Osmolality counts dissolved particles per mass of solvent; it characterizes a chemical solution, rather than the total amount of water in an organism.

Blood pressure is force per area exerted by blood on its surroundings, measured relative to a specified reference. Arterial pressure varies during the cardiac cycle, giving systolic and diastolic values. Pressure, flow and vascular resistance are related but are different physical quantities.

For an orthogonal projection, $P^k=P$ for $k\ge 1$. Summing the exponential series proves the displayed identity. At $\theta =\pi$, the operator is $I-2P$, which changes the sign on the range and fixes its orthogonal complement. In Grover search algorithm, the marked-state reflection and the uniform-state reflection compose to the search iterate up to an irrelevant global phase.

A proposed modern teaching measurement puts a pipette-measured portion of an iron ${\mathrm{Fe}}^{2+}$ chemical solution in a conical flask, acidifies with excess dilute sulfuric acid, and adds standardized potassium permanganate from a clamped burette while swirling. The documented endpoint principle is that added purple permanganate is consumed until the first small excess leaves a pale purple colour; no separate colour indicator is required. Insufficient acidity can produce brown manganese dioxide, invalidating the assumed five-electron half-reaction.^[ref]

Record initial and final burette readings; their difference is the delivered volume $V$. The following controls are proposed additions to test the inference. Run a reagent blank with the same water, sulfuric acid and endpoint criterion but no sample, obtaining $V_b$. Use a separately established potassium permanganate concentration $c$, clear the burette tip of air, and repeat sample portions. A known added amount of substance of ${\mathrm{Fe}}^{2+}$ should increase consumption by one fifth of that amount. A blank estimates reagent demand and the small endpoint excess; it cannot remove an interfering sample reactant.

Assuming complete, selective reaction according to the acidic permanganate-iron balance, the corrected inference isWith $c$ in $\mathrm{mol}{\mathrm{L}}^{-1}$, use $V$ and $V_b$ in litres. As an original stipulated calculation, not an experimental result, take $c=0.02000\mathrm{mol}{\mathrm{L}}^{-1}$, $V=12.60\mathrm{mL}$ and $V_b=0.10\mathrm{mL}$. Then the permanganate consumption is $0.2500\mathrm{mmol}$ and the inferred ${\mathrm{Fe}}^{2+}$ amount is $1.250\mathrm{mmol}$. In a $25.00\mathrm{mL}$ sample portion this corresponds to $0.05000\mathrm{mol}{\mathrm{L}}^{-1}$.

In this example the corrected volume is $12.50\mathrm{mL}=0.01250\mathrm{L}$. The acidic permanganate-iron balance gives $z_A=1$ for ${\mathrm{Fe}}^{2+}$ and $z_T=5$ for permanganate. Thus $0.2500\mathrm{mmol}$ of permanganate accepts $1.250\mathrm{mmol}$ of formal electrons, exactly what $1.250\mathrm{mmol}$ of ${\mathrm{Fe}}^{2+}$ supplies. The amount of substance ratio is five to one, despite equality of the exchanged electron amounts.

The denominator is the original $25.00\mathrm{mL}$ aliquot, not its final volume after adding sulfuric acid, water and titrant. Such dilution changes concentrations in the flask without changing the initial sampled amount of substance of ${\mathrm{Fe}}^{2+}$. Omitting the $0.10\mathrm{mL}$ titration blank would instead give $1.260\mathrm{mmol}$ and $0.05040\mathrm{mol}{\mathrm{L}}^{-1}$, an overestimate of $0.80\%$ relative to the corrected constructed value. The displayed digits express the stipulated calculation, rather than establish its measurement uncertainty.

The endpoint detects residual permanganate, not the iron identity directly. Other sample reactants that consume permanganate raise the apparent ${\mathrm{Fe}}^{2+}$ amount; prior oxidation of sample ${\mathrm{Fe}}^{2+}$ to ${\mathrm{Fe}}^{3+}$ lowers it. A recovery check probes response to the added iron but does not prove absence of every interference. The readout determines the reacting ${\mathrm{Fe}}^{2+}$ inventory under the stated conditions, rather than total iron in an arbitrary mixture. No measured titres are asserted here.

