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Dark matter haloes form from the collapse of matter around special positions in the initial field, those where the local matter flows converge to a point. For such a triaxial collapse to take place, the energy shear tensor -- the source of the evolution of the inertia tensor -- must be positive definite. It has been shown that this is indeed the case for the energy shear tensor of the vast majority of protohaloes. At generic positions in a Gaussian random field, the trace and traceless parts of the tensor are independent of one another. Here we show that, on the contrary, in positive definite matrices they correlate strongly, and these correlations are very similar to those exhibited by protohaloes. Moreover, while positive-definiteness ensures that an object will collapse, it does not specify when. Previous work has shown that the trace of the energy tensor -- the energy overdensity -- exhibits significant scatter in its values, but must lie above a critical `threshold' value for the halo to collapse by today. We show that suitable combinations of the eigenvalues of the traceless part are able to explain a substantial part of the scatter of the trace. These variables provide an efficient way to parameterise the initial value of the energy overdensity, allowing us to formulate an educated guess for the threshold of collapse. We validate our ansatz by measuring the distribution of several secondary properties of protohaloes, finding good agreement with our analytical predictions., Comment: 12 pages, 11 figures

Rapid progress in quantum technology has transformed quantum computing and quantum information science from theoretical possibilities into tangible engineering challenges. Breakthroughs in quantum algorithms, quantum simulations, and quantum error correction are bringing useful quantum computation closer to fruition. These remarkable achievements have been facilitated by advances in quantum characterization, verification, and validation (QCVV). QCVV methods and protocols enable scientists and engineers to scrutinize, understand, and enhance the performance of quantum information-processing devices. In this Tutorial, we review the fundamental principles underpinning QCVV, and introduce a diverse array of QCVV tools used by quantum researchers. We define and explain QCVV's core models and concepts -- quantum states, measurements, and processes -- and illustrate how these building blocks are leveraged to examine a target system or operation. We survey and introduce protocols ranging from simple qubit characterization to advanced benchmarking methods. Along the way, we provide illustrated examples and detailed descriptions of the protocols, highlight the advantages and disadvantages of each, and discuss their potential scalability to future large-scale quantum computers. This Tutorial serves as a guidebook for researchers unfamiliar with the benchmarking and characterization of quantum computers, and also as a detailed reference for experienced practitioners.

The characterization of exoplanetary atmospheres through transit spectra is becoming increasingly feasible, and technology for direct detection remains ongoing. The possibility of detecting spectral features could enable quantitative constraints on atmospheric composition or even serve as a potential biosignature, with the sensitivity of the instrument and observation time as key limiting factors. This paper discusses the possibility that future remote observations could detect the presence of radioactive elements in the atmospheres of exoplanets. Such radionuclides could arise from cosmogenic or geologic sources, as well as from industrial sources, all of which occur on Earth. The detection of radionuclides in an exoplanetary atmosphere could reveal important properties about the planet's geology or space environment, and potentially could serve as a technosignature. However, many radionuclides, including those from industrial sources, attach to aerosol or other particles that cannot be remotely characterized. Limited experimental and theoretical spectral data exist for long-lived radionuclides, but the sensitivity required to detect the spectral features of some known radionuclides would be at least several orders of magnitude greater than required to detect the spectral features of molecular oxygen. Present-day remote spectroscopic observing mission concepts at ultraviolet to mid-infrared wavelengths are not sensitive to discern the presence of radionuclides in exoplanetary atmospheres. Interplanetary fly-by or probe missions may be more likely to provide such data in the future., Comment: Accepted for publication in the Astrophysical Journal

