Terra Quantum AG

A computer-implemented method includes encoding a QUBO problem in a corresponding QUBO graph problem, wherein each binary variable of the QUBO problem corresponds to a node of the QUBO graph problem and edges between two nodes encode coefficients of terms containing both binary variables corresponding to the two nodes, or receiving a QUBO graph problem in a QUBO graph representation; providing the QUBO graph problem as an input to a trained graph neural network on a processing system; retrieving a predicted performance metric for solving the QUBO problem with a variational quantum solver from an output of the trained graph neural network to the QUBO graph problem provided at the input; and, based on the predicted performance metric, providing the QUBO problem to the variational quantum solver implemented on quantum hardware.

A system and method for quantum key distribution includes determining an intrinsic loss along a quantum channel; generating a pulse sequence; transmitting the pulse sequence via the quantum channel; receiving the pulse sequence; determining invalid signal positions and providing the invalid signal positions; determining a first reconciled signal from the first signal and the invalid signal positions, and determining a second reconciled signal from the second signal and the invalid signal positions; determining a total loss along the quantum channel from the at least one test pulse received, determining a signal loss from the total loss and the intrinsic loss, and providing the signal loss; determining a shared by error correcting the first reconciled signal and the second reconciled signal; and determining an amplified key from the shared key by shortening the shared key by a shortening amount that is determined from the signal loss.

A method for natural language processing comprises: receiving a sample comprising natural language; processing the sample, wherein processing the sample comprises generating a plurality of response hypotheses and generating a plurality of confidence values, wherein each response hypothesis is associated with the corresponding confidence value; and selecting a response, comprising selecting the response randomly among the plurality of response hypotheses based at least in part on the corresponding confidence value by utilizing a quantum random number generator.

A method for determining a quantum communication setup includes providing a component set indicative of a quantum communication setup comprising quantum communication components; selecting an action of a set of actions each indicative of a further quantum communication component; including the selected further quantum communication component in the component set; determining, from the component set, a quantum model; determining, from the component set and the quantum model, a maximum key rate by optimizing over an optimization parameter set comprising quantum communication component parameters; adjusting the reward value depending on the size of the maximum key rate in relation to a previous maximum key rate; and iteratively repeating the above steps until a termination criterion is satisfied, yielding an optimal component set and an optimal setup parameter set.

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 of driving a quantum computational network for finding a solution to a computational problem comprising a system of linear binary relations includes initializing computation qubits, applying a set of quantum gates and measuring an outcome state. A solution is determined based on a plurality of solution candidates, wherein a state of the register qubits is associated with a select one of the binary relations and a state of the ancilla qubits is associated with a solution candidate for the select one of the binary relations. The solution is then iteratively improved.

A method for determining a preimage element of a cryptographic hash function includes providing an output value of a cryptographic hash function and hash function operations of the cryptographic hash function; for each of the hash function operations, determining at least one hash function relation, comprising an equation and/or an inequality; determining an optimization problem comprising: the output value, at least one constraint assigned to an iteration of the cryptographic hash function, and optimization variables comprising internal state variables of the cryptographic hash function and at least one preimage variable, wherein the at least one constraint is determined from the at least one hash function relation and comprises preceding internal state variables assigned to a preceding iteration; and solving the optimization problem and determining a preimage element of the cryptographic hash function from an optimizing value of the at least one preimage variable.

The disclosure relates to a method of driving a quantum computational network for determining an extremal value of a cost function for solutions of a quadratic unconstrained binary optimization problem, the method comprising: initializing qubits, sequentially applying layers of quantum gates to the qubits, wherein each layer comprises multi-qubit quantum gates acting on a plurality of qubits and a plurality of variational quantum gates with two eigenvalues and variable actions onto the qubits, wherein the variable actions of the variational quantum gates of the layers of quantum gates form a set of variational parameters {right arrow over (θ)}, and determining an output state of the quantum computational network for obtaining a solution associated with the set of variational parameters {right arrow over (θ)}, wherein each binary variable of the quadratic unconstrained binary optimization problem is associated with a computational basis state of the register qubits, and the solution is obtained by evaluating the probabilities of measuring the computational basis states corresponding to the binary variables, and wherein the solution is iteratively improved by, determining an output state for shifted variational parameters {right arrow over (θ)}* to evaluate a partial derivative with respect to the subset of the variational parameters {right arrow over (θ)} for determining a gradient of the cost function based on the output state for the shifted variational parameters {right arrow over (θ)}*, and by updating the variational parameters {right arrow over (θ)}based on an update function of a moving average over the gradient of the cost function and of a moving average over the squared gradient of the cost function.