality of molecular fragments; transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming the qubit Hamiltonian into a quantum circuit; and determining, using the quantum circuit, the quantum mechanical energy or electronic structure of the molecular fragment. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing ab initio molecular dynamics (AIMD) simulation of the chemical system. In some embodiments, the AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, the indication comprising coordinates of each particle of a plurality of particles in the chemical system and velocities of each particle in the chemical system; and subsequent to (c): (i) determining, from the combined energy or electronic structure, a force on each particle in
CROSS-REFERENCE
This application is a continuation of International Application No. PCT/CA2020/050641, filed May 12, 2020, which claims the benefit of U.S. Provisional Application Ser. No. 62/949,263, filed Dec. 17, 2019, and U.S. Provisional Application Ser. No. 62/847,141, filed May 13, 2019, each of which is entirely incorporated herein by reference for all purposes.
BACKGROUND
In chemistry and biology, the identification and the prediction of the electronic structure and the most energetically stable conformers of a molecule have significant importance as molecular function is inherently embedded in molecular conformation. For example, the reaction rate in a catalyzed reaction can vary significantly based on which of several different conformations of the catalyst are used. As another example, a protein is more functional or functional at all when it forms a certain tertiary structure.
In order to accurately identify and predict the electronic structure and the most stable conformers, highly accurate quantum chemistry methods, such as Coupled-Cluster theory (CC) or Full Configuration Interaction (Full CI), may be performed. However, the computational costs of such methods can exponentially increase with the size of a molecule, and they often become intractable in cases where the size of a molecule exceeds about 50 atoms for CC, and about 10 atoms for Full CI, even when performed on some current state-of-the-art classical computers. Therefore, a highly efficient and accurate computational framework is needed to identify the most stable conformers of industry-relevant chemical compounds and biologically-relevant large molecules.
Quantum computing (QC) technology may be capable of computing the quantum mechanical energy and/or electronic structure of a molecule with exponentially less computational resources compared to classical computing. Thus, high-accuracy quantum chemistry calculations that are intractable using classical computing may become tractable using the QC approaches. However, QC approaches may face challenges, such as the high expense and rarity of QC resources. In addition, increasing the number of qubits in a quantum computer is a technologically challenge, which has limited the size of quantum computing devices. In addition, qubits are very sensitive to noise and environmental effects, which may cause them to decohere in a very short amount of time, thereby providing a relatively small window for running meaningful calculations.
SUMMARY
Recognized herein is the need for quantum algorithms and circuits that efficiently leverage current and near-term quantum computing systems to solve complex quantum chemistry problems. One approach is to decompose an industry-sized problem into subproblems, identify the more complex subproblems, and then use quantum computers to process a subset of problems, for example, those subproblems that are challenging for classical computers.
Systems and methods provided herein utilize problem decomposition (PD) techniques in quantum chemistry toward identification and prediction of the electronic structure and a set of the most energetically stable conformers of a molecule. Such PD techniques may include the fragment molecular orbital (FMO) method, the divide-and-conquer (DC) method, the density matrix embedding theory (DMET) method, the density matrix renormalization group (DMRG) method, tensor networks, the method of increments, and others, as described herein.
In quantum chemistry, PD techniques have been developed to efficiently compute molecular energies and/or electronic structures with reasonable accuracy using classical computing. In PD techniques, the molecule may be decomposed into smaller fragments such that the quantum mechanical energy and/or electronic structure computation becomes tractable for each fragment. The quantum mechanical energy and/or electronic structure computation may then be performed individually for each fragment. The quantum mechanical energy and/or electronic structure computations resulting from each fragment may be recombined into a solution for the original molecule.
Systems and methods provided herein to perform PD techniques on a QC platform may enable quantum mechanical energy and/or electronic structure computations to be performed with a high level of accuracy for each fragment. Further, the small size of each fragment may allow highly accurate computations to be performed on QC devices on which the scale of computations is rather restricted, thereby obtaining the energies and/or electronic structures of complex, industry-relevant molecules efficiently and accurately.
The identification of the electronic structure and the most energetically stable conformers of a molecule is a fundamental process in chemistry- and biology-related research and development. While such processes may be performed by actually synthesizing the molecule and using a variety of physicochemical measurements to identify its electronic structure and conformations, such experimental processes may require a very large amount of resources, such as human effort and time. Thus, highly efficient, and accurate computational methods and systems, such as those provided by the present disclosure, may significantly reduce the need for such resources and render common R&D processes more efficient. Further, methods and systems described herein can be applied not simply to single chemical systems structures (e.g., chemical compounds and biomolecules) but also to molecular aggregates with different associations. For example, methods and systems disclosed herein may be applied toward the identification of the most stable binding orientation of a drug candidate, relative to a target protein, determined from an ensemble of possible binding orientations.
The present disclosure provides methods and systems for using a hybrid architecture of quantum and classical computing processors to efficiently identify the electronic structure and the stable conformations of a chemical system (e.g., a molecule). A method may comprise obtaining an indication of a molecule; calculating or obtaining an ensemble of conformations of the molecule; and decomposing the chemical system into fragments (subsystems) for each conformation (which may be optionally stored in a list). The method may further comprise calculating the fermionic Hamiltonian (molecular Hamiltonian or electronic Hamiltonian) of each fragment of each conformation of the molecule; transforming each fermionic Hamiltonian to an equivalent qubit Hamiltonian; transforming the qubit Hamiltonian into a quantum circuit; calculating an initial state for qubits involved in the calculation of the total quantum mechanical energy and/or electronic structure; generating (e.g., through computational simulation) molecular quantum mechanical energy and/or electronic structure on a quantum hardware or classical simulator of a quantum circuit; and combining the energies and/or electronic structures for the plurality of the fragments to obtain an estimation of the total energy of the chemical system. The method may further comprise repeating these operations for all conformations in the ensemble of conformations and sorting the conformations in the ensemble of conformations based on the estimated total quantum mechanical energy and/or electronic structure. The method may further comprise providing an indication of the sorted conformation ensemble (e.g., in a list).
In one aspect, the present disclosure provides a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method being implemented by a hybrid computing unit comprising a classical computer and a distributed computing system comprising a plurality of one non-classical computers, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining, using the hybrid computing unit, quantum mechanical energies or electronic structures of each of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structure determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structure combined in (c).
In some embodiments, the plurality of non-classical computers comprises at least one quantum computer. In some embodiments, the at least one quantum computer comprises one or more members selected from the group consisting of a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, a quantum mechanical energy of the quantum mechanical energies comprises nuclear-nuclear repulsion energy.
In some embodiments, the method further comprises providing an input to the hybrid computing unit, the input comprising a set of atomic coordinates for the chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within the ensemble of conformations of the chemical system. In some embodiments, the method further comprises sorting the combined quantum mechanical energies or electronic structures of the at least the subset of the plurality of molecular fragments.
