Patent ID: 11934918
Assignee: MULTIVERSE COMPUTING S.L.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for quantum classification and operation control, the method including the following steps:
radiating a vacuum chamber comprising an ensemble of neutral atoms with laser configured to trap atoms of the ensemble of neutral atoms in an array of optical tweezers, thereby providing a quantum register, and each optical tweezer comprising a single neutral atom;
digitally configuring, by processing a training dataset with a plurality of vectors about a target where each vector has a historical value for each of N features of the target, a laser controlling function, and digitally reducing, based on the laser controlling function, a cost function counting an error in the classification of one or more vectors about the target where each vector has a value for each of N features of the target, wherein:
the laser controlling function includes M unitary operations, M being a natural number greater than 1 and less than or equal to N, with each unitary operation being at least dependent upon: a) the N historical values of each vector of the plurality of vectors of the training dataset, b) a set of weight values for a) and comprising a predetermined set of weight values, and c) a set of free parameters comprising a predetermined set of free parameters, and the cost function being reduced by changing the set of weight values of b) and the set of free parameters of c) of each unitary operation;

radiating the ensemble of atoms with laser configured to excite at least some atoms of the quantum register, with the laser being operated in accordance with laser parameters resulting from each unitary operation of the configured laser controlling function;
reading the quantum register with optical means, and digitally defining a bit for each atom in the quantum register with a binary value thereof based on an amount of light produced by the respective atom;
using the bits defined, digitally computing a result of the cost function counting the error in the classification of one or more vectors about the target where each vector has a value for each of N features of the target; and
digitally processing a computed result of the cost function such that: when the result is below a predetermined threshold, digitally setting a classifier for the target, the classifier being set with the values of both the sets of weight values of b) and the sets of free parameters of c) of the configured laser controlling function; and when the result is not below the predetermined threshold, carrying out the following in a looped manner until a convergence factor fulfills a predetermined criterion:
digitally storing at least the result of the cost function as last computed;
digitally modifying at least one of the sets of weight values of b) and the set of free parameters of c) of each unitary operation with an optimization technique;
digitally reconfiguring the laser controlling function by processing the training dataset, and digitally reducing, based on the reconfigured laser controlling function, the cost function with the modified at least one of the sets of weight values of b) and the set of free parameters of c) of each unitary operation;
radiating the ensemble of atoms with laser configured to excite at least some atoms of the quantum register, with the laser being operated in accordance with laser parameters resulting from each unitary operation of the laser controlling function as last reconfigured;
reading the quantum register with optical means after the last irradiation of the ensemble of atoms, and digitally defining the bits based on the quantum register as last read;
using the bits as last defined, digitally computing a result of the cost function;
digitally processing the result of the cost function as last computed, and digitally providing a convergence factor based on both said result and the result as last stored; and
if the convergence factor fulfills the predetermined criterion, digitally setting the classifier for the target, the classifier being set with the values of both the sets of weight values of b) and the sets of free parameters of c) of the laser controlling function as last reconfigured.