8 results about "Solution state" patented technology

Systems, methods, computer-readable media, and techniques disclosed herein provide for preparing a solution to a problem comprising a constraint on a non-classical computer, comprising: (a) providing a state preparation operation, wherein the state preparation operation comprises at least a portion of an implementation of the problem comprising the constraint on the non-classical computer, wherein the state preparation operation is configured to evolve a quantum register to a solution state; (b) applying a constraint detection operation, the constraint detection operation comprising entangling an ancilla qubit with a set of data qubits; and (c) measuring the ancilla qubit to determine whether a constraint of the problem is satisfied.

A one-piece thermoforming process for lip edges reduces the risk of thinning and cracking in the finished product. The process includes providing a mold, comprising a punch and a die, the punch being designed according to the inner surface shape of the lip edge, and the die being designed according to the outer surface of the lip edge; selecting an annular blank; heating the blank to 20°C-40°C below the solution state and holding it at that temperature; transferring the blank to the die, where the punch pre-stamps the blank until the pre-stamping position is reached, forming a shallow cavity structure for the lip edge, i.e., the initial blank; removing the initial blank, heating it to the solution state and holding it at that temperature; transferring the initial blank to the die, where the punch performs a second stamping operation until the pre-stamping position is reached, forming a deep cavity structure for the lip edge, i.e., the final blank; and machining the final blank to the finished product dimensions.

In an example, a pre-solution state and other attributes of each constraint problem (CP) in a first series of constraint problems (CPs) solved by a constraint solver are recorded during a first simulation run with a first testbench. The recorded attributes are mapped to at least one key value set of a plurality of key value sets. Each key value set uses a different level of generalization to represent the recorded attributes. A matching CP from the first series is determined for each CP in a second series of CPs to be solved during a second simulation run with a second testbench. The matching CP is mapped to a key value set that uses a lower level of generalization to represent the matching CP's recorded attributes relative to other key value sets. A pre-solution state of each CP in the second series is set to that of the matching CP.

The present application relates to a kind of terahertz detection biomolecule chip for solution environment and manufacturing method, by being equipped with the nanometer hole of aperture uniformity in inner cavity, after being powered on to biomolecule chip, the biological macromolecule existing in biological solution can move from other positions in inner cavity to the end where nanometer hole is located.Different biological macromolecule selects different aperture nanometer hole nanometer hole, and single biological macromolecule in conformity with the size of the size of the single biological macromolecule opened by itself is screened, so as to limit and locate single biological macromolecule in nanometer hole, avoid biological macromolecule to experience fast and various conformational transition in biological solution.Compared with prior art, the present application discloses a kind of terahertz detection biomolecule chip for solution environment and manufacturing method, can realize the purpose of in-situ real-time imaging detection of single biological macromolecule in solution state.

In an example, a pre-solution state and other attributes of each constraint problem (CP) in a first series of constraint problems (CPs) solved by a constraint solver are recorded during a first simulation run with a first testbench. The recorded attributes are mapped to at least one key value set of a plurality of key value sets. Each key value set uses a different level of generalization to represent the recorded attributes. A matching CP from the first series is determined for each CP in a second series of CPs to be solved during a second simulation run with a second testbench. The matching CP is mapped to a key value set that uses a lower level of generalization to represent the matching CP's recorded attributes relative to other key value sets. A pre-solution state of each CP in the second series is set to that of the matching CP.

In one example, during a first simulation run with a first test bench, pre-solution states and other attributes of each constraint problem (CP) in a first series of constraint problems (CP) solved by a constraint solver are recorded. The recorded attributes are mapped to at least one key value set of a plurality of key value sets. Each key value set uses a different generalization hierarchy to represent the recorded attributes. A matching CP from the first series is determined for each CP in the second series of CPs to be solved during a second simulation run with the second test bench. Matching CPs are mapped to sets of key values representing the matching CPs using a lower generalization hierarchy relative to recorded attributes of other sets of key values. The pre-solution state of each CP in the second series is set to match the pre-solution state of the CP.

The invention provides a large-scale integer linear programming solving method and system, and belongs to the field of artificial intelligence, and the method comprises the steps: constructing a feasible solution pool according to a to-be-solved integer linear programming problem instance, and determining a current solution; performing iterative optimization on the feasible solution pool and the current solution to obtain an optimized target solution; in each round of iterative optimization, determining a variable selection probability of each decision variable based on a difference between a statistical feature of each feasible solution in a current feasible solution pool and a current solution; according to the current solving state characteristics, determining neighborhood scale parameters of current iteration; and according to the variable selection probability and the neighborhood scale parameter, constructing and solving a sub-problem of the current iteration to obtain a new feasible solution, and updating the feasible solution pool and the current solution. According to the method, the variable selection strategy based on the solution pool statistical characteristics and the neighborhood scale adaptive determination strategy based on the current solution state are combined, so that accurate construction and efficient iterative solution of the sub-problems in the large-scale integer linear programming problem are realized.

The invention discloses an intelligent control method and system for electroplating soft processing. The method comprises the steps that current working condition information and real-time monitoring data of a process tank are obtained; based on the real-time monitoring data, key characteristic parameters used for representing the bath solution state are extracted; based on the current working condition information and the key characteristic parameters, matching is carried out through a preset historical working condition database, and matched initial process parameters are obtained; starting processing according to the initial process parameters, acquiring monitoring data in the process tank at regular time in the processing process, and updating the key characteristic parameters according to the monitoring data; based on the updated key feature parameters, generating optimal process parameters through a preset adaptive process model by taking a preset quality target as a guide; and generating a process parameter adjusting instruction by taking the optimal process parameter as a current process parameter set value. According to the invention, a closed-loop control architecture integrating real-time sensing and dynamic optimization is constructed, so that the consistency and stability of the electroplating soft treatment process can be improved.