Instruction Set Architectures for Quantum Processing Units

Progress in quantum computing hardware raises questions about how these devices can be controlled, programmed, and integrated with existing computational workflows. We briefly describe several prominent quantum computational models, their associated quantum processing units (QPUs), and the adoption of these devices as accelerators within high-performance computing systems. Emphasizing the interface to the QPU, we analyze instruction set architectures based on reduced and complex instruction sets, i.e., RISC and CISC architectures. We clarify the role of conventional constraints on memory addressing and instruction widths within the quantum computing context. Finally, we examine existing quantum computing platforms, including the D-Wave 2000Q and IBM Quantum Experience, within the context of future ISA development and HPC needs.Comment: To be published in the proceedings in the International Super Computing Conference 2017 publicatio

Emergence and Adult Biology of \u3ci\u3eAgrilus Difficilis\u3c/i\u3e (Coleoptera: Buprestidae), a Pest of Honeylocust, \u3ci\u3eGleditsia Triacanthos\u3c/i\u3e

Emergence and adult biology of Agrilus difficilis were examined in relation to its host Gleditsia triacanthos. began as early as 5 June in 1982 and completed as late as 22 July in 1983. Females lived significantly longer, 48 days, than males, 29 days. Average fecundity was one egg per day during a 36-day oviposition period

Algebraic and information-theoretic conditions for operator quantum error-correction

Operator quantum error-correction is a technique for robustly storing quantum information in the presence of noise. It generalizes the standard theory of quantum error-correction, and provides a unified framework for topics such as quantum error-correction, decoherence-free subspaces, and noiseless subsystems. This paper develops (a) easily applied algebraic and information-theoretic conditions which characterize when operator quantum error-correction is feasible; (b) a representation theorem for a class of noise processes which can be corrected using operator quantum error-correction; and (c) generalizations of the coherent information and quantum data processing inequality to the setting of operator quantum error-correction.Comment: 4 page

Probing the qudit depolarizing channel

For the quantum depolarizing channel with any finite dimension, we compare three schemes for channel identification: unentangled probes, probes maximally entangled with an external ancilla, and maximally entangled probe pairs. This comparison includes cases where the ancilla is itself depolarizing and where the probe is circulated back through the channel before measurement. Compared on the basis of (quantum Fisher) information gained per channel use, we find broadly that entanglement with an ancilla dominates the other two schemes, but only if entanglement is cheap relative to the cost per channel use and only if the external ancilla is well shielded from depolarization. We arrive at these results by a relatively simple analytical means. A separate, more complicated analysis for partially entangled probes shows for the qudit depolarizing channel that any amount of probe entanglement is advantageous and that the greatest advantage comes with maximal entanglement

Classification of nonproduct states with maximum stabilizer dimension

Nonproduct n-qubit pure states with maximum dimensional stabilizer subgroups of the group of local unitary transformations are precisely the generalized n-qubit Greenberger-Horne-Zeilinger states and their local unitary equivalents, for n greater than or equal to 3 but not equal to 4. We characterize the Lie algebra of the stabilizer subgroup for these states. For n=4, there is an additional maximal stabilizer subalgebra, not local unitary equivalent to the former. We give a canonical form for states with this stabilizer as well.Comment: 6 pages, version 3 has a typographical correction in the displayed equation just after numbered equation (2), and other minor correction

Left dorsolateral prefrontal cortex repetitive transcranial magnetic stimulation reduces the development of long-term muscle pain

The left dorsolateral prefrontal cortex (DLPFC) is involved in the experience and modulation of pain, and may be an important node linking pain and cognition. Repetitive transcranial magnetic stimulation (rTMS) to the left DLPFC can reduce chronic and experimental pain. However, whether left DLPFC rTMS can influence the development of chronic pain is unknown. Using repeated intramuscular injection of nerve growth factor to induce the development of sustained muscle pain (lasting weeks), 30 healthy individuals were randomized to receive 5 consecutive daily treatments of active or sham left DLPFC rTMS, starting before the first nerve growth factor injection on day 0. Muscle soreness and pain severity were collected daily for 14 days and disability on every alternate day. Before the first and 1 day after the last rTMS session, anxiety, depression, affect, pain catastrophizing, and cognitive performance on the attention network test were assessed. Left DLPFC rTMS treatment compared with sham was associated with reduced muscle soreness, pain intensity, and painful area (P < 0.05), and a similar trend was observed for disability. These effects were most evident during the days rTMS was applied lasting up to 3 days after intervention. Depression, anxiety, pain catastrophizing, and affect were unchanged. There was a trend toward improved cognitive function with rTMS compared with sham (P = 0.057). These data indicate that repeated left DLPFC rTMS reduces the pain severity in a model of prolonged muscle pain. The findings may have implications for the development of sustained pain in clinical populations

Single-trial multiwavelet coherence in application to neurophysiological time series

A method of single-trial coherence analysis is presented, through the application of continuous muldwavelets. Multiwavelets allow the construction of spectra and bivariate statistics such as coherence within single trials. Spectral estimates are made consistent through optimal time-frequency localization and smoothing. The use of multiwavelets is considered along with an alternative single-trial method prevalent in the literature, with the focus being on statistical, interpretive and computational aspects. The multiwavelet approach is shown to possess many desirable properties, including optimal conditioning, statistical descriptions and computational efficiency. The methods. are then applied to bivariate surrogate and neurophysiological data for calibration and comparative study. Neurophysiological data were recorded intracellularly from two spinal motoneurones innervating the posterior,biceps muscle during fictive locomotion in the decerebrated cat

Mixed state Pauli channel parameter estimation

The accuracy of any physical scheme used to estimate the parameter describing the strength of a single qubit Pauli channel can be quantified using standard techniques from quantum estimation theory. It is known that the optimal estimation scheme, with m channel invocations, uses initial states for the systems which are pure and unentangled and provides an uncertainty of O[1/m^(1/2)]. This protocol is analogous to a classical repetition and averaging scheme. We consider estimation schemes where the initial states available are not pure and compare a protocol involving quantum correlated states to independent state protocols analogous to classical repetition schemes. We show, that unlike the pure state case, the quantum correlated state protocol can yield greater estimation accuracy than any independent state protocol. We show that these gains persist even when the system states are separable and, in some cases, when quantum discord is absent after channel invocation. We describe the relevance of these protocols to nuclear magnetic resonance measurements

Discrimination of unitary transformations in the Deutsch-Jozsa algorithm

We describe a general framework for regarding oracle-assisted quantum algorithms as tools for discriminating between unitary transformations. We apply this to the Deutsch-Jozsa problem and derive all possible quantum algorithms which solve the problem with certainty using oracle unitaries in a particular form. We also use this to show that any quantum algorithm that solves the Deutsch-Jozsa problem starting with a quantum system in a particular class of initial, thermal equilibrium-based states of the type encountered in solution state NMR can only succeed with greater probability than a classical algorithm when the problem size exceeds $n \sim 10^5.$Comment: 7 pages, 1 figur