In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
In some embodiments, (d) comprises: determining a fermionic Hamiltonian (molecular Hamiltonian or electronic Hamiltonian) of a molecular fragment of the at least the subset of the plurality of molecular fragments; transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming the qubit Hamiltonian into a quantum circuit; and determining, using the quantum circuit, the quantum mechanical energy or electronic structure of the molecular fragment. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing ab initio molecular dynamics (AIMD) simulation of the chemical system. In some embodiments, the AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, the indication comprising coordinates of each particle of a plurality of particles in the chemical system and velocities of each particle in the chemical system; and subsequent to (c): (i) determining, from the combined energy or electronic structure, a force on each particle in the systems; (ii) updating the coordinates of each particles in the chemical system and the velocities of each particle in the chemical system; and (iii) electronically outputting a report indicative of the coordinates or velocities. In some embodiments, (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to the quantum mechanical energy or electronic structure. In some embodiments, (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
In another aspect, a system for performing a quantum mechanical energy or electronic structure calculation for a chemical system may comprise: memory comprising instructions for performing the quantum mechanical energy or electronic structure calculation for the chemical system; and a hybrid computing unit operatively coupled to the memory, wherein the hybrid computing unit comprises at least one classical computer and a distributed computing system comprising a plurality of non-classical computers, wherein the hybrid computing unit is configured to execute the instructions to at least: (a) decompose at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determine quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combine the quantum mechanical energies or electronic structures determined in (b); and (d) electronically output a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In another aspect, a non-transitory computer readable medium may comprise machine-executable code that upon execution by a hybrid computing unit comprising at least one classical computer and a distributed computing system comprising a plurality of non-classical computers, implements a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In another aspect, the present disclosure provides a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method being implemented by a hybrid computing unit comprising a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining, using the hybrid computing unit, quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In some embodiments, the at least one non-classical computer comprises at least one quantum computer. In some embodiments, the at least one quantum computer comprises one or more members selected from the group consisting of a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, a quantum mechanical energy of the quantum mechanical energies comprises nuclear-nuclear repulsion energy.
In some embodiments, the method further comprises providing an input to the hybrid computing unit, the input comprising a set of atomic coordinates for the chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within the ensemble of conformations of the chemical system. In some embodiments, the method further comprises sorting the combined quantum mechanical energies or electronic structures of the at least the subset of the plurality of molecular fragments.
In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
In some embodiments, (b) comprises: determining a fermionic Hamiltonian (molecular Hamiltonian or electronic Hamiltonian) of a molecular fragment of the at least the subset of the plurality of molecular fragments; transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming the qubit Hamiltonian into a quantum circuit; and determining, using the quantum circuit, the quantum mechanical energy or electronic structure of the molecular fragment. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining the quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming the fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing ab initio molecular dynamics (AIMD) simulation of the chemical system. In some embodiments, the AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, the indication comprising coordinates of each particle of a plurality of particles in the chemical system and velocities of each particle in the chemical system; and subsequent to (c): (i) determining, from the combined energy or electronic structure, a force on each particle in the systems; (ii) updating the coordinates of each particles in the chemical system and the velocities of each particle in the chemical system; and (iii) electronically outputting a report indicative of the coordinates or velocities. In some embodiments, (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to the quantum mechanical energy or electronic structure. In some embodiments, (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
In some embodiments, the method further comprises dispatching one or more of the plurality of fragments to one or more remote endpoints and receiving the quantum mechanical energies or electronic structures from the one or more remote endpoints. In some embodiments, at least one of the one or more remote endpoints comprises a non-classical computer. In some embodiments, the one or more remote endpoints comprises portions of a cloud computing system. In some embodiments, the method further comprises, prior to (a), receiving the at least one conformation from a client-side library and dispatching the at least one conformation to a first remote endpoint. In some embodiments, at least one of (a) and (c) occurs at the first remote endpoint. In some embodiments, the method further comprises dispatching one or more of the plurality of fragments to one or more remote second endpoints and receiving the quantum mechanical energies or electronic structures from the second one or more remote endpoints. In some embodiments, the method further comprises transmitting the report to the client-side library. In some embodiments, at least one of the second remote endpoints comprises a non-classical computer. In some embodiments, the one or more remote endpoints comprise portions of a cloud computing system.
In another aspect, a system for performing a quantum mechanical energy or electronic structure calculation for a chemical system may comprise: computer memory comprising instructions for performing the quantum mechanical energy or electronic structure calculation for the chemical system; and a hybrid computing unit operatively coupled to the memory, wherein the hybrid computing unit comprises a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, wherein the hybrid computing unit is configured to execute the instructions to at least: (a) decompose at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determine quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combine the quantum mechanical energies or electronic structures determined in (b); and (d) electronically output a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In another aspect, a non-transitory computer readable medium may comprise machine-executable code that upon execution by a hybrid computing unit comprising a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, implements a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the method comprising: (a) decomposing at least one conformation within an ensemble of conformations of the chemical system into a plurality of molecular fragments; (b) determining quantum mechanical energies or electronic structures of at least a subset of the plurality of molecular fragments; (c) combining the quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of the quantum mechanical energies or electronic structures combined in (c).
In another aspect, a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The method may be implemented by a hybrid computing unit comprising at least one classical computer and a distributed computing system comprising a plurality of non-classical computers. The method may comprise: (a) decomposing at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determining, using said hybrid computing unit, quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combining said quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of said quantum mechanical energies or electronic structures combined in (c).
In some embodiments, said plurality of non-classical computers comprises at least one quantum computer. In some embodiments, said at least one quantum computer comprises one or more members selected from the group consisting of: a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, said plurality of non-classical computers comprises different types of non-classical computers. In some embodiments, a quantum mechanical energy of said quantum mechanical energies comprises nuclear-nuclear repulsion energy. In some embodiments, the method further comprises providing an input to said hybrid computing unit, said input comprising a set of atomic coordinates for said chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within said ensemble of conformations of said chemical system. In some embodiments, the method further comprises sorting said combined quantum mechanical energies or electronic structures of said at least said subset of said plurality of molecular fragments.
