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2022-04-19
Higher-order modulations in the skyrmion-lattice phase of Cu$_2$OSeO$_3$
Using small angle neutron scattering, we have investigated higher-order peaks in the skyrmion-lattice phase of Cu$_2$OSeO$_3$, in which two different skyrmion lattices, SkX1 and SkX2, are known to form. For each skyrmion-lattice phase, we observed two sets of symmetrically inequivalent peaks at the higher-order-reflection positions with the indices $(110)$ and $(200)$. Under the condition where the SkX1 and SkX2 coexist, we confirmed the absence of the scattering at $\mathbf{Q}$ positions combining reflections from the two phases, indicating a significantly weak double-scattering component. Detailed analysis of the peak profile, as well as the temperature and magnetic-field dependence of the peak intensity, also supports the intrinsic higher-order modulation rather than the parasitic double scattering. The two higher-order modulations show contrasting magnetic-field dependence; the former $(110)$ increases as the field is increased, whereas the latter $(200)$ decreases. This indicates that, in Cu$_2$OSeO$_3$, skyrmions are weakly distorted, and the distortion is field-dependent in a way that the dominant higher-order modulation switches from $(110)$ to $(200)$ under field. Monte Carlo simulations under sweeping external magnetic field qualitatively reproduce the observed magnetic-field dependence, and suggests that the higher-order modulations correspond to the superlattices of weak swirlings appearing in the middle of the original triangular-latticed skyrmions.
2204.08614v1
2022-04-19
Emu: A Case Study for TDI-like Imaging for Infrared Observation from Space
A wide-field zenith-looking telescope operating in a mode similar to Time-Delay-Integration (TDI) or drift scan imaging can perform an infrared sky survey without active pointing control but it requires a high-speed, low-noise infrared detector. Operating from a hosted payload platform on the International Space Station (ISS), the Emu space telescope employs the paradigm-changing properties of the Leonardo SAPHIRA electron avalanche photodiode array to provide powerful new observations of cool stars at the critical water absorption wavelength (1.4 $\mu$m) largely inaccessible to ground-based telescopes due to the Earth's own atmosphere. Cool stars, especially those of spectral-type M, are important probes across contemporary astrophysics, from the formation history of the Galaxy to the formation of rocky exoplanets. Main sequence M-dwarf stars are the most abundant stars in the Galaxy and evolved M-giant stars are some of the most distant stars that can be individually observed. The Emu sky survey will deliver critical stellar properties of these cool stars by inferring oxygen abundances via measurement of the water absorption band strength at 1.4 $\mu$m. Here we present the TDI-like imaging capability of Emu mission, its science objectives, instrument details and simulation results.
2204.08713v2
2022-05-05
Photon emissivity of the quark-gluon plasma: a lattice QCD analysis of the transverse channel
We present results for the thermal photon emissivity of the quark-gluon plasma derived from spatially transverse vector correlators computed in lattice QCD at a temperature of 250 MeV. The analysis of the spectral functions, performed at fixed spatial momentum, is based on continuum-extrapolated correlators obtained with two flavours of dynamical Wilson fermions. We compare the next-to-leading order perturbative QCD correlators, as well as the ${\cal N}=4$ supersymmetric Yang-Mills correlators at infinite coupling, to the correlators from lattice QCD and find them to lie within $\sim10\%$ of each other. We then refine the comparison, performing it at the level of filtered spectral functions obtained model-independently via the Backus-Gilbert method. Motivated by these studies, for frequencies $\omega\lesssim2.5\,$GeV we use fit ans\"atze to the spectral functions that perform well when applied to mock data generated from the NLO QCD or from the strongly-coupled SYM spectral functions, while the high-frequency part, $\omega\gtrsim 2.5\,$GeV, is matched to NLO QCD. We compare our results for the photon emissivity to our previous analysis of a different vector channel at the same temperature. We obtain the most stringent constraint at photon momenta around $k\simeq0.8\,$GeV, for which we find a differential photon emission rate per unit volume of $d\Gamma_\gamma/d^3k = (\alpha_{\rm em}/(\exp(k/T)-1))\times (2.2 \pm 0.8 ) \times 10^{-3}\,{\rm GeV}$.
2205.02821v1
2022-05-17
Highlighting relations between Wave-particle duality, Uncertainty principle, Phase space and Microstates
Wave-particle duality is often considered as the modern answer to the problem of the nature of light after more than 2000 years of questioning. It is also the answer given by quantum physics concerning the nature of matter particles and any other radiations. The main objective of this work is to analyze the relations that are existing between this concept of wave-particle duality, the uncertainty principle and the concepts of phase space and microstates considered in statistical mechanics. It is mainly highlighted that while the concepts of phase space and microstates were already introduced in classical physics before the discovery of the wave-particle duality, a correct understanding of them cannot be achieved without the use of the concept of quantum phase space and phase space representation of quantum mechanics which are directly related to the uncertainty principle. The possibility of using these concepts of quantum phase space and phase space representations of quantum mechanics to help in a deeper description of the wave-particle duality and in the study of some current issues related to foundational problems of quantum mechanics like quantum decoherence and the measurement problem is also discussed.
2205.08538v4
2022-05-26
New Explicit Good Linear Sum-Rank-Metric Codes
Sum-rank-metric codes have wide applications in universal error correction, multishot network coding, space-time coding and the construction of partial-MDS codes for repair in distributed storage. Fundamental properties of sum-rank-metric codes have been studied and some explicit or probabilistic constructions of good sum-rank-metric codes have been proposed. In this paper we give three simple constructions of explicit linear sum-rank-metric codes. In finite length regime, numerous larger linear sum-rank-metric codes with the same minimum sum-rank distances as the previous constructed codes can be derived from our constructions. For example several better linear sum-rank-metric codes over ${\bf F}_q$ with small block sizes and the matrix size $2 \times 2$ are constructed for $q=2, 3, 4$ by applying our construction to the presently known best linear codes. Asymptotically our constructed sum-rank-metric codes are close to the Gilbert-Varshamov-like bound on sum-rank-metric codes for some parameters. Finally we construct a linear MSRD code over an arbitrary finite field ${\bf F}_q$ with various square matrix sizes $n_1, n_2, \ldots, n_t$ satisfying $n_i \geq n_{i+1}^2+\cdots+n_t^2$ , $i=1, 2, \ldots, t-1$, for any given minimum sum-rank distance. There is no restriction on the block lengths $t$ and parameters $N=n_1+\cdots+n_t$ of these linear MSRD codes from the sizes of the fields ${\bf F}_q$. \end{abstract}
2205.13087v8
2022-06-17
Multi-scale Super-resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness
Magnetic Resonance Spectroscopic Imaging (MRSI) is a valuable tool for studying metabolic activities in the human body, but the current applications are limited to low spatial resolutions. The existing deep learning-based MRSI super-resolution methods require training a separate network for each upscaling factor, which is time-consuming and memory inefficient. We tackle this multi-scale super-resolution problem using a Filter Scaling strategy that modulates the convolution filters based on the upscaling factor, such that a single network can be used for various upscaling factors. Observing that each metabolite has distinct spatial characteristics, we also modulate the network based on the specific metabolite. Furthermore, our network is conditioned on the weight of adversarial loss so that the perceptual sharpness of the super-resolved metabolic maps can be adjusted within a single network. We incorporate these network conditionings using a novel Multi-Conditional Module. The experiments were carried out on a 1H-MRSI dataset from 15 high-grade glioma patients. Results indicate that the proposed network achieves the best performance among several multi-scale super-resolution methods and can provide super-resolved metabolic maps with adjustable sharpness.
2206.08984v1
2022-06-20
How to Assess Trustworthy AI in Practice
This report is a methodological reflection on Z-Inspection$^{\small{\circledR}}$. Z-Inspection$^{\small{\circledR}}$ is a holistic process used to evaluate the trustworthiness of AI-based technologies at different stages of the AI lifecycle. It focuses, in particular, on the identification and discussion of ethical issues and tensions through the elaboration of socio-technical scenarios. It uses the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI. This report illustrates for both AI researchers and AI practitioners how the EU HLEG guidelines for trustworthy AI can be applied in practice. We share the lessons learned from conducting a series of independent assessments to evaluate the trustworthiness of AI systems in healthcare. We also share key recommendations and practical suggestions on how to ensure a rigorous trustworthy AI assessment throughout the life-cycle of an AI system.
2206.09887v2
2022-06-23
LRPC codes with multiple syndromes: near ideal-size KEMs without ideals
We introduce a new rank-based key encapsulation mechanism (KEM) with public key and ciphertext sizes around 3.5 Kbytes each, for 128 bits of security, without using ideal structures. Such structures allow to compress objects, but give reductions to specific problems whose security is potentially weaker than for unstructured problems. To the best of our knowledge, our scheme improves in size all the existing unstructured post-quantum lattice or code-based algorithms such as FrodoKEM or Classic McEliece. Our technique, whose efficiency relies on properties of rank metric, is to build upon existing Low Rank Parity Check (LRPC) code-based KEMs and to send multiple syndromes in one ciphertext, allowing to reduce the parameters and still obtain an acceptable decoding failure rate. Our system relies on the hardness of the Rank Support Learning problem, a well-known variant of the Rank Syndrome Decoding problem. The gain on parameters is enough to significantly close the gap between ideal and non-ideal constructions. It enables to choose an error weight close to the rank Gilbert-Varshamov bound, which is a relatively harder zone for algebraic attacks. We also give a version of our KEM that keeps an ideal structure and permits to roughly divide the bandwidth by two compared to previous versions of LRPC KEMs submitted to the NIST with a Decoding Failure Rate (DFR) of $2^{-128}$.
2206.11961v1
2022-07-08
Rate-Optimal Streaming Codes Over the Three-Node Decode-And-Forward Relay Network
In this paper, we study the three-node Decode-and-Forward (D&F) relay network subject to random and burst packet erasures. The source wishes to transmit an infinite stream of packets to the destination via the relay. The three-node D&F relay network is constrained by a decoding delay of T packets, i.e., the packet transmitted by the source at time i must be decoded by the destination by time i+T. For the individual channels from source to relay and relay to destination, we assume a delay-constrained sliding-window (DCSW) based packet-erasure model that can be viewed as a tractable approximation to the commonly-accepted Gilbert-Elliot channel model. Under the model, any time-window of width w contains either up to a random erasure or else erasure burst of length at most b (>= a). Thus the source-relay and relay-destination channels are modeled as (a_1, b_1, w_1, T_1) and (a_2, b_2, w_2, T_2) DCSW channels. We first derive an upper bound on the capacity of the three-node D&F relay network. We then show that the upper bound is tight for the parameter regime: max{b_1, b_2}|(T-b_1-b_2-max{a_1, a_2}+1), a1=a2 OR b1=b2 by constructing streaming codes achieving the bound. The code construction requires field size linear in T, and has decoding complexity equivalent to that of decoding an MDS code.
2207.04025v2
2022-07-12
Diversity of ghost notes in tubas, euphoniums and saxhorns
The ghost note is a natural note which can be played exclusively on bass brass instruments with a predominantly-expanding bore profile such as tubas, euphoniums or saxhorns. It stands between the pedal note-the lowest natural note playable, or first regime-and the instrument's second regime. However, if the interval between the pedal note and the second regime remains close to an octave regardless of the instrument, the interval between the pedal note and the ghost note vary from a minor third to a perfect fourth. References about this note are very scarce, and it is not commonly known among tuba players.This study shows that an elementary brass model describing the player coupled to the instrument is capable of bringing both the ghost and the pedal note to light. Here, we adopt a dynamical systems point of view and perform a bifurcation analysis using a software of numerical continuation. The numerical results provided in terms of frequency intervals between pedal note and ghost note are compared with frequency intervals experimentally inferred from recordings of seven different types of tuba, each of them being played by two professional tuba players.
2207.05395v3
2022-07-20
Flow-based Visual Quality Enhancer for Super-resolution Magnetic Resonance Spectroscopic Imaging
Magnetic Resonance Spectroscopic Imaging (MRSI) is an essential tool for quantifying metabolites in the body, but the low spatial resolution limits its clinical applications. Deep learning-based super-resolution methods provided promising results for improving the spatial resolution of MRSI, but the super-resolved images are often blurry compared to the experimentally-acquired high-resolution images. Attempts have been made with the generative adversarial networks to improve the image visual quality. In this work, we consider another type of generative model, the flow-based model, of which the training is more stable and interpretable compared to the adversarial networks. Specifically, we propose a flow-based enhancer network to improve the visual quality of super-resolution MRSI. Different from previous flow-based models, our enhancer network incorporates anatomical information from additional image modalities (MRI) and uses a learnable base distribution. In addition, we impose a guide loss and a data-consistency loss to encourage the network to generate images with high visual quality while maintaining high fidelity. Experiments on a 1H-MRSI dataset acquired from 25 high-grade glioma patients indicate that our enhancer network outperforms the adversarial networks and the baseline flow-based methods. Our method also allows visual quality adjustment and uncertainty estimation.
2207.10181v1
2022-07-24
Contention Resolution for Coded Radio Networks
Randomized backoff protocols, such as exponential backoff, are a powerful tool for managing access to a shared resource, often a wireless communication channel (e.g., [1]). For a wireless device to transmit successfully, it uses a backoff protocol to ensure exclusive access to the channel. Modern radios, however, do not need exclusive access to the channel to communicate; in particular, they have the ability to receive useful information even when more than one device transmits at the same time. These capabilities have now been exploited for many years by systems that rely on interference cancellation, physical layer network coding and analog network coding to improve efficiency. For example, Zigzag decoding [56] demonstrated how a base station can decode messages sent by multiple devices simultaneously. In this paper, we address the following question: Can we design a backoff protocol that is better than exponential backoff when exclusive channel access is not required. We define the Coded Radio Network Model, which generalizes traditional radio network models (e.g., [30]). We then introduce the Decodable Backoff Algorithm, a randomized backoff protocol that achieves an optimal throughput of $1-o(1)$. (Throughput $1$ is optimal, as simultaneous reception does not increase the channel capacity.) The algorithm breaks the constant throughput lower bound for traditional radio networks [47-49], showing the power of these new hardware capabilities.
2207.11824v1
2022-07-25
Control of dephasing in spin qubits during coherent transport in silicon
One of the key pathways towards scalability of spin-based quantum computing systems lies in achieving long-range interactions between electrons and increasing their inter-connectivity. Coherent spin transport is one of the most promising strategies to achieve this architectural advantage. Experimental results have previously demonstrated high fidelity transportation of spin qubits between two quantum dots in silicon and identified possible sources of error. In this theoretical study, we investigate these errors and analyze the impact of tunnel coupling, magnetic field and spin-orbit effects on the spin transfer process. The interplay between these effects gives rise to double dot configurations that include regimes of enhanced decoherence that should be avoided for quantum information processing. These conclusions permit us to extrapolate previous experimental conclusions and rationalize the future design of large scale quantum processors.