The location of the baryon acoustic oscillation (BAO) feature in the two-point correlation function (2PCF) of matter produces a standard ruler that is useful for the measurement of the expansion history of the Universe. Inspired by the possibility of reconstructing the positions of protohalos in the initial density field with a novel method rooted in optimal transport theory, we revisit the BAO signal in the protohalo correlation function. Our work examines the performance of a template 2PCF built on a tracer bias relation that includes scale dependence -- a term that can be motivated by peaks theory or a general bias expansion. Working in protohalos, halos, and the linear combination of the protohalo and matter fields that is motivated by the continuity equation, we demonstrate that this model accurately captures the shape of the BAO feature and improves the precision of the BAO scale measurement relative to a model that does not include scale-dependent bias by 47% in protohalos, 15% in halos, and 14% in the linear combination of the protohalo and matter fields. Allowing for scale dependence does not appear to introduce any shift in the BAO feature. The precision of the BAO distance scale estimate is highest with the linear combination of the protohalo and matter fields, which offers a factor of 3.5 improvement over Eulerian-space measurements and a factor of 4-8 improvement over the estimate made with protohalos alone., Comment: 13 pages, 7 figures, submitted to Physical Review D

The Baryon Acoustic Oscillation (BAO) feature in the two-point correlation function (TPCF) of discrete tracers such as galaxies is an accurate standard ruler. The covariance matrix of the TPCF plays an important role in determining how the precision of this ruler depends on the number density and clustering strength of the tracers, as well as the survey volume. An eigen-decomposition of this matrix provides an objective way to separate the contributions of cosmic variance from those of shot-noise to the statistical uncertainties. For the signal-to-noise levels that are expected in ongoing and next-generation surveys, the cosmic variance eigen-modes dominate. These modes are smooth functions of scale, meaning that: they are insensitive to the modest changes in binning that are allowed if one wishes to resolve the BAO feature in the TPCF; they provide a good description of the correlated residuals which result from fitting smooth functional forms to the measured TPCF; they motivate a simple but accurate approximation for the uncertainty on the Linear Point (LP) estimate of the BAO distance scale. This approximation allows one to quantify the precision of the BAO distance scale estimate without having to generate a large ensemble of mock catalogs and explains why: the uncertainty on the LP does not depend on the functional form fitted to the TPCF or the binning used; the LP is more constraining than the peak or dip scales in the TPCF; the evolved TPCF is less constraining than the initial one, so that reconstruction schemes can yield significant gains in precision., Comment: 10 pages, 8 figures, submitted to Physical Review D

Randomized compiling (RC) is an efficient method for tailoring arbitrary Markovian errors into stochastic Pauli channels. However, the standard procedure for implementing the protocol in software comes with a large experimental overhead -- namely, it scales linearly in the number of desired randomizations, each of which must be generated and measured independently. In this work, we introduce a hardware-efficient algorithm for performing RC on a cycle-by-cycle basis on the lowest level of our FPGA-based control hardware during the execution of a circuit. Importantly, this algorithm performs a different randomization per shot with zero runtime overhead beyond measuring a circuit without RC. We implement our algorithm using the QubiC control hardware, where we demonstrate significant reduction in the overall runtime of circuits implemented with RC, as well as a significantly lower variance in measured observables.

Baryon Acoustic Oscillations (BAOs) are crucial in cosmological analysis, providing a standard ruler, as well as constraints on dark energy. In General Relativity models, the BAO Linear Point - the midpoint between the dip and the peak in the correlation function - has been shown to be rather robust to evolution and redshift space distortions. We show that this remains true even when the gravity model is not General Relativity, at least for $f(R)$ and DGP gravity models which have the same expansion history as the standard $\Lambda$CDM. For the Linear Point to be able to distinguish between modified gravity (MG) and $\Lambda$CDM, survey volumes of order tens of cubic Gpc are required., Comment: 9 pages, 5 figures, submitted to Physical Review D, v2

As it collapses to form a halo, the shape of a protohalo patch is deformed by the initial shear field. This deformation is often modeled using the "deformation" tensor, constructed from second derivatives of the gravitational potential, whose trace gives the initial overdensity. However, especially for lower mass protohalos, this matrix is not always positive definite: one of its eigenvalues has a different sign from the others. We show that the evolution of a patch is better described by the "energy shear" tensor, which is positive definite and plays a direct role in the evolution. This positive-definiteness simplifies models of halo abundances, assembly and of the cosmic web., Comment: 9 pages, 10 figures

