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At least 1,729 records · Page 96

Hilbert space structure in quantum gravity: an algebraic perspective

If quantum gravity respects the principles of quantum mechanics, suitably generalized, it may be that a more viable approach to the theory is through identifying the relevant quantum structures rather than by quantizing classical spacetime. Here, this viewpoint is supported by difficulties of such quantization, and by the apparent lack of a fundamental role for locality. In finite or discrete quantum systems, important structure is provided by tensor factorizations of the Hilbert space. However, even in local quantum field theory properties of the generic type III von Neumann algebras and of long range gauge fields indicate that factorization of the Hilbert space is problematic. Instead it is better to focus on the structure of the algebra of observables, and in particular on its subalgebras corresponding to regions. This paper suggests that study of analogous algebraic structure in gravity gives an important perspective on the nature of the quantum theory. Significant departures from the subalgebra structure of local quantum field theory are found, working in the correspondence limit of long-distances/low-energies. Particularly, there are obstacles to identifying commuting algebras of localized operators. In addition to suggesting important properties of the algebraic structure, this and related observations pose challenges to proposals of a fundamental role for entanglement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bulk locality and cooperative flows

We use the ‘bit thread’ formulation of holographic entanglement entropy to highlight the distinction between the universally-valid strong subadditivity and the more restrictive relation called monogamy of mutual information (MMI), known to hold for geometrical states (i.e. states of holographic theories with gravitational duals describing a classical bulk geometry). In particular, we provide a novel proof of MMI, using bit threads directly. To this end, we present an explicit geometrical construction of cooperative flows which we build out of disjoint thread bundles. We conjecture that our method applies in a wide class of configurations, including ones with non-trivial topology, causal structure, and time dependence. The explicit nature of the construction reveals that MMI is more deeply rooted in bulk locality than is the case for strong subadditivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Schrödinger evolution of two-dimensional black holes

This paper systematically treats the evolving quantum state for two-dimensional black holes, with particular focus on the CGHS model, but also elucidating features generalizing to higher dimensions. This is done in Schrödinger picture(s), to exhibit the dynamic evolution of the state at intermediate times. After a review of classical solutions, also connecting to descriptions of higher-dimensional black holes, it overviews the canonical quantum treatment of the full evolution, including gravitational dynamics. Derived in an approximation to this, following conversion to “perturbation picture”, is the evolution of the quantum matter on the background geometry. Features of the evolving matter state are described, based on choice of a time slicing to put the evolution into ADM form. The choices of slicing as well as coordinates on the slices result in different quantum “pictures” for treating the evolution. If such a description is based on smooth trans-horizon slices, that avoids explicit reference to ultra-planckian modes familiar from traditional treatments, and exhibits the Hawking excitations as emerging from a “quantum atmosphere” with thickness comparable to the inverse temperature. Detailed study of the state exhibits the entanglement structure between Hawking quanta and the partner excitations inside the black hole, and the corresponding “missing information”. This explicit description also allows direct study of the evolution and features, e.g. as seen by infalling observers, of these partner excitations, helping to address various puzzles with them. Explicit treatment of the evolving state, and its extension to higher dimensions, provides further connections to information theory and a starting point for study of corrections that can unitarize evolution, arising from new quantum gravity effects — whether wormholes or something entirely different.

2D Gravity↗

Crossing Versus Locking: Bit Threads and Continuum Multiflows

Bit threads are curves in holographic spacetimes that manifest boundary entanglement, and are represented mathematically by continuum analogues of network flows or multiflows. Subject to a density bound, the maximum number of threads connecting a boundary region to its complement computes the Ryu–Takayanagi entropy. When considering several regions at the same time, for example in proving entropy inequalities, there are various inequivalent density bounds that can be imposed. Here, we investigate for which choices of bound a given set of boundary regions can be “locked”, in other words can have their entropies computed by a single thread configuration. We show that under the most stringent bound, which requires the threads to be locally parallel, non-crossing regions can in general be locked, but crossing regions cannot, where two regions are said to cross if they partially overlap and do not cover the entire boundary. We also show that, under a certain less stringent density bound, a crossing pair can be locked, and conjecture that any set of regions not containing a pairwise crossing triple can be locked, analogously to the situation for networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Absence of Barren Plateaus and Scaling of Gradients in the Energy Optimization of Isometric Tensor Network States

