Causal Asymmetry in a Quantum World Thompson, Jayne; Garner, Andrew J. P.; Mahoney, John R. ...
Physical review. X,
07/2018, Volume:
8, Issue:
3
Journal Article
Peer reviewed
Open access
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predict the future differs from the memory required to retrodict the past. There is a privileged temporal ...direction for modeling a stochastic process where memory costs are minimal. Models operating in the other direction incur an unavoidable memory overhead. Here, we show that this overhead can vanish when quantum models are allowed. Quantum models forced to run in the less-natural temporal direction not only surpass their optimal classical counterparts but also any classical model running in reverse time. This holds even when the memory overhead is unbounded, resulting in quantum models with unbounded memory advantage.
Central to the success of adaptive systems is their ability to interpret signals from their environment and respond accordingly—they act as agents interacting with their surroundings. Such agents ...typically perform better when able to execute increasingly complex strategies. This comes with a cost: the more information the agent must recall from its past experiences, the more memory it will need. Here we investigate the power of agents capable of quantum information processing. We uncover the most general form a quantum agent need adopt to maximize memory compression advantages and provide a systematic means of encoding their memory states. We show these encodings can exhibit extremely favorable scaling advantages relative to memory-minimal classical agents, particularly when information must be retained about events increasingly far into the past.
RNA-guided CRISPR-Cas9 endonucleases are widely used for genome engineering, but our understanding of Cas9 specificity remains incomplete. Here, we developed a biochemical method (SITE-Seq), using ...Cas9 programmed with single-guide RNAs (sgRNAs), to identify the sequence of cut sites within genomic DNA. Cells edited with the same Cas9-sgRNA complexes are then assayed for mutations at each cut site using amplicon sequencing. We used SITE-Seq to examine Cas9 specificity with sgRNAs targeting the human genome. The number of sites identified depended on sgRNA sequence and nuclease concentration. Sites identified at lower concentrations showed a higher propensity for off-target mutations in cells. The list of off-target sites showing activity in cells was influenced by sgRNP delivery, cell type and duration of exposure to the nuclease. Collectively, our results underscore the utility of combining comprehensive biochemical identification of off-target sites with independent cell-based measurements of activity at those sites when assessing nuclease activity and specificity.
Two approaches to small-scale and quantum thermodynamics are fluctuation relations and one-shot statistical mechanics. Fluctuation relations (such as Crooks' theorem and Jarzynski's equality) relate ...nonequilibrium behaviors to equilibrium quantities such as free energy. One-shot statistical mechanics involves statements about every run of an experiment, not just about averages over trials. We investigate the relation between the two approaches. We show that both approaches feature the same notions of work and the same notions of probability distributions over possible work values. The two approaches are alternative toolkits with which to analyze these distributions. To combine the toolkits, we show how one-shot work quantities can be defined and bounded in contexts governed by Crooks' theorem. These bounds provide a new bridge from one-shot theory to experiments originally designed for testing fluctuation theorems.
Tracking the behaviour of stochastic systems is a crucial task in the statistical sciences. It has recently been shown that quantum models can faithfully simulate such processes whilst retaining less ...information about the past behaviour of the system than the optimal classical models. We extend these results to general temporal and symbolic dynamics. Our systematic protocol for quantum model construction relies only on an elementary description of the dynamics of the process. This circumvents restrictions on corresponding classical construction protocols, and allows for a broader range of processes to be modelled efficiently. We illustrate our method with an example exhibiting an apparent unbounded memory advantage of the quantum model compared to its optimal classical counterpart.
