Control electronics for superconducting quantum processors have strict requirements for accurate command of the sensitive quantum states of their qubits.Hinging on the purity of ultra-phase-stable oscillators to upconvert very-low-noise baseband pulses, conventional control systems can become prohibitively complex and expensive when scaling to larger quantum devices, especially as high sampling rates become desirable for fine-grained pulse shaping.Few-gigahertz radio-frequency (RF) digital-to-analog converters (DACs) present a more economical avenue for high-fidelity control while simultaneously providing greater command over the spectrum of the synthesized signal.Modern RF DACs with extra-wide bandwidths are able to directly synthesize tones above their sampling rates, thereby keeping the system clock rate at a level compatible with modern digital logic systems while still being able to generate high-frequency pulses with arbitrary profiles.We have incorporated custom superconducting qubit control logic into off-the-shelf hardware capable of low-noise pulse synthesis up to 7.5 GHz using an RF DAC clocked at 5 GHz.Our approach enables highly linear and stable microwave synthesis over a wide bandwidth, giving rise to high-resolution control and a reduced number of required signal sources per qubit.We characterize the performance of the hardware using a five-transmon superconducting device and demonstrate consistently reduced two-qubit gate error (as low as 1.8%), which we show results from superior control chain linearity compared to traditional configurations.The exceptional flexibility and stability further establish a foundation for scalable quantum control beyond intermediate-scale devices.

Let's boot up a quantum computer. Far from being a simple push of a button, initializing a prototype quantum computer requires the precise tuning and calibration of many different parameters. Rather than switching transistors on and off, the controller of a quantum processor emits combinations of analog waveforms, each with a characteristic shape, frequency, and duration. These waveforms are used to either manipulate or read out the states of quantum bits (qubits), the basic units of quantum information in the processor. The analog nature of the system inherits many of the complexities of analog computing, including device parameter drift and offsets, system component tolerances and variabilities, and other well-known analog-circuit intricacies. Further, de livering these signals to the target qubits necessitates coordination between multiple low-noise and low-jitter instruments. In spite of these challenges, the quantum computing community has made tremendous progress toward useful quantum machines. We hope to provide an instructive introduction to the control, signal generation, and distribution principles currently used in small quantum systems that operate in the microwave frequency regime.

Although qubit coherence times and gate fidelities are continuously improving, logical encoding is essential to achieve fault tolerance in quantum computing. In most encoding schemes, correcting or tracking errors throughout the computation is necessary to implement a universal gate set without adding significant delays in the processor. Here we realize a classical control architecture for the fast extraction of errors based on multiple cycles of stabilizer measurements and subsequent correction. We demonstrate its application on a minimal bit-flip code with five transmon qubits, showing that real-time decoding and correction based on multiple stabilizers is superior in both speed and fidelity to repeated correction based on individual cycles. Furthermore, the encoded qubit can be rapidly measured, thus enabling conditional operations that rely on feed-forward, such as logical gates. This co-processing of classical and quantum information will be crucial in running a logical circuit at its full speed to outpace error accumulation.

We describe the hardware, gateware, and software developed at Raytheon BBN Technologies for dynamic quantum information processing experiments on superconducting qubits. In dynamic experiments, real-time qubit state information is fed back or fed forward within a fraction of the qubits' coherence time to dynamically change the implemented sequence. The hardware presented here covers both control and readout of superconducting qubits. For readout, we created a custom signal processing gateware and software stack on commercial hardware to convert pulses in a heterodyne receiver into qubit state assignments with minimal latency, alongside data taking capability. For control, we developed custom hardware with gateware and software for pulse sequencing and steering information distribution that is capable of arbitrary control flow in a fraction of superconducting qubit coherence times. Both readout and control platforms make extensive use of field programmable gate arrays to enable tailored qubit control systems in a reconfigurable fabric suitable for iterative development.