2207.11865v2
2022-07-29
Orthogonal Spin Current Injected Magnetic Tunnel Junction for Convolutional Neural Networks
We propose that a spin Hall effect driven magnetic tunnel junction device can be engineered to provide a continuous change in the resistance across it when injected with orthogonal spin currents. Using this concept, we develop a hybrid device-circuit simulation platform to design a network that realizes multiple functionalities of a convolutional neural network. At the atomistic level, we use the Keldysh non-equilibrium Green's function technique that is coupled self-consistently with the stochastic Landau-Lifshitz-Gilbert-Slonczewski equations, which in turn is coupled with the HSPICE circuit simulator. We demonstrate the simultaneous functionality of the proposed network to evaluate the rectified linear unit and max-pooling functionalities. We present a detailed power and error analysis of the designed network against the thermal stability factor of the free ferromagnets. Our results show that there exists a non-trivial power-error trade-off in the proposed network, which enables an energy-efficient network design based on unstable free ferromagnets with reliable outputs. The static power for the proposed ReLU circuit is $0.56\mu W$ and whereas the energy cost of a nine-input rectified linear unit-max-pooling network with an unstable free ferromagnet($\Delta=15$) is $3.4pJ$ in the worst-case scenario. We also rationalize the magnetization stability of the proposed device by analyzing the vanishing torque gradient points.
2207.14603v3
2022-08-09
Good locally repairable codes via propagation rules
In classical coding theory, it is common to construct new codes via propagation rules. There are various propagation rules to construct classical block codes. However, propagation rules have not been extensively explored for constructions of locally repairable codes. In this paper, we introduce a few propagation rules to construct good locally repairable codes. To our surprise, these simple propagation rules produce a few interesting results. Firstly, by concatenating a locally repairable code as an inner code with a classical block code as an outer code, we obtain quite a few dimension-optimal binary locally repairable codes. Secondly, from this concatenation, we explicitly build a family of locally repairable codes that exceeds the Zyablov-type bound. Thirdly, by a lengthening propagation rule that adds some rows and columns from a parity-check matrix of a given linear code, we are able to produce a family of dimension-optimal binary locally repairable codes from the extended Hamming codes, and to convert a classical maximum distance separable (MDS) code into a Singleton-optimal locally repairable code. Furthermore, via the lengthening propagation rule, we greatly simplify the construction of a family of locally repairable codes in \cite[Theorem 5]{MX20} that breaks the asymptotic Gilbert-Varshamov bound. In addition, we make use of three other propagation rules to produce more dimension-optimal binary locally repairable codes. Finally, one of phenomena that we observe in this paper is that some trivial propagation rules in classical block codes do not hold anymore for locally repairable codes.
2208.04484v1
2022-08-10
Forward volume magnetoacoustic spin wave excitation with micron-scale spatial resolution
The interaction between surface acoustic waves (SAWs) and spin waves (SWs) in a piezoelectric-magnetic thin film heterostructure yields potential for the realization of novel microwave devices and applications in magnonics. In the present work, we characterize magnetoacoustic waves in three adjacent magnetic micro-stripes made from CoFe+Ga, CoFe, and CoFe+Pt with a single pair of tapered interdigital transducers (TIDTs). The magnetic micro-stripes were deposited by focused electron beam-induced deposition (FEBID) and focused ion beam-induced deposition (FIBID) direct-writing techniques. The transmission characteristics of the TIDTs are leveraged to selectively address the individual micro-stripes. Here, the external magnetic field is continuously rotated out of the plane of the magnetic thin film and the forward volume SW geometry is probed with the external magnetic field along the film normal. Our experimental findings are well explained by an extended phenomenological model based on a modified Landau-Lifshitz-Gilbert approach that considers SWs with nonzero wave vectors. Magnetoelastic excitation of forward volume SWs is possible because of the vertical shear strain $\varepsilon_{xz}$ of the Rayleigh-type SAW.
2208.05205v1
2022-08-29
Programmable photonic integrated meshes for modular generation of optical entanglement links
Large-scale generation of quantum entanglement between individually controllable qubits is at the core of quantum computing, communications, and sensing. Modular architectures of remotely-connected quantum technologies have been proposed for a variety of physical qubits, with demonstrations reported in atomic and all-photonic systems. However, an open challenge in these architectures lies in constructing high-speed and high-fidelity reconfigurable photonic networks for optically-heralded entanglement among target qubits. Here we introduce a programmable photonic integrated circuit (PIC), realized in a piezo-actuated silicon nitride (SiN)-in-oxide CMOS-compatible process, that implements an N x N Mach-Zehnder mesh (MZM) capable of high-speed execution of linear optical transformations. The visible-spectrum photonic integrated mesh is programmed to generate optical connectivity on up to N = 8 inputs for a range of optically-heralded entanglement protocols. In particular, we experimentally demonstrated optical connections between 16 independent pairwise mode couplings through the MZM, with optical transformation fidelities averaging 0.991 +/- 0.0063. The PIC's reconfigurable optical connectivity suffices for the production of 8-qubit resource states as building blocks of larger topological cluster states for quantum computing. Our programmable PIC platform enables the fast and scalable optical switching technology necessary for network-based quantum information processors.
2208.13911v1
2022-09-15
Almost Ramanujan Expanders from Arbitrary Expanders via Operator Amplification
We give an efficient algorithm that transforms any bounded degree expander graph into another that achieves almost optimal (namely, near-quadratic, $d \leq 1/\lambda^{2+o(1)}$) trade-off between (any desired) spectral expansion $\lambda$ and degree $d$. Furthermore, the algorithm is local: every vertex can compute its new neighbors as a subset of its original neighborhood of radius $O(\log(1/\lambda))$. The optimal quadratic trade-off is known as the Ramanujan bound, so our construction gives almost Ramanujan expanders from arbitrary expanders. The locality of the transformation preserves structural properties of the original graph, and thus has many consequences. Applied to Cayley graphs, our transformation shows that any expanding finite group has almost Ramanujan expanding generators. Similarly, one can obtain almost optimal explicit constructions of quantum expanders, dimension expanders, monotone expanders, etc., from existing (suboptimal) constructions of such objects. Another consequence is a "derandomized" random walk on the original (suboptimal) expander with almost optimal convergence rate. Our transformation also applies when the degree is not bounded or the expansion is not constant. We obtain our results by a generalization of Ta-Shma's technique in his breakthrough paper [STOC 2017], used to obtain explicit almost optimal binary codes. Specifically, our spectral amplification extends Ta-Shma's analysis of bias amplification from scalars to matrices of arbitrary dimension in a very natural way. Curiously, while Ta-Shma's explicit bias amplification derandomizes a well-known probabilistic argument (underlying the Gilbert--Varshamov bound), there seems to be no known probabilistic (or other existential) way of achieving our explicit ("high-dimensional") spectral amplification.
2209.07024v1
2022-09-15
An analytical study of the MHD clamshell instability on a sphere
This paper studies the instability of two-dimensional magnetohydrodynamic (MHD) systems on a sphere using analytical methods. The underlying flow consists of a zonal differential rotation and a toroidal magnetic field is present. Semicircle rules that prescribe the possible domain of the wave velocity in the complex plane for general flow and field profiles are derived. The paper then sets out an analytical study of the `clamshell instability', which features field lines on the two hemispheres tilting in opposite directions (Cally 2001, Sol. Phys. vol. 199, pp. 231--249). An asymptotic solution for the instability problem is derived for the limit of weak shear of the zonal flow, via the method of matched asymptotic expansions. It is shown that when the zonal flow is solid body rotation, there exists a neutral mode that tilts the magnetic field lines, referred to as the `tilting mode'. A weak shear of the zonal flow excites the critical layer of the tilting mode, which reverses the tilting direction to form the clamshell pattern and induces the instability. The asymptotic solution provides insights into properties of the instability for a range of flow and field profiles. A remarkable feature is that the magnetic field affects the instability only through its local behaviour in the critical layer.
2209.07349v1
2022-09-15
$\tilde{O}(n+\mathrm{poly}(k))$-time Algorithm for Bounded Tree Edit Distance
Computing the edit distance of two strings is one of the most basic problems in computer science and combinatorial optimization. Tree edit distance is a natural generalization of edit distance in which the task is to compute a measure of dissimilarity between two (unweighted) rooted trees with node labels. Perhaps the most notable recent application of tree edit distance is in NoSQL big databases, such as MongoDB, where each row of the database is a JSON document represented as a labeled rooted tree, and finding dissimilarity between two rows is a basic operation. Until recently, the fastest algorithm for tree edit distance ran in cubic time (Demaine, Mozes, Rossman, Weimann; TALG'10); however, Mao (FOCS'21) broke the cubic barrier for the tree edit distance problem using fast matrix multiplication. Given a parameter $k$ as an upper bound on the distance, an $O(n+k^2)$-time algorithm for edit distance has been known since the 1980s due to the works of Myers (Algorithmica'86) and Landau and Vishkin (JCSS'88). The existence of an $\tilde{O}(n+\mathrm{poly}(k))$-time algorithm for tree edit distance has been posed as an open question, e.g., by Akmal and Jin (ICALP'21), who gave a state-of-the-art $\tilde{O}(nk^2)$-time algorithm. In this paper, we answer this question positively.
2209.07524v1
2022-09-23
Multiplexed control of spin quantum memories in a photonic circuit
A central goal in many quantum information processing applications is a network of quantum memories that can be entangled with each other while being individually controlled and measured with high fidelity. This goal has motivated the development of programmable photonic integrated circuits (PICs) with integrated spin quantum memories using diamond color center spin-photon interfaces. However, this approach introduces a challenge in the microwave control of individual spins within closely packed registers. Here, we present a quantum-memory-integrated photonics platform capable of (i) the integration of multiple diamond color center spins into a cryogenically compatible, high-speed programmable PIC platform; (ii) selective manipulation of individual spin qubits addressed via tunable magnetic field gradients; and (iii) simultaneous control of multiple qubits using numerically optimized microwave pulse shaping. The combination of localized optical control, enabled by the PIC platform, together with selective spin manipulation opens the path to scalable quantum networks on intra-chip and inter-chip platforms.
2209.11853v2
2022-09-26
A detailed star formation history for the extremely diffuse Andromeda XIX dwarf galaxy
We present deep imaging of the ultra-diffuse Andromeda XIX dwarf galaxy from the Advance Camera for Surveys on the Hubble Space Telescope which resolves its stellar populations to below the oldest main sequence turn-off. We derive a full star formation history for the galaxy using MATCH, and find no evidence of star formation in the past 8 Gyr. We calculate a quenching time of $\tau_{90}=9.7\pm0.2$~Gyr, suggesting Andromeda~XIX ceased forming stars very early on. This early quenching, combined with its extremely large half-light radius, low density dark matter halo and lower than expected metallicity make it a unique galaxy within the Local Group and raises questions about how it formed. The early quenching time allows us to rule out feedback from bursty star formation as a means to explain its diffuse stellar population and low density dark matter halo. We find that the extended stellar population, low density halo and star formation could be explained by either tidal interactions (such as tidal shocking) or by late dry mergers, with the latter also explaining its low metallicity. Proper motions and detailed abundances would allow us to distinguish between these two scenarios.
2209.12912v1
2022-10-06
Scalable photonic integrated circuits for programmable control of atomic systems
Advances in laser technology have driven discoveries in atomic, molecular, and optical (AMO) physics and emerging applications, from quantum computers with cold atoms or ions, to quantum networks with solid-state color centers. This progress is motivating the development of a new generation of "programmable optical control" systems, characterized by criteria (C1) visible (VIS) and near-infrared (IR) wavelength operation, (C2) large channel counts extensible beyond 1000s of individually addressable atoms, (C3) high intensity modulation extinction and (C4) repeatability compatible with low gate errors, and (C5) fast switching times. Here, we address these challenges by introducing an atom control architecture based on VIS-IR photonic integrated circuit (PIC) technology. Based on a complementary metal-oxide-semiconductor (CMOS) fabrication process, this Atom-control PIC (APIC) technology meets the system requirements (C1)-(C5). As a proof of concept, we demonstrate a 16-channel silicon nitride based APIC with (5.8$\pm$0.4) ns response times and -30 dB extinction ratio at a wavelength of 780 nm. This work demonstrates the suitability of PIC technology for quantum control, opening a path towards scalable quantum information processing based on optically-programmable atomic systems.
2210.03100v2
2022-10-10
Andreev processes in mesoscopic multi-terminal graphene Josephson junctions
There is growing interest in using multi-terminal Josephson junctions (MTJJs) as a platform to artificially emulate topological phases and to investigate complex superconducting mechanisms such as quartet and multiplet Cooper pairings. Current experimental signatures in MTJJs have led to conflicting interpretations of the salient features. In this work, we report a collaborative experimental and theoretical investigation of graphene-based four-terminal Josephson junctions. We observe resonant features in the differential resistance maps that resemble those ascribed to multiplet Cooper pairings. To understand these features, we model our junctions using a circuit network of coupled two-terminal resistively and capacitively shunted junctions (RCSJs). Under appropriate bias current, the model predicts that a current flowing between two diagonal terminals in a four-terminal geometry may be represented as a sinusoidal function of a weighted sum of the superconducting phases. We show that starting from a semi-classical model with diffusive current-phase relations, the MTJJ effectively emulates a general form of the expected current-phase relation for multiplet Cooper pairings. Our study therefore suggests that differential resistance measurements alone are insufficient to conclusively distinguish resonant Andreev reflection processes from semi-classical circuit-network effects.
2210.04408v3
2022-10-10
Infrared Remote Sensing Using Low Noise Avalanche Photodiode Detector
For a remote sensing optical payload to achieve a Ground Sampling Distance of ~ 10-30 m, a critical problem is platform-induced motion blur. While forward motion compensation can reduce this transit speed, it comes at the expense of a more challenging satellite attitude control system and induces a variable observation/illumination angle. This relative motion can be frozen out by simply reading the sensor system at a frame rate that matches the ground resolution element's pixel crossing time. To achieve high resolution using this Time-Delay Integration (TDI)-like approach requires high speed and hence near "zero" readout noise detector arrays to avoid swamping the observed signal. This requires associated control electronics for fast frame readout and direct interface with smart- Artificial Intelligence (AI) onboard processing. With this technique, the platform freezes out its movement concerning the ground, reducing the demands placed on the attitude control systems, which can otherwise be difficult to implement on a small satellite platform. Here we report the Australian National University's OzFuel mission which applies this technical solution to deliver high ground resolution via high frame rate imaging. OzFuel is built around the Leonardo SAPHIRA Mercury Cadmium Telluride linear mode electron avalanche photodiode (LMeAPD) detector and the in-house developed Rosella electronics control system. The mission will deliver an integrated sensor system in a suite of Short-Wave Infrared (SWIR) passbands dedicated to monitoring the flammability of Eucalypt trees. The OzFuel mission concept focuses on the application of SWIR remote sensing data to deliver a strategic evaluation of fuel loads and moisture content in the bushfire-prone Australian environment.
2210.04770v1
2022-10-17
On construction of quantum codes with dual-containing quasi-cyclic codes
One of the main objectives of quantum error-correction theory is to construct quantum codes with optimal parameters and properties. In this paper, we propose a class of 2-generator quasi-cyclic codes and study their applications in the construction of quantum codes over small fields. Firstly, some sufficient conditions for these 2-generator quasi-cyclic codes to be dual-containing concerning Hermitian inner product are determined. Then, we utilize these Hermitian dual-containing quasi-cyclic codes to produce quantum codes via the famous Hermitian construction. Moreover, we present a lower bound on the minimum distance of these quasi-cyclic codes, which is helpful to construct quantum codes with larger lengths and dimensions. As the computational results, many new quantum codes that exceed the quantum Gilbert-Varshamov bound are constructed over $F_q$, where $q$ is $2,3,4,5$. In particular, 16 binary quantum codes raise the lower bound on the minimum distance in Grassl's table \cite{Grassl:codetables}. In nonbinary cases, many quantum codes are new or have better parameters than those in the literature.
