Geographic Variation in Larval Metabolic Rate Between Northern and Southern Populations of the Invasive Gypsy Moth

Thermal regimes can diverge considerably across the geographic range of a species, and accordingly, populations can vary in their response to changing environmental conditions. Both local adaptation and acclimatization are important mechanisms for ectotherms to maintain homeostasis as environments become thermally stressful, which organisms often experience at their geographic range limits. The spatial spread of the gypsy moth (Lymantria dispar L.) (Lepidoptera: Erebidae) after introduction to North America provides an exemplary system for studying population variation in physiological traits given the gradient of climates encompassed by its current invasive range. This study quantifies differences in resting metabolic rate (RMR) across temperature for four populations of gypsy moth, two from the northern and two from southern regions of their introduced range in North America. Gypsy moth larvae were reared at high and low thermal regimes, and then metabolic activity was monitored at four temperatures using stop-flow respirometry to test for an acclimation response. For all populations, there was a significant increase in RMR as respirometry test temperature increased. Contrary to our expectations, we did not find evidence for metabolic adaptation to colder environments based on our comparisons between northern and southern populations. We also found no evidence for an acclimation response of RMR to rearing temperature for three of the four pairwise comparisons examined. Understanding the thermal sensitivity of metabolic rate in gypsy moth, and understanding the potential for changes in physiology at range extremes, is critical for estimating continued spatial spread of this invasive species both under current and potential future climatic constraints

Efficient system for bulk characterization of cryogenic CMOS components

Semiconductor integrated circuits operated at cryogenic temperature will play an essential role in quantum computing architectures. These can offer equivalent or superior performance to their room-temperature counterparts while enabling a scaling up of the total number of qubits under control. Silicon integrated circuits can be operated at a temperature stage of a cryogenic system where cooling power is sufficient (∼3.5+ K) to allow for analog signal chain components (e.g. amplifiers and mixers), local signal synthesis, signal digitization, and control logic. A critical stage in cryo-electronics development is the characterization of individual transistor devices in a particular technology node at cryogenic temperatures. This data enables the creation of a process design kit (PDK) to model devices and simulate integrated circuits operating well below the minimum standard temperature ranges covered by foundry-released models (e.g. -55 °C). Here, an efficient approach to the characterization of large numbers of components at cryogenic temperature is reported. We developed a system to perform DC measurements with Kelvin sense of individual transistors at 4.2 K using integrated on-die multiplexers, enabling bulk characterization of thousands of devices with no physical change to the measurement setup

Rapid cryogenic characterisation of 1024 integrated silicon quantum dots

Quantum computers are nearing the thousand qubit mark, with the current focus on scaling to improve computational performance. As quantum processors grow in complexity, new challenges arise such as the management of device variability and the interface with supporting electronics. Spin qubits in silicon quantum dots are poised to address these challenges with their proven control fidelities and potential for compatibility with large-scale integration. Here, we demonstrate the integration of 1024 silicon quantum dots with on-chip digital and analogue electronics, all operating below 1 K. A high-frequency analogue multiplexer provides fast access to all devices with minimal electrical connections, enabling characteristic data across the quantum dot array to be acquired in just 5 minutes. We achieve this by leveraging radio-frequency reflectometry with state-of-the-art signal integrity, reaching a minimum integration time of 160 ps. Key quantum dot parameters are extracted by fast automated machine learning routines to assess quantum dot yield and understand the impact of device design. We find correlations between quantum dot parameters and room temperature transistor behaviour that may be used as a proxy for in-line process monitoring. Our results show how rapid large-scale studies of silicon quantum devices can be performed at lower temperatures and measurement rates orders of magnitude faster than current probing techniques, and form a platform for the future on-chip addressing of large scale qubit arrays.Comment: Main text: 14 pages, 8 figures, 1 table Supplementary: 8 pages, 6 figure

Overcoming leakage in scalable quantum error correction

Leakage of quantum information out of computational states into higher energy states represents a major challenge in the pursuit of quantum error correction (QEC). In a QEC circuit, leakage builds over time and spreads through multi-qubit interactions. This leads to correlated errors that degrade the exponential suppression of logical error with scale, challenging the feasibility of QEC as a path towards fault-tolerant quantum computation. Here, we demonstrate the execution of a distance-3 surface code and distance-21 bit-flip code on a Sycamore quantum processor where leakage is removed from all qubits in each cycle. This shortens the lifetime of leakage and curtails its ability to spread and induce correlated errors. We report a ten-fold reduction in steady-state leakage population on the data qubits encoding the logical state and an average leakage population of less than $1 \times 10^{-3}$ throughout the entire device. The leakage removal process itself efficiently returns leakage population back to the computational basis, and adding it to a code circuit prevents leakage from inducing correlated error across cycles, restoring a fundamental assumption of QEC. With this demonstration that leakage can be contained, we resolve a key challenge for practical QEC at scale.Comment: Main text: 7 pages, 5 figure

