9,261 research outputs found
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
Quantum Capacities of Bosonic Channels
We investigate the capacity of bosonic quantum channels for the transmission
of quantum information. Achievable rates are determined from measurable moments
of the channel by showing that every channel can asymptotically simulate a
Gaussian channel which is characterized by second moments of the initial
channel. We calculate the quantum capacity for a class of Gaussian channels,
including channels describing optical fibers with photon losses, by proving
that Gaussian encodings are optimal. Along the way we provide a complete
characterization of degradable Gaussian channels and those arising from
teleportation protocols.Comment: 5 pages, 2 figure
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