Abstract Vanishing gradients can pose substantial obstacles for high-dimensional optimization problems. Here we consider energy minimization problems for quantum many-body systems with extensive Hamiltonians and finite-range interactions, which can be studied on classical computers or in the form of variational quantum eigensolvers on quantum computers. Barren plateaus correspond to scenarios where the average amplitude of the energy gradient decreases exponentially with increasing system size. This occurs, for example, for quantum neural networks and for brickwall quantum circuits when the depth increases polynomially in the system size. Here we prove that the variational optimization problems for matrix product states, tree tensor networks, and the multiscale entanglement renormalization ansatz are free of barren plateaus. The derived scaling properties for the gradient variance provide an analytical guarantee for the trainability of randomly initialized tensor network states (TNS) and motivate certain initialization schemes. In a suitable representation, unitary tensors that parametrize the TNS are sampled according to the uniform Haar measure. We employ a Riemannian formulation of the gradient based optimizations which simplifies the analytical evaluation.

Barthel, Thomas↗

Structure/property relationship of semicrystalline polymers during tensile deformation: a molecular dynamics approach

Molecular dynamics (MD) simulation with an ab initio numerical model is conducted to study the structure–property relationship of semicrystalline polymers during uniaxial deformation. The effects of chain length, temperature, and strain rate on mechanical properties are discussed. The influences of microstructural evolution such as bond length, entanglement density, and chain orientation are also studied quantitatively. The temperature will greatly affect the chain conformation in amorphous domains, and the results revealed that the interaction of amorphous and crystalline domains played a crucial role during stretching. Accordingly, the yielding of semicrystalline polymers follows different mechanisms at temperatures above and below T g . A melt-recrystallization scheme is observed during yielding at higher temperatures, while destruction of crystal structures is observed at lower temperatures at the yield point. The correlated effects of different temperatures and strain rates on mechanical properties are examined. This research is part of our efforts to develop a digital twin of a real experiment for efficient optimization of polymer material properties.

36 MATERIALS SCIENCE↗

Single-point parallel disk correction for asymptotically nonlinear oscillatory shear

We derive exact single-point corrections for parallel disk measurements of all four asymptotically nonlinear measures under strain-controlled oscillatory shear. In this regime, sometimes called medium-amplitude oscillatory shear (MAOS), the derivatives appearing in the general stress correction are constant over the range of interest. This enables an exact single-point correction of all four shear stress components and material functions in the asymptotically nonlinear regime. This greatly simplifies the data processing and allows convenient measurements of true nonlinear material functions with parallel disk geometries. We use a strain amplitude expansion for the stress response, introducing a general non-integer strain amplitude scaling for the leading order nonlinearity, σ ~ γ α , where typically α = 3 has been assumed in the past. The stress corrections are a multiplicative amplification by a factor f(α) = α+3/4, shown for the first time for all four asymptotically nonlinear coefficients. Experimental measurements are presented for the four asymptotically nonlinear signals on an entangled polymer melt of cis-1,4-polyisoprene, using both parallel disk and cone fixtures. The polymer melt follows a cubic (α = 3) strain amplitude scaling in the MAOS regime. Furthermore, the theoretical corrections indicate a 50 % amplification of the apparent signals measured with the parallel disk fixture. The corrected (amplified) signals match the measurements with the cone.