2210.08716v1
2022-10-18
Intense γ-photon and high-energy electron production by neutron irradiation: effects of nuclear excitations on reactor materials
The effects of neutron irradiation on materials are often interpreted in terms of atomic recoils, initiated by neutron impacts and producing crystal lattice defects. In addition, there is a remarkable two-step process, strongly pronounced in the medium-weight and heavy elements. This process involves the generation of energetic {\gamma} photons in nonelastic collisions of neutrons with atomic nuclei, achieved via capture and inelastic reactions. Subsequently, high-energy electrons are excited through the scattering of {\gamma} photons by the atomic electrons. We derive and validate equations enabling a fast and robust evaluation of photon and electron fluxes produced by the neutrons in the bulk of materials. The two-step n-{\gamma}-e scattering creates a nonequilibrium dynamically fluctuating steady-state population of high-energy electrons, with the spectra of photon and electron energies extending well into the mega-electron-volt range. This stimulates vacancy diffusion through electron-triggered atomic recoils, primarily involving vacancy-impurity dissociation, even if thermal activation is ineffective. Tungsten converts the energy of fusion or fission neutrons into a flux of {\gamma} radiation at the conversion efficiency approaching 99%, with implications for structural materials, superconductors, and insulators, as well as phenomena like corrosion, and helium and hydrogen isotope retention.
2210.09667v2
2022-11-06
A framework for leveraging machine learning tools to estimate personalized survival curves
The conditional survival function of a time-to-event outcome subject to censoring and truncation is a common target of estimation in survival analysis. This parameter may be of scientific interest and also often appears as a nuisance in nonparametric and semiparametric problems. In addition to classical parametric and semiparametric methods (e.g., based on the Cox proportional hazards model), flexible machine learning approaches have been developed to estimate the conditional survival function. However, many of these methods are either implicitly or explicitly targeted toward risk stratification rather than overall survival function estimation. Others apply only to discrete-time settings or require inverse probability of censoring weights, which can be as difficult to estimate as the outcome survival function itself. Here, we employ a decomposition of the conditional survival function in terms of observable regression models in which censoring and truncation play no role. This allows application of an array of flexible regression and classification methods rather than only approaches that explicitly handle the complexities inherent to survival data. We outline estimation procedures based on this decomposition, empirically assess their performance, and demonstrate their use on data from an HIV vaccine trial.
2211.03031v4
2022-11-14
High-resolution single-shot spiral diffusion-weighted imaging at 7T using expanded encoding with compressed sensing
Purpose: The expanded encoding model incorporates spatially- and time-varying field perturbations for correction during reconstruction. So far, these reconstructions have used the conjugate gradient method with early stopping used as implicit regularization. However, this approach is likely suboptimal for low-SNR cases like diffusion or high-resolution MRI. Here, we investigate the extent that l1-wavelet regularization, or equivalently compressed sensing (CS), combined with expanded encoding improves trade-offs between spatial resolution, readout time and SNR for single-shot spiral diffusion-weighted imaging at 7T. The reconstructions were performed using our open-source GPU-enabled reconstruction toolbox, MatMRI, that allows inclusion of the different components of the expanded encoding model, with or without CS. Methods: In vivo accelerated single-shot spirals were acquired with five acceleration factors (2-6) and three in-plane spatial resolutions (1.5, 1.3, and 1.1 mm). From the in vivo reconstructions, we estimated diffusion tensors and computed fractional anisotropy maps. Then, simulations were used to quantitatively investigate and validate the impact of CS-based regularization on image quality when compared to a known ground truth. Results: In vivo reconstructions revealed improved image quality with retainment of small features when CS was used. Simulations showed that the joint use of the expanded encoding model and CS improves accuracy of image reconstructions (reduced mean-squared error) over the range of acceleration factors investigated. Conclusion: The expanded encoding model and CS regularization are complementary tools for single-shot spiral diffusion MRI, which enables both higher spatial resolutions and higher acceleration factors.
2211.07532v1
2022-11-17
On universal butterfly and antisymmetric magnetoresistances
Butterfly magnetoresistance (BMR) and antisymmetric magnetoresistance (ASMR) are about a butterfly-cross curve and a curve with one peak and one valley when a magnetic field is swept up and down along a fixed direction. Other than the parallelogram-shaped magnetoresistance-curve (MR-curve) often observed in magnetic memory devices, BMR and ASMR are two ubiquitous types of MR-curves observed in diversified magnetic systems, including van der Waals materials, strongly correlated systems, and traditional magnets. Here, we reveal the general principles and the picture behind the BMR and the ASMR that do not depend on the detailed mechanisms of magnetoresistance: 1) The systems exhibit hysteresis loops, common for most magnetic materials with coercivities. 2) The magnetoresistance of the magnetic structures in a large positive magnetic field and in a large negative magnetic field is approximately the same. With the generalized Ohm's law in magnetic materials, these principles explain why most BMR appears in the longitudinal resistance measurements and is very rare in the Hall resistance measurements. Simple toy models, in which the Landau-Lifshitz-Gilbert equation governs magnetization, are used to demonstrate the principles and explain the appearance and disappearance of BMR in various experiments. Our finding provides a simple picture to understand magnetoresistance-related experiments.
2211.09369v1
2022-12-22
Photon production rate from Transverse-Longitudinal ($T-L$) mesonic correlator on the lattice
Thermal photons from the QGP provide important information about the interaction among plasma constituents. The photon production rate from a thermally equilibrated system is proportional to the transverse spectral function $\rho_T(\omega=|\vec k|, \vec k)$. One can also calculate the photon production rate from the difference between $\rho_T(\omega,\vec k)$ (transverse) and $\rho_L(\omega,\vec k)$ (longitudinal) projections, as $\rho_L$ vanishes on the photon point. Because the UV part of $\rho_T-\rho_L$ is suppressed, the corresponding Euclidean correlator receives most of its contribution from the IR part. We calculate the $T\!-\!L$ correlator on $N_f=2+1$ flavour HISQ configurations with $m_l=m_s/5$ at temperature of about $1.15\,T_{pc}$ (220 MeV). We have used two ans\"{a}tze for the spectral function: 1) A polynomial connected to the UV region consistent with OPE expansion and 2) a hydro-inspired spectral function. We have also applied the Backus-Gilbert method to estimate the spectral function. All these different approaches are combined to estimate the photon production rate.
2212.11509v2
2023-01-12
Incremental Dead State Detection in Logarithmic Time
Identifying live and dead states in an abstract transition system is a recurring problem in formal verification; for example, it arises in our recent work on efficiently deciding regex constraints in SMT. However, state-of-the-art graph algorithms for maintaining reachability information incrementally (that is, as states are visited and before the entire state space is explored) assume that new edges can be added from any state at any time, whereas in many applications, outgoing edges are added from each state as it is explored. To formalize the latter situation, we propose guided incremental digraphs (GIDs), incremental graphs which support labeling closed states (states which will not receive further outgoing edges). Our main result is that dead state detection in GIDs is solvable in $O(\log m)$ amortized time per edge for $m$ edges, improving upon $O(\sqrt{m})$ per edge due to Bender, Fineman, Gilbert, and Tarjan (BFGT) for general incremental directed graphs. We introduce two algorithms for GIDs: one establishing the logarithmic time bound, and a second algorithm to explore a lazy heuristics-based approach. To enable an apples-to-apples experimental comparison, we implemented both algorithms, two simpler baselines, and the state-of-the-art BFGT baseline using a common directed graph interface in Rust. Our evaluation shows $110$-$530$x speedups over BFGT for the largest input graphs over a range of graph classes, random graphs, and graphs arising from regex benchmarks.
2301.05308v2
2023-01-23
Correction of high-order phase variation effects in dynamic field monitoring
Purpose: Field monitoring measures field perturbations, which can be accounted for during image reconstructions. In certain field monitoring environments, significant phase deviations can arise far from isocenter due to the finite extent of the gradient and/or main magnet. This can degrade the accuracy of field dynamics when field probes are placed near or outside the diameter spherical volume of the gradient coils and/or main magnet, leading to corrupted image quality. The objective of this work was to develop a correction algorithm that reduces errors from highly nonlinear phase variations at distant field probes in field dynamic fits. Methods: The algorithm is split into three components. Component one fits phase coefficients one spatial order at a time, while the second implements a weighted least squares solution based on probe distance. After initial fitting, component three calculates phase residuals and removes the phase for distant probes before re-fitting. Two healthy volunteers were scanned on a head-only 7T MRI using diffusion-weighted single-shot spiral and EPI sequences and field monitoring was performed. Images were reconstructed with and without phase coefficient correction and compared qualitatively. Results: The algorithm was able to correct corrupted field dynamics, resulting in image quality improvements. Significant artefact reduction was observed when correcting higher order fits, especially for diffusion weighted images. Stepwise fitting provided the most correction benefit, which was marginally improved when adding weighted least squares and phase residual corrections. Conclusion: The proposed algorithm can mitigate effects of phase errors in field monitoring, providing improved reliability of field dynamic characterization.
2301.09726v1
2023-02-07
Computational capability for physical reservoir computing using a spin-torque oscillator with two free layers
A numerical analysis on the computational capability of physical reservoir computing utilizing a spin-torque oscillator with two free layers is reported. Conventional spintronics devices usually consist of two ferromagnets, where the direction of magnetization in one layer, called the free layer, can move while that of the other, the reference layer, is fixed. Recently, however, devices with two free layers, where the reference layer is replaced by another free layer, have been developed for various practical applications. Adding another free layer drastically changes the dynamical response of the device through the couplings via the spin-transfer effect and the dipole magnetic field. A numerical simulation of the Landau-Lifshitz-Gilbert equation and a statistical analyses of the Lyapunov exponent and the synchronization index reveal the appearance of an amplitude-modulated oscillation and chaos in the oscillators with two free layers. Such complex dynamics qualitatively change the computational capability of physical reservoir computing because the computational resource is dynamics of the physical system. An evaluation of the short-term memory capacity clarifies that oscillators with two free layers have a larger capacity than those of conventional oscillators. An enhancement in capacity near the edge of echo state property, i.e., the boundary between zero and finite synchronization index, is also found.
2302.03769v1
2023-02-13
Ultra-bright single photon source based on an atomically thin material
Solid-state single photon sources are central building blocks in quantum communication networks and on-chip quantum information processing. Atomically thin crystals were established as possible candidates to emit non-classical states of light, however, the performance of monolayer-based single photon sources has so far been lacking behind state-of-the-art devices based on volume crystals. Here, we implement a single photon source based on an atomically thin sheet of WSe2 coupled to a spectrally tunable optical cavity. It is characterized by a high single photon purity with a $g^{(2)}(0)$ value as low as $4.7 \pm 0.7 \%$ and a record-high first lens brightness of linearly polarized photons as large as $65 \pm 4 \%$. Interestingly, the high performance of our devices allows us to observe genuine quantum interference phenomena in a Hong-Ou-Mandel experiment. Our results demonstrate that open cavities and two-dimensional materials constitute an excellent platform for ultra-bright quantum light sources: the unique properties of such two-dimensional materials and the versatility of open cavities open an inspiring avenue for novel quantum optoelectronic devices.
2302.06340v1
2023-02-21
A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific qualities (and quantities) of generated output. Prompts are also a form of programming that can customize the outputs and interactions with an LLM. This paper describes a catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs. Prompt patterns are a knowledge transfer method analogous to software patterns since they provide reusable solutions to common problems faced in a particular context, i.e., output generation and interaction when working with LLMs. This paper provides the following contributions to research on prompt engineering that apply LLMs to automate software development tasks. First, it provides a framework for documenting patterns for structuring prompts to solve a range of problems so that they can be adapted to different domains. Second, it presents a catalog of patterns that have been applied successfully to improve the outputs of LLM conversations. Third, it explains how prompts can be built from multiple patterns and illustrates prompt patterns that benefit from combination with other prompt patterns.
2302.11382v1
2023-03-11
Power efficient ReLU design for neuromorphic computing using spin Hall effect
We demonstrate a magnetic tunnel junction injected with spin Hall current to exhibit linear rotation of magnetization of the free-ferromagnet using only the spin current. Using the linear resistance change of the MTJ, we devise a circuit for the rectified linear activation (ReLU) function of the artificial neuron. We explore the role of different spin Hall effect (SHE) heavy metal layers on the power consumption of the ReLU circuit. We benchmark the power consumption of the ReLU circuit with different SHE layers by defining a new parameter called the spin Hall power factor. It combines the spin Hall angle, resistivity, and thickness of the heavy metal layer, which translates to the power consumption of the different SHE layers during spin-orbit switching/rotation of the free FM. We employ a hybrid spintronics-CMOS simulation framework that couples Keldysh non-equilibrium Green's function formalism with Landau-Lifshitz-Gilbert-Slonzewski equations and the HSPICE circuit simulator to account for diverse physics of spin-transport and the CMOS elements in our proposed ReLU design. We also demonstrate the robustness of the proposed ReLU circuit against thermal noise and non-trivial power-error trade-off that enables the use of an unstable free-ferromagnet for energy-efficient design. Using the proposed circuit, we evaluate the performance of the convolutional neural network for MNIST datasets and demonstrate comparable classification accuracies to the ideal ReLU with an energy consumption of 75 $pJ$ per sample.
2303.06463v1
2023-03-28
Optimal Scheduling Policies for Remote Estimation of Autoregressive Markov Processes over Time-Correlated Fading Channel
We consider the problem of transmission scheduling for the remote estimation of a discrete-time autoregressive Markov process that is driven by white Gaussian noise. A sensor observes this process, and then decides to either encode the current state of this process into a data packet and attempts to transmit it to the estimator over an unreliable wireless channel modeled as a Gilbert-Elliott channel, or does not send any update. Each transmission attempt consumes $\lambda$ units of transmission power, and the remote estimator is assumed to be linear. The channel state is revealed only via the feedback (ACK\slash NACK) of a transmission, and hence the channel state is not revealed if no transmission occurs. The goal of the scheduler is to minimize the expected value of an infinite-horizon cumulative discounted cost, in which the instantaneous cost is composed of the following two quantities: (i)~squared estimation error, (ii) transmission power. We show that this problem can equivalently be posed as a partially observable Markov decision process (POMDP), in which the scheduler maintains a belief about the current state of the channel, and makes decisions on the basis of the current value of the estimation error, and the belief state.~We then show that the optimal policy is of threshold-type, i.e. for each value of the estimation error $e$, there is a threshold $b\ust(e)$ such that when the error is equal to $e$, then it is optimal to transmit only when the current belief state is greater than $b\ust(e)$.