In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments. In some embodiments, (b) comprises: determining a fermionic Hamiltonian of a molecular fragment of said at least said subset of said plurality of molecular fragments; transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming said qubit Hamiltonian into a quantum circuit; and determining, using said quantum circuit, a quantum mechanical energy or electronic structure of said molecular fragment. In some embodiments, the method further comprises determining said quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining said quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing an ab initio molecular dynamics (AIMD) simulation of said chemical system. In some embodiments, said AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, said indication comprising coordinates of each particle of a plurality of particles in said chemical system and velocities of each particle in said chemical system; and subsequent to (c): (i) determining, from said combined energy or electronic structure, a force on each particle in said chemical system; (ii) updating said coordinates of said each particle in said chemical system and said velocities of said each particle in said chemical system; and (iii) electronically outputting a report indicative of said coordinates or said velocities. In some embodiments, (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to said quantum mechanical energy or electronic structure. In some embodiments, (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
In some embodiments, the method further comprises dispatching one or more of said plurality of fragments to one or more remote endpoints and receiving said quantum mechanical energies or electronic structures from said one or more remote endpoints. In some embodiments, at least one of said one or more remote endpoints comprises a non-classical computer. In some embodiments, said one or more remote endpoints comprise portions of a cloud computing system. In some embodiments, the method further comprises, prior to (a), receiving said at least one conformation from a client-side library and dispatching said at least one conformation to a first remote endpoint. In some embodiments, at least one of (a) and (c) occur at said first remote endpoint.
In some embodiments, the method further comprises dispatching one or more of said plurality of fragments to one or more remote second endpoints and receiving said quantum mechanical energies or electronic structures from said second one or more remote endpoints. In some embodiments, the method further comprises transmitting said report to said client-side library. In some embodiments, at least one of said second remote endpoints comprises a non-classical computer. In some embodiments, said one or more remote endpoints comprise portions of a cloud computing system. In some embodiments, said decomposing in (a) is performed using said at least one classical computer. In some embodiments, said determining in (b) is performed using at least one non-classical computer of said plurality of non-classical computers. In some embodiments, said combining in (c) is performed using said at least one classical computer.
In another aspect a system for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The system may comprise: a hybrid computing unit operatively coupled to said memory, wherein said hybrid computing unit comprises at least one classical computer and a distributed computing system comprising a plurality of non-classical computers, wherein said hybrid computing unit is configured to at least: (a) decompose at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determine quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combine said quantum mechanical energies or electronic structures determined in (b); and (d) electronically output a report indicative of said quantum mechanical energies or electronic structures combined in (c).
In some embodiments, the system further comprises computer memory comprising instructions for performing said quantum mechanical energy or electronic structure calculation for said chemical system, wherein said hybrid computing unit is configured to implement said instructions to perform at least (a)-(d).
In another aspect, a non-transitory computer readable medium comprising machine-executable code that upon execution by a hybrid computing unit comprising at least one classical computer and a distributed computing system comprising a plurality of non-classical computers, implements a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The method may comprise: (a) decomposing at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determining quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combining said quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of said quantum mechanical energies or electronic structures combined in (c).
In another aspect, a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The method may be implemented by a hybrid computing unit comprising a distributed computing system comprising a plurality of classical computers and at least one non-classical computer. The method may comprise: (a) decomposing at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determining, using said hybrid computing unit, quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combining said quantum mechanical energies or electronic structures determined in (b); and (d) electronically outputting a report indicative of said quantum mechanical energies or electronic structures combined in (c).
In some embodiments, said at least one non-classical computer comprises at least one quantum computer. In some embodiments, said at least one quantum computer comprises one or more members selected from the group consisting of: a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, said at least one non-classical computer comprises a plurality of different types of non-classical computers. In some embodiments, an energy of said quantum mechanical energies comprises nuclear-nuclear repulsion energy. In some embodiments, the method further comprises providing an input to said hybrid computing unit, said input comprising a set of atomic coordinates for said chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within said ensemble of conformations of said chemical system. In some embodiments, the method further comprises sorting said combined quantum mechanical energies or electronic structures of said at least said subset of said plurality of molecular fragments.
In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
In some embodiments, (b) comprises: (i) determining a fermionic Hamiltonian of a molecular fragment of said at least said subset of said plurality of molecular fragments; (ii) transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian; (iii) transforming said qubit Hamiltonian into a quantum circuit; and (iv) determining, using said quantum circuit, a quantum mechanical energy or electronic structure of said molecular fragment. In some embodiments, the method further comprises determining said quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining said quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing an ab initio molecular dynamics (AIMD) simulation of said chemical system. In some embodiments, said AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, said indication comprising coordinates of each particle of a plurality of particles in said chemical system and velocities of each particle in said chemical system; and subsequent to (c): (i) determining, from said combined energy or electronic structure, a force on each particle in said chemical system; (ii) updating said coordinates of said each particle in said chemical system and said velocities of said each particle in said chemical system; and (iii) electronically outputting a report indicative of said coordinates or said velocities. In some embodiments, (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to said quantum mechanical energy or electronic structure. In some embodiments, (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
In some embodiments, the method further comprises dispatching one or more of said plurality of fragments to one or more remote endpoints and receiving said quantum mechanical energies or electronic structures from said one or more remote endpoints. In some embodiments, at least one of said one or more remote endpoints comprises a non-classical computer. In some embodiments, said one or more remote endpoints comprise portions of a cloud computing system.
In some embodiments, the method further comprises, prior to (a), receiving said at least one conformation from a client-side library and dispatching said at least one conformation to a first remote endpoint. In some embodiments, at least one of (a) and (c) occur at said first remote endpoint. In some embodiments, the method further comprises dispatching one or more of said plurality of fragments to one or more remote second endpoints and receiving said quantum mechanical energies or electronic structures from said second one or more remote endpoints. In some embodiments, the method further comprises transmitting said report to said client-side library. In some embodiments, at least one of said second remote endpoints comprises a non-classical computer. In some embodiments, said one or more remote endpoints comprise portions of a cloud computing system.
In some embodiments, said decomposing in (a) is performed using at least one classical computer of said plurality of classical computers. In some embodiments, said determining in (b) is performed using said at least one non-classical computer. In some embodiments, said combining in (c) is performed using at least one classical computer of said plurality of classical computers.
In another aspect, a system for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The system may comprise: a hybrid computing unit operatively coupled to said memory, wherein said hybrid computing unit comprises a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, wherein said hybrid computing unit is configured to at least: (a) decompose at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determine quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combine said quantum mechanical energies or electronic structures determined in (b); and (d) electronically output a report indicative of said quantum mechanical energies or electronic structures combined in (c).
In some embodiments, the system further comprises computer memory comprising instructions for performing said quantum mechanical energy or electronic structure calculation for said chemical system, wherein said hybrid computing unit is configured to implement said instructions to perform at least (a)-(d).
In another aspect, a non-transitory computer readable medium comprising machine-executable code that upon execution by a hybrid computing unit comprising a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, implements a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The method may comprise: (a) decomposing at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determining quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combining said quantum mechanical energies or electronic structures determined in (d); and (d) electronically outputting a report indicative of said quantum mechanical energies or electronic structures combined in (c).