42 ENGINEERING↗

Arabinose substitution effect on xylan rigidity and self-aggregation

Substituted xylans play an important role in the structure and mechanics of the primary cell wall of plants. Arabinoxylans (AX) consist of a xylose backbone substituted with arabinose, while glucuronoarabinoxylans (GAX) also contain glucuronic acid substitutions and ferulic acid esters on some of the arabinoses. Here, we provide a molecular-level description on the dependence of xylan conformational, self-aggregation properties and binding to cellulose on the degree of arabinose substitution. Molecular dynamics simulations reveal fully solubilized xylans with a low degree of arabinose substitution (lsAX) to be stiffer than their highly substituted (hsAX) counterparts. Small-angle neutron scattering experiments indicate that both wild-type hsAX and debranched lsAX form macromolecular networks that are penetrated by water. In those networks, lsAX are more folded and entangled than hsAX chains. Increased conformational entropy upon network formation for hsAX contributes to AX loss of solubility upon debranching. Furthermore, simulations show the intermolecular contacts to cellulose are not affected by arabinose substitution (within the margin of error). Ferulic acid is the GAX moiety found here to bind to cellulose most strongly, suggesting it may play an anchoring role to strengthen GAX-cellulose interactions. The above results suggest highly substituted GAX acts as a spacer, keeping cellulose microfibrils apart, whereas low substitution GAX is more localized in plant cell walls and promotes cellulose bundling.

59 BASIC BIOLOGICAL SCIENCES↗

Resolving the black hole causality paradox

The black hole information paradox is actually a combination of two problems: the causality paradox and the entanglement problem. The causality paradox arises because in the semiclassical approximation infalling matter gets causally trapped inside its own horizon; it is therefore unable to send its information back to infinity if we disallow propagation outside the light cone. We show how the causality paradox is resolved in the fuzzball paradigm. One needs to consider between two kinds of Rindler spaces: (a) Rindler space obtained by choosing accelerating coordinates in Minkowski space and (b) `pseudo-Rindler' space, which describes the region near the surface of a fuzzball. These two spaces differ in their vacuum fluctuations. While low energy waves propagate the same way on both spaces, infalling objects with energies $E\gg T$ suffer an `entropy enhanced tunneling' in the pseudo-Rindler spacetime (b); this leads to the nucleation of a fuzzball before the infalling object gets trapped inside a horizon.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Novel Hyperbranched Polymeric Flocculant for Waste-Water Treatment

Cationic hyperbranched oligomer poly(N-acryloyl-1,2-diaminoethane hydrochloride) (HADE) was firstly synthesized by Michael addition reaction. And then, a series of cationic flocculants poly(acrylamide/N-acryloyl-1,2-diaminoethane hydrochlorides) (PAM-HADEs) with hyperbranched structure was prepared from HADE as macro-monomer and acrylamide (AM). The structures of PAM-HADEs were characterized by Fourier transform infrared spectrometry, {sup 1}H and {sup 13}C nuclear magnetic resonance spectroscopy, gel permeation chromatography (GPC) and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF). And the properties were systematically evaluated by intrinsic viscosity, zeta potential and hydrodynamic radius. The mechanism of the cationic hyperbranched copolymer used in water treatment was extensively studied via a jar test in which the transmittance of the supernatant, settling time, and average floc size were used to evaluate the flocculability. Compared with the linear flocculant poly (acrylamide/liner-N-acryloyl-1,2-diaminoethane hydrochloride) (PAM-LADE), the novel hyperbranched polymeric flocculants exhibited outstanding flocculability which were reflected by shorter settlement time, high transmittance and large floc size. The primary cause that PAM-HADEs owned excellent flocculability is the more stretching configuration and less chains entanglement of PAM-HADEs in waste-water due to their hyperbranched structure compared with that of the linear PAM-LADE which exhibited curly coil configuration. On the other hand, abundant and exposed cationic terminal groups of PAM-HADEs originated from their hyperbranched structure also hint higher flocculation capacity. At optimum dosages of the polymer, the transmittance of the supernatant is less at low and high pH values, indicating that the natural pH (pH 7.29) of the suspension is the most appropriate pH for the flocculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Novel Wastewater Treating Material: Cationic Poly Acrylamide/Diatomite Composite Flocculant

