On the obfuscatability of quantum point functions

Cryptographic Primitives that Resist Backdooring and Subversion

People today, in addition to their concerns about getting old and having to go through watching themselves grow weak and wrinkly, are facing an increasing fear of dementia. There are around 47 million people affected by dementia worldwide and the cost associated with providing them health and social care support is estimated to reach 2 trillion by 2030 which is almost equivalent to the 18th largest economy in the world. The most common form of dementia with the highest costs in health and social care is Alzheimer’s disease, which gradually kills neurons and causes patients to lose loving memories, the ability to recognise family members, childhood memories, and even the ability to follow simple instructions. Alzheimer’s disease is irreversible, unstoppable and has no known cure. Besides being a calamity to affected patients, it is a great financial burden on health providers. Health care providers also face a challenge in diagnosing the disease as current methods used to diagnose Alzheimer’s disease rely on manual evaluations of a patient’s medical history and mental examinations such as the Mini-Mental State Examination. These diagnostic methods often give a false diagnosis and were designed to identify Alzheimer’s after stage two when the part of all symptoms are evident. The problem is that clinicians are unable to stop or control the progress of Alzheimer’s disease, because of a lack of knowledge on the patterns that triggered the development of the disease. In this thesis, we explored and investigated Alzheimer’s disease from a computational perspective to uncover different risk factors and present a strategic framework called Early Prediction of Alzheimer’s Disease Framework (EPADf) that would give a future prediction of early-onset Alzheimer’s disease. Following extensive background research that resulted in the formalisation of the framework concept, prediction approaches, and the concept of ranking the risk factors based on clinical instinct, knowledge and experience using mathematical reasoning, we carried out experiments to get further insight and investigate the disease further using machine learning models. In this study, we used machine learning models and conducted two classification experiments for early prediction of Alzheimer’s disease, and one ranking experiment to rank its risk factors by importance. Besides these experiments, we also presented two logical approaches to search for patterns in an Alzheimer’s dataset, and a ranking algorithm to rank Alzheimer’s disease risk factors based on clinical evaluation. For the classification experiments we used five different Machine Learning models; Random Forest (RF), Random Oracle Model (ROM), a hybrid model combined of Levenberg-Marquardt neural network and Random Forest, combined using Fischer discriminate analysis (H2), Linear Neural Networks (LNN), and Multi-layer Perceptron Model (MLP). These models were deployed on a de-identified multivariable patient’s data, provided by the ADNI (Alzheimer’s disease Neuroimaging Initiative), to illustrate the effective use of data analysis to investigate Alzheimer’s disease biological and behavioural risk factors. We found that the continues enhancement of patient’s data and the use of combined machine learning models can provide an early cost-effective prediction of Alzheimer’s disease, and help in extracting insightful information on the risk factors of the disease. Based on this work and findings we have developed the strategic framework (EPADf) which is discussed in more depth in this thesis.

We construct a quantum circuit for Shor's factoring algorithm that uses 2n + 2 qubits,where n is the length of the number to be factored. The depth and size of the circuitare O(n3) and O(n3 log n),...

This article discusses the overlap between social history and medical history. The aim is to use the study of medical history to contribute to a better understanding of social history. Five points are discussed: 1. Understanding the body The concept of the circulation of the chi through the living body was central to Chinese medical theory rather than the study of anatomy through dissection. 2. The relationship between those who treated the sick: Shamans, Taoists and Confucians in Chinese history. Before Western medicine was introduced into China, the social background of those who treated the sick was different at different stages of Chinese history. At the earliest stage, before the Warring States, those who treated the sick had much in common with Shamans, from the Warring States until the T'ang Dynasty doctors were usually Taoists, and from the T'ang onward, doctors generally held Confucian beliefs. 3. Sexual health, pediatrics and health care in old age as family history. These include ideas about contraception, pregnancy, ways to influence the sex of a fetus, child-rearing and maintaining health in old age. All these can be seen as aspects of family history. 4. Medicine and cultural influence In this article I concentrate on the Indian influence on Chinese medicine in the medieval period: from the Indian system China only adopted technical skill of ophthalmology and pharmacopoeia. 5. Medical treatment reflecting social mentality I discuss the belief that supernatural beings influenced people's health and the use of methods such as exorcism in treatment.

