Granular retrosplenial cortex layer 2/3 generates high-frequency oscillations dynamically coupled with hippocampal rhythms across brain states.

The granular retrosplenial cortex (gRSC) exhibits high-frequency oscillations (HFOs; ∼150 Hz), which can be driven by a hippocampus-subiculum pathway. How the cellular-synaptic and laminar organization of gRSC facilitates HFOs is unknown. Here, we probe gRSC HFO generation and coupling with hippocampal rhythms using focal optogenetics and silicon-probe recordings in behaving mice. ChR2-mediated excitation of CaMKII-expressing cells in L2/3 or L5 induces HFOs, but spontaneous HFOs are found only in L2/3, where HFO power is highest. HFOs couple to CA1 sharp wave-ripples (SPW-Rs) during rest and the descending phase of theta. gRSC HFO current sources and sinks are the same for events during both SPW-Rs and theta oscillations. Independent component analysis shows that high gamma (50-100 Hz) in CA1 stratum lacunosum moleculare is comodulated with HFO power. HFOs may thus facilitate interregional communication of a multisynaptic loop between the gRSC, hippocampus, and medial entorhinal cortex during distinct brain and behavioral states.

T-DOpE probes reveal sensitivity of hippocampal oscillations to cannabinoids in behaving mice.

Understanding the neural basis of behavior requires monitoring and manipulating combinations of physiological elements and their interactions in behaving animals. We developed a thermal tapering process enabling fabrication of low-cost, flexible probes combining ultrafine features: dense electrodes, optical waveguides, and microfluidic channels. Furthermore, we developed a semi-automated backend connection allowing scalable assembly. We demonstrate T-DOpE (Tapered Drug delivery, Optical stimulation, and Electrophysiology) probes achieve in single neuron-scale devices (1) high-fidelity electrophysiological recording (2) focal drug delivery and (3) optical stimulation. The device tip can be miniaturized (as small as 50 µm) to minimize tissue damage while the ~20 times larger backend allows for industrial-scale connectorization. T-DOpE probes implanted in mouse hippocampus revealed canonical neuronal activity at the level of local field potentials (LFP) and neural spiking. Taking advantage of the triple-functionality of these probes, we monitored LFP while manipulating cannabinoid receptors (CB1R; microfluidic agonist delivery) and CA1 neuronal activity (optogenetics). Focal infusion of CB1R agonist downregulated theta and sharp wave-ripple oscillations (SPW-Rs). Furthermore, we found that CB1R activation reduces sharp wave-ripples by impairing the innate SPW-R-generating ability of the CA1 circuit.

Parallel window decoding enables scalable fault tolerant quantum computation.

Large-scale quantum computers have the potential to hold computational capabilities beyond conventional computers. However, the physical qubits are prone to noise which must be corrected in order to perform fault-tolerant quantum computations. Quantum Error Correction (QEC) provides the path for realizing such computations. QEC generates a continuous stream of data that decoders must process at the rate it is received, which can be as fast as 1 µs per QEC round in superconducting quantum computers. If the decoder infrastructure cannot keep up, a data backlog problem is encountered and the computation runs exponentially slower. Today's leading approaches to quantum error correction are not scalable as existing decoders typically run slower as the problem size is increased, inevitably hitting the backlog problem. Here, we show how to parallelize decoding to achieve almost arbitrary speed, removing this roadblock to scalability. Our parallelization requires some classical feed forward decisions to be delayed, slowing-down the logical clock speed. However, the slow-down is now only polynomial in the size of the QEC code, averting the exponential slowdown. We numerically demonstrate our parallel decoder for the surface code, showing no noticeable reduction in logical fidelity compared to previous decoders and demonstrating the predicted speedup.

Granular retrosplenial cortex layer 2/3 generates high-frequency oscillations coupled with hippocampal theta and gamma in online states or sharp-wave ripples in offline states.

