Publications

The cloud-scale physics of star formation and feedback represent the main uncertainty in galaxy formation studies. Progress is hampered by the limited empirical constraints outside the restricted environment of the Local Group. In particular, the poorly-quantified time evolution of the molecular cloud lifecycle, star formation, and feedback obstructs robust predictions on the scales smaller than the disc scale height that are resolved in modern galaxy formation simulations. We present a new statistical method to derive the evolutionary timeline of molecular clouds and star-forming regions. By quantifying the excess or deficit of the gas-to-stellar flux ratio around peaks of gas or star formation tracer emission, we directly measure the relative rarity of these peaks, which allows us to derive their lifetimes. We present a step-by-step, quantitative description of the method and demonstrate its practical application. The method's accuracy is tested in nearly 300 experiments using simulated galaxy maps, showing that it is capable of constraining the molecular cloud lifetime and feedback time-scale to <0.1 dex precision. Access to the evolutionary timeline provides a variety of additional physical quantities, such as the cloud-scale star formation efficiency, the feedback outflow velocity, the mass loading factor, and the feedback energy or momentum coupling efficiencies to the ambient medium. We show that the results are robust for a wide variety of gas and star formation tracers, spatial resolutions, galaxy inclinations, and galaxy sizes. Finally, we demonstrate that our method can be applied out to high redshift (z≲4) with a feasible time investment on current large-scale observatories. This is a major shift from previous studies that constrained the physics of star formation and feedback in the immediate vicinity of the Sun.

We develop a unified model of darkgenesis and baryogenesis involving strongly interacting dark quarks, utilizing the gravitational anomaly of chiral gauge theories. In these models, both the visible and dark baryon asymmetries are generated by the gravitational anomaly induced by the presence of chiral primordial gravitational waves. We provide a concrete model of an SU(2) gauge theory with two massless quarks. In this model, the dark quarks condense and form a dark baryon charge superfluid (DBS), in which the Higgs-mode acts as cold dark matter. We elucidate the essential features of this dark matter scenario and discuss its phenomenological prospects.

Massive galaxy clusters are now found as early as 3 billion years after the Big Bang, containing stars that formed at even earlier epochs. The high-redshift progenitors of these galaxy clusters, termed 'protoclusters', are identified in cosmological simulations with the highest dark matter overdensities. While their observational signatures are less well defined compared to virialized clusters with a substantial hot intra-cluster medium (ICM), protoclusters are expected to contain extremely massive galaxies that can be observed as luminous starbursts. Recent claimed detections of protoclusters hosting such starbursts do not support the kind of rapid cluster core formation expected in simulations because these structures contain only a handful of starbursting galaxies spread throughout a broad structure, with poor evidence for eventual collapse into a protocluster. Here we report that the source SPT2349-56 consists of at least 14 gas-rich galaxies all lying at z = 4.31 based on sensitive observations of carbon monoxide and ionized carbon. We demonstrate that each of these galaxies is forming stars between 50 and 1000 times faster than our own Milky Way, and all are located within a projected region only ∼ 130 kiloparsecs in diameter. This galaxy surface density is more than 10 times the average blank field value (integrated over all redshifts) and >1000 times the average field volume density. The velocity dispersion (∼ 410 km s−1) of these galaxies and enormous gas and star formation densities suggest that this system represents a galaxy cluster core at an advanced stage of formation when the Universe was only 1.4 billion years old. A comparison with other known protoclusters at high redshifts shows that SPT2349-56 is a uniquely massive and dense system that could be building one of the most massive structures in the Universe today.

We study the abundance and clustering properties of HI at redshifts z⩽5 using TNG100, a large state-of-the-art magneto-hydrodynamic simulation of a 75 Mpc/h box size. We show that most of the HI lies within dark matter halos and quantify the average HI mass hosted by halos of mass M at redshift z. We find that only halos with circular velocities larger than ≃ 30 km/s contain HI. While the density profiles of HI exhibit a large halo-to-halo scatter, the mean profiles are universal across mass and redshift. The HI in low-mass halos is mostly located in the central galaxy, while in massive halos is concentrated in the satellites. We show that the HI and matter density probability distribution functions differ significantly. Our results point out that for small halos the HI bulk velocity goes in the same direction and has the same magnitude as the halo peculiar velocity, while in large halos differences show up. We find that halo HI velocity dispersion follows a power-law with halo mass. We find a complicated HI bias, with HI becoming non-linear already at k=0.3 h/Mpc at z≳3. Our simulation reproduces the DLAs bias value from observations. We find that the clustering of HI can be accurately reproduced by perturbative methods. We identify a new secondary bias, by showing that the clustering of halos depends not only on mass but also on HI content. We compute the amplitude of the HI shot-noise and find that it is small at all redshifts. We study the clustering of HI in redshift-space, and show that linear theory can explain the ratio between the monopoles in redshift- and real-space down to small scales at high redshift. We find that the amplitude of the Fingers-of-God effect is larger for HI than for matter. We point out that accurate 21 cm maps can be created from N-body or approximate simulations rather than full hydrodynamic simulations.

