Peter L. McMahon

In-Plane Resistivity Anisotropy in an Underdoped Iron Arsenide Superconductor

Jiun-Haw Chu, 2 James G. Analytis, 2 Kristiaan De Greve, Peter L. McMahon, Zahirul Islam, Yoshihisa Yamamoto, 5 and Ian R. Fisher 2 Department of Applied Physics and Geballe Laboratory for Advanced Materials, Stanford University, Stanford, California 94305, USA Stanford Institute of Energy and Materials Science, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park 94025,California 94305, USA E. L. Ginzton Laboratory, Stanford University, Stanford, California 94305, USA The Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, USA National Institute of Informatics, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8403, Japan (Dated: February 18, 2010)De-Twinning a Superconductor Insight into the mechanism of electrical transport in a solid can often be gained by measuring its resistivity along different spatial directions. However, iron-based superconductors form numerous twin boundaries where two different orientations of a crystal meet, and so the measured resistivity along any in-plane direction will be averaged over these orientations. Chu et al. (p. 824) were able to “de-twin” the compound Ba(Fe1−xCox)2As2, enabling unambiguous measurements of its normal-state resistivity along the in-plane lattice axes. Differences were observed in the resistivity values along the two axes, which suggests that the breaking of the symmetry of the lattice and electron subsystems occur simultaneously. Electronic ordering coincides with a lattice structural transition in an exotic superconductor. High-temperature superconductivity often emerges in the proximity of a symmetry-breaking ground state. For superconducting iron arsenides, in addition to the antiferromagnetic ground state, a small structural distortion breaks the crystal’s C4 rotational symmetry in the underdoped part of the phase diagram. We reveal that the representative iron arsenide Ba(Fe1−xCox)2As2 develops a large electronic anisotropy at this transition via measurements of the in-plane resistivity of detwinned single crystals, with the resistivity along the shorter b axis ρb being greater than ρa. The anisotropy reaches a maximum value of ~2 for compositions in the neighborhood of the beginning of the superconducting dome. For temperatures well above the structural transition, uniaxial stress induces a resistivity anisotropy, indicating a substantial nematic susceptibility.

Quantum-dot spin–photon entanglement via frequency downconversion to telecom wavelength

Long-distance quantum teleportation and quantum repeater technologies require entanglement between a single matter quantum bit (qubit) and a telecommunications (telecom)-wavelength photonic qubit. Electron spins in III–V semiconductor quantum dots are among the matter qubits that allow for the fastest spin manipulation and photon emission, but entanglement between a single quantum-dot spin qubit and a flying (propagating) photonic qubit has yet to be demonstrated. Moreover, many quantum dots emit single photons at visible to near-infrared wavelengths, where silica fibre losses are so high that long-distance quantum communication protocols become difficult to implement. Here we demonstrate entanglement between an InAs quantum-dot electron spin qubit and a photonic qubit, by frequency downconversion of a spontaneously emitted photon from a singly charged quantum dot to a wavelength of 1,560 nanometres. The use of sub-10-picosecond pulses at a wavelength of 2.2 micrometres in the frequency downconversion process provides the necessary quantum erasure to eliminate which-path information in the photon energy. Together with previously demonstrated indistinguishable single-photon emission at high repetition rates, the present technique advances the III–V semiconductor quantum-dot spin system as a promising platform for long-distance quantum communication.

Layered architecture for quantum computing

We develop a layered quantum computer architecture, which is a systematic framework for tackling the individual challenges of developing a quantum computer while constructing a cohesive device design. We discuss many of the prominent techniques for implementing circuit-model quantum computing and introduce several new methods, with an emphasis on employing surface code quantum error correction. In doing so, we propose a new quantum computer architecture based on optical control of quantum dots. The timescales of physical hardware operations and logical, error-corrected quantum gates differ by several orders of magnitude. By dividing functionality into layers, we can design and analyze subsystems independently, demonstrating the value of our layered architectural approach. Using this concrete hardware platform, we provide resource analysis for executing fault-tolerant quantum algorithms for integer factoring and quantum simulation, finding that the quantum dot architecture we study could solve such problems on the timescale of days.