Approximating decoupling by a single time and retaining only a photon monopole and Doppler dipole omits the finite cosmological visibility function width, diffusion or Silk damping, quadrupole anisotropy and polarization generated as tight coupling fails. The photon-baryon acoustic oscillator also make the emission density and velocity strongly scale dependent. They can be included in the initial monopole and dipole, so their existence alone does not invalidate the subsequent collisionless line-of-sight solution for free-streaming photons. Smaller angles correspond to larger angular multipole $\ell$.

The extended real numbers adjoin $-\infty$ and $+\infty$ to $\mathbb{R}$. They preserve the total order but leave some arithmetic expressions, such as $+\infty -\infty$, undefined.

A number line represents real numbers as points on a line, with zero as origin and a chosen positive direction and unit scale. Addition becomes a shift and multiplication becomes a rescaling about zero.

For nondecreasing real $\beta$, convergence of the displayed improper integral forces $\beta (x)/x\to 1$. For $\lambda >1$, the integral over $[X,\lambda X]$ tends to zero and is at least $(1-{\lambda }^{-1})\beta (X)/X-\log \lambda$. The integral over $[X/\lambda ,X]$ tends to zero and is at most $(\lambda -1)\beta (X)/X-\log \lambda$. These bound the upper and lower limits by $\log \lambda /(1-{\lambda }^{-1})$ and $\log \lambda /(\lambda -1)$. Letting $\lambda \downarrow 1$ squeezes both to one. The limit of the improper integral must be finite.

Asymptotic analysis describes what remains dominant as an argument approaches a specified limit. It compares functions or sequences by scale: how much of a complicated expression can be replaced by a simpler one, and how large is the omitted part? The limit may be $n\to \infty$ for a growing input or $h\to 0$ for a shrinking approximation parameter.

For example, $n^2+10^{5}n$ is eventually dominated by its quadratic term, since division by $n^2$ gives $1+10^5/n\to 1$. But at $n=100$, the linear term contributes $10^7$, compared with only $10^4$ from the quadratic term. A statement about the limiting scale and a good approximation at a particular input are different claims.

Three useful comparisons keep their strengths distinct. Big O notation supplies an eventual upper bound up to a constant multiplier; big theta notation supplies both an upper bound and a lower bound up to constants; asymptotic equivalence makes the ratio tend to one. Little o notation says that a term becomes negligible relative to a specified scale. These distinctions make approximations checkable instead of merely calling one expression small.

The same language connects time complexity with Taylor remainders. In an operation-count model, one asks how a cost scales with input size. In a Taylor expansion, one asks how the approximation error scales with the increment. Neither use requires interpreting the unspecified constant as one. The asymptotic comparison of exponential functions gives another example: dividing by the largest contributing exponential reveals the terms that disappear.

For a subset $A$ of a partially ordered set, its infimum is its greatest lower bound and its supremum is its least upper bound. An upper bound only has to lie above every member; the supremum is the smallest such bound. A lower bound lies below every member; the infimum is the largest such bound. These definitions identify the exact edges of a set even when neither edge belongs to it.

For example, $(0,1)$ and $[0,1]$ both have infimum zero and supremum one. Only $[0,1]$ has a minimum and a maximum: those must be actual members of the set. The set $C=\{1/n:n\in {\mathbb{N}}_{>0}\}$ has infimum zero without a minimum, but its supremum one is also its maximum. Such examples distinguish a bound from an attained extremal value. ^[ref].

For a nonempty subset of the real numbers, completeness of the real numbers guarantees a real supremum when it is bounded above, and a real infimum when it is bounded below. The bound and the ambient partially ordered set both matter: $\{q\in \mathbb{Q}:q\ge 0,q^2<2\}$ has supremum $\sqrt{2}$ in the real numbers, but no supremum in the rational numbers. The detailed explanation belongs to completeness of the real numbers.

Why are unattained bounds useful? They specify a precise limiting target. In mathematical optimization, $f(x)=x$ on $(0,1)$ has infimum zero but no global minimizer. The inputs $x_n=1/n$ for $n\ge 2$ give a minimizing sequence: their objective values approach zero without ever reaching it. Bounds therefore describe what approximation can achieve even when no feasible input is best. The approximation property of an infimum and approximation property of a supremum express this idea quantitatively.

Hardy's inequality bounds averages or weighted functions by their original size or derivatives. For $p>1$ and $f\ge 0$, its integral form is ${\int }_0^{\infty }(x^{-1}{\int }_0^{x}f(t)dt{)}^{p}dx\le (p/(p-1){)}^p{\int }_0^{\infty }f(x{)}^{p}dx$. Spatial weighted forms include the Hardy inequality in Euclidean space.