In another aspect, a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The method may be implemented by a hybrid computing unit comprising at least one classical computer and a distributed computing system comprising a plurality of non-classical computers. The method may comprise: (a) decomposing at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) dispatching a subset of the plurality of molecular fragments to a plurality of solvers; (c) determining, using said plurality of solvers, quantum mechanical energies or electronic structures of a plurality of molecular fragments of said subset of said plurality of molecular fragments; and (d) electronically outputting a report indicative of said quantum mechanical energies or electronic structures determined in (c).
In some embodiments, said plurality of non-classical computers comprises at least one quantum computer. In some embodiments, said at least one quantum computer comprises one or more members selected from the group consisting of: a quantum hardware device and a classical simulator of a quantum circuit. In some embodiments, said plurality of non-classical computers comprises different types of non-classical computers. In some embodiments, a quantum mechanical energy of said quantum mechanical energies comprises nuclear-nuclear repulsion energy. In some embodiments, the method further comprises: providing an input to said hybrid computing unit, said input comprising a set of atomic coordinates for said chemical system. In some embodiments, the method further comprises performing (a)-(c) for two or more conformations within said ensemble of conformations of said chemical system. In some embodiments, the method further comprises said combined quantum mechanical energies or electronic structures of said at least said subset of said plurality of molecular fragments. In some embodiments, (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
In some embodiments, (c) comprises: determining a fermionic Hamiltonian of a molecular fragment of said plurality of molecular fragments; transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming said qubit Hamiltonian into a quantum circuit; and determining, using said quantum circuit, a quantum mechanical energy or electronic structure of said molecular fragment. In some embodiments, the method further comprises determining said quantum mechanical energy or electronic structure using a molecular Hamiltonian. In some embodiments, the method further comprises determining said quantum mechanical energy or electronic structure using an electronic Hamiltonian. In some embodiments, transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
In some embodiments, the method further comprises performing an ab initio molecular dynamics (AIMD) simulation of said chemical system. In some embodiments, said AIMD simulation comprises: prior to (a), obtaining an indication of a chemical system, said indication comprising coordinates of each particle of a plurality of particles in said chemical system and velocities of each particle in said chemical system; and subsequent to (c): (i) determining, from said combined energy or electronic structure, a force on each particle in said chemical system; (ii) updating said coordinates of said each particle in said chemical system and said velocities of said each particle in said chemical system; and (iii) electronically outputting a report indicative of said coordinates or said velocities. In some embodiments, (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to said quantum mechanical energy or electronic structure. In some embodiments, (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
In some embodiments, said plurality of solvers comprises one or more remote endpoints. In some embodiments, the method further comprises receiving said quantum mechanical energies or electronic structures from said one or more remote endpoints. In some embodiments, at least one of said one or more remote endpoints comprises a non-classical computer. In some embodiments, said one or more remote endpoints comprise portions of a cloud computing system.
In some embodiments, the method further comprises, prior to (a), receiving said at least one conformation from a client-side library and dispatching said at least one conformation to a first remote endpoint. In some embodiments, at least one of (a) and (c) occur at said first remote endpoint. In some embodiments, the method further comprises dispatching one or more of said plurality of fragments to one or more remote second endpoints and receiving said quantum mechanical energies or electronic structures from said second one or more remote endpoints. In some embodiments, the method further comprises transmitting said report to said client-side library. In some embodiments, at least one of said second remote endpoints comprises a non-classical computer. In some embodiments, said one or more remote endpoints comprises portions of a cloud computing system.
In some embodiments, said decomposing in (a) is performed using said at least one classical computer. In some embodiments, said dispatching in (b) is preformed using said at least one classical computer. In some embodiments, said dispatching in (b) is preformed using a classical computer remote from said at least one classical computer. In some embodiments, said determining in (c) is performed using at least one non-classical computer of said plurality of non-classical computers. In some embodiments, said outputting in (d) is performed using said at least one classical computer.
In another aspect, a system for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The system may comprise: a hybrid computing unit operatively coupled to said memory, wherein said hybrid computing unit comprises a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, wherein said hybrid computing unit is configured to at least: (a) decompose at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) dispatch a subset of the plurality of molecular fragments to a plurality of solvers; (c) determine, using said plurality of solvers, quantum mechanical energies or electronic structures of a plurality of molecular fragments of said subset of said plurality of molecular fragments; and (d) electronically output a report indicative of said quantum mechanical energies or electronic structures determined in (c). In some embodiments, the system further comprises: computer memory comprising instructions for performing said quantum mechanical energy or electronic structure calculation for said chemical system, wherein said hybrid computing unit is configured to implement said instructions to perform at least (a)-(d).
In another aspect, a non-transitory computer readable medium comprising machine-executable code that upon execution by a hybrid computing unit comprising a distributed computing system comprising a plurality of classical computers and at least one non-classical computer, implements a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system is provided. The method may comprise: (a) decomposing at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) determining quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (c) combining said quantum mechanical energies or electronic structures determined in (d); and (d) electronically outputting a report indicative of said quantum mechanical energies or electronic structures combined in (c).
Another aspect of the present disclosure provides a non-transitory computer readable medium comprising machine executable code that, upon execution by one or more computer processors, implements any of the methods above or elsewhere herein.
Another aspect of the present disclosure provides a system comprising one or more computer processors and computer memory coupled thereto. The computer memory comprises machine executable code that, upon execution by the one or more computer processors, implements any of the methods above or elsewhere herein.
Additional aspects and advantages of the present disclosure will become readily apparent to those skilled in this art from the following detailed description, wherein only illustrative embodiments of the present disclosure are shown and described. As will be realized, the present disclosure is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the disclosure. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.
INCORPORATION BY REFERENCE
All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. To the extent publications and patents or patent applications incorporated by reference contradict the disclosure contained in the specification, the specification is intended to supersede and/or take precedence over any such contradictory material.
BRIEF DESCRIPTION OF THE DRAWINGS
The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings (also âFigureâ and âFIG.â herein), of which:
FIG. 1 illustrates a flowchart for an example of a method for providing an indication of a sorted list of conformers of a molecule using problem decomposition techniques on quantum computing hardware, in accordance with some embodiments disclosed herein.
FIG. 2 illustrates a flowchart for an example of a method for providing an indication of the quantum mechanical energy and/or electronic structure of a subsystem, which is defined by problem decomposition techniques, on quantum computing hardware, in accordance with some embodiments disclosed herein.
FIG. 3 illustrates a flowchart for an example of a method for providing an indication of the expectation value of the Hamiltonian, on quantum computing hardware, in accordance with some embodiments disclosed herein.
FIG. 4 is an example illustration of n-heptane, where the dotted lines indicate the bond detached atom in the fragment molecular orbital (FMO) fragmentation.