Faster quantum chemistry simulation on fault-tolerant quantum computers

Quantum computers can in principle simulate quantum physics exponentially faster than their classical counterparts, but some technical hurdles remain. We propose methods which substantially improve the performance of a particular form of simulation, ab initio quantum chemistry, on fault-tolerant quantum computers; these methods generalize readily to other quantum simulation problems. Quantum teleportation plays a key role in these improvements and is used extensively as a computing resource. To improve execution time, we examine techniques for constructing arbitrary gates which perform substantially faster than circuits based on the conventional Solovay–Kitaev algorithm (Dawson and Nielsen 2006 Quantum Inform. Comput. 6 81). For a given approximation error ϵ, arbitrary single-qubit gates can be produced fault-tolerantly and using a restricted set of gates in time which is O(log ϵ) or O(log log ϵ); with sufficient parallel preparation of ancillas, constant average depth is possible using a method we call programmable ancilla rotations. Moreover, we construct and analyze efficient implementations of first- and second-quantized simulation algorithms using the fault-tolerant arbitrary gates and other techniques, such as implementing various subroutines in constant time. A specific example we analyze is the ground-state energy calculation for lithium hydride.Quantum computers can in principle simulate quantum physics exponentially faster than their classical counterparts, but some technical hurdles remain. Here we consider methods to make proposed chemical simulation algorithms computationally fast on fault-tolerant quantum computers in the circuit model. Fault tolerance constrains the choice of available gates, so that arbitrary gates required for a simulation algorithm must be constructed from sequences of fundamental operations. We examine techniques for constructing arbitrary gates which perform substantially faster than circuits based on the conventional Solovay-Kitaev algorithm [C.M. Dawson and M.A. Nielsen, Quantum Inf. Comput., 6:81, 2006]. For a given approximation error , arbitrary singlequbit gates can be produced fault-tolerantly and using a limited set of gates in time which is O(log ) or O(log log ); with sufficient parallel preparation of ancillas, constant average depth is possible using a method we call programmable ancilla rotations. Moreover, we construct and analyze efficient implementations of firstand second-quantized simulation algorithms using the fault-tolerant arbitrary gates and other techniques, such as implementing various subroutines in constant time. A specific example we analyze is the ground-state energy calculation for Lithium hydride. PACS numbers: 03.67.Ac, 03.67.Lx, 31.15.A-

A highly scalable Restricted Boltzmann Machine FPGA implementation

Restricted BoltzmannMachines (RBMs)— the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However, future research in applications of DBNs is hampered by the considerable computation that training requires. In this paper, we describe a novel architecture and FPGA implementation that accelerates the training of general RBMs in a scalable manner, with the goal of producing a system that machine learning researchers can use to investigate ever-larger networks. Our design uses a highly efficient, fully-pipelined architecture based on 16-bit arithmetic for performing RBM training on an FPGA. We show that only 16-bit arithmetic precision is necessary, and we consequently use embedded hardware multiply-and-add (MADD) units. We present performance results to show that a speedup of 25–30X can be achieved over an optimized software implementation on a high-end CPU.

A Scalable Correlator Architecture Based on Modular FPGA Hardware, Reuseable Gateware, and Data Packetization

ABSTRACT. A new generation of radio telescopes is achieving unprecedented levels of sensitivity and resolution, as well as increased agility and field of view, by employing high-performance digital signal-processing hardware to phase and correlate signals from large numbers of antennas. The computational demands of these imaging systems scale in proportion to BMN2 B M N 2 , where B B is the signal bandwidth, M M is the number of independent beams, and N N is the number of antennas. The specifications of many new arrays lead to demands in excess of tens of PetaOps per second. To meet this challenge, we have developed a general-purpose correlator architecture using standard 10-Gbit Ethernet switches to pass data between flexible hardware modules containing Field Programmable Gate Array (FPGA) chips. These chips are programmed using open-source signal-processing libraries that we have developed to be flexible, scalable, and chip-independent. This work reduces the time and cost of implementing a wide range of...

The Allen Telescope Array Fly's Eye Survey for Fast Radio Transients

The relatively unexplored fast radio transient parameter space is known to be home to a variety of interesting sources, including pulsars, pulsar giant pulses, and non-thermal emission from planetary magnetospheres. In addition, a variety of hypothesized but as-yet-unobserved phenomena such as primordial black hole evaporation and prompt emission associated with coalescing massive objects have been suggested. The 2007 announcement by Lorimer et al. of the detection of a bright (30 Jy) radio pulse that was inferred to be of extragalactic origin and the subsequent consternation have demonstrated both the need for wide-field surveys characterizing the fast-transient parameter space and the potential utility of bright radio pulses as probes of the interstellar medium and intergalactic medium. Here we present results from the 450 hr, 150 deg2 Flys Eye survey for bright dispersed radio pulses at the Allen Telescope Array (ATA). The Flys Eye Spectrometer produces 128 channel power spectra over a 209 MHz bandwidth, centered at 1430 MHz, on 44 independent signal paths originating with 30 independent ATA antennae. Data were dedispersed between 0 and 2000 pc cm–3 and searched for pulses with dispersion measures greater than 50 pc cm–3 between 625 μs and 5 s in duration. No pulses were detected in the survey, implying a limiting rate of less than 2 sky–1 hr–1 for 10 ms duration pulses having apparent energy densities greater than 440 kJy μs, or mean flux densities greater than 44 Jy. Here we present details of the instrument, experiment, and observations, including a discussion of our results in light of other single pulse searches.