A rate law specifies how a reaction rate depends on concentrations under stated conditions. A common form iswhere $k$ is a rate constant and the exponents are partial orders of reaction. Determine them experimentally, or derive them from a justified reaction mechanism. Do not infer $\alpha =a$ and $\beta =b$ from the net chemical equation: its coefficients describe consumption ratios, whereas the exponents describe sensitivity to concentration. See IUPAC Gold Book: rate law and Flowers et al., Chemistry 2e, §12.3: rate laws.

A rate law becomes a prediction of time evolution when combined with stoichiometry in a rate equation, for example $d[\mathrm{A}]/dt=-av$. Agreement with a measured rate law is useful evidence for a reaction mechanism, but several routes can give the same dependence.

The disappearance rate of a reactant A is its positive net loss of concentration per unit time, $v_{\mathrm{A}}=-d[\mathrm{A}]/dt$. For the fixed-volume, single-chemical reaction setting of reaction rate, consuming $a$ units of A per conversion gives $v_{\mathrm{A}}=av$. The factor belongs to the stoichiometry; stating it is essential when quoting a rate constant. A negative net disappearance rate means that A is accumulating.

An elementary reaction is one microscopic step in a reaction mechanism, with no intervening reaction intermediate needed within that step. Its molecularity counts the participating reacting entities. In an ideal dilute, uniformly mixed model, the law of mass action gives the directional reaction rate from the step's reactant concentrations: $\mathrm{A}⟶\mathrm{P}$ has $r=k[\mathrm{A}]$, while $\mathrm{A}+\mathrm{B}⟶\mathrm{P}$ has $r=k[\mathrm{A}][\mathrm{B}]$. Applying those powers to a net chemical equation requires separate evidence that it is elementary.^[ref]

For a reversible step $\mathrm{A}+\mathrm{B}\rightleftharpoons \mathrm{I}$, apply that rule separately: $r_f=k_f[\mathrm{A}][\mathrm{B}]$ and $r_r=k_r[\mathrm{I}]$, giving net production of I as $r_f-r_r$. Their difference can vanish at chemical equilibrium while both directional reaction rates remain nonzero. For $2\mathrm{A}⟶\mathrm{P}$, the elementary normalized reaction rate is $r=k[\mathrm{A}{]}^2$, whereas A's disappearance rate is $2r$; see second-order reaction for the complete factor-of-two example.

Calling a step slow does not remove the need for its actual reactant concentrations. If a reaction intermediate enters its rate law, determine that concentration from the other rate equations or a justified approximation. In the consecutive first-order reaction mechanism, an intermediate maximum is only one instant at which its production and consumption match. Replacing its entire evolution by that one balance would lose the initial buildup and delayed reaction product formation. A successful overall first-order reaction fit likewise does not establish an elementary event: both worked reaction mechanisms above provide ways for microscopic detail to remain hidden in one reactant trace.

A reaction coordinate parametrizes changes in molecular configuration along a chemical reaction path. It can involve a bond length, a bond angle, or a combination of geometric changes. It is not elapsed time and is not the bulk extent of reaction: one describes configurations, while the other accounts for how much material has converted. The precise choice matters when interpreting an energy profile. See the IUPAC Gold Book: reaction coordinate.

A reaction intermediate is formed during a reaction mechanism and consumed in a subsequent step, cancelling from the net chemical equation. It can accumulate, as I does in the consecutive first-order reaction mechanism. A reaction intermediate can also connect transformations in energy coupling. Unlike a catalyst, it need not be present before conversion begins.^[ref]

A reaction intermediate is distinct from a transition state: the former can persist between steps, whereas the latter describes passage through a barrier. The existing potential energy surface and energy profile provide the configuration-space picture; the time-dependent concentration of an intermediate instead measures an ensemble of reacting entities. Low concentration or short lifetime can make detection difficult, so failure to detect a proposed reaction intermediate is not by itself proof of absence. Conversely, detecting a chemical species does not establish that it carries the proposed route to the final reaction products; it could belong to a competing route.