FIG. 5 is an example illustration of n-heptane, showing comparisons between results obtained by exact CCSD and divide-and-conquer CCSD (DC-CCSD), and between results obtained by exact CCSD and fragment molecular orbital CCSD (FMO-CCSD).
FIG. 6 is an example illustration of n-heptane, showing the minimal sphere (dotted circle) to accommodate the conformer, and the distance (solid line) between the end carbon-atoms involved in a dihedral angle (1-4 distance) [left]; a plot showing the relation between the total quantum mechanical energy (left arrow) and the diameter of the minimal sphere (right arrow) for each of the conformers, which are sorted based on the total quantum mechanical energy [middle]; and a plot showing the relation between the total quantum mechanical energy (left arrow) and the smallest 1-4 distance (right arrow) for each conformer [right].
FIG. 7 is an example illustration of 3-methylheptane, where the dotted lines indicate the bond detached atoms in the fragment molecular orbital (FMO) fragmentation.
FIG. 8 illustrates the quantum mechanical energy distribution for n-heptane (blue) and 3-methylheptane (red).
FIG. 9 is an example illustration of 3-methylheptane, showing comparisons between results obtained by exact CCSD and divide-and-conquer CCSD (DC-CCSD), and between results obtained by exact CCSD and fragment molecular orbital CCSD (FMO-CCSD).
FIG. 10 illustrates a computer control system that is programmed or otherwise configured to implement methods provided herein.
FIG. 11 illustrates a flowchart for an example of a method of increments for performing problem decomposition.
FIG. 12 illustrates molecular orbitals, atoms, molecular fragments, and molecules used as bases for the method of increments.
FIG. 13 illustrates a flowchart for an example of a method for performing ab initio molecular dynamics (AIMD) on a molecule using problem decomposition techniques on quantum computing hardware, in accordance with some embodiments disclosed herein.
FIG. 14 illustrates a flowchart for an example of a method for calculating the force on each particle of a system in an ab initio molecular dynamics (AIMD) simulation, in accordance with some embodiments disclosed herein.
FIG. 15 illustrates examples of systems or combinations of systems that may be used to solve a problem, such as a quantum chemistry problem or simulation.
FIG. 16 illustrates a flowchart for an example of a method for performing a quantum mechanical energy or electronic structure calculation for a chemical system using a distributed computing system.
FIG. 17 illustrates an example of an architecture for a distributed computing system comprising a non-classical (e.g., quantum computer) and a plurality of classical computers.
FIG. 18 illustrates a distributed computing system comprising a sequential problem decomposition, in accordance with some embodiments disclosed herein.
FIG. 19 illustrates a distributed computing system comprising a problem dispatch, in accordance with some embodiments disclosed herein.
FIG. 20 illustrates an example architecture of a distributed computing system comprising a problem dispatch within a client-side library, in accordance with some embodiments disclosed herein.
FIG. 21 illustrates an example architecture of a distributed computing system comprising a problem dispatch at a remote endpoint, in accordance with some embodiments disclosed herein.
DETAILED DESCRIPTION
While various embodiments of the invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments ar
CLAIMS
Claims ( 17 )
What is claimed is:
1 . A method for performing a quantum mechanical energy or electronic structure calculation for a chemical system, said method being implemented by a distributed computing system comprising at least three computers, wherein the at least three computers comprises a central classical computer and multiple electronic structure solvers, each electronic structure solver implementing one or more respective electronic structure solver types, each electronic structure solver type being defined by an algorithmic method, a hardware configuration, or both, the electronic structure solvers comprising quantum computing systems, non-classical computing systems, or hybrid computing units, said method comprising:
(a) decomposing, at the central classical computer, at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) generating, at the central classical computer and for each of one or more of said plurality of molecular fragments, a respective data structure for the molecular fragment, wherein the data structure specifies (i) a specification of the molecular fragment, (ii) an electronic structure solver type and (iii) solver parameters to be passed to an electronic structure solver of the specified type, the solver parameters comprising a hardware backend type and ansatz type to be used by the electronic structure solver of the specified type to determine quantum mechanical energies or electronic structures for the molecular fragment; (c) identifying, at the central classical computer and for each of the one or more of said plurality of molecular fragments, an electronic structure solver included in the distributed computing system dedicated to the type specified in the data structure for the molecular fragment: (d) dispatching the one or more of said plurality of molecular fragments and respective data structures from the central classical computer to the electronic structure solvers included in the distributed computing system of the types specified in the respective data structures; (e) determining, by the electronic structure solvers included in the distributed system of the types specified in the respective data structures, using the hardware backend types specified in the respective data structures and according to the solver parameters in the respective data structures, quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (f) combining, at the central classical computer said quantum mechanical energies or electronic structures determined in (e); and (g) electronically outputting a report indicative of said quantum mechanical energies or electronic structures combined in (f).
2 . The method of claim 1 , wherein the non-classical computers comprise at least one Hitachi Ising solver or a coherent Ising machine based on optical parameters and wherein the quantum computer systems comprise one or more members selected from the group consisting of: a quantum hardware device and a classical simulator of a quantum circuit.
3 . The method of claim 1 , wherein a quantum mechanical energy of said quantum mechanical energies comprises nuclear-nuclear repulsion energy.
4 . The method of claim 1 , further comprising providing an input to said central classical computer, said input comprising a set of atomic coordinates for said chemical system.
5 . The method of claim 1 , further comprising performing (a)-(f) for two or more conformations within said ensemble of conformations of said chemical system.
6 . The method of claim 1 , wherein (a) comprises applying one or more members selected from the group consisting of: a fragment molecular orbital (FMO) method, a divide-and-conquer (DC) method, a density matrix embedding theory (DMET) method, a density matrix renormalization group (DMRG) method, a tensor network, and a method of increments.
7 . The method of claim 1 , wherein (e) comprises: determining a fermionic Hamiltonian of a molecular fragment of said at least said subset of said plurality of molecular fragments; transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian; transforming said qubit Hamiltonian into a quantum circuit; and determining, using said quantum circuit, a quantum mechanical energy or electronic structure of said molecular fragment.
8 . The method of claim 7 , further comprising determining said quantum mechanical energy or electronic structure using one or more members selected from the group consisting of: a molecular Hamiltonian and an electronic Hamiltonian.
9 . The method of claim 7 , wherein transforming said fermionic Hamiltonian into an equivalent qubit Hamiltonian comprises transforming a fermionic operator of a Hamiltonian to a qubit operator.
10 . The method of claim 1 , further comprising, based on the quantum mechanical energies or electronic structures combined in (f), performing an ab initio molecular dynamics (AIMD) simulation of said chemical system.