When we perform probabilistic inferences with the Gaia Mission data, we technically require a likelihood function, or a probability of the (raw-ish) data as a function of stellar (astrometric and photometric) properties. Unfortunately, we aren't (at present) given access to the Gaia data directly; we are only given a Catalog of derived astrometric properties for the stars. How do we perform probabilistic inferences in this context? The answer - implicit in many publications - is that we should look at the Gaia Catalog as containing the parameters of a likelihood function, or a probability of the Gaia data, conditioned on stellar properties, evaluated at the location of the data. Concretely, my recommendation is to assume (for, say, the parallax) that the Catalog-reported value and uncertainty are the mean and root-variance of a Gaussian function that can stand in for the true likelihood function. This is the implicit assumption in most Gaia literature to date; my only goal here is to make the assumption explicit. Certain technical choices by the Mission team slightly invalidate this assumption for DR1 (TGAS), but not seriously. Generalizing beyond Gaia, it is important to downstream users of any Catalog products that they deliver likelihood information about the fundamental data; this is a challenge for the probabilistic catalogs of the future.

When we perform probabilistic inferences with the Gaia Mission data, we technically require a likelihood function, or a probability of the (raw-ish) data as a function of stellar (astrometric and photometric) properties. Unfortunately, we aren't (at present) given access to the Gaia data directly; we are only given a Catalog of derived astrometric properties for the stars. How do we perform probabilistic inferences in this context? The answer - implicit in many publications - is that we should look at the Gaia Catalog as containing the parameters of a likelihood function, or a probability of the Gaia data, conditioned on stellar properties, evaluated at the location of the data. Concretely, my recommendation is to assume (for, say, the parallax) that the Catalog-reported value and uncertainty are the mean and root-variance of a Gaussian function that can stand in for the true likelihood function. This is the implicit assumption in most Gaia literature to date; my only goal here is to make the assumption explicit. Certain technical choices by the Mission team slightly invalidate this assumption for DR1 (TGAS), but not seriously. Generalizing beyond Gaia, it is important to downstream users of any Catalog products that they deliver likelihood information about the fundamental data; this is a challenge for the probabilistic catalogs of the future.

Cold stellar streams---produced by tidal disruptions of clusters---are long-lived, coherent dynamical features in the halo of the Milky Way. Due to their different ages and different positions in phase space, different streams tell us different things about the Galaxy. Here we employ a Cramer--Rao (CRLB) or Fisher-matrix approach to understand the quantitative information content in eleven known streams (ATLAS, GD-1, Hermus, Kwando, Orinoco, PS1A, PS1C, PS1D, PS1E, Sangarius and Triangulum). This approach depends on a generative model, which we have developed previously, and which permits calculation of derivatives of predicted stream properties with respect to Galaxy and stream parameters. We find that in simple analytic models of the Milky Way, streams on eccentric orbits contain the most information about the halo shape. For each stream, there are near-degeneracies between dark-matter-halo properties and parameters of the bulge, the disk, and the stream progenitor, but simultaneous fitting of multiple streams will constrain all parameters at the percent level. At this precision, simulated dark matter halos deviate from simple analytic parametrizations, so we add an expansion of basis functions to give the gravitational potential more freedom. As freedom increases, the information about the halo reduces overall, and it becomes more localized to the current position of the stream. In the limit of high model freedom, a stellar stream appears to measure the local acceleration at its current position; this motivates thinking about future non-parametric approaches. The CRLB formalism also permits us to assess the value of future measurements of stellar velocities, distances, and proper motions. We show that kinematic measurements of stream stars are essential for producing competitive constraints on the distribution of dark matter, which bodes well for stream studies in the age of Gaia.

We compute the electronic Green’s function of the topologically ordered Higgs phase of a SU(2) gauge theory of fluctuating antiferromagnetism on the square lattice. The results are compared with cluster extensions of dynamical mean field theory, and quantum Monte Carlo calculations, on the pseudogap phase of the strongly interacting hole-doped Hubbard model. Good agreement is found in the momentum, frequency, hopping, and doping dependencies of the spectral function and electronic self-energy. We show that lines of (approximate) zeros of the zero-frequency electronic Green’s function are signs of the underlying topological order of the gauge theory and describe how these lines of zeros appear in our theory of the Hubbard model. We also derive a modified, nonperturbative version of the Luttinger theorem that holds in the Higgs phase.

The wide-band limit is a commonly used approximation to analyze transport through nanoscale devices. In this work we investigate its applicability to the study of charge and heat transport through molecular break junctions exposed to voltage biases and temperature gradients. We find that while this approximation faithfully describes the long-time charge and heat transport, it fails to characterize the short-time behavior of the junction. In particular, we find that the charge current flowing through the device shows a discontinuity when a temperature gradient is applied, while the energy flow is discontinuous when a voltage bias is switched on and even diverges when the junction is exposed to both a temperature gradient and a voltage bias. We provide an explanation for this pathological behavior and propose two possible solutions to this problem.