Neuronal oscillations support information transfer by temporally aligning the activity of anatomically distributed 'writer' and 'reader' cell assemblies. High-frequency oscillations (HFOs) such as hippocampal CA1 sharp-wave ripples (SWRs; 100-250 Hz) are sufficiently fast to initiate synaptic plasticity between assemblies and are required for memory consolidation. HFOs are observed in parietal and midline cortices including granular retrosplenial cortex (gRSC). In 'offline' brain states (e.g. quiet wakefulness) gRSC HFOs co-occur with CA1 SWRs, while in 'online' states (e.g. ambulation) HFOs persist with the emergence of theta oscillations. The mechanisms of gRSC HFO oscillations, specifically whether the gRSC can intrinsically generate HFOs, and which layers support HFOs across states, remain unclear. We addressed these issues in behaving mice using optogenetic excitation in individual layers of the gRSC and high density silicon-probe recordings across gRSC layers and hippocampus CA1. Optogenetically induced HFOs (iHFOs) could be elicited by depolarizing excitatory neurons with 100 ms half-sine wave pulses in layer 2/3 (L2/3) or layer 5 (L5) though L5 iHFOs were of lower power than in L2/3. Critically, spontaneous HFOs were only observed in L2/3 and never in L5. Intra-laminar monosynaptic connectivity between excitatory and inhibitory neurons was similar across layers, suggesting other factors restrict HFOs to L2/3. To compare HFOs in online versus offline states we analyzed, separately, HFOs that did or did not co-occur with CA1 SWRs. Using current-source density analysis we found uniform synaptic inputs to L2/3 during all gRSC HFOs, suggesting layer-specific inputs may dictate the localization of HFOs to L2/3. HFOs occurring without SWRs were aligned with the descending phase of both gRSC and CA1 theta oscillations and were coherent with CA1 high frequency gamma oscillations (50-80 Hz). These results demonstrate that gRSC can internally generate HFOs without rhythmic inputs and that HFOs occur exclusively in L2/3, coupled to distinct hippocampal oscillations in online versus offline states.

Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry.

Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.

Water splitting with silicon p-i-n superlattices suspended in solution.

Photoelectrochemical (PEC) water splitting to produce hydrogen fuel was first reported 50 years ago1, yet artificial photosynthesis has not become a widespread technology. Although planar Si solar cells have become a ubiquitous electrical energy source economically competitive with fossil fuels, analogous PEC devices have not been realized, and standard Si p-type/n-type (p-n) junctions cannot be used for water splitting because the bandgap precludes the generation of the needed photovoltage. An alternative paradigm, the particle suspension reactor (PSR), forgoes the rigid design in favour of individual PEC particles suspended in solution, a potentially low-cost option compared with planar systems2,3. Here we report Si-based PSRs by synthesizing high-photovoltage multijunction Si nanowires (SiNWs) that are co-functionalized to catalytically split water. By encoding a p-type-intrinsic-n-type (p-i-n) superlattice within single SiNWs, tunable photovoltages exceeding 10 V were observed under 1 sun illumination. Spatioselective photoelectrodeposition of oxygen and hydrogen evolution co-catalysts enabled water splitting at infrared wavelengths up to approximately 1,050 nm, with the efficiency and spectral dependence of hydrogen generation dictated by the photonic characteristics of the sub-wavelength-diameter SiNWs. Although initial energy conversion efficiencies are low, multijunction SiNWs bring the photonic advantages of a tunable, mesoscale geometry and the material advantages of Si-including the small bandgap and economies of scale-to the PSR design, providing a new approach for water-splitting reactors.

Randomized Quantum Algorithm for Statistical Phase Estimation.

Phase estimation is a quantum algorithm for measuring the eigenvalues of a Hamiltonian. We propose and rigorously analyze a randomized phase estimation algorithm with two distinctive features. First, our algorithm has complexity independent of the number of terms L in the Hamiltonian. Second, unlike previous L-independent approaches, such as those based on qDRIFT, all algorithmic errors in our method can be suppressed by collecting more data samples, without increasing the circuit depth.

Probiotic Treatment Enhances Pre-feeding Larval Development and Early Survival in Zebrafish Danio rerio.