Ionic liquids (ILs) hold great promise in many fields including energy storage and generation, mechanical, pharmaceutical, synthetic and separation applications to name just a few. For any given application, the desired physical properties of the ideal IL may differ substantially from others and no widely applicable patterns or trends to facilitate intuitive design. The origins of physical properties lie in the characteristics of the intermolecular energetics, which consist of a complex interplay between electrostatic and dispersion forces. This thesis investigates and develops computational methodologies for calculating a reliable description of the intermolecular interactions for this challenging class of solvents and electrolytes of the future. The electrostatic approximation used in classical molecular dynamics (MD) where atomic partial charges are assigned was investigated in terms of methods based on density matrix partitioning, and the restrained electrostatic potentials (RESP) approaches. It was found that the “geodesic” atomic partial charge scheme, part of the RESP family, produced the most accurate charges. This was measured in terms of (a) charge convergence with increasing basis set size; (b) charge invariance with changes to the coordinate system; (c) insensitivity to minor structural changes on the resulting charges; (d) adequate capture of charge transfer effects; and (e) the preservation of symmetric of charges in symmetric molecules. Although charges can vary dramatically depending on the scheme used, the careful use of atomic partial charge schemes may still produce reliable forcefields, or at least serve as a rapid diagnostic tool to quantify electrostatic interactions and charge transfer. In moving towards unbiased a priori descriptions of IL intermolecular interactions, second-order Moller-Plesset perturbation theory (MP2) was used with the linear-scaling fragment molecular orbital (FMO) framework to assess the extent to which dispersion forces play a role in the intermolecular energetics. ILs of increasing size were examined such that the many-body effects may be captured. The dispersion energy contribution formed up to 20% of the total interaction energy. Furthermore, the interaction energy as produced by FMO was within 1 kJ mol−1 of the full-wavefunction MP2 interaction energy when three-body effects were included. As the dispersion interaction is purely a quantum mechanical phenomenon, correlated quantum mechanical methods, such as MP2 or coupled-cluster approaches, are required to provide an unbiased account of these effects. Ab initio methods such as MP2 and CCSD(T) scale formally as N⁵ an N⁷, respectively, with chemical system size. While the FMO approach provides a marked improvement in efficiency, the counterpoise (CP) approach to correcting the basis set superposition error (BSSE) is not amenable to fragmented approaches and requires each ion in the cluster to be calculated in the basis set of the entire system. In order to remove this bottleneck, the spin-component scaled second-order Moller Plesset perturbation theory (SCS-MP2) methodology was refined by fitting 174 non-CP corrected interaction energies at the MP2/cc-pVTZ level of theory to CP corrected CCSD(T)/CBS benchmark energies. This has resulted in an implicit BSSE correction that may be used within the highly efficient FMO framework, and is shown to yield results on par with or exceeding the accuracy of MP2/cc-pVQZ for clusters of two and four ion pairs (IPs). This new approach as been termed SCS-IL-MP2. An alternative dispersion corrected density functional theory (DFT) approach, DFT- D3, was assessed and refined in view of producing accurate interaction energies at the same CCSD(T)/CBS quality. The same test set of 174 ILs was used to fit the SCS-IL-MP2 approach was used to refit the DFT-D3 approach for both the Hartree-Fock (HF) wavefunction and the PBE and BLYP density functionals (DFs). In most cases, the selection of the DF and associated DFT-D version 3 (DFT-D3) parameters differed negligibly with all reaching within 1 to 2 kJ mol−1 per IP. HF-D3 parameters, on the other hand, showed a substantial improvement, particularly when used with the Becke-Johnson (BJ) damping function. Refitted HF-D3 and the BJ damping function was able to consistently provide interaction energy errors below 5 kJ mol−1 per IP. It would be worthwhile further investigating the application of the refined HF-D3 in its ability to produce reliable energies and geometries over a more diverse set of ILs. Both the SCS-IL-MP2 and new DFT-D3 approaches may be applied to the highly scal- able FMO framework. These form the core elements of the quantum chemistry toolbox for the study and understanding of the physicochemical properties of ILs that have so far been only superficially characterised by electronic structure theory. From this starting point, a rigorous and unbiased a priori understanding of the intermolecular interactions and resulting physicochemical properties may be predicted by means of efficient ab initio molecular dynamics (AIMD) techniques.