2303.16285v1
2023-04-14
Study on Soft Robotic Pinniped Locomotion
Legged locomotion is a highly promising but under-researched subfield within the field of soft robotics. The compliant limbs of soft-limbed robots offer numerous benefits, including the ability to regulate impacts, tolerate falls, and navigate through tight spaces. These robots have the potential to be used for various applications, such as search and rescue, inspection, surveillance, and more. The state-of-the-art still faces many challenges, including limited degrees of freedom, a lack of diversity in gait trajectories, insufficient limb dexterity, and limited payload capabilities. To address these challenges, we develop a modular soft-limbed robot that can mimic the locomotion of pinnipeds. By using a modular design approach, we aim to create a robot that has improved degrees of freedom, gait trajectory diversity, limb dexterity, and payload capabilities. We derive a complete floating-base kinematic model of the proposed robot and use it to generate and experimentally validate a variety of locomotion gaits. Results show that the proposed robot is capable of replicating these gaits effectively. We compare the locomotion trajectories under different gait parameters against our modeling results to demonstrate the validity of our proposed gait models.
2304.06945v1
2023-04-19
Local object crop collision network for efficient simulation of non-convex objects in GPU-based simulators
Our goal is to develop an efficient contact detection algorithm for large-scale GPU-based simulation of non-convex objects. Current GPU-based simulators such as IsaacGym and Brax must trade-off speed with fidelity, generality, or both when simulating non-convex objects. Their main issue lies in contact detection (CD): existing CD algorithms, such as Gilbert-Johnson-Keerthi (GJK), must trade off their computational speed with accuracy which becomes expensive as the number of collisions among non-convex objects increases. We propose a data-driven approach for CD, whose accuracy depends only on the quality and quantity of offline dataset rather than online computation time. Unlike GJK, our method inherently has a uniform computational flow, which facilitates efficient GPU usage based on advanced compilers such as XLA (Accelerated Linear Algebra). Further, we offer a data-efficient solution by learning the patterns of colliding local crop object shapes, rather than global object shapes which are harder to learn. We demonstrate our approach improves the efficiency of existing CD methods by a factor of 5-10 for non-convex objects with comparable accuracy. Using the previous work on contact resolution for a neural-network-based contact detector, we integrate our CD algorithm into the open-source GPU-based simulator, Brax, and show that we can improve the efficiency over IsaacGym and generality over standard Brax. We highly recommend the videos of our simulator included in the supplementary materials.
2304.09439v2
2023-04-25
Semantic Compression With Large Language Models
The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks. However, in addition to confidently presenting factually inaccurate information at times (known as "hallucinations"), LLMs are also inherently limited by the number of input and output tokens that can be processed at once, making them potentially less effective on tasks that require processing a large set or continuous stream of information. A common approach to reducing the size of data is through lossless or lossy compression. Yet, in some cases it may not be strictly necessary to perfectly recover every detail from the original data, as long as a requisite level of semantic precision or intent is conveyed. This paper presents three contributions to research on LLMs. First, we present the results from experiments exploring the viability of approximate compression using LLMs, focusing specifically on GPT-3.5 and GPT-4 via ChatGPT interfaces. Second, we investigate and quantify the capability of LLMs to compress text and code, as well as to recall and manipulate compressed representations of prompts. Third, we present two novel metrics -- Exact Reconstructive Effectiveness (ERE) and Semantic Reconstruction Effectiveness (SRE) -- that quantify the level of preserved intent between text compressed and decompressed by the LLMs we studied. Our initial results indicate that GPT-4 can effectively compress and reconstruct text while preserving the semantic essence of the original text, providing a path to leverage $\sim$5$\times$ more tokens than present limits allow.
2304.12512v1
2023-04-28
Optimal majority rules and quantitative Condorcet properties of setwise Kemeny voting schemes
The important Kemeny problem, which consists of computing median consensus rankings of an election with respect to the Kemeny voting rule, admits important applications in biology and computational social choice and was generalized recently via an interesting setwise approach by Gilbert et. al. Our first results establish optimal quantitative extensions of the Unanimity property and the well-known $3/4$-majority rule of Betzler et al. for the classical Kemeny median problem. Moreover, by elaborating an exhaustive list of quantified axiomatic properties (such as the Condorcet and Smith criteria, the $5/6$-majority rule, etc.) of the $3$-wise Kemeny rule where not only pairwise comparisons but also the discordance between the winners of subsets of three candidates are also taken into account, we come to the conclusion that the $3$-wise Kemeny voting scheme induced by the $3$-wise Kendall-tau distance presents interesting advantages in comparison with the classical Kemeny rule. For example, it satisfies several improved manipulation-proof properties. Since the $3$-wise Kemeny problem is NP-hard, our results also provide some of the first useful space reduction techniques by determining the relative orders of pairs of alternatives. Our works suggest similar interesting properties of higher setwise Kemeny voting schemes which justify and compensate for the more expensive computational cost than the classical Kemeny scheme.
2304.14980v1
2023-05-25
Packaging code for reproducible research in the public sector
The effective and ethical use of data to inform decision-making offers huge value to the public sector, especially when delivered by transparent, reproducible, and robust data processing workflows. One way that governments are unlocking this value is through making their data publicly available, allowing more people and organisations to derive insights. However, open data is not enough in many cases: publicly available datasets need to be accessible in an analysis-ready form from popular data science tools, such as R and Python, for them to realise their full potential. This paper explores ways to maximise the impact of open data with reference to a case study of packaging code to facilitate reproducible analysis. We present the jtstats project, which consists of R and Python packages for importing, processing, and visualising large and complex datasets representing journey times, for many modes and purposes at multiple geographic levels, released by the UK Department of Transport. jtstats shows how domain specific packages can enable reproducible research within the public sector and beyond, saving duplicated effort and reducing the risks of errors from repeated analyses. We hope that the jtstats project inspires others, particularly those in the public sector, to add value to their data sets by making them more accessible.
2305.16205v1
2023-05-25
COMPLETE: A flagship mission for complete understanding of 3D coronal magnetic energy release
COMPLETE is a flagship mission concept combining broadband spectroscopic imaging and comprehensive magnetography from multiple viewpoints around the Sun to enable tomographic reconstruction of 3D coronal magnetic fields and associated dynamic plasma properties, which provide direct diagnostics of energy release. COMPLETE re-imagines the paradigm for solar remote-sensing observations through purposefully co-optimized detectors distributed on multiple spacecraft that operate as a single observatory, linked by a comprehensive data/model assimilation strategy to unify individual observations into a single physical framework. We describe COMPLETE's science goals, instruments, and mission implementation. With targeted investment by NASA, COMPLETE is feasible for launch in 2032 to observe around the maximum of Solar Cycle 26.
2305.16533v1
2023-05-25
Magnetic Energy Powers the Corona: How We Can Understand its 3D Storage & Release
The coronal magnetic field is the prime driver behind many as-yet unsolved mysteries: solar eruptions, coronal heating, and the solar wind, to name a few. It is, however, still poorly observed and understood. We highlight key questions related to magnetic energy storage, release, and transport in the solar corona, and their relationship to these important problems. We advocate for new and multi-point co-optimized measurements, sensitive to magnetic field and other plasma parameters, spanning from optical to $\gamma$-ray wavelengths, to bring closure to these long-standing and fundamental questions. We discuss how our approach can fully describe the 3D magnetic field, embedded plasma, particle energization, and their joint evolution to achieve these objectives.
2305.17146v1
2023-05-27
Optimization's Neglected Normative Commitments
Optimization is offered as an objective approach to resolving complex, real-world decisions involving uncertainty and conflicting interests. It drives business strategies as well as public policies and, increasingly, lies at the heart of sophisticated machine learning systems. A paradigm used to approach potentially high-stakes decisions, optimization relies on abstracting the real world to a set of decision(s), objective(s) and constraint(s). Drawing from the modeling process and a range of actual cases, this paper describes the normative choices and assumptions that are necessarily part of using optimization. It then identifies six emergent problems that may be neglected: 1) Misspecified values can yield optimizations that omit certain imperatives altogether or incorporate them incorrectly as a constraint or as part of the objective, 2) Problematic decision boundaries can lead to faulty modularity assumptions and feedback loops, 3) Failing to account for multiple agents' divergent goals and decisions can lead to policies that serve only certain narrow interests, 4) Mislabeling and mismeasurement can introduce bias and imprecision, 5) Faulty use of relaxation and approximation methods, unaccompanied by formal characterizations and guarantees, can severely impede applicability, and 6) Treating optimization as a justification for action, without specifying the necessary contextual information, can lead to ethically dubious or faulty decisions. Suggestions are given to further understand and curb the harms that can arise when optimization is used wrongfully.
2305.17465v2
2023-05-30
Hardness of Approximation in PSPACE and Separation Results for Pebble Games
We consider the pebble game on DAGs with bounded fan-in introduced in [Paterson and Hewitt '70] and the reversible version of this game in [Bennett '89], and study the question of how hard it is to decide exactly or approximately the number of pebbles needed for a given DAG in these games. We prove that the problem of eciding whether $s$~pebbles suffice to reversibly pebble a DAG $G$ is PSPACE-complete, as was previously shown for the standard pebble game in [Gilbert, Lengauer and Tarjan '80]. Via two different graph product constructions we then strengthen these results to establish that both standard and reversible pebbling space are PSPACE-hard to approximate to within any additive constant. To the best of our knowledge, these are the first hardness of approximation results for pebble games in an unrestricted setting (even for polynomial time). Also, since [Chan '13] proved that reversible pebbling is equivalent to the games in [Dymond and Tompa '85] and [Raz and McKenzie '99], our results apply to the Dymond--Tompa and Raz--McKenzie games as well, and from the same paper it follows that resolution depth is PSPACE-hard to determine up to any additive constant. We also obtain a multiplicative logarithmic separation between reversible and standard pebbling space. This improves on the additive logarithmic separation previously known and could plausibly be tight, although we are not able to prove this. We leave as an interesting open problem whether our additive hardness of approximation result could be strengthened to a multiplicative bound if the computational resources are decreased from polynomial space to the more common setting of polynomial time.
2305.19104v1
2023-06-01
Every Bit Counts in Consensus
Consensus enables n processes to agree on a common valid L-bit value, despite t < n/3 processes being faulty and acting arbitrarily. A long line of work has been dedicated to improving the worst-case communication complexity of consensus in partial synchrony. This has recently culminated in the worst-case word complexity of O(n^2). However, the worst-case bit complexity of the best solution is still O(n^2 L + n^2 kappa) (where kappa is the security parameter), far from the \Omega(n L + n^2) lower bound. The gap is significant given the practical use of consensus primitives, where values typically consist of batches of large size (L > n). This paper shows how to narrow the aforementioned gap while achieving optimal linear latency. Namely, we present a new algorithm, DARE (Disperse, Agree, REtrieve), that improves upon the O(n^2 L) term via a novel dispersal primitive. DARE achieves O(n^{1.5} L + n^{2.5} kappa) bit complexity, an effective sqrt{n}-factor improvement over the state-of-the-art (when L > n kappa). Moreover, we show that employing heavier cryptographic primitives, namely STARK proofs, allows us to devise DARE-Stark, a version of DARE which achieves the near-optimal bit complexity of O(n L + n^2 poly(kappa)). Both DARE and DARE-Stark achieve optimal O(n) latency.
2306.00431v2
2023-06-12
Accountability Infrastructure: How to implement limits on platform optimization to protect population health
Attention capitalism has generated design processes and product development decisions that prioritize platform growth over all other considerations. To the extent limits have been placed on these incentives, interventions have primarily taken the form of content moderation. While moderation is important for what we call "acute harms," societal-scale harms -- such as negative effects on mental health and social trust -- require new forms of institutional transparency and scientific investigation, which we group under the term accountability infrastructure. This is not a new problem. In fact, there are many conceptual lessons and implementation approaches for accountability infrastructure within the history of public health. After reviewing these insights, we reinterpret the societal harms generated by technology platforms through reference to public health. To that end, we present a novel mechanism design framework and practical measurement methods for that framework. The proposed approach is iterative and built into the product design process, and is applicable for both internally-motivated (i.e. self regulation by companies) and externally-motivated (i.e. government regulation) interventions for a range of societal problems, including mental health. We aim to help shape a research agenda of principles for the design of mechanisms around problem areas on which there is broad consensus and a firm base of support. We offer constructive examples and discussion of potential implementation methods related to these topics, as well as several new data illustrations for potential effects of exposure to online content.
2306.07443v1
2023-06-16
Microlayer in nucleate boiling seen as Landau-Levich film with dewetting and evaporation
Both experimental and theoretical studies on the microscale and fast physical phenomena occurring during the growth of vapor bubbles in nucleate pool boiling are reported. The focus is on the liquid film of micrometric thickness (``microlayer'') that can form between the heater and the liquid-vapor interface of a bubble on the millisecond time scale. The microlayer strongly affects the macroscale heat transfer and is thus important to be understood. It is shown that the microlayer can be seen as the Landau-Levich film deposited by the bubble foot edge during its receding when the bubble grows. The microlayer profile measured with white-light interferometry, the temperature distribution over the heater, and the bubble shape were observed with synchronized high-speed cameras. The microlayer consists of two regions: a ridge near the contact line followed by a longer and flatter part. The ridge could not be measured because of the intrinsic limitation of interferometry, which is analyzed. The simulations show that the ridge grows over time due to collection of liquid at contact line receding, the theoretical dynamics of which agrees with the experiment. The flatter part of the microlayer is bumped and its physical origin is explained.
2306.09838v1
2023-06-20
High frequency oscillations in spin-torque nano oscillator due to bilinear coupling
Exchange coupling in an interfacial context is crucial for spin-torque nano oscillator (STNO) that consists of a non-magnetic spacer which is alloyed with a ferromagnetic material. Currently, investigations on the dynamics of the free layer magnetization and frequency enhancement in the STNO with bilinear coupling are still being actively pursued. In the present work, we investigate the dynamics of the STNO in the presence of bilinear coupling but in the absence of an external magnetic field by analyzing the associated Landau-Lifshitz-Gilbert-Sloncewski(LLGS) equation, and consequently the impact of the bilinear coupling on the dynamics of the magnetization of the free layer is studied. It is observed that the frequency of the oscillations in the magnetization component along the direction of the pinned layer polarization can be enhanced above 300 GHz by positive bilinear coupling and up to around 30 GHz by negative bilinear coupling. We further reveal a transition from in-plane to out-of-plane precession both for positive and negative bi-linear couplings. We also analyze the switching of the magnetization for different values of current and bilinear coupling. Our detailed investigations of STNO with bilinear coupling aim at the possibilities of high-frequency devices by considering the applied current and bilinear coupling in the absence of a magnetic field.
2306.11415v1
2023-06-20
Convolutional neural networks for large-scale dynamical modeling of itinerant magnets
Complex spin textures in itinerant electron magnets hold promises for next-generation memory and information technology. The long-ranged and often frustrated electron-mediated spin interactions in these materials give rise to intriguing localized spin structures such as skyrmions. Yet, simulations of magnetization dynamics for such itinerant magnets are computationally difficult due to the need for repeated solutions to the electronic structure problems. We present a convolutional neural network (CNN) model to accurately and efficiently predict the electron-induced magnetic torques acting on local spins. Importantly, as the convolutional operations with a fixed kernel (receptive field) size naturally take advantage of the locality principle for many-electron systems, CNN offers a scalable machine learning approach to spin dynamics. We apply our approach to enable large-scale dynamical simulations of skyrmion phases in itinerant spin systems. By incorporating the CNN model into Landau-Lifshitz-Gilbert dynamics, our simulations successfully reproduce the relaxation process of the skyrmion phase and stabilize a skyrmion lattice in larger systems. The CNN model also allows us to compute the effective receptive fields, thus providing a systematic and unbiased method for determining the locality of the original electron models.