It is a fundamental prediction of quantum theory that states of physical systems are described by complex vectors or density operators on a Hilbert space. However, many experiments admit effective ...descriptions in terms of other state spaces, such as classical probability distributions or quantum systems with superselection rules. Which kind of effective statistics would allow us to experimentally falsify quantum theory as a fundamental description of nature? Here, we address this question by introducing a methodological principle that generalizes Spekkens’s notion of noncontextuality: Processes that are statistically indistinguishable in an effective theory should not require explanation by multiple distinguishable processes in a more fundamental theory. We formulate this principle in terms of linear embeddings and simulations of one probabilistic theory by another, show how this concept subsumes standard notions of contextuality, and prove a multitude of fundamental results on the exact and approximate embedding of theories (in particular, into quantum theory). We prove that only Jordan-algebraic state spaces are exactly embeddable into quantum theory, and show how results on Bell inequalities can be used for the certification of nonapproximate embeddability. From this, we propose an experimental test of quantum theory by probing single physical systems without assuming access to a tomographically complete set of procedures or calibration of the devices, arguably avoiding a significant loophole of earlier approaches.
Simulating the stochastic evolution of real quantities on a digital computer requires a trade-off between the precision to which these quantities are approximated, and the memory required to store ...them. The statistical accuracy of the simulation is thus generally limited by the internal memory available to the simulator. Here, using tools from computational mechanics, we show that quantum processors with a fixed finite memory can simulate stochastic processes of real variables to arbitrarily high precision. This demonstrates a provable, unbounded memory advantage that a quantum simulator can exhibit over its best possible classical counterpart.
KIT is the major oncogenic driver of gastrointestinal stromal tumors (GIST). Imatinib, sunitinib, and regorafenib are approved therapies; however, efficacy is often limited by the acquisition of ...polyclonal secondary resistance mutations in KIT, with those located in the activation (A) loop (exons 17/18) being particularly problematic. Here, we explore the KIT-inhibitory activity of ponatinib in preclinical models and describe initial characterization of its activity in patients with GIST.
The cellular and in vivo activities of ponatinib, imatinib, sunitinib, and regorafenib against mutant KIT were evaluated using an accelerated mutagenesis assay and a panel of engineered and GIST-derived cell lines. The ponatinib-KIT costructure was also determined. The clinical activity of ponatinib was examined in three patients with GIST previously treated with all three FDA-approved agents.
In engineered and GIST-derived cell lines, ponatinib potently inhibited KIT exon 11 primary mutants and a range of secondary mutants, including those within the A-loop. Ponatinib also induced regression in engineered and GIST-derived tumor models containing these secondary mutations. In a mutagenesis screen, 40 nmol/L ponatinib was sufficient to suppress outgrowth of all secondary mutants except V654A, which was suppressed at 80 nmol/L. This inhibitory profile could be rationalized on the basis of structural analyses. Ponatinib (30 mg daily) displayed encouraging clinical activity in two of three patients with GIST.
Ponatinib possesses potent activity against most major clinically relevant KIT mutants and has demonstrated preliminary evidence of activity in patients with refractory GIST. These data strongly support further evaluation of ponatinib in patients with GIST.
Recent clinical data indicates that the emergence of mutant drug-resistant kinase alleles may be particularly relevant for targeted kinase inhibitors. In order to explore how different classes of ...targeted therapies impact upon resistance mutations, we performed EGFR (epidermal-growth-factor receptor) resistance mutation screens with erlotinib, lapatinib and CI-1033. Distinct mutation spectra were generated with each inhibitor and were reflective of their respective mechanisms of action. Lapatinib yielded the widest variety of mutations, whereas mutational variability was lower in the erlotinib and CI-1033 screens. Lapatinib was uniquely sensitive to mutations of residues located deep within the selectivity pocket, whereas mutation of either Gly(796) or Cys(797) resulted in a dramatic loss of CI-1033 potency. The clinically observed T790M mutation was common to all inhibitors, but occurred with varying frequencies. Importantly, the presence of C797S with T790M in the same EGFR allele conferred complete resistance to erlotinib, lapatinib and CI-1033. The combination of erlotinib and CI-1033 effectively reduced the number of drug-resistant clones, suggesting a possible clinical strategy to overcome drug resistance. Interestingly, our results also indicate that co-expression of ErbB2 (v-erb-b2 erythroblastic leukaemia viral oncogene homologue 2) has an impact upon the EGFR resistance mutations obtained, suggesting that ErbB2 may play an active role in the acquisition of drug-resistant mutations.
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