html5-img
1 / 30

Authors Faisal Shah Khan Marek A. Perkowski

Authors Faisal Shah Khan Marek A. Perkowski. Slides prepared by Faisal Shah Khan . Overview. ه A qudit replaces a classical dit as an information unit in d -valued quantum computing.

hunter
Télécharger la présentation

Authors Faisal Shah Khan Marek A. Perkowski

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Authors Faisal Shah Khan Marek A. Perkowski Slides prepared by Faisal Shah Khan

  2. Overview هA qudit replaces a classical dit as an information unit in d-valued quantum computing. ه A qudit represented as a unit vector in the state space, which is a complex projective d-dimensional Hilbert space, ه In the computational basis, the basis vectors of are written in Dirac notation as where 1 is in the i-th position

  3. Overview هAn arbitrary vector incan be expressed as a linear combination ه The real number is the probability that the state vector will be in i-th basis state upon measurement. هWhen the state spaces of n qudits of different d-valued dimensions are combined via their algebraic tensor product, the result is a n qudit hybridstate space where is the state space of the qudit.

  4. Overview هThe computational basis for H will consist of all possible tensor products of the computational basis vectors of the component state spaces . هIf all the different are assigned the same value d, the resulting state space is that of n d-valued qudits. هThe evolution of state space changes the state of the qudits via the action of a unitary (length preserving) operator on the qudits. ه A unitary operator can be represented by a square unitary evolution matrix. ه For the hybrid state space H, an evolution matrix will have size while the evolution matrix for will be of size

  5. Overview هIn the context of quantum logic synthesis, an evolution matrix is a quantum logic circuit that needs to be realized by a universal set of quantum logic gates. ه It is well established (Brylinski, Muthukrishnan) that sets of one and two qudit quantum gates are universal. Hence, the synthesis of an evolution matrix requires that the matrix be decomposed to the level of unitary matrices acting on one or two qudits. ه Unitary matrix decomposition methods like the QR factorization and the Cosine Sine decomposition (CSD) from matrix perturbation theory have been used for 2-valued (binary) and 3-valued (Ternary) quantum logic synthesis. ه Mottonen et. al, Shende et. al – Binary CSD sythesis هKhan and Perkowski – Ternary CSD synthesis

  6. Cosine-Sine Decomposition (CSD)

  7. n-qubit (Binary) Quantum Logic Synthesis via CSD هIn this case, unitary W matrices are of size . هLet so that هNow the CSD gives W decomposed as هEach block in the block matrices of the CSD of W are of size

  8. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) هNote that the CSD can be iteratively applied to the unitary block diagonals that occur in the decomposition at each stage. هThe iteration stops when the block are of size 2 x 2. هHowever, there may be local optimizations involving a CNOT (4x4 matrix) and 2 x 2 gates.

  9. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) هShende et al and Mottonen et al give the following realization of the factors in the CSD at each iterative level: a) Block diagonal matrices are Quantum Multiplexers. b) The cosine-sine matrices are uniformly controlled rotations, a variation of the multiplexer.

  10. n-qubit Quantum Multiplexer

  11. Uniformly (n-1)-controlled rotation

  12. n-qubit Quantum Multiplexer in Dirac / Matrix notation (M-1) where is the i-th qubit in he circuit, and both block matrices are of size ه Depending on whether , (M-1) reduces to

  13. (n-1)-controlled rotation in Dirac / Matrix notation (R-1)

  14. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) A 2-qubit quantum multiplexer U U 0 M V 1 V A 2-qubit uniformly 1-controlled rotation R0 R1

  15. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) Example 1. A 2-qubit quantum multiplexer matrix. The first qubit controls the second. ه If the first qubit is 0, then U is applied to the second qubit. ه If the first qubit is 1, then V is applied to the second qubit. ه For n-qubits, a quantum multiplexer will control the lowest (n-1) qubits via the top qubit.

  16. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) Example 2. A 2-qubit uniformly controlled rotation matrix. This 4 x 4 matrix acts on the tensor product of the two qubits

  17. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) Calculations give: (1) Let Then (1) becomes Let Then (1) becomes

  18. n-qubit (Binary) Quantum Logic Synthesis via CSD (continued) ه A uniformly controlled rotation is essentially a multiplexer. ه In our example, the bottom qubit controls the top. ه For n-qubits, a uniformly controlled rotations is a multiplexer in which the lowest qubit controls the top (n-1) qubits.

  19. n-qutrit (Ternary) Quantum Logic Synthesis via CSD ه In this case, unitary matrices W are of size ه Let so that ه Now the CSD gives W decomposed as ه The top corner blocks in the diagonal matrices are of size ه The lower corner blocks, are of size Both C and S matrices are of size (2)

  20. n-qutrit (Ternary) Quantum Logic Synthesis via CSD (continued) Uniformly controlled rotation around x-axis in Uniformly controlled rotation around z-axis in Multiplexer

  21. n-qutrit Quantum Multiplexer

  22. (n-1)-controlled R_x rotation

  23. d-valued Quantum Logic Synthesis vis CSD ه Consider the matrix

More Related