This paper highlights methods from geostatistics that are relevant to the interpretation, intercomparison, and synthesis of atmospheric model data, with a specific application to exoplanet atmospheric modeling. Climate models are increasingly used to study theoretical and observational properties of exoplanets, which include a hierarchy of models ranging from fast and idealized models to those that are slower but more comprehensive. Exploring large parameter spaces with computationally-expensive models can be accomplished with sparse sampling techniques, but analyzing such sparse samples can pose challenges for conventional interpolation functions. Ordinary kriging is a statistical method for describing the spatial distribution of a data set in terms of the variogram function, which can be used to interpolate sparse samples across any number of dimensions. Variograms themselves may also be useful diagnostic tools for describing the spatial distribution of model data in exoplanet atmospheric model intercomparison projects. Universal kriging is another method that can synthesize data calculated by models of different complexity, which can be used to combine sparse samples of data from slow models with larger samples of data from fast models. Ordinary and universal kriging can also provide a way to synthesize model predictions with sparse samples of exoplanet observations and may have other applications in exoplanet science., Comment: Accepted for publication in the Planetary Science Journal

Atmospheric pollutants such as CFCs and NO$_{2}$ have been proposed as potential remotely detectable atmospheric technosignature gases. Here we investigate the potential for artificial greenhouse gases including CF$_{4}$, C$_{2}$F$_{6}$, C$_{3}$F$_{8}$, SF$_{6}$, and NF$_{3}$ to generate detectable atmospheric signatures. In contrast to passive incidental byproducts of industrial processes, artificial greenhouse gases would represent an intentional effort to change the climate of a planet with long-lived, low toxicity gases and would possess low false positive potential. An extraterrestrial civilization may be motivated to undertake such an effort to arrest a predicted snowball state on their home world or to terraform an otherwise uninhabitable terrestrial planet within their system. Because artificial greenhouse gases strongly absorb in the thermal mid-infrared window of temperate atmospheres, a terraformed planet will logically possess strong absorption features from these gases at mid-IR wavelengths ($\sim$8-12 $\mu$m), possibly accompanied by diagnostic features in the near-IR. As a proof of concept, we calculate the needed observation time to detect 1 [10](100) ppm of C$_{2}$F$_{6}$/C$_{3}$F$_{8}$/SF$_{6}$ on TRAPPIST-1f with JWST MIRI/LRS and NIRSpec. We find that a combination of 1[10](100) ppm each of C$_{2}$F$_{6}$, C$_{3}$F$_{8}$, and SF$_{6}$ can be detected with an S/N $\geq$ 5 in as few as 25[10](5) transits with MIRI/LRS. We further explore mid-infrared direct-imaging scenarios with the LIFE mission concept and find these gases are more detectable than standard biosignatures at these concentrations. Consequently, artificial greenhouse gases can be readily detected (or excluded) during normal planetary characterization observations with no additional overhead., Comment: 18 pages, 8 figures, 6 tables; ApJ, 969, 20

Patients diagnosed with metastatic breast cancer (mBC) typically undergo several radiographic assessments during their treatment. mBC often involves multiple metastatic lesions in different organs, it is imperative to accurately track and assess these lesions to gain a comprehensive understanding of the disease's response to treatment. Computerized analysis methods that rely on lesion-level tracking have often used manual matching of corresponding lesions, a time-consuming process that is prone to errors. This paper introduces an automated lesion correspondence algorithm designed to precisely track both targets' lesions and non-targets' lesions in longitudinal data. Here we demonstrate the applicability of our algorithm on the anonymized data from two Phase III trials. The dataset contains imaging data of patients for different follow-up timepoints and the radiologist annotations for the patients enrolled in the trials. Target and non-target lesions are annotated by either one or two groups of radiologists. To facilitate accurate tracking, we have developed a registration-assisted lesion correspondence algorithm. The algorithm employs a sequential two-step pipeline: (a) Firstly, an adaptive Hungarian algorithm is used to establish correspondence among lesions within a single volumetric image series which have been annotated by multiple radiologists at a specific timepoint. (b) Secondly, after establishing correspondence and assigning unique names to the lesions, three-dimensional rigid registration is applied to various image series at the same timepoint. Registration is followed by ongoing lesion correspondence based on the adaptive Hungarian algorithm and updating lesion names for accurate tracking. Validation of our automated lesion correspondence algorithm is performed through triaxial plots based on axial, sagittal, and coronal views, confirming its efficacy in matching lesions.