The growth and development of healthy culture subjects are essential in increasing productivity in the aquaculture industry. A primary determinant of aquatic animal productivity is the ambient microbial population. If an aquatic animal's microbiome is diverse, with bacteria favoring beneficial over pathogenic species, the health and growth of the animal (i.e., fish or crustacean) can be substantially improved. Embryonic and newly hatched Zebrafish Danio rerio larvae were reared in the presence of (1) water from the broodstock culture tank as a control, (2) a probiotic solution containing 19 strains of live lactic acid bacteria (LAB), or (3) an antibiotic (AB) solution with amoxycillin. Developmental parameters were monitored until 10 d postfertilization. Bacteria present in the water and larvae were cultured and identified by sequencing the V4 hypervariable region of bacterial 16S ribosomal RNA. Probiotic-treated larvae showed significant increases in every measured morphological parameter and in survival compared to the controls and AB-treated larvae, including TL, eye development, and swim bladder development before first feeding. Staining with DASPEI (2-(4-[dimethylamino]styryl)-N-ethylpyridinium iodide) produced fluorescence, revealing increased mitochondrial activity in the gastrointestinal tracts of probiotic-treated larvae and reflecting advancement of initial metabolic function. Probiotic-treated larvae showed accelerated yolk absorption, resulting in increased nutrient mobilization and growth. Microbial analyses revealed a greater concentration of bacteria in larvae in response to the probiotic treatment compared to the other two treatments. Species identified in all three treatments included Pseudomonas spp. and Aeromonas spp. (Proteobacteria). The second most diverse and abundant microbiome was seen in controls, whereas AB-treated larvae had the least diverse microbiome. All treatments revealed the presence of proteobacteria, but an AB-resistant pathogenic bacterium (Stenotrophomonas maltophilia) was identified in the AB group. These results reveal that the presence of LAB and other bacteria favorably influenced early larval growth, development, digestive function, and survival in Zebrafish even before the onset of feeding.

Electrostatic tip effects in scanning probe microscopy of nanostructures.

Electrical scanning probe microscopies (SPM) use ultrasharp metallic tips to obtain nanometer spatial resolution and are a key tool for characterizing nanoscale semiconducting materials and systems. However, these tips are not passive probes; their high work functions can induce local band bending whose effects depend sensitively on the local geometry and material properties and thus are inherently difficult to quantify. We use sequential finite element simulations to first explore the magnitude and spatial distribution of charge reorganization due to tip-induced band bending (TIBB) for planar and nanostructured geometries. We demonstrate that tip-induced depletion and accumulation of carriers can be significantly modified in confined geometries such as nanowires compared to a bulk planar response. This charge reorganization is due to finite size effects that arise as the nanostructure size approaches the Debye length, with significant implications for a range of SPM techniques. We then use the reorganized charge distribution from our model to describe experimentally measured quantities, using in operando scanning microwave impedance microscopy measurements on axial p-i-n silicon nanowire devices as a specific example. By incorporating TIBB, we reveal that our experimentally observed enhancement (absence) of contrast at the p-i (i-n) junction is explained by the tip-induced accumulation (depletion) of carriers at the interface. Our results demonstrate that the inclusion of TIBB is critical for an accurate interpretation of electrical SPM measurements, and is especially important for weakly screening or low-doped materials, as well as the complex doping patterns and confined geometries commonly encountered in nanoscale systems.

Financial Preparedness for Birth Among Rural Zambian Women: Do Antenatal Care Contacts Make a Difference?

INTRODUCTION: Financial constraints are one of the biggest barriers for women of low-income countries to receive necessary reproductive health services. Educating women about the importance of saving money has been incorporated as a component of antenatal care (ANC) contacts, but little is known whether ANC contacts influence women's saving. METHODS: A secondary analysis was conducted on data from a cross-sectional household survey study of 1109 women who recently gave birth in two rural districts of Zambia. RESULTS: Receiving ANC contacts early and often and discussing saving money during ANC were associated with saving money for the mother's birth, but not with saving enough money for the most recent birth. DISCUSSION: Continued effort is needed to encourage women to attend ANC contacts earlier and more frequently. Additionally, the importance of saving money for birth should be discussed during ANC contacts. Future studies need to explore why women's action in saving does not necessarily lead to saving enough for childbirth.

Detecting Malware with Information Complexity.

Malware concealment is the predominant strategy for malware propagation. Black hats create variants of malware based on polymorphism and metamorphism. Malware variants, by definition, share some information. Although the concealment strategy alters this information, there are still patterns on the software. Given a zoo of labelled malware and benign-ware, we ask whether a suspect program is more similar to our malware or to our benign-ware. Normalized Compression Distance (NCD) is a generic metric that measures the shared information content of two strings. This measure opens a new front in the malware arms race, one where the countermeasures promise to be more costly for malware writers, who must now obfuscate patterns as strings qua strings, without reference to execution, in their variants. Our approach classifies disk-resident malware with 97.4% accuracy and a false positive rate of 3%. We demonstrate that its accuracy can be improved by combining NCD with the compressibility rates of executables using decision forests, paving the way for future improvements. We demonstrate that malware reported within a narrow time frame of a few days is more homogeneous than malware reported over two years, but that our method still classifies the latter with 95.2% accuracy and a 5% false positive rate. Due to its use of compression, the time and computation cost of our method is nontrivial. We show that simple approximation techniques can improve its running time by up to 63%. We compare our results to the results of applying the 59 anti-malware programs used on the VirusTotal website to our malware. Our approach outperforms each one used alone and matches that of all of them used collectively.

