15 results about "Unitary matrix" patented technology

The invention discloses a method for generating an amplitude preparation circuit and a quantum state preparation method and device, and the method comprises the steps: setting a main diagonal element of a block matrix as a to-be-prepared amplitude, and setting other elements as 0, so that the block matrix is equivalent to a diagonal matrix, thereby facilitating the construction of a unitary matrix through employing the block matrix, and in the unitary matrix, the unitary matrix is not damaged; the to-be-prepared amplitude is arranged at the upper left corner of the unitary matrix, so that the amplitude preparation of the to-be-prepared quantum state can be carried out by utilizing a circuit corresponding to the unitary matrix, and the preparation of the to-be-prepared quantum state by utilizing a large-scale operator can also be understood, thereby being beneficial to more efficiently and accurately preparing the to-be-prepared quantum state.

The invention discloses a quantum state coding method of a polynomial function and a related device, and belongs to the technical field of quantum computing, and the method comprises the steps: determining the scale of a unitary matrix based on the highest order of the polynomial function, and constructing a target matrix based on a plurality of function values of the polynomial function; wherein the quantum logic gate corresponding to the unitary matrix is used for constructing a quantum circuit of a quantum state of a coding polynomial function, and the line number of the target matrix is the same as that of the unitary matrix; performing singular value decomposition on the target matrix to obtain a plurality of unitary matrixes; and determining a quantum logic gate corresponding to each unitary matrix, and acting each quantum logic gate on the corresponding quantum bit to obtain the quantum state of the polynomial function, thereby realizing coding from the classical data form to the quantum state of the polynomial function.

The invention discloses a load flow calculation method, system and device based on quantum singular value transformation and a medium, and belongs to the technical field of load flow calculation, and the method comprises the steps: obtaining the initial power parameter of each node of a power system and the given power of each node, and determining the power unbalance amount; constructing a node admittance matrix according to the initial power parameters, constructing a correction equation of Newton method load flow calculation, and converting the correction equation into a linear equation set for expression; coding the coefficient matrix into a unitary matrix by using block coding, and executing polynomial transformation based on quantum singular value transformation to construct a quantum circuit representing an inverse matrix of the unitary matrix; encoding the power unbalance amount into a quantum initial state, and enabling a quantum circuit to act on the quantum initial state and performing measurement; and determining the correction of the node voltage based on the measurement result, judging whether to iterate based on the convergence condition, and outputting a load flow calculation result. By utilizing the characteristics of quantum parallelism and quantum singular value transformation, the time consumption of large-scale power system load flow calculation is remarkably reduced.

The invention provides an ISAC complementary sequence generation method and device, and relates to the technical field of communication perception integration, and the method comprises the steps: presetting a sequence length parameter which is a positive integer not less than 2; generating a constant modulus sequence with the length based on the length parameter; the permutation of the preset set is obtained, an initial complementary sequence is generated based on the constant modulus sequence and the permutation, and the initial complementary sequence A is composed of N subsequences {a0, a1,..., aN-1} with the length being N; presetting a sequence set size parameter which is a positive integer not less than 2, and selecting a P-order unitary matrix O; and expanding the initial complementary sequence based on the unitary matrix to generate a complementary sequence set. According to the method, the self-fuzzy function of the complementary sequence is in a drawing pin type, and zero cross-fuzzy function values exist among different complementary sequences.

The invention discloses an amplitude preparation method of a quantum state and a related device, and belongs to the technical field of quantum computing, the method comprises the following steps: determining each partial component of a target quantum state to be prepared, each partial component comprising a ground state of the target quantum state and a probability amplitude of the ground state; a plurality of target matrixes are constructed based on the probability amplitudes of the partial components, singular value decomposition is carried out on the target matrixes to obtain unitary matrixes, and quantum logic gates corresponding to the unitary matrixes obtained through decomposition act together to evolve a target quantum state into 0gt; state; constructing inverse mapping of quantum logic gates corresponding to the unitary matrixes, and acting on the initial state 0gt; an amplitude preparation quantum circuit is obtained on the quantum bit of the state, and the amplitude preparation quantum circuit is used for generating the target quantum state. According to the scheme, the amplitude preparation quantum circuit is constructed based on the idea of deentanglement, and the amplitude preparation of the quantum state can be more efficiently carried out.

