Multiverse Computing S.L.

The disclosure relates to a quantum computing system comprising: a reservoir of quantum computational units, wherein the quantum computational units are disposed in a non-lattice computational arrangement; means for computationally manipulating quantum computational units of the reservoir; means for enabling computational interaction between at least two quantum computational units computationally manipulated; and a measurement means for measuring a quantum property of at least one of the at least two quantum computational units after said computational interaction.

A computer-implemented method for simulating and analyzing material deformations with principles of linear elasticity, comprising: splitting material properties of a material into pieces; decomposition of the geometry into simple domains and computing mesh-grid tensors for all dimensions for specifying a corresponding coordinate with a defining mesh-grid function; using the mesh-grid tensors for each simple domains that are defined for all available dimensions to compute components of a Jacobian, and mapping a reference element into a small element of each simple domain to compute the components all at once; processing stress and strain fields of the material, external forces applied thereto and test function equations over local elements through the Jacobian components; assembling stiffness TN-operators and mass TN-operators for each simple domain; stitching the stiffness TN-operators and the mass TN-operators together for enforcing continuity over interfaces; and applying a mass TN-operator to a predefined external force TN-vector.

A method including the following steps: computing availability of at least one renewable electrical energy production device that delivers electricity to at least one household associated therewith to deliver electricity to an electric grid; computing an electricity usage plan for the predetermined period of time; optimizing the electricity usage plan so that: the electricity to be delivered is to be delivered to the electric grid at one or more different time periods at least when an amount of the possible electric power generation corresponding to non-renewable electrical energy generators is greater than at other time periods within the predetermined period of time; and during a predetermined duration after the time period or periods when the electricity is delivered to the electric grid, the electricity delivered by the at least one renewable electrical energy production device for consumption by the respective household is lower than the computed availability during the predetermined duration.

The method enhances computational efficiency and performance of large language models (LLMs) through hybrid classical-quantum processing. The method involves a classical computer receiving an input for processing by a selected LLM comprising deep self-attention and multilayer perceptron layers and decomposing the LLM's weight matrices into a first Matrix Product Operator (MPO). The classical computer identifies one or more disentanglers which factorize the MPO into a non-unitary tensor network and a set of unitary subcomponents. The non-unitary tensor network enables compression by localizing quantum correlations. The unitary subcomponents correspond to first and second variational quantum circuits, configured to run sequentially on a quantum computer. The execution of the second quantum circuit is conditioned on both the measurements of the first quantum circuit and outputs from the tensor network, enabling enhanced correlation capture and efficient model representation.

A method includes: receiving, by an apparatus or system, a first set of values for an electric grid, a second set for a first electricity supply, and a third set for a second electricity supply; receiving data from electricity controllers, wherein all the received data form a fourth set of values, wherein each electricity controller of the controllers is associated with a household of multiple households and controls electricity supplied to the electric grid, stored and requested from the electric grid at the different time periods within the PT, wherein each household includes at least one renewable electrical energy production device and the fourth set of values is indicative of electrical energy producible by each device of the at least one renewable energy production device at the different time periods within the PT; solving, by the apparatus or system based on the four sets of values, an optimization problem.

A computer-implemented method and system for identifying trends in a network of elements. The method comprises obtaining a plurality of properties for the elements in the network, creating a multi-dimensional configuration space from the measured plurality of properties and storing the multi-dimensional configuration space in data storage. A cost function which is representative of the trends in the network is then built and the cost function is passed to a quantum processor for solving to identify a minimum in the cost function. The identified minimum is processed extract in a central processing unit the trends from the identified minimum. The cost function has one or more components which are representative of interaction between different elements in the network.

There is presented a method of driving a quantum computer to find one or more states of interest of a network. In one example, the network comprising a plurality of players. The method determines a set of adjacent graphs by determining, for each graph, whether each of the other graphs are adjacent. The method defines a cost function associated with a Hamiltonian operator of the quantum computer; the cost function comprising a set of parameters determined by analysing the utilities of vertices in the set of adjacent graphs. The method further comprises outputting a plurality of control signals for driving the quantum computer wherein the control signals are associated with the set of parameters and comprise: one or more control signals for controlling the states of qubits in the quantum computer; and, one or more control signals for controlling the entanglement of qubits in the quantum computer.

A computer-implemented method for improving the computational efficiency and performance of large language models (LLMs) within at least one hybrid classical-quantum computation system with involving quantum circuits and tensor networks; and the classical computing device applies disentanglers to decompose the weight matrices of self-attention layers and multilayer perceptron (MLP) layers of a pre-selected large language model (LLM) into an unitary quantum circuits and a non-unitary tensor network for allowing transformation into quantum circuits into quantum gates; and sends this information to at least one quantum computing device within a quantum circuits; and processes non-unitary tensor network with at least one classical computing device and combines both results to reconstruct the large language model; and enlarges the bond dimension of the non-unitary tensor network and the number of layers of the quantum circuits; and optimizes the new parameters variationally in order to improve the accuracy beyond that of the original LLM.

A computer implemented method for solving a classical optimization problem of integer factorization implemented on a digital computer system is described. The method is implemented on a classical processor adapted to execute a time evolving block decimation algorithm. The method comprises in a first step an inputting a lattice basis and a target lattice vector to an input device of the classical processor followed by an implementing a lattice basis reduction algorithm on the lattice basis in an implementation module, thereby obtaining a reduced orthogonal lattice basis. The method further comprises a projecting the target lattice vector on the reduced orthogonal lattice basis followed by a building a closest vector to the target lattice vector and optimizing the closest vector using a tropical time-evolving block decimation algorithm by the classical processor and finally outputting an integer vector.

Data acquirable from a physical system is received and processed by at least one classical computing device to provide data indicative of a digital twin of the physical system by digitally computing a quantum-inspired algorithm. The data indicative of the digital twin is indicative of a reconfiguration of a physical parameter of the physical system, and the physical parameter has a reconfigurable digital counterpart in the digital twin.