The two dimensional electron gas subjected to a perpendicular magnetic field is a model system that supports a variety of electronic phases. Perhaps the most well-known are the fractional quantum Hall states, but in recent years there has been an upsurge of interest in the charge ordered phases commonly referred to as electron solids. These solids are a consequence of electron-electron interactions in a magnetic field. While some solid phases form in the lowest Landau level, the charged ordered phases are most abundant in the higher Landau levels. Examples of such phases include the Wigner solids, electronic bubble phases and stripe or nematic phases. Open questions surround the exact role of disorder, confinement potential, temperature and the Landau level index in determining the stability and competition of these phases with other ground states. The interface of GaAs/AlGaAs remains the cleanest host for the two-dimensional electron gas due to the extremely high quality of materials available and the advancement in molecular beam epitaxy growth techniques. As a result, exceptionally high electron mobilities in this system have been instrumental in the discovery of numerous electron solids. In this Thesis, I discuss the discovery and properties of several electron solids that develop in such state-of-the-art two dimensional electron gases. These electron solids often develop at ultra low temperatures, in the milliKelvin temperature range. After an introduction to the physics of the quantum Hall effect in two dimensions, in chapter 3, I discuss electron solids developing in the N=1 Landau level. While these solids have been known for some time, details of the competition of these phases xiii with the nearby fractional quantum Hall states remains elusive. A number of reports observe new fractional quantum Hall states at filling factors where electron solids are found in other experiments. We undertook a systematic study to answer some of these unsettled questions. We see evidence for incipient fractional quantum Hall states at 2+2/7 and 2+5/7 at intermediate temperatures which are overtaken by the electronic bubble phases at lower temperatures. Several missing fractional states including those at filling factors 2+3/5, 2+3/7, 2+4/9 highlight the relative stability of the electronic solids called the bubble phases in the vicinity in our sample. In chapter 4, I discuss a newly seen electron crystal which manifests itself in transport measurements as a reentrant integer quantum Hall state. Reentrant integer behavior is common in high Landau levels, but so far it was not observed in the lowest Landau level in narrow quantum well samples. In contrast to high Landau levels, where such reentrant integer behavior was associated with electronic bubbles, we believe that the same signature in the N=0 Landau level is due to an electronic Wigner crystal. The filling factors at which we observe such reentrance reveal that it is a crystal of holes, rather than electrons. The discovery of this reentrant integer state paints a complex picture of the interplay of the Wigner crystal and fractional quantum Hall states. Finally, in chapter 5, I discuss the observation of a novel phenomenon, that of reentrant fractional quantum Hall effect. In the lowest Landau level, we observe a fractional quantum Hall state, but as the field is increased, we see a deviation and then a return to quantization in the Hall resistance. Such a behavior indicates a novel electron solid. In contrast to the collective localization of electrons evidenced by the reentrant integer quantum Hall effect, such reentrance to a fractional Hall resistance clearly points to the involvement of composite fermion quasiparticles. This property thus distinguishes the ground state we observed as a solid formed of composite fermions. Such a solid phase is evidence for exotic electron-electron correlations at play which are clearly different from those in the traditional Wigner solid of electrons.