To provide, generally, data communication, and more specifically, techniques for increasing the wireless transmission efficiency using a layered construction of arbitrary unitary matrices.SOLUTION: A method includes: generating, via a first processor of a first compute device, symbols based on incoming data; and decomposing a unitary matrix of size NN by 1) applying a permutation to each symbol using a permutation matrix, to produce permuted symbols, and 2) transforming each symbol using at least one primitive transformation matrix of size MM, M being less than or equal to N, to produce transformed symbols. The method also includes sending a signal representing the transformed symbols to a plurality of transmitters for transmission of a signal representing the transformed symbols to a plurality of receivers. A signal representing the unitary matrix is sent to a second compute device for transmission of the unitary matrix to the receivers for recovery of the plurality of symbols at the plurality of receivers.SELECTED DRAWING: Figure 2

A system, method, and computer program product for efficient node embedding for use in predictive models are described. The method includes receiving graph data associated with a graph including a plurality of nodes associated with a plurality of entities and a plurality of edges associated with interactions between the entities. The method further includes generating a plurality of node inlays of the plurality of nodes, and generating a matrix based on each positive node pair and the plurality of node inlays. The method also includes decomposing the matrix to provide a left unitary matrix, a diagonal matrix, and a right unitary matrix. The method also includes determining a plurality of updated node embedding of the plurality of nodes based on the left unitary matrix and the diagonal matrix. The method also includes transmitting the plurality of updated node inlays for input into a machine learning model to generate a prediction.

The invention relates to methods and systems for operating a quantum computing device to sample from an approximate stationary distribution of a Markov chain P having n states, through the construction and execution of a quantum circuit, said method comprising the step of: Initialize an ancilla qubit to the ∣0> state and at least one qubit register in its initial state; Prepare an unitary matrix U, which encodes a discriminant D in block form, allowing polynomial transformations of its singular values or eigenvalues; Apply successively a single qubit gate on the ancilla qubit and the ancilla controlled unitary matrix U on the qubit registers creating a reflection about an approximation of the stationary distribution of the Markov Chain P; and Prepare an approximation of the sought coherent quantum state associated with the stationary distribution, preferably using quantum amplitude amplification

Aspects of the disclosure include decomposing a matrix for a Clifford unitary into a product of first and second involution matrices, determining first symplectic matrix that transforms first involution matrix into a first matrix, a first Clifford unitary matrix being described by first symplectic matrix, and determining second symplectic matrix that transforms second involution matrix into second matrix, a second Clifford unitary matrix being described by second symplectic matrix. Aspects include, responsive to first matrix being a diagonal matrix, setting a second number to size of first matrix and setting a second sequence to include the second number of generalized S gates, and responsive to second matrix being a diagonal matrix, setting a first number to size of second matrix and setting a first sequence to include the first number of generalized S gates. Aspects include executing first sequence, second sequence, and a Pauli unitary P on the quantum computer.

The invention relates to an asymmetric intelligent metasurface modeling method and device, a model and an antenna array. In at least one embodiment of the invention, a model matrix of the asymmetric intelligent metasurface is formed by multiplying a first real unitary matrix used for power distribution, a complex diagonal matrix used for phase adjustment and a second real unitary matrix used for power distribution, power distribution is firstly carried out on an input signal, and then phase adjustment is carried out. And finally, power distribution is carried out again, so that the transmission process of the input signal from the model matrix of the asymmetric intelligent metasurface is realized, and the asymmetric intelligent metasurface can be deployed in a transmission-type scene. Compared with the mode that the model matrix of the symmetric intelligent metasurface needs to be subjected to complex matrix decomposition for optimal configuration, the mode matrix of the asymmetric intelligent metasurface is obtained by multiplying the three matrixes, therefore, complex matrix decomposition does not need to be carried out, the three matrixes are directly optimized, the optimization efficiency is improved, and the cost is reduced. And computing resource consumption caused by matrix decomposition is reduced.

This invention provides a quasi-probabilistic decomposition method and apparatus for quantum unitary matrices based on a diffusion model, primarily relating to the field of quantum computing technology. The method includes: responding to a received target quantum unitary matrix, encoding the target quantum unitary matrix based on decomposition constraints to obtain a joint condition vector; performing back-diffusion processing on the joint condition vector based on a conditional diffusion model to obtain a target tensor satisfying the decomposition constraints; decoding the target tensor to obtain multiple candidate sub-circuits; calculating a weighted sum matrix of the multiple candidate sub-circuits based on their respective real weights; and determining the multiple candidate sub-circuits and their corresponding weights as the decomposition result of the target quantum unitary matrix, provided that the fidelity between the weighted sum matrix of the multiple candidate sub-circuits and the target quantum unitary matrix meets a preset fidelity threshold.

