A Programmable True Random Number Generator Using Commercial Quantum Computers

Random number generators (RNG) are essential elements in many cryptographic systems. True random number generators (TRNG) rely upon sources of randomness from natural processes such as those arising from quantum mechanics phenomena. We demonstrate that a quantum computer can serve as a high-quality, weakly random source for a generalized user-defined probability mass function (PMF). Specifically, QC measurement implements the process of variate sampling according to a user-specified PMF resulting in a word comprised of electronic bits that can then be processed by an extractor function to address inaccuracies due to non-ideal quantum gate operations and other system biases. We introduce an automated and flexible method for implementing a TRNG as a programmed quantum circuit that executes on commercially-available, gate-model quantum computers. The user specifies the desired word size as the number of qubits and a definition of the desired PMF. Based upon the user specification of the PMF, our compilation tool automatically synthesizes the desired TRNG as a structural OpenQASM file containing native gate operations that are optimized to reduce the circuit's quantum depth. The resulting TRNG provides multiple bits of randomness for each execution/measurement cycle; thus, the number of random bits produced in each execution is limited only by the size of the QC. We provide experimental results to illustrate the viability of this approach.Comment: 15 pages, 7 figures, SPIE Defense + Commercial Sensing: Quantum Information Science, Sensing, and Computation X

Automated Quantum Oracle Synthesis with a Minimal Number of Qubits

Several prominent quantum computing algorithms--including Grover's search algorithm and Shor's algorithm for finding the prime factorization of an integer--employ subcircuits termed 'oracles' that embed a specific instance of a mathematical function into a corresponding bijective function that is then realized as a quantum circuit representation. Designing oracles, and particularly, designing them to be optimized for a particular use case, can be a non-trivial task. For example, the challenge of implementing quantum circuits in the current era of NISQ-based quantum computers generally dictates that they should be designed with a minimal number of qubits, as larger qubit counts increase the likelihood that computations will fail due to one or more of the qubits decohering. However, some quantum circuits require that function domain values be preserved, which can preclude using the minimal number of qubits in the oracle circuit. Thus, quantum oracles must be designed with a particular application in mind. In this work, we present two methods for automatic quantum oracle synthesis. One of these methods uses a minimal number of qubits, while the other preserves the function domain values while also minimizing the overall required number of qubits. For each method, we describe known quantum circuit use cases, and illustrate implementation using an automated quantum compilation and optimization tool to synthesize oracles for a set of benchmark functions; we can then compare the methods with metrics including required qubit count and quantum circuit complexity.Comment: 18 pages, 10 figures, SPIE Defense + Commercial Sensing: Quantum Information Science, Sensing, and Computation X

Automated Synthesis of Quantum Subcircuits

The quantum computer has become contemporary reality, with the first two-qubit machine of mere decades ago transforming into cloud-accessible devices with tens, hundreds, or--in a few cases--even thousands of qubits. While such hardware is noisy and still relatively small, the increasing number of operable qubits raises another challenge: how to develop the now-sizeable quantum circuits executable on these machines. Preparing circuits manually for specifications of any meaningful size is at best tedious and at worst impossible, creating a need for automation. This article describes an automated quantum-software toolkit for synthesis, compilation, and optimization, which transforms classically-specified, irreversible functions to both technology-independent and technology-dependent quantum circuits. We also describe and analyze the toolkit's application to three situations--quantum read-only memories, quantum random number generators, and quantum oracles--and illustrate the toolkit's start-to-finish features from the input of classical functions to the output of quantum circuits ready-to-run on commercial hardware. Furthermore, we illustrate how the toolkit enables research beyond circuit synthesis, including comparison of synthesis and optimization methods and deeper understanding of even well-studied quantum algorithms. As quantum hardware continues to develop, such quantum circuit toolkits will play a critical role in realizing its potential.Comment: 49 pages, 25 figures, 20 table

Inelastic neutron scattering studies of methyl chloride synthesis over alumina

Not only is alumina the most widely used catalyst support material in the world, it is also an important catalyst in its own right. One major chemical process that uses alumina in this respect is the industrial production of methyl chloride. This is a large scale process (650 000 metric tons in 2010 in the United States), and a key feedstock in the production of silicones that are widely used as household sealants. In this Account, we show how, in partnership with conventional spectroscopic and reaction testing methods, inelastic neutron scattering (INS) spectroscopy can provide additional insight into the active sites present on the catalyst, as well as the intermediates present on the catalyst surface.<p></p> INS spectroscopy is a form of vibrational spectroscopy, where the spectral features are dominated by modes involving hydrogen. Because of this, most materials including alumina are largely transparent to neutrons. Advantageously, in this technique, the entire “mid-infrared”, 0–4000 cm<sup>–1</sup>, range is accessible; there is no cut-off at 1400 cm<sup>–1</sup> as in infrared spectroscopy. It is also straightforward to distinguish fundamental modes from overtones and combinations. <p></p> A key parameter in the catalyst’s activity is the surface acidity. In infrared spectroscopy of adsorbed pyridine, the shifts in the ring stretching modes are dependent on the strength of the acid site. However, there is a very limited spectral range available. We discuss how we can observe the low energy ring deformation modes of adsorbed pyridine by INS spectroscopy. These modes can undergo shifts that are as large as those seen with infrared inspectroscopy, potentially enabling finer discrimination between acid sites. <p></p> Surface hydroxyls play a key role in alumina catalysis, but in infrared spectroscopy, the presence of electrical anharmonicity complicates the interpretation of the O–H stretch region. In addition, the deformations lie below the infrared cut-off. Both of these limitations are irrelevant to INS spectroscopy, and all the modes are readily observable. When we add HCl to the catalyst surface, the acid causes changes in the spectra. We can then deduce both that the surface chlorination leads to enhanced Lewis acidity and that the hydroxyl group must be threefold coordinated. <p></p> When we react η-alumina with methanol, the catalyst forms a chemisorbed methoxy species. Infrared spectroscopy clearly shows its presence but also indicates the possible coexistence of a second species. Because of INS spectroscopy’s ability to discriminate between fundamental modes and combinations, we were able to unambiguously show that there is a single intermediate present on the surface of the active catalyst. This work represents a clear example where an understanding of the chemistry at the molecular level can help rationalize improvements in a large scale industrial process with both financial and environmental benefits. <p></p&gt