2306.11833v1
2023-06-29
Relaxed Local Correctability from Local Testing
We construct the first asymptotically good relaxed locally correctable codes with polylogarithmic query complexity, bringing the upper bound polynomially close to the lower bound of Gur and Lachish (SICOMP 2021). Our result follows from showing that a high-rate locally testable code can boost the block length of a smaller relaxed locally correctable code, while preserving the correcting radius and incurring only a modest additive cost in rate and query complexity. We use the locally testable code's tester to check if the amount of corruption in the input is low; if so, we can "zoom-in" to a suitable substring of the input and recurse on the smaller code's local corrector. Hence, iterating this operation with a suitable family of locally testable codes due to Dinur, Evra, Livne, Lubotzky, and Mozes (STOC 2022) yields asymptotically good codes with relaxed local correctability, arbitrarily large block length, and polylogarithmic query complexity. Our codes asymptotically inherit the rate and distance of any locally testable code used in the final invocation of the operation. Therefore, our framework also yields nonexplicit relaxed locally correctable codes with polylogarithmic query complexity that have rate and distance approaching the Gilbert-Varshamov bound.
2306.17035v2
2023-07-13
Words are not Wind -- How Joint Commitment and Reputation Solve Social Dilemmas, without Repeated Interactions or Enforcement by Third Parties
Joint commitment was argued to "make our social world" (Gilbert, 2014) and to separate us from other primates. 'Joint' entails that neither of us promises anything, unless the other promises as well. When we need to coordinate for the best mutual outcome, any commitment is beneficial. However, when we are tempted to free-ride (i.e. in social dilemmas), commitment serves no obvious purpose. We show that a reputation system, which judges action in social dilemmas only after joint commitment, can prevent free-riding. Keeping commitments builds trust. We can selectively enter joint commitments with trustworthy individuals to ensure their cooperation (since they will now be judged). We simply do not commit to cooperate with those we do not trust, and hence can freely defect without losing the trust of others. This principle might be the reason for pointedly public joint commitments, such as marriage. It is especially relevant to our evolutionary past, in which no mechanisms existed to enforce commitments reliably and impartially (e.g. via a powerful and accountable government). Much research from anthropology, philosophy and psychology made the assumption that past collaborations were mutually beneficial and had little possibilities to free-ride, for which there is little support. Our evolutionary game theory approach proves that this assumption is not necessary, because free-riding could have been dealt with joint commitments and reputation.
2307.06898v1
2023-07-18
Multi-Stage Cable Routing through Hierarchical Imitation Learning
We study the problem of learning to perform multi-stage robotic manipulation tasks, with applications to cable routing, where the robot must route a cable through a series of clips. This setting presents challenges representative of complex multi-stage robotic manipulation scenarios: handling deformable objects, closing the loop on visual perception, and handling extended behaviors consisting of multiple steps that must be executed successfully to complete the entire task. In such settings, learning individual primitives for each stage that succeed with a high enough rate to perform a complete temporally extended task is impractical: if each stage must be completed successfully and has a non-negligible probability of failure, the likelihood of successful completion of the entire task becomes negligible. Therefore, successful controllers for such multi-stage tasks must be able to recover from failure and compensate for imperfections in low-level controllers by smartly choosing which controllers to trigger at any given time, retrying, or taking corrective action as needed. To this end, we describe an imitation learning system that uses vision-based policies trained from demonstrations at both the lower (motor control) and the upper (sequencing) level, present a system for instantiating this method to learn the cable routing task, and perform evaluations showing great performance in generalizing to very challenging clip placement variations. Supplementary videos, datasets, and code can be found at https://sites.google.com/view/cablerouting.
2307.08927v5
2023-07-20
Fallout from U.S. atmospheric nuclear tests in New Mexico and Nevada (1945-1962)
One hundred and one atmospheric nuclear weapon tests were conducted between 1945 and 1962 in the United States, resulting in widespread dispersion of radioactive fallout, and leading to environmental contamination and population exposures. Accurate assessment of the extent of fallout from nuclear weapon tests has been challenging in the United States and elsewhere, due to limited monitoring and data accessibility. Here we address this deficit by combining U.S. government data, high-resolution reanalyzed historical weather fields, and atmospheric transport modeling to reconstruct radionuclide deposition across the contiguous United States, with 10-kilometer spatial and one-hour temporal resolution for five days following detonation, from all 94 atmospheric tests detonated in New Mexico and Nevada with fission yields sufficient to generate mushroom clouds. Our analysis also includes deposition estimates for 10 days following the detonation of Trinity, the first ever nuclear weapon test, on July 16, 1945. We identify locations where radionuclide deposition significantly exceeded levels in areas covered by the U.S. Radiation Exposure Compensation Act (RECA). These findings include deposition in all 48 contiguous U.S. states. They provide an opportunity for re-evaluating the public health and environmental implications from atmospheric nuclear testing. Finally, our findings also speak to debates about marking the beginning of the Anthropocene with nuclear weapons fallout. Our deposition estimates indicate that direct fallout from Trinity, a plutonium device, reached Crawford Lake in Canada, the proposed "golden spike" site marking the beginning of the Anthropocene epoch, starting on July 20, 1945.
2307.11040v1
2023-07-23
Characterizing non-Markovian Quantum Process by Fast Bayesian Tomography
To push gate performance to levels beyond the thresholds for quantum error correction, it is important to characterize the error sources occurring on quantum gates. However, the characterization of non-Markovian error poses a challenge to current quantum process tomography techniques. Fast Bayesian Tomography (FBT) is a self-consistent gate set tomography protocol that can be bootstrapped from earlier characterization knowledge and be updated in real-time with arbitrary gate sequences. Here we demonstrate how FBT allows for the characterization of key non-Markovian error processes. We introduce two experimental protocols for FBT to diagnose the non-Markovian behavior of two-qubit systems on silicon quantum dots. To increase the efficiency and scalability of the experiment-analysis loop, we develop an online FBT software stack. To reduce experiment cost and analysis time, we also introduce a native readout method and warm boot strategy. Our results demonstrate that FBT is a useful tool for probing non-Markovian errors that can be detrimental to the ultimate realization of fault-tolerant operation on quantum computing.
2307.12452v2
2023-07-27
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Reinforcement learning from human feedback (RLHF) is a technique for training AI systems to align with human goals. RLHF has emerged as the central method used to finetune state-of-the-art large language models (LLMs). Despite this popularity, there has been relatively little public work systematizing its flaws. In this paper, we (1) survey open problems and fundamental limitations of RLHF and related methods; (2) overview techniques to understand, improve, and complement RLHF in practice; and (3) propose auditing and disclosure standards to improve societal oversight of RLHF systems. Our work emphasizes the limitations of RLHF and highlights the importance of a multi-faceted approach to the development of safer AI systems.
2307.15217v2
2023-08-03
Predicting Ki67, ER, PR, and HER2 Statuses from H&E-stained Breast Cancer Images
Despite the advances in machine learning and digital pathology, it is not yet clear if machine learning methods can accurately predict molecular information merely from histomorphology. In a quest to answer this question, we built a large-scale dataset (185538 images) with reliable measurements for Ki67, ER, PR, and HER2 statuses. The dataset is composed of mirrored images of H\&E and corresponding images of immunohistochemistry (IHC) assays (Ki67, ER, PR, and HER2. These images are mirrored through registration. To increase reliability, individual pairs were inspected and discarded if artifacts were present (tissue folding, bubbles, etc). Measurements for Ki67, ER and PR were determined by calculating H-Score from image analysis. HER2 measurement is based on binary classification: 0 and 1+ (IHC scores representing a negative subset) vs 3+ (IHC score positive subset). Cases with IHC equivocal score (2+) were excluded. We show that a standard ViT-based pipeline can achieve prediction performances around 90% in terms of Area Under the Curve (AUC) when trained with a proper labeling protocol. Finally, we shed light on the ability of the trained classifiers to localize relevant regions, which encourages future work to improve the localizations. Our proposed dataset is publicly available: https://ihc4bc.github.io/
2308.01982v1
2023-08-06
Unravelling metallic contaminants in complex polyimide heterostructures using deep ultraviolet spectroscopic ellipsometry
Metallic contaminants in complex heterostructures are important topics due to their significant roles in determining physical properties as well as device performance. Heterostructures of polyimide via on Al pad and Cu redistribution layer (RDL) on polyimide have shown exotic properties and are important for advanced semiconductor packaging systems. One main problem is significant leakage current variations, which affect the performance of the devices, yet the origin is far from understood. Furthermore, metal contaminations would occur at the buried interfaces and it is particularly challenging to probe them. Until now, the electronic and optical properties of complex polyimide heterostructures and the roles of metallic contaminants, especially in the deep ultraviolet (DUV) have not been studied extensively. Herewith, using spectroscopic ellipsometry (SE) in a broad DUV range supported with finite-difference time-domain (FDTD) calculations, we determine optical properties of contaminants with various concentrations and reveal their influence on device performance of under-bump vias and redistribution layer (RDL) architectures. The complex dielectric function shows varying contamination levels and different metals responsible for chip performance. Metallic contaminants are found embedded within 50 nm in the polyimide and different metals are distinguishable with varying concentrations, in agreement with contact measurements in highly complex structures. Our result shows the potency of spectroscopic ellipsometry in the DUV and paves the way for non-destructive, advanced quality control and metrology applications in integrated advanced electronics packaging systems.
2308.03015v1
2023-08-14
Nanoelectromechanical control of spin-photon interfaces in a hybrid quantum system on chip
Atom-like defects or color centers (CC's) in nanostructured diamond are a leading platform for optically linked quantum technologies, with recent advances including memory-enhanced quantum communication, multi-node quantum networks, and spin-mediated generation of photonic cluster states. Scaling to practically useful applications motivates architectures meeting the following criteria: C1 individual optical addressing of spin qubits; C2 frequency tuning of CC spin-dependent optical transitions; C3 coherent spin control in CC ground states; C4 active photon routing; C5 scalable manufacturability; and C6 low on-chip power dissipation for cryogenic operations. However, no architecture meeting C1-C6 has thus far been demonstrated. Here, we introduce a hybrid quantum system-on-chip (HQ-SoC) architecture that simultaneously achieves C1-C6. Key to this advance is the realization of piezoelectric strain control of diamond waveguide-coupled tin vacancy centers to meet C2 and C3, with ultra-low power dissipation necessary for C6. The DC response of our device allows emitter transition tuning by over 20 GHz, while the large frequency range (exceeding 2 GHz) enables low-power AC control. We show acoustic manipulation of integrated tin vacancy spins and estimate single-phonon coupling rates over 1 kHz in the resolved sideband regime. Combined with high-speed optical routing with negligible static hold power, this HQ-SoC platform opens the path to scalable single-qubit control with optically mediated entangling gates.
2308.07161v1
2023-08-23
MOFO: MOtion FOcused Self-Supervision for Video Understanding
Self-supervised learning (SSL) techniques have recently produced outstanding results in learning visual representations from unlabeled videos. Despite the importance of motion in supervised learning techniques for action recognition, SSL methods often do not explicitly consider motion information in videos. To address this issue, we propose MOFO (MOtion FOcused), a novel SSL method for focusing representation learning on the motion area of a video, for action recognition. MOFO automatically detects motion areas in videos and uses these to guide the self-supervision task. We use a masked autoencoder which randomly masks out a high proportion of the input sequence; we force a specified percentage of the inside of the motion area to be masked and the remainder from outside. We further incorporate motion information into the finetuning step to emphasise motion in the downstream task. We demonstrate that our motion-focused innovations can significantly boost the performance of the currently leading SSL method (VideoMAE) for action recognition. Our method improves the recent self-supervised Vision Transformer (ViT), VideoMAE, by achieving +2.6%, +2.1%, +1.3% accuracy on Epic-Kitchens verb, noun and action classification, respectively, and +4.7% accuracy on Something-Something V2 action classification. Our proposed approach significantly improves the performance of the current SSL method for action recognition, indicating the importance of explicitly encoding motion in SSL.
2308.12447v2
2023-08-25
Thermal effect on microwave pulse driven magnetization switching of Stoner particle
Recently it has been demonstrated that the cosine chirp microwave pulse (CCMP) is capable of achieving fast and energy-efficient magnetization-reversal of a nanoparticle with zero-Temperature. However, we investigate the finite temperature, $T$ effect on the CCMP-driven magnetization reversal using the framework of the stochastic Landau Lifshitz Gilbert equation. At finite Temperature, we obtain the CCMP-driven fast and energy-efficient reversal and hence estimate the maximal temperature, $T_{max}$ at which the magnetization reversal is valid. $T_{max}$ increases with increasing the nanoparticle cross-sectional area/shape anisotropy up to a certain value, and afterward $T_{max}$ decreases with the further increment of nanoparticle cross-sectional area/shape anisotropy. This is because of demagnetization/shape anisotropy field opposes the magnetocrystalline anisotropy, i.e., reduces the energy barrier which separates the two stable states. For smaller cross-sectional area/shape anisotropy, the controlling parameters of CCMP show decreasing trend with temperature. We also find that with the increment easy-plane shape-anisotropy, the required initial frequency of CCMP significantly reduces. For the larger volume of nanoparticles, the parameters of CCMP remains constant for a wide range of temperature which are desired for the device application. Therefore, The above findings might be useful to realize the CCMP-driven fast and energy-efficient magnetization reversal in realistic conditions.
2308.13124v1
2023-09-04
Impact of electrostatic crosstalk on spin qubits in dense CMOS quantum dot arrays
Quantum processors based on integrated nanoscale silicon spin qubits are a promising platform for highly scalable quantum computation. Current CMOS spin qubit processors consist of dense gate arrays to define the quantum dots, making them susceptible to crosstalk from capacitive coupling between a dot and its neighbouring gates. Small but sizeable spin-orbit interactions can transfer this electrostatic crosstalk to the spin g-factors, creating a dependence of the Larmor frequency on the electric field created by gate electrodes positioned even tens of nanometers apart. By studying the Stark shift from tens of spin qubits measured in nine different CMOS devices, we developed a theoretical frawework that explains how electric fields couple to the spin of the electrons in increasingly complex arrays, including those electric fluctuations that limit qubit dephasing times $T_2^*$. The results will aid in the design of robust strategies to scale CMOS quantum technology.