Quantum circuits utilizing real time feedback techniques (such as active reset and mid-circuit measurement) are a powerful tool for NISQ-era quantum computing. Such techniques are crucial for implementing error correction protocols, and can reduce the resource requirements of certain quantum algorithms. Realizing these capabilities requires flexible, low-latency classical control. We have developed a custom FPGA-based processor architecture for QubiC, an open source platform for superconducting qubit control. Our architecture is distributed in nature, and consists of a bank of lightweight cores, each configured to control a small (1-3) number of signal generator channels. Each core is capable of executing parameterized control and readout pulses, as well as performing arbitrary control flow based on mid-circuit measurement results. We have also developed a modular compiler stack and domain-specific intermediate representation for programming the processor. Our representation allows users to specify circuits using both gate and pulse-level abstractions, and includes high-level control flow constructs (e.g. if-else blocks and loops). The compiler stack is designed to integrate with quantum software tools and programming languages, such as TrueQ, pyGSTi, and OpenQASM3. In this work, we will detail the design of both the processor and compiler stack, and demonstrate its capabilities with a quantum state teleportation experiment using transmon qubits at the LBNL Advanced Quantum Testbed., Comment: 10 pages, 13 figures

A leading application of quantum computers is the efficient simulation of large unitary quantum systems. Extending this advantage to the study of open Cavity Quantum Electrodynamics (CQED) systems could enable the use of quantum computers in the exploration and design of many-body quantum optical devices. Such devices have promising applications in optical quantum communication, simulation, and computing. In this work, we present an early exploration of the potential for quantum computers to efficiently investigate open CQED physics. Our simulations make use of a recent quantum algorithm that maps the dynamics of a singly excited open Tavis-Cummings model containing $N$ atoms coupled to a lossy cavity. We report the results of executing this algorithm on two noisy intermediate-scale quantum computers, a superconducting processor and a trapped ion processor, to simulate the population dynamics of an open CQED system featuring $N = 3$ atoms. By applying technology-specific transpilation and error mitigation techniques, we minimize the impact of gate errors, noise, and decoherence in each hardware platform, obtaining results which agree closely with the exact solution of the system. These results provide confidence that future simulation algorithms, combined with emerging large-scale quantum processors, can be a powerful tool for studying cavity quantum electrodynamics., Comment: 10 pages, 15 figures

We demonstrate the effectiveness of one of the many multi-tracer analyses enabled by Optimal Transport (OT) reconstruction. Leveraging a semi-discrete OT algorithm, we determine the displacements between initial and observed positions of biased tracers and the remaining matter field. With only redshift-space distorted final positions of biased tracers and a simple premise for the remaining mass distribution as input, OT solves the displacement field. This extracted field, assuming asymptotically uniform density and a gradient flow displacement, enables reconstruction of the initial overdensity fluctuation field. We show that the divergence of the OT displacement field is a good proxy of the linear density field, even though the method never assumes the linear theory growth. Additionally, this divergence field can be combined with the reconstructed protohalos to provide a higher signal-to-noise measurement of the BAO standard ruler than was possible with either measurement individually., Comment: 12 pages, 10 figures