Shear strength properties of wet granular materials

We investigate shear strength properties of wet granular materials in the pendular state (i.e. the state where the liquid phase is discontinuous) as a function of water content. Sand and glass beads were wetted and tested in a direct shear cell and under various confining pressures. In parallel, we carried out three-dimensional molecular dynamics simulations by using an explicit equation expressing capillary force as a function of interparticle distance, water bridge volume and surface tension. We show that, due to the peculiar features of capillary interactions, the major influence of water content over the shear strength stems from the distribution of liquid bonds. This property results in shear strength saturation as a function of water content. We arrive at the same conclusion by a microscopic analysis of the shear strength. We propose a model that accounts for the capillary force, the granular texture and particle size polydispersity. We find fairly good agreement of the theoretical estimate of the shear strength with both experimental data and simulations. From numerical data, we analyze the connectivity and anisotropy of different classes of liquid bonds according to the sign and level of the normal force as well as the bond direction. We find that weak compressive bonds are almost isotropically distributed whereas strong compressive and tensile bonds have a pronounced anisotropy. The probability distribution function of normal forces is exponentially decreasing for strong compressive bonds, a decreasing power-law function over nearly one decade for weak compressive bonds and an increasing linear function in the range of tensile bonds. These features suggest that different bond classes do not play the same role with respect to the shear strength.Comment: 12 page

Rasch analysis of the hospital anxiety and depression scale (hads) for use in motor neurone disease

<p>Abstract</p> <p>Background</p> <p>The Hospital Anxiety and Depression Scale (HADS) is commonly used to assess symptoms of anxiety and depression in motor neurone disease (MND). The measure has never been specifically validated for use within this population, despite questions raised about the scale's validity. This study seeks to analyse the construct validity of the HADS in MND by fitting its data to the Rasch model.</p> <p>Methods</p> <p>The scale was administered to 298 patients with MND. Scale assessment included model fit, differential item functioning (DIF), unidimensionality, local dependency and category threshold analysis.</p> <p>Results</p> <p>Rasch analyses were carried out on the HADS total score as well as depression and anxiety subscales (HADS-T, D and A respectively). After removing one item from both of the seven item scales, it was possible to produce modified HADS-A and HADS-D scales which fit the Rasch model. An 11-item higher-order HADS-T total scale was found to fit the Rasch model following the removal of one further item.</p> <p>Conclusion</p> <p>Our results suggest that a modified HADS-A and HADS-D are unidimensional, free of DIF and have good fit to the Rasch model in this population. As such they are suitable for use in MND clinics or research. The use of the modified HADS-T as a higher-order measure of psychological distress was supported by our data. Revised cut-off points are given for the modified HADS-A and HADS-D subscales.</p

Internal states of model isotropic granular packings. III. Elastic properties

In this third and final paper of a series, elastic properties of numerically simulated isotropic packings of spherical beads assembled by different procedures and subjected to a varying confining pressure P are investigated. In addition P, which determines the stiffness of contacts by Hertz's law, elastic moduli are chiefly sensitive to the coordination number, the possible values of which are not necessarily correlated with the density. Comparisons of numerical and experimental results for glass beads in the 10kPa-10MPa range reveal similar differences between dry samples compacted by vibrations and lubricated packings. The greater stiffness of the latter, in spite of their lower density, can hence be attributed to a larger coordination number. Voigt and Reuss bounds bracket bulk modulus B accurately, but simple estimation schemes fail for shear modulus G, especially in poorly coordinated configurations under low P. Tenuous, fragile networks respond differently to changes in load direction, as compared to load intensity. The shear modulus, in poorly coordinated packings, tends to vary proportionally to the degree of force indeterminacy per unit volume. The elastic range extends to small strain intervals, in agreement with experimental observations. The origins of nonelastic response are discussed. We conclude that elastic moduli provide access to mechanically important information about coordination numbers, which escape direct measurement techniques, and indicate further perspectives.Comment: Published in Physical Review E 25 page