The application discloses a quantum state preparation method and a related device, and the method comprises the following steps: determining each partial component of a target quantum state to be prepared, each partial component comprising one ground state of the target quantum state and an amplitude of the ground state; constructing a plurality of target matrices based on the amplitudes of the partial components, and performing SVD decomposition on the target matrices to obtain a unitary matrix, determining a disentanglement quantum logic gate based on the unitary matrix, and applying a plurality of disentanglement quantum logic gates on a quantum bit with an initial state being the target quantum state to obtain a disentanglement quantum circuit; inversely deriving the target quantum circuit from the disentanglement quantum circuit, wherein the target quantum circuit has a target quantum logic gate, and the target quantum logic gate is determined based on a conjugate transpose matrix of the unitary matrix. (logn) The application discloses a quantum state preparation method and a related device, and the method comprises the following steps: determining each partial component of a target quantum state to be prepared, each partial component comprising one ground state of the target quantum state and an amplitude of the ground state; constructing a plurality of target matrices based on the amplitudes of the partial components, and performing SVD decomposition on the target matrices to obtain a unitary matrix, determining a disentanglement quantum logic gate based on the unitary matrix, and applying a plurality of disentanglement quantum logic gates on a quantum bit with an initial state being the target quantum state to obtain a disentanglement quantum circuit; inversely deriving the target quantum circuit from the disentanglement quantum circuit, wherein the target quantum circuit has a target quantum logic gate, and the target quantum logic gate is determined based on a conjugate transpose matrix of the unitary matrix. (logn) The application discloses a quantum state preparation method and a related device, and the method comprises the following steps: determining each partial component of a target quantum state to be prepared, each partial component comprising one ground state of the target quantum state and an amplitude of the ground state; constructing a plurality of target matrices based on the amplitudes of the partial components, and performing SVD decomposition on the target matrices to obtain a unitary matrix, determining a disentanglement quantum logic gate based on the unitary matrix, and applying a plurality of disentanglement quantum logic gates on a quantum bit with an initial state being the target quantum state to obtain a disentanglement quantum circuit

The invention discloses a quantum variational algorithm suitable for a three-dimensional steady-state N-S equation, which effectively reduces the calculation complexity of traditional numerical solution by combining a mixed architecture of a classical optimizer and a quantum computer. The core innovation comprises four points: 1, solving a discrete algebraic system by using a variable component sub-algorithm, and decomposing and processing any coefficient matrix through a parameterized quantum circuit and a unitary matrix to realize quantization expression of the system; 2, introducing a Jacobian preprocessing condition factor to reduce a condition number, converting algebraic solution into loss function minimization through unitary transformation, and establishing a classical-quantum bridge; 3, providing a multi-Ansatz tree framework aiming at the barren plateau problem, exploring a quantum state space in parallel, enhancing the search capability and reducing the number of quantum bits; and 4, dynamically allocating resources to quantitatively determine the optimal quantum bit number and the Ansatz tree scale based on the complexity of the coefficient matrix, and improving the calculation efficiency. According to the algorithm, the complexity performance is obviously superior to that of a traditional method while the precision is guaranteed.

Aspects of the disclosure include decomposing a matrix for a Clifford unitary into a product of first and second involution matrices, determining first symplectic matrix that transforms first involution matrix into a first matrix, a first Clifford unitary matrix being described by first symplectic matrix, and determining second symplectic matrix that transforms second involution matrix into second matrix, a second Clifford unitary matrix being described by second symplectic matrix. Aspects include, responsive to first matrix being a diagonal matrix, setting a second number to size of first matrix and setting a second sequence to include the second number of generalized S gates, and responsive to second matrix being a diagonal matrix, setting a first number to size of second matrix and setting a first sequence to include the first number of generalized S gates. Aspects include executing first sequence, second sequence, and a Pauli unitary P on the quantum computer.

The invention discloses a load flow calculation method, system and device based on quantum fast inversion and a medium, and belongs to the technical field of load flow calculation, and the method comprises the steps: obtaining the initial power parameters of each node of a power system and the given power of each node, calculating the power value of each node based on the node parameters, and combining with the given power to determine the power unbalance amount; constructing a node admittance matrix according to the initial power parameters, constructing a correction equation of Newton method load flow calculation, and converting the correction equation into a linear equation set for expression; coding the coefficient matrix into a unitary matrix by adopting block coding, and constructing a quantum circuit for representing an inverse matrix of the unitary matrix based on a quantum fast inversion method; encoding the power unbalance amount into a quantum initial state, and enabling a quantum circuit to act on the quantum initial state and performing measurement; and determining the correction of the node voltage based on the measurement result, judging whether to iterate based on the convergence condition, and outputting a load flow calculation result. According to the method, exponential acceleration of the quantum linear system is realized, and the solving efficiency is improved.