The double integrator is the linear time-invariant system in which one control input is integrated into velocity, and velocity into position. It is a mathematical idealization of one-dimensional motion under commanded acceleration; for a constant mass $m$ and net force $F$, Newton's second law gives $u=F/m$. The worked examples here use normalized dimensionless quantities and assume no control disturbances, rather than describing a laboratory record. ^[ref]

Writing $x=(p,v{)}^T$ givesThe Kalman rank criterion therefore gives controllability in every $T>0$ for unrestricted real control inputs. More concretely, choose constants $a,b$ on the first and second halves. Starting at $x_0=(p_0,v_0{)}^T$, direct integration givesThe endpoint map has determinant $T^3/8\ne 0$, so these two amplitudes can supply any desired endpoint displacement. For a rest-to-rest move of distance $d$, take $a=4d/T^2$, $b=-4d/T^2$. At $T=2$ and $d=1$ these are the two commands in the first figure. No impulse is needed; shorter deadlines require larger finite commands.

The reachable set ${\mathcal{R}}_T(x_0)$ collects all endpoints attainable from $x_0$ at exactly $T$ by admissible control inputs. If arrival any time up to $T$ is allowed, use ${\mathcal{R}}_{\le T}(x_0)={\bigcup }_{0\le t\le T}{\mathcal{R}}_t(x_0)$, with ${\mathcal{R}}_0(x_0)=\{x_0\}$. These definitions differ: a general dynamical system may drift away after early arrival, so waiting need not preserve the target. The reachable set is always relative to a declared input class and any constraints on the entire path.

For the double integrator starting from $(0,0)$, now require measurable functions as control inputs with $|u(t)|\le 1$ almost everywhere. Write $(p,v)$ for its endpoint at $T>0$. Two integrals determine the endpoint:Our mathematical example has the exact reachable setTo see the upper boundary, fix $v$: put $u=1$ first and $u=-1$ last, switching at $s=(T+v)/2$. This maximizes the weighted integral for position because early commands have the largest weight $T-t$; the required net velocity fixes $s$. Formally, $(T-t)-(T-s)=s-t$ has the same sign as this maximizing command, so changing to any other admissible command with the same integral cannot increase $p$. Reversing the order gives the lower boundary. Pointwise convex combinations of these two commands preserve $v$ and attain every intermediate $p$, so the formula describes the whole region, not merely a bound. The extreme commands are bang-bang control.

In particular, the bounded double integrator can move from rest to position $d$ and rest again exactly when $|d|\le T^2/4$. Its minimum duration is therefore $2\sqrt{|d|}$ in these normalized units. With freely chosen time every rest-to-rest distance is attainable; with a fixed deadline many are excluded. Changing the amplitude bound to $|u|\le a$ with $a>0$ scales this condition to $|d|\le a{T}^2/4$. This shows why specifying the controls matters even when the Kalman rank criterion gives full rank of a matrix.

In closed quantum control, a density operator reachable set lies inside its unitary orbit of a density operator, since coherent evolution preserves the spectrum. That orbit need not be fully reachable under the available control inputs.

Consider uniform fields $B_{-}\hat{\mathbf{y}}$ below and $B_{+}\hat{\mathbf{x}}$ above an interface, with local constant densities ${\rho }_{-},{\rho }_{+}$. For ideal magnetohydrodynamics and local incompressible potential flow, the interface displacement $h{e}^{st+ikx+imy}$ has displacement potentials ${\chi }_{-}=h{e}^{Kz}/K$ and ${\chi }_{+}=-h{e}^{-Kz}/K$, $K=\sqrt{k^2+m^2}$. Magnetic flux freezing gives ${\mathbf{b}}_i=({\mathbf{B}}_i\cdot \nabla )\nabla {\chi }_i$. The linear magnetohydrodynamic total pressure is $-[{\rho }_i{s}^2+({\mathbf{k}}_h\cdot {\mathbf{B}}_i{)}^2/{\mu }_0]{\chi }_i$. Matching Lagrangian total pressure gives the displayed dispersion relation. For ${\rho }_{+}>{\rho }_{-}$ the most unstable orientation has its wavevector along the weaker field.

// Target: continuum-mechanics.bigb

A fraction $a/b$ represents the quotient of its numerator $a$ by its nonzero denominator $b$. For integers $a,b$ this is a rational number. Different fractions can represent the same number: $252/198=14/11$. Dividing both entries by their greatest common divisor gives a reduced fraction, with the sign convention that the denominator is positive.