11 . The method of claim 10 , wherein said AIMD simulation comprises:
prior to (a), obtaining an indication of a chemical system, said indication comprising coordinates of each particle of a plurality of particles in said chemical system and velocities of each particle in said chemical system; and subsequent to (f): (i) determining, from said combined energy or electronic structure, a force on each particle in said chemical system; (ii) updating said coordinates of said each particle in said chemical system and said velocities of said each particle in said chemical system; and (iii) electronically outputting a report indicative of said coordinates or said velocities.
12 . The method of claim 11 , wherein (i) comprises applying Jordan's quantum algorithm for numerical gradient estimation to said quantum mechanical energy or electronic structure.
13 . The method of claim 11 , wherein (ii) comprises applying one or more members selected from the group consisting of: a Verlet procedure, a velocity Verlet procedure, symplectic integration, Runge-Kutta integration, and Beeman integration.
14 . The method of claim 1 , further comprising dispatching one or more of said plurality of fragments to one or more remote endpoints and receiving said quantum mechanical energies or electronic structures from said one or more remote endpoints, wherein said one or more remote endpoints comprise portions of a cloud computing system.
15 . The method of claim 14 , wherein at least one of said one or more remote endpoints comprises a non-classical computer.
16 . The method of claim 1 , further comprising, prior to (a), receiving said at least one conformation from a client-side library and dispatching said at least one conformation to a first remote endpoint, dispatching one or more of said plurality of fragments to one or more remote second endpoints and receiving said quantum mechanical energies or electronic structures from said second one or more remote endpoints, and transmitting said report to said client-side library, and wherein at least one of (a) and (f) occur at said first remote endpoint.
17 . A distributed computing system for performing a quantum mechanical energy or electronic structure calculation for a chemical system, the distributed computing system comprising a central classical computer operatively coupled to a memory, said memory comprising instructions for performing a quantum mechanical energy or electronic structure calculation for a chemical system, wherein the distributed computing system further comprises multiple electronic structure solvers, each electronic structure solver implementing one or more respective electronic structure solver types, each electronic structure solver type being defined by an algorithmic method, a hardware configuration, or both, the electronic structure solvers comprising quantum computing systems, non-classical computing systems, or hybrid computing units, wherein said distributed computing system is configured to at least:
(a) decompose, at the central classical computer, at least one conformation within an ensemble of conformations of said chemical system into a plurality of molecular fragments; (b) generate, at the central classical computer and for each of one or more of said plurality of molecular fragments, a respective data structure for the molecular fragment, wherein the data structure specifies (i) a specification of the molecular fragment, (ii) an electronic structure solver type and (iii) solver parameters to be passed to an electronic structure solver of the specified type, the solver parameters comprising a hardware backend type and ansatz type to be used by the electronic structure solver of the specified type to determine quantum mechanical energies or electronic structures for the molecular fragment; (c) identify, at the central classical computer and for each of the one or more of said plurality of molecular fragments, an electronic structure solver included in the distributed computing system of the type specified in the data structure for the molecular fragment; (d) dispatch the one or more of said plurality of molecular fragments and respective data structures to electronic structure solvers included in the distributed computing system of the types specified in the respective data structures; (e) determine, by the electronic structure solvers included in the distributed system of the types specified in the respective data structures, using the hardware backend types specified in the respective data structures and according to the solver parameters in the respective data structures, quantum mechanical energies or electronic structures of at least a subset of said plurality of molecular fragments; (f) combine said quantum mechanical energies or electronic structures determined in (e); and (g) electronically output a report indicative of said quantum mechanical energies or electronic structures combined in (f).
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US11797641B2
( en )
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2023-10-24
1Qb Information Technologies Inc.
Method and system for solving the lagrangian dual of a constrained binary quadratic programming problem using a quantum annealer
CA2881033C
( en )
2015-02-03
2016-03-15
1Qb Information Technologies Inc.
Method and system for solving lagrangian dual of a constrained binary quadratic programming problem
WO2019104443A1
( en )
2017-12-01
2019-06-06
1Qb Information Technologies Inc.
Systems and methods for stochastic optimization of a robust inference problem
EP3891668A4
( en )
2018-12-06
2023-01-25
1QB Information Technologies Inc.
QUANTUM COMPUTING CONTROLLED BY ARTIFICIAL INTELLIGENCE
WO2020227825A1
( en )
2019-05-13
2020-11-19
1Qb Information Technologies Inc.
Methods and systems for quantum computing enabled molecular ab initio simulations
WO2020255076A1
( en )
2019-06-19
2020-12-24
1Qb Information Technologies Inc.
Method and system for mapping a dataset from a hilbert space of a given dimension to a hilbert space of a different dimension
CA3157216A1
( en )
2019-12-03
2021-06-10
Pooya Ronagh
System and method for enabling an access to a physics-inspired computer and to a physics-inspired computer simulator
CA3179781A1
( en )
2020-05-27
2021-12-02
Silvan Shiwa KUTTIMALAI
Methods and systems for solving an optimization problem using a flexible modular approach
US20220414513A1
( en )
*
2021-06-23
2022-12-29
IonQ, Inc.
Accelerated molecular dynamics simulation method on a quantum-classical hybrid computing system
CN114627971B
( en )
*
2022-03-18
2023-10-31
å京æç«¹å± ç½ç»ææ¯æéå ¬å¸
Data processing methods and devices for solid systems
KR102758771B1
( en )
*
2022-04-28
2025-01-23
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Electronic Structure Calculation of Material using Quantum Computing
JP2025520058A
( en )
*
2022-05-22
2025-07-01
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Hybrid quantum-classical simulation of chemical systems
US20230377693A1
( en )
*
2022-05-22
2023-11-23
Cambridge Quantum Computing Limited
Hybrid quantum-classical computing simulation of chemical systems
EP4290420A1
( en )
*
2022-06-08
2023-12-13
Molecular Quantum Solutions ApS
Method of performing a quantum computation
CN115329965B
( en )
*
2022-08-16
2025-08-01
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Data processing method and electronic equipment
CN115169565B
( en )
*
2022-09-09
2023-01-24
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A Hamiltonian simulation method and device for a small molecule chemical system
CN115527629B
( en )
*
2022-09-29
2025-07-18
å京æç«¹å± ç½ç»ææ¯æéå ¬å¸
Data processing method and device for quantum chemical system
CN117079738B
( en )
*
2022-10-24
2024-07-09
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A comprehensive calculation method for molecular binding energy based on quantum computing
US11862295B1
( en )
*
2022-11-08
2024-01-02
United Arab Emirates University
Method of classifying conformers
CN116739101B
( en )
*
2023-06-27
2024-07-26
å¤æ¦å¤§å¦
Quantum optimization method and device
US12176075B1
( en )
2023-11-14
2024-12-24
United Arab Emirates University
Method of matching conformers of different molecules
Citations (171)
* Cited by examiner, â Cited by third party
Publication number
Priority date
Publication date
Assignee
Title
US20030005068A1
( en )
2000-12-28
2003-01-02
Nickel Ronald H.