In this work, poly(methacrylatoethyl trimethyl ammonium chloride -co-acrylamide)/diatomite composite flocculant was synthesized via in situ polymerization in aqueous solution and applied in waste water treatment. The structure of composite flocculants was characterized by FT-IR, {sup 1}HNMR and XRD, TGA and viscometer. Herein, the apparent viscosity of composite flocculants was employed as comparison standard of their performance to evaluate the influence of the reaction parameters, such as monomer feeding ratio, diatomite mass fraction and polymerization temperature, etc. on their flocculation performance. And based on the above investigations, the optimum synthesis condition could be found. By comparing flocculation properties of composite flocculants with that of the conventional cationic flocculant, the dosage of composite flocculant that could make the transmittance of treated waste water exceed 95 % was only 7.5 ppm which was far lower than that of conventional flocculant (60–90 ppm). Meanwhile, the settling time was lower than 5 s which was similarly to that of conventional flocculant. Finally, the conclusion was that the composite flocculant owned higher absorption capacity and larger chain extending space than those of conventional linear flocculant due to the introduction of diatomite as backbone, which could make linear polymer chains free from entanglement and improve the flocculation capacity notably.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solving MaxCut with quantum imaginary time evolution

We introduce a method to solve the MaxCut problem efficiently based on quantum imaginary time evolution (QITE). We employ a linear Ansatz for unitary updates and an initial state involving no entanglement, as well as an imaginary-time-dependent Hamiltonian interpolating between a given graph and a subgraph with two edges excised. We apply the method to thousands of randomly selected graphs with up to fifty vertices. We show that our algorithm exhibits a 93% and above performance converging to the maximum solution of the MaxCut problem for all considered graphs. Our results compare favorably with the performance of classical algorithms, such as the greedy and Goemans–Williamson algorithms. We also discuss the overlap of the final state of the QITE algorithm with the ground state as a performance metric, which is a quantum feature not shared by other classical algorithms.

97 MATHEMATICS AND COMPUTING↗

Robust implementation of generative modeling with parametrized quantum circuits

Although the performance of hybrid quantum-classical algorithms is highly dependent on the selection of the classical optimizer and the circuit ansätze, a robust and thorough assessment on-hardware of such features has been missing to date. From the optimizer perspective, the primary challenge lies in the solver’s stochastic nature, and their significant variance over the random initialization. Therefore, a robust comparison requires one to perform several training curves for each solver before one can reach conclusions about their typical performance. Since each of the training curves requires the execution of thousands of quantum circuits in the quantum computer, such a robust study remained a steep challenge for most hybrid platforms available today. In this work, we leverage on Rigetti’s Quantum Cloud Services (QCS™) to overcome this implementation barrier, and we study the on-hardware performance of the data-driven quantum circuit learning (DDQCL) for three different state-of-the-art classical solvers, and on two-different circuit ansätze associated to different entangling connectivity graphs for the same task. Additionally, we assess the gains in performance from varying circuit depths. To evaluate the typical performance associated with each of these settings in this benchmark study, we use at least five independent runs of DDQCL towards the generation of quantum generative models capable of capturing the patterns of the canonical Bars and Stripes dataset. In this experimental benchmarking, the gradient-free optimization algorithms show an outstanding performance compared to the gradient-based solver. In particular, one of them had better performance when handling the unavoidable noisy objective function to be minimized under experimental conditions.

97 MATHEMATICS AND COMPUTING↗

Mode connectivity in the loss landscape of parameterized quantum circuits

Variational training of parameterized quantum circuits (PQCs) underpins many workflows employed on near-term noisy intermediate scale quantum (NISQ) devices. It is a hybrid quantum-classical approach that minimizes an associated cost function in order to train a parameterized ansatz. In this work we adapt the qualitative loss landscape characterization for neural networks introduced in Goodfellow et al. (2014); Li et al. (2017) and tests for connectivity used in Draxler et al. (2018) to study the loss landscape features in PQC training. We present results for PQCs trained on a simple regression task, using the bilayer circuit ansatz, which consists of alternating layers of parameterized rotation gates and entangling gates. Multiple circuits are trained with 3 different batch gradient optimizers: stochastic gradient descent, the quantum natural gradient, and Adam. We identify large features in the landscape that can lead to faster convergence in training workflows.