The importance of reliability and fault tolerance is paramount in quantum computation. This paper proposes a Fault Tolerance Algorithms and Methodologies (FTAM) assessment technique for quantum circuits, by adopting the saboteur-based Simulated Fault Injection methodology from classical computation. By drawing the inspiration from classical computation, the HDLs were employed for performing fault injection, due to their capacity of behavioral and structural circuit description, including hierarchical features. The cornerstone of this approach is the adaptation of the available quantum computation error models (with the quantum computing features and constraints) to the classical, HDL framework of the simulated fault injection techniques. The experimental simulated fault injection campaign results are consistent with the analytical assessments -from a qualitative point of view - but at the same time they provide a much realistic description.

Quantum computing promises an exponential speed-up of computation compared to what is nowadays achievable with classical computers. In this way, it enables the evaluation of more complex models and the breaching of current security algorithms. For the operation of a quantum system, many questions remain to be answered. Currently, there are several quantum technologies that promise to be both reliable and scalable, two features required for large scale quantum operations. Common to all technologies is the operating temperature that needs to be close to absolute zero, i.e. below 100 mK, to suppress environment noise and allow the quantum properties to become 'visible'.<br/><br/>In order for any quantum processor to be operated, a so-called quantum-classical interface is required for the quantum bit (qubit) read-out and control. This interface consists of various electronic blocks, such as analog-to-digital converters, digital-to-analog converters, mixers, amplifiers and a digital controller. Especially the analog blocks require effort to meet the noise and stability constraints as not to disturb the very sensitive qubits and allow reading of the tiny signals. As the qubits live in extremely deep-cryogenic temperatures, long wires interface the cryogenic with the room temperature environment, where most of the electronics is situated. However, for a scalable system, heat injection becomes a serious problem, with many wires between 300 K and sub-Kelvin. Furthermore, such amount of interconnects is challenging to mechanically place in a dilution refrigerator. <br/><br/>Therefore, in this work, we propose to implement the electronics not at room temperature, but at a temperature much closer to the qubits, for example at 4 K. This not only reduces significantly the wiring between room temperature and the qubits, but we can also benefit from lower electronic noise at such a temperature. The operation of conventional electronics almost 200°C below its normal temperature range is not trivial as device properties alter significantly and most circuits no longer operate as intended.<br/><br/>In CMOS processes, the main technology in the integrated electronics world, the behaviour of the transistors, required for the implementation of any circuit, deviates considerably at low temperatures. The transistor's threshold voltage goes up, the mobility increases and the subthreshold slope becomes steeper, to name just a few of these deviations. Although there are improvements in performance, there are also some counter effects, and characterization of the transistors is needed to observe the changes. Once devices are characterized at such low temperatures, new models can be built and circuits can be simulated and adapted to operate properly at cryogenic temperatures. Luckily, there are various commercially available devices that can already withstand the chills of cold. We demonstrated various commercially available devices, such as a field-programmable gate array (FPGA) implemented in a 28 nm CMOS process, to be operating without major concerns at 4~K. Its properties alter only slightly, within 5 to 10%, and all tested circuit implementations, working at 300~K, also worked at 4 K. <br/><br/>We combined both commercially available devices, that operate 200 K below their specified temperature range, with custom designed CMOS circuits to implement a cryogenic read-out platform for spin qubits. This system comprises amplifiers, an ADC, an FPGA, voltage regulators and a clock generator. It allows to amplify the tiny signal from the qubits and digitize it directly in the FPGA in order to process the data locally at 4~K. This system is one of the first systematic attempts at operating a part of the quantum-classical interface at cryogenic temperatures and forms the basis for future systems comprising the complete electronic interface for qubits to operate at such low temperatures. <br/><br/>One of the main problems to tackle for cryogenic electronic systems is their power consumption. Power budgets are simply limited to roughly 1 or 2 Watts at 4 K and exponentially lower at deeper cryogenic temperatures, thus limiting the size of large-scale electronic systems. Our approach of combined commercial and custom circuits will have to be steadily replaced by a single (custom) technology that meets both power and scalability constraints. One of the best candidates is CMOS, a technology that the industry has relied upon for several decades and benefits from many optimizations thanks to Moore's law.