System and method for creating a virtual supercomputer using computers working collaboratively in parallel and uses for the same
US20030121028A1
( en )
2001-12-22
2003-06-26
Michael Coury
Quantum computing integrated development environment
JP2004503011A
( en )
2000-07-05
2004-01-29
ã¢ã¼ã³ã¹ããï¼ãã¤ã³ã°ãã¨ã«ã¨ã«ãã¼
Method and apparatus for providing computer services
US6811771B1
( en )
1999-04-27
2004-11-02
Ebara Corporation
Bactericidal organic polymeric material
US20040254735A1
( en )
*
2003-06-13
2004-12-16
Horn Hans Werner
Method of performing three-dimensional molecular superposition and similarity searches in databases of flexible molecules
US20040267916A1
( en )
2003-06-25
2004-12-30
International Business Machines Corporation
Method for improving performance in a computer storage system by regulating resource requests from clients
US20050027458A1
( en )
2003-05-13
2005-02-03
Merz Kenneth M.
Quantum mechanics based method for scoring protein-ligand interactions
US20050182614A1
( en )
2004-02-12
2005-08-18
Microsoft Corporation
Systems and methods that facilitate quantum computer simulation
US20050187844A1
( en )
2004-02-20
2005-08-25
Kete Charles Chalermkraivuth
Systems and methods for multi-objective portfolio optimization
US20050250651A1
( en )
2004-03-29
2005-11-10
Amin Mohammad H S
Adiabatic quantum computation with superconducting qubits
US20050273306A1
( en )
2001-12-22
2005-12-08
Hilton Jeremy P
Hybrid classical-quantum computer architecture for molecular modeling
WO2005122052A1
( en )
2004-06-05
2005-12-22
D-Wave Systems, Inc.
Hybrid classical-quantum computer architecture for molecular modeling
JP2006061926A
( en )
2004-08-25
2006-03-09
Shoei Insatsu Kk
Cutting method by laser beam, laser beam cutting device used for the method, and article manufactured by the method
WO2006026985A2
( en )
2004-07-12
2006-03-16
Atomistix A/S
Method and computer system for quantum chemical modelling of molecules under non-equilibrium conditions
US7113967B2
( en )
2001-05-29
2006-09-26
Magiq Technologies, Inc
Efficient quantum computing operations
US20060225165A1
( en )
2004-12-23
2006-10-05
Maassen Van Den Brink Alec
Analog processor comprising quantum devices
US20060221978A1
( en )
2005-03-31
2006-10-05
Muthaiah Venkatachalam
Backlogged queue manager
US7234144B2
( en )
2002-01-04
2007-06-19
Microsoft Corporation
Methods and system for managing computational resources of a coprocessor in a computing system
US20070180586A1
( en )
2006-01-27
2007-08-02
Amin Mohammad H
Methods of adiabatic quantum computation
WO2007089674A2
( en )
2006-01-27
2007-08-09
The Arizona Board Of Regents, A Body Corporate Acting On Behalf Of Arizona State University
Methods for generating a distribution of optimal solutions to nondeterministic polynomial optimization problems
US20070239366A1
( en )
2004-06-05
2007-10-11
Hilton Jeremy P
Hybrid classical-quantum computer architecture for molecular modeling
US20080186918A1
( en )
2006-12-05
2008-08-07
Qualcomm Incorporated
Method and system for reducing backhaul utilization during base station handoff in wireless networks
US20080215850A1
( en )
2006-12-05
2008-09-04
Berkley Andrew J
Systems, methods and apparatus for local programming of quantum processor elements
US20080218519A1
( en )
2006-11-02
2008-09-11
Michael Coury
Graph embedding techniques
US20080262990A1
( en )
2000-09-25
2008-10-23
Harsh Kapoor
Systems and methods for processing data flows
US20080313430A1
( en )
2007-06-12
2008-12-18
Bunyk Paul I
Method and system for increasing quantum computer processing speed using digital co-processor
US20090070402A1
( en )
2007-09-11
2009-03-12
Geordie Rose
Systems, methods, and apparatus for a distributed network of quantum computers
US20090078932A1
( en )
2007-09-25
2009-03-26
Amin Mohammad H
Systems, devices, and methods for controllably coupling qubits
US20090164435A1
( en )
2007-12-20
2009-06-25
Routt Thomas J
Methods and systems for quantum search, computation and memory
US7619437B2
( en )
2004-12-30
2009-11-17
D-Wave Systems, Inc.
Coupling methods and architectures for information processing
US20090306902A1
( en )
2005-12-20
2009-12-10
Biosolveit Gmbh
Screening Method
US7639035B2
( en )
2005-04-26
2009-12-29
D-Wave Systems, Inc.
Qubit state copying
US20090325694A1
( en )
2008-06-27
2009-12-31
Microsoft Corpration
Macroscopic quantum effects for computer games
US7660533B1
( en )
2004-08-04
2010-02-09
The United States Of America As Represented By The Secretary Of The Army
Quantum Fourier transform based information transmission system and method
JP2010182106A
( en )
2009-02-05
2010-08-19
Toyota Motor Corp
Method of searching liquid repellent capsule, simulation method for predicting liquid repellent property of capsule, and simulation program
US20100261481A1
( en )
2009-04-13
2010-10-14
Resende Mauricio Guilherme De Carvalho
Networks with redundant points of presence using approximation methods and systems
WO2010148120A2
( en )
2009-06-17
2010-12-23
D-Wave Systems Inc.
Systems and methods for solving computational problems
US7898282B2
( en )
2005-04-26
2011-03-01
D-Wave Systems Inc.
Systems, devices, and methods for controllably coupling qubits
US20110238378A1
( en )
2007-12-12
2011-09-29
Allen Edward H
Computer systems and methods for quantum verification and validation
US20110238855A1
( en )
2000-09-25
2011-09-29
Yevgeny Korsunsky
Processing data flows with a data flow processor
US20110296229A1
( en )
2010-05-28
2011-12-01
International Business Machines Corporation
Decimal floating-pointing quantum exception detection
US20120072579A1
( en )
2010-09-17
2012-03-22
Microsoft Corporation
Monitoring cloud-runtime operations
US20120084242A1
( en )
2010-10-04
2012-04-05
Mind Over Matter Ai, Llc.
Coupling of rational agents to quantum processes
JP2012083427A
( en )
2010-10-07
2012-04-26
Osaka Prefecture Univ
Method for controlling transmission of light energy between nano substances, and method and apparatus for evaluating transmission efficiency of light energy between nano substances
US8175995B2
( en )
2008-06-10
2012-05-08
D-Wave Systems Inc.
Quantum and digital processor hybrid systems and methods to solve problems
US8195596B2
( en )
2007-01-12
2012-06-05
D-Wave Systems Inc.
