We develop a computation model for solving Boolean networks that implements wires through quantum ground-state computation and implements gates through identities following from angular momentum algebra and statistics. The gates are static in the sense that they contribute Hamiltonian 0 and hold as constants of the motion; only the wires are dynamic. Just as a spin 1/2 makes an ideal 1-bit memory element, a spin 1 makes an ideal 3-bit gate. Such gates cost no computation time: relaxing the wires alone solves the network. We compare computation time with that of an easier Boolean network where all the gate constraints are simply removed. This computation model is robust with respect to decoherence and yields a generalized quantum speed-up for all NP problems.
We develop a computation model for solving Boolean networks that implements wires dynamically through quantum ground–state computation and implements gates kinematically through identities following from angular–momentum algebra and statistics. The gates are extra–dynamical in the sense that they contribute nothing to the Hamiltonian and hold as constants of the motion; only the wires are dynamical. Just as a spin ½ makes an ideal 1–bit memory element, a spin 1 makes an ideal 3–bit gate. Such gates cost no computation time; relaxing the wires alone solves the network. We compare computation time heuristically with that of an easier Boolean network where all the gate constraints are simply removed. This computation model is robust with respect to decoherence and yields a generalized quantum speed–up for all NP (non–deterministic–polynomial) problems. We give an Ising model for such a logical network composed of spins of 1 with bilinear couplings.
Tailoring many-body interactions among a proper quantum system endows it with computing ability by means of static quantum computation in the sense that some of the physical degrees of freedom can be used to store binary information and the corresponding binary variables satisfy some given logic relations if and only if the system is in the ground state. Two theorems are proved showing that the universal static quantum computer can encode the solutions for any P and NP problem into its ground state using only polynomial number (in the problem input size) of logic gates. The second step is to read out the solutions by relaxing the system. The time complexity is relevant when one tries to read out the solution by relaxing the system, therefore our model of static quantum computation provides a new connection between the computational complexity and the dynamics of a complex system.
Systems of spin 1, such as triplet pairs of spin-1/2 fermions (like orthohydrogen nuclei) make useful three-terminal elements for quantum computation, and when interconnected by qubit equality relations are universal for quantum computation. This is an instance of quantum-statistical computation: some of the logical relations of the problem are satisfied identically in virtue of quantum statistics, which takes no time. We show heuristically that quantum-statistical ground-mode computation is substantially faster than pure ground-mode computation when the ground mode is reached by annealing.
We consider an extended model of quantum computation where a scalable fault-tolerant quantum computer is coupled to one or more ancilla qubits that evolve according to a nonlinear Schrödinger equation. Following the approach of Abrams and Lloyd, an efficient quantum circuit evaluating an
n-bit Boolean function in conjunctive normal form is used to prepare an ancilla encoding its number
s of satisfying assignments (
0≤s≤2n). This is followed by a nonlinear quantum state discrimination gate on the ancilla qubit that is used to learn properties of
s. Here we consider three types of state discriminators generated by different nonlinear Hamiltonians. First, given a restricted Boolean satisfiability problem with the promise of at most one satisfying assignment ($ 0 \le s \le 1$), we show that a qubit with
⟨σz⟩σz nonlinearity can be used to efficiently determine whether
s=0 or
s=1, solving the UNIQUE SAT problem. Here $\langle A \rangle := \langle ψ| A |ψ\rangle $ denotes expectation in the current state. UNIQUE SAT is NP-hard under a randomized polynomial-time reduction (of course any discussion of complexity assumes a scalable, fault-tolerant implementation). Second, for unrestricted satisfiability problems with $ 0 \le s \le 2^n$, a Hamiltonian with $ \langle σ^x \rangle σ^y - \langle σ^y \rangle σ^x$ nonlinearity can be used to efficiently determine whether
s=0 or
s>0, thereby solving 3SAT, which is NP-complete. Finally, we show that $ \langle σ^y \rangle \langle σ^z \rangle σ^x - \langle σ^x \rangle \langle σ^z \rangle σ^y $ nonlinearity can be used to efficiently measure
s and solve #SAT, which is #P-complete. The nonlinear models are of mean field type and might be simulated with ultracold atoms.
We expand a set of notions recently introduced providing the general setting for a universal representation of the quantum structure on which quantum information stands. The dynamical evolution process associated with generic quantum information manipulation is based on the (re)coupling theory of SU(2) angular momenta. Such scheme automatically incorporates all the essential features that make quantum information encoding much more efficient than classical: it is fully discrete; it deals with inherently entangled states, naturally endowed with a tensor product structure; it allows for generic encoding patterns. The model proposed can be thought of as the non-Boolean generalization of the quantum circuit model, with unitary gates expressed in terms of 3nj coefficients connecting inequivalent binary coupling schemes of n+1 angular momentum variables, as well as Wigner rotations in the eigenspace of the total angular momentum. A crucial role is played by elementary j-gates (6j symbols) which satisfy algebraic identities that make the structure of the model similar to "state sum models", employed in discretizing Topological Quantum Field Theories and quantum gravity. The spin network simulator can thus be viewed also as a Combinatorial QFT model for computation. The semiclassical limit (large j's) is discussed.