The James Webb Space Telescope (JWST) has provided the first opportunity to study the atmospheres of terrestrial exoplanets and estimate their surface conditions. Earth-sized planets around Sun-like stars are currently inaccessible with JWST however, and will have to be observed using the next generation of telescopes with direct imaging capabilities. Detecting active volcanism on an Earth-like planet would be particularly valuable as it would provide insight into its interior, and provide context for the commonality of the interior states of Earth and Venus. In this work we used a climate model to simulate four exoEarths over eight years with ongoing large igneous province eruptions with outputs ranging from 1.8-60 Gt of sulfur dioxide. The atmospheric data from the simulations were used to model direct imaging observations between 0.2-2.0 $\mu$m, producing reflectance spectra for every month of each exoEarth simulation. We calculated the amount of observation time required to detect each of the major absorption features in the spectra, and identified the most prominent effects that volcanism had on the reflectance spectra. These effects include changes in the size of the O$_3$, O$_2$, and H$_2$O absorption features, and changes in the slope of the spectrum. Of these changes, we conclude that the most detectable and least ambiguous evidence of volcanism are changes in both O$_3$ absorption and the slope of the spectrum., Comment: 13 pages, 5 figures, 4 tables, Accepted for publication in AJ (September 26, 2023)

Researchers manipulate and measure quantum processing units via the classical electronics control system. We developed an open-source FPGA-based quantum bit control system called QubiC for superconducting qubits. After a few years of qubit calibration and testing experience on QubiC 1.0, we recognized the need for mid-circuit measurements and feed-forward capabilities to implement advanced quantum algorithms effectively. Moreover, following the development of RFSoC technology, we upgraded the system to QubiC 2.0 on an Xilinx ZCU216 evaluation board and developed all these enriched features. The system uses portable FPGA gateware with a simplified processor to handle commands on-the-fly. For design simplicity and straightforward scaling, we adopted a multi-core distributed architecture, assigning one processor core per qubit. The actual pulses combine the unique pulse envelope and carrier information specified in a command. Each pulse envelope is pre-stored on FPGA's block RAMs, ensuring the speed and reusability during the whole circuit. The pulse parameters including amplitude, phase, and frequency can be updated from pulse to pulse. The software stack is developed in Python, running on both the FPGA's ARM core and host computer via XML-RPC. The quantum circuit can be described in a high-level language, which supports programming at both pulse-level and native-gate level, and includes high-level control flow constructs. The QubiC software stack compiles these quantum programs into binary commands that can be loaded into the FPGA. With Qubic 2.0, we successfully achieved multi-FPGA synchronization in bench tests and demonstrated simplified feed-forward experiments on conditional circuits. The enhanced QubiC system represents a significant step forward in quantum computing, providing researchers with powerful tools to explore and implement advanced quantum algorithms and applications.

We review the non-linear statistics of Primordial Black Holes that form from the collapse of over-densities in a radiation dominated Universe. We focus on the scenario in which large over-densities are generated by rare and Gaussian curvature perturbations during inflation. As new results, we show that the mass spectrum follows a power law determined by the critical exponent of the self-similar collapse up to a power spectrum dependent cut-off, and that the abundance related to very narrow power spectra is exponentially suppressed. Related to this, we discuss and explicitly show that the Press-Schechter approximation, as well as the statistics of mean profiles, lead to wrong conclusions for the abundance and mass spectrum. Finally, we clarify that the transfer function in the statistics of initial conditions for primordial black holes formation (the abundance) does not play a significant role., Comment: v2 typos corrected and clarifications added. Results unchanged. Version accepted for publication as a review in the journal Universe, special issue on PBHs. 18 pages; 7 figures

Recent research has emphasized the benefits of accurately reconstructing the initial Lagrangian positions of biased tracers from their positions at a later time, to gain cosmological information. A weighted semi-discrete optimal transport algorithm can achieve the required accuracy, provided the late-time positions are known, with minimal information about the background cosmology. The algorithm's performance relies on knowing the masses of the biased tracers, and depends on how one models the distribution of the remaining mass that is not associated with these tracers. We demonstrate that simple models of the remaining mass result in accurate retrieval of the initial Lagrangian positions, which we quantify using pair statistics and the void probability function. This is true even if the input positions are affected by redshift-space distortions. The most sophisticated models assume that the masses of the tracers, and the amount and clustering of the missing mass are known; we show that the method is robust to realistic errors in the masses of the tracers and remains so as the model for the missing mass becomes increasingly crude., Comment: 15 pages, 18 figures