2309.01849v1
2023-09-05
Connectivity and interference in device-to-device networks in Poisson-Voronoi cities
To study the overall connectivity in device-to-device networks in cities, we incorporate a signal-to-interference-plus-noise connectivity model into a Poisson-Voronoi tessellation model representing the streets of a city. Relays are located at crossroads (or street intersections), whereas (user) devices are scattered along streets. Between any two adjacent relays, we assume data can be transmitted either directly between the relays or through users, given they share a common street. Our simulation results reveal that the network connectivity is ensured when the density of users (on the streets) exceeds a certain critical value. But then the network connectivity disappears when the user density exceeds a second critical value. The intuition is that for longer streets, where direct relay-to-relay communication is not possible, users are needed to transmit data between relays, but with too many users the interference becomes too strong, eventually reducing the overall network connectivity. This observation on the user density evokes previous results based on another wireless network model, where transmitter-receivers were scattered across the plane. This effect disappears when interference is removed from the model, giving a variation of the classic Gilbert model and recalling the lesson that neglecting interference in such network models can give overly optimistic results. For physically reasonable model parameters, we show that crowded streets (with more than six users on a typical street) lead to a sudden drop in connectivity. We also give numerical results outlining a relationship between the user density and the strength of any interference reduction techniques.
2309.02137v2
2023-09-16
On non-expandable cross-bifix-free codes
A cross-bifix-free code of length $n$ over $\mathbb{Z}_q$ is defined as a non-empty subset of $\mathbb{Z}_q^n$ satisfying that the prefix set of each codeword is disjoint from the suffix set of every codeword. Cross-bifix-free codes have found important applications in digital communication systems. One of the main research problems on cross-bifix-free codes is to construct cross-bifix-free codes as large as possible in size. Recently, Wang and Wang introduced a family of cross-bifix-free codes $S_{I,J}^{(k)}(n)$, which is a generalization of the classical cross-bifix-free codes studied early by Lvenshtein, Gilbert and Chee {\it et al.}. It is known that $S_{I,J}^{(k)}(n)$ is nearly optimal in size and $S_{I,J}^{(k)}(n)$ is non-expandable if $k=n-1$ or $1\leq k<n/2$. In this paper, we first show that $S_{I,J}^{(k)}(n)$ is non-expandable if and only if $k=n-1$ or $1\leq k<n/2$, thereby improving the results in [Chee {\it et al.}, IEEE-TIT, 2013] and [Wang and Wang, IEEE-TIT, 2022]. We then construct a new family of cross-bifix-free codes $U^{(t)}_{I,J}(n)$ to expand $S_{I,J}^{(k)}(n)$ such that the resulting larger code $S_{I,J}^{(k)}(n)\bigcup U^{(t)}_{I,J}(n)$ is a non-expandable cross-bifix-free code whenever $S_{I,J}^{(k)}(n)$ is expandable. Finally, we present an explicit formula for the size of $S_{I,J}^{(k)}(n)\bigcup U^{(t)}_{I,J}(n)$.
2309.08915v1
2023-09-21
Real-time feedback protocols for optimizing fault-tolerant two-qubit gate fidelities in a silicon spin system
Recently, several groups have demonstrated two-qubit gate fidelities in semiconductor spin qubit systems above 99%. Achieving this regime of fault-tolerant compatible high fidelities is nontrivial and requires exquisite stability and precise control over the different qubit parameters over an extended period of time. This can be done by efficiently calibrating qubit control parameters against different sources of micro- and macroscopic noise. Here, we present several single- and two-qubit parameter feedback protocols, optimised for and implemented in state-of-the-art fast FPGA hardware. Furthermore, we use wavelet-based analysis on the collected feedback data to gain insight into the different sources of noise in the system. Scalable feedback is an outstanding challenge and the presented implementation and analysis gives insight into the benefits and drawbacks of qubit parameter feedback, as feedback related overhead increases. This work demonstrates a pathway towards robust qubit parameter feedback and systematic noise analysis, crucial for mitigation strategies towards systematic high-fidelity qubit operation compatible with quantum error correction protocols.
2309.12541v1
2023-09-21
Spatio-temporal correlations of noise in MOS spin qubits
In quantum computing, characterising the full noise profile of qubits can aid the efforts towards increasing coherence times and fidelities by creating error mitigating techniques specific to the type of noise in the system, or by completely removing the sources of noise. Spin qubits in MOS quantum dots are exposed to noise originated from the complex glassy behaviour of two-level fluctuators, leading to non-trivial correlations between qubit properties both in space and time. With recent engineering progress, large amounts of data are being collected in typical spin qubit device experiments, and it is beneficiary to explore data analysis options inspired from fields of research that are experienced in managing large data sets, examples include astrophysics, finance and climate science. Here, we propose and demonstrate wavelet-based analysis techniques to decompose signals into both frequency and time components to gain a deeper insight into the sources of noise in our systems. We apply the analysis to a long feedback experiment performed on a state-of-the-art two-qubit system in a pair of SiMOS quantum dots. The observed correlations serve to identify common microscopic causes of noise, as well as to elucidate pathways for multi-qubit operation with a more scalable feedback system.
2309.12542v2
2023-09-29
Glioma subtype classification from histopathological images using in-domain and out-of-domain transfer learning: An experimental study
We provide in this paper a comprehensive comparison of various transfer learning strategies and deep learning architectures for computer-aided classification of adult-type diffuse gliomas. We evaluate the generalizability of out-of-domain ImageNet representations for a target domain of histopathological images, and study the impact of in-domain adaptation using self-supervised and multi-task learning approaches for pretraining the models using the medium-to-large scale datasets of histopathological images. A semi-supervised learning approach is furthermore proposed, where the fine-tuned models are utilized to predict the labels of unannotated regions of the whole slide images (WSI). The models are subsequently retrained using the ground-truth labels and weak labels determined in the previous step, providing superior performance in comparison to standard in-domain transfer learning with balanced accuracy of 96.91% and F1-score 97.07%, and minimizing the pathologist's efforts for annotation. Finally, we provide a visualization tool working at WSI level which generates heatmaps that highlight tumor areas; thus, providing insights to pathologists concerning the most informative parts of the WSI.
2309.17223v1
2023-10-13
Midpoint geometric integrators for inertial magnetization dynamics
We consider the numerical solution of the inertial version of Landau-Lifshitz-Gilbert equation (iLLG), which describes high-frequency nutation on top of magnetization precession due to angular momentum relaxation. The iLLG equation defines a higher-order nonlinear dynamical system with very different nature compared to the classical LLG equation, requiring twice as many degrees of freedom for space-time discretization. It exhibits essential conservation properties, namely magnetization amplitude preservation, magnetization projection conservation, and a balance equation for generalized free energy, leading to a Lyapunov structure (i.e. the free energy is a decreasing function of time) when the external magnetic field is constant in time. We propose two second-order numerical schemes for integrating the iLLG dynamics over time, both based on implicit midpoint rule. The first scheme unconditionally preserves all the conservation properties, making it the preferred choice for simulating inertial magnetization dynamics. However, it implies doubling the number of unknowns, necessitating significant changes in numerical micromagnetic codes and increasing computational costs especially for spatially inhomogeneous dynamics simulations. To address this issue, we present a second time-stepping method that retains the same computational cost as the implicit midpoint rule for classical LLG dynamics while unconditionally preserving magnetization amplitude and projection. Special quasi-Newton techniques are developed for solving the nonlinear system of equations required at each time step due to the implicit nature of both time-steppings. The numerical schemes are validated on analytical solution for macrospin terahertz frequency response and the effectiveness of the second scheme is demonstrated with full micromagnetic simulation of inertial spin waves propagation in a magnetic thin-film.
2310.09043v1
2023-10-28
Einstein-de Haas torque as a discrete spectroscopic probe allows nanomechanical measurement of a magnetic resonance
The Einstein-de Haas (EdH) effect is a fundamental, mechanical consequence of any temporal change of magnetism in an object. EdH torque results from conserving the object's total angular momentum: the angular momenta of all the specimen's magnetic moments, together with its mechanical angular momentum. Although the EdH effect is usually small and difficult to observe, it increases in magnitude with detection frequency. We explore the frequency-dependence of EdH torque for a thin film permalloy microstructure by employing a ladder of flexural beam modes (with five distinct resonance frequencies spanning from 3 to 208 MHz) within a nanocavity optomechanical torque sensor via magnetic hysteresis curves measured at mechanical resonances. At low DC fields the gyrotropic resonance of a magnetic vortex spin texture overlaps the 208 MHz mechanical mode. The massive EdH mechanical torques arising from this co-resonance yield a fingerprint of vortex core pinning and depinning in the sample. The experimental results are discussed in relation to mechanical torques predicted from both macrospin (at high DC magnetic field) and finite-difference solutions to the Landau-Lifshitz-Gilbert (LLG) equation. A global fit of the LLG solutions to the frequency-dependent data reveals a statistically significant discrepancy between the experimentally observed and simulated torque phase behaviours at spin texture transitions that can be reduced through the addition of a time constant to the conversion between magnetic cross-product torque and mechanical torque, constrained by experiment to be in the range of 0.5 - 4 ns.
2310.18546v2
2023-10-31
Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows
High-fidelity computational simulations and physical experiments of hypersonic flows are resource intensive. Training scientific machine learning (SciML) models on limited high-fidelity data offers one approach to rapidly predict behaviors for situations that have not been seen before. However, high-fidelity data is itself in limited quantity to validate all outputs of the SciML model in unexplored input space. As such, an uncertainty-aware SciML model is desired. The SciML model's output uncertainties could then be used to assess the reliability and confidence of the model's predictions. In this study, we extend a DeepONet using three different uncertainty quantification mechanisms: mean-variance estimation, evidential uncertainty, and ensembling. The uncertainty aware DeepONet models are trained and evaluated on the hypersonic flow around a blunt cone object with data generated via computational fluid dynamics over a wide range of Mach numbers and altitudes. We find that ensembling outperforms the other two uncertainty models in terms of minimizing error and calibrating uncertainty in both interpolative and extrapolative regimes.
2311.00060v2
2023-11-11
Double-Free-Layer Stochastic Magnetic Tunnel Junctions with Synthetic Antiferromagnets
Stochastic magnetic tunnel junctions (sMTJ) using low-barrier nanomagnets have shown promise as fast, energy-efficient, and scalable building blocks for probabilistic computing. Despite recent experimental and theoretical progress, sMTJs exhibiting the ideal characteristics necessary for probabilistic bits (p-bit) are still lacking. Ideally, the sMTJs should have (a) voltage bias independence preventing read disturbance (b) uniform randomness in the magnetization angle between the free layers, and (c) fast fluctuations without requiring external magnetic fields while being robust to magnetic field perturbations. Here, we propose a new design satisfying all of these requirements, using double-free-layer sMTJs with synthetic antiferromagnets (SAF). We evaluate the proposed sMTJ design with experimentally benchmarked spin-circuit models accounting for transport physics, coupled with the stochastic Landau-Lifshitz-Gilbert equation for magnetization dynamics. We find that the use of low-barrier SAF layers reduces dipolar coupling, achieving uncorrelated fluctuations at zero-magnetic field surviving up to diameters exceeding ($D\approx 100$ nm) if the nanomagnets can be made thin enough ($\approx 1$-$2$ nm). The double-free-layer structure retains bias-independence and the circular nature of the nanomagnets provides near-uniform randomness with fast fluctuations. Combining our full sMTJ model with advanced transistor models, we estimate the energy to generate a random bit as $\approx$ 3.6 fJ, with fluctuation rates of $\approx$ 3.3 GHz per p-bit. Our results will guide the experimental development of superior stochastic magnetic tunnel junctions for large-scale and energy-efficient probabilistic computation for problems relevant to machine learning and artificial intelligence.
2311.06642v2
2023-11-14
Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderators
Extensive efforts in automated approaches for content moderation have been focused on developing models to identify toxic, offensive, and hateful content with the aim of lightening the load for moderators. Yet, it remains uncertain whether improvements on those tasks have truly addressed moderators' needs in accomplishing their work. In this paper, we surface gaps between past research efforts that have aimed to provide automation for aspects of content moderation and the needs of volunteer content moderators, regarding identifying violations of various moderation rules. To do so, we conduct a model review on Hugging Face to reveal the availability of models to cover various moderation rules and guidelines from three exemplar forums. We further put state-of-the-art LLMs to the test, evaluating how well these models perform in flagging violations of platform rules from one particular forum. Finally, we conduct a user survey study with volunteer moderators to gain insight into their perspectives on useful moderation models. Overall, we observe a non-trivial gap, as missing developed models and LLMs exhibit moderate to low performance on a significant portion of the rules. Moderators' reports provide guides for future work on developing moderation assistant models.
2311.07879v2
2023-11-14
All Byzantine Agreement Problems are Expensive
Byzantine agreement, arguably the most fundamental problem in distributed computing, operates among n processes, out of which t < n can exhibit arbitrary failures. The problem states that all correct (non-faulty) processes must eventually decide (termination) the same value (agreement) from a set of admissible values defined by the proposals of the processes (validity). Depending on the exact version of the validity property, Byzantine agreement comes in different forms, from Byzantine broadcast to strong and weak consensus, to modern variants of the problem introduced in today's blockchain systems. Regardless of the specific flavor of the agreement problem, its communication cost is a fundamental metric whose improvement has been the focus of decades of research. The Dolev-Reischuk bound, one of the most celebrated results in distributed computing, proved 40 years ago that, at least for Byzantine broadcast, no deterministic solution can do better than Omega(t^2) exchanged messages in the worst case. Since then, it remained unknown whether the quadratic lower bound extends to seemingly weaker variants of Byzantine agreement. This paper answers the question in the affirmative, closing this long-standing open problem. Namely, we prove that any non-trivial agreement problem requires Omega(t^2) messages to be exchanged in the worst case. To prove the general lower bound, we determine the weakest Byzantine agreement problem and show, via a novel indistinguishability argument, that it incurs Omega(t^2) exchanged messages.
2311.08060v2
2023-11-21
Nonparametric variable importance for time-to-event outcomes with application to prediction of HIV infection
In survival analysis, complex machine learning algorithms have been increasingly used for predictive modeling. Given a collection of features available for inclusion in a predictive model, it may be of interest to quantify the relative importance of a subset of features for the prediction task at hand. In particular, in HIV vaccine trials, participant baseline characteristics are used to predict the probability of infection over the intended follow-up period, and investigators may wish to understand how much certain types of predictors, such as behavioral factors, contribute toward overall predictiveness. Time-to-event outcomes such as time to infection are often subject to right censoring, and existing methods for assessing variable importance are typically not intended to be used in this setting. We describe a broad class of algorithm-agnostic variable importance measures for prediction in the context of survival data. We propose a nonparametric efficient estimation procedure that incorporates flexible learning of nuisance parameters, yields asymptotically valid inference, and enjoys double-robustness. We assess the performance of our proposed procedure via numerical simulations and analyze data from the HVTN 702 study to inform enrollment strategies for future HIV vaccine trials.
2311.12726v2
2023-11-29
Atmospheric Escape From Three Terrestrial Planets in the L 98-59 System
A critically important process affecting the climate evolution and potential habitability of an exoplanet is atmospheric escape, in which high-energy radiation from a star drives the escape of hydrogen atoms and other light elements from a planet's atmosphere. L 98-59 is a benchmark system for studying such atmospheric processes, with three transiting terrestrial-size planets receiving Venus-like instellations (4-25 S$_\oplus$) from their M3 host star. We use the VPLanet model to simulate the evolution of the L 98-59 system and the atmospheric escape of its inner three small planets, given different assumed initial water quantities. We find that, regardless of their initial water content, all three planets accumulate significant quantities of oxygen due to efficient water photolysis and hydrogen loss. All three planets also receive enough XUV flux to drive rapid water loss, which considerably affects their developing climates and atmospheres. Even in scenarios of low initial water content, our results suggest that the James Webb Space Telescope (JWST) will be sensitive to observations of retained oxygen on the L 98-59 planets in its future scheduled observations, with planets b and c being the most likely targets to possess an extended atmosphere. Our results constrain the atmospheric evolution of these small rocky planets, and they provide context for current and future observations of the L 98-59 system to generalize our understanding of multi-terrestrial planet systems.