97 MATHEMATICS AND COMPUTING↗

Quantum circuit fidelity estimation using machine learning

The computational power of real-world quantum computers is limited by errors. When using quantum computers to perform algorithms which cannot be efficiently simulated classically, it is important to quantify the accuracy with which the computation has been performed. In this work, we introduce a machine learning-based technique to estimate the fidelity between the state produced by a noisy quantum circuit and the target state corresponding to ideal noise-free computation. Our machine learning model is trained in a supervised manner, using smaller or simpler circuits for which the fidelity can be estimated using other techniques like direct fidelity estimation and quantum state tomography. Here we demonstrate that, for simulated random quantum circuits with a realistic noise model, the trained model can predict the fidelities of more complicated circuits for which such methods are infeasible. In particular, we show that the trained model may make predictions for circuits with higher degrees of entanglement than were available in the training set and that the model may make predictions for non-Clifford circuits even when the training set included only Clifford-reducible circuits. This empirical demonstration suggests classical machine learning may be useful for making predictions about beyond-classical quantum circuits for some non-trivial problems.

97 MATHEMATICS AND COMPUTING↗

Effect of 3D printing conditions on the micro- and macrostructure and properties of high-performance thermoplastic composites

Within the scope of extrusion based additive manufacturing, this chapter provides a review of the research in understanding the physical relationships between microstructure variables and macrostructure properties of high-performance thermoplastic polymers. The development of interlayer strength has been discussed based on the theory of inter-diffusion and re-entanglement of polymer chains at interface. The observations from the study in joining and direct-bonding of polymer surfaces provide insights into the mechanisms of the formation of interface between adjacent layers. Quantitative prediction of interfacial strength as a function of processing temperature and contact time is presented. The mechanisms that lead to reduced mechanical strength at the interface are discussed. The second half of the chapter outlined a set of printing conditions and their influence on structural properties.

Liu, Peng↗

Hydrogen Bonding Stiffens Peptide Amphiphile Supramolecular Filaments by Aza-Glycine Residues

Peptide amphiphiles (PAs) are a class of molecules comprised of short amino acid sequences conjugated to hydrophobic moieties that may exhibit self-assembly in water into supramolecular structures. Here, we investigate here how mechanical properties of hydrogels formed by PA supramolecular nanofibers are affected by hydrogen bond densities within their internal structure by substituting glycine for aza-glycine (azaG) residues. We found that increasing the number of PA molecules that contain azaG up to 5 mol% in PA supramolecular nanofibers increases their persistence length fivefold and decreases their diffusion coefficients as measured by fluorescence recovery after photobleaching. When these PAs are used to create hydrogels, their bulk storage modulus (G') was found to increase as azaG PA content in the supramolecular assemblies increases up to a value of 10 mol% and beyond this value a decrease was observed, likely due to diminished levels of nanofiber entanglement in the hydrogels as a direct result of increased supramolecular rigidity. Interestingly, we found that the bioactivity of the scaffolds toward dopaminergic neurons derived from induced pluripotent stem cells can be enhanced directly by persistence length independently of storage modulus. We hypothesize that this is due to interactions between the cells and the extracellular environment across different size scales: from filopodia adhering to individual nanofiber bundles to cell adhesion sites that interact with the hydrogel as a bulk substrate. Fine tuning of hydrogen bond density in self-assembling peptide biomaterials such as PAs provides an approach to control nanoscale stiffness as part of an overall strategy to optimize bioactivity in these supramolecular systems. supramolecular biomaterials.

36 MATERIALS SCIENCE↗

Controlling substrate temperature with infrared heating to improve mechanical properties of large-scale printed parts

Additively manufactured parts made with polymer extrusion techniques can be 50-75% weaker in the z-direction (across layers) than in the x- and y-directions. This has been attributed to poor mobility of polymer chains and a low degree of entanglement across a cold deposition interface. This is particularly a challenge when printing large-scale parts, such as with the Big Area Additive Manufacturing (BAAM) system, because layer times can exceed several minutes. The current work presents a method for controlling the temperature of the substrate material on the BAAM just prior to deposition using infrared heating lamps. Additionally, long layer times were simulated by actively cooling the material following deposition of each layer. The effect of substrate temperature on the z-direction mechanical properties of 20% carbon fiber reinforced acrylonitrile butadiene styrene (ABS) was measured for an initial temperature ranging from 50 °C to 150 °C and a preheated temperature ranging from 150 °C to 220 °C. Infrared preheating proved to be very effective when applied to substrates that had cooled considerably, almost doubling the tensile strength and increasing the fracture toughness by a factor of 7x.

36 MATERIALS SCIENCE↗