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the 1D Heisenberg model were conjectured to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we study the probability distribution, $P(\mathcal{M})$, of the magnetization transferred across the chain's center. The first two moments of $P(\mathcal{M})$ show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments rule out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide key insights into universal behavior in quantum systems

Measurement-induced entanglement and teleportation on a noisy quantum processor

Measurement has a special role in quantum theory: by collapsing the wavefunction it can enable phenomena such as teleportation and thereby alter the "arrow of time" that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time that go beyond established paradigms for characterizing phases, either in or out of equilibrium. On present-day NISQ processors, the experimental realization of this physics is challenging due to noise, hardware limitations, and the stochastic nature of quantum measurement. Here we address each of these experimental challenges and investigate measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping, to avoid mid-circuit measurement and access different manifestations of the underlying phases -- from entanglement scaling to measurement-induced teleportation -- in a unified way. We obtain finite-size signatures of a phase transition with a decoding protocol that correlates the experimental measurement record with classical simulation data. The phases display sharply different sensitivity to noise, which we exploit to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realize measurement-induced physics at scales that are at the limits of current NISQ processors

Non-Abelian braiding of graph vertices in a superconducting processor

Indistinguishability of particles is a fundamental principle of quantum mechanics. For all elementary and quasiparticles observed to date - including fermions, bosons, and Abelian anyons - this principle guarantees that the braiding of identical particles leaves the system unchanged. However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions. Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well developed mathematical description of non-Abelian anyons and numerous theoretical proposals, the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. While efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasi-particles, superconducting quantum processors allow for directly manipulating the many-body wavefunction via unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons, we implement a generalized stabilizer code and unitary protocol to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of employing the anyons for quantum computation and utilize braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and - through the future inclusion of error correction to achieve topological protection - could open a path toward fault-tolerant quantum computing

Measurement of cryoelectronics heating using a local quantum dot thermometer in silicon

Silicon technology offers the enticing opportunity for monolithic integration of quantum and classical electronic circuits. However, the power consumption levels of classical electronics may compromise the local chip temperature and hence affect the fidelity of qubit operations. In the current work, a quantum-dot-based thermometer embedded in an industry-standard silicon field-effect transistor (FET) was adopted to assess the local temperature increase produced by an active FET placed in close proximity. The impact of both static and dynamic operation regimes was thoroughly investigated. When the FET was operated statically, a power budget of 45 nW at 100-nm separation was found, whereas at 216 μm, the power budget was raised to 150 μW. Negligible temperature increase for the switch frequencies tested up to 10 MHz was observed when operating dynamically. The current work introduced a method to accurately map out the available power budget at a distance from a solid-state quantum processor, and indicated the possible conditions under which cryoelectronics circuits may allow the operation of hybrid quantum–classical systems

Data

Please see the accompanying README file for details

Data from: Geographic variation in larval metabolic rate between northern and southern populations of the invasive gypsy moth

Thermal regimes can diverge considerably across the geographic range of a species, and accordingly, populations can vary in their response to changing environmental conditions. Both local adaptation and acclimatization are important mechanisms for ectotherms to maintain homeostasis as environments become thermally stressful, which organisms often experience at their geographic range limits. The spatial spread of the gypsy moth (Lymantria dispar L.) after introduction to North America provides an exemplary system for studying population variation in physiological traits given the gradient of climates encompassed by its current invasive range. This study quantifies differences in resting metabolic rate (RMR) across temperature for four populations of gypsy moth, two from the northern and two from southern regions of their introduced range in North America. Gypsy moth larvae were reared at high and low thermal regimes, then metabolic activity was monitored at four temperatures using stop-flow respirometry to test for an acclimation response. For all populations, there was a significant increase in RMR as respirometry test temperature increased. Contrary to our expectations, we did not find evidence for metabolic adaptation to colder environments based on our comparisons between northern and southern populations. We also found no evidence for an acclimation response of RMR to rearing temperature for three of the four pairwise comparisons examined. Understanding the thermal sensitivity of metabolic rate in gypsy moth, and understanding the potential for changes in physiology at range extremes, is critical for estimating continued spatial spread of this invasive species both under current and potential future climatic constraints