2312.00062v1
2023-12-03
Heisenberg machines with programmable spin-circuits
We show that we can harness two recent experimental developments to build a compact hardware emulator for the classical Heisenberg model in statistical physics. The first is the demonstration of spin-diffusion lengths in excess of microns in graphene even at room temperature. The second is the demonstration of low barrier magnets (LBMs) whose magnetization can fluctuate rapidly even at sub-nanosecond rates. Using experimentally benchmarked circuit models, we show that an array of LBMs driven by an external current source has a steady-state distribution corresponding to a classical system with an energy function of the form $E = -1/2\sum_{i,j} J_{ij} (\hat{m}_i \cdot \hat{m}_j$). This may seem surprising for a non-equilibrium system but we show that it can be justified by a Lyapunov function corresponding to a system of coupled Landau-Lifshitz-Gilbert (LLG) equations. The Lyapunov function we construct describes LBMs interacting through the spin currents they inject into the spin neutral substrate. We suggest ways to tune the coupling coefficients $J_{ij}$ so that it can be used as a hardware solver for optimization problems involving continuous variables represented by vector magnetizations, similar to the role of the Ising model in solving optimization problems with binary variables. Finally, we implement a Heisenberg AND gate based on a network of three coupled stochastic LLG equations, illustrating the concept of probabilistic computing with a programmable Heisenberg model.
2312.01477v1
2023-12-05
A complex-projected Rayleigh quotient iteration for targeting interior eigenvalues
We introduce a new Projected Rayleigh Quotient Iteration aimed at improving the convergence behaviour of classic Rayleigh Quotient iteration (RQI) by incorporating approximate information about the target eigenvector at each step. While classic RQI exhibits local cubic convergence for Hermitian matrices, its global behaviour can be unpredictable, whereby it may converge to an eigenvalue far away from the target, even when started with accurate initial conditions. This problem is exacerbated when the eigenvalues are closely spaced. The key idea of the new algorithm is at each step to add a complex-valued projection to the original matrix (that depends on the current eigenvector approximation), such that the unwanted eigenvalues are lifted into the complex plane while the target stays close to the real line, thereby increasing the spacing between the target eigenvalue and the rest of the spectrum. Making better use of the eigenvector approximation leads to more robust convergence behaviour and the new method converges reliably to the correct target eigenpair for a significantly wider range of initial vectors than does classic RQI. We prove that the method converges locally cubically and we present several numerical examples demonstrating the improved global convergence behaviour. In particular, we apply it to compute eigenvalues in a band-gap spectrum of a Sturm-Liouville operator used to model photonic crystal fibres, where the target and unwanted eigenvalues are closely spaced. The examples show that the new method converges to the desired eigenpair even when the eigenvalue spacing is very small, often succeeding when classic RQI fails.
2312.02847v2
2023-12-14
On statistical zonostrophic instability and the effect of magnetic fields
Zonal flows are mean flows in the east-west direction, which are ubiquitous on planets, and can be formed through 'zonostrophic instability': within turbulence or random waves, a weak large-scale zonal flow can grow exponentially to become prominent. In this paper, we study the statistical behaviour of the zonostrophic instability and the effect of magnetic fields. We use a stochastic white noise forcing to drive random waves, and study the growth of a mean flow in this random system. The dispersion relation for the growth rate of the expectation of the mean flow is derived, and properties of the instability are discussed. In the limits of weak and strong magnetic diffusivity, the dispersion relation reduces to manageable expressions, which provide clear insights into the effect of the magnetic field and scaling laws for the threshold of instability. The magnetic field mainly plays a stabilising role and thus impedes the formation of the zonal flow, but under certain conditions it can also have destabilising effects. Numerical simulation of the stochastic flow is performed to confirm the theory. Results indicate that the magnetic field can significantly increase the randomness of the zonal flow. It is found that the zonal flow of an individual realisation may behave very differently from the expectation. For weak magnetic diffusivity and moderate magnetic field strengths, this leads to considerable variation of the outcome, that is whether zonostrophic instability takes place or not in individual realisations.
2312.08905v1
2023-12-19
Towards a theta correspondence in families for type II dual pairs
Let $R$ be a commutative $\mathbb{Z}[1/p]$-algebra, let $m \leq n$ be positive integers, and let $G_n=\text{GL}_n(F)$ and $G_m=\text{GL}_m(F)$ where $F$ is a $p$-adic field. The Weil representation is the smooth $R[G_n\times G_m]$-module $C_c^{\infty}(\text{Mat}_{n\times m}(F),R)$ with the action induced by matrix multiplication. When $R=\mathbb{C}$ or is any algebraically closed field of banal characteristic compared to $G_n$ and $G_m$, the local theta correspondence holds by the work of Howe and M\'inguez. At the level of supercuspidal support, we interpret the theta correspondence as a morphism of varieties $\theta_R$, which we describe as an explicit closed immersion. For arbitrary $R$, we construct a canonical ring homomorphism $\theta^\#_{R} : \mathfrak{Z}_{R}(G_n)\to \mathfrak{Z}_{R}(G_m)$ that controls the action of the center $\mathfrak{Z}_{R}(G_n)$ of the category of smooth $R[G_n]$-modules on the Weil representation. We use the rank filtration of the Weil representation to first obtain $\theta_{\mathbb{Z}[1/p]}^\#$, then obtain $\theta^\#_R$ for arbitrary $R$ by proving $\mathfrak{Z}_R(G_n)$ is compatible with scalar extension. In particular, the map $\text{Spec}(\mathfrak{Z}_R(G_m))\to \text{Spec}(\mathfrak{Z}_R(G_n))$ induced by $\theta_R^\#$ recovers $\theta_R$ in the $R=\mathbb{C}$ case and in the banal case. We use gamma factors to prove $\theta_R^\#$ is surjective for any $R$. Finally, we describe $\theta^\#_R$ in terms of the moduli space of Langlands parameters and use this description to give an alternative proof of surjectivity in the tamely ramified case.
2312.12031v1
2023-12-19
Microscopic theory of current-induced skyrmion transport and its application in disordered spin textures
Magnetic skyrmions hold great promise for realizing compact and stable memory devices that can be manipulated at very low energy costs via electronic current densities. In this work, we extend a recently introduced method to describe classical skyrmion textures coupled to dynamical itinerant electrons. In this scheme, the electron dynamics is described via nonequilibrium Green's functions (NEGF) within the generalized Kadanoff-Baym ansatz, and the classical spins are treated via the Landau-Lifshitz-Gilbert equation. The framework is here extended to open systems, by the introduction of a non-interacting approximation to the collision integral of NEGF. This, in turn, allows us to perform computations of the real-time response of skyrmions to electronic currents in large quantum systems coupled to electronic reservoirs, which exhibit a linear scaling in the number of time steps. We use this approach to investigate how electronic spin currents and dilute spin disorder affects skyrmion transport and the skyrmion Hall drift. Our results show that the skyrmion dynamics is sensitive to the specific form of spin disorder, such that different disorder configurations leads to qualitatively different skyrmion trajectories for the same applied bias. This sensitivity arises from the local spin dynamics around the magnetic impurities, a feature that is expected not to be well captured by phenomenological or spin-only descriptions. At the same time, our findings illustrate the potential of engineering microscopic impurity patterns to steer skyrmion trajectories.
2312.12201v1
2024-01-09
Characterization of two fast-turnaround dry dilution refrigerators for scanning probe microscopy
Low-temperature scanning probe microscopes (SPMs) are critical for the study of quantum materials and quantum information science. Due to the rising costs of helium, cryogen-free cryostats have become increasingly desirable. However, they typically suffer from comparatively worse vibrations than cryogen-based systems, necessitating the understanding and mitigation of vibrations for SPM applications. Here we demonstrate the construction of two cryogen-free dilution refrigerator SPMs with minimal modifications to the factory default and we systematically characterize their vibrational performance. We measure the absolute vibrations at the microscope stage with geophones, and use both microwave impedance microscopy and a scanning single electron transistor to independently measure tip-sample vibrations. Additionally, we implement customized filtering and thermal anchoring schemes, and characterize the cooling power at the scanning stage and the tip electron temperature. This work serves as a reference to researchers interested in cryogen-free SPMs, as such characterization is not standardized in the literature or available from manufacturers.
2401.04373v1
2024-01-11
Micromagnetic simulations of the size dependence of the Curie temperature in ferromagnetic nanowires and nanolayers
We solve the Landau-Lifshitz-Gilbert equation in the finite-temperature regime, where thermal fluctuations are modeled by a random magnetic field whose variance is proportional to the temperature. By rescaling the temperature proportionally to the computational cell size $\Delta x$ ($T \to T\,\Delta x/a_{\text{eff}}$, where $a_{\text{eff}}$ is the lattice constant) [M. B. Hahn, J. Phys. Comm., 3:075009, 2019], we obtain Curie temperatures $T_{\text{C}}$ that are in line with the experimental values for cobalt, iron and nickel. For finite-sized objects such as nanowires (1D) and nanolayers (2D), the Curie temperature varies with the smallest size $d$ of the system. We show that the difference between the computed finite-size $T_{\text{C}}$ and the bulk $T_{\text{C}}$ follows a power-law of the type: $(\xi_0/d)^\lambda$, where $\xi_0$ is the correlation length at zero temperature, and $\lambda$ is a critical exponent. We obtain values of $\xi_0$ in the nanometer range, also in accordance with other simulations and experiments. The computed critical exponent is close to $\lambda=2$ for all considered materials and geometries. This is the expected result for a mean-field approach, but slightly larger than the values observed experimentally.
2401.05722v1
2024-01-24
How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment
Exposure to large language model output is rapidly increasing. How will seeing AI-generated ideas affect human ideas? We conducted an experiment (800+ participants, 40+ countries) where participants viewed creative ideas that were from ChatGPT or prior experimental participants and then brainstormed their own idea. We varied the number of AI-generated examples (none, low, or high exposure) and if the examples were labeled as 'AI' (disclosure). Our dynamic experiment design -- ideas from prior participants in an experimental condition are used as stimuli for future participants in the same experimental condition -- mimics the interdependent process of cultural creation: creative ideas are built upon prior ideas. Hence, we capture the compounding effects of having LLMs 'in the culture loop'. We find that high AI exposure (but not low AI exposure) did not affect the creativity of individual ideas but did increase the average amount and rate of change of collective idea diversity. AI made ideas different, not better. There were no main effects of disclosure. We also found that self-reported creative people were less influenced by knowing an idea was from AI, and that participants were more likely to knowingly adopt AI ideas when the task was difficult. Our findings suggest that introducing AI ideas into society may increase collective diversity but not individual creativity.
2401.13481v1
2024-01-31
Multimaterial Inkjet Printing of Mechanochromic Materials
Inkjet printing technology achieves the precise deposition of liquid-phase materials via the digitally controlled formation of picoliter-sized droplets. Beyond graphical printing, inkjet printing has been employed for the deposition of separated drops on surfaces or the formation of continuous layers, which allows to construct materials gradients or periodic features that provide enhanced functionalities. Here, we explore the use of multinozzle, drop-on-demand piezoelectric inkjet technology for the manufacturing of mechanochromic materials, i.e., materials that change their color or fluorescence in response to mechanical deformation. To accomplish this, suitable polyurethane polymers of differing hardness grades were tested with a range of organic solvents to formulate low-viscosity, inkjet-printable solutions. Following their rheological characterization, two solutions comprised of "soft" and "hard" polyurethanes were selected for in-depth study. The solutions were imbibed with a mechanochromic additive to yield fluorescent inks, which were either dropcast onto polymeric substrates or printed to form checkerboard patterns of alternating hardness using a lab-built, multimaterial inkjet platform. Fluorescence imaging and spectroscopy were used to identify different hardness grades in the dropcast and printed materials, as well as to monitor the responses of these gradient materials to mechanical deformation. The insights gained in this study are expected to facilitate the development of inkjet-printable, mechanochromic polymer materials for a wide range of applications.
2401.17758v2
2024-01-11
Resonant inelastic x-ray scattering in warm-dense Fe compounds beyond the SASE FEL resolution limit
Resonant inelastic x-ray scattering (RIXS) is a widely used spectroscopic technique, providing access to the electronic structure and dynamics of atoms, molecules, and solids. However, RIXS requires a narrow bandwidth x-ray probe to achieve high spectral resolution. The challenges in delivering an energetic monochromated beam from an x-ray free electron laser (XFEL) thus limit its use in few-shot experiments, including for the study of high energy density systems. Here we demonstrate that by correlating the measurements of the self-amplified spontaneous emission (SASE) spectrum of an XFEL with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate, we can achieve electronic structure resolutions substantially higher than those normally afforded by the bandwidth of the incoming x-ray beam. We further show how this technique allows us to discriminate between the valence structures of Fe and Fe$_2$O$_3$, and provides access to temperature measurements as well as M-shell binding energies estimates in warm-dense Fe compounds.
2402.00039v1
2024-02-08
Trustful Coopetitive Infrastructures for the New Space Exploration Era
In the new space economy, space agencies, large enterprises, and start-ups aim to launch space multi-robot systems (MRS) for various in-situ resource utilization (ISRU) purposes, such as mapping, soil evaluation, and utility provisioning. However, these stakeholders' competing economic interests may hinder effective collaboration on a centralized digital platform. To address this issue, neutral and transparent infrastructures could facilitate coordination and value exchange among heterogeneous space MRS. While related work has expressed legitimate concerns about the technical challenges associated with blockchain use in space, we argue that weighing its potential economic benefits against its drawbacks is necessary. This paper presents a novel architectural framework and a comprehensive set of requirements for integrating blockchain technology in MRS, aiming to enhance coordination and data integrity in space exploration missions. We explored distributed ledger technology (DLT) to design a non-proprietary architecture for heterogeneous MRS and validated the prototype in a simulated lunar environment. The analyses of our implementation suggest global ISRU efficiency improvements for map exploration, compared to a corresponding group of individually acting robots, and that fostering a coopetitive environment may provide additional revenue opportunities for stakeholders.
2402.06014v1
2024-02-08
Designing Trustful Cooperation Ecosystems is Key to the New Space Exploration Era
In the emerging space economy, autonomous robotic missions with specialized goals such as mapping and mining are gaining traction, with agencies and enterprises increasingly investing resources. Multirobot systems (MRS) research has provided many approaches to establish control and communication layers to facilitate collaboration from a technical perspective, such as granting more autonomy to heterogeneous robotic groups through auction-based interactions in mesh networks. However, stakeholders' competing economic interests often prevent them from cooperating within a proprietary ecosystem. Related work suggests that distributed ledger technology (DLT) might serve as a mechanism for enterprises to coordinate workflows and trade services to explore space resources through a transparent, reliable, non-proprietary digital platform. We challenge this perspective by pointing to the core technical weaknesses of blockchains, in particular, increased energy consumption, low throughput, and full transparency through redundancy. Our objective is to advance the discussion in a direction where the benefits of DLT from an economic perspective are weighted against the drawbacks from a technical perspective. We finally present a possible DLT-driven heterogeneous MRS for map exploration to study the opportunities for economic collaboration and competitiveness.