Many sensor network studies assume that the energy cost for sensing is negligible compared with the cost of communications or computing. Opportunities exist to deploy sensor networks utilizing active sensors with a high energy cost such as radar. For a node utilizing radar as its primary sensor, the actual sensing procedure is the main power consumer. In the worst case almost 50% of the power is consumed by the sensing procedure, while only 3% is used for communication, the remainder is consumed by the computing platform. In this paper we examine a wireless sensor network composed of short range radars used to monitor rainfall. These short-range radar nodes are designed to be deployed as part of an ad-hoc network and to limit their reliance on existing infrastructure. We refer to these networks as "off-the-grid" (OTG) weather radar networks. Independence of the wired infrastructure (power or communications) allows OTG networks to be deployed in specific regions where sensing needs are greatest, such as mountain valleys prone to flash-flooding, geographic regions where the infrastructure is susceptible to failure, and underdeveloped regions lacking urban infrastructure. We present a simulation based investigation of such an OTG sensor network. We focus on power management and energy harvesting for the network. We use these simulations to demonstrate how geographic location, battery capacity, optimization of power consumption, and node density have an impact on the performance and operational lifetime of such a sensor network. In addition to these simulations, we present the design and implementation of an OTG prototype sensor node. Experiences and data gained from the operation of this node are used as input parameters for the simulations.

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's longrange weather radars. One class of potential distributed radar network designs includes Off-the-Grid (OTG) weather radar networks. These are short-range radar nodes designed to be deployed as part of an ad-hoc network and to limit their reliance on existing infrastructure. Independence of the wired infrastructure (power or communications) would allow OTG networks to be deployed in specific regions where sensing needs are greatest, such as mountain valleys prone to flash-flooding, geographic regions where the infrastructure is susceptible to failure, and underdeveloped regions lacking urban infrastructure. This paper will present an OTG network testbed being deployed in Western Massachusetts to support experimentation with OTG nodes. This testbed will focus on the energy performance of the OTG network and the virtualization of the radar sensor.

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's long-range weather radars. One class of potential distributed radar network designs includes Off-the-Grid (OTG) weather radar networks. These are short-range radar nodes designed to be deployed as part of an ad-hoc network and to limit their reliance on existing infrastructure. Independence of the wired infrastructure (power or communications) would allow OTG networks to be deployed in specific regions where sensing needs are greatest, such as mountain valleys prone to flash-flooding, geographic regions where the infrastructure is susceptible to failure, and underdeveloped regions lacking urban infrastructure. This paper will present a system model and simulation framework for the design of OTG networks. The model estimates the energy requirements of the three major system functions, sensing, communicating and computing, as well as power generated from the solar panel. The simulation will be used to develop an energy cost function to be used in control decisions.

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's long-range weather radars. Future distributed radar networks will involve thousands of small radars, and the design of these systems will be conducted in a trade-space that balances requirements among radar sensing, communications, networking, and distributed computation functions while addressing infras- tructure constraints (such as size, weight, space, and prime power requirements) to achieve cost-effective designs. This paper presents preliminary work on the development of "Off-The- Grid" (OTG) weather radar networks. These are envisioned as self-contained networks of small remote-sensing / commu- nication / computation nodes, each occupying a volume of 1.5 m 3 and capable of operating independent of the wired power and communication infrastructure. Operating a radar network independently of the electrical grid will require understanding the energy requirements for sensing. This paper will present the current progress in the development of the energy balancing algorithms necessary for OTG operation. Included in this paper will be an energy consumption model for OTG network analysis. The energy model includes the energy cost associated with the three main functions (sensing, computing, communicating) of each radar node in an OTG network. The energy consumption model is a fundamental component of an OTG network emulator that will allow for the testing of the energy balancing algorithms. This paper will present the OTG node energy model that has been developed and that will be used to analyze the developing energy balancing algorithms.

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's long-range weather radars. Future distributed radar networks will involve thousands of small radars, and the design of these systems will be conducted in a trade-space that balances requirements among radar sensing, communications, networking, and distributed computation functions while addressing infrastructure constraints (such as size, weight, space, and prime power requirements) to achieve cost-effective designs. This paper examines the trade-space and operating concepts behind "Off-The-Grid" (OTG) weather radar networks. These are envisioned as self-contained networks of small remote-sensing/communication/computation nodes, each occupying a volume of 1.5 m(3) and capable of operating independent of the wired power/communication infrastructure.

flection by targets in the atmosphere. The distributed na- ture of meteorological targets causes the received power to fluctuate as targets move, a phenomenon referred to as fading. Fading may be reduced by averaging successive pulses resulting in a reduction in the standard deviation of the target's reflectivity. By combining fading with the radar equation one is able to estimate radar sensitivity. 2.1. Fading