A method for determining a cryptographic key is carried out in a data processing system, and comprises: providing a plaintext and a ciphertext determined from the plaintext using a cryptographic key and a cryptographic procedure which comprises cryptographic operations; for each cryptographic operation of the cryptographic procedure, providing at least one intermediate relation which comprises an intermediate equation and/or an intermediate inequality; determining an optimization problem comprising: the plaintext and the ciphertext; at least one optimization expression assigned to a round of the cryptographic procedure; and optimization variables comprising state variables of the cryptographic procedure and a cryptographic key variable; wherein the at least one optimization expression is determined from the at least one intermediate relation and comprises at least one preceding state variable assigned to a preceding round. The method further comprises: solving the optimization problem and determining the cryptographic key from an optimizing value of the cryptographic key variable.

A method includes: obtaining training texts; for each of the training texts, performing the following operations: obtaining a word vector of each word in the current training text as a parameter of a first quantum circuit to obtain quantum states; inputting each of the quantum states to second, third, and fourth quantum circuits and performing measurement; calculating one group of weight values corresponding to each word to obtain a feature vector corresponding to the current training text; inputting the feature vector to a neural network model to obtain a prediction value; and determining a value of loss function based on the prediction value and a label value, and adjusting parameters corresponding to the second, third, and fourth quantum circuits and the neural network model based on the value of the loss function.

A method includes: obtaining training texts; for each of the training texts, performing the following operations: obtaining a word vector of each word in the current training text as a parameter of a first quantum circuit to obtain quantum states; inputting each of the quantum states to second, third, and fourth quantum circuits and performing measurement; calculating one group of weight values corresponding to each word to obtain a feature vector corresponding to the current training text; inputting the feature vector to a neural network model to obtain a prediction value; and determining a value of loss function based on the prediction value and a label value, and adjusting parameters corresponding to the second, third, and fourth quantum circuits and the neural network model based on the value of the loss function.

A method of measuring a physical quantity implemented in a hybrid classical-quantum system, the method comprising initializing the plurality of controllable quantum systems in an initial state, applying a set of preparation gates to the plurality of controllable quantum systems for preparing the plurality of controllable quantum systems in a non-classical state, evolving the non-classical state over a time period for obtaining an evolved state of the plurality of controllable quantum systems, applying a set of decoding gates to the plurality of controllable quantum systems in the evolved state, performing a measurement of the plurality of controllable quantum systems, and determining a derived value of the physical quantity based on a mapping function between an outcome of the measurement and the physical quantity on the classical computation system.

A method and system are provided for modeling the relative performance of algorithms, including quantum algorithms, over a set of problem instances. The model, referred to as a performance estimator, is generated from a selected algorithm and a set a set of problem instances as input, resulting in a generated model. Unlike prior methods, which model the performance of a fixed algorithm on a set of instances, embodiments of the present technology produce a performance estimate without needing to explicitly model the underlying algorithm. The model, once generated by the disclosed technology, may then be utilized to estimate the performance of new algorithms that the model has not been trained on.

A method and system are provided for modeling the relative performance of algorithms, including quantum algorithms, over a set of problem instances. The model, referred to as a performance estimator, is generated from a selected algorithm and a set a set of problem instances as input, resulting in a generated model. Unlike prior methods, which model the performance of a fixed algorithm on a set of instances, embodiments of the present technology produce a performance estimate without needing to explicitly model the underlying algorithm. The model, once generated by the disclosed technology, may then be utilized to estimate the performance of new algorithms that the model has not been trained on.

An integrated circuit and a method for operating the integrated circuit to perform quantum analog computing. The integrated circuit comprises a plurality of qubits connected to each other, each qubit of the plurality of qubits comprising resistors, inductors, capacitors and a switch, which can be implemented using CMOS elements, wherein the qubits are connected to each other according to a connectivity topology, such as a Hopfield network, that provides an analog of quantum behavior at room temperature.

Methods, systems, and apparatus for training quantum evolutions using sub-logical controls. In one aspect, a method includes the actions of accessing quantum hardware, wherein the quantum hardware includes a quantum system comprising one or more multi-level quantum subsystems; one or more control devices that operate on the one or more multi-level quantum subsystems according to one or more respective control parameters that relate to a parameter of a physical environment in which the multi-level quantum subsystems are located; initializing the quantum system in an initial quantum state, wherein an initial set of control parameters form a parameterization that defines the initial quantum state; obtaining one or more quantum system observables and one or more target quantum states; and iteratively training until an occurrence of a completion event.

Disclosed is a data encryption method performed by an apparatus, which includes encrypting plaintext data based on an encryption key to generate first ciphertext data, applying a noise vector being periodically extracted to an artificial intelligence-based generative model to generate a first signature code and a second signature code, and applying the first signature code and the second signature code to the first ciphertext data to generate second ciphertext data. The generating of the first signature code includes determining a type and a replacement location of a character necessary to generate the first signature code by means of a predetermined conversion formula and generating a first character, which is obtained by calculating an existing encryption character being present at the replacement location in the first ciphertext data and the character in a predetermined scheme, as the first signature code.

Disclosed is a data encryption method performed by an apparatus, which includes encrypting plaintext data based on an encryption key to generate first ciphertext data, applying a noise vector being periodically extracted to an artificial intelligence-based generative model to generate a first signature code and a second signature code, and applying the first signature code and the second signature code to the first ciphertext data to generate second ciphertext data. The generating of the first signature code includes determining a type and a replacement location of a character necessary to generate the first signature code by means of a predetermined conversion formula and generating a first character, which is obtained by calculating an existing encryption character being present at the replacement location in the first ciphertext data and the character in a predetermined scheme, as the first signature code.