Interacting electrons on material lattices can build up strong quantum correlations, which in turn can lead to the emergence of a wide range of novel and potentially useful magnetic and electronic material properties. Our understanding of this physics, however, is severely limited by the exponential growth in complexity with system size, which leads all classical methods to fall fundamentally short. In this thesis, I show how artificial lattices of conduction band electrons in semiconductors, so-called quantum dot arrays, can be used to directly emulate and therefore elucidate such Fermi-Hubbard physics. To this end, I focus on two approaches. A top-down approach allows to scale easily, but lacks to ability to control or measure individual sites. A bottom-up approach on the other hand utilizes the small devices employed by the community for qubit experiments, in which the control of individual sites is both a blessing and a curse. We address the issue of control to the point where mapping to relevant models is possible and efficiently calibrating larger devices becomes feasible. These results open up the inherently well-suited and scalable platform of quantum dots to emulate novel quantum states of matter.

A multiple round quantum dense coding scheme based on the quantum phase estimation algorithm is proposed and implemented in a three qubit nuclear magnetic resonance (NMR) quantum computer. Using anm+1 qubit system, Bod can transmit one of 2m+1 messages to Alice, through manipulating only one qubit and exchanging it between Alice and Bob form rounds. The information capacity is enhanced tom+1 bits as compared tom bits in a classical scheme. The scheme has been demonstrated in NMR system, and the experimental results show a good agreement between theory and experiment.

Computational complexity of uniform quantum circuit families and quantum Turing machines Communicated by O. Watanabe

Falls prevention education between older adults and healthcare providers during transition from hospital to community-living

Traditional electronic and communication devices operate by processing binary information encoded as bits. Such digital devices have led to the most advanced technologies that we encounter in our everyday lives and they influence virtually every aspect of our society. Nonetheless, there exists a much richer way to encode and process information. By encoding information in quantum mechanical states as qubits, phenomena such as coherence and entanglement can be harnessed to execute tasks that are intractable to digital devices. Under this paradigm, it should be possible to realize quantum computers, quantum communication networks and quantum sensors that outperform their classical counterparts. The electronic spin states of color-center defects in the semiconductor silicon carbide have recently emerged as promising qubit candidates. They have long-lived quantum coherence up to room temperature, they can be controlled with mature magnetic resonance techniques, and they have a built-in optical interface operating near the telecommunication bands. In this thesis I will present two of our contributions to this field. The first is the electric-field control of electron spin qubits. This development lays foundation for quantum electronics that operate via electrical gating, much like traditional electronics. The second is the universal control and entanglement of electron and nuclear spin qubits in an ensemble under ambient conditions. This development lays foundation for quantum devices that have a built-in redundancy and can operate in real-world conditions. Both developments represent important steps towards practical quantum devices in an electronic grade material.

We analyze simple quantum error detection and quantum error correction protocols relevant to current experiments with superconducting qubits. We show that for qubits with energy relaxation the repetitive $N$-qubit codes cannot be used for quantum error correction, but can be used for quantum error detection. In the latter case it is sufficient to use only two qubits for the encoding. In the analysis we demonstrate a useful technique of unraveling the qubit energy relaxation into ``relaxation'' and ``no relaxation'' scenarios. Also, we propose and numerically analyze several two-qubit algorithms for quantum error detection and correction, which can be readily realized at the present-day level of the phase qubit technology.

Balancing it out: the process by which midwifery students provide care to women following stillbirth in Papua New Guinea