2402.06036v1
2024-02-19
Density estimation for elliptic PDE with random input by preintegration and quasi-Monte Carlo methods
In this paper, we apply quasi-Monte Carlo (QMC) methods with an initial preintegration step to estimate cumulative distribution functions and probability density functions in uncertainty quantification (UQ). The distribution and density functions correspond to a quantity of interest involving the solution to an elliptic partial differential equation (PDE) with a lognormally distributed coefficient and a normally distributed source term. There is extensive previous work on using QMC to compute expected values in UQ, which have proven very successful in tackling a range of different PDE problems. However, the use of QMC for density estimation applied to UQ problems will be explored here for the first time. Density estimation presents a more difficult challenge compared to computing the expected value due to discontinuities present in the integral formulations of both the distribution and density. Our strategy is to use preintegration to eliminate the discontinuity by integrating out a carefully selected random parameter, so that QMC can be used to approximate the remaining integral. First, we establish regularity results for the PDE quantity of interest that are required for smoothing by preintegration to be effective. We then show that an $N$-point lattice rule can be constructed for the integrands corresponding to the distribution and density, such that after preintegration the QMC error is of order $\mathcal{O}(N^{-1+\epsilon})$ for arbitrarily small $\epsilon>0$. This is the same rate achieved for computing the expected value of the quantity of interest. Numerical results are presented to reaffirm our theory.
2402.11807v1
2024-02-29
Magnon spectrum of altermagnets: Time-dependent matrix product states vs. linearized Holstein-Primakoff calculations unravelling spontaneous magnon decay
The energy-momentum dispersion of magnons, viewed as noninteracting and infinitely long-lived quasiparticles describing collective low-energy excitations of magnetic materials, is often presented as sharp bands obtained from the effective quantum spin Hamiltonian, after being simplified via linearized Holstein-Primakoff (HP) transformations. However, magnons are prone to many-body interactions with other quasiparticles which can lead to their spontaneous decay. The magnon-magnon interactions could affect newly classified altermagnets. On the other hand, sharp bands of noninteracting chiral magnons in RuO2, as the canonical example of altermagnets, have been very recently predicted. Here, we employ nonperturbative numerically (quasi)exact quantum many-body calculations, via time-dependent matrix product states (TDMPS), to obtain magnon spectral function of RuO2. These calculations produce a broadened magnon dispersion, which overlaps with linearized HP theory sharp bands only at edges/center of the Brillouin zone. Substantially deviating otherwise. Artificially making exchange interaction within two sublattices of RuO2 closer in value forces these two spectra to overlap, thereby explaining the origin of the failure of linearized HP theory. Such features translate into the difference between their respective density of states, which we also compute and which could be tested by Raman scattering experiments. Finally, we employ popular Landau-Lifshitz-Gilbert (LLG) equation-based classical atomistic spin dynamics (ASD) simulations to obtain dynamical structure factor and extract magnon spectrum from it at finite temperature. Despite including magnon-magnon interactions via nonlinearity of LLG equation, ASD simulations cannot fully match the TDMPS-computed magnon spectrum due to nonclassical effects harbored by altermagnets.
2402.19433v1
2024-03-07
Controllable Skyrmion Islands in a Moiré Magnet
Antiferromagnetic(AFM) skyrmions have been in the spotlight as ideal topological magnetic bits. Although they are topologically protected, they do not exhibit the skyrmion Hall effect unlike the ferromagnetic ones. Thus, AFM skyrmions are considered to provide a better control of the skyrmion's motion due to the absence of the skyrmion Magnus effect. In this work, we propose a possible realization of controllable AFM skyrmions in a twisted Moir\'e magnet. The tunability of Moir\'e materials is not only a good platform for the provision of rich phases, but also for the stabilization of skyrmion phase. We investigate the ground state of twisted bilayer AFM system by solving the Landau-Lifshitz-Gilbert equation in a continuum model. We show that the AFM skyrmions are stabilized even in the absence of the external/dipolar magnetic field, as a consequence of the interplay of interlayer coupling, Dzyaloshinskii-Moriya (DM) interaction and Ising anisotropy. More interestingly, due to the magnetoelectric effect, the application of an external electric field locally stabilizes the skyrmions in the twisted bilayer AFM systems, even in the absence of DM interaction. It also allows the skyrmion helicity to change continuously when both the DM interaction and an electric field are present. We show the phase diagram with respect to the strength of interlayer coupling, the DM interaction and an electric field. Our results suggest the possibility of using AFM skyrmions as stable, controllable topological magnetic bits.
2403.04208v1
2024-03-08
A Data Augmentation Pipeline to Generate Synthetic Labeled Datasets of 3D Echocardiography Images using a GAN
Due to privacy issues and limited amount of publicly available labeled datasets in the domain of medical imaging, we propose an image generation pipeline to synthesize 3D echocardiographic images with corresponding ground truth labels, to alleviate the need for data collection and for laborious and error-prone human labeling of images for subsequent Deep Learning (DL) tasks. The proposed method utilizes detailed anatomical segmentations of the heart as ground truth label sources. This initial dataset is combined with a second dataset made up of real 3D echocardiographic images to train a Generative Adversarial Network (GAN) to synthesize realistic 3D cardiovascular Ultrasound images paired with ground truth labels. To generate the synthetic 3D dataset, the trained GAN uses high resolution anatomical models from Computed Tomography (CT) as input. A qualitative analysis of the synthesized images showed that the main structures of the heart are well delineated and closely follow the labels obtained from the anatomical models. To assess the usability of these synthetic images for DL tasks, segmentation algorithms were trained to delineate the left ventricle, left atrium, and myocardium. A quantitative analysis of the 3D segmentations given by the models trained with the synthetic images indicated the potential use of this GAN approach to generate 3D synthetic data, use the data to train DL models for different clinical tasks, and therefore tackle the problem of scarcity of 3D labeled echocardiography datasets.
2403.05384v1
2024-03-10
Dynamical generation of skyrmion and bimeron crystals by a circularly polarized electric field in frustrated magnets
A skyrmion crystal (SkX) has attracted much attention in condensed matter physics, since topologically nontrivial structures induce fascinating physical phenomena. The SkXs have been experimentally observed in a variety of materials, where the Zeeman coupling to the static magnetic field plays an important role in the formation of the SkXs. In this study, we theoretically propose another route to generate the SkXs by using a circularly polarized electric field. We investigate a non-equilibrium steady state in a classical frustrated Heisenberg magnet under the circularly polarized electric field, where the electric field is coupled to the electric polarization via the spin-current mechanism. By numerically solving the Landau-Lifshitz-Gilbert equation at zero temperature, we show that the electric field radiation generates a SkX with a high topological number in the high-frequency regime, where the sign of the skyrmion number is fixed to be negative (positive) under the left (right) circularly polarized field. The intense electric field melts these SkXs and generates isolated skyrmions. We clarify that the microscopic origin is effective electric-field-induced three-spin interactions by adopting the high-frequency expansion in the Floquet formalism. Furthermore, we find that the electric field radiation generates another type of SkXs, a bimeron crystal, in the low-frequency regime. Our results provide a way to generate the SkXs and control the topology by the circularly polarized electric field.
2403.06118v1
2024-03-12
Flexible Non-intrusive Dynamic Instrumentation for WebAssembly
A key strength of managed runtimes over hardware is the ability to gain detailed insight into the dynamic execution of programs with instrumentation. Analyses such as code coverage, execution frequency, tracing, and debugging, are all made easier in a virtual setting. As a portable, low-level bytecode, WebAssembly offers inexpensive in-process sandboxing with high performance. Yet to date, Wasm engines have not offered much insight into executing programs, supporting at best bytecode-level stepping and basic source maps, but no instrumentation capabilities. In this paper, we show the first non-intrusive dynamic instrumentation system for WebAssembly in the open-source Wizard Research Engine. Our innovative design offers a flexible, complete hierarchy of instrumentation primitives that support building high-level, complex analyses in terms of low-level, programmable probes. In contrast to emulation or machine code instrumentation, injecting probes at the bytecode level increases expressiveness and vastly simplifies the implementation by reusing the engine's JIT compiler, interpreter, and deoptimization mechanism rather than building new ones. Wizard supports both dynamic instrumentation insertion and removal while providing consistency guarantees, which is key to composing multiple analyses without interference. We detail a fully-featured implementation in a high-performance multi-tier Wasm engine, show novel optimizations specifically designed to minimize instrumentation overhead, and evaluate performance characteristics under load from various analyses. This design is well-suited for production engine adoption as probes can be implemented to have no impact on production performance when not in use.
2403.07973v1
2024-03-13
Highly confined epsilon-near-zero- and surface-phonon polaritons in SrTiO3 membranes
Recent theoretical studies have suggested that transition metal perovskite oxide membranes can enable surface phonon polaritons in the infrared range with low loss and much stronger subwavelength confinement than bulk crystals. Such modes, however, have not been experimentally observed so far. Here, using a combination of far-field Fourier-transform infrared (FTIR) spectroscopy and near-field synchrotron infrared nanospectroscopy (SINS) imaging, we study the phonon-polaritons in a 100 nm thick freestanding crystalline membrane of SrTiO3 transferred on metallic and dielectric substrates. We observe a symmetric-antisymmetric mode splitting giving rise to epsilon-near-zero and Berreman modes as well as highly confined (by a factor of 10) propagating phonon polaritons, both of which result from the deep-subwavelength thickness of the membranes. Theoretical modeling based on the analytical finite-dipole model and numerical finite-difference methods fully corroborate the experimental results. Our work reveals the potential of oxide membranes as a promising platform for infrared photonics and polaritonics.
2403.08500v1
2024-03-18
Lattice QCD estimates of thermal photon production from the QGP
Thermal photons produced in heavy-ion collision experiments are an important observable for understanding quark-gluon plasma (QGP). The thermal photon rate from the QGP at a given temperature can be calculated from the spectral function of the vector current correlator. Extraction of the spectral function from the lattice correlator is known to be an ill-conditioned problem, as there is no unique solution for a spectral function for a given lattice correlator with statistical errors. The vector current correlator, on the other hand, receives a large ultraviolet contribution from the vacuum, which makes the extraction of the thermal photon rate difficult from this channel. We therefore consider the difference between the transverse and longitudinal part of the spectral function, only capturing the thermal contribution to the current correlator, simplifying the reconstruction significantly. The lattice correlator is calculated for light quarks in quenched QCD at $T=470~$MeV ($\sim 1.5\, T_c$), as well as in 2+1 flavor QCD at $T=220~$MeV ($\sim 1.2 \, T_{pc}$) with $m_{\pi}=320$ MeV. In order to quantify the non-perturbative effects, the lattice correlator is compared with the corresponding $\text{NLO}+\text{LPM}^{\text{LO}}$ estimate of correlator. The reconstruction of the spectral function is performed in several different frameworks, ranging from physics-informed models of the spectral function to more general models in the Backus-Gilbert method and Gaussian Process regression. We find that the resulting photon rates agree within errors.
2403.11647v1
2024-03-20
Optimal Risk-Sensitive Scheduling Policies for Remote Estimation of Autoregressive Markov Processes
We design scheduling policies that minimize a risk-sensitive cost criterion for a remote estimation setup. Since risk-sensitive cost objective takes into account not just the mean value of the cost, but also higher order moments of its probability distribution, the resulting policy is robust to changes in the underlying system's parameters. The setup consists of a sensor that observes a discrete-time autoregressive Markov process, and at each time $t$ decides whether or not to transmit its observations to a remote estimator using an unreliable wireless communication channel after encoding these observations into data packets. We model the communication channel as a Gilbert-Elliott channel \cite{10384144}. Sensor probes the channel \cite{laourine2010betting} and hence knows the channel state at each time $t$ before making scheduling decision. The scheduler has to minimize the expected value of the exponential of the finite horizon cumulative cost that is sum of the following two quantities (i) the cumulative transmission power consumed, (ii) the cumulative squared estimator error. We pose this dynamic optimization problem as a Markov decision process (MDP), in which the system state at time $t$ is composed of (i) the instantaneous error $\Delta(t):= x(t)-a\hat{x}(t-1)$, where $x(t),\hat{x}(t-1)$ are the system state and the estimate at time $t,t-1$ respectively, and (ii) the channel state $c(t)$. We show that there exists an optimal policy that has a threshold structure, i.e., at each time $t$, for each possible channel state $c$, there is a threshold $\D\ust(c)$ such that if the current channel state is $c$, then it transmits only when the error $\D(t)$ exceeds $\D\ust(c)$.
2403.13898v1
2024-03-27
The Correlations of Scene Complexity, Workload, Presence, and Cybersickness in a Task-Based VR Game
This investigation examined the relationships among scene complexity, workload, presence, and cybersickness in virtual reality (VR) environments. Numerous factors can influence the overall VR experience, and existing research on this matter is not yet conclusive, warranting further investigation. In this between-subjects experimental setup, 44 participants engaged in the Pendulum Chair game, with half exposed to a simple scene with lower optic flow and lower familiarity, and the remaining half to a complex scene characterized by higher optic flow and greater familiarity. The study measured the dependent variables workload, presence, and cybersickness and analyzed their correlations. Equivalence testing was also used to compare the simple and complex environments. Results revealed that despite the visible differences between the environments, within the 10% boundaries of the maximum possible value for workload and presence, and 13.6% of the maximum SSQ value, a statistically significant equivalence was observed between the simple and complex scenes. Additionally, a moderate, negative correlation emerged between workload and SSQ scores. The findings suggest two key points: (1) the nature of the task can mitigate the impact of scene complexity factors such as optic flow and familiarity, and (2) the correlation between workload and cybersickness may vary, showing either a positive or negative relationship.
2403.19019v1
2024-03-28
Long-range Phase Coherence and Tunable Second Order $φ_0$-Josephson Effect in a Dirac Semimetal $1T-PtTe_2$
Superconducting diode effects have recently attracted much attention for their potential applications in superconducting logic circuits. Several mechanisms such as magneto-chiral effects, finite momentum Cooper pairing, asymmetric edge currents have been proposed to give rise to a supercurrent diode effect in different materials. In this work, we establish the presence of a large intrinsic Josephson diode effect in a type-II Dirac semimetal $1T-PtTe_2$ facilitated by its helical spin-momentum locking and distinguish it from other extrinsic effects. The magnitude of the Josephson diode effect is shown to be directly correlated to the large second-harmonic component of the supercurrent that is induced by the significant contribution of the topological spin-momentum locked states that promote coherent Andreev processes in the junction. We denote such junctions, where the relative phase between the two harmonics corresponding to charge transfers of $2e$ and $4e$ can be tuned by a magnetic field, as second order ${\phi}_0$-junctions. The direct correspondence between the second harmonic supercurrent component and the diode effect in $1T-PtTe_2$ junctions makes topological semimetals with high transparency an ideal platform to study and implement the Josephson diode effect, while also enabling further research on higher order supercurrent transport in Josephson junctions.
2403.19445v1