A coherent Ising machine for 2000-node optimization problems

Taking the pulse of optimization Finding the optimum solution of multiparameter or multifunctional problems is important across many disciplines, but it can be computationally intensive. Many such problems defined as computationally difficult can be mathematically mapped onto the so-called Ising problem, which looks at finding the minimum energy configuration for an array of coupled spins. Inagaki et al. and McMahon et al. show that an optical processing approach based on a network of coupled optical pulses in a ring fiber can be used to model and optimize large-scale Ising systems. Such a scalable architecture could help to optimize solutions to a wide range of complex problems. Science, this issue pp. 603 and 614 An optical-based processor is developed to solve a broad class of complex optimization problems. The analysis and optimization of complex systems can be reduced to mathematical problems collectively known as combinatorial optimization. Many such problems can be mapped onto ground-state search problems of the Ising model, and various artificial spin systems are now emerging as promising approaches. However, physical Ising machines have suffered from limited numbers of spin-spin couplings because of implementations based on localized spins, resulting in severe scalability problems. We report a 2000-spin network with all-to-all spin-spin couplings. Using a measurement and feedback scheme, we coupled time-multiplexed degenerate optical parametric oscillators to implement maximum cut problems on arbitrary graph topologies with up to 2000 nodes. Our coherent Ising machine outperformed simulated annealing in terms of accuracy and computation time for a 2000-node complete graph.

A Large-Scale Architecture for Restricted Boltzmann Machines

Deep Belief Nets (DBNs) are an emerging application in the machine learning domain, which use Restricted Boltzmann Machines (RBMs) as their basic building block. Although small scale DBNs have shown great potential, the computational cost of RBM training has been a major challenge in scaling to large networks. In this paper we present a highly scalable architecture for Deep Belief Net processing on hardware systems that can handle hundreds of boards, if not more, of customized logic with near linear performance increase. We elucidate tradeoffs between flexibility in the neuron connections, and the hardware resources, such as memory and communication bandwidth, required to build a custom processor design that has optimal efficiency. We illustrate how our architecture can easily support sparse networks with dense regions of connections between neighboring sets of neurons, which is relevant to applications where there are obvious spatial correlations in the data, such as in image processing. We demonstrate the feasibility of our approach by implementing a multi-FPGA system. We show that a speedup of 46X-112X over an optimized single core CPU implementation can be achieved for a four-FPGA implementation.

New SETI Sky Surveys for Radio Pulses

Berkeley conducts 7 SETI programs at IR, visible and radio wavelengths. Here we review two of the newest e orts, Astropulse and Fly’s Eye. A variety of possible sources of microsecond to millisecond radio pulses have been suggested in the last several decades, among them such exotic events as evaporating primordial black holes, hyper-flares from neutron stars, emissions from cosmic strings or perhaps extraterrestrial civilizations, but to-date few searches have been conducted capable of detecting them. The recent announcement by Lorimer et al. of the detection of a powerful ( 30 Jy) and highly dispersed ( 375 cm 3 pc) radio pulse in Parkes multi-beam survey data has fueled additional interest in such phenomena. We are carrying out two searches in hopes of finding and characterizing these uS to mS time scale dispersed radio pulses. These two observing programs are orthogonal in search space; the Allen Telescope Array’s (ATA) ”Fly’s Eye” experiment observes a 100 square degree field by pointing each 6m ATA antenna in a di erent direction; by contrast, the Astropulse sky survey at Arecibo is extremely sensitive but has 1/3,000 of the instantaneous sky coverage. Astropulse’s multibeam data is transferred via the internet to the computers of millions of volunteers. These computers perform a coherent de-dispersion analysis faster than the fastest available supercomputers and allow us to resolve pulses as short as 400 nS. Overall, the Astropulse survey will be 30 times more sensitive than the best previous searches. Analysis of results from Astropulse is at a very early stage. The Fly’s Eye was successfully installed at the ATA in December of 2007, and to-date approximately 450 hours of observation has been performed. We have detected three pulsars (B0329+54, B0355+54, B0950+08) and six giant pulses from the Crab pulsar in our diagnostic pointing data. We have not yet detected any other convincing bursts of astronomical origin in our survey data.