Quantifying magic for multi-qubit operations.

The development of a framework for quantifying 'non-stabilizerness' of quantum operations is motivated by the magic state model of fault-tolerant quantum computation and by the need to estimate classical simulation cost for noisy intermediate-scale quantum (NISQ) devices. The robustness of magic was recently proposed as a well-behaved magic monotone for multi-qubit states and quantifies the simulation overhead of circuits composed of Clifford + T gates, or circuits using other gates from the Clifford hierarchy. Here we present a general theory of the 'non-stabilizerness' of quantum operations rather than states, which are useful for classical simulation of more general circuits. We introduce two magic monotones, called channel robustness and magic capacity, which are well-defined for general n-qubit channels and treat all stabilizer-preserving CPTP maps as free operations. We present two complementary Monte Carlo-type classical simulation algorithms with sample complexity given by these quantities and provide examples of channels where the complexity of our algorithms is exponentially better than previously known simulators. We present additional techniques that ease the difficulty of calculating our monotones for special classes of channels.

Interplay of Surface Recombination and Diode Geometry for the Performance of Axial p-i-n Nanowire Solar Cells.

Nanowires (NWs) with axial p-i-n junctions have been widely explored as microscopic diodes for optoelectronic and solar energy applications, and their performance is strongly influenced by charge recombination at the surface. We delineate how the photovoltaic performance of these diodes is dictated not only by the surface but also by the complex and seemingly counterintuitive interplay of diode geometry, that is, radius ( R) and intrinsic length ( Li), with the surface recombination velocity ( S). An analytical model to describe these relationships is developed and compared to finite-element simulations, which verify the accuracy and limitations of the model. The dependence of the dark saturation current ( I0), internal quantum efficiency (IQE), short-circuit current ( ISC), and open-circuit voltage ( VOC) on both geometric and recombination parameters demonstrates that no single set of parameters produces optimal performance; instead, various trade-offs in performance are observed. For instance, longer Li might be expected to produce higher ISC, yet at high values of S the ISC declines because of decreases in IQE. Moreover, longer Li produces a concurrent decline in VOC regardless of S due to increases in I0. We also find that ISC and VOC trends are radius independent, yet I0 is directly proportional to R, causing NWs with smaller R to display higher turn-on voltages. The analysis regarding the interplay of these parameters, verified by experimental measurements with various p-i-n geometries and surface treatments, provides clear guidance for the rational design of performance metrics for photodiode and photovoltaic devices.

Author Correction: Roads towards fault-tolerant universal quantum computation.

In Fig. 2b of this Review, two of the gates were inadvertently swapped. At the top right, 'Xa+c' should have been 'Zb', and at the bottom right 'Zb' should have been 'Xa+c'. Fig. 2b has been corrected online. The Supplementary Information of this Author Correction contains the original, incorrect Fig. 2b, for transparency.

Mapping Free-Carriers in Multijunction Silicon Nanowires Using Infrared Near-Field Optical Microscopy.

We report the use of infrared (IR) scattering-type scanning near-field optical microscopy (s-SNOM) as a nondestructive method to map free-carriers in axially modulation-doped silicon nanowires (SiNWs) with nanoscale spatial resolution. Using this technique, we can detect local changes in the electrically active doping concentration based on the infrared free-carrier response in SiNWs grown using the vapor-liquid-solid (VLS) method. We demonstrate that IR s-SNOM is sensitive to both p-type and n-type free-carriers for carrier densities above ∼1 × 1019 cm-3. We also resolve subtle changes in local conductivity properties, which can be correlated with growth conditions and surface effects. The use of s-SNOM is especially valuable in low mobility materials such as boron-doped p-type SiNWs, where optimization of growth has been difficult to achieve due to the lack of information on dopant distribution and junction properties. s-SNOM can be widely employed for the nondestructive characterization of nanostructured material synthesis and local electronic properties without the need for contacts or inert atmosphere.