Systems, devices, and methods for interconnected processor topology
US8195726B2
( en )
2006-06-20
2012-06-05
D-Wave Systems Inc.
Systems, devices, and methods for solving computational problems
US20120159506A1
( en )
2010-12-20
2012-06-21
Microsoft Corporation
Scheduling and management in a personal datacenter
US8230432B2
( en )
2007-05-24
2012-07-24
International Business Machines Corporation
Defragmenting blocks in a clustered or distributed computing system
US20120240185A1
( en )
2000-09-25
2012-09-20
Harsh Kapoor
Systems and methods for processing data flows
US20120253926A1
( en )
2011-03-31
2012-10-04
Google Inc.
Selective delivery of content items
US20120326720A1
( en )
2011-06-14
2012-12-27
International Business Machines Corporation
Modular array of fixed-coupling quantum systems for quantum information processing
CA2840958A1
( en )
2011-07-06
2013-01-10
D-Wave Systems Inc.
Quantum processor based systems and methods that minimize an objective function
US20130026183A1
( en )
2011-07-27
2013-01-31
Diana Foster
Single use dispenser package
US8421053B2
( en )
2008-03-24
2013-04-16
D-Wave Systems Inc.
Oubit based systems, devices, and methods for analog processing
US20130144925A1
( en )
2011-11-15
2013-06-06
D-Wave Systems Inc.
Systems and methods for solving computational problems
JP2013114366A
( en )
2011-11-28
2013-06-10
Hitachi Ltd
Quantum computer system, control method and program for quantum computer system
US8503885B2
( en )
2004-08-04
2013-08-06
The United States Of America As Represented By The Secretary Of The Army
Quantum based information transmission system and method
US20130263131A1
( en )
2012-03-28
2013-10-03
Joseph S. Beda, III
Global computing interface
US20130308956A1
( en )
2004-08-04
2013-11-21
U.S. Army Research Laboratory ATT: RDRL-LOC-I
Quantum based information transfer system and method
US20130336472A1
( en )
2012-06-19
2013-12-19
Twilio, Inc.
System and method for queuing a communication session
US20140025606A1
( en )
2010-11-19
2014-01-23
William G. Macready
Methods for solving computational problems using a quantum processor
US8655828B2
( en )
2007-04-19
2014-02-18
D-Wave Systems Inc.
Systems, methods, and apparatus for solving problems
US20140122702A1
( en )
2012-10-31
2014-05-01
Elwha Llc
Methods and systems for monitoring and/or managing device data
US20140123325A1
( en )
2012-11-26
2014-05-01
Elwha Llc
Methods and systems for managing data and/or services for devices
US20140214257A1
( en )
2013-01-25
2014-07-31
D-Wave Systems Inc.
Systems and methods for real-time quantum computer-based control of mobile systems
US20140250288A1
( en )
2012-12-18
2014-09-04
D-Wave Systems Inc.
Systems and methods that formulate embeddings of problems for solving by a quantum processor
US20140258730A1
( en )
2013-03-08
2014-09-11
Martin Stecher
Data protection using programmatically generated key pairs from a master key and a descriptor
US20140324933A1
( en )
2012-12-18
2014-10-30
D-Wave Systems Inc.
Systems and methods that formulate problems for solving by a quantum processor using hardware graph decomposition
US20140337612A1
( en )
2013-04-12
2014-11-13
D-Wave Systems Inc
Systems and methods for interacting with a quantum computing system
US20140344322A1
( en )
2013-05-17
2014-11-20
D-Wave Systems Inc.
Quantum processor based systems and methods that minimize a continuous variable objective function
US20140379924A1
( en )
2013-06-21
2014-12-25
Microsoft Corporation
Dynamic allocation of resources while considering resource reservations
WO2014210368A1
( en )
2013-06-28
2014-12-31
D-Wave Systems Inc.
Systems and methods for quantum processing of data
WO2015006494A1
( en )
2013-07-09
2015-01-15
Board Of Trustees Of The Leland Stanford Junior University
Computation using a network of optical parametric oscillators
US20150032993A1
( en )
2013-07-23
2015-01-29
D-Wave Systems Inc.
Systems and methods for achieving orthogonal control of non-orthogonal qubit parameters
US20150032991A1
( en )
2013-07-24
2015-01-29
D-Wave Systems Inc.
Systems and methods for increasing the energy scale of a quantum processor
US20150055961A1
( en )
2004-08-04
2015-02-26
U.S. Army Research Laboratory
System and method for quantum based information transfer
CA2881033A1
( en )
2015-02-03
2015-04-06
1Qb Information Technologies Inc.
Method and system for solving lagrangian dual of a constrained binary quadratic programming problem
US20150111754A1
( en )
2013-10-22
2015-04-23
D-Wave Systems Inc.
Universal adiabatic quantum computing with superconducting qubits
US20150120555A1
( en )
2013-10-29
2015-04-30
Elwha Llc
Exchange authorization analysis infused with network-acquired data stream information
WO2015060915A2
( en )
2013-07-29
2015-04-30
President And Fellows Of Harvard College
Quantum processor problem compilation
US20150120551A1
( en )
2013-10-29
2015-04-30
Elwha LLC, a limited liability corporation of the State of Delaware
Mobile device-facilitated guaranty provisioning
US20150142398A1
( en )
*
2013-11-20
2015-05-21
California Institute Of Technology
Methods for a multi-scale description of the electronic structure of molecular systems and materials and related applications
US20150169746A1
( en )
2008-07-24
2015-06-18
Hamid Hatami-Hanza
Ontological Subjects Of A Universe And Knowledge Processing Thereof
US20150178349A1
( en )
2013-12-19
2015-06-25
Mimecast North America Inc.
Displaying messages relevant to system administration
US20150193692A1
( en )
2013-11-19
2015-07-09
D-Wave Systems Inc.
Systems and methods of finding quantum binary optimization problems
US20150205759A1
( en )
2013-11-19
2015-07-23
D-Wave Systems Inc.
Systems and methods for finding quantum binary optimization problems
US20150220852A1
( en )
2008-07-24
2015-08-06
Hamid Hatami-Hanza
Assisted Knowledge discovery and publication system and method
US20150227559A1
( en )
2007-07-26
2015-08-13
Dr. Hamid Hatami-Hanza
Methods and systems for investigation of compositions of ontological subjects
WO2015121619A2
( en )
2014-02-14
2015-08-20
The University Court Of The University Of Edinburgh
Client-server communication system
US20150262074A1
( en )
2014-03-12
2015-09-17
Temporal Defense Systems, Llc
Solving digital logic constraint problems via adiabatic quantum computation
US20150269124A1
( en )
2013-12-05
2015-09-24
D-Wave Systems Inc.